Search results for: interference mitigation

Authors: Wonil Nam, Xiang Ren, Inyoung Kim, Masoud Agah, Wei Zhou

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Despite its ultrasensitive detection capability, surface-enhanced Raman spectroscopy (SERS) faces challenges as a quantitative biochemical analysis tool due to the significant dependence of local field intensity in hotspots on nanoscale geometric variations of plasmonic nanostructures. Therefore, despite enormous progress in plasmonic nanoengineering of high-performance SERS devices, it is still challenging to quantitatively correlate the measured SERS signals with the actual molecule concentrations at hotspots. A significant effort has been devoted to developing SERS calibration methods by introducing internal standards. It has been achieved by placing Raman tags at plasmonic hotspots. Raman tags undergo similar SERS enhancement at the same hotspots, and ratiometric SERS signals for analytes of interest can be generated with reduced dependence on geometrical variations. However, using Raman tags still faces challenges for real-world applications, including spatial competition between the analyte and tags in hotspots, spectral interference, laser-induced degradation/desorption due to plasmon-enhanced photochemical/photothermal effects. We show that electronic Raman scattering (ERS) signals from metallic nanostructures at hotspots can serve as the internal calibration standard to enable quantitative SERS analysis and improve biostatistical analysis. We perform SERS with Au-SiO₂ multilayered metal-insulator-metal nano laminated plasmonic nanostructures. Since the ERS signal is proportional to the volume density of electron-hole occupation in hotspots, the ERS signals exponentially increase when the wavenumber is approaching the zero value. By a long-pass filter, generally used in backscattered SERS configurations, to chop the ERS background continuum, we can observe an ERS pseudo-peak, IERS. Both ERS and SERS processes experience the |E|⁴ local enhancements during the excitation and inelastic scattering transitions. We calibrated IMRS of 10 μM Rhodamine 6G in solution by IERS. The results show that ERS calibration generates a new analytical value, ISERS/IERS, insensitive to variations from different hotspots and thus can quantitatively reflect the molecular concentration information. Given the calibration capability of ERS signals, we performed label-free SERS analysis of living biological systems using four different breast normal and cancer cell lines cultured on nano-laminated SERS devices. 2D Raman mapping over 100 μm × 100 μm, containing several cells, was conducted. The SERS spectra were subsequently analyzed by multivariate analysis using partial least square discriminant analysis. Remarkably, after ERS calibration, MCF-10A and MCF-7 cells are further separated while the two triple-negative breast cancer cells (MDA-MB-231 and HCC-1806) are more overlapped, in good agreement with the well-known cancer categorization regarding the degree of malignancy. To assess the strength of ERS calibration, we further carried out a drug efficacy study using MDA-MB-231 and different concentrations of anti-cancer drug paclitaxel (PTX). After ERS calibration, we can more clearly segregate the control/low-dosage groups (0 and 1.5 nM), the middle-dosage group (5 nM), and the group treated with half-maximal inhibitory concentration (IC50, 15 nM). Therefore, we envision that ERS calibrated SERS can find crucial opportunities in label-free molecular profiling of complicated biological systems.

Keywords: cancer cell drug efficacy, plasmonics, surface-enhanced Raman spectroscopy (SERS), SERS calibration

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Authors: Dominique Arrouays, Songchao Chen, Anne C. Richer-De-Forges

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Soils are at the crossing of many issues such as food and water security, sustainable energy, climate change mitigation and adaptation, biodiversity protection, human health and well-being. They deliver many ecosystem services that are essential to life on Earth. Therefore, there is a growing demand for soil information on a national and global scale. Unfortunately, many countries do not have detailed soil maps, and, when existing, these maps are generally based on more or less complex and often non-harmonized soil classifications. An estimate of their uncertainty is also often missing. Thus, there are not easy to understand and often not properly used by end-users. Therefore, there is an urgent need to provide end-users with spatially exhaustive grids of essential soil properties, together with an estimate of their uncertainty. One way to achieve this is digital soil mapping (DSM). The concept of DSM relies on the hypothesis that soils and their properties are not randomly distributed, but that they depend on the main soil-forming factors that are climate, organisms, relief, parent material, time (age), and position in space. All these forming factors can be approximated using several exhaustive spatial products such as climatic grids, remote sensing products or vegetation maps, digital elevation models, geological or lithological maps, spatial coordinates of soil information, etc. Thus, DSM generally relies on models calibrated with existing observed soil data (point observations or maps) and so-called “ancillary co-variates” that come from other available spatial products. Then the model is generalized on grids where soil parameters are unknown in order to predict them, and the prediction performances are validated using various methods. With the growing demand for soil information at a national and global scale and the increase of available spatial co-variates national and continental DSM initiatives are continuously increasing. This short review illustrates the main national and continental advances in Europe, the diversity of the approaches and the databases that are used, the validation techniques and the main scientific and other issues. Examples from several countries illustrate the variety of products that were delivered during the last ten years. The scientific production on this topic is continuously increasing and new models and approaches are developed at an incredible speed. Most of the digital soil mapping (DSM) products rely mainly on machine learning (ML) prediction models and/or the use or pedotransfer functions (PTF) in which calibration data come from soil analyses performed in labs or for existing conventional maps. However, some scientific issues remain to be solved and also political and legal ones related, for instance, to data sharing and to different laws in different countries. Other issues related to communication to end-users and education, especially on the use of uncertainty. Overall, the progress is very important and the willingness of institutes and countries to join their efforts is increasing. Harmonization issues are still remaining, mainly due to differences in classifications or in laboratory standards between countries. However numerous initiatives are ongoing at the EU level and also at the global level. All these progress are scientifically stimulating and also promissing to provide tools to improve and monitor soil quality in countries, EU and at the global level.

Keywords: digital soil mapping, global soil mapping, national and European initiatives, global soil mapping products, mini-review

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Authors: Pedro A. V. Ramos, Duarte M. S. Albuquerque, José C. F. Pereira

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Global warming mitigation is one of the main challenges of this century, having the net balance of greenhouse gas (GHG) emissions to be null or negative in 2050. Industry electrification is one of the main paths to achieving carbon neutrality within the goals of the Paris Agreement. Microwave heating is becoming a popular industrial heating mechanism due to the absence of direct GHG emissions, but also the rapid, volumetric, and efficient heating. In the present study, a mathematical model is used to simulate the production using microwave heating of two ceramic pigments, at high temperatures (above 1200 Celsius degrees). The two pigments studied were the yellow (Pr, Zr)SiO₂ and the brown (Ti, Sb, Cr)O₂. The chemical conversion of reactants into products was included in the model by using the kinetic triplet obtained with the model-fitting method and experimental data present in the Literature. The coupling between the electromagnetic, thermal, and chemical interfaces was also included. The simulations were computed in COMSOL Multiphysics. The geometry includes a moving plunger to allow for the cavity impedance matching and thus maximize the electromagnetic efficiency. To accomplish this goal, a MATLAB controller was developed to automatically search the position of the moving plunger that guarantees the maximum efficiency. The power is automatically and permanently adjusted during the transient simulation to impose stationary regime and total conversion, the two requisites of every converged solution. Both 2D and 3D geometries were used and a parametric study regarding the axial bed velocity and the heat transfer coefficient at the boundaries was performed. Moreover, a Verification and Validation study was carried out by comparing the conversion profiles obtained numerically with the experimental data available in the Literature; the numerical uncertainty was also estimated to attest to the result's reliability. The results show that the model-fitting method employed in this work is a suitable tool to predict the chemical conversion of reactants into the pigment, showing excellent agreement between the numerical results and the experimental data. Moreover, it was demonstrated that higher velocities lead to higher thermal efficiencies and thus lower energy consumption during the process. This work concludes that the electromagnetic heating of materials having high loss tangent and low thermal conductivity, like ceramic materials, maybe a challenge due to the presence of hot spots, which may jeopardize the product quality or even the experimental apparatus. The MATLAB controller increased the electromagnetic efficiency by 25% and global efficiency of 54% was obtained for the titanate brown pigment. This work shows that electromagnetic heating will be a key technology in the decarbonization of the ceramic sector as reductions up to 98% in the specific GHG emissions were obtained when compared to the conventional process. Furthermore, numerical simulations appear as a suitable technique to be used in the design and optimization of microwave applicators, showing high agreement with experimental data.

Keywords: automatic impedance matching, ceramic pigments, efficiency maximization, high-temperature microwave heating, input power control, numerical simulation

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Authors: Mahsa Mousavi, Hamid Reza Pourshaghaghi, Mohammad Tahghighi, Henk Corporaal

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Recently, Statistic Random-Access Memory-based (SRAM-based) Field-Programmable Gate Arrays (FPGAs) are widely used in aeronautics and space systems where high dependability is demanded and considered as a mandatory requirement. Since design’s circuit is stored in configuration memory in SRAM-based FPGAs; they are very sensitive to Single Event Upsets (SEUs). In addition, the adverse effects of SEUs on the electronics used in space are much higher than in the Earth. Thus, developing fault tolerant techniques play crucial roles for the use of SRAM-based FPGAs in space. However, fault tolerance techniques introduce additional penalties in system parameters, e.g., area, power, performance and design time. In this paper, an accurate estimation of configuration memory vulnerability to SEUs is proposed for approximate-tolerant applications. This vulnerability estimation is highly required for compromising between the overhead introduced by fault tolerance techniques and system robustness. In this paper, we study applications in which the exact final output value is not necessarily always a concern meaning that some of the SEU-induced changes in output values are negligible. We therefore define and propose Approximate-based Configuration Memory Vulnerability Factor (ACMVF) estimation to avoid overestimating configuration memory vulnerability to SEUs. In this paper, we assess the vulnerability of configuration memory by injecting SEUs in configuration memory bits and comparing the output values of a given circuit in presence of SEUs with expected correct output. In spite of conventional vulnerability factor calculation methods, which accounts any deviations from the expected value as failures, in our proposed method a threshold margin is considered depending on user-case applications. Given the proposed threshold margin in our model, a failure occurs only when the difference between the erroneous output value and the expected output value is more than this margin. The ACMVF is subsequently calculated by acquiring the ratio of failures with respect to the total number of SEU injections. In our paper, a test-bench for emulating SEUs and calculating ACMVF is implemented on Zynq-7000 FPGA platform. This system makes use of the Single Event Mitigation (SEM) IP core to inject SEUs into configuration memory bits of the target design implemented in Zynq-7000 FPGA. Experimental results for 32-bit adder show that, when 1% to 10% deviation from correct output is considered, the counted failures number is reduced 41% to 59% compared with the failures number counted by conventional vulnerability factor calculation. It means that estimation accuracy of the configuration memory vulnerability to SEUs is improved up to 58% in the case that 10% deviation is acceptable in output results. Note that less than 10% deviation in addition result is reasonably tolerable for many applications in approximate computing domain such as Convolutional Neural Network (CNN).

Keywords: fault tolerance, FPGA, single event upset, approximate computing

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Authors: Hadush Kidane Meresa

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The hydrological extremes frequency analysis is the foundation for the hydraulic engineering design, flood protection, drought management and water resources management and planning to utilize the available water resource to meet the desired objectives of different organizations and sectors in a country. This spatial variation of the statistical characteristics of the extreme flood and drought events are key practice for regional flood and drought analysis and mitigation management. For different hydro-climate of the regions, where the data set is short, scarcity, poor quality and insufficient, the regionalization methods are applied to transfer at-site data to a region. This study aims in regional high and low flow frequency analysis for Poland River Basins. Due to high frequent occurring of hydrological extremes in the region and rapid water resources development in this basin have caused serious concerns over the flood and drought magnitude and frequencies of the river in Poland. The magnitude and frequency result of high and low flows in the basin is needed for flood and drought planning, management and protection at present and future. Hydrological homogeneous high and low flow regions are formed by the cluster analysis of site characteristics, using the hierarchical and C- mean clustering and PCA method. Statistical tests for regional homogeneity are utilized, by Discordancy and Heterogeneity measure tests. In compliance with results of the tests, the region river basin has been divided into ten homogeneous regions. In this study, frequency analysis of high and low flows using AM for high flow and 7-day minimum low flow series is conducted using six statistical distributions. The use of L-moment and LL-moment method showed a homogeneous region over entire province with Generalized logistic (GLOG), Generalized extreme value (GEV), Pearson type III (P-III), Generalized Pareto (GPAR), Weibull (WEI) and Power (PR) distributions as the regional drought and flood frequency distributions. The 95% percentile and Flow duration curves of 1, 7, 10, 30 days have been plotted for 10 stations. However, the cluster analysis performed two regions in west and east of the province where L-moment and LL-moment method demonstrated the homogeneity of the regions and GLOG and Pearson Type III (PIII) distributions as regional frequency distributions for each region, respectively. The spatial variation and regional frequency distribution of flood and drought characteristics for 10 best catchment from the whole region was selected and beside the main variable (streamflow: high and low) we used variables which are more related to physiographic and drainage characteristics for identify and delineate homogeneous pools and to derive best regression models for ungauged sites. Those are mean annual rainfall, seasonal flow, average slope, NDVI, aspect, flow length, flow direction, maximum soil moisture, elevation, and drainage order. The regional high-flow or low-flow relationship among one streamflow characteristics with (AM or 7-day mean annual low flows) some basin characteristics is developed using Generalized Linear Mixed Model (GLMM) and Generalized Least Square (GLS) regression model, providing a simple and effective method for estimation of flood and drought of desired return periods for ungauged catchments.

Keywords: flood , drought, frequency, magnitude, regionalization, stochastic, ungauged, Poland

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Authors: Ursula Das, Manavjit Singh Dhindsa, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

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Wildland fires, also known as forest fires or wildfires, are exhibiting an alarming surge in frequency in recent times, further adding to its perennial global concern. Forest fires often lead to devastating consequences ranging from loss of healthy forest foliage and wildlife to substantial economic losses and the tragic loss of human lives. Despite the existence of substantial literature on the detection of active forest fires, numerous potential research avenues in forest fire management, such as preventative measures and ancillary effects of forest fires, remain largely underexplored. This paper undertakes a systematic review of these underexplored areas in forest fire research, meticulously categorizing them into distinct phases, namely pre-fire, during-fire, and post-fire stages. The pre-fire phase encompasses the assessment of fire risk, analysis of fuel properties, and other activities aimed at preventing or reducing the risk of forest fires. The during-fire phase includes activities aimed at reducing the impact of active forest fires, such as the detection and localization of active fires, optimization of wildfire suppression methods, and prediction of the behavior of active fires. The post-fire phase involves analyzing the impact of forest fires on various aspects, such as the extent of damage in forest areas, post-fire regeneration of forests, impact on wildlife, economic losses, and health impacts from byproducts produced during burning. A comprehensive understanding of the three stages is imperative for effective forest fire management and mitigation of the impact of forest fires on both ecological systems and human well-being. Artificial intelligence and machine learning (AI/ML) methods have garnered much attention in the cyber-physical systems domain in recent times leading to their adoption in decision-making in diverse applications including disaster management. This paper explores the current state of AI/ML applications for managing the activities in the aforementioned phases of forest fire. While conventional machine learning and deep learning methods have been extensively explored for the prevention, detection, and management of forest fires, a systematic classification of these methods into distinct AI research domains is conspicuously absent. This paper gives a comprehensive overview of the state of forest fire research across more recent and prominent AI/ML disciplines, including big data, classical machine learning, computer vision, explainable AI, generative AI, natural language processing, optimization algorithms, and time series forecasting. By providing a detailed overview of the potential areas of research and identifying the diverse ways AI/ML can be employed in forest fire research, this paper aims to serve as a roadmap for future investigations in this domain.

Keywords: artificial intelligence, computer vision, deep learning, during-fire activities, forest fire management, machine learning, pre-fire activities, post-fire activities

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Authors: Kimberley Adamek

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According to the Council on Tall Buildings, there has been a rapid increase in the construction of tall or “megatall” buildings over the past two decades. Simultaneously, the New England Journal of Medicine has reported that there has been a steady increase in climate related natural disasters since the 1970s; the eastern expansion of the USA's infamous Tornado Alley being just one of many current issues. In the future, this could mean that tall buildings, which already guide high speed winds down to pedestrian levels would have to withstand stronger forces and protect pedestrians in more extreme ways. Although many projects are required to be verified within wind tunnels and a handful of cities such as San Francisco have included wind testing within building code standards, there are still many examples where wind is only considered for basic loading. This typically results in and an increase of structural expense and unwanted mitigation strategies that are proposed late within a project. When building cities, architects rarely consider how each building alters the invisible patterns of wind and how these alterations effect other areas in different ways later on. It is not until these forces move, overpower and even destroy cities that people take notice. For example, towers have caused winds to blow objects into people (Walkie-Talkie Tower, Leeds, England), cause building parts to vibrate and produce loud humming noises (Beetham Tower, Manchester), caused wind tunnels in streets as well as many other issues. Alternatively, there exist towers which have used their form to naturally draw in air and ventilate entire facilities in order to eliminate the needs for costly HVAC systems (The Met, Thailand) and used their form to increase wind speeds to generate electricity (Bahrain Tower, Dubai). Wind and weather exist and effect all parts of the world in ways such as: Science, health, war, infrastructure, catastrophes, tourism, shopping, media and materials. Working in partnership with a leading wind engineering company RWDI, a series of tests, images and animations documenting discovered interactions of different building forms with wind will be collected to emphasize the possibilities for wind use to architects. A site within San Francisco (due to its increasing tower development, consistently wind conditions and existing strict wind comfort criteria) will host a final design. Iterations of this design will be tested within the wind tunnel and computational fluid dynamic systems which will expose, utilize and manipulate wind flows to create new forms, technologies and experiences. Ultimately, this thesis aims to question the amount which the environment is allowed to permeate building enclosures, uncover new programmatic possibilities for wind in buildings, and push the boundaries of working with the wind to ensure the development and safety of future cities. This investigation will improve and expand upon the traditional understanding of wind in order to give architects, wind engineers as well as the general public the ability to broaden their scope in order to productively utilize this living phenomenon that everyone constantly feels but cannot see.

Keywords: wind engineering, climate, visualization, architectural aerodynamics

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Authors: Simrat Kaur, Fatema Diwan, Brad Reddersen

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The unsustainable and injudicious use of natural renewable resources beyond the self-replenishment limits of our planet has proved catastrophic. Most of the Earth’s resources, including land, water, minerals, and biodiversity, have been overexploited. Owing to this, there is a steep rise in the global events of natural calamities of contrasting nature, such as torrential rains, storms, heat waves, rising sea levels, and megadroughts. These are all interconnected through common elements, namely oceanic currents and land’s the green cover. The deforestation fueled by the ‘economic elites’ or the global players have already cleared massive forests and ecological biomes in every region of the globe, including the Amazon. These were the natural carbon sinks prevailing and performing CO2 sequestration for millions of years. The forest biomes have been turned into mono cultivation farms to produce feedstock crops such as soybean, maize, and sugarcane; which are one of the biggest green house gas emitters. Such unsustainable agriculture practices only provide feedstock for livestock and food processing industries with huge carbon and water footprints. These are two main factors that have ‘cause and effect’ relationships in the context of climate change. In contrast to organic and sustainable farming, the mono-cultivation practices to produce food, fuel, and feedstock using chemicals devoid of the soil of its fertility, abstract surface, and ground waters beyond the limits of replenishment, emit green house gases, and destroy biodiversity. There are numerous cases across the planet where due to overuse; the levels of surface water reservoir such as the Lake Mead in Southwestern USA and ground water such as in Punjab, India, have deeply shrunk. Unlike the rain fed food production system on which the poor communities of the world relies; the blue water (surface and ground water) dependent mono-cropping for industrial and processed food create water deficit which put the burden on the domestic users. Excessive abstraction of both surface and ground waters for high water demanding feedstock (soybean, maize, sugarcane), cereal crops (wheat, rice), and cash crops (cotton) have a dual and synergistic impact on the global green house gas emissions and prevalence of megadroughts. Both these factors have elevated global temperatures, which caused cascading events such as soil water deficits, flash fires, and unprecedented burning of the woods, creating megafires in multiple continents, namely USA, South America, Europe, and Australia. Therefore, it is imperative to reduce the green and blue water footprints of agriculture and industrial sectors through recycling of black and gray waters. This paper explores various opportunities for successful implementation of wastewater management for drought preparedness in high risk communities.

Keywords: wastewater, drought, biodiversity, water footprint, nutrient recovery, algae

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Authors: Annika J. Meyer, Tom Piechotta

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Unmanned Aerial Vehicles (UAVs) have increasingly become vital tools in various applications, including surveillance, search and rescue, and environmental monitoring. One common approach to ensure redundant communication systems when flying beyond visual line of sight is for UAVs to employ multiple mobile data modems by different providers. Although widely adopted, this approach suffers from several drawbacks, such as high costs, added weight and potential increases in signal interference. In light of these challenges, this paper proposes a communication framework intermeshing mobile networks and LoRa (Long Range) technology—a low-power, long-range communication protocol. LoRaWAN (Long Range Wide Area Network) is commonly used in Internet of Things applications, relying on stationary gateways and Internet connectivity. This paper, however, utilizes the underlying LoRa protocol, taking advantage of the protocol’s low power and long-range capabilities while ensuring efficiency and reliability. Conducted in collaboration with the Potsdam Fire Department, the implementation of mobile network technology in combination with the LoRa protocol in small UAVs (take-off weight < 0.4 kg), specifically designed for search and rescue and area monitoring missions, is explored. This research aims to test the viability of LoRa as an additional redundant communication system during UAV flights as well as its intermeshing with the primary, mobile network-based controller. The methodology focuses on direct UAV-to-UAV and UAV-to-ground communications, employing different spreading factors optimized for specific operational scenarios—short-range for UAV-to-UAV interactions and long-range for UAV-to-ground commands. This explored use case also dramatically reduces one of the major drawbacks of LoRa communication systems, as a line of sight between the modules is necessary for reliable data transfer. Something that UAVs are uniquely suited to provide, especially when deployed as a swarm. Additionally, swarm deployment may enable UAVs that have lost contact with their primary network to reestablish their connection through another, better-situated UAV. The experimental setup involves multiple phases of testing, starting with controlled environments to assess basic communication capabilities and gradually advancing to complex scenarios involving multiple UAVs. Such a staged approach allows for meticulous adjustment of parameters and optimization of the communication protocols to ensure reliability and effectiveness. Furthermore, due to the close partnership with the Fire Department, the real-world applicability of the communication system is assured. The expected outcomes of this paper include a detailed analysis of LoRa's performance as a communication tool for UAVs, focusing on aspects such as signal integrity, range, and reliability under different environmental conditions. Additionally, the paper seeks to demonstrate the cost-effectiveness and operational efficiency of using a single type of communication technology that reduces UAV payload and power consumption. By shifting from traditional cellular network communications to a more robust and versatile cellular and LoRa-based system, this research has the potential to significantly enhance UAV capabilities, especially in critical applications where reliability is paramount. The success of this paper could pave the way for broader adoption of LoRa in UAV communications, setting a new standard for UAV operational communication frameworks.

Keywords: LoRa communication protocol, mobile network communication, UAV communication systems, search and rescue operations

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Authors: Kimberly Samaha

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The Bio-Hub Ecosystem model was developed to address a critical area of concern within the global energy market regarding biomass as a feedstock for power plants. Yet the lack of an economically-viable business model for bioenergy facilities has resulted in the continuation of idled and decommissioned plants. This study analyzed data and submittals to the Born Global Maine Innovation Challenge. The Innovation Challenge was a global innovation challenge to identify process innovations that could address a ‘whole-tree’ approach of maximizing the products, byproducts, energy value and process slip-streams into a circular zero-waste design. Participating companies were at various stages of developing bioproducts and included biofuels, lignin-based products, carbon capture platforms and biochar used as both a filtration medium and as a soil amendment product. This case study shows the QCA (Qualitative Comparative Analysis) methodology of the prequalification process and the resulting techno-economic model that was developed for the maximizing profitability of the Bio-Hub Ecosystem through continuous expansion of system waste streams into valuable process inputs for co-hosts. A full site plan for the integration of co-hosts (biorefinery, land-based shrimp and salmon aquaculture farms, a tomato green-house and a hops farm) at an operating forestry-based biomass to energy plant in West Enfield, Maine USA. This model and process for evaluating the profitability not only proposes models for integration of forestry, aquaculture and agriculture in cradle-to-cradle linkages of what have typically been linear systems, but the proposal also allows for the early measurement of the circularity and impact of resource use and investment risk mitigation, for these systems. In this particular study, profitability is assessed at two levels CAPEX (Capital Expenditures) and in OPEX (Operating Expenditures). Given that these projects start with repurposing facilities where the industrial level infrastructure is already built, permitted and interconnected to the grid, the addition of co-hosts first realizes a dramatic reduction in permitting, development times and costs. In addition, using the biomass energy plant’s waste streams such as heat, hot water, CO₂ and fly ash as valuable inputs to their operations and a significant decrease in the OPEX costs, increasing overall profitability to each of the co-hosts bottom line. This case study utilizes a proprietary techno-economic model to demonstrate how utilizing waste streams of a biomass energy plant and/or biorefinery, results in significant reduction in OPEX for both the biomass plants and the agriculture and aquaculture co-hosts. Economically viable Bio-Hubs with favorable environmental and community impacts may prove critical in garnering local and federal government support for pilot programs and more wide-scale adoption, especially for those living in severely economically depressed rural areas where aging industrial sites have been shuttered and local economies devastated.

Keywords: bio-economy, biomass energy, financing, zero-waste

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Authors: Manju Bala Jassi

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The Covid 19 pandemic has badly mauled Dubai’s GDP heavily dependent on hospitality, tourism, entertainment, logistics, property and the retail sectors. In the context of the World Health protocols on social distancing for better maintenance of health and hygiene, the revival of the battered tourism and hospitality sectors has serious lessons for designers- interiors and public places. The tangible and intangible aesthetic elements and design –ambiance, materials, furnishings, colors, lighting and interior with architectural design issues of tourism and hospitality need a rethink to ensure a memorable tourist experience. Designers ought to experiment with sustainable places of tourism and design, develop, build and projects are aesthetic and leave as little negative impacts on the environment and public as possible. In short, they ought to conceive public spaces that makes use of little untouched materials and energy, and creates pollution and waste that are minimal. The spaces can employ healthier and more resource-efficient prototypes of construction, renovation, operation, maintenance, and demolition and thereby mitigate the environment impacts of the construction activities and it is sustainable These measures encompass the hospitality sector that includes hotels and restaurants which has taken the hardest fall from the pandemic. The paper sought to examine building energy efficiency and materials and design employed in public places, green buildings to achieve constructive sustainability and to establish the benefits of utilizing energy efficiency, green materials and sustainable design; to document diverse policy interventions, design and Spatial dimensions of tourism and hospitality sectors; to examine changes in the hospitality, aviation sector especially from a design perspective regarding infrastructure or operational constraints and additional risk-mitigation measures; to dilate on the nature of implications for interior designers and architects to design public places to facilitate sustainable tourism and hospitality while balancing convenient space and their operations' natural surroundings. The qualitative research approach was adopted for the study. The researcher collected and analyzed data in continuous iteration. Secondary data was collected from articles in journals, trade publications, government reports, newspaper/ magazine articles, policy documents etc. In depth interviews were conducted with diverse stakeholders. Preliminary data indicates that designers have started imagining public places of tourism and hospitality against the backdrop of the government push and WHO guidelines. For instance, with regard to health, safety, hygiene and sanitation, Emirates, the Dubai-based airline has augmented health measures at the Dubai International Airport and on board its aircraft. It has leveraged high tech/ Nano-tech, social distancing to encourage least human contact, flexible design layouts to limit the occupancy. The researcher organized the data into thematic categories and found that the Government of Dubai has initiated comprehensive measures in the hospitality, tourism and aviation sectors in compliance with the WHO guidelines.

Keywords: Covid 19, design, Dubai, hospitality, public spaces, tourism

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Authors: Swadha Singh

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International Solar Alliance is the foremost treaty-based global organization concerned with tapping the potential of sun-abundant nations between the Tropics of Cancer and Capricorn and enables co-operation among them. As a founding member of the International Solar Alliance, India exhibits its positioning as an upcoming leader in clean energy. India has set ambitious goals and targets to expand the share of solar in its energy mix and is playing a proactive role both at the regional and global levels. ISA aims to serve multiple goals- bring about scale commercialization of solar power, boost domestic manufacturing, and leverage solar diplomacy in African countries, amongst others. Against this backdrop, this paper attempts to examine the ways in which ISA as an intergovernmental organization under Indian leadership can leverage the cause of clean energy (solar) diplomacy and effectively shape partnerships and collaborations with other developing countries in terms of sharing solar technology, capacity building, risk mitigation, mobilizing financial investment and providing an aggregate market. A more specific focus of ISA is on the developing countries, which in the absence of a collective, are constrained by technology and capital scarcity, despite being naturally endowed with solar resources. Solar rich but finance-constrained economies face political risk, foreign exchange risk, and off-taker risk. Scholars argue that aligning India’s climate change discourse and growth prospects in its engagements, collaborations, and partnerships at the bilateral, multilateral and regional level can help promote trade, attract investments, and promote resilient energy transition both in India and in partner countries. For developing countries, coming together in an action-oriented way on issues of climate and clean energy is particularly important since it is developing and underdeveloped countries that face multiple and coalescing challenges such as the adverse impact of climate change, uneven and low access to reliable energy, and pressing employment needs. Investing in green recovery is agreed to be an assured way to create resilient value chains, create sustainable livelihoods, and help mitigate climate threats. If India is able to ‘green its growth’ process, it holds the potential to emerge as a climate leader internationally. It can use its experience in the renewable sector to guide other developing countries in balancing multiple similar objectives of development, energy security, and sustainability. The challenges underlying solar expansion in India have lessons to offer other developing countries, giving India an opportunity to assume a leadership role in solar diplomacy and expand its geopolitical influence through inter-governmental organizations such as ISA. It is noted that India has limited capacity to directly provide financial funds and support and is not a leading manufacturer of cheap solar equipment, as does China; however, India can nonetheless leverage its large domestic market to scale up the commercialization of solar power and offer insights and learnings to similarly placed abundant solar countries. The paper examines the potential of and limits placed on India’s solar diplomacy.

Keywords: climate diplomacy, energy security, solar diplomacy, renewable energy

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Authors: Kimberly Samaha

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In order to attract new types of investors into the emerging Bio-Economy, a new set of metrics and measurement system is needed to better quantify the environmental, social and economic impacts of circular zero-waste design. The Bio-Hub Ecosystem model was developed to address a critical area of concern within the global energy market regarding the use of biomass as a feedstock for power plants. Lack of an economically-viable business model for bioenergy facilities has resulted in the continuation of idled and decommissioned plants. In particular, the forestry-based plants which have been an invaluable outlet for woody biomass surplus, forest health improvement, timber production enhancement, and especially reduction of wildfire risk. This study looked at repurposing existing biomass-energy plants into Circular Zero-Waste Bio-Hub Ecosystems. A Bio-Hub model that first targets a ‘whole-tree’ approach and then looks at the circular economics of co-hosting diverse industries (wood processing, aquaculture, agriculture) in the vicinity of the Biomass Power Plants facilities. It proposes not only models for integration of forestry, aquaculture, and agriculture in cradle-to-cradle linkages of what have typically been linear systems, but the proposal also allows for the early measurement of the circularity and impact of resource use and investment risk mitigation, for these systems. Typically, life cycle analyses measure environmental impacts of different industrial production stages and are not integrated with indicators of material use circularity. This concept paper proposes the further development of a new set of metrics that would illustrate not only the typical life-cycle analysis (LCA), which shows the reduction in greenhouse gas (GHG) emissions, but also the zero-waste circularity measures of mass balance of the full value chain of the raw material and energy content/caloric value. These new measures quantify key impacts in making hyper-efficient use of natural resources and eliminating waste to landfills. The project utilized traditional LCA using the GREET model where the standalone biomass energy plant case was contrasted with the integration of a jet-fuel biorefinery. The methodology was then expanded to include combinations of co-hosts that optimize the life cycle of woody biomass from tree to energy, CO₂, heat and wood ash both from an energy/caloric value and for mass balance to include reuse of waste streams which are typically landfilled. The major findings of both a formal LCA study resulted in the masterplan for the first Bio-Hub to be built in West Enfield, Maine. Bioenergy facilities are currently at a critical juncture where they have an opportunity to be repurposed into efficient, profitable and socially responsible investments, or be idled and scrapped. If proven as a model, the expedited roll-out of these innovative scenarios can set a new standard for circular zero-waste projects that advance the critical transition from the current ‘take-make-dispose’ paradigm inherent in the energy, forestry and food industries to a more sustainable bio-economy paradigm where waste streams become valuable inputs, supporting local and rural communities in simple, sustainable ways.

Keywords: bio-economy, biomass energy, financing, metrics

Procedia PDF Downloads 156

Authors: Shuai Yuan, Minxia Shi, Xu Zhang, Jianzhi Yang, Kangqi Tian, Yuzheng Ma

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The precise measurement of muscle activities is essential for understanding the function of various body movements. This work aims to develop a muscle magnetic field signal detection system based on mathematical analysis. Medical research has underscored that early detection of muscle atrophy, coupled with lifestyle adjustments such as dietary control and increased exercise, can significantly enhance muscle-related diseases. Currently, surface electromyography (sEMG) is widely employed in research as an early predictor of muscle atrophy. Nonetheless, the primary limitation of using sEMG to forecast muscle strength is its inability to directly measure the signals generated by muscles. Challenges arise from potential skin-electrode contact issues due to perspiration, leading to inaccurate signals or even signal loss. Additionally, resistance and phase are significantly impacted by adipose layers. The recent emergence of optically pumped magnetometers introduces a fresh avenue for bio-magnetic field measurement techniques. These magnetometers possess high sensitivity and obviate the need for a cryogenic environment unlike superconducting quantum interference devices (SQUIDs). They detect muscle magnetic field signals in the range of tens to thousands of femtoteslas (fT). The utilization of magnetometers for capturing muscle magnetic field signals remains unaffected by issues of perspiration and adipose layers. Since their introduction, optically pumped atomic magnetometers have found extensive application in exploring the magnetic fields of organs such as cardiac and brain magnetism. The optimal operation of these magnetometers necessitates an environment with an ultra-weak magnetic field. To achieve such an environment, researchers usually utilize a combination of active magnetic compensation technology with passive magnetic shielding technology. Passive magnetic shielding technology uses a magnetic shielding device built with high permeability materials to attenuate the external magnetic field to a few nT. Compared with more layers, the coils that can generate a reverse magnetic field to precisely compensate for the residual magnetic fields are cheaper and more flexible. To attain even lower magnetic fields, compensation coils designed by Biot-Savart law are involved to generate a counteractive magnetic field to eliminate residual magnetic fields. By solving the magnetic field expression of discrete points in the target region, the parameters that determine the current density distribution on the plane can be obtained through the conventional target field method. The current density is obtained from the partial derivative of the stream function, which can be represented by the combination of trigonometric functions. Optimization algorithms in mathematics are introduced into coil design to obtain the optimal current density distribution. A one-dimensional linear regression analysis was performed on the collected data, obtaining a coefficient of determination R2 of 0.9349 with a p-value of 0. This statistical result indicates a stable relationship between the peak-to-peak value (PPV) of the muscle magnetic field signal and the magnitude of grip strength. This system is expected to be a widely used tool for healthcare professionals to gain deeper insights into the muscle health of their patients.

Keywords: muscle magnetic signal, magnetic shielding, compensation coils, trigonometric functions.

Procedia PDF Downloads 56

Authors: Alberto Azevedo, Ricardo Martins, André B. Fortunato, Anabela Oliveira

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Water is under severe threat today because of the rising population, increased agricultural and industrial needs, and the intensifying effects of climate change. Due to sea-level rise, erosion, and demographic pressure, the coastal regions are of significant concern to the scientific community. The Water Monitoring Sentinel Cloud platform (WORSICA) service is focused on providing new tools for monitoring water in coastal and inland areas, taking advantage of remote sensing, in situ and tidal modeling data. WORSICA is a service that can be used to determine the coastline, coastal inundation areas, and the limits of inland water bodies using remote sensing (satellite and Unmanned Aerial Vehicles - UAVs) and in situ data (from field surveys). It applies to various purposes, from determining flooded areas (from rainfall, storms, hurricanes, or tsunamis) to detecting large water leaks in major water distribution networks. This service was built on components developed in national and European projects, integrated to provide a one-stop-shop service for remote sensing information, integrating data from the Copernicus satellite and drone/unmanned aerial vehicles, validated by existing online in-situ data. Since WORSICA is operational using the European Open Science Cloud (EOSC) computational infrastructures, the service can be accessed via a web browser and is freely available to all European public research groups without additional costs. In addition, the private sector will be able to use the service, but some usage costs may be applied, depending on the type of computational resources needed by each application/user. Although the service has three main sub-services i) coastline detection; ii) inland water detection; iii) water leak detection in irrigation networks, in the present study, an application of the service to Óbidos lagoon in Portugal is shown, where the user can monitor the evolution of the lagoon inlet and estimate the topography of the intertidal areas without any additional costs. The service has several distinct methodologies implemented based on the computations of the water indexes (e.g., NDWI, MNDWI, AWEI, and AWEIsh) retrieved from the satellite image processing. In conjunction with the tidal data obtained from the FES model, the system can estimate a coastline with the corresponding level or even topography of the inter-tidal areas based on the Flood2Topo methodology. The outcomes of the WORSICA service can be helpful for several intervention areas such as i) emergency by providing fast access to inundated areas to support emergency rescue operations; ii) support of management decisions on hydraulic infrastructures operation to minimize damage downstream; iii) climate change mitigation by minimizing water losses and reduce water mains operation costs; iv) early detection of water leakages in difficult-to-access water irrigation networks, promoting their fast repair.

Keywords: remote sensing, coastline detection, water detection, satellite data, sentinel, Copernicus, EOSC

Procedia PDF Downloads 126

Authors: Erica Cochran Hameen, Bobuchi Ken-Opurum, Mounica Guturu

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The United Stated (U.S.) populous spends the majority of their time indoors in spaces where building codes and voluntary sustainability standards provide clear Indoor Environmental Quality (IEQ) metrics. The existing sustainable building standards and codes are aimed towards improving IEQ, health of occupants, and reducing the negative impacts of buildings on the environment. While they address the post-occupancy stage of buildings, there are fewer standards on the pre-occupancy stage thereby placing a large labor population in environments much less regulated. Construction personnel are often exposed to a variety of uncomfortable and unhealthy elements while on construction sites, primarily thermal, visual, acoustic, and air quality related. Construction site power generators, equipment, and machinery generate on average 9 decibels (dBA) above the U.S. OSHA regulations, creating uncomfortable noise levels. Research has shown that frequent exposure to high noise levels leads to chronic physiological issues and increases noise induced stress, yet beyond OSHA no other metric focuses directly on the impacts of noise on contractors’ well-being. Research has also associated natural light with higher productivity and attention span, and lower cases of fatigue in construction workers. However, daylight is not always available as construction workers often perform tasks in cramped spaces, dark areas, or at nighttime. In these instances, the use of artificial light is necessary, yet lighting standards for use during lengthy tasks and arduous activities is not specified. Additionally, ambient air, contaminants, and material off-gassing expelled at construction sites are one of the causes of serious health effects in construction workers. Coupled with extreme hot and cold temperatures for different climate zones, health and productivity can be seriously compromised. This research evaluates the impact of existing green building metrics on construction and risk management, by analyzing two codes and nine standards including LEED, WELL, and BREAM. These metrics were chosen based on the relevance to the U.S. construction industry. This research determined that less than 20% of the sustainability context within the standards and codes (texts) are related to the pre-occupancy building sector. The research also investigated the impact of construction personnel’s health and well-being on construction management through two surveys of project managers and on-site contractors’ perception of their work environment on productivity. To fully understand the risks of limited Environmental and Health Quality metrics for contractors (EHQ) this research evaluated the connection between EHQ factors such as inefficient lighting, on construction workers and investigated the correlation between various site coping strategies for comfort and productivity. Outcomes from this research are three-pronged. The first includes fostering a discussion about the existing conditions of EQH elements, i.e. thermal, lighting, ergonomic, acoustic, and air quality on the construction labor force. The second identifies gaps in sustainability standards and codes during the pre-occupancy stage of building construction from ground-breaking to substantial completion. The third identifies opportunities for improvements and mitigation strategies to improve EQH such as increased monitoring of effects on productivity and health of contractors and increased inclusion of the pre-occupancy stage in green building standards.

Keywords: construction contractors, health and well-being, environmental quality, risk management

Procedia PDF Downloads 132

Authors: Yu-Hsin Tsai

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A new, mandated county regional plan system has been initiated since 2010 nationwide in Taiwan, with its role situated in-between the policy-led cross-county regional plan and the blueprint-led city plan. This new regional plan contain both urban and rural areas in one single plan, which provides a more complete planning territory, i.e., city region within the county’s jurisdiction, and to be executed and managed effectively by the county government. However, the full picture of its functions and characteristics seems still not totally clear, compared with other levels of plans; either are planning goals and issues that can be most appropriately dealt with at this spatial scale. In addition, the extent to which the inclusion of sustainability ideal and measures to cope with climate change are unclear. Based on the above issues, this study aims to clarify the roles of county regional plan, to analyze the extent to which the measures cope with sustainability, climate change, and forecasted declining population, and the success factors and issues faced in the planning process. The methodology applied includes literature review, plan quality evaluation, and interview with officials of the central and local governments and urban planners involved for all the 23 counties in Taiwan. The preliminary research results show, first, growth management related policies have been widely implemented and expected to have effective impact, including incorporating resources capacity to determine maximum population for the city region as a whole, developing overall vision of urban growth boundary for all the whole city region, prioritizing infill development, and use of architectural land within urbanized area over rural area to cope with urban growth. Secondly, planning-oriented zoning is adopted in urban areas, while demand-oriented planning permission is applied in the rural areas with designated plans. Then, public participation has been evolved to the next level to oversee all of government’s planning and review processes due to the decreasing trust in the government, and development of public forum on the internet etc. Next, fertile agricultural land is preserved to maintain food self-supplied goal for national security concern. More adoption-based methods than mitigation-based methods have been applied to cope with global climate change. Finally, better land use and transportation planning in terms of avoiding developing rail transit stations and corridor in rural area is promoted. Even though many promising, prompt measures have been adopted, however, challenges exist to surround: first, overall urban density, likely affecting success of UGB, or use of rural agricultural land, has not been incorporated, possibly due to implementation difficulties. Second, land-use related measures to mitigating climate change seem less clear and hence less employed. Smart decline has not drawn enough attention to cope with predicted population decrease in the next decade. Then, some reluctance from county’s government to implement county regional plan can be observed vaguely possibly since limits have be set on further development on agricultural land and sensitive areas. Finally, resolving issue on existing illegal factories on agricultural land remains the most challenging dilemma.

Keywords: city region plan, sustainability, global climate change, growth management

Procedia PDF Downloads 349

Authors: Antonella Falanga, Armando Cartenì

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"Big data" refers to extremely vast and complex sets of data, encompassing extraordinarily large and intricate datasets that require specific tools for meaningful analysis and processing. These datasets can stem from diverse origins like sensors, mobile devices, online transactions, social media platforms, and more. The utilization of big data is pivotal, offering the chance to leverage vast information for substantial advantages across diverse fields, thereby enhancing comprehension, decision-making, efficiency, and fostering innovation in various domains. Big data, distinguished by its remarkable attributes of enormous volume, high velocity, diverse variety, and significant value, represent a transformative force reshaping the industry worldwide. Their pervasive impact continues to unlock new possibilities, driving innovation and advancements in technology, decision-making processes, and societal progress in an increasingly data-centric world. The use of these technologies is becoming more widespread, facilitating and accelerating operations that were once much more complicated. In particular, big data impacts across multiple sectors such as business and commerce, healthcare and science, finance, education, geography, agriculture, media and entertainment and also mobility and logistics. Within the transportation sector, which is the focus of this study, big data applications encompass a wide variety, spanning across optimization in vehicle routing, real-time traffic management and monitoring, logistics efficiency, reduction of travel times and congestion, enhancement of the overall transportation systems, but also mitigation of pollutant emissions contributing to environmental sustainability. Meanwhile, in public administration and the development of smart cities, big data aids in improving public services, urban planning, and decision-making processes, leading to more efficient and sustainable urban environments. Access to vast data reservoirs enables deeper insights, revealing hidden patterns and facilitating more precise and timely decision-making. Additionally, advancements in cloud computing and artificial intelligence (AI) have further amplified the potential of big data, enabling more sophisticated and comprehensive analyses. Certainly, utilizing big data presents various advantages but also entails several challenges regarding data privacy and security, ensuring data quality, managing and storing large volumes of data effectively, integrating data from diverse sources, the need for specialized skills to interpret analysis results, ethical considerations in data use, and evaluating costs against benefits. Addressing these difficulties requires well-structured strategies and policies to balance the benefits of big data with privacy, security, and efficient data management concerns. Building upon these premises, the current research investigates the efficacy and influence of big data by conducting an overview of the primary and recent implementations of big data in transportation systems. Overall, this research allows us to conclude that big data better provide to enhance rational decision-making for mobility choices and is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, public transport, sustainable mobility, transport demand, transportation planning

Procedia PDF Downloads 60

Authors: Sarah Fitzpatrick, Hossein Zare-Behtash, Konstantinos Kontis

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Traditionally, the focus of horizontal axis wind turbine (HAWT) blade aerodynamic optimisation studies has been the outer working region of the blade. However, recent works seek to better understand, and thus improve upon, the performance of the inboard blade region to enhance power production, maximise load reduction and better control the wake behaviour. This paper presents the design considerations and characterisation of a wind turbine wind tunnel model devised to further the understanding and fundamental definition of horizontal axis wind turbine root vortex shedding and interactions. Additionally, the application of passive and active flow control mechanisms – vortex generators and plasma actuators – to allow for the manipulation and mitigation of unsteady aerodynamic behaviour at the blade inboard section is investigated. A static, modular blade wind turbine model has been developed for use in the University of Glasgow’s de Havilland closed return, low-speed wind tunnel. The model components - which comprise of a half span blade, hub, nacelle and tower - are scaled using the equivalent full span radius, R, for appropriate Mach and Strouhal numbers, and to achieve a Reynolds number in the range of 1.7x105 to 5.1x105 for operational speeds up to 55m/s. The half blade is constructed to be modular and fully dielectric, allowing for the integration of flow control mechanisms with a focus on plasma actuators. Investigations of root vortex shedding and the subsequent wake characteristics using qualitative – smoke visualisation, tufts and china clay flow – and quantitative methods – including particle image velocimetry (PIV), hot wire anemometry (HWA), and laser Doppler anemometry (LDA) – were conducted over a range of blade pitch angles 0 to 15 degrees, and Reynolds numbers. This allowed for the identification of shed vortical structures from the maximum chord position, the transitional region where the blade aerofoil blends into a cylindrical joint, and the blade nacelle connection. Analysis of the trailing vorticity interactions between the wake core and freestream shows the vortex meander and diffusion is notably affected by the Reynold’s number. It is hypothesized that the shed vorticity from the blade root region directly influences and exacerbates the nacelle wake expansion in the downstream direction. As the design of inboard blade region form is, by necessity, driven by function rather than aerodynamic optimisation, a study is undertaken for the application of flow control mechanisms to manipulate the observed vortex phenomenon. The designed model allows for the effective investigation of shed vorticity and wake interactions with a focus on the accurate geometry of a root region which is representative of small to medium power commercial HAWTs. The studies undertaken allow for an enhanced understanding of the interplay of shed vortices and their subsequent effect in the near and far wake. This highlights areas of interest within the inboard blade area for the potential use of passive and active flow control devices which contrive to produce a more desirable wake quality in this region.

Keywords: vortex shedding, wake interactions, wind tunnel model, wind turbine

Procedia PDF Downloads 235

Authors: Ananya Barui, Provas Banerjee, Jyotirmoy Chatterjee

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Application of optical technology in medicine and biology has a long track-record. In this endeavor, OCT is able to attract both engineers and biologists to work together in the field of photonics for establishing a striking non-invasive imaging technology. In contrast to other in vivo imaging modalities like Raman imaging, confocal imaging, two-photon microscopy etc. which can perform in vivo imaging upto 100-200 micron depth due to limitation in numerical aperture or scattering, however, OCT can achieve high-resolution imaging upto few millimeters of tissue structures depending on their refractive index in different anatomical location. This tomographic system depends on interference of two light waves in an interferometer to produce a depth profile of specimen. In wound healing, frequent collection of biopsies for follow-up of repair process could be avoided by such imaging technique. Real time skin OCT (the optical biopsy) has efficacy in deeper and faster illumination of cutaneou tissue to acquire high resolution cross sectional images of their internal micro-structure. Swept Source-OCT (SS-OCT), a novel imaging technique, can generate high-speed depth profile (~ 2 mm) of wound at a sweeping rate of laser with micron level resolution and optimum coherent length of 5-6 mm. Normally multi-layered skin tissue depicts different optical properties along with variation in thickness, refractive index and composition (i.e. keratine layer, water, fat etc.) according to their anatomical location. For instance, stratum corneum, the upper-most and relatively dehydrated layer of epidermis reflects more light and produces more lucid and a sharp demarcation line with rest of the hydrated epidermal region. During wound healing or regeneration, optical properties of cutaneous tissue continuously altered with maturation of wound bed. More mature and less hydrated tissue component reflects more light and becomes visible as a brighter area in comparison to immature region which content higher amount water or fat that depicts as a darker area in OCT image. Non-healing wound possess prolonged inflammation and inhibits nascent proliferative stage. Accumulation of necrotic tissues also prevents the repair of non-healing wounds. Due to high resolution and potentiality to reflect the compositional aspects of tissues in terms of their optical properties, this tomographic method may facilitate in differentiating non-healing and acute wounds in addition to clinical observations. Non-invasive OCT offers better insight regarding specific biological status of tissue in health and pathological conditions, OCT images could be associated with histo-pathological ‘gold standard’. This correlated SS-OCT and microscopic evaluation of the wound edges can provide information regarding progressive healing and maturation of the epithelial components. In the context of searching analogy between two different imaging modalities, their relative performances in imaging of healing bed were estimated for probing an alternative approach. Present study validated utility of SS-OCT in revealing micro-anatomic structure in the healing bed with newer information. Exploring precise correspondence of OCT images features with histo-chemical findings related to epithelial integrity of the regenerated tissue could have great implication. It could establish the ‘optical biopsy’ as a potent non-invasive diagnostic tool for cutaneous pathology.

Keywords: histo-pathology, non invasive imaging, OCT, wound healing

Procedia PDF Downloads 279

Authors: M. Reza Hashemi, Chris Small, Scott Hayward

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The Northeast Coast of the US faces damaging effects of coastal flooding and winds due to Atlantic tropical and extratropical storms each year. Historically, several large storm events have produced substantial levels of damage to the region; most notably of which were the Great Atlantic Hurricane of 1938, Hurricane Carol, Hurricane Bob, and recently Hurricane Sandy (2012). The objective of this study was to develop an integrated modeling system that could be used as a forecasting/hindcasting tool to evaluate and communicate the risk coastal communities face from these coastal storms. This modeling system utilizes the ADvanced CIRCulation (ADCIRC) model for storm surge predictions and the Simulating Waves Nearshore (SWAN) model for the wave environment. These models were coupled, passing information to each other and computing over the same unstructured domain, allowing for the most accurate representation of the physical storm processes. The coupled SWAN-ADCIRC model was validated and has been set up to perform real-time forecast simulations (as well as hindcast). Modeled storm parameters were then passed to a coastal risk assessment tool. This tool, which is generic and universally applicable, generates spatial structural damage estimate maps on an individual structure basis for an area of interest. The required inputs for the coastal risk model included a detailed information about the individual structures, inundation levels, and wave heights for the selected region. Additionally, calculation of wind damage to structures was incorporated. The integrated coastal risk assessment system was then tested and applied to Charlestown, a small vulnerable coastal town along the southern shore of Rhode Island. The modeling system was applied to Hurricane Sandy and a synthetic storm. In both storm cases, effect of natural dunes on coastal risk was investigated. The resulting damage maps for the area (Charlestown) clearly showed that the dune eroded scenarios affected more structures, and increased the estimated damage. The system was also tested in forecast mode for a large Nor’Easters: Stella (March 2017). The results showed a good performance of the coupled model in forecast mode when compared to observations. Finally, a nearshore model XBeach was then nested within this regional grid (ADCIRC-SWAN) to simulate nearshore sediment transport processes and coastal erosion. Hurricane Irene (2011) was used to validate XBeach, on the basis of a unique beach profile dataset at the region. XBeach showed a relatively good performance, being able to estimate eroded volumes along the beach transects with a mean error of 16%. The validated model was then used to analyze the effectiveness of several erosion mitigation methods that were recommended in a recent study of coastal erosion in New England: beach nourishment, coastal bank (engineered core), and submerged breakwater as well as artificial surfing reef. It was shown that beach nourishment and coastal banks perform better to mitigate shoreline retreat and coastal erosion.

Keywords: ADCIRC, coastal flooding, storm surge, coastal risk assessment, living shorelines

Procedia PDF Downloads 116

Authors: Mona Ghafouri-Azar, Sara Diamond, Jeremy Bowes, Grace Yuan, Aimee Burnett, Michelle Wyndham-West, Sara Wagner, Anand Pariyarath

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Transportation is the fastest growing source of greenhouse gas emissions worldwide. In Canada, it is responsible for 23% of total CO2emissions from fuel combustion, and emissions from the transportation sector are the second largest source of emissions after the oil and gas sector. Currently, most Canadian public transportation systems rely on buses that operateon fossil fuels.Canada is currently investing billions of dollars to replacediesel buses with electric busesas this isperceived to have a significant impact on climate mitigation. This paper focuses on the possible impacts of zero emission buses (ZEB) on sustainable development, considering three dimensions of sustainability; environmental quality, economic growth, and social development.A sustainable transportation system is one that is safe, affordable, accessible, efficient, and resilient and that contributes minimal emissions of carbon and other pollutants.To enable implementation of these goals, relevant indicators were selected and defined that measure progress towards a sustainable transportation system. These were drawn from Canadian and international examples. Studies compare different European cities in terms of development, sustainability, and infrastructures, by using transport performance indicators. A Normalized Transport Sustainability index measures and compares policies in different urban areas and allows fine-tuning of policies. Analysts use a number ofmethods for sustainable analysis, like cost-benefit analysis (CBA) toassess economic benefit, life-cycle assessment (LCA) to assess social, economic, and environment factors and goals, and multi-criteria decision making (MCDM) analysis which can comparediffering stakeholder preferences.A multi criteria decision making approach is an appropriate methodology to plan and evaluate sustainable transit development and to provide insights and meaningful information for decision makers and transit agencies. It is essential to develop a system thataggregates specific discrete indices to assess the sustainability of transportation systems.Theseprioritize indicators appropriate for the differentCanadian transit system agencies and theirpreferences and requirements. This studywill develop an integrating index that alliesexistingdiscrete indexes to supporta reliable comparison between the current transportation system (diesel buses) and the new ZEB system emerging in Canada. As a first step, theindexes for each category are selected, and the index matrix constructed. Second, the selected indicators arenormalized to remove anyinconsistency between them. Next, the normalized matrix isweighted based on the relative importance of each index to the main domains of sustainability using the analytical hierarchy process (AHP) method. This is accomplished through expert judgement around the relative importance of different attributes with respect to the goals through apairwise comparison matrix. The considerationof multiple environmental, economic, and social factors (including equity and health) is integrated intoa sustainable transit planning index (STPI) which supportsrealistic ZEB implementation in Canada and beyond and is useful to different stakeholders, agencies, and ministries.

Keywords: zero emission buses, sustainability, sustainable transit, transportation, analytical hierarchy process, environment, economy, social

Procedia PDF Downloads 128

Authors: Samuel Olajide Babawale, Jonathan Bridge

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Natural Flood Management (NFM) is promoted as part of sustainable flood management (SFM) in response to climate change adaptation. Stakeholder engagement is central to this approach, and current trends are progressively moving towards a collaborative learning approach where stakeholder participation is perceived as one of the indicators of sustainable development. Within this methodology, participation embraces a diversity of knowledge and values underpinned by a philosophy of empowerment, equity, trust, and learning. To identify barriers to NFM uptake, there is a need for a new understanding of how stakeholder participation could be enhanced to benefit individual and community resilience within SFM. This is crucial in light of climate change threats and scientific reliability concerns. In contributing to this new understanding, this research evaluated the proposed interventions on six (6) UK NFM in a catchment known as the Sheffield Lakeland Partnership Area with reference to the Environment Agency Working with Natural Processes (WWNP) Potentials/Opportunities. Three of the opportunities, namely Run-off Attenuation Potential of 1%, Run-off Attenuation Potential of 3.3% and Riparian Woodland Potential, were modeled. In all the models, the interventions, though they have been proposed or already in place, are not in agreement with the data presented by EA WWNP. Findings show some institutional weaknesses, which are seen to inhibit the development of adequate flood management solutions locally with damaging implications for vulnerable communities. The gap in communication from practitioners poses a challenge to the implementation of real flood mitigating measures that align with the lead agency’s nationally accepted measures which are identified as not feasible by the farm management officers within this context. Findings highlight a dominant top-bottom approach to management with very minimal indication of local interactions. Current WWNP opportunities have been termed as not realistic by the people directly involved in the daily management of the farms, with less emphasis on prevention and mitigation. The targeted approach suggested by the EA WWNP is set against adaptive flood management and community development. The study explores dimensions of participation using the self-reliance and self-help approach to develop a methodology that facilitates reflections of currently institutionalized practices and the need to reshape spaces of interactions to enable empowered and meaningful participation. Stakeholder engagement and resilience planning underpin this research. The findings of the study suggest different agencies have different perspectives on “community participation”. It also shows communities in the case study area appear to be least influential, denied a real chance of discussing their situations and influencing the decisions. This is against the background that the communities are in the most productive regions, contributing massively to national food supplies. The results are discussed concerning practical implications for addressing interagency partnerships and conducting grassroots collaborations that empower local communities and seek solutions to sustainable development challenges. This study takes a critical look into the challenges and progress made locally in sustainable flood risk management and adaptation to climate change by the United Kingdom towards achieving the global 2030 agenda for sustainable development.

Keywords: natural flood management, sustainable flood management, sustainable development, working with natural processes, environment agency, run-off attenuation potential, climate change

Procedia PDF Downloads 72

Authors: George Kyriakopoulos, Photini Pazartzis, Anthi Koskina, Crystalie Bourcha

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The need for securing safe access to and return from outer space, as well as ensuring the viability of outer space operations, maintains vivid the debate over the promotion of organization of space traffic through a Space Traffic Management System (STM). The proliferation of outer space activities in recent years as well as the dynamic emergence of the private sector has gradually resulted in a diverse universe of actors operating in outer space. The said developments created an increased adverse impact on outer space sustainability as the case of the growing number of space debris clearly demonstrates. The above landscape sustains considerable threats to outer space environment and its operators that need to be addressed by a combination of scientific-technological measures and regulatory interventions. In this context, recourse to recent technological advancements and, in particular, to Artificial Intelligence (AI) and machine learning systems, could achieve exponential results in promoting space traffic management with respect to collision avoidance as well as launch and re-entry procedures/phases. New technologies can support the prospects of a successful space traffic management system at an international scale by enabling, inter alia, timely, accurate and analytical processing of large data sets and rapid decision-making, more precise space debris identification and tracking and overall minimization of collision risks and reduction of operational costs. What is more, a significant part of space activities (i.e. launch and/or re-entry phase) takes place in airspace rather than in outer space, hence the overall discussion also involves the highly developed, both technically and legally, international (and national) Air Traffic Management System (ATM). Nonetheless, from a regulatory perspective, the use of AI for the purposes of space traffic management puts forward implications that merit particular attention. Key issues in this regard include the delimitation of AI-based activities as space activities, the designation of the applicable legal regime (international space or air law, national law), the assessment of the nature and extent of international legal obligations regarding space traffic coordination, as well as the appropriate liability regime applicable to AI-based technologies when operating for space traffic coordination, taking into particular consideration the dense regulatory developments at EU level. In addition, the prospects of institutionalizing international cooperation and promoting an international governance system, together with the challenges of establishment of a comprehensive international STM regime are revisited in the light of intervention of AI technologies. This paper aims at examining regulatory implications advanced by the use of AI technology in the context of space traffic management operations and its key correlating concepts (SSA, space debris mitigation) drawing in particular on international and regional considerations in the field of STM (e.g. UNCOPUOS, International Academy of Astronautics, European Space Agency, among other actors), the promising advancements of the EU approach to AI regulation and, last but not least, national approaches regarding the use of AI in the context of space traffic management, in toto. Acknowledgment: The present work was co-funded by the European Union and Greek national funds through the Operational Program "Human Resources Development, Education and Lifelong Learning " (NSRF 2014-2020), under the call "Supporting Researchers with an Emphasis on Young Researchers – Cycle B" (MIS: 5048145).

Keywords: artificial intelligence, space traffic management, space situational awareness, space debris

Procedia PDF Downloads 258

Authors: Natasa Ilic, Alisa Gruden-Movsesijan, Maja Kosanovic, Sofija Glamoclija, Marina Bekic, Ljiljana Sofronic-Milosavljevic, Sergej Tomic

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As a very promising candidate for modulation of immune response in the sense of biasing the inflammatory towards an anti-inflammatory type of response, Trichinella spiralis infection was shown to successfully alleviate the severity of experimental autoimmune encephalomyelitis, the animal model of human disease multiple sclerosis. This effect is achieved via its excretory-secretory muscle larvae (ES L1) products which affect the maturation status and function of dendritic cells (DCs) by inducing the tolerogenic status of DCs, which leads to the mitigation of the Th1 type of response and the activation of a regulatory type of immune response both in vitro and in vivo. ES L1 alone or via treated DCs successfully mitigated EAE in the same manner as the infection itself. On the other hand, it has been shown that T. spiralis infection slows down the tumour growth and significantly reduces the tumour size in the model of mouse melanoma, while ES L1 possesses a pro-apoptotic and anti-survival effect on melanoma cells in vitro. Hence, although the mechanisms still need to be revealed, T. spiralis infection and its ES L1 products have a bit of controversial potential to modulate both inflammatory diseases and malignancies. The recent discovery of T. spiralis extracellular vesicles (TsEVs) suggested that the induction of complex regulation of the immune response requires simultaneous delivery of different signals in nano-sized packages. This study aimed to explore whether TsEVs bare the similar potential as ES L1 to influence the status of DCs in initiation, progression and regulation of immune response, but also to investigate the effect of both ES L1 and TsEVs on myeloid derived suppressor cells (MDSC) which present the regular tumour tissue environment. TsEVs were enriched from the conditioned medium of T. spiralis muscle larvae by differential centrifugation and used for the treatment of human monocyte-derived DCs and MDSC. On DCs, TsEVs induced low expression of HLA DR and CD40, moderate CD83 and CD86, and increased expression of ILT3 and CCR7 on treated DCs, i.e., they induced tolerogenic DCs. Such DCs possess the capacity to polarize T cell immune response towards regulatory type, with an increased proportion of IL-10 and TGF-β producing cells, similarly to ES L1. These findings indicated that the ability of TsEVs to induce tolerogenic DCs favoring anti-inflammatory responses may be helpful in coping with diseases that involve Th1/Th17-, but also Th2-mediated inflammation. In MDSC in vitro model, although both ES L1 and TsEVs had the same impact on MDSC phenotype i.e., they acted suppressive, ES L1 treated MDSC, unlike TsEVs treated ones, induced T cell response characterized by the increased RoRγT and IFN-γ, while the proportion of regulatory cells was decreased followed by the decrease in IL-10 and TGF-β positive cells proportion within this population. These findings indicate the interesting ability of ES L1 to modulate T cells response via MDSC towards pro-inflamatory type, suggesting that, unlike TsEVs which consistently demonstrate the suppresive effect on inflammatory response, it could be used also for the development of new approaches aimed for the treatment of malignant diseases. Acknowledgment: This work was funded by the Promis project – Nano-MDCS-Thera, Science Fund, Republic of Serbia.

Keywords: dendritic cells, myeloid derived suppressor cells, immunomodulation, Trichinella spiralis

Procedia PDF Downloads 204

Authors: Chenyi Ma

Abstract:

Background: The second costliest hurricane in U.S. history, Sandy landed in southern New Jersey on October 29, 2012, and struck the entire state with high winds and torrential rains. The disaster killed more than 100 people, left more than 8.5 million households without power, and damaged or destroyed more than 200,000 homes across the state. Immediately after the disaster, public policy support was provided in nine coastal counties that constituted 98% of the major and severely damaged housing units in NJ overall. The programs include Individuals and Households Assistance Program, Small Business Loan Program, National Flood Insurance Program, and the Federal Emergency Management Administration (FEMA) Public Assistance Grant Program. In the most severely affected counties, additional funding was provided through Community Development Block Grant: Reconstruction, Rehabilitation, Elevation, and Mitigation Program, and Homeowner Resettlement Program. How these policies individually and as a whole impacted housing recovery across communities with different socioeconomic and demographic profiles has not yet been studied, particularly in relation to damage levels. The concept of community social vulnerability has been widely used to explain many aspects of natural disasters. Nevertheless, how communities are vulnerable has been less fully examined. Community resilience has been conceptualized as a protective factor against negative impacts from disasters, however, how community resilience buffers the effects of vulnerability is not yet known. Because housing recovery is a dynamic social and economic process that varies according to context, this study examined the path from community vulnerability and resilience to housing recovery looking at both community characteristics and policy interventions. Sample/Methods: This retrospective longitudinal case study compared a literature-identified set of pre-disaster community characteristics, the effects of multiple public policy programs, and a set of time-variant community resilience indicators to changes in housing stock (operationally defined by percent of building permits to total occupied housing units/households) between 2010 and 2014, two years before and after Hurricane Sandy. The sample consisted of 51 municipalities in the nine counties in which between 4% and 58% of housing units suffered either major or severe damage. Structural equation modeling (SEM) was used to determine the path from vulnerability to the housing recovery, via multiple public programs, separately and as a whole, and via the community resilience indicators. The spatial analytical tool ArcGIS 10.2 was used to show the spatial relations between housing recovery patterns and community vulnerability and resilience. Findings: Holding damage levels constant, communities with higher proportions of Hispanic households had significantly lower levels of housing recovery while communities with households with an adult >age 65 had significantly higher levels of the housing recovery. The contrast was partly due to the different levels of total public support the two types of the community received. Further, while the public policy programs individually mediated the negative associations between African American and female-headed households and housing recovery, communities with larger proportions of African American, female-headed and Hispanic households were “vulnerable” to lower levels of housing recovery because they lacked sufficient public program support. Even so, higher employment rates and incomes buffered vulnerability to lower housing recovery. Because housing is the "wobbly pillar" of the welfare state, the housing needs of these particular groups should be more fully addressed by disaster policy.

Keywords: community social vulnerability, community resilience, hurricane, public policy

Procedia PDF Downloads 372

Authors: Zbigniew Czyz, Ksenia Siadkowska, Krzysztof Skiba, Karol Scislowski

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Today’s progress in the rotorcraft is mostly associated with an optimization of aircraft performance achieved by active and passive modifications of main rotor assemblies and a tail propeller. The key task is to improve their performance, improve the hover quality factor for rotors but not change in specific fuel consumption. One of the tasks to improve the helicopter is an active optimization of the main rotor providing for flight stages, i.e., an ascend, flight, a descend. An active interference with the airflow around the rotor blade section can significantly change characteristics of the aerodynamic airfoil. The efficiency of actuator systems modifying aerodynamic coefficients in the current solutions is relatively high and significantly affects the increase in strength. The solution to actively change aerodynamic characteristics assumes a periodic change of geometric features of blades depending on flight stages. Changing geometric parameters of blade warping enables an optimization of main rotor performance depending on helicopter flight stages. Structurally, an adaptation of shape memory alloys does not significantly affect rotor blade fatigue strength, which contributes to reduce costs associated with an adaptation of the system to the existing blades, and gains from a better performance can easily amortize such a modification and improve profitability of such a structure. In order to obtain quantitative and qualitative data to solve this research problem, a number of numerical analyses have been necessary. The main problem is a selection of design parameters of the main rotor and a preliminary optimization of its performance to improve the hover quality factor for rotors. This design concept assumes a three-bladed main rotor with a chord of 0.07 m and radius R = 1 m. The value of rotor speed is a calculated parameter of an optimization function. To specify the initial distribution of geometric warping, a special software has been created that uses a numerical method of a blade element which respects dynamic design features such as fluctuations of a blade in its joints. A number of performance analyses as a function of rotor speed, forward speed, and altitude have been performed. The calculations were carried out for the full model assembly. This approach makes it possible to observe the behavior of components and their mutual interaction resulting from the forces. The key element of each rotor is the shaft, hub and pins holding the joints and blade yokes. These components are exposed to the highest loads. As a result of the analysis, the safety factor was determined at the level of k > 1.5, which gives grounds to obtain certification for the strength of the structure. The construction of the joint rotor has numerous moving elements in its structure. Despite the high safety factor, the places with the highest stresses, where the signs of wear and tear may appear, have been indicated. The numerical analysis carried out showed that the most loaded element is the pin connecting the modular bearing of the blade yoke with the element of the horizontal oscillation joint. The stresses in this element result in a safety factor of k=1.7. The other analysed rotor components have a safety factor of more than 2 and in the case of the shaft, this factor is more than 3. However, it must be remembered that the structure is as strong as the weakest cell is. Designed rotor for unmanned aerial vehicles adapted to work with blades with intelligent materials in its structure meets the requirements for certification testing. Acknowledgement: This work has been financed by the Polish National Centre for Research and Development under the LIDER program, Grant Agreement No. LIDER/45/0177/L-9/17/NCBR/2018.

Keywords: main rotor, rotorcraft aerodynamics, shape memory alloy, materials, unmanned helicopter

Procedia PDF Downloads 158

Authors: Doriane Delafosse, Dominique Fontvieille

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Background: Wastewater treatment plants (WWTPs) generally display significant efficacy in virus retention yet, are sometimes highly variable, partly in relation to large fluctuating loads at the head of the plant and partly because of episodic dysfunctions in some treatment processes. The problem is especially sensitive when human enteric viruses, such as human Noroviruses Genogroup I or Adenoviruses, are in concern: their release downstream WWTP, in environments often interconnected to recreational areas, may be very harmful to human communities even at low concentrations. It points out the importance of WWTP permanent monitoring from which their internal treatment processes could be adjusted. One way to adjust primary treatments is to add coagulants and flocculants to sewage ahead settling tanks to improve decantation. In this work, sludge produced by three coagulants (two organics, one mineral), four flocculants (three cationic, one anionic), and their combinations were studied for their efficacy in human enteric virus retention. Sewage samples were coming from a WWTP in the vicinity of the laboratory. All experiments were performed three times and in triplicates in laboratory pilots, using Murine Norovirus (MNV-1), a surrogate of human Norovirus, as an internal control (spiking). Viruses were quantified by (RT-)qPCR after nucleic acid extraction from both treated water and sediment. Results: Low values of sludge virus retention (from 4 to 8% of the initial sewage concentration) were observed with each cationic organic flocculant added to wastewater and no coagulant. The largest part of the virus load was detected in the treated water (48 to 90%). However, it was not counterbalancing the amount of the introduced virus (MNV-1). The results pertained to two types of cationic flocculants, branched and linear, and in the last case, to two percentages of cations. Results were quite similar to the association of a linear cationic organic coagulant and an anionic flocculant, though suggesting that differences between water and sludges would sometimes be related to virus size or virus origins (autochthonous/allochthonous). FeCl₃, as a mineral coagulant associated with an anionic flocculant, significantly increased both auto- and allochthonous virus retention in the sediments (15 to 34%). Accordingly, virus load in treated water was lower (14 to 48%) but with a total that still does not reach the amount of the introduced virus (MNV-1). It also appeared that the virus retrieval in a bare 0.1M NaCl suspension varied rather strongly according to the FeCl₃ concentration, suggesting an inhibiting effect on the molecular analysis used to detect the virus. Finally, no viruses were detected in both phases (sediment and water) with the combination branched cationic coagulant-linear anionic flocculant, which was later demonstrated as an effect, here also, of polymers on the virus detection-molecular analysis. Conclusions: The combination of FeCl₃-anionic flocculant gave its highest performance to the decantation-based virus removal process. However, large unbalanced values in spiking experiments were observed, suggesting that polymers cast additional obstacles to both elution buffer and lysis buffer on their way to reach the virus. The situation was probably even worse with autochthonous viruses already embedded into sewage's particulate matter. Polymers and FeCl₃ also appeared to interfere in some steps of molecular analyses. More attention should be paid to such impediments wherever chemical additives are considered to be used to enhance WWTP processes. Acknowledgments: This research was supported by the ABIOLAB laboratory (Montbonnot Saint-Martin, France) and by the ASPOSAN association. Field experiments were possible thanks to the Grand Chambéry WWTP authorities (Chambéry, France).

Keywords: flocculants-coagulants, polymers, enteric viruses, wastewater sedimentation treatment plant

Procedia PDF Downloads 124

Authors: Ajit Rai, Hamza Deroui, Blandine Vacher, Khwansiri Ninpan, Arthur Aumont, Francesco Vitillo, Robert Plana

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Large-scale critical industrial scheduling problems are based on Resource-Constrained Project Scheduling Problems (RCPSP), that necessitate integration with other optimization problems (e.g., vehicle routing, supply chain, or unique industrial ones), thus requiring practical solutions (i.e., modular, computationally efficient with feasible solutions). To the best of our knowledge, the current industrial state of the art is not addressing this holistic problem. We propose an original modular solution that answers the issues exhibited by the delivery of complex projects. With three interlinked entities (project, task, resources) having their constraints, it uses a greedy heuristic with a dynamic cost function for each task with a situational assessment at each time step. It handles large-scale data and can be easily integrated with other optimization problems, already existing industrial tools and unique constraints as required by the use case. The solution has been tested and validated by domain experts on three use cases: outage management in Nuclear Power Plants (NPPs), planning of future NPP maintenance operation, and application in the defense industry on supply chain and factory relocation. In the first use case, the solution, in addition to the resources’ availability and tasks’ logical relationships, also integrates several project-specific constraints for outage management, like, handling of resource incompatibility, updating of tasks priorities, pausing tasks in a specific circumstance, and adjusting dynamic unit of resources. With more than 20,000 tasks and multiple constraints, the solution provides a feasible schedule within 10-15 minutes on a standard computer device. This time-effective simulation corresponds with the nature of the problem and requirements of several scenarios (30-40 simulations) before finalizing the schedules. The second use case is a factory relocation project where production lines must be moved to a new site while ensuring the continuity of their production. This generates the challenge of merging job shop scheduling and the RCPSP with location constraints. Our solution allows the automation of the production tasks while considering the rate expectation. The simulation algorithm manages the use and movement of resources and products to respect a given relocation scenario. The last use case establishes a future maintenance operation in an NPP. The project contains complex and hard constraints, like on Finish-Start precedence relationship (i.e., successor tasks have to start immediately after predecessors while respecting all constraints), shareable coactivity for managing workspaces, and requirements of a specific state of "cyclic" resources (they can have multiple states possible with only one at a time) to perform tasks (can require unique combinations of several cyclic resources). Our solution satisfies the requirement of minimization of the state changes of cyclic resources coupled with the makespan minimization. It offers a solution of 80 cyclic resources with 50 incompatibilities between levels in less than a minute. Conclusively, we propose a fast and feasible modular approach to various industrial scheduling problems that were validated by domain experts and compatible with existing industrial tools. This approach can be further enhanced by the use of machine learning techniques on historically repeated tasks to gain further insights for delay risk mitigation measures.

Keywords: deterministic scheduling, optimization coupling, modular scheduling, RCPSP

Procedia PDF Downloads 198

Authors: Bryan Jenkins

Abstract:

Introduction: The expansion of irrigation in the Canterbury region has led to the sustainability limits being reached for water availability and the cumulative effects of land use intensification. The institutional framework under New Zealand’s Resource Management Act was found to be an inadequate basis for managing water at sustainability limits. An alternative paradigm for water management was developed based on collaborative governance and nested adaptive systems. This led to the formulation and implementation of the Canterbury Water Management Strategy. Methods: The nested adaptive system approach was adopted. Sustainability issues were identified at multiple spatial and time scales and defined potential failure pathways for the water resource system. These included biophysical and socio-economic issues such as water availability, cumulative effects on water quality due to land use intensification, projected changes in climate, public health, institutional arrangements, economic outcomes and externalities, and, social effects of changing technology. This led to the derivation of sustainability strategies to address these failure pathways. The collaborative governance approach involved stakeholder participation and community engagement to decide on a regional strategy; regional and zone committees of community and rūnanga (Māori groups) members to develop implementation programmes for the strategy; and, farmer collectives for operational management. Findings: The strategy identified improvements in the efficiency of use of water already allocated was more effective in improving water availability than a reliance on increased storage alone. New forms of storage with less adverse impacts were introduced, such as managed aquifer recharge and off-river storage. Reductions of nutrients from land use intensification by improving management practices has been a priority. Solutions packages for addressing the degradation of vulnerable lakes and rivers have been prepared. Biodiversity enhancement projects have been initiated. Greater involvement of Māori has led to the incorporation of kaitiakitanga (resource stewardship) into implementation programmes. Emerging issues are the need for improved integration of surface water and groundwater interactions, increased use of modelling of water and financial outcomes to guide decision making, and, equity in allocation among existing users as well as between existing and future users. Conclusions: However, sustainability analysis indicates that the proposed levels of management interventions are not sufficient to achieve community targets for water management. There is a need for more proactive recovery and rehabilitation measures. Managing to environmental limits is not sufficient, rather managing adaptive cycles is needed. Better measurement and management of water use efficiency is required. Proposed implementation packages are not sufficient to deliver desired water quality outcomes. Greater attention to targets important to environmental and recreational interests is needed to maintain trust in the collaborative process. Implementation programmes don’t adequately address climate change adaptations and greenhouse gas mitigation. Affordability is a constraint on adaptive capacity of farmers and communities. More funding mechanisms are required to implement proactive measures. The legislative and institutional framework needs to be changed to incorporate water framework legislation, regional sustainability strategies and water infrastructure coordination.

Keywords: collaborative governance, irrigation management, nested adaptive systems, sustainable water management

Procedia PDF Downloads 158