Search results for: printed sensors
63 Outdoor Thermal Comfort Strategies: The Case of Cool Facades
Authors: Noelia L. Alchapar, Cláudia C. Pezzuto, Erica N. Correa
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Mitigating urban overheating is key to achieving the environmental and energy sustainability of cities. The management of the optical properties of the materials that make up the urban envelope -roofing, pavement, and facades- constitutes a profitable and effective tool to improve the urban microclimate and rehabilitate urban areas. Each material that makes up the urban envelope has a different capacity to reflect received solar radiation, which alters the fraction of solar radiation absorbed by the city. However, the paradigm of increasing solar reflectance in all areas of the city without distinguishing their relative position within the urban canyon can cause serious problems of overheating and discomfort among its inhabitants. The hypothesis that supports the research postulates that not all reflective technologies that contribute to urban radiative cooling favor the thermal comfort conditions of pedestrians to equal measure. The objective of this work is to determine to what degree the management of the optical properties of the facades modifies outdoor thermal comfort, given that the mitigation potential of materials with high reflectance in facades is strongly conditioned by geographical variables and by the geometric characteristics of the urban profile aspect ratio (H/W). This research was carried out under two climatic contexts, that of the city of Mendoza-Argentina and that of the city of Campinas-Brazil, according to the Köppen climate classification: BWk and Cwa, respectively. Two areas in two different climatic contexts (Mendoza - Argentina and Campinas - Brazil) were selected. Both areas have comparable urban morphology patterns. These areas are located in a region with low horizontal building density and residential zoning. The microclimatic conditions were monitored during the summer period with temperature and humidity fixed sensors inside vial channels. The microclimate model was simulated in ENVI-Met V5. A grid resolution of 3.5 x 3.5 x 3.5m was used for both cities, totaling an area of 145x145x30 grids. Based on the validated theoretical model, ten scenarios were simulated, modifying the height of buildings and the solar reflectivity of facades. The solar reflectivity façades ranges were: low (0.3) and high (0.75). The density scenarios range from 1th to the 5th level. The study scenarios' performance was assessed by comparing the air temperature, physiological equivalent temperature (PET), and thermal climate index (UTCI). As a result, it is observed that the behavior of the materials of the urban outdoor space depends on complex interactions. Many urban environmental factors influence including constructive characteristics, urban morphology, geographic locations, local climate, and so forth. The role of the vertical urban envelope is decisive for the reduction of urban overheating. One of the causes of thermal gain is the multiple reflections within the urban canyon, which affects not only the air temperature but also the pedestrian thermal comfort. One of the main findings of this work leads to the remarkable importance of considering both the urban warming and the thermal comfort aspects of pedestrians in urban mitigation strategies.Keywords: materials facades, solar reflectivity, thermal comfort, urban cooling
Procedia PDF Downloads 8562 Low-Cost, Portable Optical Sensor with Regression Algorithm Models for Accurate Monitoring of Nitrites in Environments
Authors: David X. Dong, Qingming Zhang, Meng Lu
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Nitrites enter waterways as runoff from croplands and are discharged from many industrial sites. Excessive nitrite inputs to water bodies lead to eutrophication. On-site rapid detection of nitrite is of increasing interest for managing fertilizer application and monitoring water source quality. Existing methods for detecting nitrites use spectrophotometry, ion chromatography, electrochemical sensors, ion-selective electrodes, chemiluminescence, and colorimetric methods. However, these methods either suffer from high cost or provide low measurement accuracy due to their poor selectivity to nitrites. Therefore, it is desired to develop an accurate and economical method to monitor nitrites in environments. We report a low-cost optical sensor, in conjunction with a machine learning (ML) approach to enable high-accuracy detection of nitrites in water sources. The sensor works under the principle of measuring molecular absorptions of nitrites at three narrowband wavelengths (295 nm, 310 nm, and 357 nm) in the ultraviolet (UV) region. These wavelengths are chosen because they have relatively high sensitivity to nitrites; low-cost light-emitting devices (LEDs) and photodetectors are also available at these wavelengths. A regression model is built, trained, and utilized to minimize cross-sensitivities of these wavelengths to the same analyte, thus achieving precise and reliable measurements with various interference ions. The measured absorbance data is input to the trained model that can provide nitrite concentration prediction for the sample. The sensor is built with i) a miniature quartz cuvette as the test cell that contains a liquid sample under test, ii) three low-cost UV LEDs placed on one side of the cell as light sources, with each LED providing a narrowband light, and iii) a photodetector with a built-in amplifier and an analog-to-digital converter placed on the other side of the test cell to measure the power of transmitted light. This simple optical design allows measuring the absorbance data of the sample at the three wavelengths. To train the regression model, absorbances of nitrite ions and their combination with various interference ions are first obtained at the three UV wavelengths using a conventional spectrophotometer. Then, the spectrophotometric data are inputs to different regression algorithm models for training and evaluating high-accuracy nitrite concentration prediction. Our experimental results show that the proposed approach enables instantaneous nitrite detection within several seconds. The sensor hardware costs about one hundred dollars, which is much cheaper than a commercial spectrophotometer. The ML algorithm helps to reduce the average relative errors to below 3.5% over a concentration range from 0.1 ppm to 100 ppm of nitrites. The sensor has been validated to measure nitrites at three sites in Ames, Iowa, USA. This work demonstrates an economical and effective approach to the rapid, reagent-free determination of nitrites with high accuracy. The integration of the low-cost optical sensor and ML data processing can find a wide range of applications in environmental monitoring and management.Keywords: optical sensor, regression model, nitrites, water quality
Procedia PDF Downloads 6761 Water Ingress into Underground Mine Voids in the Central Rand Goldfields Area, South Africa-Fluid Induced Seismicity
Authors: Artur Cichowicz
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The last active mine in the Central Rand Goldfields area (50 km x 15 km) ceased operations in 2008. This resulted in the closure of the pumping stations, which previously maintained the underground water level in the mining voids. As a direct consequence of the water being allowed to flood the mine voids, seismic activity has increased directly beneath the populated area of Johannesburg. Monitoring of seismicity in the area has been on-going for over five years using the network of 17 strong ground motion sensors. The objective of the project is to improve strategies for mine closure. The evolution of the seismicity pattern was investigated in detail. Special attention was given to seismic source parameters such as magnitude, scalar seismic moment and static stress drop. Most events are located within historical mine boundaries. The seismicity pattern shows a strong relationship between the presence of the mining void and high levels of seismicity; no seismicity migration patterns were observed outside the areas of old mining. Seven years after the pumping stopped, the evolution of the seismicity has indicated that the area is not yet in equilibrium. The level of seismicity in the area appears to not be decreasing over time since the number of strong events, with Mw magnitudes above 2, is still as high as it was when monitoring began over five years ago. The average rate of seismic deformation is 1.6x1013 Nm/year. Constant seismic deformation was not observed over the last 5 years. The deviation from the average is in the order of 6x10^13 Nm/year, which is a significant deviation. The variation of cumulative seismic moment indicates that a constant deformation rate model is not suitable. Over the most recent five year period, the total cumulative seismic moment released in the Central Rand Basin was 9.0x10^14 Nm. This is equivalent to one earthquake of magnitude 3.9. This is significantly less than what was experienced during the mining operation. Characterization of seismicity triggered by a rising water level in the area can be achieved through the estimation of source parameters. Static stress drop heavily influences ground motion amplitude, which plays an important role in risk assessments of potential seismic hazards in inhabited areas. The observed static stress drop in this study varied from 0.05 MPa to 10 MPa. It was found that large static stress drops could be associated with both small and large events. The temporal evolution of the inter-event time provides an understanding of the physical mechanisms of earthquake interaction. Changes in the characteristics of the inter-event time are produced when a stress change is applied to a group of faults in the region. Results from this study indicate that the fluid-induced source has a shorter inter-event time in comparison to a random distribution. This behaviour corresponds to a clustering of events, in which short recurrence times tend to be close to each other, forming clusters of events.Keywords: inter-event time, fluid induced seismicity, mine closure, spectral parameters of seismic source
Procedia PDF Downloads 28060 Rotational and Linear Accelerations of an Anthropometric Test Dummy Head from Taekwondo Kicks among Amateur Practitioners
Authors: Gabriel P. Fife, Saeyong Lee, David M. O'Sullivan
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Introduction: Although investigations into injury characteristics are represented well in the literature, few have investigated the biomechanical characteristics associated with head impacts in Taekwondo. Therefore, the purpose of this study was to identify the kinematic characteristics of head impacts due to taekwondo kicks among non-elite practitioners. Participants: Male participants (n= 11, 175 + 5.3 cm, 71 + 8.3 kg) with 7.5 + 3.6 years of taekwondo training volunteered for this study. Methods: Participants were asked to perform five repetitions of each technique (i.e., turning kick, spinning hook kick, spinning back kick, front axe kick, and clench axe kick) aimed at the Hybrid III head with their dominant kicking leg. All participants wore a protective foot pad (thickness = 12 mm) that is commonly used in competition and training. To simulate head impact in taekwondo, the target consisted of a Hybrid III 50th Percentile Crash Test Dummy (Hybrid III) head (mass = 5.1 kg) and neck (fitted with taekwondo headgear) secured to an aluminum support frame and positioned to each athlete’s standing height. The Hybrid III head form was instrumented with a 500 g tri-axial accelerometer (PCB Piezotronics) mounted to the head center of gravity to obtain resultant linear accelerations (RLA). Rotational accelerations were collected using three angular rate sensors mounted orthogonally to each other (Diversified Technical Systems ARS-12 K Angular Rate Sensor). The accelerometers were interfaced via a 3-channel, battery-powered integrated circuit piezoelectric sensor signal conditioner (PCB Piezotronics) and connected to a desktop computer for analysis. Acceleration data were captured using LABVIEW Signal Express and processed in accordance with SAE J211-1 channel frequency class 1000. Head injury criteria values (HIC) were calculated using the VSRSoftware. A one-way analysis of variance was used to determine differences between kicks, while the Tukey HSD test was employed for pairwise comparisons. The level of significance was set to an effect size of 0.20. All statistical analyses were done using R 3.1.0. Results: A statistically significant difference was observed in RLA (p = 0.00075); however, these differences were not clinically meaningful (η² = 0.04, 95% CI: -0.94 to 1.03). No differences were identified with ROTA (p = 0.734, η² = 0.0004, 95% CI: -0.98 to 0.98). A statistically significant difference (p < 0.001) between kicks in HIC was observed, with a medium effect (η2= 0.08, 95% CI: -0.98 to 1.07). However, the confidence interval of this difference indicates uncertainty. Tukey HSD test identified differences (p < 0.001) between kicking techniques in RLA and HIC. Conclusion: This study observed head impact levels that were comparable to previous studies of similar objectives and methodology. These data are important as impact measures from this study may be more representative of impact levels experienced by non-elite competitors. Although the clench axe kick elicited a lower RLA, the ROTA of this technique was higher than levels from other techniques (although not large differences in reference to effect sizes). As the axe kick has been reported to cause severe head injury, future studies may consider further study of this kick important.Keywords: Taekwondo, head injury, biomechanics, kicking
Procedia PDF Downloads 759 A Distributed Smart Battery Management System – sBMS, for Stationary Energy Storage Applications
Authors: António J. Gano, Carmen Rangel
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Currently, electric energy storage systems for stationary applications have known an increasing interest, namely with the integration of local renewable energy power sources into energy communities. Li-ion batteries are considered the leading electric storage devices to achieve this integration, and Battery Management Systems (BMS) are decisive for their control and optimum performance. In this work, the advancement of a smart BMS (sBMS) prototype with a modular distributed topology is described. The system, still under development, has a distributed architecture with modular characteristics to operate with different battery pack topologies and charge capacities, integrating adaptive algorithms for functional state real-time monitoring and management of multicellular Li-ion batteries, and is intended for application in the context of a local energy community fed by renewable energy sources. This sBMS system includes different developed hardware units: (1) Cell monitoring units (CMUs) for interfacing with each individual cell or module monitoring within the battery pack; (2) Battery monitoring and switching unit (BMU) for global battery pack monitoring, thermal control and functional operating state switching; (3) Main management and local control unit (MCU) for local sBMS’s management and control, also serving as a communications gateway to external systems and devices. This architecture is fully expandable to battery packs with a large number of cells, or modules, interconnected in series, as the several units have local data acquisition and processing capabilities, communicating over a standard CAN bus and will be able to operate almost autonomously. The CMU units are intended to be used with Li-ion cells but can be used with other cell chemistries, with output voltages within the 2.5 to 5 V range. The different unit’s characteristics and specifications are described, including the different implemented hardware solutions. The developed hardware supports both passive and active methods for charge equalization, considered fundamental functionalities for optimizing the performance and the useful lifetime of a Li-ion battery package. The functional characteristics of the different units of this sBMS system, including different process variables data acquisition using a flexible set of sensors, can support the development of custom algorithms for estimating the parameters defining the functional states of the battery pack (State-of-Charge, State-of-Health, etc.) as well as different charge equalizing strategies and algorithms. This sBMS system is intended to interface with other systems and devices using standard communication protocols, like those used by the Internet of Things. In the future, this sBMS architecture can evolve to a fully decentralized topology, with all the units using Wi-Fi protocols and integrating a mesh network, making unnecessary the MCU unit. The status of the work in progress is reported, leading to conclusions on the system already executed, considering the implemented hardware solution, not only as fully functional advanced and configurable battery management system but also as a platform for developing custom algorithms and optimizing strategies to achieve better performance of electric energy stationary storage devices.Keywords: Li-ion battery, smart BMS, stationary electric storage, distributed BMS
Procedia PDF Downloads 9258 Multi-scale Geographic Object-Based Image Analysis (GEOBIA) Approach to Segment a Very High Resolution Images for Extraction of New Degraded Zones. Application to The Region of Mécheria in The South-West of Algeria
Authors: Bensaid A., Mostephaoui T., Nedjai R.
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A considerable area of Algerian lands are threatened by the phenomenon of wind erosion. For a long time, wind erosion and its associated harmful effects on the natural environment have posed a serious threat, especially in the arid regions of the country. In recent years, as a result of increases in the irrational exploitation of natural resources (fodder) and extensive land clearing, wind erosion has particularly accentuated. The extent of degradation in the arid region of the Algerian Mécheriadepartment generated a new situation characterized by the reduction of vegetation cover, the decrease of land productivity, as well as sand encroachment on urban development zones. In this study, we attempt to investigate the potential of remote sensing and geographic information systems for detecting the spatial dynamics of the ancient dune cords based on the numerical processing of PlanetScope PSB.SB sensors images by September 29, 2021. As a second step, we prospect the use of a multi-scale geographic object-based image analysis (GEOBIA) approach to segment the high spatial resolution images acquired on heterogeneous surfaces that vary according to human influence on the environment. We have used the fractal net evolution approach (FNEA) algorithm to segment images (Baatz&Schäpe, 2000). Multispectral data, a digital terrain model layer, ground truth data, a normalized difference vegetation index (NDVI) layer, and a first-order texture (entropy) layer were used to segment the multispectral images at three segmentation scales, with an emphasis on accurately delineating the boundaries and components of the sand accumulation areas (Dune, dunes fields, nebka, and barkhane). It is important to note that each auxiliary data contributed to improve the segmentation at different scales. The silted areas were classified using a nearest neighbor approach over the Naâma area using imagery. The classification of silted areas was successfully achieved over all study areas with an accuracy greater than 85%, although the results suggest that, overall, a higher degree of landscape heterogeneity may have a negative effect on segmentation and classification. Some areas suffered from the greatest over-segmentation and lowest mapping accuracy (Kappa: 0.79), which was partially attributed to confounding a greater proportion of mixed siltation classes from both sandy areas and bare ground patches. This research has demonstrated a technique based on very high-resolution images for mapping sanded and degraded areas using GEOBIA, which can be applied to the study of other lands in the steppe areas of the northern countries of the African continent.Keywords: land development, GIS, sand dunes, segmentation, remote sensing
Procedia PDF Downloads 10257 Phospholipid Cationic and Zwitterionic Compounds as Potential Non-Toxic Antifouling Agents: A Study of Biofilm Formation Assessed by Micro-titer Assays with Marine Bacteria and Eco-toxicological Effect on Marine Microalgae
Authors: D. Malouch, M. Berchel, C. Dreanno, S. Stachowski-Haberkorn, P-A. Jaffres
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Biofouling is a complex natural phenomenon that involves biological, physical and chemical properties related to the environment, the submerged surface and the living organisms involved. Bio-colonization of artificial structures can cause various economic and environmental impacts. The increase in costs associated with the over-consumption of fuel from biocolonized vessels has been widely studied. Measurement drifts from submerged sensors, as well as obstructions in heat exchangers, and deterioration of offshore structures are major difficulties that industries are dealing with. Therefore, surfaces that inhibit biocolonization are required in different areas (water treatment, marine paints, etc.) and many efforts have been devoted to produce efficient and eco-compatible antifouling agents. The different steps of surface fouling are widely described in literature. Studying the biofilm and its stages provides a better understanding of how to elaborate more efficient antifouling strategies. Several approaches are currently applied, such as the use of biocide anti-fouling paint (mainly with copper derivatives) and super-hydrophobic coatings. While these two processes are proving to be the most effective, they are not entirely satisfactory, especially in a context of a changing legislation. Nowadays, the challenge is to prevent biofouling with non-biocide compounds, offering a cost effective solution, but with no toxic effects on marine organisms. Since the micro-fouling phase plays an important role in the regulation of the following steps of biofilm formation, it is desired to reduce or delate biofouling of a given surface by inhibiting the micro-fouling at its early stages. In our recent works, we reported that some amphiphilic compounds exhibited bacteriostatic or bactericidal properties at a concentration that did not affect mammalian eukaryotic cells. These remarkable properties invited us to assess this type of bio-inspired phospholipids to prevent the colonization of surfaces by marine bacteria. Of note, other studies reported that amphiphilic compounds interacted with bacteria leading to a reduction of their development. An amphiphilic compound is a molecule consisting of a hydrophobic domain and a polar head (ionic or non-ionic). These compounds appear to have interesting antifouling properties: some ionic compounds have shown antimicrobial activity, and zwitterions can reduce nonspecific adsorption of proteins. Herein, we investigate the potential of amphiphilic compounds as inhibitors of bacterial growth and marine biofilm formation. The aim of this study is to compare the efficacy of four synthetic phospholipids that features a cationic charge or a zwitterionic polar-head group to prevent microfouling with marine bacteria. Toxicity of these compounds was also studied in order to identify the most promising compounds that inhibit biofilm development and show low cytotoxicity on two links representative of coastal marine food webs: phytoplankton and oyster larvae.Keywords: amphiphilic phospholipids, biofilm, marine fouling, non-toxique assays
Procedia PDF Downloads 13156 Rapid Building Detection in Population-Dense Regions with Overfitted Machine Learning Models
Authors: V. Mantey, N. Findlay, I. Maddox
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The quality and quantity of global satellite data have been increasing exponentially in recent years as spaceborne systems become more affordable and the sensors themselves become more sophisticated. This is a valuable resource for many applications, including disaster management and relief. However, while more information can be valuable, the volume of data available is impossible to manually examine. Therefore, the question becomes how to extract as much information as possible from the data with limited manpower. Buildings are a key feature of interest in satellite imagery with applications including telecommunications, population models, and disaster relief. Machine learning tools are fast becoming one of the key resources to solve this problem, and models have been developed to detect buildings in optical satellite imagery. However, by and large, most models focus on affluent regions where buildings are generally larger and constructed further apart. This work is focused on the more difficult problem of detection in populated regions. The primary challenge with detecting small buildings in densely populated regions is both the spatial and spectral resolution of the optical sensor. Densely packed buildings with similar construction materials will be difficult to separate due to a similarity in color and because the physical separation between structures is either non-existent or smaller than the spatial resolution. This study finds that training models until they are overfitting the input sample can perform better in these areas than a more robust, generalized model. An overfitted model takes less time to fine-tune from a generalized pre-trained model and requires fewer input data. The model developed for this study has also been fine-tuned using existing, open-source, building vector datasets. This is particularly valuable in the context of disaster relief, where information is required in a very short time span. Leveraging existing datasets means that little to no manpower or time is required to collect data in the region of interest. The training period itself is also shorter for smaller datasets. Requiring less data means that only a few quality areas are necessary, and so any weaknesses or underpopulated regions in the data can be skipped over in favor of areas with higher quality vectors. In this study, a landcover classification model was developed in conjunction with the building detection tool to provide a secondary source to quality check the detected buildings. This has greatly reduced the false positive rate. The proposed methodologies have been implemented and integrated into a configurable production environment and have been employed for a number of large-scale commercial projects, including continent-wide DEM production, where the extracted building footprints are being used to enhance digital elevation models. Overfitted machine learning models are often considered too specific to have any predictive capacity. However, this study demonstrates that, in cases where input data is scarce, overfitted models can be judiciously applied to solve time-sensitive problems.Keywords: building detection, disaster relief, mask-RCNN, satellite mapping
Procedia PDF Downloads 16655 A Flexible Piezoelectric - Polymer Composite for Non-Invasive Detection of Multiple Vital Signs of Human
Authors: Sarah Pasala, Elizabeth Zacharias
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Vital sign monitoring is crucial for both everyday health and medical diagnosis. A significant factor in assessing a human's health is their vital signs, which include heart rate, breathing rate, blood pressure, and electrocardiogram (ECG) readings. Vital sign monitoring has been the focus of many system and method innovations recently. Piezoelectrics are materials that convert mechanical energy into electrical energy and can be used for vital sign monitoring. Piezoelectric energy harvesters that are stretchable and flexible can detect very low frequencies like airflow, heartbeat, etc. Current advancements in piezoelectric materials and flexible sensors have made it possible to create wearable and implantable medical devices that can continuously monitor physiological signals in humans. But because of their non-biocompatible nature, they also produce a large amount of e-waste and require another surgery to remove the implant. This paper presents a biocompatible and flexible piezoelectric composite material for wearable and implantable devices that offers a high-performance platform for seamless and continuous monitoring of human physiological signals and tactile stimuli. It also addresses the issue of e-waste and secondary surgery. A Lead-free piezoelectric, SrBi4Ti4O15, is found to be suitable for this application because the properties can be tailored by suitable substitutions and also by varying the synthesis temperature protocols. In the present work, SrBi4Ti4O15 modified by rare-earth has been synthesized and studied. Coupling factors are calculated from resonant (fr) and anti-resonant frequencies (fa). It is observed that Samarium substitution in SBT has increased the Curie temperature, dielectric and piezoelectric properties. From impedance spectroscopy studies, relaxation, and non-Debye type behaviour are observed. The composite of bioresorbable poly(l-lactide) and Lead-free rare earth modified Bismuth Layered Ferroelectrics leads to a flexible piezoelectric device for non-invasive measurement of vital signs, such as heart rate, breathing rate, blood pressure, and electrocardiogram (ECG) readings and also artery pulse signals in near-surface arteries. These composites are suitable to detect slight movement of the muscles and joints. This Lead-free rare earth modified Bismuth Layered Ferroelectrics – polymer composite is synthesized using a ball mill and the solid-state double sintering method. XRD studies indicated the two phases in the composite. SEM studies revealed the grain size to be uniform and in the range of 100 nm. The electromechanical coupling factor is improved. The elastic constants are calculated and the mechanical flexibility is found to be improved as compared to the single-phase rare earth modified Bismuth Latered piezoelectric. The results indicate that this composite is suitable for the non-invasive detection of multiple vital signs of humans.Keywords: composites, flexible, non-invasive, piezoelectric
Procedia PDF Downloads 3254 Optimization of Metal Pile Foundations for Solar Power Stations Using Cone Penetration Test Data
Authors: Adrian Priceputu, Elena Mihaela Stan
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Our research addresses a critical challenge in renewable energy: improving efficiency and reducing the costs associated with the installation of ground-mounted photovoltaic (PV) panels. The most commonly used foundation solution is metal piles - with various sections adapted to soil conditions and the structural model of the panels. However, direct foundation systems are also sometimes used, especially in brownfield sites. Although metal micropiles are generally the first design option, understanding and predicting their bearing capacity, particularly under varied soil conditions, remains an open research topic. CPT Method and Current Challenges: Metal piles are favored for PV panel foundations due to their adaptability, but existing design methods rely heavily on costly and time-consuming in situ tests. The Cone Penetration Test (CPT) offers a more efficient alternative by providing valuable data on soil strength, stratification, and other key characteristics with reduced resources. During the test, a cone-shaped probe is pushed into the ground at a constant rate. Sensors within the probe measure the resistance of the soil to penetration, divided into cone penetration resistance and shaft friction resistance. Despite some existing CPT-based design approaches for metal piles, these methods are often cumbersome and difficult to apply. They vary significantly due to soil type and foundation method, and traditional approaches like the LCPC method involve complex calculations and extensive empirical data. The method was developed by testing 197 piles on a wide range of ground conditions, but the tested piles were very different from the ones used for PV pile foundations, making the method less accurate and practical for steel micropiles. Project Objectives and Methodology: Our research aims to develop a calculation method for metal micropile foundations using CPT data, simplifying the complex relationships involved. The goal is to estimate the pullout bearing capacity of piles without additional laboratory tests, streamlining the design process. To achieve this, a case study was selected which will serve for the development of an 80ha solar power station. Four testing locations were chosen spread throughout the site. At each location, two types of steel profiles (H160 and C100) were embedded into the ground at various depths (1.5m and 2.0m). The piles were tested for pullout capacity under natural and inundated soil conditions. CPT tests conducted nearby served as calibration points. The results served for the development of a preliminary equation for estimating pullout capacity. Future Work: The next phase involves validating and refining the proposed equation on additional sites by comparing CPT-based forecasts with in situ pullout tests. This validation will enhance the accuracy and reliability of the method, potentially transforming the foundation design process for PV panels.Keywords: cone penetration test, foundation optimization, solar power stations, steel pile foundations
Procedia PDF Downloads 4453 Single Pass Design of Genetic Circuits Using Absolute Binding Free Energy Measurements and Dimensionless Analysis
Authors: Iman Farasat, Howard M. Salis
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Engineered genetic circuits reprogram cellular behavior to act as living computers with applications in detecting cancer, creating self-controlling artificial tissues, and dynamically regulating metabolic pathways. Phenemenological models are often used to simulate and design genetic circuit behavior towards a desired behavior. While such models assume that each circuit component’s function is modular and independent, even small changes in a circuit (e.g. a new promoter, a change in transcription factor expression level, or even a new media) can have significant effects on the circuit’s function. Here, we use statistical thermodynamics to account for the several factors that control transcriptional regulation in bacteria, and experimentally demonstrate the model’s accuracy across 825 measurements in several genetic contexts and hosts. We then employ our first principles model to design, experimentally construct, and characterize a family of signal amplifying genetic circuits (genetic OpAmps) that expand the dynamic range of cell sensors. To develop these models, we needed a new approach to measuring the in vivo binding free energies of transcription factors (TFs), a key ingredient of statistical thermodynamic models of gene regulation. We developed a new high-throughput assay to measure RNA polymerase and TF binding free energies, requiring the construction and characterization of only a few constructs and data analysis (Figure 1A). We experimentally verified the assay on 6 TetR-homolog repressors and a CRISPR/dCas9 guide RNA. We found that our binding free energy measurements quantitatively explains why changing TF expression levels alters circuit function. Altogether, by combining these measurements with our biophysical model of translation (the RBS Calculator) as well as other measurements (Figure 1B), our model can account for changes in TF binding sites, TF expression levels, circuit copy number, host genome size, and host growth rate (Figure 1C). Model predictions correctly accounted for how these 8 factors control a promoter’s transcription rate (Figure 1D). Using the model, we developed a design framework for engineering multi-promoter genetic circuits that greatly reduces the number of degrees of freedom (8 factors per promoter) to a single dimensionless unit. We propose the Ptashne (Pt) number to encapsulate the 8 co-dependent factors that control transcriptional regulation into a single number. Therefore, a single number controls a promoter’s output rather than these 8 co-dependent factors, and designing a genetic circuit with N promoters requires specification of only N Pt numbers. We demonstrate how to design genetic circuits in Pt number space by constructing and characterizing 15 2-repressor OpAmp circuits that act as signal amplifiers when within an optimal Pt region. We experimentally show that OpAmp circuits using different TFs and TF expression levels will only amplify the dynamic range of input signals when their corresponding Pt numbers are within the optimal region. Thus, the use of the Pt number greatly simplifies the genetic circuit design, particularly important as circuits employ more TFs to perform increasingly complex functions.Keywords: transcription factor, synthetic biology, genetic circuit, biophysical model, binding energy measurement
Procedia PDF Downloads 46852 Simulation Research of Innovative Ignition System of ASz62IR Radial Aircraft Engine
Authors: Miroslaw Wendeker, Piotr Kacejko, Mariusz Duk, Pawel Karpinski
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The research in the field of aircraft internal combustion engines is currently driven by the needs of decreasing fuel consumption and CO2 emissions, while fulfilling the level of safety. Currently, reciprocating aircraft engines are found in sports, emergency, agricultural and recreation aviation. Technically, they are most at a pre-war knowledge of the theory of operation, design and manufacturing technology, especially if compared to that high level of development of automotive engines. Typically, these engines are driven by carburetors of a quite primitive construction. At present, due to environmental requirements and dealing with a climate change, it is beneficial to develop aircraft piston engines and adopt the achievements of automotive engineering such as computer-controlled low-pressure injection, electronic ignition control and biofuels. The paper describes simulation research of the innovative power and control systems for the aircraft radial engine of high power. Installing an electronic ignition system in the radial aircraft engine is a fundamental innovative idea of this solution. Consequently, the required level of safety and better functionality as compared to the today’s plug system can be guaranteed. In this framework, this research work focuses on describing a methodology for optimizing the electronically controlled ignition system. This attempt can reduce emissions of toxic compounds as a result of lowered fuel consumption, optimized combustion and engine capability of efficient combustion of ecological fuels. New, redundant elements of the control system can improve the safety of aircraft. Consequently, the required level of safety and better functionality as compared to the today’s plug system can be guaranteed. The simulation research aimed to determine the vulnerability of the values measured (they were planned as the quantities measured by the measurement systems) to determining the optimal ignition angle (the angle of maximum torque at a given operating point). The described results covered: a) research in steady states; b) velocity ranging from 1500 to 2200 rpm (every 100 rpm); c) loading ranging from propeller power to maximum power; d) altitude ranging according to the International Standard Atmosphere from 0 to 8000 m (every 1000 m); e) fuel: automotive gasoline ES95. The three models of different types of ignition coil (different energy discharge) were studied. The analysis aimed at the optimization of the design of the innovative ignition system for an aircraft engine. The optimization involved: a) the optimization of the measurement systems; b) the optimization of actuator systems. The studies enabled the research on the vulnerability of the signals to the control of the ignition timing. Accordingly, the number and type of sensors were determined for the ignition system to achieve its optimal performance. The results confirmed the limited benefits, in terms of fuel consumption. Thus, including spark management in the optimization is mandatory to significantly decrease the fuel consumption. This work has been financed by the Polish National Centre for Research and Development, INNOLOT, under Grant Agreement No. INNOLOT/I/1/NCBR/2013.Keywords: piston engine, radial engine, ignition system, CFD model, engine optimization
Procedia PDF Downloads 38251 Buoyant Gas Dispersion in a Small Fuel Cell Enclosure: A Comparison Study Using Plain and Pressed Louvre Vent Passive Ventilation Schemes
Authors: T. Ghatauray, J. Ingram, P. Holborn
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The transition from a ‘carbon rich’ fossil fuel dependent to a ‘sustainable’ and ‘renewable’ hydrogen based society will see the deployment of hydrogen fuel cells (HFC) in transport applications and in the generation of heat and power for buildings, as part of a decentralised power network. Many deployments will be low power HFCs for domestic combined heat and power (CHP) and commercial ‘transportable’ HFCs for environmental situations, such as lighting and telephone towers. For broad commercialisation of small fuel cells to be achieved there needs to be significant confidence in their safety in both domestic and environmental applications. Low power HFCs are housed in protective steel enclosures. Standard enclosures have plain rectangular ventilation openings intended for thermal management of electronics and not the dispersion of a buoyant gas. Degradation of the HFC or supply pipework in use could lead to a low-level leak and a build-up of hydrogen gas in the enclosure. Hydrogen’s wide flammable range (4-75%) is a significant safety concern, with ineffective enclosure ventilation having the potential to cause flammable mixtures to develop with the risk of explosion. Mechanical ventilation is effective at managing enclosure hydrogen concentrations, but drains HFC power and is vulnerable to failure. This is undesirable in low power and remote installations and reliable passive ventilation systems are preferred. Passive ventilation depends upon buoyancy driven flow, with the size, shape and position of ventilation openings critical for producing predictable flows and maintaining low buoyant gas concentrations. With environmentally sited enclosures, ventilation openings with pressed horizontal and angled louvres are preferred to protect the HFC and electronics inside. There is an economic cost to adding louvres, but also a safety concern. A question arises over whether the use of pressed louvre vents impairs enclosure passive ventilation performance, when compared to same opening area plain vents. Comparison small enclosure (0.144m³) tests of same opening area pressed louvre and plain vents were undertaken. A displacement ventilation arrangement was incorporated into the enclosure with opposing upper and lower ventilation openings. A range of vent areas were tested. Helium (used as a safe analogue for hydrogen) was released from a 4mm nozzle at the base of the enclosure to simulate a hydrogen leak at leak rates from 1 to 10 lpm. Helium sensors were used to record concentrations at eight heights in the enclosure. The enclosure was otherwise empty. These tests determined that the use of pressed and angled louvre ventilation openings on the enclosure impaired the passive ventilation flow and increased helium concentrations in the enclosure. High-level stratified buoyant gas layers were also found to be deeper than with plain vent openings and were within the flammable range. The presence of gas within the flammable range is of concern, particularly as the addition of the fuel cell and electronics in the enclosure would further reduce the available volume and increase concentrations. The opening area of louvre vents would need to be greater than equivalent plain vents to achieve comparable ventilation flows or alternative schemes would need to be considered.Keywords: enclosure, fuel cell, helium, hydrogen safety, louvre vent, passive ventilation
Procedia PDF Downloads 26750 Fully Autonomous Vertical Farm to Increase Crop Production
Authors: Simone Cinquemani, Lorenzo Mantovani, Aleksander Dabek
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New technologies in agriculture are opening new challenges and new opportunities. Among these, certainly, robotics, vision, and artificial intelligence are the ones that will make a significant leap, compared to traditional agricultural techniques, possible. In particular, the indoor farming sector will be the one that will benefit the most from these solutions. Vertical farming is a new field of research where mechanical engineering can bring knowledge and know-how to transform a highly labor-based business into a fully autonomous system. The aim of the research is to develop a multi-purpose, modular, and perfectly integrated platform for crop production in indoor vertical farming. Activities will be based both on hardware development such as automatic tools to perform different activities on soil and plants, as well as research to introduce an extensive use of monitoring techniques based on machine learning algorithms. This paper presents the preliminary results of a research project of a vertical farm living lab designed to (i) develop and test vertical farming cultivation practices, (ii) introduce a very high degree of mechanization and automation that makes all processes replicable, fully measurable, standardized and automated, (iii) develop a coordinated control and management environment for autonomous multiplatform or tele-operated robots in environments with the aim of carrying out complex tasks in the presence of environmental and cultivation constraints, (iv) integrate AI-based algorithms as decision support system to improve quality production. The coordinated management of multiplatform systems still presents innumerable challenges that require a strongly multidisciplinary approach right from the design, development, and implementation phases. The methodology is based on (i) the development of models capable of describing the dynamics of the various platforms and their interactions, (ii) the integrated design of mechatronic systems able to respond to the needs of the context and to exploit the strength characteristics highlighted by the models, (iii) implementation and experimental tests performed to test the real effectiveness of the systems created, evaluate any weaknesses so as to proceed with a targeted development. To these aims, a fully automated laboratory for growing plants in vertical farming has been developed and tested. The living lab makes extensive use of sensors to determine the overall state of the structure, crops, and systems used. The possibility of having specific measurements for each element involved in the cultivation process makes it possible to evaluate the effects of each variable of interest and allows for the creation of a robust model of the system as a whole. The automation of the laboratory is completed with the use of robots to carry out all the necessary operations, from sowing to handling to harvesting. These systems work synergistically thanks to the knowledge of detailed models developed based on the information collected, which allows for deepening the knowledge of these types of crops and guarantees the possibility of tracing every action performed on each single plant. To this end, artificial intelligence algorithms have been developed to allow synergistic operation of all systems.Keywords: automation, vertical farming, robot, artificial intelligence, vision, control
Procedia PDF Downloads 3149 Gamification of eHealth Business Cases to Enhance Rich Learning Experience
Authors: Kari Björn
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Introduction of games has expanded the application area of computer-aided learning tools to wide variety of age groups of learners. Serious games engage the learners into a real-world -type of simulation and potentially enrich the learning experience. Institutional background of a Bachelor’s level engineering program in Information and Communication Technology is introduced, with detailed focus on one of its majors, Health Technology. As part of a Customer Oriented Software Application thematic semester, one particular course of “eHealth Business and Solutions” is described and reflected in a gamified framework. Learning a consistent view into vast literature of business management, strategies, marketing and finance in a very limited time enforces selection of topics relevant to the industry. Health Technology is a novel and growing industry with a growing sector in consumer wearable devices and homecare applications. The business sector is attracting new entrepreneurs and impatient investor funds. From engineering education point of view the sector is driven by miniaturizing electronics, sensors and wireless applications. However, the market is highly consumer-driven and usability, safety and data integrity requirements are extremely high. When the same technology is used in analysis or treatment of patients, very strict regulatory measures are enforced. The paper introduces a course structure using gamification as a tool to learn the most essential in a new market: customer value proposition design, followed by a market entry game. Students analyze the existing market size and pricing structure of eHealth web-service market and enter the market as a steering group of their company, competing against the legacy players and with each other. The market is growing but has its rules of demand and supply balance. New products can be developed with an R&D-investment, and targeted to market with unique quality- and price-combinations. Product cost structure can be improved by investing to enhanced production capacity. Investments can be funded optionally by foreign capital. Students make management decisions and face the dynamics of the market competition in form of income statement and balance sheet after each decision cycle. The focus of the learning outcome is to understand customer value creation to be the source of cash flow. The benefit of gamification is to enrich the learning experience on structure and meaning of financial statements. The paper describes the gamification approach and discusses outcomes after two course implementations. Along the case description of learning challenges, some unexpected misconceptions are noted. Improvements of the game or the semi-gamified teaching pedagogy are discussed. The case description serves as an additional support to new game coordinator, as well as helps to improve the method. Overall, the gamified approach has helped to engage engineering student to business studies in an energizing way.Keywords: engineering education, integrated curriculum, learning experience, learning outcomes
Procedia PDF Downloads 23848 Intelligent Crop Circle: A Blockchain-Driven, IoT-Based, AI-Powered Sustainable Agriculture System
Authors: Mishak Rahul, Naveen Kumar, Bharath Kumar
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Conceived as a high-end engine to revolutionise sustainable agri-food production, the intelligent crop circle (ICC) aims to incorporate the Internet of Things (IoT), blockchain technology and artificial intelligence (AI) to bolster resource efficiency and prevent waste, increase the volume of production and bring about sustainable solutions with long-term ecosystem conservation as the guiding principle. The operating principle of the ICC relies on bringing together multidisciplinary bottom-up collaborations between producers, researchers and consumers. Key elements of the framework include IoT-based smart sensors for sensing soil moisture, temperature, humidity, nutrient and air quality, which provide short-interval and timely data; blockchain technology for data storage on a private chain, which maintains data integrity, traceability and transparency; and AI-based predictive analysis, which actively predicts resource utilisation, plant growth and environment. This data and AI insights are built into the ICC platform, which uses the resulting DSS (Decision Support System) outlined as help in decision making, delivered through an easy-touse mobile app or web-based interface. Farmers are assumed to use such a decision-making aid behind the power of the logic informed by the data pool. Building on existing data available in the farm management systems, the ICC platform is easily interoperable with other IoT devices. ICC facilitates connections and information sharing in real-time between users, including farmers, researchers and industrial partners, enabling them to cooperate in farming innovation and knowledge exchange. Moreover, ICC supports sustainable practice in agriculture by integrating gamification techniques to stimulate farm adopters, deploying VR technologies to model and visualise 3D farm environments and farm conditions, framing the field scenarios using VR headsets and Real-Time 3D engines, and leveraging edge technologies to facilitate secure and fast communication and collaboration between users involved. And through allowing blockchain-based marketplaces, ICC offers traceability from farm to fork – that is: from producer to consumer. It empowers informed decision-making through tailor-made recommendations generated by means of AI-driven analysis and technology democratisation, enabling small-scale and resource-limited farmers to get their voice heard. It connects with traditional knowledge, brings together multi-stakeholder interactions as well as establishes a participatory ecosystem to incentivise continuous growth and development towards more sustainable agro-ecological food systems. This integrated approach leverages the power of emerging technologies to provide sustainable solutions for a resilient food system, ensuring sustainable agriculture worldwide.Keywords: blockchain, internet of things, artificial intelligence, decision support system, virtual reality, gamification, traceability, sustainable agriculture
Procedia PDF Downloads 3147 Modeling Thermal Changes of Urban Blocks in Relation to the Landscape Structure and Configuration in Guilan Province
Authors: Roshanak Afrakhteh, Abdolrasoul Salman Mahini, Mahdi Motagh, Hamidreza Kamyab
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Urban Heat Islands (UHIs) are distinctive urban areas characterized by densely populated central cores surrounded by less densely populated peripheral lands. These areas experience elevated temperatures, primarily due to impermeable surfaces and specific land use patterns. The consequences of these temperature variations are far-reaching, impacting the environment and society negatively, leading to increased energy consumption, air pollution, and public health concerns. This paper emphasizes the need for simplified approaches to comprehend UHI temperature dynamics and explains how urban development patterns contribute to land surface temperature variation. To illustrate this relationship, the study focuses on the Guilan Plain, utilizing techniques like principal component analysis and generalized additive models. The research centered on mapping land use and land surface temperature in the low-lying area of Guilan province. Satellite data from Landsat sensors for three different time periods (2002, 2012, and 2021) were employed. Using eCognition software, a spatial unit known as a "city block" was utilized through object-based analysis. The study also applied the normalized difference vegetation index (NDVI) method to estimate land surface radiance. Predictive variables for urban land surface temperature within residential city blocks were identified categorized as intrinsic (related to the block's structure) and neighboring (related to adjacent blocks) variables. Principal Component Analysis (PCA) was used to select significant variables, and a Generalized Additive Model (GAM) approach, implemented using R's mgcv package, modeled the relationship between urban land surface temperature and predictor variables.Notable findings included variations in urban temperature across different years attributed to environmental and climatic factors. Block size, shared boundary, mother polygon area, and perimeter-to-area ratio were identified as main variables for the generalized additive regression model. This model showed non-linear relationships, with block size, shared boundary, and mother polygon area positively correlated with temperature, while the perimeter-to-area ratio displayed a negative trend. The discussion highlights the challenges of predicting urban surface temperature and the significance of block size in determining urban temperature patterns. It also underscores the importance of spatial configuration and unit structure in shaping urban temperature patterns. In conclusion, this study contributes to the growing body of research on the connection between land use patterns and urban surface temperature. Block size, along with block dispersion and aggregation, emerged as key factors influencing urban surface temperature in residential areas. The proposed methodology enhances our understanding of parameter significance in shaping urban temperature patterns across various regions, particularly in Iran.Keywords: urban heat island, land surface temperature, LST modeling, GAM, Gilan province
Procedia PDF Downloads 6846 Intelligent Cooperative Integrated System for Road Safety and Road Infrastructure Maintenance
Authors: Panagiotis Gkekas, Christos Sougles, Dionysios Kehagias, Dimitrios Tzovaras
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This paper presents the architecture of the “Intelligent cooperative integrated system for road safety and road infrastructure maintenance towards 2020” (ODOS2020) advanced infrastructure, which implements a number of cooperative ITS applications based on Internet of Things and Infrastructure-to-Vehicle (V2I) technologies with the purpose to enhance the active road safety level of vehicles through the provision of a fully automated V2I environment. The primary objective of the ODOS2020 project is to contribute to increased road safety but also to the optimization of time for maintenance of road infrastructure. The integrated technological solution presented in this paper addresses all types of vehicles and requires minimum vehicle equipment. Thus, the ODOS2020 comprises a low-cost solution, which is one of its main benefits. The system architecture includes an integrated notification system to transmit personalized information on road, traffic, and environmental conditions, in order for the drivers to receive real-time and reliable alerts concerning upcoming critical situations. The latter include potential dangers on the road, such as obstacles or road works ahead, extreme environmental conditions, etc., but also informative messages, such as information on upcoming tolls and their charging policies. At the core of the system architecture lies an integrated sensorial network embedded in special road infrastructures (strips) that constantly collect and transmit wirelessly information about passing vehicles’ identification, type, speed, moving direction and other traffic information in combination with environmental conditions and road wear monitoring and predictive maintenance data. Data collected from sensors is transmitted by roadside infrastructure, which supports a variety of communication technologies such as ITS-G5 (IEEE-802.11p) wireless network and Internet connectivity through cellular networks (3G, LTE). All information could be forwarded to both vehicles and Traffic Management Centers (TMC) operators, either directly through the ITS-G5 network, or to smart devices with Internet connectivity, through cloud-based services. Therefore, through its functionality, the system could send personalized notifications/information/warnings and recommendations for upcoming events to both road users and TMC operators. In the course of the ODOS2020 project pilot operation has been conducted to allow drivers of both C-ITS equipped and non-equipped vehicles to experience the provided added value services. For non-equipped vehicles, the provided information is transmitted to a smartphone application. Finally, the ODOS2020 system and infrastructure is appropriate for installation on both urban, rural, and highway environments. The paper presents the various parts of the system architecture and concludes by outlining the various challenges that had to be overcome during its design, development, and deployment in a real operational environment. Acknowledgments: Work presented in this paper was co-financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation (call RESEARCH–CREATE–INNOVATE) under contract no. Τ1EDK-03081 (project ODOS2020).Keywords: infrastructure to vehicle, intelligent transportation systems, internet of things, road safety
Procedia PDF Downloads 11145 Solid Polymer Electrolyte Membranes Based on Siloxane Matrix
Authors: Natia Jalagonia, Tinatin Kuchukhidze
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Polymer electrolytes (PE) play an important part in electrochemical devices such as batteries and fuel cells. To achieve optimal performance, the PE must maintain a high ionic conductivity and mechanical stability at both high and low relative humidity. The polymer electrolyte also needs to have excellent chemical stability for long and robustness. According to the prevailing theory, ionic conduction in polymer electrolytes is facilitated by the large-scale segmental motion of the polymer backbone, and primarily occurs in the amorphous regions of the polymer electrolyte. Crystallinity restricts polymer backbone segmental motion and significantly reduces conductivity. Consequently, polymer electrolytes with high conductivity at room temperature have been sought through polymers which have highly flexible backbones and have largely amorphous morphology. The interest in polymer electrolytes was increased also by potential applications of solid polymer electrolytes in high energy density solid state batteries, gas sensors and electrochromic windows. Conductivity of 10-3 S/cm is commonly regarded as a necessary minimum value for practical applications in batteries. At present, polyethylene oxide (PEO)-based systems are most thoroughly investigated, reaching room temperature conductivities of 10-7 S/cm in some cross-linked salt in polymer systems based on amorphous PEO-polypropylene oxide copolymers.. It is widely accepted that amorphous polymers with low glass transition temperatures Tg and a high segmental mobility are important prerequisites for high ionic conductivities. Another necessary condition for high ionic conductivity is a high salt solubility in the polymer, which is most often achieved by donors such as ether oxygen or imide groups on the main chain or on the side groups of the PE. It is well established also that lithium ion coordination takes place predominantly in the amorphous domain, and that the segmental mobility of the polymer is an important factor in determining the ionic mobility. Great attention was pointed to PEO-based amorphous electrolyte obtained by synthesis of comb-like polymers, by attaching short ethylene oxide unit sequences to an existing amorphous polymer backbone. The aim of presented work is to obtain of solid polymer electrolyte membranes using PMHS as a matrix. For this purpose the hydrosilylation reactions of α,ω-bis(trimethylsiloxy)methyl¬hydrosiloxane with allyl triethylene-glycol mo¬nomethyl ether and vinyltriethoxysilane at 1:28:7 ratio of initial com¬pounds in the presence of Karstedt’s catalyst, platinum hydrochloric acid (0.1 M solution in THF) and platinum on the carbon catalyst in 50% solution of anhydrous toluene have been studied. The synthesized olygomers are vitreous liquid products, which are well soluble in organic solvents with specific viscosity ηsp ≈ 0.05 - 0.06. The synthesized olygomers were analysed with FTIR, 1H, 13C, 29Si NMR spectroscopy. Synthesized polysiloxanes were investigated with wide-angle X-ray, gel-permeation chromatography, and DSC analyses. Via sol-gel processes of doped with lithium trifluoromethylsulfonate (triflate) or lithium bis¬(trifluoromethylsulfonyl)¬imide polymer systems solid polymer electrolyte membranes have been obtained. The dependence of ionic conductivity as a function of temperature and salt concentration was investigated and the activation energies of conductivity for all obtained compounds are calculatedKeywords: synthesis, PMHS, membrane, electrolyte
Procedia PDF Downloads 25044 Satellite Connectivity for Sustainable Mobility
Authors: Roberta Mugellesi Dow
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As the climate crisis becomes unignorable, it is imperative that new services are developed addressing not only the needs of customers but also taking into account its impact on the environment. The Telecommunication and Integrated Application (TIA) Directorate of ESA is supporting the green transition with particular attention to the sustainable mobility.“Accelerating the shift to sustainable and smart mobility” is at the core of the European Green Deal strategy, which seeks a 90% reduction in related emissions by 2050 . Transforming the way that people and goods move is essential to increasing mobility while decreasing environmental impact, and transport must be considered holistically to produce a shared vision of green intermodal mobility. The use of space technologies, integrated with terrestrial technologies, is an enabler of smarter traffic management and increased transport efficiency for automated and connected multimodal mobility. Satellite connectivity, including future 5G networks, and digital technologies such as Digital Twin, AI, Machine Learning, and cloud-based applications are key enablers of sustainable mobility.SatCom is essential to ensure that connectivity is ubiquitously available, even in remote and rural areas, or in case of a failure, by the convergence of terrestrial and SatCom connectivity networks, This is especially crucial when there are risks of network failures or cyber-attacks targeting terrestrial communication. SatCom ensures communication network robustness and resilience. The combination of terrestrial and satellite communication networks is making possible intelligent and ubiquitous V2X systems and PNT services with significantly enhanced reliability and security, hyper-fast wireless access, as well as much seamless communication coverage. SatNav is essential in providing accurate tracking and tracing capabilities for automated vehicles and in guiding them to target locations. SatNav can also enable location-based services like car sharing applications, parking assistance, and fare payment. In addition to GNSS receivers, wireless connections, radar, lidar, and other installed sensors can enable automated vehicles to monitor surroundings, to ‘talk to each other’ and with infrastructure in real-time, and to respond to changes instantaneously. SatEO can be used to provide the maps required by the traffic management, as well as evaluate the conditions on the ground, assess changes and provide key data for monitoring and forecasting air pollution and other important parameters. Earth Observation derived data are used to provide meteorological information such as wind speed and direction, humidity, and others that must be considered into models contributing to traffic management services. The paper will provide examples of services and applications that have been developed aiming to identify innovative solutions and new business models that are allowed by new digital technologies engaging space and non space ecosystem together to deliver value and providing innovative, greener solutions in the mobility sector. Examples include Connected Autonomous Vehicles, electric vehicles, green logistics, and others. For the technologies relevant are the hybrid satcom and 5G providing ubiquitous coverage, IoT integration with non space technologies, as well as navigation, PNT technology, and other space data.Keywords: sustainability, connectivity, mobility, satellites
Procedia PDF Downloads 12543 Backward-Facing Step Measurements at Different Reynolds Numbers Using Acoustic Doppler Velocimetry
Authors: Maria Amelia V. C. Araujo, Billy J. Araujo, Brian Greenwood
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The flow over a backward-facing step is characterized by the presence of flow separation, recirculation and reattachment, for a simple geometry. This type of fluid behaviour takes place in many practical engineering applications, hence the reason for being investigated. Historically, fluid flows over a backward-facing step have been examined in many experiments using a variety of measuring techniques such as laser Doppler velocimetry (LDV), hot-wire anemometry, particle image velocimetry or hot-film sensors. However, some of these techniques cannot conveniently be used in separated flows or are too complicated and expensive. In this work, the applicability of the acoustic Doppler velocimetry (ADV) technique is investigated to such type of flows, at various Reynolds numbers corresponding to different flow regimes. The use of this measuring technique in separated flows is very difficult to find in literature. Besides, most of the situations where the Reynolds number effect is evaluated in separated flows are in numerical modelling. The ADV technique has the advantage in providing nearly non-invasive measurements, which is important in resolving turbulence. The ADV Nortek Vectrino+ was used to characterize the flow, in a recirculating laboratory flume, at various Reynolds Numbers (Reh = 3738, 5452, 7908 and 17388) based on the step height (h), in order to capture different flow regimes, and the results compared to those obtained using other measuring techniques. To compare results with other researchers, the step height, expansion ratio and the positions upstream and downstream the step were reproduced. The post-processing of the AVD records was performed using a customized numerical code, which implements several filtering techniques. Subsequently, the Vectrino noise level was evaluated by computing the power spectral density for the stream-wise horizontal velocity component. The normalized mean stream-wise velocity profiles, skin-friction coefficients and reattachment lengths were obtained for each Reh. Turbulent kinetic energy, Reynolds shear stresses and normal Reynolds stresses were determined for Reh = 7908. An uncertainty analysis was carried out, for the measured variables, using the moving block bootstrap technique. Low noise levels were obtained after implementing the post-processing techniques, showing their effectiveness. Besides, the errors obtained in the uncertainty analysis were relatively low, in general. For Reh = 7908, the normalized mean stream-wise velocity and turbulence profiles were compared directly with those acquired by other researchers using the LDV technique and a good agreement was found. The ADV technique proved to be able to characterize the flow properly over a backward-facing step, although additional caution should be taken for measurements very close to the bottom. The ADV measurements showed reliable results regarding: a) the stream-wise velocity profiles; b) the turbulent shear stress; c) the reattachment length; d) the identification of the transition from transitional to turbulent flows. Despite being a relatively inexpensive technique, acoustic Doppler velocimetry can be used with confidence in separated flows and thus very useful for numerical model validation. However, it is very important to perform adequate post-processing of the acquired data, to obtain low noise levels, thus decreasing the uncertainty.Keywords: ADV, experimental data, multiple Reynolds number, post-processing
Procedia PDF Downloads 13642 Force Sensor for Robotic Graspers in Minimally Invasive Surgery
Authors: Naghmeh M. Bandari, Javad Dargahi, Muthukumaran Packirisamy
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Robot-assisted minimally invasive surgery (RMIS) has been widely performed around the world during the last two decades. RMIS demonstrates significant advantages over conventional surgery, e.g., improving the accuracy and dexterity of a surgeon, providing 3D vision, motion scaling, hand-eye coordination, decreasing tremor, and reducing x-ray exposure for surgeons. Despite benefits, surgeons cannot touch the surgical site and perceive tactile information. This happens due to the remote control of robots. The literature survey identified the lack of force feedback as the riskiest limitation in the existing technology. Without the perception of tool-tissue contact force, the surgeon might apply an excessive force causing tissue laceration or insufficient force causing tissue slippage. The primary use of force sensors has been to measure the tool-tissue interaction force in real-time in-situ. Design of a tactile sensor is subjected to a set of design requirements, e.g., biocompatibility, electrical-passivity, MRI-compatibility, miniaturization, ability to measure static and dynamic force. In this study, a planar optical fiber-based sensor was proposed to mount at the surgical grasper. It was developed based on the light intensity modulation principle. The deflectable part of the sensor was a beam modeled as a cantilever Euler-Bernoulli beam on rigid substrates. A semi-cylindrical indenter was attached to the bottom surface the beam at the mid-span. An optical fiber was secured at both ends on the same rigid substrates. The indenter was in contact with the fiber. External force on the sensor caused deflection in the beam and optical fiber simultaneously. The micro-bending of the optical fiber would consequently result in light power loss. The sensor was simulated and studied using finite element methods. A laser light beam with 800nm wavelength and 5mW power was used as the input to the optical fiber. The output power was measured using a photodetector. The voltage from photodetector was calibrated to the external force for a chirp input (0.1-5Hz). The range, resolution, and hysteresis of the sensor were studied under monotonic and harmonic external forces of 0-2.0N with 0 and 5Hz, respectively. The results confirmed the validity of proposed sensing principle. Also, the sensor demonstrated an acceptable linearity (R2 > 0.9). A minimum external force was observed below which no power loss was detectable. It is postulated that this phenomenon is attributed to the critical angle of the optical fiber to observe total internal reflection. The experimental results were of negligible hysteresis (R2 > 0.9) and in fair agreement with the simulations. In conclusion, the suggested planar sensor is assessed to be a cost-effective solution, feasible, and easy to use the sensor for being miniaturized and integrated at the tip of robotic graspers. Geometrical and optical factors affecting the minimum sensible force and the working range of the sensor should be studied and optimized. This design is intrinsically scalable and meets all the design requirements. Therefore, it has a significant potential of industrialization and mass production.Keywords: force sensor, minimally invasive surgery, optical sensor, robotic surgery, tactile sensor
Procedia PDF Downloads 22341 Quantum Dots Incorporated in Biomembrane Models for Cancer Marker
Authors: Thiago E. Goto, Carla C. Lopes, Helena B. Nader, Anielle C. A. Silva, Noelio O. Dantas, José R. Siqueira Jr., Luciano Caseli
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Quantum dots (QD) are semiconductor nanocrystals that can be employed in biological research as a tool for fluorescence imagings, having the potential to expand in vivo and in vitro analysis as cancerous cell biomarkers. Particularly, cadmium selenide (CdSe) magic-sized quantum dots (MSQDs) exhibit stable luminescence that is feasible for biological applications, especially for imaging of tumor cells. For these facts, it is interesting to know the mechanisms of action of how such QDs mark biological cells. For that, simplified models are a suitable strategy. Among these models, Langmuir films of lipids formed at the air-water interface seem to be adequate since they can mimic half a membrane. They are monomolecular films formed at liquid-gas interfaces that can spontaneously form when organic solutions of amphiphilic compounds are spread on the liquid-gas interface. After solvent evaporation, the monomolecular film is formed, and a variety of techniques, including tensiometric, spectroscopic and optic can be applied. When the monolayer is formed by membrane lipids at the air-water interface, a model for half a membrane can be inferred where the aqueous subphase serve as a model for external or internal compartment of the cell. These films can be transferred to solid supports forming the so-called Langmuir-Blodgett (LB) films, and an ampler variety of techniques can be additionally used to characterize the film, allowing for the formation of devices and sensors. With these ideas in mind, the objective of this work was to investigate the specific interactions of CdSe MSQDs with tumorigenic and non-tumorigenic cells using Langmuir monolayers and LB films of lipids and specific cell extracts as membrane models for diagnosis of cancerous cells. Surface pressure-area isotherms and polarization modulation reflection-absorption spectroscopy (PM-IRRAS) showed an intrinsic interaction between the quantum dots, inserted in the aqueous subphase, and Langmuir monolayers, constructed either of selected lipids or of non-tumorigenic and tumorigenic cells extracts. The quantum dots expanded the monolayers and changed the PM-IRRAS spectra for the lipid monolayers. The mixed films were then compressed to high surface pressures and transferred from the floating monolayer to solid supports by using the LB technique. Images of the films were then obtained with atomic force microscopy (AFM) and confocal microscopy, which provided information about the morphology of the films. Similarities and differences between films with different composition representing cell membranes, with or without CdSe MSQDs, was analyzed. The results indicated that the interaction of quantum dots with the bioinspired films is modulated by the lipid composition. The properties of the normal cell monolayer were not significantly altered, whereas for the tumorigenic cell monolayer models, the films presented significant alteration. The images therefore exhibited a stronger effect of CdSe MSQDs on the models representing cancerous cells. As important implication of these findings, one may envisage for new bioinspired surfaces based on molecular recognition for biomedical applications.Keywords: biomembrane, langmuir monolayers, quantum dots, surfaces
Procedia PDF Downloads 19040 Detection of Patient Roll-Over Using High-Sensitivity Pressure Sensors
Authors: Keita Nishio, Takashi Kaburagi, Yosuke Kurihara
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Recent advances in medical technology have served to enhance average life expectancy. However, the total time for which the patients are prescribed complete bedrest has also increased. With patients being required to maintain a constant lying posture- also called bedsore- development of a system to detect patient roll-over becomes imperative. For this purpose, extant studies have proposed the use of cameras, and favorable results have been reported. Continuous on-camera monitoring, however, tends to violate patient privacy. We have proposed unconstrained bio-signal measurement system that could detect body-motion during sleep and does not violate patient’s privacy. Therefore, in this study, we propose a roll-over detection method by the date obtained from the bi-signal measurement system. Signals recorded by the sensor were assumed to comprise respiration, pulse, body motion, and noise components. Compared the body-motion and respiration, pulse component, the body-motion, during roll-over, generate large vibration. Thus, analysis of the body-motion component facilitates detection of the roll-over tendency. The large vibration associated with the roll-over motion has a great effect on the Root Mean Square (RMS) value of time series of the body motion component calculated during short 10 s segments. After calculation, the RMS value during each segment was compared to a threshold value set in advance. If RMS value in any segment exceeded the threshold, corresponding data were considered to indicate occurrence of a roll-over. In order to validate the proposed method, we conducted experiment. A bi-directional microphone was adopted as a high-sensitivity pressure sensor and was placed between the mattress and bedframe. Recorded signals passed through an analog Band-pass Filter (BPF) operating over the 0.16-16 Hz bandwidth. BPF allowed the respiration, pulse, and body-motion to pass whilst removing the noise component. Output from BPF was A/D converted with the sampling frequency 100Hz, and the measurement time was 480 seconds. The number of subjects and data corresponded to 5 and 10, respectively. Subjects laid on a mattress in the supine position. During data measurement, subjects—upon the investigator's instruction—were asked to roll over into four different positions—supine to left lateral, left lateral to prone, prone to right lateral, and right lateral to supine. Recorded data was divided into 48 segments with 10 s intervals, and the corresponding RMS value for each segment was calculated. The system was evaluated by the accuracy between the investigator’s instruction and the detected segment. As the result, an accuracy of 100% was achieved. While reviewing the time series of recorded data, segments indicating roll-over tendencies were observed to demonstrate a large amplitude. However, clear differences between decubitus and the roll-over motion could not be confirmed. Extant researches possessed a disadvantage in terms of patient privacy. The proposed study, however, demonstrates more precise detection of patient roll-over tendencies without violating their privacy. As a future prospect, decubitus estimation before and after roll-over could be attempted. Since in this paper, we could not confirm the clear differences between decubitus and the roll-over motion, future studies could be based on utilization of the respiration and pulse components.Keywords: bedsore, high-sensitivity pressure sensor, roll-over, unconstrained bio-signal measurement
Procedia PDF Downloads 11539 SkyCar Rapid Transit System: An Integrated Approach of Modern Transportation Solutions in the New Queen Elizabeth Quay, Perth, Western Australia
Authors: Arfanara Najnin, Michael W. Roach, Jr., Dr. Jianhong Cecilia Xia
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The SkyCar Rapid Transit System (SRT) is an innovative intelligent transport system for the sustainable urban transport system. This system will increase the urban area network connectivity and decrease urban area traffic congestion. The SRT system is designed as a suspended Personal Rapid Transit (PRT) system that travels under a guideway 5m above the ground. A driver-less passenger is via pod-cars that hang from slender beams supported by columns that replace existing lamp posts. The beams are setup in a series of interconnecting loops providing non-stop travel from beginning to end to assure journey time. The SRT forward movement is effected by magnetic motors built into the guideway. Passenger stops are at either at line level 5m above the ground or ground level via a spur guideway that curves off the main thoroughfare. The main objective of this paper is to propose an integrated Automated Transit Network (ATN) technology for the future intelligent transport system in the urban built environment. To fulfil the objective a 4D simulated model in the urban built environment has been proposed by using the concept of SRT-ATN system. The methodology for the design, construction and testing parameters of a Technology Demonstrator (TD) for proof of concept and a Simulator (S) has been demonstrated. The completed TD and S will provide an excellent proving ground for the next development stage, the SRT Prototype (PT) and Pilot System (PS). This paper covered by a 4D simulated model in the virtual built environment is to effectively show how the SRT-ATN system works. OpenSim software has been used to develop the model in a virtual environment, and the scenario has been simulated to understand and visualize the proposed SkyCar Rapid Transit Network model. The SkyCar system will be fabricated in a modular form which is easily transported. The system would be installed in increasingly congested city centers throughout the world, as well as in airports, tourist resorts, race tracks and other special purpose for the urban community. This paper shares the lessons learnt from the proposed innovation and provides recommendations on how to improve the future transport system in urban built environment. Safety and security of passengers are prime factors to be considered for this transit system. Design requirements to meet the safety needs to be part of the research and development phase of the project. Operational safety aspects would also be developed during this period. The vehicles, the track and beam systems and stations are the main components that need to be examined in detail for safety and security of patrons. Measures will also be required to protect columns adjoining intersections from errant vehicles in vehicular traffic collisions. The SkyCar Rapid Transit takes advantage of all current disruptive technologies; batteries, sensors and 4G/5G communication and solar energy technologies which will continue to reduce the costs and make the systems more profitable. SkyCar's energy consumption is extremely low compared to other transport systems.Keywords: SkyCar, rapid transit, Intelligent Transport System (ITS), Automated Transit Network (ATN), urban built environment, 4D Visualization, smart city
Procedia PDF Downloads 20938 Investigation of Natural Resource Sufficiency for Development of a Sustainable Agriculture Strategy Based on Permaculture in Malta
Authors: Byron Baron
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Typical of the Mediterranean region, the Maltese islands exhibit calcareous soils containing low organic carbon content and high salinity, in addition to being relatively shallow. This has lead to the common practice of applying copious amounts of artificial fertilisers as well as other chemical inputs, together with the use of ground water having high salinity. Such intensive agricultural activities, over a prolonged time period, on such land has lead further to the loss of any soil fertility, together with direct negative impacts on the quality of fresh water reserves and the local ecosystem. The aim of this study was to investigate whether the natural resources on the island would be sufficient to apply ecological intensification i.e. the use of natural processes to replace anthropological inputs without any significant loss in food production. This was implementing through a sustainable agricultural system based on permaculture practices. Ecological intensification following permaculture principles was implemented for two years in order to capture the seasonal changes in duplicate. The areas dedicated to wild plants were only trimmed back to avoid excessive seeding but never mowing. A number of local staple crops were grown throughout this period, also in duplicate. Concomitantly, a number of practices were implemented following permaculture principles such as reducing land tilling, applying only natural fertiliser, mulching, monitoring of soil parameters using sensors, no use of herbicides or pesticides, and precision irrigation linked to a desalination system. Numerous environmental parameters were measured at regular intervals so as to quantify any improvements in ecological conditions. Crop output was also measured as kilos of produce per area. The results clearly show that over the two year period, the variety of wild plant species increased, the number of visiting pollinators increased, there were no pest infestations (although an increase in the number of pests was observed), and a slight improvement in overall soil health was also observed. This was obviously limited by the short duration of the testing implementation. Dedicating slightly less than 15% of total land area to wild plants in the form of borders around plots of crops assisted pollination and provided a foraging area for gleaning bats (measured as an increased number of feeding buzzes) whilst not giving rise to any pest infestations and no apparent yield losses or ill effects to the crops. Observed increases in crop yields were not significant. The study concluded that with the right support for the initial establishment of a healthy ecosystem and controlled intervention, the available natural resources on the island can substantially improve the condition of the local agricultural land area, resulting is a more prolonged economical output with greater ecological sustainability. That being said, more comprehensive and long-term monitoring is required in order to fully validate these results and design a sustainable agriculture system that truly achieves the best outcome for the Maltese context.Keywords: ecological intensification, soil health, sustainable agriculture, permaculture
Procedia PDF Downloads 6237 Explanation of Sentinel-1 Sigma 0 by Sentinel-2 Products in Terms of Crop Water Stress Monitoring
Authors: Katerina Krizova, Inigo Molina
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The ongoing climate change affects various natural processes resulting in significant changes in human life. Since there is still a growing human population on the planet with more or less limited resources, agricultural production became an issue and a satisfactory amount of food has to be reassured. To achieve this, agriculture is being studied in a very wide context. The main aim here is to increase primary production on a spatial unit while consuming as low amounts of resources as possible. In Europe, nowadays, the staple issue comes from significantly changing the spatial and temporal distribution of precipitation. Recent growing seasons have been considerably affected by long drought periods that have led to quantitative as well as qualitative yield losses. To cope with such kind of conditions, new techniques and technologies are being implemented in current practices. However, behind assessing the right management, there is always a set of the necessary information about plot properties that need to be acquired. Remotely sensed data had gained attention in recent decades since they provide spatial information about the studied surface based on its spectral behavior. A number of space platforms have been launched carrying various types of sensors. Spectral indices based on calculations with reflectance in visible and NIR bands are nowadays quite commonly used to describe the crop status. However, there is still the staple limit by this kind of data - cloudiness. Relatively frequent revisit of modern satellites cannot be fully utilized since the information is hidden under the clouds. Therefore, microwave remote sensing, which can penetrate the atmosphere, is on its rise today. The scientific literature describes the potential of radar data to estimate staple soil (roughness, moisture) and vegetation (LAI, biomass, height) properties. Although all of these are highly demanded in terms of agricultural monitoring, the crop moisture content is the utmost important parameter in terms of agricultural drought monitoring. The idea behind this study was to exploit the unique combination of SAR (Sentinel-1) and optical (Sentinel-2) data from one provider (ESA) to describe potential crop water stress during dry cropping season of 2019 at six winter wheat plots in the central Czech Republic. For the period of January to August, Sentinel-1 and Sentinel-2 images were obtained and processed. Sentinel-1 imagery carries information about C-band backscatter in two polarisations (VV, VH). Sentinel-2 was used to derive vegetation properties (LAI, FCV, NDWI, and SAVI) as support for Sentinel-1 results. For each term and plot, summary statistics were performed, including precipitation data and soil moisture content obtained through data loggers. Results were presented as summary layouts of VV and VH polarisations and related plots describing other properties. All plots performed along with the principle of the basic SAR backscatter equation. Considering the needs of practical applications, the vegetation moisture content may be assessed using SAR data to predict the drought impact on the final product quality and yields independently of cloud cover over the studied scene.Keywords: precision agriculture, remote sensing, Sentinel-1, SAR, water content
Procedia PDF Downloads 12136 Optimized Processing of Neural Sensory Information with Unwanted Artifacts
Authors: John Lachapelle
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Introduction: Neural stimulation is increasingly targeted toward treatment of back pain, PTSD, Parkinson’s disease, and for sensory perception. Sensory recording during stimulation is important in order to examine neural response to stimulation. Most neural amplifiers (headstages) focus on noise efficiency factor (NEF). Conversely, neural headstages need to handle artifacts from several sources including power lines, movement (EMG), and neural stimulation itself. In this work a layered approach to artifact rejection is used to reduce corruption of the neural ENG signal by 60dBv, resulting in recovery of sensory signals in rats and primates that would previously not be possible. Methods: The approach combines analog techniques to reduce and handle unwanted signal amplitudes. The methods include optimized (1) sensory electrode placement, (2) amplifier configuration, and (3) artifact blanking when necessary. The techniques together are like concentric moats protecting a castle; only the wanted neural signal can penetrate. There are two conditions in which the headstage operates: unwanted artifact < 50mV, linear operation, and artifact > 50mV, fast-settle gain reduction signal limiting (covered in more detail in a separate paper). Unwanted Signals at the headstage input: Consider: (a) EMG signals are by nature < 10mV. (b) 60 Hz power line signals may be > 50mV with poor electrode cable conditions; with careful routing much of the signal is common to both reference and active electrode and rejected in the differential amplifier with <50mV remaining. (c) An unwanted (to the neural recorder) stimulation signal is attenuated from stimulation to sensory electrode. The voltage seen at the sensory electrode can be modeled Φ_m=I_o/4πσr. For a 1 mA stimulation signal, with 1 cm spacing between electrodes, the signal is <20mV at the headstage. Headstage ASIC design: The front end ASIC design is designed to produce < 1% THD at 50mV input; 50 times higher than typical headstage ASICs, with no increase in noise floor. This requires careful balance of amplifier stages in the headstage ASIC, as well as consideration of the electrodes effect on noise. The ASIC is designed to allow extremely small signal extraction on low impedance (< 10kohm) electrodes with configuration of the headstage ASIC noise floor to < 700nV/rt-Hz. Smaller high impedance electrodes (> 100kohm) are typically located closer to neural sources and transduce higher amplitude signals (> 10uV); the ASIC low-power mode conserves power with 2uV/rt-Hz noise. Findings: The enhanced neural processing ASIC has been compared with a commercial neural recording amplifier IC. Chronically implanted primates at MGH demonstrated the presence of commercial neural amplifier saturation as a result of large environmental artifacts. The enhanced artifact suppression headstage ASIC, in the same setup, was able to recover and process the wanted neural signal separately from the suppressed unwanted artifacts. Separately, the enhanced artifact suppression headstage ASIC was able to separate sensory neural signals from unwanted artifacts in mouse-implanted peripheral intrafascicular electrodes. Conclusion: Optimizing headstage ASICs allow observation of neural signals in the presence of large artifacts that will be present in real-life implanted applications, and are targeted toward human implantation in the DARPA HAPTIX program.Keywords: ASIC, biosensors, biomedical signal processing, biomedical sensors
Procedia PDF Downloads 32235 Gas-Phase Noncovalent Functionalization of Pristine Single-Walled Carbon Nanotubes with 3D Metal(II) Phthalocyanines
Authors: Vladimir A. Basiuk, Laura J. Flores-Sanchez, Victor Meza-Laguna, Jose O. Flores-Flores, Lauro Bucio-Galindo, Elena V. Basiuk
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Noncovalent nanohybrid materials combining carbon nanotubes (CNTs) with phthalocyanines (Pcs) is a subject of increasing research effort, with a particular emphasis on the design of new heterogeneous catalysts, efficient organic photovoltaic cells, lithium batteries, gas sensors, field effect transistors, among other possible applications. The possibility of using unsubstituted Pcs for CNT functionalization is very attractive due to their very moderate cost and easy commercial availability. However, unfortunately, the deposition of unsubstituted Pcs onto nanotube sidewalls through the traditional liquid-phase protocols turns to be very problematic due to extremely poor solubility of Pcs. On the other hand, unsubstituted free-base H₂Pc phthalocyanine ligand, as well as many of its transition metal complexes, exhibit very high thermal stability and considerable volatility under reduced pressure, which opens the possibility for their physical vapor deposition onto solid surfaces, including nanotube sidewalls. In the present work, we show the possibility of simple, fast and efficient noncovalent functionalization of single-walled carbon nanotubes (SWNTs) with a series of 3d metal(II) phthalocyanines Me(II)Pc, where Me= Co, Ni, Cu, and Zn. The functionalization can be performed in a temperature range of 400-500 °C under moderate vacuum and requires about 2-3 h only. The functionalized materials obtained were characterized by means of Fourier-transform infrared (FTIR), Raman, UV-visible and energy-dispersive X-ray spectroscopy (EDS), scanning and transmission electron microscopy (SEM and TEM, respectively) and thermogravimetric analysis (TGA). TGA suggested that Me(II)Pc weight content is 30%, 17% and 35% for NiPc, CuPc, and ZnPc, respectively (CoPc exhibited anomalous thermal decomposition behavior). The above values are consistent with those estimated from EDS spectra, namely, of 24-39%, 27-36% and 27-44% for CoPc, CuPc, and ZnPc, respectively. A strong increase in intensity of D band in the Raman spectra of SWNT‒Me(II)Pc hybrids, as compared to that of pristine nanotubes, implies very strong interactions between Pc molecules and SWNT sidewalls. Very high absolute values of binding energies of 32.46-37.12 kcal/mol and the highest occupied and lowest unoccupied molecular orbital (HOMO and LUMO, respectively) distribution patterns, calculated with density functional theory by using Perdew-Burke-Ernzerhof general gradient approximation correlation functional in combination with the Grimme’s empirical dispersion correction (PBE-D) and the double numerical basis set (DNP), also suggested that the interactions between Me(II) phthalocyanines and nanotube sidewalls are very strong. The authors thank the National Autonomous University of Mexico (grant DGAPA-IN200516) and the National Council of Science and Technology of Mexico (CONACYT, grant 250655) for financial support. The authors are also grateful to Dr. Natalia Alzate-Carvajal (CCADET of UNAM), Eréndira Martínez (IF of UNAM) and Iván Puente-Lee (Faculty of Chemistry of UNAM) for technical assistance with FTIR, TGA measurements, and TEM imaging, respectively.Keywords: carbon nanotubes, functionalization, gas-phase, metal(II) phthalocyanines
Procedia PDF Downloads 12434 Big Data Applications for the Transport Sector
Authors: Antonella Falanga, Armando Cartenì
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Today, an unprecedented amount of data coming from several sources, including mobile devices, sensors, tracking systems, and online platforms, characterizes our lives. The term “big data” not only refers to the quantity of data but also to the variety and speed of data generation. These data hold valuable insights that, when extracted and analyzed, facilitate informed decision-making. The 4Vs of big data - velocity, volume, variety, and value - highlight essential aspects, showcasing the rapid generation, vast quantities, diverse sources, and potential value addition of these kinds of data. This surge of information has revolutionized many sectors, such as business for improving decision-making processes, healthcare for clinical record analysis and medical research, education for enhancing teaching methodologies, agriculture for optimizing crop management, finance for risk assessment and fraud detection, media and entertainment for personalized content recommendations, emergency for a real-time response during crisis/events, and also mobility for the urban planning and for the design/management of public and private transport services. Big data's pervasive impact enhances societal aspects, elevating the quality of life, service efficiency, and problem-solving capacities. However, during this transformative era, new challenges arise, including data quality, privacy, data security, cybersecurity, interoperability, the need for advanced infrastructures, and staff training. Within the transportation sector (the one investigated in this research), applications span planning, designing, and managing systems and mobility services. Among the most common big data applications within the transport sector are, for example, real-time traffic monitoring, bus/freight vehicle route optimization, vehicle maintenance, road safety and all the autonomous and connected vehicles applications. Benefits include a reduction in travel times, road accidents and pollutant emissions. Within these issues, the proper transport demand estimation is crucial for sustainable transportation planning. Evaluating the impact of sustainable mobility policies starts with a quantitative analysis of travel demand. Achieving transportation decarbonization goals hinges on precise estimations of demand for individual transport modes. Emerging technologies, offering substantial big data at lower costs than traditional methods, play a pivotal role in this context. Starting from these considerations, this study explores the usefulness impact of big data within transport demand estimation. This research focuses on leveraging (big) data collected during the COVID-19 pandemic to estimate the evolution of the mobility demand in Italy. Estimation results reveal in the post-COVID-19 era, more than 96 million national daily trips, about 2.6 trips per capita, with a mobile population of more than 37.6 million Italian travelers per day. Overall, this research allows us to conclude that big data better enhances rational decision-making for mobility demand estimation, which is imperative for adeptly planning and allocating investments in transportation infrastructures and services.Keywords: big data, cloud computing, decision-making, mobility demand, transportation
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