Search results for: boiler modelling

Authors: Swee Yang Low, Dong Eon Kim, Canh Tien Trinh Nguyen, Yixiong Cai, Shie-Yui Liong

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Nee Soon swamp forest is one of the last vestiges of tropical wetland in Singapore. Understanding the hydrological regime of the swamp forest and implications for water quality is critical to guide stakeholders in implementing effective measures to preserve the wetland against anthropogenic impacts. In particular, although current field measurement data do not indicate a concern with organic pollution, reviewing the ways in which the wetland responds to elevated organic waste influx (and the corresponding impact on dissolved oxygen, DO) can help identify potential hotspots, and the impact on the outflow from the catchment which drains into downstream controlled watercourses. An integrated water quality model is therefore developed in this study to investigate spatial and temporal concentrations of DO levels and organic pollution (as quantified by biochemical oxygen demand, BOD) within the catchment’s river network under hypothetical, projected scenarios of spiked upstream inflow. The model was developed using MIKE HYDRO for modelling the study domain, as well as the MIKE ECO Lab numerical laboratory for characterising water quality processes. Model parameters are calibrated against time series of observed discharges at three measurement stations along the river network. Over a simulation period of April 2014 to December 2015, the calibrated model predicted that a continuous spiked inflow of 400 mg/l BOD will elevate downstream concentrations at the catchment outlet to an average of 12 mg/l, from an assumed nominal baseline BOD of 1 mg/l. Levels of DO were decreased from an initial 5 mg/l to 0.4 mg/l. Though a scenario of spiked organic influx at the swamp forest’s undeveloped upstream sub-catchments is currently unlikely to occur, the outcomes nevertheless will be beneficial for future planning studies in understanding how the water quality of the catchment will be impacted should urban redevelopment works be considered around the swamp forest.

Keywords: hydrology, modeling, water quality, wetland

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Authors: Tomasz Komornicki

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The primary aim of the presentation is to try to model border traffic and, at the same time to explain on which economic variables the intensity of border traffic depended in the long term. For this purpose, long series of traffic data on the Polish borders were used. Models were estimated for three variants of explanatory variables: a) for total arrivals and departures (total movement of Poles and foreigners), b) for arrivals and departures of Poles, and c) for arrivals and departures of foreigners. Each of the defined explanatory variables in the models appeared as the logarithm of the natural number of persons. Data from 1994-2017 were used for modeling (for internal Schengen borders for the years 1994-2007). Information on the number of people arriving in and leaving Poland was collected for a total of 303 border crossings. On the basis of the analyses carried out, it was found that one of the main factors determining border traffic is generally differences in the level of economic development (GDP) and the condition of the economy (level of unemployment) and the degree of border permeability. Also statistically significant for border traffic are differences in the prices of goods (fuels, tobacco, and alcohol products) and services (mainly basic ones, e.g., hairdressing services). Such a relationship exists mainly on the eastern border (border traffic determined largely by differences in the prices of goods) and on the border with Germany (in the first analysed period, border traffic was determined mainly by the prices of goods, later - after Poland's accession to the EU and the Schengen area - also by the prices of services). The models also confirmed differences in the set of factors shaping the volume and structure of border traffic on the Polish borders resulting from general geopolitical conditions, with the year 2007 being an important caesura, after which the classical population mobility factors became visible. The results obtained were additionally related to changes in traffic that occurred as a result of the CPOVID-19 pandemic and as a result of the Russian aggression against Ukraine.

Keywords: border, modal structure, transport, Ukraine

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Authors: Christopher B. Obida, George A. Blackburn, James D. Whyatt, Kirk T. Semple

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In many regions of the world, especially in developing countries, river network data are outdated or completely absent, yet such information is critical for supporting important functions such as flood mitigation efforts, land use and transportation planning, and the management of water resources. In this study, a method was developed for delineating river networks using Sentinel 1 imagery. Unsupervised classification was applied to multi-temporal Sentinel 1 data to discriminate water bodies from other land covers then the outputs were combined to generate a single persistent water bodies product. A thinning algorithm was then used to delineate river centre lines, which were converted into vector features and built into a topologically structured geometric network. The complex river system of the Niger Delta was used to compare the performance of the Sentinel-based method against alternative freely available water body products from United States Geological Survey, European Space Agency and OpenStreetMap and a river network derived from a Shuttle Rader Topography Mission Digital Elevation Model. From both raster-based and vector-based accuracy assessments, it was found that the Sentinel-based river network products were superior to the comparator data sets by a substantial margin. The geometric river network that was constructed permitted a flow routing analysis which is important for a variety of environmental management and planning applications. The extracted network will potentially be applied for modelling dispersion of hydrocarbon pollutants in Ogoniland, a part of the Niger Delta. The approach developed in this study holds considerable potential for generating up to date, detailed river network data for the many countries where such data are deficient.

Keywords: Sentinel 1, image processing, river delineation, large scale mapping, data comparison, geometric network

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Authors: Jeet Shende, Leonid Shpanin, Misko Abramiuk, Mattew Goodwin, Nicholas Pickett

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Energy harvesting on board the Unmanned Ariel Vehicle (UAV) is one of the most rapidly growing emerging technologies and consists of the collection of small amounts of energy, for different applications, from unconventional sources that are incidental to the operation of the parent system or device. Different energy harvesting techniques have already been investigated in the multirotor drones, where the energy collected comes from the systems surrounding ambient environment and typically involves the conversion of solar, kinetic, or thermal energies into electrical energy. The energy harvesting from the vibrated propeller using the piezoelectric components inside the propeller has also been proven to be feasible. However, the impact on the UAV flight performance using this technology has not been investigated. In this contribution the impact on the multirotor drone operation has been investigated at different flight control configurations which support the efficient performance of the propeller vibration energy harvesting. The industrially made MANTIS X8-PRO octocopter frame kit was used to explore the octocopter operation which was modelled using SolidWorks 3D CAD package for simulation studies. The octocopter flight control strategy is developed through integration of the SolidWorks 3D CAD software and MATLAB/Simulink simulation environment for evaluation of the octocopter behaviour under different simulated flight modes and octocopter geometries. Analysis of the two modelled octocopter geometries and their flight performance is presented via graphical representation of simulated parameters. The possibility of not using the landing gear in octocopter geometry is demonstrated. The conducted study evaluates the octocopter’s flight control technique and its impact on the energy harvesting mechanism developed on board the octocopter. Finite Element Analysis (FEA) simulation results of the modelled octocopter in operation are presented exploring the performance of the octocopter flight control and structural configurations. Applications of both octocopter structures and their flight control strategy are discussed.

Keywords: energy harvesting, flight control modelling, object modeling, unmanned aerial vehicle

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Authors: Adamu Abubakar, Abdulganiyu Yunusa, Likkason Othniel Kamfani, Abdulrahman Idris Augie

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This research study is being carried out in accordance with the Gwandu formation's potential exploratory activities in the inland basin of northwest Nigeria.The present research aims to identify and characterize subsurface anomalies within Gwandu formation using electrical resistivity tomography (ERT) and magnetic surveys, providing valuable insights for mineral exploration. The study utilizes various data enhancement techniques like derivatives, upward continuation, and spectral analysis alongside 2D modeling of electrical imaging profiles to analyze subsurface structures and anomalies. Data was collected through ERT and magnetic surveys, with subsequent processing including derivatives, spectral analysis, and 2D modeling. The results indicate significant subsurface structures such as faults, folds, and sedimentary layers. The study area's geoelectric and magnetic sections illustrate the depth and distribution of sedimentary formations, enhancing understanding of the geological framework. Thus, showed that the entire formations of Eocene sediment of Gwandu are overprinted by the study area's Tertiary strata. The NE to SW and E to W cross-profile for the pseudo geoelectric sections beneath the study area were generated using a two-dimensional (2D) electrical resistivity imaging. 2D magnetic modelling, upward continuation, and derivative analysis are used to delineate the signatures of subsurface magnetic anomalies. The results also revealed The sediment thickness by surface depth ranges from ∼4.06 km and ∼23.31 km. The Moho interface, the lower and upper mantle crusts boundary, and magnetic crust are all located at depths of around ∼10.23 km. The vertical distance between the local models of the foundation rocks to the north and south of the Sokoto Group was approximately ∼6 to ∼8 km and ∼4.5 km, respectively.

Keywords: high-resolution aeromagnetic data, electrical resistivity imaging, subsurface anomalies, 2d dorward modeling

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Authors: Shady Adib, Vladimir Vinogradov, Peter Gosling

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Digital Twin (DT) technology is a new technology that appeared in the early 21st century. The DT is defined as the digital representation of living and non-living physical assets. By connecting the physical and virtual assets, data are transmitted smoothly, allowing the virtual asset to fully represent the physical asset. Although there are lots of studies conducted on the DT concept, there is still limited information about the ability of the DT models for monitoring and detecting unexpected changes in structural behaviour in real time. This is due to the large computational efforts required for the analysis and an excessively large amount of data transferred from sensors. This paper aims to develop the DT concept to be able to detect the abnormal changes in structural behaviour in real time using advanced modelling techniques, deep learning algorithms, and data acquisition systems, taking into consideration model uncertainties. finite element (FE) models were first developed offline to be used with a reduced basis (RB) model order reduction technique for the construction of low-dimensional space to speed the analysis during the online stage. The RB model was validated against experimental test results for the establishment of a DT model of a two-dimensional truss. The established DT model and deep learning algorithms were used to identify the location of damage once it has appeared during the online stage. Finally, the RB model was used again to identify the damage severity. It was found that using the RB model, constructed offline, speeds the FE analysis during the online stage. The constructed RB model showed higher accuracy for predicting the damage severity, while deep learning algorithms were found to be useful for estimating the location of damage with small severity.

Keywords: data acquisition system, deep learning, digital twin, model uncertainties, reduced basis, reduced order model

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Authors: Isabel Carrero, Raquel Redondo, Carmen Valor

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An unclosed issue in sustainable consumption (SC) literature is the relationship between SC and well-being. This paper seeks to address three limitations in past research. First, well-being has been measured as a single-faceted construct. However, other authors have defended the need to broaden the well-being construct since it goes beyond the emotional experiences and life satisfaction. By examining the relationship between SC and the multifaceted construct of psychological well-being, past contradictory results may be reconciled. To illustrate, past studies have shown that sustainable consumers experience negative emotions when they become aware of the harm that human beings inflict on the planet but they realize they have limited power to solving the problem or when they find limited alternatives or useful information to make sustainable decisions. Thus, these experiences may negatively affect the dimension of well-being 'environmental mastery'. However, as past studies have demonstrated that sustainable consumers feel meaningful, their assessment of the dimension 'purpose in life' would be positive. Thus, we need to understand how SC impinge on the different facets of psychological well-being, in order to better understand the relationship between SC and well-being. Another limitation of past research is that most studies failed to distinguish among different pro-environmental actions under SC (i.e., boycotting, buycotting) among others. For instance, activists have been found to experience higher levels of well-being and sense of meaning than less committed sustainable consumers but also burnt-out and social rejection, which should affect negatively the dimension of 'positive relations'. Finally, the influence of gender has been overlooked in the literature of SC and well-being when it has been identified consistently as a moderator variable in SC. Therefore, this study aims to (1) investigate the effect of SC on the six facets of psychological well-being, (2) distinguish between conventional SC behaviors vs. activism to examine whether these behaviors influence psychological well-being differently (3) and test gender as a moderator variable. It does so by surveying 861 individuals. This paper contributes to existing literature by showing that the relationship between well-being and SC is more intricate than it has been presented in previous literature, as it depends on the facet, the type of behavior carried out and gender.

Keywords: activism, gender, psychological well-being, structural equation modelling, sustainable consumption

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Authors: Morten Brøgger, Kim Wittchen

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Focus on reducing energy consumption in existing buildings at large scale, e.g. in cities or countries, has been increasing in recent years. In order to reduce energy consumption in existing buildings, political incentive schemes are put in place and large scale investments are made by utility companies. Prioritising these investments requires a comprehensive overview of the energy consumption in the existing building stock, as well as potential energy-savings. However, a building stock comprises thousands of buildings with different characteristics making it difficult to model energy consumption accurately. Moreover, the complexity of the building stock makes it difficult to convey model results to policymakers and other stakeholders. In order to manage the complexity of the building stock, building archetypes are often employed in building stock energy models (BSEMs). Building archetypes are formed by segmenting the building stock according to specific characteristics. Segmenting the building stock according to building type and building age is common, among other things because this information is often easily available. This segmentation makes it easy to convey results to non-experts. However, using a single archetypical building to represent all buildings in a segment of the building stock is associated with loss of detail. Thermal characteristics are aggregated while other characteristics, which could affect the energy efficiency of a building, are disregarded. Thus, using a simplified representation of the building stock could come at the expense of the accuracy of the model. The present study evaluates the accuracy of a conventional archetype-based BSEM that segments the building stock according to building type- and age. The accuracy is evaluated in terms of the archetypes’ ability to accurately emulate the average energy demands of the corresponding buildings they were meant to represent. This is done for the buildings’ energy demands as a whole as well as for relevant sub-demands. Both are evaluated in relation to the type- and the age of the building. This should provide researchers, who use archetypes in BSEMs, with an indication of the expected accuracy of the conventional archetype model, as well as the accuracy lost in specific parts of the calculation, due to use of the archetype method.

Keywords: building stock energy modelling, energy-savings, archetype

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Authors: Beatrice Wamuyu Muchiri, Monika M. L. Dos Santos

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An increasingly recognised prevention approach for substance use entails reduction in risk factors and enhancement of promotive or protective factors in individuals and the environment surrounding them during their growth and development. However, in order to enhance the effectiveness of this approach, continuous study of risk aspects targeting different cultures, social groups and mixture of society has been recommended. This study evaluated the impact of potential risk and protective factors associated with family management and relations on adolescent substance abuse in South Africa. Exploratory analysis and cumulative odds ordinal logistic regression modelling was performed on the data while controlling for demographic and socio-economic characteristics on adolescent substance use. The most intensely used substances were tobacco, cannabis, cocaine, heroin and alcohol in decreasing order of use intensity. The specific protective or risk impact of family management or relations factors varied from substance to substance. Risk factors associated with demographic and socio-economic factors included being male, younger age, being in lower education grades, coloured ethnicity, adolescents from divorced parents and unemployed or fully employed mothers. Significant family relations risk and protective factors against substance use were classified as either family functioning and conflict or family bonding and support. Several family management factors, categorised as parental monitoring, discipline, behavioural control and rewards, demonstrated either risk or protective effect on adolescent substance use. Some factors had either interactive risk or protective impact on substance use or lost significance when analysed jointly with other factors such as controlled variables. Interaction amongst risk or protective factors as well as the type of substance should be considered when further considering interventions based on these risk or protective factors. Studies in other geographical regions, institutions and with better gender balance are recommended to improve upon the representativeness of the results. Several other considerations to be made when formulating interventions, the shortcomings of this study and possible improvements as well as future studies are also suggested.

Keywords: risk factors, protective factors, substance use, adolescents

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Authors: Pelin Yılmaz Çetiner, Metin Mert İlgün, Nazlı Çetindağ, Emine Birci, Gizemnur Yıldız Uysal, Özcan Hatipoğlu, Ehsan Tuzcuoğlu, Gökhan Sır

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Water scarcity is an inevitable problem affecting more and more people day by day. It is a worldwide crisis and a consequence of rapid population growth, urbanization and overexploitation. Thus, the solutions providing the reclamation of the wastewater are the desired approach. Wastewater contains various substances such as organic, soaps and detergents, solvents, biological substances, and inorganic substances. The physical properties of the wastewater differs regarding to its origin such as commerical, domestic or hospital usage. Thus, the treatment strategy of this type of wastewater is should be comprehensively investigated and properly treated. The advanced oxidation process comes up as a hopeful method associated with the formation of reactive hydroxyl radicals that are highly reactive to oxidize of organic pollutants. This process has a priority on other methods such as coagulation, flocuation, sedimentation and filtration since it was not cause any undesirable by-products. In the present study, it was aimed to investigate the applicability of advanced oxidation process for the treatment of household appliances wastewater. For this purpose, the laboratory studies providing the effectively addressing of the formed radicals to organic pollutants were carried out. Then the effect of process parameters were comprehensively studied by using response surface methodology, Box-Benhken experimental desing. The final chemical oxygen demand (COD) was the main output to evaluate the optimum point providing the expected COD removal. The linear alkyl benzene sulfonate (LAS), total dissolved solids (TDS) and color were measured for the optimum point providing the expected COD removal. Finally, present study pointed out that advanced oxidation process might be efficiently preffered to treat of the household appliances wastewater and the optimum process parameters provided that expected removal of COD.

Keywords: advanced oxidation process, household appliances wastewater, modelling, water reuse

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Authors: Ting Kai Chia, Ruifeng Yan, Feifei Bai, Tapan Saha

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This research presents a real-world power system oscillation incident in 2022 originated by a hybrid solar photovoltaic (PV) and wind renewable energy farm with a rated capacity of approximately 300MW in Australia. The voltage and reactive power outputs recorded at the point of common coupling (PCC) oscillated at a sub-synchronous frequency region, which sustained for approximately five hours in the network. The reactive power oscillation gradually increased over time and reached a recorded maximum of approximately 250MVar peak-to-peak (from inductive to capacitive). The network service provider was not able to quickly identify the location of the oscillation source because the issue was widespread across the network. After the incident, the original equipment manufacturer (OEM) concluded that the oscillation problem was caused by the incorrect setting recovery of the hybrid power plant controller (HPPC) in the voltage and reactive power control loop after a loss of communication event. The voltage controller normally outputs a reactive (Q) reference value to the Q controller which controls the Q dispatch setpoint of PV and wind plants in the hybrid farm. Meanwhile, a feed-forward (FF) configuration is used to bypass the Q controller in case there is a loss of communication. Further study found that the FF control mode was still engaged when communication was re-established, which ultimately resulted in the oscillation event. However, there was no detailed explanation of why the FF control mode can cause instability in the hybrid farm. Also, there was no duplication of the event in the simulation to analyze the root cause of the oscillation. Therefore, this research aims to model and replicate the oscillation event in a simulation environment and investigate the underlying behavior of the HPPC and the consequent oscillation mechanism during the incident. The outcome of this research will provide significant benefits to the safe operation of large-scale renewable energy generators and power networks.

Keywords: PV, oscillation, modelling, wind

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Authors: Fengqing Li, Petra Schneider

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Failure of tailings management facilities (TMF) of radioactive residues is an enormous challenge worldwide and can result in major catastrophes. Particularly in transboundary regions, such failure is most likely to lead to international conflict. This risk occurs in Kyrgyzstan and Uzbekistan, where the current major challenge is the quantification of impacts due to pollution from uranium legacy sites and especially the impact on river basins after natural hazards (i.e., landslides). By means of GoldSim, a probabilistic simulation model, the amount of tailing material that flows into the river networks of Mailuu Suu in Kyrgyzstan after pond failure was simulated for three scenarios, namely 10%, 20%, and 30% of material inputs. Based on Muskingum-Cunge flood routing procedure, the peak value of uranium flood wave along the river network was simulated. Among the 23 TMF, 19 ponds are close to the river networks. The spatiotemporal distributions of uranium along the river networks were then simulated for all the 19 ponds under three scenarios. Taking the TP7 which is 30 km far from the Kyrgyzstan-Uzbekistan border as one example, the uranium concentration decreased continuously along the longitudinal gradient of the river network, the concentration of uranium was observed at the border after 45 min of the pond failure and the highest value was detected after 69 min. The highest concentration of uranium at the border were 16.5, 33, and 47.5 mg/L under scenarios of 10%, 20%, and 30% of material inputs, respectively. In comparison to the guideline value of uranium in drinking water (i.e., 30 µg/L) provided by the World Health Organization, the observed concentrations of uranium at the border were 550‒1583 times higher. In order to mitigate the transboundary impact of a radioactive pollutant release, an integrated framework consisting of three major strategies were proposed. Among, the short-term strategy can be used in case of emergency event, the medium-term strategy allows both countries handling the TMF efficiently based on the benefit-sharing concept, and the long-term strategy intends to rehabilitate the site through the relocation of all TMF.

Keywords: Central Asia, contaminant transport modelling, radioactive residue, transboundary conflict

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Authors: Patrick Ebong Ebewo

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The trend of high unemployment levels globally is a growing concern, which suggests that university students especially those studying the creative industries are most likely to face unemployment upon completion of their studies. Therefore the effort of university in fostering entrepreneurial knowledge is equally important to the development of student’s soft skill. The purpose of this paper is to assess the significance of perceived university environment and perceived educational support that influencing University students’ intention in starting their own business in the future. Thus, attempting to answer the question 'How does perceived university environment affect students’ attitude towards entrepreneurship as a career option, perceived entrepreneurial abilities, subjective norm and entrepreneurial intentions?' The study is based on the Theory of Planned Behaviour model adapted from previous studies and empirically tested on graduates at the Tshwane University of Technology. A sample of 150 graduates from the Arts and Design graduates took part in the study and data collected were analysed using structural equation modelling (SEM). Our findings seem to suggest the indirect impact of perceived university environment on entrepreneurial intention through perceived environment support and perceived entrepreneurial abilities. Thus, any increase in perceived university environment might influence students to become entrepreneurs. Based on these results, it is recommended that: (a) Tshwane University of Technology and other universities of technology should establish an ‘Entrepreneurship Internship Programme’ as a tool for stimulated work integrated learning. Post-graduation intervention could be implemented by the development of a ‘Graduate Entrepreneurship Program’ which should be embedded in the Bachelor of Technology (B-Tech now Advance Diploma) and Postgraduate courses; (b) Policymakers should consider the development of a coherent national policy framework that addresses entrepreneurship for the Arts/creative industries sector. This would create the enabling environment for the evolution of Higher Education Institutions from merely Teaching, Learning & Research to becoming drivers for creative entrepreneurship.

Keywords: business venture, entrepreneurship education, entrepreneurial intent, university environment

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Authors: Indunil Jayatilake, Warna Karunasena

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Fiber Reinforced Polymer (FRP) composites enjoy an array of applications ranging from aerospace, marine and military to automobile, recreational and civil industry due to their outstanding properties. A structural glass fiber reinforced polymer (GFRP) composite sandwich panel made from E-glass fiber skin and a modified phenolic core has been manufactured in Australia for civil engineering applications. One of the major mechanisms of damage in FRP composites is skin-core debonding. The presence of debonding is of great concern not only because it severely affects the strength but also it modifies the dynamic characteristics of the structure, including natural frequency and vibration modes. This paper deals with the investigation of the dynamic characteristics of a GFRP beam with single and multiple debonding by finite element based numerical simulations and analyses using the STRAND7 finite element (FE) software package. Three-dimensional computer models have been developed and numerical simulations were done to assess the dynamic behavior. The FE model developed has been validated with published experimental, analytical and numerical results for fully bonded as well as debonded beams. A comparative analysis is carried out based on a comprehensive parametric investigation. It is observed that the reduction in natural frequency is more affected by single debonding than the equally sized multiple debonding regions located symmetrically to the single debonding position. Thus it is revealed that a large single debonding area leads to more damage in terms of natural frequency reduction than isolated small debonding zones of equivalent area, appearing in the GFRP beam. Furthermore, the extents of natural frequency shifts seem mode-dependent and do not seem to have a monotonous trend of increasing with the mode numbers.

Keywords: debonding, dynamic response, finite element modelling, novel FRP beams

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Authors: Laurent Pitteloud, Jörg Meier

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Piled raft foundations represent an efficient and reliable technique for transferring high vertical and horizontal loads to the subsoil. Piled raft foundations were success­fully implemented for several high-rise buildings world­wide over the last decades. For the structural design of this foundation type the stiffnesses of both the piles and the raft have to be deter­mined for the static (e.g. dead load, live load) and the dynamic load cases (e.g. earthquake). In this context the question often arises, to which proportion wind loads are to be considered as dynamic loads. Usually a piled raft foundation has to be monitored in order to verify the design hypotheses. As an additional benefit, the analysis of this monitoring data may lead to a better under­standing of the behaviour of this foundation type for future projects in similar subsoil conditions. In case the measurement frequency is high enough, one may also draw conclusions on the effect of wind loading on the piled raft foundation. For a 41-storey office building in Basel, Switzerland, the preliminary design showed that a piled raft foundation was the best solution to satisfy both design requirements, as well as economic aspects. A high-frequency monitoring of the foundation including pile loads, vertical stresses under the raft, as well as pore water pressures was performed over 5 years. In windy situations the analysis of the measure­ments shows that the pile load increment due to wind consists of a static and a cyclic load term. As piles and raft react with different stiffnesses under static and dynamic loading, these measure­ments are useful for the correct definition of stiffnesses of future piled raft foundations. This paper outlines the design strategy and the numerical modelling of the aforementioned piled raft foundation. The measurement results are presented and analysed. Based on the findings, comments and conclusions on the definition of pile and raft stiffnesses for vertical and wind loading are proposed.

Keywords: design, dynamic, foundation, monitoring, pile, raft, wind load

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Authors: S. Jayasinghe, R. B. N. Dissanayake

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Optimization modelling together with the Network models and Linear Programming techniques is a powerful tool in problem solving and decision making in real world applications. This study developed a mathematical model to optimize the net profit by minimizing the transportation cost. This model focuses the transportation among decentralized production plants to a centralized distribution centre and then the distribution among island wide agencies considering the customer satisfaction as a requirement. This company produces basically 9 types of food items with 82 different varieties and 4 types of non-food items with 34 different varieties. Among 6 production plants, 4 were located near the city of Mawanella and the other 2 were located in Galewala and Anuradhapura cities which are 80 km and 150 km away from Mawanella respectively. The warehouse located in the Mawanella was the main production plant and also the only distribution plant. This plant distributes manufactured products to 39 agencies island-wide. The average values and average amount of the goods for 6 consecutive months from May 2013 to October 2013 were collected and then average demand values were calculated. The following constraints are used as the necessary requirement to satisfy the optimum condition of the model; there was one source, 39 destinations and supply and demand for all the agencies are equal. Using transport cost for a kilometer, total transport cost was calculated. Then the model was formulated using distance and flow of the distribution. Network optimization and linear programming techniques were used to originate the model while excel solver is used in solving. Results showed that company requires total transport cost of Rs. 146, 943, 034.50 to fulfil the customers’ requirement for a month. This is very much less when compared with data without using the model. Model also proved that company can reduce their transportation cost by 6% when distributing to island-wide customers. Company generally satisfies their customers’ requirements by 85%. This satisfaction can be increased up to 97% by using this model. Therefore this model can be used by other similar companies in order to reduce the transportation cost.

Keywords: mathematical model, network optimization, linear programming

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Authors: Md. Akiz Uddin

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This research attempted to identify the determining factors that extensively persuaded customers of the First Security Islamic Bank Limited (FSIBL) to open accounts and their perception and satisfaction level towards it. Initially, a theoretical model was established based on existing literature reviews. After that, a self-administered structured questionnaire was developed, and data were collected from 180 customers of the FSIBL of Bangladesh using purposive sampling technique. The collected data were later analyzed through a statistical software. Structural Equation Modelling (SEM) was used to verify the model of the study and test the hypotheses. The study particularly examined the determinants of opening accounts, customers’ perception and their satisfaction level towards the bank on several factors like the bank’s compliance with Shariah law, use of modern technology, assurance, reliability, empathy, profitability, and responsiveness. To examine the impact of religious belief on being FSIBL clients, the study also investigates non-Muslim clients’ perception about FSIBL. The study focused on FSIBL customers only from five branches of Dhaka city. The study found that the religious beliefs is the most significant factors for Muslim customers for considering FSIBL to open an account, and they are satisfied with the services, too. However, for non-Muslim customers, other benefits like E-banking, various user-friendly services are the most significant factors for choosing FSIBL. Their satisfaction level is also statistically significant. Furthermore, even if the non- Muslim customers didn’t consider religious beliefs as determinant factors for choosing FSIBL, the respondents informed that they have trust that people who believe in shariah law are more reliable to keep money with them. These findings open up the avenue for future researchers to conduct more study in this area through employing a larger sample size and more branches and extending the current model by incorporating new variables. The study will be an important addition to the potentials of Islamic banking system, literature of service quality and customer satisfaction level, particularly in the success of Islamic banking system in Bangladesh.

Keywords: islamic banking, customers’ satisfaction, customers’ perception, shariah law

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Authors: Peterson Thokozani Ngema, Paramespri Naidoo, Amir H. Mohammadi, Deresh Ramjugernath

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Phase equilibrium data (dissociation data) for clathrate hydrate (gas hydrate) were undertaken for systems involving fluorinated refrigerants with a single and mixed electrolytes (NaCl, CaCl₂, MgCl₂, and Na₂SO₄) aqueous solution at various salt concentrations in the absence and presence of cyclopentane (CP). The ternary systems for (R410a or R507) with the water system in the presence of CP were performed in the temperature and pressures ranges of (279.8 to 294.4) K and (0.158 to 1.385) MPa, respectively. Measurements for R410a with single electrolyte {NaCl or CaCl₂} solution in the presence of CP were undertaken at salt concentrations of (0.10, 0.15 and 0.20) mass fractions in the temperature and pressure ranges of (278.4 to 293.7) K and (0.214 to1.179) MPa, respectively. The temperature and pressure conditions for R410a with Na₂SO₄ aqueous solution system were investigated at a salt concentration of 0.10 mass fraction in the range of (283.3 to 291.6) K and (0.483 to 1.373) MPa respectively. Measurements for {R410a or R507} with mixed electrolytes {NaCl, CaCl₂, MgCl₂} aqueous solution was undertaken at various salt concentrations of (0.002 to 0.15) mass fractions in the temperature and pressure ranges of (274.5 to 292.9) K and (0.149 to1.119) MPa in the absence and presence of CP, in which there is no published data related to mixed salt and a promoter. The phase equilibrium measurements were performed using a non-visual isochoric equilibrium cell that co-operates the pressure-search technique. This study is focused on obtaining equilibrium data that can be utilized to design and optimize industrial wastewater, desalination process and the development of Hydrate Electrolyte–Cubic Plus Association (HE–CPA) Equation of State. The results show an impressive improvement in the presence of promoter (CP) on hydrate formation because it increases the dissociation temperatures near ambient conditions. The results obtained were modeled using a developed HE–CPA equation of state. The model results strongly agree with the measured hydrate dissociation data.

Keywords: association, desalination, electrolytes, promoter

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Authors: Heval Serhat Uluk, Sam M. Dakka, Kuldeep Singh, Richard Jefferson-Loveday

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The carbon footprint of the aviation sector in total measured 3.8% in 2017, and it is expected to triple by 2050. New combustion approaches and fuel types are necessary to prevent this. This paper will focus on using propane, methane, and hydrogen as fuel replacements for kerosene and implement a trapped vortex combustor design to increase efficiency. Reacting simulations were conducted for axisymmetric trapped vortex combustor to investigate the static pressure drop, combustion efficiency and pattern factor for various cavity aspect ratios for 0.3, 0.6 and 1 and air mass flow rates for 14 m/s, 28 m/s and 42 m/s. Propane, methane and hydrogen are used as alternative fuels. The combustion model was anchored based on swirl flame configuration with an emphasis on high fidelity of boundary conditions with favorable results of eddy dissipation model implementation. Reynolds Averaged Navier Stokes (RANS) k-ε model turbulence model for the validation effort was used for turbulence modelling. A grid independence study was conducted for the three-dimensional model to reduce computational time. Preliminary results for 24 m/s air mass flow rate provided a close temperature profile inside the cavity relative to the experimental study. The investigation will be carried out on the effect of air mass flow rates and cavity aspect ratio on the combustion efficiency, pattern factor and static pressure drop in the combustor. A comparison study among pure methane, propane and hydrogen will be conducted to investigate their suitability for trapped vortex combustors and conclude their advantages and disadvantages as a fuel replacement. Therefore, the study will be one of the milestones to achieving 2050 zero carbon emissions or reducing carbon emissions.

Keywords: computational fluid dynamics, aerodynamic, aerospace, propulsion, trapped vortex combustor

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Authors: Rahul Paul, Peter Mctaggart, Luke Skinner

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Maintaining public safety and network reliability are the core objectives of all electricity distributors globally. For many electricity distributors, managing vegetation clearances from their above ground assets (poles and conductors) is the most important and costly risk mitigation control employed to meet these objectives. Light Detection And Ranging (LiDAR) is widely used by utilities as a cost-effective method to inspect their spatially-distributed assets at scale, often captured using high powered LiDAR scanners attached to fixed wing or rotary aircraft. The resulting 3D point cloud model is used by these utilities to perform engineering grade measurements that guide the prioritisation of vegetation cutting programs. Advances in computer vision and machine-learning approaches are increasingly applied to increase automation and reduce inspection costs and time; however, real-world LiDAR capture variables (e.g., aircraft speed and height) create complexity, noise, and missing data, reducing the effectiveness of these approaches. This paper proposes a method for identifying each conductor from LiDAR data via clustering methods that can precisely reconstruct conductors in complex real-world configurations in the presence of high levels of noise. It proposes 3D catenary models for individual clusters fitted to the captured LiDAR data points using a least square method. An iterative learning process is used to identify potential conductor models between pole pairs. The proposed method identifies the optimum parameters of the catenary function and then fits the LiDAR points to reconstruct the conductors.

Keywords: point cloud, LİDAR data, machine learning, computer vision, catenary curve, vegetation management, utility industry

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Authors: Levicatus Mugenyi, Joaniter Nankabirwa, Emmanuel Arinaitwe, John Rek, Niel Hens, Moses Kamya, Grant Dorsey

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Background: Indoor residual spraying (IRS) reduces vector densities and malaria transmission, however, the most effective spraying intervals for IRS have not been well established. We aim to estimate the optimal timing interval for IRS using a modeling approach. Methods: We use a generalized additive model to estimate the optimal timing interval for IRS using the predicted malaria incidence. The model is applied to post IRS cohort clinical data from children aged 0.5–10 years in selected households in Tororo, historically a high malaria transmission setting in Uganda. Six rounds of IRS were implemented in Tororo during the study period (3 rounds with bendiocarb: December 2014 to December 2015, and 3 rounds with actellic: June 2016 to July 2018). Results: Monthly incidence of malaria from October 2014 to February 2019 decreased from 3.25 to 0.0 per person-years in the children under 5 years, and 1.57 to 0.0 for 5-10 year-olds. The optimal time interval for IRS differed between bendiocarb and actellic and by IRS round. It was estimated to be 17 and 40 weeks after the first round of bendiocarb and actellic, respectively. After the third round of actellic, 36 weeks was estimated to be optimal. However, we could not estimate from the data the optimal time after the second and third rounds of bendiocarb and after the second round of actellic. Conclusion: We conclude that to sustain the effect of IRS in a high-medium transmission setting, the second rounds of bendiocarb need to be applied roughly 17 weeks and actellic 40 weeks after the first round, and the timing differs for subsequent rounds. The amount of rainfall did not influence the trend in malaria incidence after IRS, as well as the IRS timing intervals. Our results suggest that shorter intervals for the IRS application can be more effective compared to the current practice, which is about 24 weeks for bendiocarb and 48 weeks for actellic. However, when considering our findings, one should account for the cost and drug resistance associated with IRS. We also recommend that the timing and incidence should be monitored in the future to improve these estimates.

Keywords: incidence, indoor residual spraying, generalized additive model, malaria

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Authors: Anders Troedsson

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For us humans, risks are intimately linked to human vulnerabilities - where there is vulnerability, there is potentially insecurity, and risk. Reducing vulnerability through compensatory measures means increasing security and decreasing risk. The paper suggests that a meaningful way to approach the study of risks (including threats, assaults, crisis etc.), is to understand the vulnerabilities these external phenomena evoke in humans. As is argued, the basis of risk evaluation, as well as responses, is the more or less subjective perception by the individual person, or a group of persons, exposed to the external event or phenomena in question. This will be determined primarily by the vulnerability or vulnerabilities that the external factor are perceived to evoke. In this way, risk perception is primarily an inward dynamic, rather than an outward one. Therefore, a route towards an understanding of the perception of risks, is a closer scrutiny of the vulnerabilities which they can evoke, thereby approaching an understanding of what in the paper is called the essence of risk (including threat, assault etc.), or that which a certain perceived risk means to an individual or group of individuals. As a necessary basis for gauging the wide spectrum of potential risks and their meaning, the paper proposes a model of human vulnerabilities, drawing from i.a. a long tradition of needs theory. In order to account for the subjectivity factor, which mediates between the innate vulnerabilities on the one hand, and the event or phenomenon out there on the other hand, an ensuing ontological discussion about the timespace characteristics of risk/threat/assault as perceived by humans leads to the positing of two dimensions. These two dimensions are applied on the vulnerabilities, resulting in a modelling effort featuring four realms of vulnerabilities which are related to each other and together represent a dynamic whole. In approaching the problem of risk perception, the paper thus defines the relevant realms of vulnerabilities, depicting them as a dynamic whole. With reference to a substantial body of literature and a growing international policy trend since the 1990s, this model is put in the language of human security - a concept relevant not only for international security studies and policy, but also for other academic disciplines and spheres of human endeavor.

Keywords: human security, timespace, vulnerabilities, risk perception

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Authors: Baladitya Swaika, Rahul Khatry

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Computer Adaptive Tests (CATs) is one of the most efficient ways for testing the cognitive abilities of students. CATs are based on Item Response Theory (IRT) which is based on item selection and ability estimation using statistical methods of maximum information selection/selection from posterior and maximum-likelihood (ML)/maximum a posteriori (MAP) estimators respectively. This study aims at combining both classical and Bayesian approaches to IRT to create a dataset which is then fed to a neural network which automates the process of ability estimation and then comparing it to traditional CAT models designed using IRT. This study uses python as the base coding language, pymc for statistical modelling of the IRT and scikit-learn for neural network implementations. On creation of the model and on comparison, it is found that the Neural Network based model performs 7-10% worse than the IRT model for score estimations. Although performing poorly, compared to the IRT model, the neural network model can be beneficially used in back-ends for reducing time complexity as the IRT model would have to re-calculate the ability every-time it gets a request whereas the prediction from a neural network could be done in a single step for an existing trained Regressor. This study also proposes a new kind of framework whereby the neural network model could be used to incorporate feature sets, other than the normal IRT feature set and use a neural network’s capacity of learning unknown functions to give rise to better CAT models. Categorical features like test type, etc. could be learnt and incorporated in IRT functions with the help of techniques like logistic regression and can be used to learn functions and expressed as models which may not be trivial to be expressed via equations. This kind of a framework, when implemented would be highly advantageous in psychometrics and cognitive assessments. This study gives a brief overview as to how neural networks can be used in adaptive testing, not only by reducing time-complexity but also by being able to incorporate newer and better datasets which would eventually lead to higher quality testing.

Keywords: computer adaptive tests, item response theory, machine learning, neural networks

Procedia PDF Downloads 175

Authors: Said Benaissa, David Plets, Emmeric Tanghe, Jens Trogh, Luc Martens, Leen Vandaele, Annelies Van Nuffel, Frank A. M. Tuyttens, Bart Sonck, Wout Joseph

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The herd monitoring and managing - in particular the detection of ‘attention animals’ that require care, treatment or assistance is crucial for effective reproduction status, health, and overall well-being of dairy cows. In large sized farms, traditional methods based on direct observation or analysis of video recordings become labour-intensive and time-consuming. Thus, automatic monitoring systems using sensors have become increasingly important to continuously and accurately track the health status of dairy cows. Wireless sensor networks (WSNs) and internet-of-things (IoT) can be effectively used in health tracking of dairy cows to facilitate herd management and enhance the cow welfare. Since on-cow measuring devices are energy-constrained, a proper characterization of the off-body wireless channel between the on-cow sensor nodes and the back-end base station is required for a power-optimized deployment of these networks in barns. The aim of this study was to characterize the off-body wireless channel in indoor (barns) environment at 868 MHz using LoRa nodes. LoRa is an emerging wireless technology mainly targeted at WSNs and IoT networks. Both large scale fading (i.e., path loss) and temporal fading were investigated. The obtained path loss values as a function of the transmitter-receiver separation were well fitted by a lognormal path loss model. The path loss showed an additional increase of 4 dB when the wireless node was actually worn by the cow. The temporal fading due to movement of other cows was well described by Rician distributions with a K-factor of 8.5 dB. Based on this characterization, network planning and energy consumption optimization of the on-body wireless nodes could be performed, which enables the deployment of reliable dairy cow monitoring systems.

Keywords: channel, channel modelling, cow monitoring, dairy cows, health monitoring, IoT, LoRa, off-body propagation, PLF, propagation

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Authors: Nicholas Bayfield, Liam Bibo, Charley Budgeon, Robert Larbalestier, Tom Briffa

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Introduction: Stress hyperglycaemia is common following cardiac surgery. Its optimal management is uncertain and may differ by diabetic status. This study assesses the in-hospital glycaemic management of cardiac surgery patients and associated postoperative outcomes. Methods: A retrospective cohort analysis of all patients undergoing cardiac surgery at Fiona Stanley Hospital from February 2015 to May 2019 was undertaken. Management and outcomes of hyperglycaemia following cardiac surgery were assessed. Follow-up was assessed to 1 year postoperatively. Multivariate regression modelling was utilised. Results: 1050 non-diabetic patients and 689 diabetic patients were included. In the non-diabetic cohort, patients with mild (peak blood sugar level [BSL] < 14.3), transient stress hyperglycaemia managed without insulin were not at an increased risk of wound-related morbidity (P=0.899) or mortality at 1 year (P=0.483). Insulin management was associated with wound-related readmission to hospital (P=0.004) and superficial sternal wound infection (P=0.047). Prolonged or severe stress hyperglycaemia was predictive of hospital re-admission (P=0.050) but not morbidity or mortality (P=0.546). Diabetes mellitus was an independent risk factor 1-year mortality (OR; 1.972 [1.041–3.736], P=0.037), graft harvest site wound infection (OR; 1.810 [1.134–2.889], P=0.013) and wound-related readmission (OR; 1.866 [1.076–3.236], P=0.026). In diabetics, postoperative peak BSL > 13.9mmol/L was predictive of graft harvest site infections (OR; 3.528 [1.724-7.217], P=0.001) and wound-related readmission OR; 3.462 [1.540-7.783], P=0.003) regardless of modality of management. A peak BSL of 10.0-13.9 did not increase the risk of morbidity/mortality compared to a peak BSL of < 10.0 (P=0.557). Diabetics with a peak BSL of 13.9 or less did not have significantly increased morbidity/mortality outcomes compared to non-diabetics (P=0.418). Conclusion: In non-diabetic patients, transient mild stress hyperglycaemia following cardiac surgery does not uniformly require treatment. In diabetic patients, postoperative hyperglycaemia with peak BSL exceeding 13.9mmol/L was associated with wound-related morbidity and hospital readmission following cardiac surgery.

Keywords: cardiac surgery, pulmonary embolism, pulmonary embolectomy, cardiopulmonary bypass

Procedia PDF Downloads 162

Authors: Roengchai Tansuchat, Woraphon Yamaka, Paravee Maneejuk

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From the past recent, the global financial crisis, economic instability, and large fluctuation in agricultural commodity price have led to increased concerns about the volatility transmission among them. The problem is further exacerbated by commodities volatility caused by other commodity price fluctuations, hence the decision on hedging strategy has become both costly and useless. Thus, this paper is conducted to analysis the volatility spillover effect among major agriculture including corn, soybeans, wheat and rice, to help the commodity suppliers hedge their portfolios, and manage the risk and co-volatility of them. We provide a switching regime approach to analyzing the issue of volatility spillovers in different economic conditions, namely upturn and downturn economic. In particular, we investigate relationships and volatility transmissions between these commodities in different economic conditions. We purposed a Copula-based multivariate Markov Switching GARCH model with two regimes that depend on an economic conditions and perform simulation study to check the accuracy of our proposed model. In this study, the correlation term in the cross-hedge ratio is obtained from six copula families – two elliptical copulas (Gaussian and Student-t) and four Archimedean copulas (Clayton, Gumbel, Frank, and Joe). We use one-step maximum likelihood estimation techniques to estimate our models and compare the performance of these copula using Akaike information criterion (AIC) and Bayesian information criteria (BIC). In the application study of agriculture commodities, the weekly data used are conducted from 4 January 2005 to 1 September 2016, covering 612 observations. The empirical results indicate that the volatility spillover effects among cereal futures are different, as response of different economic condition. In addition, the results of hedge effectiveness will also suggest the optimal cross hedge strategies in different economic condition especially upturn and downturn economic.

Keywords: agricultural commodity futures, cereal, cross-hedge, spillover effect, switching regime approach

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Authors: Thi Thanh Nga Pham, Damien Philippon, Alexis Drogoul, Thi Thu Thuy Nguyen, Tien Cong Nguyen

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Mekong River Delta region of Vietnam is recognized as one of the most vulnerable to climate change due to flooding and seawater rise and therefore an increased burden of climate change-related diseases. Changes in temperature and precipitation are likely to alter the incidence and distribution of vector-borne diseases such as dengue fever. In this region, the peak of the dengue epidemic period is around July to September during the rainy season. It is believed that climate is an important factor for dengue transmission. This study aims to enhance the capacity of dengue prediction by the relationship of dengue incidences with climate and environmental variables for Mekong River Delta of Vietnam during 2005-2015. Mathematical models for vector-host infectious disease, including larva, mosquito, and human being were used to calculate the impacts of climate to the dengue transmission with incorporating geospatial data for model input. Monthly dengue incidence data were collected at provincial level. Precipitation data were extracted from satellite observations of GSMaP (Global Satellite Mapping of Precipitation), land surface temperature and land cover data were from MODIS. The value of seasonal reproduction number was estimated to evaluate the potential, severity and persistence of dengue infection, while the final infected number was derived to check the outbreak of dengue. The result shows that the dengue infection depends on the seasonal variation of climate variables with the peak during the rainy season and predicted dengue incidence follows well with this dynamic for the whole studied region. However, the highest outbreak of 2007 dengue was not captured by the model reflecting nonlinear dependences of transmission on climate. Other possible effects will be discussed to address the limitation of the model. This suggested the need of considering of both climate variables and another variability across temporal and spatial scales.

Keywords: infectious disease, dengue, geospatial data, climate

Procedia PDF Downloads 383

Authors: Soukat Kumar Das

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Rapid industrialization and increase in population has resulted in the scarcity of suitable ground conditions. It has driven the need of ground improvement by means of reinforcement with geosynthetics with the minimum possible settlement and with maximum possible safety. Prestressing the geosynthetics offers an economical yet safe method of gaining the goal. Commercially available software PLAXIS 3D has made the analysis of prestressed geosynthetics simpler with much practical simulations of the ground. Attempts have been made so far to analyse the effect of prestressing geosynthetics and the effect of interference of footing on Unreinforced (UR), Geogrid Reinforced (GR) and Prestressed Geogrid Reinforced (PGR) soil on the load bearing capacity and the settlement characteristics of prestressed geogrid reinforced soil using the numerical analysis by using the software PLAXIS 3D. The results of the numerical analysis have been validated and compared with those given in the referred paper. The results have been found to be in very good agreement with those of the actual field values with very small variation. The GR soil has been found to be improve the bearing pressure 240 % whereas the PGR soil improves it by almost 500 % for 1mm settlement. In fact, the PGR soil has enhanced the bearing pressure of the GR soil by almost 200 %. The settlement reduction has also been found to be very significant as for 100 kPa bearing pressure the settlement reduction of the PGR soil has been found to be about 88 % with respect to UR soil and it reduced to up to 67 % with respect to GR soil. The prestressing force has resulted in enhanced reinforcement mechanism, resulting in the increased bearing pressure. The deformation at the geogrid layer has been found to be 13.62 mm for GR soil whereas it decreased down to mere 3.5 mm for PGR soil which certainly ensures the effect of prestressing on the geogrid layer. The parameter Improvement factor or conventionally known as Bearing Capacity Ratio for different settlements and which depicts the improvement of the PGR with respect to UR and GR soil and the improvement of GR soil with respect to UR soil has been found to vary in the range of 1.66-2.40 in the present analysis for GR soil and was found to be vary between 3.58 and 5.12 for PGR soil with respect to UR soil. The effect of prestressing was also observed in case of two interfering square footings. The centre to centre distance between the two footings (SFD) was taken to be B, 1.5B, 2B, 2.5B and 3B where B is the width of the footing. It was found that for UR soil the improvement of the bearing pressure was up to 1.5B after which it remained almost same. But for GR soil the zone of influence rose up to 2B and for PGR it further went up to 2.5B. So the zone of interference for PGR soil has increased by 67% than Unreinforced (UR) soil and almost 25 % with respect to GR soil.

Keywords: bearing, geogrid, prestressed, reinforced

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Authors: Diana C. El Assal, Fatima Monteiro, Caroline May, Peter Barbuti, Silvia Bolognin, Averina Nicolae, Hulda Haraldsdottir, Lemmer R. P. El Assal, Swagatika Sahoo, Longfei Mao, Jens Schwamborn, Rejko Kruger, Ines Thiele, Kathrin Marcus, Ronan M. T. Fleming

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Degeneration of substantia nigra pars compacta dopaminergic neurons is one of the hallmarks of Parkinson's disease. These neurons have a highly complex axonal arborisation and a high energy demand, so any reduction in ATP synthesis could lead to an imbalance between supply and demand, thereby impeding normal neuronal bioenergetic requirements. Synaptic mitochondria exhibit increased vulnerability to dysfunction in Parkinson's disease. After biogenesis in and transport from the cell body, synaptic mitochondria become highly dependent upon oxidative phosphorylation. We applied a systems biochemistry approach to identify the metabolic pathways used by neuronal mitochondria for energy generation. The mitochondrial component of an existing manual reconstruction of human metabolism was extended with manual curation of the biochemical literature and specialised using omics data from Parkinson's disease patients and controls, to generate reconstructions of synaptic and somal mitochondrial metabolism. These reconstructions were converted into stoichiometrically- and fluxconsistent constraint-based computational models. These models predict that Parkinson's disease is accompanied by an increase in the rate of glycolysis and a decrease in the rate of oxidative phosphorylation within synaptic mitochondria. This is consistent with independent experimental reports of a compensatory switching of bioenergetic pathways in the putamen of post-mortem Parkinson's disease patients. Ongoing work, in the context of the SysMedPD project is aimed at computational prediction of mitochondrial drug targets to slow the progression of neurodegeneration in the subset of Parkinson's disease patients with overt mitochondrial dysfunction.

Keywords: bioenergetics, mitochondria, Parkinson's disease, systems biochemistry

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Authors: Sezer Kefeli, Sertaç Arslan

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In this paper, supercavitationphenomena, and parameters are explained, and hydrodynamic design approaches are investigated for supercavitating torpedoes. In addition, drag force calculation methods ofsupercavitatingvehicles are obtained. Basically, conventional heavyweight torpedoes reach up to ~50 knots by classic hydrodynamic techniques, on the other hand super cavitating torpedoes may reach up to ~200 knots, theoretically. However, in order to reachhigh speeds, hydrodynamic viscous forces have to be reduced or eliminated completely. This necessity is revived the supercavitation phenomena that is implemented to conventional torpedoes. Supercavitation is a type of cavitation, after all, it is more stable and continuous than other cavitation types. The general principle of supercavitation is to separate the underwater vehicle from water phase by surrounding the vehicle with cavitation bubbles. This situation allows the torpedo to operate at high speeds through the water being fully developed cavitation. Conventional torpedoes are entitled as supercavitating torpedoes when the torpedo moves in a cavity envelope due to cavitator in the nose section and solid fuel rocket engine in the rear section. There are two types of supercavitation phase, these are natural and artificial cavitation phases. In this study, natural cavitation is investigated on the disk cavitators based on numerical methods. Once the supercavitation characteristics and drag reduction of natural cavitationare studied on CFD platform, results are verified with the empirical equations. As supercavitation parameters cavitation number (), pressure distribution along axial axes, drag coefficient (C_?) and drag force (D), cavity wall velocity (U_?) and dimensionless cavity shape parameters, which are cavity length (L_?/d_?), cavity diameter(d_ₘ/d_?) and cavity fineness ratio (〖L_?/d〗_ₘ) are investigated and compared with empirical results. This paper has the characteristics of feasibility study to carry out numerical solutions of the supercavitation phenomena comparing with empirical equations.

Keywords: CFD, cavity envelope, high speed underwater vehicles, supercavitating flows, supercavitation, drag reduction, supercavitation parameters

Procedia PDF Downloads 173