Search results for: asset liability modelling

Authors: Michael Ayomoh, Adriaan Roux, Oyindamola Omotuyi

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This paper presents an efficient robot navigation model in a multi-target domain amidst static and dynamic workspace obstacles. The problem is that of developing an optimal algorithm to minimize the total travel time of a robot as it visits all target points within its task domain amidst unknown workspace obstacles and finally return to its initial position. In solving this problem, a classical algorithm was first developed to compute the optimal number of paths to be travelled by the robot amidst the network of paths. The principle of shortest distance between robot and targets was used to compute the target point visitation order amidst workspace obstacles. Algorithm premised on the standard polar coordinate system was developed to determine the length of obstacles encountered by the robot hence giving room for a geometrical estimation of the total surface area occupied by the obstacle especially when classified as a relevant obstacle i.e. obstacle that lies in between a robot and its potential visitation point. A stochastic model was developed and used to estimate the likelihood of a dynamic obstacle bumping into the robot’s navigation path and finally, the navigation/obstacle avoidance algorithm was hinged on the hybrid virtual force field (HVFF) method. Significant modelling constraints herein include the choice of navigation path to selected target points, the possible presence of static obstacles along a desired navigation path and the likelihood of encountering a dynamic obstacle along the robot’s path and the chances of it remaining at this position as a static obstacle hence resulting in a case of re-routing after routing. The proposed algorithm demonstrated a high potential for optimal solution in terms of efficiency and effectiveness.

Keywords: multi-target, mobile robot, optimal path, static obstacles, dynamic obstacles

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Authors: Rashi Rajput, Manisha Singh

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Escitalopram oxalate (ETP), an FDA approved antidepressant drug from the category of SSRI (selective serotonin reuptake inhibitor) and is used in treatment of general anxiety disorder (GAD), major depressive disorder (MDD).When taken orally, it is metabolized to S-demethylcitalopram (S-DCT) and S-didemethylcitalopram (S-DDCT) in the liver with the help of enzymes CYP2C19, CYP3A4 and CYP2D6. Hence, causing side effects such as dizziness, fast or irregular heartbeat, headache, nausea etc. Therefore, targeted and sustained drug delivery will be a helpful tool for increasing its efficacy and reducing side effects. The present study is designed for formulating mucoadhesive nanoparticle formulation for the same Escitalopram loaded polymeric nanoparticles were prepared by ionic gelation method and characterization of the optimised formulation was done by zeta average particle size (93.63nm), zeta potential (-1.89mV), TEM (range of 60nm to 115nm) analysis also confirms nanometric size range of the drug loaded nanoparticles along with polydispersibility index of 0.117. In this research, we have studied the in vitro drug release profile for ETP nanoparticles, through a semi permeable dialysis membrane. The three important characteristics affecting the drug release behaviour were – particle size, ionic strength and morphology of the optimised nanoparticles. The data showed that on increasing the particle size of the drug loaded nanoparticles, the initial burst was reduced which was comparatively higher in drug. Whereas, the formulation with 1mg/ml chitosan in 1.5mg/ml tripolyphosphate solution showed steady release over the entire period of drug release. Then this data was further validated through mathematical modelling to establish the mechanism of drug release kinetics, which showed a typical linear diffusion profile in optimised ETP loaded nanoparticles.

Keywords: ionic gelation, mucoadhesive nanoparticle, semi-permeable dialysis membrane, zeta potential

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Authors: Maryam Kheirollahpour, Mahmoud Danaee, Amir Faisal Merican, Asma Ahmad Shariff

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Background: The presence of nonlinearity among the risk factors of eating behavior causes a bias in the prediction models. The accuracy of estimation of eating behaviors risk factors in the primary prevention of obesity has been established. Objective: The aim of this study was to explore the potential of a hybrid model of structural equation modeling (SEM) and Artificial Neural Networks (ANN) to predict eating behaviors. Methods: The Partial Least Square-SEM (PLS-SEM) and a hybrid model (SEM-Artificial Neural Networks (SEM-ANN)) were applied to evaluate the factors affecting eating behavior patterns among university students. 340 university students participated in this study. The PLS-SEM analysis was used to check the effect of emotional eating scale (EES), body shape concern (BSC), and body appreciation scale (BAS) on different categories of eating behavior patterns (EBP). Then, the hybrid model was conducted using multilayer perceptron (MLP) with feedforward network topology. Moreover, Levenberg-Marquardt, which is a supervised learning model, was applied as a learning method for MLP training. The Tangent/sigmoid function was used for the input layer while the linear function applied for the output layer. The coefficient of determination (R²) and mean square error (MSE) was calculated. Results: It was proved that the hybrid model was superior to PLS-SEM methods. Using hybrid model, the optimal network happened at MPLP 3-17-8, while the R² of the model was increased by 27%, while, the MSE was decreased by 9.6%. Moreover, it was found that which one of these factors have significantly affected on healthy and unhealthy eating behavior patterns. The p-value was reported to be less than 0.01 for most of the paths. Conclusion/Importance: Thus, a hybrid approach could be suggested as a significant methodological contribution from a statistical standpoint, and it can be implemented as software to be able to predict models with the highest accuracy.

Keywords: hybrid model, structural equation modeling, artificial neural networks, eating behavior patterns

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Authors: Pintip Vajarothai, Saad Al-Jibouri, Johannes I. M. Halman

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Public investment projects are primarily aimed at achieving development strategies to increase national economies of scale and overall improvement in a country. However, experience shows that public projects, particularly in developing countries, struggle or fail to fulfill the immediate needs of local communities. In many cases, the reason for that is that projects are selected in a subjective manner and that a major part of the problem is related to the evaluation criteria and techniques used. The evaluation process is often based on a broad strategic economic effects rather than real benefits of projects to society or on the various needs from different levels (e.g. national, regional, local) and conditions (e.g. long-term and short-term requirements). In this paper, an extensive literature review of the types of criteria used in the past by various researchers in project evaluation and selection process is carried out and the effectiveness of such criteria and techniques is discussed. The paper proposes substitute social and project sustainability criteria to improve the conditions of local people and in particular the disadvantaged groups of the communities. Furthermore, it puts forward a way for modelling the interaction between the selected criteria and the achievement of the social goals of the affected community groups. The described work is part of developing a broader decision model for public investment project selection by integrating various aspects and techniques into a practical methodology. The paper uses Thailand as a case to review what and how the various evaluation techniques are currently used and how to improve the project evaluation and selection process related to social and sustainability issues in the country. The paper also uses an example to demonstrates how to test the feasibility of various criteria and how to model the interaction between projects and communities. The proposed model could be applied to other developing and developed countries in the project evaluation and selection process to improve its effectiveness in the long run.

Keywords: evaluation criteria, developing countries, public investment, project selection methodology

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Authors: Eric York, James Tadio, Silas Owusu Antwi

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Laundry wastewater contains a diverse range of chemical pollutants that can have detrimental effects on human health and the environment. In this study, simulation studies by Spyder Python software v 3.2 to assess the efficacy of biochar in removing PO₄³⁻ from wastewater were conducted. Through modeling and simulation, the mechanisms involved in the adsorption process of phosphate by biochar were studied by altering variables which is specific to the phosphate from common laundry phosphate detergents, such as the aqueous solubility, initial concentration, and temperature using the Dudinin Approach (DA). Results showed that the concentration equilibrate at near the highest concentrations for Sugar beet-120 mgL⁻¹, Tailing-85 mgL⁻¹, CaO- rich-50 mgL⁻¹, Eggshell and rice straw-48 mgL⁻¹, Undaria Pinnatifida Roots-190 mgL⁻¹, Ca-Alginate Granular Beads -240 mgL⁻¹, Laminaria Japonica Powder -900 mgL⁻¹, Pinesaw dust-57 mgL⁻¹, Ricehull-190 mgL⁻¹, sesame straw- 470 mgL⁻¹, Sugar Bagasse-380 mgL⁻¹, Miscanthus Giganteus-240 mgL⁻¹, Wood Bc-130 mgL⁻¹, Pine-25 mgL⁻¹, Sawdust-6.8 mgL⁻¹, Sewage Sludge-, Rice husk-12 mgL⁻¹, Corncob-117 mgL⁻¹, Maize straw- 1800 mgL⁻¹ while Peanut -Eucalyptus polybractea-, Crawfish equilibrated at near concentration. CO₂ activated Thalia, sewage sludge biochar, Broussonetia Papyrifera Leaves equilibrated just at the lower concentration. Only Soyer bean Stover exhibited a sharp rise and fall peak in mid-concentration at 2 mgL⁻¹ volume. The modelling results were consistent with experimental findings from the literature, ensuring the accuracy, repeatability, and reliability of the simulation study. The simulation study provided insights into adsorption for PO₄³⁻ from wastewater by biochar using concentration per volume that can be adsorbed ideally under the given conditions. Studies showed that applying the principle experimentally in real wastewater with all its complexity is warranted and not far-fetched.

Keywords: simulation studies, phosphate removal, biochar, adsorption, wastewater treatment

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Authors: Yaxin Bi, Peter Nicholl

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The rapid advancement of Information and communication technologies (ICT) is extremely influencing every aspect of Higher Education. It has transformed traditional teaching, learning, assessment and feedback into a new era of Digital Education. This also introduces many challenges in capturing and understanding student engagement with their studies in Higher Education. The School of Computing at Ulster University has developed a Feedback And Notification (FAN) Online tool that has been used to send students links to personalized feedback on their submitted assessments and record students’ frequency of review of the shared feedback as well as the speed of collection. The feedback that the students initially receive is via a personal email directing them through to the feedback via a URL link that maps to the feedback created by the academic marker. This feedback is typically a Word or PDF report including comments and the final mark for the work submitted approximately three weeks before. When the student clicks on the link, the student’s personal feedback is viewable in the browser and they can view the contents. The FAN tool provides the academic marker with a report that includes when and how often a student viewed the feedback via the link. This paper presents an investigation into student engagement through analyzing the interaction timestamps and frequency of review by the student. We have proposed an approach to modeling interaction timestamps and use sentiment classification techniques to analyze the data collected over the last five years for a set of modules. The data studied is across a number of final years and second-year modules in the School of Computing. The paper presents the details of quantitative analysis methods and describes further their interactions with the feedback overtime on each module studied. We have projected the students into different groups of engagement based on sentiment analysis results and then provide a suggestion of early targeted intervention for the set of students seen to be under-performing via our proposed model.

Keywords: feedback, engagement, interaction modelling, sentiment analysis

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Authors: Allison Tucker, Carolyn Clarke, Erin Keith

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Introduction: In education, the determination to uncover privileged practices requires critical reflection to be placed at the center of both pre-service and in-service teacher education. Confronting deficit thinking about children’s abilities and shifting to holding an image of the child as capable and competent is necessary for teachers to engage in responsive pedagogy that meets children where they are in their learning and builds on strengths. This paper explores the ways in which early elementary teachers' perceptions of the assets of children might shift through the pedagogical use of video clubs. Video club is a pedagogical practice whereby teachers record and view short videos with the intended purpose of deepening their practices. The use of video club as a learning tool has been an extensively documented practice. In this study, a video club is used to watch short recordings of playing children to identify the assets of their students. Methodology: The study on which this paper is based asks the question: What are the ways in which teachers’ image of the child and teaching practices evolve through the use of video club focused on the strengths of children demonstrated during play? Using critical reflection, it aims to identify and describe participants’ experiences of examining their personally held image of the child through the pedagogical tool video club, and how that image influences their practices, specifically in implementing play pedagogy. Teachers enrolled in a graduate-level play pedagogy course record and watch videos of their own students as a means to notice and reflect on the learning that happens during play. Using a co-constructed viewing protocol, teachers identify student strengths and consider their pedagogical responses. Video club provides a framework for teachers to critically reflect in action, return to the video to rewatch the children or themselves and discuss their noticings with colleagues. Critical reflection occurs when there is focused attention on identifying the ways in which actions perpetuate or challenge issues of inherent power in education. When the image of the child held by the teacher is from a deficit position and is influenced by hegemonic dimensions of practice, critical reflection is essential in naming and addressing power imbalances, biases, and practices that are harmful to children and become barriers to their thriving. The data is comprised of teacher reflections, analyzed using phenomenology. Phenomenology seeks to understand and appreciate how individuals make sense of their experiences. Teacher reflections are individually read, and researchers determine pools of meaning. Categories are identified by each researcher, after which commonalities are named through a recursive process of returning to the data until no more themes emerge or saturation is reached. Findings: The final analysis and interpretation of the data are forthcoming. However, emergent analysis of the data collected using teacher reflections reveals the ways in which the use of video club grew teachers’ awareness of their image of the child. It shows video club as a promising pedagogical tool when used with in-service teachers to prompt opportunities for play and to challenge deficit thinking about children and their abilities to thrive in learning.

Keywords: asset-based teaching, critical reflection, image of the child, video club

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Authors: Khanyisile Mnguni, Muthukrishnavellaisamy Kumarasamy, Jeff C. Smithers

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Umgeni Water is a water board that supplies most parts of KwaZulu Natal with bulk portable water. Currently, Umgeni Water is running its distribution system based on required reservoir levels and demands and does not consider the energy cost at different times of the day, number of pump switches, and background leakages. Including these constraints can reduce operational cost, energy usage, leakages, and increase performance. Optimising pump schedules can reduce energy usage and costs while adhering to hydraulic and operational constraints. Umgeni Water has installed an online hydraulic software, WaterNet Advisor, that allows running different operational scenarios prior to implementation in order to optimise the distribution system. This study will investigate operation scenarios using optimisation techniques and WaterNet Advisor for a local water distribution system. Based on studies reported in the literature, introducing pump scheduling optimisation can reduce energy usage by approximately 30% without any change in infrastructure. Including tariff structures in an optimisation problem can reduce pumping costs by 15%, while including leakages decreases cost by 10%, and pressure drop in the system can be up to 12 m. Genetical optimisation algorithms are widely used due to their ability to solve nonlinear, non-convex, and mixed-integer problems. Other methods such as branch and bound linear programming have also been successfully used. A suitable optimisation method will be chosen based on its efficiency. The objective of the study is to reduce energy usage, operational cost, and leakages, and the feasibility of optimal solution will be checked using the Waternet Advisor. This study will provide an overview of the optimisation of hydraulic networks and progress made to date in multi-objective optimisation for a selected sub-system operated by Umgeni Water.

Keywords: energy usage, pump scheduling, WaterNet Advisor, leakages

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Authors: Y. Smirlis, G. Koronakos, S. Plitsos

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Shipbrokers assist the ship companies in chartering or selling and buying vessels, acting as intermediates between them and the market. They facilitate deals, providing their expertise, negotiating skills, and knowledge about ship market bargains. Their role is very important as it affects the profitability and market position of a shipping company. Due to their significant contribution, the shipping companies have to employ systematic procedures to evaluate the shipbrokers’ services in order to select the best and, consequently, to achieve the best deals. Towards this, in this paper, we consider shipbrokers as financial service providers, and we formulate the problem of evaluating and selecting shipbrokers’ services as a multi-criteria decision making (MCDM) procedure. The proposed methodology comprises a first normalization step to adjust different scales and orientations of the criteria and a second step that includes the mathematical model to evaluate the performance of the shipbrokers’ services involved in the assessment. The criteria along which the shipbrokers are assessed may refer to their size and reputation, the potential efficiency of the services, the terms and conditions imposed, the expenses (e.g., commission – brokerage), the expected time to accomplish a chartering or selling/buying task, etc. and according to our modelling approach these criteria may be assigned different importance. The mathematical programming model performs a comparative assessment and estimates for the shipbrokers involved in the evaluation, a relative score that ranks the shipbrokers in terms of their potential performance. To illustrate the proposed methodology, we present a case study in which a shipping company evaluates and selects the most suitable among a number of sale and purchase (S&P) brokers. Acknowledgment: This study is supported by the OptiShip project, implemented within the framework of the National Recovery Plan and Resilience “Greece 2.0” and funded by the European Union – NextGenerationEU programme.

Keywords: shipbrokers, multi-criteria decision making, mathematical programming, service-provider selection

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Authors: Chloé Kernaléguen, Laura Kundun, Tessie Lery, Ryan Laleg, Zhangyun Tan

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This study explores global disparities in respiratory syncytial virus (RSV) bronchiolitis incidence among children aged 0-2 years, focusing on the human development index (HDI) as a key determinant. RSV bronchiolitis poses a significant health risk to young children, influenced by factors, including socio-economic conditions captured by the HDI. Through a comprehensive systematic review and dataset selection (Switzerland, Brazil, United States of America), we formulated an HDI-SEIRS numerical model within the SEIRS framework. Results show variations in RSV bronchiolitis dynamics across countries, emphasizing the influence of HDI. Modelling reveals a correlation between higher HDI and increased bronchiolitis spread, notably in the USA and Switzerland. The ratios HDIcountry over HDImax strengthen this association, while climate disparities contribute to variations, especially in colder climates like the USA and Switzerland. The study raises the hypothesis of an indirect link between higher HDI and more frequent bronchiolitis, underlining the need for nuanced understanding. Factors like improved healthcare access, population density, mobility, and social behaviors in higher HDI countries might contribute to unexpected trends. Limitations include dataset quality and restricted RSV bronchiolitis data. Future research should encompass diverse HDI datasets to refine HDI's role in bronchiolitis dynamics. In conclusion, HDI-SEIRS models offer insights into factors influencing RSV bronchiolitis spread. While HDI is a significant indicator, its impact is indirect, necessitating a holistic approach to effective public health policies. This analysis sets the stage for further investigations into multifaceted interactions shaping bronchiolitis dynamics in diverse socio-economic contexts.

Keywords: bronchiolitis propagation, HDI influence, respiratory syncytial virus, SEIRS model

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Authors: Enes Gunaltili, Burak Dam

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The airplane history started with the Wright brothers' aircraft and improved day by day. With the help of this advancements, big aircrafts replace with small and unmanned air vehicles, so in this study we design this type of air vehicles. First of all, aircrafts mainly divided into two main parts in our day as a rotary and fixed wing aircrafts. The fixed wing aircraft generally use for transport, cargo, military and etc. The rotary wing aircrafts use for same area but there are some superiorities from each other. The rotary wing aircraft can take off vertically from the ground, and it can use restricted area. On the other hand, rotary wing aircrafts generally can fly lower range than fixed wing aircraft. There are one kind of aircraft consist of this two types specifications. It is named as VTOL (vertical take-off and landing) type aircraft. VTOLs are able to takeoff and land vertically and fly horizontally. The VTOL aircrafts generally can fly higher range from the rotary wings but can fly lower range from the fixed wing aircraft but it gives beneficial range between them. There are many other advantages of VTOL aircraft from the rotary and fixed wing aircraft. Because of that, VTOLs began to use for generally military, cargo, search, rescue and mapping areas. Within this framework, this study answers the question that how can we design VTOL as a small unmanned aircraft systems for search and rescue application for benefiting the advantages of fixed wing and rotary wing aircrafts by eliminating the disadvantages of them. To answer that question and design VTOL aircraft, multidisciplinary design optimizations (MDO), some theoretical terminologies, formulations, simulations and modelling systems based on CFD (Computational Fluid Dynamics) is used in same time as design methodology to determine design parameters and steps. As a conclusion, based on tests and simulations depend on design steps, suggestions on how the VTOL aircraft designed and advantages, disadvantages, and observations for design parameters are listed, then VTOL is designed and presented with the design parameters, advantages, and usage areas.

Keywords: airplane, rotary, fixed, VTOL, CFD

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Authors: Rui Li, Min Wen, Kim Bang Salling

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For the modern railways, maintenance is critical for ensuring safety, train punctuality and overall capacity utilization. The cost of railway maintenance in Europe is high, on average between 30,000 – 100,000 Euros per kilometer per year. In order to reduce such maintenance expenditures, this paper presents a mixed 0-1 linear mathematical model designed to optimize the predictive railway tamping activities for ballast track in the planning horizon of three to four years. The objective function is to minimize the tamping machine actual costs. The approach of the research is using the simple dynamic model for modelling condition-based tamping process and the solution method for finding optimal condition-based tamping schedule. Seven technical and practical aspects are taken into account to schedule tamping: (1) track degradation of the standard deviation of the longitudinal level over time; (2) track geometrical alignment; (3) track quality thresholds based on the train speed limits; (4) the dependency of the track quality recovery on the track quality after tamping operation; (5) Tamping machine operation practices (6) tamping budgets and (7) differentiating the open track from the station sections. A Danish railway track between Odense and Fredericia with 42.6 km of length is applied for a time period of three and four years in the proposed maintenance model. The generated tamping schedule is reasonable and robust. Based on the result from the Danish railway corridor, the total costs can be reduced significantly (50%) than the previous model which is based on optimizing the number of tamping. The different maintenance strategies have been discussed in the paper. The analysis from the results obtained from the model also shows a longer period of predictive tamping planning has more optimal scheduling of maintenance actions than continuous short term preventive maintenance, namely yearly condition-based planning.

Keywords: integer programming, railway tamping, predictive maintenance model, preventive condition-based maintenance

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Authors: Suresh Hettiarachchi, Conrad Wasko, Ashish Sharma

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The ever changing and expanding urban landscape increases the stress on urban systems to support and maintain safe and functional living spaces. Flooding presents one of the more serious threats to this safety, putting a larger number of people in harm’s way in congested urban settings. Climate change is adding to this stress by creating a dichotomy in the urban flood response. On the one hand, climate change is causing storms to intensify, resulting in more destructive, rarer floods, while on the other hand, longer dry periods are decreasing the severity of more frequent, less intense floods. This variability is creating a need to be more agile and innovative in how we design for and manage urban flooding. Here, we argue that to cope with this challenge climate change brings, we need to move towards urban flood management through resilience rather than flood prevention. We also argue that dealing with the larger variation in flood response to climate change means that we need to look at flooding from all aspects rather than the single-dimensional focus of flood depths and extents. In essence, we need to rethink how we manage flooding in the urban space. This change in our thought process and approach to flood management requires a practical way to assess and quantify resilience that is built into the urban landscape so that informed decision-making can support the required changes in planning and infrastructure design. Towards that end, we propose a Simple Urban Flood Resilience Index (SUFRI) based on a robust definition of resilience as a tool to assess flood resilience. The application of a simple resilience index such as the SUFRI can provide a practical tool that considers urban flood management in a multi-dimensional way and can present solutions that were not previously considered. When such an index is grounded on a clear and relevant definition of resilience, it can be a reliable and defensible way to assess and assist the process of adapting to the increasing challenges in urban flood management with climate change.

Keywords: urban flood resilience, climate change, flood management, flood modelling

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Authors: Jubee Varghese, Pouria Hafiz

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Increased use of lightweight concrete in the construction industry is mainly due to its reduction in the weight of the structural elements, which in turn reduces the cost of production, transportation, and the overall project cost. However, the structural application of these lightweight concrete structures is limited due to its reduced density. Hence, further investigations are in progress to study the effect of fiber inclusion in improving the mechanical properties of lightweight concrete. Incorporating structural steel fibers, in general, enhances the performance of concrete and increases its durability by minimizing its potential to cracking and providing crack arresting mechanism. In this research, Geometric and Materially Non-linear Analysis (GMNA) was conducted for Finite Element Modelling using a software known as ABAQUS, to investigate the structural behavior of lightweight concrete with and without the addition of steel fibers and shear reinforcement. 21 finite element models of beams were created to study the effect of steel fibers based on three main parameters; fiber volume fraction (Vf = 0, 0.5 and 0.75%), shear span to depth ratio (a/d of 2, 3 and 4) and ratio of area of shear stirrups to spacing (As/s of 0.7, 1 and 1.6). The models created were validated with the previous experiment conducted by H.K. Kang et al. in 2011. It was seen that the lightweight fiber reinforcement can replace the use of fiber reinforced normal weight concrete as structural elements. The effect of an increase in steel fiber volume fraction is dominant for beams with higher shear span to depth ratio than for lower ratios. The effect of stirrups in the presence of fibers was very negligible; however; it provided extra confinement to the cracks by reducing the crack propagation and extra shear resistance than when compared to beams with no stirrups.

Keywords: ABAQUS, beams, fiber-reinforced concrete, finite element, light weight, shear span-depth ratio, steel fibers, steel-fiber volume fraction

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Authors: Musa Akdere, Gunnar Seide, Thomas Gries

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Carbon fibres are fibrous materials with a carbon atom amount of more than 90%. They combine excellent mechanicals properties with a very low density. Thus carbon fibre reinforced plastics (CFRP) are very often used in lightweight design and construction. The precursor material is usually polyacrylonitrile (PAN) based and wet-spun. During the production of carbon fibre, the precursor has to be stabilized thermally to withstand the high temperatures of up to 1500 °C which occur during carbonization. Even though carbon fibre has been used since the late 1970s in aerospace application, there is still no general method available to find the optimal production parameters and the trial-and-error approach is most often the only resolution. To have a much better insight into the process the chemical reactions during stabilization have to be analyzed particularly. Therefore, a model of the chemical reactions (cyclization, dehydration, and oxidation) based on the research of Dunham and Edie has been developed. With the presented model, it is possible to perform a complete simulation of the fibre undergoing all zones of stabilization. The fiber bundle is modeled as several circular fibers with a layer of air in-between. Two thermal mechanisms are considered to be the most important: the exothermic reactions inside the fiber and the convective heat transfer between the fiber and the air. The exothermic reactions inside the fibers are modeled as a heat source. Differential scanning calorimetry measurements have been performed to estimate the amount of heat of the reactions. To shorten the required time of a simulation, the number of fibers is decreased by similitude theory. Experiments were conducted to validate the simulation results of the fibre temperature during stabilization. The experiments for the validation were conducted on a pilot scale stabilization oven. To measure the fibre bundle temperature, a new measuring method is developed. The comparison of the results shows that the developed simulation model gives good approximations for the temperature profile of the fibre bundle during the stabilization process.

Keywords: carbon fibre, coupled simulation, exothermic reactions, fibre-air-interface

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Authors: S. Mondal, L. M. Olsen-Kettle, L. Gross

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Fracture propagation and damage evolution are extremely important for many industrial applications including mining industry, composite materials, earthquake simulations, hydraulic fracturing. The influence of pre-existing flaws and rock heterogeneity on the processes and mechanisms of rock fracture has important ramifications in many mining and reservoir engineering applications. We simulate the damage evolution and fracture propagation in an isotropic sandstone specimen containing a pre-existing 3-D surface flaw in different configurations under uniaxial compression. We apply a damage model based on the unified strength theory and solve the solid deformation and damage evolution equations using the Finite Element Method (FEM) with tetrahedron elements on unstructured meshes through the simulation software, eScript. Unstructured meshes provide higher geometrical flexibility and allow a more accurate way to model the varying flaw depth, angle, and length through locally adapted FEM meshes. The heterogeneity of rock is considered by initializing material properties using a Weibull distribution sampled over a cubic grid. In our model, we introduce a length scale related to the rock heterogeneity which is independent of the mesh size. We investigate the effect of parameters including the heterogeneity of the elastic moduli and geometry of the single flaw in the stress strain response. The generation of three typical surface cracking patterns, called wing cracks, anti-wing cracks and far-field cracks were identified, and these depend on the geometry of the pre-existing surface flaw. This model results help to advance our understanding of fracture and damage growth in heterogeneous rock with the aim to develop fracture simulators for different industry applications.

Keywords: finite element method, heterogeneity, isotropic damage, uniaxial compression

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Authors: Ameer A. Jebur, William Atherton, Rafid M. Alkhaddar, Edward Loffill

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Superstructures like offshore platforms, tall buildings, transition towers, skyscrapers and bridges are normally designed to resist compression, uplift and lateral forces from wind waves, negative skin friction, ship impact and other applied loads. Better understanding and the precise simulation of the response of batter piles under the action of independent uplift loads is a vital topic and an area of active research in the field of geotechnical engineering. This paper investigates the use of finite element code (FEC) to examine the behaviour of model batter piles penetrated in dense sand, subjected to pull-out pressure by means of numerical modelling. The concept of the Winkler Model (beam on elastic foundation) has been used in which the interaction between the pile embedded depth and adjacent soil in the bearing zone is simulated by nonlinear p-y curves. The analysis was conducted on different pile slenderness ratios (lc⁄d) ranging from 7.5, 15.22 and 30 respectively. In addition, the optimum batter angle for a model steel pile penetrated in dense sand has been chosen to be 20° as this is the best angle for this simulation as demonstrated by other researcher published in literature. In this numerical analysis, the soil response is idealized as elasto-plastic and the model piles are described as elastic materials for the purpose of simulation. The results revealed that the applied loads affect the pullout pile capacity as well as the lateral pile response for dense sand together with varying shear strength parameters linked to the pile critical depth. Furthermore, the pile pull-out capacity increases with increasing the pile aspect ratios.

Keywords: slenderness ratio, soil-pile interaction, winkler model (beam on elastic foundation), pull-out capacity

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Authors: Yunhui Sun, Qingquan Liu, Xiaoliang Wang

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Dense granular flows widely exist in geological flows such as debris flow, landslide, or sheet flow, where both the interparticle and solid-liquid interactions are important to modify the flow. So, a two-phase approach with both phases correctly modelled is important for a better investigation of the saturated granular flows. However, a proper closure model covering a wide range of flowing states for the solid phase is still lacking. This study first employs a chute flow experiment based on the refractive index matching method, which makes it possible to obtain internal flow information such as velocity, shear rate, granular fluctuation, and volume fraction. The granular stress is obtained based on a steady assumption. The kinetic theory is found to describe the stress dependence on the flow state well. More importantly, the granular rheology is found to be frictionally dominated under weak shear and collisionally dominated under strong shear. The results presented thus provide direct experimental evidence on a possible frictional-collisional closure model for the granular phase. The data indicates that both frictional stresses exist over a wide range of the volume fraction, though traditional theory believes it vanishes below a critical volume fraction. Based on the findings, a two-phase model is used to simulate the chute flow. Both phases are modelled as continuum media, and the inter-phase interactions, such as drag force and pressure gradient force, are considered. The frictional-collisional model is used for the closure of the solid phase stress. The profiles of the kinematic properties agree well with the experiments. This model is further used to simulate immersed granular collapse, which is unsteady in nature, to study the applicability of this model, which is derived from steady flow.

Keywords: closure model, collision, friction, granular flow, two-phase model

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Authors: Jikhil Joseph, Satish Kumar S R.

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Cold-formed steel frames are preferable for framed constructions due to its low seismic weights and results into low seismic forces, but on the contrary, significant lateral deflections are expected under seismic/wind loading. The various factors affecting the lateral stiffness of steel frames are the stiffness of connections, beams and columns. So, by increasing the stiffness of beam, column and making the connections rigid will enhance the lateral stiffness. The present study focused on Structural elements made of rectangular hollow sections and fastened with screwed in-plane moment connections for the building frames. The self-drilling screws can be easily drilled on either side of the connection area with the help of gusset plates. The strength of screwed connections can be made 1.2 times the connecting elements. However, achieving high stiffness in connections is also a challenging job. Hence in addition to beam and column stiffness’s the connection stiffness are also going to be a governing parameter in the lateral deflections of the frames. SAP 2000 Non-linear static analysis has been planned to study the seismic behavior of steel frames. The SAP model will be consisting of nonlinear spring model for the connection to account the semi-rigid connections and the nonlinear hinges will be assigned for beam and column sections according to FEMA 273 guidelines. The reliable spring and hinge parameters will be assigned based on an experimental and analytical database. The non-linear static analysis is mainly focused on the identification of various hinge formations and the estimation of lateral deflection and these will contribute as an inputs for the direct displacement-based Seismic design. The research output from this study are the modelling techniques and suitable design guidelines for the performance-based seismic design of cold-formed steel frames.

Keywords: buckling, cold formed steel, nonlinear static analysis, screwed connections

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Authors: Guillaume Craveur

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This study shows the opportunity to use numerical tools dedicated to Fire Safety Engineering for the Rolling Stock. Indeed, some lawful requirements can now be demonstrated by using numerical tools. The first part of this study presents the use of modelling evacuation tool to satisfy the criteria of evacuation time for the rolling stock. The buildingEXODUS software is used to model and simulate the evacuation of rolling stock. Firstly, in order to demonstrate the reliability of this tool to calculate the complete evacuation time, a comparative study was achieved between a real test and simulations done with buildingEXODUS. Multiple simulations are performed to capture the stochastic variations in egress times. Then, a new study is done to calculate the complete evacuation time of a train with the same geometry but with a different interior architecture. The second part of this study shows some applications of Computational Fluid Dynamics. This work presents the approach of a multi scales validation of numerical simulations of standardized tests with Fire Dynamics Simulations software developed by the National Institute of Standards and Technology (NIST). This work highlights in first the cone calorimeter test, described in the standard ISO 5660, in order to characterize the fire reaction of materials. The aim of this process is to readjust measurement results from the cone calorimeter test in order to create a data set usable at the seat scale. In the second step, the modelisation concerns the fire seat test described in the standard EN 45545-2. The data set obtained thanks to the validation of the cone calorimeter test was set up in the fire seat test. To conclude with the third step, after controlled the data obtained for the seat from the cone calorimeter test, a larger scale simulation with a real part of train is achieved.

Keywords: fire safety engineering, numerical tools, rolling stock, multi-scales validation

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Authors: Hanee Ryu

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The former president Lee Myung-bak's administration of Korea presented “green growth” as a catchphrase from 2008. He declared “low-carbon, green growth” the nation's vision for the next decade according to United Nation Framework on Climate Change. The government designed omnidirectional policy for low-carbon and green growth with concentrating all effort of departments. The structural change was expected because this slogan is the identity of the government, which is strongly driven with the whole department. After his administration ends, the purpose of this paper is to quantify the policy effect and to compare with the value of the other OECD countries. The major target values under direct policy objectives were suggested, but it could not capture the entire landscape on which the policy makes changes. This paper figures out the policy impacts through comparing the value of ex-ante between the one of ex-post. Furthermore, each index level of Korea’s low-carbon and green growth comparing with the value of the other OECD countries. To measure the policy effect, indicators international organizations have developed are considered. Environmental Sustainable Index (ESI) and Environmental Performance Index (EPI) have been developed by Yale University’s Center for Environmental Law and Policy and Columbia University’s Center for International Earth Science Information Network in collaboration with the World Economic Forum and Joint Research Center of European Commission. It has been widely used to assess the level of natural resource endowments, pollution level, environmental management efforts and society’s capacity to improve its environmental performance over time. Recently OCED publish the Green Growth Indicator for monitoring progress towards green growth based on internationally comparable data. They build up the conceptual framework and select indicators according to well specified criteria: economic activities, natural asset base, environmental dimension of quality of life and economic opportunities and policy response. It considers the socio-economic context and reflects the characteristic of growth. Some selected indicators are used for measuring the level of changes the green growth policies have induced in this paper. As results, the CO2 productivity and energy productivity show trends of declination. It means that policy intended industry structure shift for achieving carbon emission target affects weakly in the short-term. Increasing green technologies patents might result from the investment of previous period. The increasing of official development aids which can be immediately embarked by political decision with no time lag present only in 2008-2009. It means international collaboration and investment to developing countries via ODA has not succeeded since the initial stage of his administration. The green growth framework makes the public expect structural change, but it shows sporadic effect. It needs organization to manage it in terms of the long-range perspectives. Energy, climate change and green growth are not the issue to be handled in the one period of the administration. The policy mechanism to transfer cost problem to value creation should be developed consistently.

Keywords: comparing ex-ante between ex-post indicator, green growth indicator, implication for green growth policy, measuring policy effect

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Authors: Sana Fatima, Paul Sadler, Jon Cooper, David Mendel, Ayesha Jameel

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Background: Neurodiversity refers to intrinsic differences between human minds and encompasses dyspraxia, dyslexia, attention deficit hyperactivity disorder, dyscalculia, autism spectrum disorder, and Tourette syndrome. There is increasing recognition of neurodiversity in relation to disability/diversity in medical education and the associated impact on training, career progression, and personal and professional wellbeing. In addition, documented and anecdotal evidence suggests that medical educators and training providers in all four nations (UK) are increasingly concerned about understanding neurodiversity and identifying and providing support for neurodivergent trainees. Summary of Work: A national Neurodiversity Task and Finish group were established to survey Health Education England local office Professional Support teams about insights into infrastructure, training for educators, triggers for assessment, resources, and intervention protocols. This group drew from educational leadership, professional and personal neurodiverse expertise, occupational medicine, employer human resource, and trainees. An online, exploratory survey was conducted to gather insights from supervisors and trainers across England using the Professional Support Units' platform. Summary of Results: This survey highlighted marked heterogeneity in the identification, assessment, and approaches to support and management of neurodivergent trainees and highlighted a 'deficit' approach to neurodiversity. It also demonstrated a paucity of educational and protocol resources for educators and supervisors in supporting neurodivergent trainees. Discussions and Conclusions: In phase one, we focused on faculty development. An educational repository for all supervising trainees using a thematic approach was formalised. This was guided by our survey findings specific for neurodiversity and took a triple 'A' approach: awareness, assessment, and action. This is further supported by video material incorporating stories in training as well as mobile workshops for trainers for more immersive learning. The subtle theme from both the survey and Task and finish group suggested a move away from deficit-focused methods toward a positive holistic, interdisciplinary approach within a biopsychosocial framework. Contributions: 1. Faculty Knowledge and basic understanding of neurodiversity are key to supporting trainees with known or underlying Neurodiverse conditions. This is further complicated by challenges around non-disclosure, varied presentations, stigma, and intersectionality. 2. There is national (and international) inconsistency in the approach to how trainees are managed once a neurodiverse condition is suspected or diagnosed. 3. A carefully constituted and focussed Task and Finish group can rapidly identify national inconsistencies in neurodiversity and implement rapid educational interventions. 4. Nuanced findings from surveys and discussion can reframe the approach to neurodiversity; from a medical model to a more comprehensive, asset-based, biopsychosocial model of support, fostering a cultural shift, accepting 'diversity' in all its manifestations, visible and hidden.

Keywords: neurodiversity, professional support, human considerations, workplace wellbeing

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Authors: Mahbod Seyednia, Shidvash Vakilipour, Mehran Masdari

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Computations for two-dimensional flow past a stationary and harmonically pitching wind turbine airfoil at a moderate value of Reynolds number (400000) are carried out by progressively increasing the angle of attack for stationary airfoil and at fixed pitching frequencies for rotary one. The incompressible Navier-Stokes equations in conjunction with Unsteady Reynolds Average Navier-Stokes (URANS) equations for turbulence modeling are solved by OpenFOAM package to investigate the aerodynamic phenomena occurred at stationary and pitching conditions on a NACA 6-series wind turbine airfoil. The aim of this study is to enhance the accuracy of numerical simulation in predicting the aerodynamic behavior of an oscillating airfoil in OpenFOAM. Hence, for turbulence modelling, k-ω-SST with low-Reynolds correction is employed to capture the unsteady phenomena occurred in stationary and oscillating motion of the airfoil. Using aerodynamic and pressure coefficients along with flow patterns, the unsteady aerodynamics at pre-, near-, and post-static stall regions are analyzed in harmonically pitching airfoil, and the results are validated with the corresponding experimental data possessed by the authors. The results indicate that implementing the mentioned turbulence model leads to accurate prediction of the angle of static stall for stationary airfoil and flow separation, dynamic stall phenomenon, and reattachment of the flow on the surface of airfoil for pitching one. Due to the geometry of the studied 6-series airfoil, the vortex on the upper surface of the airfoil during upstrokes is formed at the trailing edge. Therefore, the pattern flow obtained by our numerical simulations represents the formation and change of the trailing-edge vortex at near- and post-stall regions where this process determines the dynamic stall phenomenon.

Keywords: CFD, moderate Reynolds number, OpenFOAM, pitching oscillation, unsteady aerodynamics, wind turbine

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Authors: Danica Maljkovic, Igor Balen, Bojana Dalbelo Basic

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Following the regulation of EU Directive on Energy Efficiency, specifically Article 9, individual metering in district heating systems has to be introduced by the end of 2016. These directions have been implemented in member state’s legal framework, Croatia is one of these states. The directive allows installation of both heat metering devices and heat cost allocators. Mainly due to bad communication and PR, the general public false image was created that the heat cost allocators are devices that save energy. Although this notion is wrong, the aim of this work is to develop a model that would precisely express the influence of installation heat cost allocators on potential energy savings in each unit within multifamily buildings. At the same time, in recent years, a science of machine learning has gain larger application in various fields, as it is proven to give good results in cases where large amounts of data are to be processed with an aim to recognize a pattern and correlation of each of the relevant parameter as well as in the cases where the problem is too complex for a human intelligence to solve. A special method of machine learning, decision tree method, has proven an accuracy of over 92% in prediction general building consumption. In this paper, a machine learning algorithms will be used to isolate the sole impact of installation of heat cost allocators on a single building in multifamily houses connected to district heating systems. Special emphasises will be given regression analysis, logistic regression, support vector machines, decision trees and random forest method.

Keywords: district heating, heat cost allocator, energy efficiency, machine learning, decision tree model, regression analysis, logistic regression, support vector machines, decision trees and random forest method

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Authors: Di Yao, Gunther Prokop, Kay Buttner

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Dynamic parameters, including the center of gravity, mass and inertia moments of vehicle, play an essential role in vehicle simulation, collision test and real-time control of vehicle active systems. To identify the important vehicle dynamic parameters, a systematic parameter identification procedure is studied in this work. In the first step of the procedure, a conceptual parallel manipulator (virtual test rig), which possesses three rotational degrees-of-freedom, is firstly proposed. To realize kinematic characteristics of the conceptual parallel manipulator, the kinematic analysis consists of inverse kinematic and singularity architecture is carried out. Based on the Euler's rotation equations for rigid body dynamics, the dynamic model of parallel manipulator and derivation of measurement matrix for parameter identification are presented subsequently. In order to reduce the sensitivity of parameter identification to measurement noise and other unexpected disturbances, a parameter optimization process of searching for optimal exciting trajectory of parallel manipulator is conducted in the following section. For this purpose, the 321-Euler-angles defined by parameterized finite-Fourier-series are primarily used to describe the general exciting trajectory of parallel manipulator. To minimize the condition number of measurement matrix for achieving better parameter identification accuracy, the unknown coefficients of parameterized finite-Fourier-series are estimated by employing an iterative algorithm based on MATLAB®. Meanwhile, the iterative algorithm will ensure the parallel manipulator still keeps in an achievable working status during the execution of optimal exciting trajectory. It is showed that the proposed procedure and methods in this work can effectively identify the vehicle dynamic parameters and could be an important application of parallel manipulator in the fields of parameter identification and test rig development.

Keywords: parameter identification, parallel manipulator, singularity architecture, dynamic modelling, exciting trajectory

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Authors: Briony Gray, Glenn Simpson, Hajira Dambha-Miller, Andrew Farmer

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Multimorbidity may be strongly affected by a variety of conditions, factors, and variables requiring higher demands on health and social care services, infrastructure, and expenses. Holding one or more conditions increases one’s risk for development of future conditions; with patients over 65 years old at highest risk. Psychosocial factors such as anxiety and depression are rising exponentially globally, which has been amplified by the COVID19 pandemic. These are highly correlated and predict poorer outcomes when held in coexistence and increase the likelihood of comorbid physical health conditions. While possible future reform of social and healthcare systems may help to alleviate some of these mounting pressures, there remains an urgent need to better understand the potential role health behaviours and psychosocial conditions - such as anxiety and depression – may have on aging populations. Using the UK healthcare scene as a lens for analysis, this study uses big data collected in the UK Longitudinal Study of Aging (ELSA) to examine the role of anxiety and depression in ageing populations (65yrs+). Using logistic regression modelling, results identify the 10 most significant variables correlated with both anxiety and depression from data categorised into the areas of health behaviour, psychosocial, socioeconomic, and life satisfaction (each demonstrated through literature review to be of significance). These are compared with wider global research findings with the aim of better understanding the areas in which social and healthcare reform can support multimorbidity interventions, making suggestions for improved patient-centred care. Scope of future research is outlined, which includes analysis of 59 total multimorbidity variables from the ELSA dataset, going beyond anxiety and depression.

Keywords: multimorbidity, health behaviours, patient centred care, psychosocial factors

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Authors: Joseph Lillington, Tom Gout, Mike Harrison, Ian Farnan

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The vitrification of high-level nuclear waste within borosilicate glass and its incorporation within a multi-barrier repository deep underground is widely accepted as the preferred disposal method. However, for this to happen, any safety case will require validation that the initially localized radionuclides will not be considerably released into the near/far-field. Therefore, accurate mechanistic models are necessary to predict glass dissolution, and these should be robust to a variety of incorporated waste species and leaching test conditions, particularly given substantial variations across international waste-streams. Here, machine learning is used to predict glass material properties (viscosity, density) and glass leaching model parameters from large-scale industrial data. A variety of different machine learning algorithms have been compared to assess performance. Density was predicted solely from composition, whereas viscosity additionally considered temperature. To predict suitable glass leaching model parameters, a large simulated dataset was created by coupling MATLAB and the chemical reactive-transport code HYTEC, considering the state-of-the-art GRAAL model (glass reactivity in allowance of the alteration layer). The trained models were then subsequently applied to the large-scale industrial, experimental data to identify potentially appropriate model parameters. Results indicate that ensemble methods can accurately predict viscosity as a function of temperature and composition across all three industrial datasets. Glass density prediction shows reliable learning performance with predictions primarily being within the experimental uncertainty of the test data. Furthermore, machine learning can predict glass dissolution model parameters behavior, demonstrating potential value in GRAAL model development and in assessing suitable model parameters for large-scale industrial glass dissolution data.

Keywords: machine learning, predictive modelling, pattern recognition, radioactive waste glass

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Authors: H. Dakhlaoui, D. Ruelland, Y. Tramblay, Z. Bargaoui

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To evaluate the impact of climate change on water resources at the catchment scale, not only future projections of climate are necessary but also robust rainfall-runoff models that are able to be fairly reliable under changing climate conditions. This study aims at assessing the robustness of three conceptual rainfall-runoff models (GR4j, HBV and IHACRES) on five basins in Northern Tunisia under long-term climate variability. Their robustness was evaluated according to a differential split sample test based on a climate classification of the observation period regarding simultaneously precipitation and temperature conditions. The studied catchments are situated in a region where climate change is likely to have significant impacts on runoff and they already suffer from scarcity of water resources. They cover the main hydrographical basins of Northern Tunisia (High Medjerda, Zouaraâ, Ichkeul and Cap bon), which produce the majority of surface water resources in Tunisia. The streamflow regime of the basins can be considered as natural since these basins are located upstream from storage-dams and in areas where withdrawals are negligible. A 30-year common period (1970‒2000) was considered to capture a large spread of hydro-climatic conditions. The calibration was based on the Kling-Gupta Efficiency (KGE) criterion, while the evaluation of model transferability is performed according to the Nash-Suttfliff efficiency criterion and volume error. The three hydrological models were shown to have similar behaviour under climate variability. Models prove a better ability to simulate the runoff pattern when transferred toward wetter periods compared to the case when transferred to drier periods. The limits of transferability are beyond -20% of precipitation and +1.5 °C of temperature in comparison with the calibration period. The deterioration of model robustness could in part be explained by the climate dependency of some parameters.

Keywords: rainfall-runoff modelling, hydro-climate variability, model robustness, uncertainty, Tunisia

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Authors: Rohit Agarwal, Mrityunjay K. Singh, Soma Ghosh, Ramesh Shankar, Biswajit Ghosh, Vinay V. Mahashabde

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Thermo-mechanical treatment (TMT) of rebars is a critical process to impart sufficient strength and ductility to rebar. TMT rebars are produced by the Tempcore process, involves an 'in-line' heat treatment in which hot rolled bar (temperature is around 1080°C) is passed through water boxes where it is quenched under high pressure water jets (temperature is around 25°C). The quenching rate dictates composite structure consisting (four non-homogenously distributed phases of rebar microstructure) pearlite-ferrite, bainite, and tempered martensite (from core to rim). The ferrite and pearlite phases present at core induce ductility to rebar while martensitic rim induces appropriate strength. The TMT process is difficult to model as it brings multitude of complex physics such as heat transfer, highly turbulent fluid flow, multicomponent and multiphase flow present in the control volume. Additionally the presence of film boiling regime (above Leidenfrost point) due to steam formation adds complexity to domain. A coupled heat transfer and fluid flow model based on computational fluid dynamics (CFD) has been developed at product technology division of Tata Steel, India which efficiently predicts temperature profile and percentage martensite rim thickness of rebar during quenching process. The model has been validated with 16 mm rolling of New Bar mill (NBM) plant of Tata Steel Limited, India. Furthermore, based on the scenario analyses, optimal configuration of nozzles was found which helped in subsequent increase in rolling speed.

Keywords: boiling, critical heat flux, nozzles, thermo-mechanical treatment

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Authors: Yashas Bedre Raghavendra, Pim Vullers

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This study presents the design and implementation of an abstract cryptographic coprocessor, leveraging AMBA(Advanced Microcontroller Bus Architecture) protocols - APB (Advanced Peripheral Bus) and AHB (Advanced High-performance Bus), to enable seamless integration with the main CPU(Central processing unit) and enhance the coprocessor’s algorithm flexibility. The primary objective is to create a versatile coprocessor that can execute various cryptographic algorithms, including ECC(Elliptic-curve cryptography), RSA(Rivest–Shamir–Adleman), and AES (Advanced Encryption Standard) while providing a robust and secure solution for modern secure embedded systems. To achieve this goal, the coprocessor is equipped with a tightly coupled memory (TCM) for rapid data access during cryptographic operations. The TCM is placed within the coprocessor, ensuring quick retrieval of critical data and optimizing overall performance. Additionally, the program memory is positioned outside the coprocessor, allowing for easy updates and reconfiguration, which enhances adaptability to future algorithm implementations. Direct links are employed instead of DMA(Direct memory access) for data transfer, ensuring faster communication and reducing complexity. The AMBA-based communication architecture facilitates seamless interaction between the coprocessor and the main CPU, streamlining data flow and ensuring efficient utilization of system resources. The abstract nature of the coprocessor allows for easy integration of new cryptographic algorithms in the future. As the security landscape continues to evolve, the coprocessor can adapt and incorporate emerging algorithms, making it a future-proof solution for cryptographic processing. Furthermore, this study explores the addition of custom instructions into RISC-V ISE (Instruction Set Extension) to enhance cryptographic operations. By incorporating custom instructions specifically tailored for cryptographic algorithms, the coprocessor achieves higher efficiency and reduced cycles per instruction (CPI) compared to traditional instruction sets. The adoption of RISC-V 128-bit architecture significantly reduces the total number of instructions required for complex cryptographic tasks, leading to faster execution times and improved overall performance. Comparisons are made with 32-bit and 64-bit architectures, highlighting the advantages of the 128-bit architecture in terms of reduced instruction count and CPI. In conclusion, the abstract cryptographic coprocessor presented in this study offers significant advantages in terms of algorithm flexibility, security, and integration with the main CPU. By leveraging AMBA protocols and employing direct links for data transfer, the coprocessor achieves high-performance cryptographic operations without compromising system efficiency. With its TCM and external program memory, the coprocessor is capable of securely executing a wide range of cryptographic algorithms. This versatility and adaptability, coupled with the benefits of custom instructions and the 128-bit architecture, make it an invaluable asset for secure embedded systems, meeting the demands of modern cryptographic applications.

Keywords: abstract cryptographic coprocessor, AMBA protocols, ECC, RSA, AES, tightly coupled memory, secure embedded systems, RISC-V ISE, custom instructions, instruction count, cycles per instruction

Procedia PDF Downloads 70