Search results for: ESCA potential model
25794 An Elbow Biomechanical Model and Its Coefficients Adjustment
Authors: Jie Bai, Yongsheng Gao, Shengxin Wang, Jie Zhao
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Through the establishment of the elbow biomechanical model, it can provide theoretical guide for rehabilitation therapy on the upper limb of the human body. A biomechanical model of the elbow joint can be built by the connection of muscle force model and elbow dynamics. But there are many undetermined coefficients in the model like the optimal joint angle and optimal muscle force which are usually specified as the experimental parameters of other workers. Because of the individual differences, there is a certain deviation of the final result. To this end, the RMS value of the deviation between the actual angle and calculated angle is considered. A set of coefficients which lead to the minimum RMS value will be chosen to be the optimal parameters. The direct search method and the conjugacy search method are used to get the optimal parameters, thus the model can be more accurate and mode adaptability.Keywords: elbow biomechanical model, RMS, direct search, conjugacy search
Procedia PDF Downloads 55025793 Surveying Energy Dissipation in Stepped Spillway Using Finite Element Modeling
Authors: Mehdi Fuladipanah
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Stepped spillway includes several steps from the crest to the toe. The steps of stepped spillway could cause to decrease the energy with making energy distribution in the longitude mode and also to reduce the outcome speed. The aim of this study was to stimulate the stepped spillway combined with stilling basin-step using Fluent model and the turbulent superficial flow using RNG, K-ε. The free surface of the flow was monitored by VOF model. The velocity and the depth of the flow were measured by tail water depth by the numerical model and then the dissipated energy was calculated along the spillway. The results indicated that the stilling basin-step complex may cause energy dissipation increment in the stepped spillway. Also, the numerical model was suggested as an effective method to predict the circular and complicated flows in the stepped spillways.Keywords: stepped spillway, fluent model, VOF model, K-ε model, energy distribution
Procedia PDF Downloads 37225792 Grading of Emulsified Agarwood Oil Using Gel Electrophoresis Technique
Authors: Y. T. Boon, M. N. Naim, R. Zakaria, N. F. Abu Bakar, N. Ahmad, I. W. Lenggoro
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In this study, encapsulation of agarwood oil with non-ionic surfactant, Tween 80 was prepared at critical micelle concentration of 0.0167 % v/v to produce the most stable nano-emulsion in aqueous. The encapsulation has minimized the bioactive compounds degradation in various pH conditions thus prolong their shelf life and maintained its initial oil grade. The oil grading of the prepared samples were conducted using the gel electrophoresis instead of using common analytical industrial grading such as gas chromatography- mass spectrometry (GC- MS). The grading method was chosen due to their unique zeta potential value after the encapsulation process. This paper demonstrates the feasibility of applying the electrophoresis principles to separate the encapsulated agarwood oil or grading of the emulsified agarwood oil. The results indicated that the grading process are potential to be further investigate based on their droplet size and zeta potential value at various pH condition when the droplet were migrate through polyacrylamide gel.Keywords: electrophoretic mobility, essential oil, nanoemulsion, polyacrylamide gel electrophoresis, tween 80, zeta potential
Procedia PDF Downloads 38125791 Comparative Assessment of the Potential Impact of Joining the World Trade Organization and African Continental Free Trade Area on the Ethiopia Economy
Authors: Agidew Abay, Nobuhiro Hosoe
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Ethiopia signed the AfCFTA in 2018 and is in ongoing negotiations to join the WTO. To assess the potential impacts of joining these trade agreements on Ethiopia's trade, output, and welfare, we conducted a comprehensive analysis using a world trade computable general equilibrium (CGE) model. The results of our policy experiment, which include scenarios involving the reduction of tariff and non-tariff measures, indicate that AfCFTA and WTO accession would positively affect Ethiopia's welfare, with WTO membership expected to bring more significant benefits. On the one hand, AfCFTA membership would significantly increase Ethiopian imports from AfCFTA regions while decreasing imports from non-AfCFTA regions. Conversely, it would boost Ethiopian exports to Southern Africa while showing minimal change to other AfCFTA and non-AfCFTA regions. By contrast, WTO membership would significantly increase Ethiopia’s imports from Asia and North Africa and decrease those from Europe, the rest of the world, and East Africa. It would increase exports to all regions, especially Europe, Asia, and the rest of the world. In terms of industrial output, while these two trade deals would largely favor agriculture and the meat and livestock sector and harm many manufacturing sectors (especially the light manufacturing sector), the impact of WTO accession on the Ethiopian economy would be overwhelmingly more significant than that of AfCFTA.Keywords: trade liberalization, AfCFTA, WTO, computable general equilibrium model, tariff, non-tariff measures
Procedia PDF Downloads 1225790 Increasing Recoverable Oil in Northern Afghanistan Kashkari Oil Field by Low-Salinity Water Flooding
Authors: Zabihullah Mahdi, Khwaja Naweed Seddiqi
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Afghanistan is located in a tectonically complex and dynamic area, surrounded by rocks that originated on the mother continent of Gondwanaland. The northern Afghanistan basin, which runs along the country's northern border, has the potential for petroleum generation and accumulation. The Amu Darya basin has the largest petroleum potential in the region. Sedimentation occurred in the Amu Darya basin from the Jurassic to the Eocene epochs. Kashkari oil field is located in northern Afghanistan's Amu Darya basin. The field structure consists of a narrow northeast-southwest (NE-SW) anticline with two structural highs, the northwest limb being mild and the southeast limb being steep. The first oil production well in the Kashkari oil field was drilled in 1976, and a total of ten wells were drilled in the area between 1976 and 1979. The amount of original oil in place (OOIP) in the Kashkari oil field, based on the results of surveys and calculations conducted by research institutions, is estimated to be around 140 MMbbls. The objective of this study is to increase recoverable oil reserves in the Kashkari oil field through the implementation of low-salinity water flooding (LSWF) enhanced oil recovery (EOR) technique. The LSWF involved conducting a core flooding laboratory test consisting of four sequential steps with varying salinities. The test commenced with the use of formation water (FW) as the initial salinity, which was subsequently reduced to a salinity level of 0.1%. Afterward, the numerical simulation model of core scale oil recovery by LSWF was designed by Computer Modelling Group’s General Equation Modeler (CMG-GEM) software to evaluate the applicability of the technology to the field scale. Next, the Kahskari oil field simulation model was designed, and the LSWF method was applied to it. To obtain reasonable results, laboratory settings (temperature, pressure, rock, and oil characteristics) are designed as far as possible based on the condition of the Kashkari oil field, and several injection and production patterns are investigated. The relative permeability of oil and water in this study was obtained using Corey’s equation. In the Kashkari oilfield simulation model, three models: 1. Base model (with no water injection), 2. FW injection model, and 3. The LSW injection model was considered for the evaluation of the LSWF effect on oil recovery. Based on the results of the LSWF laboratory experiment and computer simulation analysis, the oil recovery increased rapidly after the FW was injected into the core. Subsequently, by injecting 1% salinity water, a gradual increase of 4% oil can be observed. About 6.4% of the field is produced by the application of the LSWF technique. The results of LSWF (salinity 0.1%) on the Kashkari oil field suggest that this technology can be a successful method for developing Kashkari oil production.Keywords: low-salinity water flooding, immiscible displacement, Kashkari oil field, two-phase flow, numerical reservoir simulation model
Procedia PDF Downloads 4125789 The 2017 Shanghai Model Breaking Stalemate in Chinese Education Reform: A Discussion of China’s Scheduled Experiment in Access to Higher Education Between 2017 and 2020
Authors: Ping Chou, Xiaoyan Zhou
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Domestically and internationally, the Chinese education has long been criticized for being test-oriented, and in spite of efforts made by the Chinese government, it remains hard to find a solution. This paper intends to look at the situation in a comparatively objective manner and discuss the significance of the Shanghai Model as a newly-scheduled experiment for education reform. As a breakthrough, in addition to comprehensive inner-quality evaluation, a small but important step is to be taken in shifting focus of attention back to students by giving them more freedom in selecting certain courses for aptitude tests for college admission. As the first author of the paper has studied and taught both in Chinese and American colleges and universities, comparisons are made when the situation becomes relevant. The official solution for test-oriented education is to make students well-rounded but the writers of this paper believe that it is even more important to make the system well-rounded so it can accept a spectrum of diverse individuals with different potential.Keywords: college admission, education reform, Shanghai model, test-oriented education
Procedia PDF Downloads 33825788 A Multi-Scale Study of Potential-Dependent Ammonia Synthesis on IrO₂ (110): DFT, 3D-RISM, and Microkinetic Modeling
Authors: Shih-Huang Pan, Tsuyoshi Miyazaki, Minoru Otani, Santhanamoorthi Nachimuthu, Jyh-Chiang Jiang
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Ammonia (NH₃) is crucial in renewable energy and agriculture, yet its traditional production via the Haber-Bosch process faces challenges due to the inherent inertness of nitrogen (N₂) and the need for high temperatures and pressures. The electrocatalytic nitrogen reduction (ENRR) presents a more sustainable option, functioning at ambient conditions. However, its advancement is limited by selectivity and efficiency challenges due to the competing hydrogen evolution reaction (HER). The critical roles of protonation of N-species and HER highlight the necessity of selecting optimal catalysts and solvents to enhance ENRR performance. Notably, transition metal oxides, with their adjustable electronic states and excellent chemical and thermal stability, have shown promising ENRR characteristics. In this study, we use density functional theory (DFT) methods to investigate the ENRR mechanisms on IrO₂ (110), a material known for its tunable electronic properties and exceptional chemical and thermal stability. Employing the constant electrode potential (CEP) model, where the electrode - electrolyte interface is treated as a polarizable continuum with implicit solvation, and adjusting electron counts to equalize work functions in the grand canonical ensemble, we further incorporate the advanced 3D Reference Interaction Site Model (3D-RISM) to accurately determine the ENRR limiting potential across various solvents and pH conditions. Our findings reveal that the limiting potential for ENRR on IrO₂ (110) is significantly more favorable than for HER, highlighting the efficiency of the IrO₂ catalyst for converting N₂ to NH₃. This is supported by the optimal *NH₃ desorption energy on IrO₂, which enhances the overall reaction efficiency. Microkinetic simulations further predict a promising NH₃ production rate, even at the solution's boiling point¸ reinforcing the catalytic viability of IrO₂ (110). This comprehensive approach provides an atomic-level understanding of the electrode-electrolyte interface in ENRR, demonstrating the practical application of IrO₂ in electrochemical catalysis. The findings provide a foundation for developing more efficient and selective catalytic strategies, potentially revolutionizing industrial NH₃ production.Keywords: density functional theory, electrocatalyst, nitrogen reduction reaction, electrochemistry
Procedia PDF Downloads 2225787 Energy Consumption Models for Electric Vehicles: Survey and Proposal of a More Realistic Model
Authors: I. Sagaama, A. Kechiche, W. Trojet, F. Kamoun
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Replacing combustion engine vehicles by electric vehicles (EVs) is a major step in recent years due to their potential benefits. Battery autonomy and charging processes are still a big issue for that kind of vehicles. Therefore, reducing the energy consumption of electric vehicles becomes a necessity. Many researches target introducing recent information and communication technologies in EVs in order to propose reducing energy consumption services. Evaluation of realistic scenarios is a big challenge nowadays. In this paper, we will elaborate a state of the art of different proposed energy consumption models in the literature, then we will present a comparative study of these models, finally, we will extend previous works in order to propose an accurate and realistic energy model for calculating instantaneous power consumption of electric vehicles.Keywords: electric vehicle, vehicular networks, energy models, traffic simulation
Procedia PDF Downloads 37125786 Assessment of the Natural and Human Potential of the Municipality of Tirana for the Development of Agritourism
Authors: Dritan Lloçi, Xhulia Bygjymi
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The topic is about one of the new trends with the greatest expectations in the field of tourism, such as agritourism. It is chosen exactly this type of tourism to address as this issue is one of the newest trends not only for Tirana or Albania but also beyond. The other reason is that this topic is quite current and challenging for the reality in which we find ourselves, and the opportunities for research work and to make our own contribution are quite large. It is chosen Tirana because seeing the many opportunities it offers for the development of agritourism as a result of the rich natural potential it offers; the fact that it is the capital of Albania makes this space absorb a good part of the investments in the rural tourism sector but not alone. The study is organized into several main issues regarding the natural and human potentials of the area, which are in function of the development of agrotourism. The first issue has to do with the natural potentials of the municipality of Tirana and how they can be used for agritourism. The second issue has to do with the cultural potential that the municipality of Tirana possesses, causing tourist flows to be more concentrated in this geographical-administrative space. The third issue has to do with the human potential that is a function of agrotourism. So the way of life, hospitality, cooking, etc.Keywords: agrotourism, natural potential, agrotourism farms, tirana municipality, tourism development
Procedia PDF Downloads 7625785 VideoAssist: A Labelling Assistant to Increase Efficiency in Annotating Video-Based Fire Dataset Using a Foundation Model
Authors: Keyur Joshi, Philip Dietrich, Tjark Windisch, Markus König
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In the field of surveillance-based fire detection, the volume of incoming data is increasing rapidly. However, the labeling of a large industrial dataset is costly due to the high annotation costs associated with current state-of-the-art methods, which often require bounding boxes or segmentation masks for model training. This paper introduces VideoAssist, a video annotation solution that utilizes a video-based foundation model to annotate entire videos with minimal effort, requiring the labeling of bounding boxes for only a few keyframes. To the best of our knowledge, VideoAssist is the first method to significantly reduce the effort required for labeling fire detection videos. The approach offers bounding box and segmentation annotations for the video dataset with minimal manual effort. Results demonstrate that the performance of labels annotated by VideoAssist is comparable to those annotated by humans, indicating the potential applicability of this approach in fire detection scenarios.Keywords: fire detection, label annotation, foundation models, object detection, segmentation
Procedia PDF Downloads 1425784 Monitoring Three-Dimensional Models of Tree and Forest by Using Digital Close-Range Photogrammetry
Authors: S. Y. Cicekli
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In this study, tree-dimensional model of tree was created by using terrestrial close range photogrammetry. For this close range photos were taken. Photomodeler Pro 5 software was used for camera calibration and create three-dimensional model of trees. In first test, three-dimensional model of a tree was created, in the second test three-dimensional model of three trees were created. This study aim is creating three-dimensional model of trees and indicate the use of close-range photogrammetry in forestry. At the end of the study, three-dimensional model of tree and three trees were created. This study showed that usability of close-range photogrammetry for monitoring tree and forests three-dimensional model.Keywords: close- range photogrammetry, forest, tree, three-dimensional model
Procedia PDF Downloads 38925783 A Mathematical-Based Formulation of EEG Fluctuations
Authors: Razi Khalafi
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Brain is the information processing center of the human body. Stimuli in form of information are transferred to the brain and then brain makes the decision on how to respond to them. In this research we propose a new partial differential equation which analyses the EEG signals and make a relationship between the incoming stimuli and the brain response to them. In order to test the proposed model, a set of external stimuli applied to the model and the model’s outputs were checked versus the real EEG data. The results show that this model can model the EEG signal well. The proposed model is useful not only for modeling of the EEG signal in case external stimuli but it can be used for the modeling of brain response in case of internal stimuli.Keywords: Brain, stimuli, partial differential equation, response, eeg signal
Procedia PDF Downloads 43325782 Performance and Availability Analysis of 2N Redundancy Models
Authors: Yutae Lee
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In this paper, we consider the performance and availability of a redundancy model. The redundancy model is a form of resilience that ensures service availability in the event of component failure. This paper considers a 2N redundancy model. In the model there are at most one active service unit and at most one standby service unit. The active one is providing the service while the standby is prepared to take over the active role when the active fails. We design our analysis model using Stochastic Reward Nets, and then evaluate the performance and availability of 2N redundancy model using Stochastic Petri Net Package (SPNP).Keywords: availability, performance, stochastic reward net, 2N redundancy
Procedia PDF Downloads 42125781 Impact Evaluation and Technical Efficiency in Ethiopia: Correcting for Selectivity Bias in Stochastic Frontier Analysis
Authors: Tefera Kebede Leyu
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The purpose of this study was to estimate the impact of LIVES project participation on the level of technical efficiency of farm households in three regions of Ethiopia. We used household-level data gathered by IRLI between February and April 2014 for the year 2013(retroactive). Data on 1,905 (754 intervention and 1, 151 control groups) sample households were analyzed using STATA software package version 14. Efforts were made to combine stochastic frontier modeling with impact evaluation methodology using the Heckman (1979) two-stage model to deal with possible selectivity bias arising from unobservable characteristics in the stochastic frontier model. Results indicate that farmers in the two groups are not efficient and operate below their potential frontiers i.e., there is a potential to increase crop productivity through efficiency improvements in both groups. In addition, the empirical results revealed selection bias in both groups of farmers confirming the justification for the use of selection bias corrected stochastic frontier model. It was also found that intervention farmers achieved higher technical efficiency scores than the control group of farmers. Furthermore, the selectivity bias-corrected model showed a different technical efficiency score for the intervention farmers while it more or less remained the same for that of control group farmers. However, the control group of farmers shows a higher dispersion as measured by the coefficient of variation compared to the intervention counterparts. Among the explanatory variables, the study found that farmer’s age (proxy to farm experience), land certification, frequency of visit to improved seed center, farmer’s education and row planting are important contributing factors for participation decisions and hence technical efficiency of farmers in the study areas. We recommend that policies targeting the design of development intervention programs in the agricultural sector focus more on providing farmers with on-farm visits by extension workers, provision of credit services, establishment of farmers’ training centers and adoption of modern farm technologies. Finally, we recommend further research to deal with this kind of methodological framework using a panel data set to test whether technical efficiency starts to increase or decrease with the length of time that farmers participate in development programs.Keywords: impact evaluation, efficiency analysis and selection bias, stochastic frontier model, Heckman-two step
Procedia PDF Downloads 7625780 Leveraging Natural Language Processing for Legal Artificial Intelligence: A Longformer Approach for Taiwanese Legal Cases
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Legal artificial intelligence (LegalAI) has been increasing applications within legal systems, propelled by advancements in natural language processing (NLP). Compared with general documents, legal case documents are typically long text sequences with intrinsic logical structures. Most existing language models have difficulty understanding the long-distance dependencies between different structures. Another unique challenge is that while the Judiciary of Taiwan has released legal judgments from various levels of courts over the years, there remains a significant obstacle in the lack of labeled datasets. This deficiency makes it difficult to train models with strong generalization capabilities, as well as accurately evaluate model performance. To date, models in Taiwan have yet to be specifically trained on judgment data. Given these challenges, this research proposes a Longformer-based pre-trained language model explicitly devised for retrieving similar judgments in Taiwanese legal documents. This model is trained on a self-constructed dataset, which this research has independently labeled to measure judgment similarities, thereby addressing a void left by the lack of an existing labeled dataset for Taiwanese judgments. This research adopts strategies such as early stopping and gradient clipping to prevent overfitting and manage gradient explosion, respectively, thereby enhancing the model's performance. The model in this research is evaluated using both the dataset and the Average Entropy of Offense-charged Clustering (AEOC) metric, which utilizes the notion of similar case scenarios within the same type of legal cases. Our experimental results illustrate our model's significant advancements in handling similarity comparisons within extensive legal judgments. By enabling more efficient retrieval and analysis of legal case documents, our model holds the potential to facilitate legal research, aid legal decision-making, and contribute to the further development of LegalAI in Taiwan.Keywords: legal artificial intelligence, computation and language, language model, Taiwanese legal cases
Procedia PDF Downloads 7325779 Modeling of Bioelectric Activity of Nerve Cells Using Bond Graph Method
Authors: M. Ghasemi, F. Eskandari, B. Hamzehei, A. R. Arshi
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Bioelectric activity of nervous cells might be changed causing by various factors. This alteration can lead to unforeseen circumstances in other organs of the body. Therefore, the purpose of this study was to model a single neuron and its behavior under an initial stimulation. This study was developed based on cable theory by means of the Bond Graph method. The numerical values of the parameters were derived from empirical studies of cellular electrophysiology experiments. Initial excitation was applied through square current functions, and the resulted action potential was estimated along the neuron. The results revealed that the model was developed in this research adapted with the results of experimental studies and demonstrated the electrical behavior of nervous cells properly.Keywords: bond graph, stimulation, nervous cells, modeling
Procedia PDF Downloads 43025778 Predicting Radioactive Waste Glass Viscosity, Density and Dissolution with Machine Learning
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
Procedia PDF Downloads 11725777 Slope Stability Considering the Top Building Load
Authors: Micke Didit, Xiwen Zhang, Weidong Zhu
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Slope stability is one of the most important subjects of geotechnics. The slope top-loading plays a key role in the stability of slopes in hill slope areas. Therefore, it is of great importance to study the relationship between the load and the stability of the slope. This study aims to analyze the influence of the building load applied on the top of the slope and deduces its effect on the slope stability. For this purpose, a three-dimensional slope model under different building loads with different distances to the slope shoulder was established using the finite-difference analysis software Flac3D. The results show that the loads applied at different distances on the top of the slope have different effects on the slope stability. The slope factor of safety (fos) increases with the increase of the distance between the top-loading and the slope shoulder, resulting in the decrease of the coincidence area between the load-deformation and the potential sliding surface. The slope is no longer affected by the potential risk of sliding at approximately 20 m away from the slope shoulder.Keywords: building load, finite-difference analysis, FLAC3D software, slope factor of safety, slope stability
Procedia PDF Downloads 17925776 A Numerical Study of the Interaction between Residual Stress Profiles Induced by Quasi-Static Plastification
Authors: Guilherme F. Guimaraes, Alfredo R. De Faria, Ronnie R. Rego, Andre L. R. D'Oliveira
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The development of methods for predicting manufacturing phenomena steadily grows due to their high potential to contribute to the component’s performance and durability. One of the most relevant phenomena in manufacturing is the residual stress state development through the manufacturing chain. In most cases, the residual stresses have their origin due to heterogenous plastifications produced by the processes. Although a few manufacturing processes have been successfully approached by numerical modeling, there is still a lack of understanding on how these processes' interactions will affect the final stress state. The objective of this work is to analyze the influence of previous stresses on the residual stress state induced by plastic deformation of a quasi-static indentation. The model consists of a simplified approach of shot peening, modeling four cases with variations in indenter size and force. This model was validated through topography, measured by optical 3D focus-variation, and residual stress, measured with the X-ray diffraction technique. The validated model was then exposed to several initial stress states, and the effect on the final residual stress was analyzed.Keywords: plasticity, residual stress, finite element method, manufacturing
Procedia PDF Downloads 20725775 Performance Evaluation of a Small Microturbine Cogeneration Functional Model
Authors: Jeni A. Popescu, Sorin G. Tomescu, Valeriu A. Vilag
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The paper focuses on the potential methods of increasing the performance of a microturbine by combining additional elements available for utilization in a cogeneration plant. The activity is carried out within the framework of a project aiming to develop, manufacture and test a microturbine functional model with high potential in energetic industry utilization. The main goal of the analysis is to determine the parameters of the fluid flow passing through each section of the turbine, based on limited data available in literature for the focus output power range or provided by experimental studies, starting from a reference cycle, and considering different cycle options, including simple, intercooled and recuperated options, in order to optimize a small cogeneration plant operation. The studied configurations operate under the same initial thermodynamic conditions and are based on a series of assumptions, in terms of individual performance of the components, pressure/velocity losses, compression ratios, and efficiencies. The thermodynamic analysis evaluates the expected performance of the microturbine cycle, while providing a series of input data and limitations to be included in the development of the experimental plan. To simplify the calculations and to allow a clear estimation of the effect of heat transfer between fluids, the working fluid for all the thermodynamic evolutions is, initially, air, the combustion being modelled by simple heat addition to the system. The theoretical results, along with preliminary experimental results are presented, aiming for a correlation in terms of microturbine performance.Keywords: cogeneration, microturbine, performance, thermodynamic analysis
Procedia PDF Downloads 17125774 A Sharp Interface Model for Simulating Seawater Intrusion in the Coastal Aquifer of Wadi Nador (Algeria)
Authors: Abdelkader Hachemi, Boualem Remini
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Seawater intrusion is a significant challenge faced by coastal aquifers in the Mediterranean basin. This study aims to determine the position of the sharp interface between seawater and freshwater in the aquifer of Wadi Nador, located in the Wilaya of Tipaza, Algeria. A numerical areal sharp interface model using the finite element method is developed to investigate the spatial and temporal behavior of seawater intrusion. The aquifer is assumed to be homogeneous and isotropic. The simulation results are compared with geophysical prospection data obtained through electrical methods in 2011 to validate the model. The simulation results demonstrate a good agreement with the geophysical prospection data, confirming the accuracy of the sharp interface model. The position of the sharp interface in the aquifer is found to be approximately 1617 meters from the sea. Two scenarios are proposed to predict the interface position for the year 2024: one without pumping and the other with pumping. The results indicate a noticeable retreat of the sharp interface position in the first scenario, while a slight decline is observed in the second scenario. The findings of this study provide valuable insights into the dynamics of seawater intrusion in the Wadi Nador aquifer. The predicted changes in the sharp interface position highlight the potential impact of pumping activities on the aquifer's vulnerability to seawater intrusion. This study emphasizes the importance of implementing measures to manage and mitigate seawater intrusion in coastal aquifers. The sharp interface model developed in this research can serve as a valuable tool for assessing and monitoring the vulnerability of aquifers to seawater intrusion.Keywords: seawater intrusion, sharp interface, coastal aquifer, algeria
Procedia PDF Downloads 12025773 An Empirical Study of Factors that Impact Government E-Services Acceptance by Citizens: Case Study from UAE
Authors: Emad Bataineh, Sara Al-Mutawa
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The primary focus of this study is to investigate and identify the perceptions of potential end users relating to factors which impact on e-services acceptance. Technology Acceptance Model (TAM) has been adopted in this study as it can be extended when technologies are introduced. This research validates the developed TAM model and evaluates the variance of the outcome variable (acceptance of e-services). Five factors were adopted as determinants of acceptance of e-services: ease of use, security, trust, web skills, and language. The study was undertaken in the General Directorate of Residency and Foreigners Affairs (GDRFA) in the UAE. A quantitative survey methodology was adopted in this study, which surveyed 466 customers who use the GDRFA e-services. The overall findings revealed that security language, web skills and support significantly affected ease of use and perceived usefulness. However, the trust doesn’t affect the ease of use. Further, ease of use significantly affects intention to use and perceived usefulness while in turn intention to use was influenced by perceived usefulness. This study offers an understanding of people’s adoption of e-government services with the help of established theories such as TAM and various factors that influence the e-government adoption with reference to UAE.Keywords: e-government portal, e-service, usability, TAM model
Procedia PDF Downloads 43425772 A Mathematical Equation to Calculate Stock Price of Different Growth Model
Authors: Weiping Liu
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This paper presents an equation to calculate stock prices of different growth model. This equation is mathematically derived by using discounted cash flow method. It has the advantages of being very easy to use and very accurate. It can still be used even when the first stage is lengthy. This equation is more generalized because it can be used for all the three popular stock price models. It can be programmed into financial calculator or electronic spreadsheets. In addition, it can be extended to a multistage model. It is more versatile and efficient than the traditional methods.Keywords: stock price, multistage model, different growth model, discounted cash flow method
Procedia PDF Downloads 40725771 Musical Instrument Recognition in Polyphonic Audio Through Convolutional Neural Networks and Spectrograms
Authors: Rujia Chen, Akbar Ghobakhlou, Ajit Narayanan
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This study investigates the task of identifying musical instruments in polyphonic compositions using Convolutional Neural Networks (CNNs) from spectrogram inputs, focusing on binary classification. The model showed promising results, with an accuracy of 97% on solo instrument recognition. When applied to polyphonic combinations of 1 to 10 instruments, the overall accuracy was 64%, reflecting the increasing challenge with larger ensembles. These findings contribute to the field of Music Information Retrieval (MIR) by highlighting the potential and limitations of current approaches in handling complex musical arrangements. Future work aims to include a broader range of musical sounds, including electronic and synthetic sounds, to improve the model's robustness and applicability in real-time MIR systems.Keywords: binary classifier, CNN, spectrogram, instrument
Procedia PDF Downloads 8425770 Using Serious Games to Integrate the Potential of Mass Customization into the Fuzzy Front-End of New Product Development
Authors: Michael N. O'Sullivan, Con Sheahan
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Mass customization is the idea of offering custom products or services to satisfy the needs of each individual customer while maintaining the efficiency of mass production. Technologies like 3D printing and artificial intelligence have many start-ups hoping to capitalize on this dream of creating personalized products at an affordable price, and well established companies scrambling to innovate and maintain their market share. However, the majority of them are failing as they struggle to understand one key question – where does customization make sense? Customization and personalization only make sense where the value of the perceived benefit outweighs the cost to implement it. In other words, will people pay for it? Looking at the Kano Model makes it clear that it depends on the product. In products where customization is an inherent need, like prosthetics, mass customization technologies can be highly beneficial. However, for products that already sell as a standard, like headphones, offering customization is likely only an added bonus, and so the product development team must figure out if the customers’ perception of the added value of this feature will outweigh its premium price tag. This can be done through the use of a ‘serious game,’ whereby potential customers are given a limited budget to collaboratively buy and bid on potential features of the product before it is developed. If the group choose to buy customization over other features, then the product development team should implement it into their design. If not, the team should prioritize the features on which the customers have spent their budget. The level of customization purchased can also be translated to an appropriate production method, for example, the most expensive type of customization would likely be free-form design and could be achieved through digital fabrication, while a lower level could be achieved through short batch production. Twenty-five teams of final year students from design, engineering, construction and technology tested this methodology when bringing a product from concept through to production specification, and found that it allowed them to confidently decide what level of customization, if any, would be worth offering for their product, and what would be the best method of producing it. They also found that the discussion and negotiations between players during the game led to invaluable insights, and often decided to play a second game where they offered customers the option to buy the various customization ideas that had been discussed during the first game.Keywords: Kano model, mass customization, new product development, serious game
Procedia PDF Downloads 13525769 Impact of Climate Change on Irrigation and Hydropower Potential: A Case of Upper Blue Nile Basin in Western Ethiopia
Authors: Elias Jemal Abdella
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The Blue Nile River is an important shared resource of Ethiopia, Sudan and also, because it is the major contributor of water to the main Nile River, Egypt. Despite the potential benefits of regional cooperation and integrated joint basin management, all three countries continue to pursue unilateral plans for development. Besides, there is great uncertainty about the likely impacts of climate change in water availability for existing as well as proposed irrigation and hydropower projects in the Blue Nile Basin. The main objective of this study is to quantitatively assess the impact of climate change on the hydrological regime of the upper Blue Nile basin, western Ethiopia. Three models were combined, a dynamic Coordinated Regional Climate Downscaling Experiment (CORDEX) regional climate model (RCM) that is used to determine climate projections for the Upper Blue Nile basin for Representative Concentration Pathways (RCPs) 4.5 and 8.5 greenhouse gas emissions scenarios for the period 2021-2050. The outputs generated from multimodel ensemble of four (4) CORDEX-RCMs (i.e., rainfall and temperature) were used as input to a Soil and Water Assessment Tool (SWAT) hydrological model which was setup, calibrated and validated with observed climate and hydrological data. The outputs from the SWAT model (i.e., projections in river flow) were used as input to a Water Evaluation and Planning (WEAP) water resources model which was used to determine the water resources implications of the changes in climate. The WEAP model was set-up to simulate three development scenarios. Current Development scenario was the existing water resource development situation, Medium-term Development scenario was planned water resource development that is expected to be commissioned (i.e. before 2025) and Long-term full Development scenario were all planned water resource development likely to be commissioned (i.e. before 2050). The projected change of mean annual temperature for period (2021 – 2050) in most of the basin are warmer than the baseline (1982 -2005) average in the range of 1 to 1.4oC, implying that an increase in evapotranspiration loss. Subbasins which already distressed from drought may endure to face even greater challenges in the future. Projected mean annual precipitation varies from subbasin to subbasin; in the Eastern, North Eastern and South western highland of the basin a likely increase of mean annual precipitation up to 7% whereas in the western lowland part of the basin mean annual precipitation projected to decrease by 3%. The water use simulation indicates that currently irrigation demand in the basin is 1.29 Bm3y-1 for 122,765 ha of irrigation area. By 2025, with new schemes being developed, irrigation demand is estimated to increase to 2.5 Bm3y-1 for 277,779 ha. By 2050, irrigation demand in the basin is estimated to increase to 3.4 Bm3y-1 for 372,779 ha. The hydropower generation simulation indicates that 98 % of hydroelectricity potential could be produced if all planned dams are constructed.Keywords: Blue Nile River, climate change, hydropower, SWAT, WEAP
Procedia PDF Downloads 35525768 Numerical Solutions of Fractional Order Epidemic Model
Authors: Sadia Arshad, Ayesha Sohail, Sana Javed, Khadija Maqbool, Salma Kanwal
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The dynamical study of the carriers play an essential role in the evolution and global transmission of infectious diseases and will be discussed in this study. To make this approach novel, we will consider the fractional order model which is generalization of integer order derivative to an arbitrary number. Since the integration involved is non local therefore this property of fractional operator is very useful to study epidemic model for infectious diseases. An extended numerical method (ODE solver) is implemented on the model equations and we will present the simulations of the model for different values of fractional order to study the effect of carriers on transmission dynamics. Global dynamics of fractional model are established by using the reproduction number.Keywords: Fractional differential equation, Numerical simulations, epidemic model, transmission dynamics
Procedia PDF Downloads 60225767 Modeling Residual Modulus of Elasticity of Self-Compacted Concrete Using Artificial Neural Networks
Authors: Ahmed M. Ashteyat
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Artificial Neural Network (ANN) models have been widely used in material modeling, inter-correlations, as well as behavior and trend predictions when the nonlinear relationship between system parameters cannot be quantified explicitly and mathematically. In this paper, ANN was used to predict the residual modulus of elasticity (RME) of self compacted concrete (SCC) damaged by heat. The ANN model was built, trained, tested and validated using a total of 112 experimental data sets, gathered from available literature. The data used in model development included temperature, relative humidity conditions, mix proportions, filler types, and fiber type. The result of ANN training, testing, and validation indicated that the RME of SCC, exposed to different temperature and relative humidity levels, could be predicted accurately with ANN techniques. The reliability between the predicated outputs and the actual experimental data was 99%. This show that ANN has strong potential as a feasible tool for predicting residual elastic modulus of SCC damaged by heat within the range of input parameter. The ANN model could be used to estimate the RME of SCC, as a rapid inexpensive substitute for the much more complicated and time consuming direct measurement of the RME of SCC.Keywords: residual modulus of elasticity, artificial neural networks, self compacted-concrete, material modeling
Procedia PDF Downloads 53625766 The Influence of Online Marketing Tactics in Tourist Destination Reputation: Egypt as a Case Study
Authors: Alyaa Darwish, Peter Burns, Sofia Reino
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Online marketing has been the key focus of attention for the majority of destinations since the Internet became the primarily information tool for travel marketing. Tourism is a reputation-dependent industry; potential travelers who do not have previous experience with the destination face numerous risks during the process of decision-making. An accurate perception of the destination’s reputation helps to minimize risk against unsatisfying travel experiences. However, there has been limited investigation with regards to the reputation of tourist destination. Taking the importance of reputation to the tourism industry, this research aims to: 1) Develop a destination reputation model; 2) Assess the tourist destination approach towards online marketing tactics; 3) Evaluate the impact of differentiated online marketing tactics on reputation; and 4) Measure the potential for using online marketing tactics to manage the destination’s online reputation. This research follows an interpretivism epistemological research approach through using four research methods; interviews, questionnaire, content analysis, and experiment to achieve the research goals.Keywords: destination reputation, online marketing, reputation, tactics
Procedia PDF Downloads 35725765 Hybrid Energy System for the German Mining Industry: An Optimized Model
Authors: Kateryna Zharan, Jan C. Bongaerts
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In recent years, economic attractiveness of renewable energy (RE) for the mining industry, especially for off-grid mines, and a negative environmental impact of fossil energy are stimulating to use RE for mining needs. Being that remote area mines have higher energy expenses than mines connected to a grid, integration of RE may give a mine economic benefits. Regarding the literature review, there is a lack of business models for adopting of RE at mine. The main aim of this paper is to develop an optimized model of RE integration into the German mining industry (GMI). Hereby, the GMI with amount of around 800 mill. t. annually extracted resources is included in the list of the 15 major mining country in the world. Accordingly, the mining potential of Germany is evaluated in this paper as a perspective market for RE implementation. The GMI has been classified in order to find out the location of resources, quantity and types of the mines, amount of extracted resources, and access of the mines to the energy resources. Additionally, weather conditions have been analyzed in order to figure out where wind and solar generation technologies can be integrated into a mine with the highest efficiency. Despite the fact that the electricity demand of the GMI is almost completely covered by a grid connection, the hybrid energy system (HES) based on a mix of RE and fossil energy is developed due to show environmental and economic benefits. The HES for the GMI consolidates a combination of wind turbine, solar PV, battery and diesel generation. The model has been calculated using the HOMER software. Furthermore, the demonstrated HES contains a forecasting model that predicts solar and wind generation in advance. The main result from the HES such as CO2 emission reduction is estimated in order to make the mining processing more environmental friendly.Keywords: diesel generation, German mining industry, hybrid energy system, hybrid optimization model for electric renewables, optimized model, renewable energy
Procedia PDF Downloads 344