Search results for: material chemistry modeling

Authors: Adji Achmad Rinaldo Fernandes

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The research was conducted to apply semiparametric SEM modeling to the timeliness of paying credit. Semiparametric SEM is structural modeling in which two combined approaches of parametric and nonparametric approaches are used. The analysis method in this research is semiparametric SEM with a nonparametric approach using a truncated spline. The data in the study were obtained through questionnaires distributed to Bank X mortgage debtors and are confidential. The study used 3 variables consisting of one exogenous variable, one intervening endogenous variable, and one endogenous variable. The results showed that (1) the effect of capacity and willingness to pay variables on timeliness of payment is significant, (2) modeling the capacity variable on willingness to pay also produces a significant estimate, (3) the effect of the capacity variable on the timeliness of payment variable is not influenced by the willingness to pay variable as an intervening variable, (4) the R^2 value of 0.763 or 76.33% indicates that the model has good predictive relevance.

Keywords: structural equation modeling semiparametric, credit bank, accuracy of payment time, willingness to pay

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Authors: Pranav Gunhal., Krish Jhurani

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This study tackles the significant computational challenge of predicting excited state dynamics in organic photovoltaic (OPV) materials—a pivotal factor in the performance of solar energy solutions. Time-dependent density functional theory (TDDFT), though effective, is computationally prohibitive for larger and more complex molecules. As a solution, the research explores the application of transformer neural networks, a type of artificial intelligence (AI) model known for its superior performance in natural language processing, to predict excited state dynamics in OPV materials. The methodology involves a two-fold process. First, the transformer model is trained on an extensive dataset comprising over 10,000 TDDFT calculations of excited state dynamics from a diverse set of OPV materials. Each training example includes a molecular structure and the corresponding TDDFT-calculated excited state lifetimes and key electronic transitions. Second, the trained model is tested on a separate set of molecules, and its predictions are rigorously compared to independent TDDFT calculations. The results indicate a remarkable degree of predictive accuracy. Specifically, for a test set of 1,000 OPV materials, the transformer model predicted excited state lifetimes with a mean absolute error of 0.15 picoseconds, a negligible deviation from TDDFT-calculated values. The model also correctly identified key electronic transitions contributing to the excited state dynamics in 92% of the test cases, signifying a substantial concordance with the results obtained via conventional quantum chemistry calculations. The practical integration of the transformer model with existing quantum chemistry software was also realized, demonstrating its potential as a powerful tool in the arsenal of materials scientists and chemists. The implementation of this AI model is estimated to reduce the computational cost of predicting excited state dynamics by two orders of magnitude compared to conventional TDDFT calculations. The successful utilization of transformer neural networks to accurately predict excited state dynamics provides an efficient computational pathway for the accelerated discovery and design of new OPV materials, potentially catalyzing advancements in the realm of sustainable energy solutions.

Keywords: transformer neural networks, organic photovoltaic materials, excited state dynamics, time-dependent density functional theory, predictive modeling

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Authors: Jiun Jeon, Byung-Ju Yi

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This paper investigates modeling and shape prediction of elastic kinematic chains such as colonoscopy. 2D and 3D models of elastic kinematic chains are suggested and their behaviors are demonstrated through simulation. To corroborate the effectiveness of those models, experimental work is performed using a magnetic sensor system.

Keywords: elastic kinematic chain, shape prediction, colonoscopy, modeling

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Authors: R. Mkahl, A. Nait-Sidi-Moh, M. Wack

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Batteries of electric vehicles (BEV) are becoming more attractive with the advancement of new battery technologies and promotion of electric vehicles. BEV batteries are recharged on board vehicles using either the grid (G2V for Grid to Vehicle) or renewable energies in a stand-alone application (H2V for Home to Vehicle). This paper deals with the modeling, sizing and control of a photo voltaic stand-alone application that can charge the BEV at home. The modeling approach and developed mathematical models describing the system components are detailed. Simulation and experimental results are presented and commented.

Keywords: electric vehicles, photovoltaic energy, lead-acid batteries, charging process, modeling, simulation, experimental tests

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Authors: Bekim Berisha, Sebastian Hirsiger, Pavel Hora

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Advanced material models involving several sets of model parameters require a big experimental effort. As models are getting more and more complex like e.g. the so called “Homogeneous Anisotropic Hardening - HAH” model for description of the yielding behavior in the 2D/3D stress space, the number and complexity of the required experiments are also increasing continuously. In the context of sheet metal forming, these requirements are even more pronounced, because of the anisotropic behavior or sheet materials. In addition, some of the experiments are very difficult to perform e.g. the plane stress biaxial compression test. Accordingly, tensile tests in at least three directions, biaxial tests and tension-compression or shear-reverse shear experiments are performed to determine the parameters of the macroscopic models. Therefore, determination of the macroscopic model parameters based on virtual experiments is a very promising strategy to overcome these difficulties. For this purpose, in the framework of multiscale material modeling, a dislocation density based crystal plasticity model in combination with a FFT-based spectral solver is applied to perform virtual experiments. Modeling of the plastic behavior of metals based on crystal plasticity theory is a well-established methodology. However, in general, the computation time is very high and therefore, the computations are restricted to simplified microstructures as well as simple polycrystal models. In this study, a dislocation density based crystal plasticity model – including an implementation of the backstress – is used in a spectral solver framework to generate virtual experiments for three deep drawing materials, DC05-steel, AA6111-T4 and AA4045 aluminum alloys. For this purpose, uniaxial as well as multiaxial loading cases, including various pre-strain histories, has been computed and validated with real experiments. These investigations showed that crystal plasticity modeling in the framework of Representative Volume Elements (RVEs) can be used to replace most of the expensive real experiments. Further, model parameters of advanced macroscopic models like the HAH model can be determined from virtual experiments, even for multiaxial deformation histories. It was also found that crystal plasticity modeling can be used to model anisotropic hardening more accurately by considering the backstress, similar to well-established macroscopic kinematic hardening models. It can be concluded that an efficient coupling of crystal plasticity models and the spectral solver leads to a significant reduction of the amount of real experiments needed to calibrate macroscopic models. This advantage leads also to a significant reduction of computational effort needed for the optimization of metal forming process. Further, due to the time efficient spectral solver used in the computation of the RVE models, detailed modeling of the microstructure are possible.

Keywords: anisotropic hardening, crystal plasticity, micro structure, spectral solver

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Authors: Sendi Zohra, Belhadjsalah Hedi, Labergere Carl, Saanouni Khemais

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The modeling of mechanical problems including both material and geometric nonlinearities with Finite Element Method (FEM) remains challenging. Meshless methods offer special properties to get rid of well-known drawbacks of the FEM. The main objective of Meshless Methods is to eliminate the difficulty of meshing and remeshing the entire structure by simply insertion or deletion of nodes, and alleviate other problems associated with the FEM, such as element distortion, locking and others. In this study, a robust numerical implementation of an Element Free Galerkin Method for an elastoplastic coupled to damage problem is presented. Several results issued from the numerical simulations by a DynamicExplicit resolution scheme are analyzed and critically compared with Element Finite Method results. Finally, different numerical examples are carried out to demonstrate the efficiency of this method.

Keywords: damage, dynamic explicit, elastoplasticity, isotropic hardening, meshless

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Authors: Un-Hwan Park, Jun-Hyeok Heo, In-Sung Lee, Tae-Hyeon Oh, Dae-Gyu Park

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Nonwoven fabric such as an automobile interior material becomes consists of several material layers required for the sound-absorbing function. Because several material layers, many experimental tuning is required to achieve the target of sound absorption. Therefore, a lot of time and money is spent in the development of the car interior materials. In this study, we present the method to predict the sound-absorbing performance of the various layers with physical properties of each material. and we will verify it with the measured value of a prototype. If the sound absorption can be estimated, it can be optimized without a number of tuning tests of the interiors. So, it can reduce the development cost and time during development

Keywords: automotive interior material, sound absorbing, optimization design, nonwoven fabric

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Authors: Yaser E. Greish, Emad F. Hindawy, Maryam S. Al Nehayan

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Introductory courses such as General Chemistry I, General Physics I and General Biology need special attention as students taking these courses are usually at their first year of the university. In addition to the language barrier for most of them, they also face other difficulties if these elementary courses are taught in the traditional way. Changing the routine method of teaching of these courses is therefore mandated. In this regard, podcasting of chemistry lectures was used as an add-on to the traditional and non-traditional methods of teaching chemistry to science and non-science students. Podcasts refer to video files that are distributed in a digital format through the Internet using personal computers or mobile devices. Pedagogical strategy is another way of identifying podcasts. Three distinct teaching approaches are evident in the current literature and include receptive viewing, problem-solving, and created video podcasts. The digital format and dispensing of video podcasts have stabilized over the past eight years, the type of podcasts vary considerably according to their purpose, degree of segmentation, pedagogical strategy, and academic focus. In this regard, the whole syllabus of 'General Chemistry I' course was developed as podcasts and were delivered to students throughout the semester. Students used the podcasted files extensively during their studies, especially as part of their preparations for exams. Feedback of students strongly supported the idea of using podcasting as it reflected its effect on the overall understanding of the subject, and a consequent improvement of their grades.

Keywords: podcasting, introductory course, interactivity, flipped classroom

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Authors: H. Ghodbane, A. A. Taleb, O. Kraa

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This paper presents geometric design of induction heating system. The objective of this design is to improve the temperature distribution in the load. The study of such a device requires the use of models or modeling representation, physical, mathematical, and numerical. This modeling is the basis of the understanding, the design, and optimization of these systems. The optimization technique is to find values of variables that maximize or minimize the objective function.

Keywords: optimization, modeling, geometric design system, temperature increase

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Authors: F. Jafari, S. GharehzadehShirazi, S. Khodabakhshi

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An efficient, simple, and environmentally benign procedure for the one-pot synthesis of dicoumarols was reported. The reaction entails the condensation of aryl glyoxals and 4-hydroxyxoumarin in the presence of catalytic amount of zinc oxide nanoparticles (ZnO NPs) as recyclable catalyst in aqueous media. High product yields and use of clean conditions are important factors of green chemistry.Part of our continued interest to achieve high atom economic reactions by the use safe catalysts. The reaction mixture was refluxed with catalytic amount (3 mol%) of zinc oxide nanoparticles.Reducing the amount of toxic waste and byproducts arising from chemical reactions is an important issue in the context of green chemistry. In comparison with commonly organic solvents, the aqueous media is cheaper and more environmentally friendly. Avoiding the use of organic solvents is an important way to prevent waste in chemical processes. In the context of green and sustainable chemistry, one ofthe most promising approaches is the use of water as the reaction media. In recent years, there has been increasing recognition that water is an attractive media for manyorganic reactions. Using water continues to attract wide attention among synthetic chemists in the design of new synthetic methods.

Keywords: zinc oxide, dicoumarol, aryl glyoxal, green chemistry, catalyst

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Authors: Hassan M. Al-Ahmadi, Hamad Bader Almobayedh

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Planning for urban transportation is essential for developing effective and sustainable transportation networks that meet the needs of various communities. Advanced modeling software is required for effective transportation planning, management, and optimization. This paper compares PTV VISUM, Aimsun, TransCAD, and Emme, four industry-leading software tools for transportation planning and modeling. Each software has strengths and limitations, and the project's needs, financial constraints, and level of technical expertise influence the choice of software. Transportation experts can design and improve urban transportation systems that are effective, sustainable, and meet the changing needs of their communities by utilizing these software tools.

Keywords: PTV VISUM, Aimsun, TransCAD, transportation modeling software

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Authors: Lauren Dawson, Sean Comber, Richard Sandford, Alan Tappin, Bruce Stockley

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The West Dart River is underperforming for Salmon (Salmo salar) survival rates due to acidified pH troughs under the European Water Framework Directive (2000/60/EC). These troughs have been identified as being caused by historic acid rain pollution which is being held in situ by peat bog presence at site and released during flushing events. Natural recovery has been deemed unlikely by the year 2020 using steady state water chemistry models and therefore a program of monitored calcium carbonate (CaCO3) introductions are being conducted to eliminate these troughs, which can drop to pH 2.93 (salmon survival – pH 5.5). The river should be naturally acidic (pH 5.5-6) due to the granite geology of Dartmoor and therefore the CaCO3 introductions are under new methodology (the encasing of the CaCO3 in permeable sacks) to ensure removal should the water pH rise above neutral levels. The water chemistry and ecology are undergoing comprehensive monitoring, including pH and turbidity levels, dissolved organic carbon and aluminum concentration and speciation, while the aquatic biota is being used to assess the potential water chemistry changes. While this project is ongoing, results from the preliminary field trial show only a temporary, localized increase in pH following CaCO3 introductions into the water column. However, changes to the water chemistry have only been identified in the West Dart after methodology adjustments to account for flow rates and spate-dissolution, though no long-term changes have so far been found in the ecology of the river. However, this is not necessarily a negative factor, as the aim of the study is to protect the current ecological communities and the natural pH of the river while remediating only the detrimental pH troughs.

Keywords: anthropogenic acidification recovery, calcium carbonate introductions, ecology monitoring, water chemistry monitoring

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Authors: Tsvetanka Filipova

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Entrepreneurial mindset learning (EML) is the combined process of instilling curiosity and invention, developing insight and value creation while building on other active pedagogy, such as project-based learning (PBL). It is essential to introduce students to chemistry and chemical engineering entrepreneurship in a manner that gives a holistic approach by first educating students on diverse entrepreneurial skills and then providing an opportunity to build their innovation. Chemistry and chemical engineering students have an opportunity to be engaged in an entrepreneurial class project in the Green Chemistry and Processes course at South Dakota Mines. The course provides future chemists and chemical engineers with the knowledge and skills required to enable them to design materials and processes in an environmentally benign way. This paper presents findings from implementing an open-ended design project in the Green Chemistry and Processes course. The goal of this team project is to have student teams design sustainable polymer materials to fulfill a need and/or opportunity related to a fictitious aerospace company that satisfies technical, safety, environmental, regulatory, economic, and social needs. Each student team is considered a start-up company charged with the task of designing sustainable polymer materials for aerospace applications. Through their work on the project, students utilize systems and entrepreneurial thinking in selecting their design project, being aware of the existent technologies (literature and patent search) and users and clients (connections), determining the goals and motivations (creating value), and what need or problem they are trying to address (curiosity). The project draws systems boundaries by focusing on student exploration of feedstocks to end-of-life of polymeric materials and products. Additional subtopics to explore are green processes for syntheses, green engineering for process design, and the economics of sustainable polymers designed for circularity. Project deliverables are team project reports and project presentations to a panel of industry, chemistry, and engineering professionals. Project deliverables are team project reports and project presentations to a panel of industry, chemistry, and engineering professionals. The impact of the entrepreneurial mindset project is evaluated through a student survey at the end of the semester. It has been found that the Innovative Solution project was excellent in promoting student curiosity, creativity, critical and systems thinking and teamwork. The results of this study suggest that incorporating EML positively impacted students’ professional skill development, their ability to understand and appreciate the socio-technical context of chemistry and engineering, and the cultivation of an entrepreneurial mindset to discover, evaluate and exploit opportunities.

Keywords: curriculum, entrepreneurial mindset learning, green chemistry and engineering, systems thinking

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Authors: Robert Kwame Kpaliba, Dennis Kpakpor Adotey, Yaw Serfor-Armah

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Increase in the oceanic carbon dioxide absorbance from the atmosphere due to climate change has led to appreciable change in the chemistry of the oceans. The change in oceanic pH referred to as ocean acidification poses multiple threats and stresses on marine species, biodiversity, goods and services, and livelihoods. Marine ecosystems are continuously threatened by plethora of natural and anthropogenic stressors including carbon dioxide (CO₂) emissions causing a lot of changes which has not been experienced for approximately 60 years. Little has been done in Africa as a whole and Ghana in particular to improve the understanding of the variations of the carbonate chemistry of seawater and the biophysical impacts of ocean acidification on security of seafood, nutrition, climate and environmental change. There is, therefore, the need for regular monitoring of carbonate chemistry of seawater along Ghana’s coastline to generate reliable data to aid marine policy formulation. Samples of seawater were collected thrice every month for a one-year period from five study sites for the various parameters to be analyzed. Analysis of the measured physico-chemical and the carbonate chemistry parameters was done using simple statistics. Correlation test and ANOVA were run on both of the physico-chemical and carbonate chemistry parameters. The carbonate chemistry parameters were measured using computer software programme (CO₂cal v4.0.9) except total alkalinity and pH. The study assessed the variability of seawater carbonate chemistry in selected portions of the Central Atlantic Coastline of Ghana (Tsokomey/Bortianor, Kokrobitey, Gomoa Nyanyanor, Gomoa Fetteh, and Senya Breku landing beaches) over a 1-year period (June 2016–May 2017). For physico-chemical parameters, there was insignificant variation in nitrate (NO₃⁻) (1.62 - 2.3 mg/L), ammonia (NH₃) (1.52 - 2.05 mg/L), and salinity (sal) (34.50 - 34.74 ppt). Carbonate chemistry parameters for all the five study sites showed significant variation: partial pressure of carbon dioxide (pCO₂) (414.08-715.5 µmol/kg), carbonate ion (CO₃²⁻) (115-157.92 µmol/kg), pH (7.9-8.12), total alkalinity (TA) (1711.8-1986 µmol/kg), total carbon dioxide (TCO₂) (1512.1 - 1792 µmol/kg), dissolved carbon dioxide (CO₂aq) (10.97-18.92 µmol/kg), Revelle Factor (RF) (9.62-11.84), aragonite (ΩAr) (0.75-1.48) and calcite (ΩCa) (1.08-2.14). The study revealed that the partial pressure of carbon dioxide and temperature did not have a significant effect on each other (r² = 0.31) (p-value = 0.0717). There was an appreciable effect of pH on dissolved carbon dioxide (r² = 0.921) (p-value = 0.0000). The variation between total alkalinity and dissolved carbon dioxide was appreciable (r² = 0.731) (p-value = 0.0008). There was a significant correlation between total carbon dioxide and dissolved carbon dioxide (r² = 0.852) (p-value = 0.0000). Revelle factor correlated strongly with dissolved carbon dioxide (r² = 0.982) (p-value = 0.0000). Partial pressure of carbon dioxide corresponds strongly with atmospheric carbon dioxide (r² = 0.9999) (p-value = 0.00000).

Keywords: carbonate chemistry, seawater, central atlantic coastline, Ghana, ocean acidification

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Authors: Ahmed Aboforn

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Butene-1 product is consider effectively raw material in Polyethylene production, however Oxygenates impurities existing will be effected ethylene/butene-1 copolymers synthesized through titanium-magnesium-supported Ziegler-Natta catalysts. Laterally, Petrochemical industries are challenge against poor quality of Butene-1 and other C4 mix – feedstock that reflected on business impact and production losing. In addition, propylene product suffering from contamination by oxygenates components and causing for lose production and plant upset of Polypropylene process plants. However, Multidimensional gas chromatography (MDGC) innovative analytical methodology is a chromatography technique used to separate complex samples, as mixing different functional group as Hydrocarbon and oxygenates compounds and have similar retention factors, by running the eluent through two or more columns instead of the customary single column. This analytical study striving to enhance the quality of Oxygenates analytical method, as monitoring the concentration of oxygenates with accurate and precise analytical method by utilizing multidimensional GC supported by Backflush technique and Flame Ionization Detector, which have high performance separation of hydrocarbon and Oxygenates; also improving the minimum detection limits (MDL) to detect the concentration <1.0 ppm. However different types of oxygenates as (Alcohols, Aldehyde, Ketones, Ester and Ether) may be determined in other Hydrocarbon streams asC3, C4-mix, until C12 mixture, supported by liquid injection auto-sampler.

Keywords: analytical chemistry, gas chromatography, petrochemicals, oxygenates

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Authors: A. Torokhti

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A new method of mathematical modeling of the distributed nonlinear system is developed. The system is represented by a combination of the set of spatially distributed sensors and the fusion center. Its mathematical model is obtained from the iterative procedure that converges to the model which is optimal in the sense of minimizing an associated cost function.

Keywords: mathematical modeling, non-linear system, spatially distributed sensors, fusion center

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Authors: Dong Wook Lee

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This paper describes a method for analyzing penetration for composite material using an explicit nonlinear Finite Element Analysis (FEA). This method may be used in the early stage of design for the protection of military vehicles, aircraft engines and nuclear power plant structures made of composite materials. This paper deals with simple ballistic penetration tests for composite materials and the FEA modeling method and results. The FEA was performed to interpret the ballistic field test phenomenon regarding the damage propagation in the structure subjected to local foreign object impact.

Keywords: computer aided engineering, finite element analysis, impact analysis, penetration analysis, composite material

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Authors: Satyananda Patra, Venugopal Rayasam

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The quality of pellets produced is affected by quality and type of green pellets, amount of addition of binders and fluxing agents along with the provided firing conditions. The green pellet quality depends upon chemistry, mineralogy and granulometry of fines used for pellet making, the feed size, its moisture content and porosity. During firing of green pellets, ingredients present within reacts to form different phases and microstructure. So in turn, physical and metallurgical properties of pellets are influenced by amount and type of binder and flux addition, induration time and temperature. During iron making process, the metallurgical properties of fired pellets are decided by the type and amount of these phases and their chemistry. Green pelletizing and induration studies have been already carried out with magnetite and hematite ore fines but for Indian iron ores of high alumina content showing different pelletizing characters, these studies cannot be directly interpreted. The main objective of proposed research work is to understand the green pelletizing process and determine the water bentonite interaction at different levels. Swelling behavior of bentonite and microstructure of the green pellet are investigated. Conversion of iron ore fines into pellets, the key raw material and process variables that influence the pellet quality needs to be identified and a correlation should be established between them.

Keywords: iron ore, pelletization, binders, green pellets, microstructure

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Authors: Erhan Çetin, Ali Kurşun, Şafak Aksoy, Merve Tunay Çetin

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The closed form study deal with elastic stress analysis of annular bi-material discs with variable thickness subjected to the mechanical and termomechanical loads. Those discs have many applications in the aerospace industry, such as gas turbines and gears. Those discs normally work under thermal and mechanical loads. Their life cycle can increase when stress components are minimized. Each material property is assumed to be isotropic. The results show that material combinations and thickness profiles play an important role in determining the responses of bi-material discs and an optimal design of those structures. Stress distribution is investigated and results are shown as graphs.

Keywords: bi-material discs, elastic stress analysis, mechanical loads, rotating discs

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Authors: Vallisree Sivathanu, Kumaraswamidhas Lakshmi Annamalai, Trupti Ranjan Lenka

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We report a tandem solar cell model with Silicon as the bottom cell absorber material and Cu₂BaSn(S, Se)₄(CBTSSe) as absorber material for the top cell. As a first step, the top and bottom cells were modelled and validated by comparison with the experiment. Once the individual cells are validated, then the tandem structure is modelled with Indium Tin Oxide(ITO) as conducting layer between the top and bottom cells. The tandem structure yielded better open circuit voltage and fill factor; however, the efficiency obtained is 7.01%. The top cell and the bottom cells are investigated with the help of electron-hole current density, photogeneration rate, and external quantum efficiency profiles. In order to minimize the various loss mechanisms in the tandem solar cell, the material parameters are optimized within experimentally achievable limits. Initially, the top cell optimization was carried out; then, the bottom cell is optimized for maximizing the light absorption, and upon minimizing the current and photon losses in the tandem structure, the maximum achievable efficiency is predicted to be 19.52%.

Keywords: CBTSSe, silicon, tandem, solar cell, device modeling, current losses, photon losses

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Authors: Larbi Hammadi, N. Boudjenane, N. Benhallou, R. Houjedje, R. Reffis, M. Belhadri

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Many of clays exhibited the thixotropic behavior in which, the apparent viscosity of material decreases with time of shearing at constant shear rate. The structural kinetic model (SKM) was used to characterize the thixotropic behavior of two different kinds of clays used in fabrication of ceramic. Clays selected for analysis represent the fluid and semisolid clays materials. The SKM postulates that the change in the rheological behavior is associated with shear-induced breakdown of the internal structure of the clays. This model for the structure decay with time at constant shear rate assumes nth order kinetics for the decay of the material structure with a rate constant.

Keywords: ceramic, clays, structural kinetic model, thixotropy, viscosity

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Authors: Zhanat Umarova

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Until the present time, modeling of the pores form influence on the hydraulic resistance of membranes and their permeability has not been analyzed. The aim of the given work is the theoretical consideration of the issue on the productivity of polymer membranes with the profile pores and determination of the optimum form of pores.

Keywords: modeling, polymer membranes, permeability, pore’s density

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Authors: Rizki Nor Amelia, Farida A. Setiawati

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This study aimed to: (1) describe the characteristics of teacher-made test instrument used to measure the ability of students’chemistry, and (2) identify the presence of the compability difficulty level set by teachers to difficulty level by empirical results. Based on these objectives, this study was a descriptive research. The analysis in this study used the Rasch model and Chi-square statistics. Analysis using Rasch Model was based on the response patterns of high school students to the teacher-made test instrument on chemistry subject Academic Year 2015/2016 in the Yogyakarta. The sample of this research were 358 students taken by cluster random sampling technique. The analysis showed that: (1) a teacher-made tests instrument has a medium on the mean difficulty level. This instrument is capable to measure the ability on the interval of -0,259 ≤ θ ≤ 0,659 logit. Maximum Test Information Function obtained at 18.187 on the ability +0,2 logit; (2) 100% items categorized either as easy or difficult by rasch model is match with the teachers’ judgment; while 37 items are categorized according to rasch model which 8.10% and 10.81% categorized as easy and difficult items respectively according to the teachers, the others are medium categorized. Overall, the distribution of the level of difficulty formulated by the teachers has the distinction (not match) to the level of difficulty based on the empirical results.

Keywords: chemistry, items parameter fitness, Rasch model, teacher-made test

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Authors: O. Hassoon, M. Tarfoui, A. El Malk

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Fiber Bragg optic sensor embedded in composite material to detect and monitor the damage which is occur in composite structure. In this paper we deal with the mode-Ι delamination to determine the resistance of material to crack propagation, and use the coupling mode theory and T-matrix method to simulating the FBGs spectrum for both uniform and non-uniform strain distribution. The double cantilever beam test which is modeling in FEM to determine the Longitudinal strain, there are two models which are used, the first is the global half model, and the second the sub-model to represent the FBGs with refine mesh. This method can simulate the damage in the composite structure and converting the strain to wavelength shifting of the FBG spectrum.

Keywords: fiber bragg grating, delamination detection, DCB, FBG spectrum, structure health monitoring

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Authors: Salma El Aimani

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Freshwater is an essential material in our daily life; its availability is on the decline due to population growth and climate change. To meet the demand for fresh water in regions where reserves are insufficient, several countries have adopted seawater desalination. Several physical methods allow the production of fresh water from seawater; among these methods are distillation and reverse osmosis, and there is great potential to use renewable energy sources such as solar Photovoltaics. The work presented in this paper consists of three parts. First, the generalities of desalination technologies will be presented. The second part is devoted to the presentation of different water desalination systems combined with renewable energy and their benefits and drawbacks on different sides. In the third part, we will perform a modeling of a PV water desalination system under Matlab Simulink software. Then, according to the obtained simulation results, we conclude this paper with the prospects of the presented work.

Keywords: reverse-osmosis, desalination, modelling, ‎irradiation, Matlab

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Authors: Maria Pintea, Nigel Mason

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Induced chemistry is one of the newest pathways in the nanotechnology field with applications in the focused electron beam induced processes for deposition of nm scale structures. Si(OPr)₄ and Ti(OEt)₄ are two of the precursors that have not been so extensively researched, though highly sought for semiconductor and medical applications fields, the two compounds make good candidates for FEBIP and are the subject of velocity slice map imaging analysis for deposition purposes, offering information on kinetic energies, fragmentation channels, and angular distributions. The velocity slice map imaging technique is a method used for the characterization of molecular dynamics of the molecule and the fragmentation channels as a result of induced chemistry. To support the gas-phase analysis, Meso-Bio-Nano simulations of irradiation dynamics studies are employed with final results on Fe(CO)₅ deposited on various substrates. The software is capable of running large scale simulations for complex biomolecular, nano- and mesoscopic systems with applications to thermos-mechanical DNA damage, complex materials, gases, nanoparticles for cancer research and deposition applications for nanotechnology, using a large library of classical potentials, many-body force fields, molecular force fields involved in the classical molecular dynamics.

Keywords: focused electron beam induced deposition, FEBID, induced chemistry, molecular dynamics, velocity map slice imaging

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Authors: Raz Flieshman, Adam Michael Altenbuchner, Jörg Krüger

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This paper presents an approach to optimizing the Fused Deposition Modeling (FDM) 3D printing process through a preprocess calibration routine of printing parameters. The core of this method involves the use of a low-cost thermal sensor capable of measuring tempera-tures within the range of -20 to 500 degrees Celsius for detailed process observation. The calibration process is conducted by printing a predetermined path while varying the process parameters through machine instructions (g-code). This enables the extraction of critical thermal, dimensional, and surface properties along the printed path. The calibration routine utilizes computer vision models to extract features and metrics from the thermal images, in-cluding temperature distribution, layer adhesion quality, surface roughness, and dimension-al accuracy and consistency. These extracted properties are then analyzed to optimize the process parameters to achieve the desired qualities of the printed material. A significant benefit of this calibration method is its potential to create printing parameter profiles for new polymer and composite materials, thereby enhancing the versatility and application range of FDM 3D printing. The proposed method demonstrates significant potential in enhancing the precision and reliability of FDM 3D printing, making it a valuable contribution to the field of additive manufacturing.

Keywords: FDM 3D printing, preprocess calibration, thermal sensor, process optimization, additive manufacturing, computer vision, material profiles

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Authors: Ridha Salhi, Mondher Labidi, Fethi Choubani

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Metamaterials have attracted much attention in recent years because of their electromagnetic exquisite proprieties. We will present, in this paper, the modeling of three metamaterial structures by equivalent circuit model. We begin by modeling the SRR (Split Ring Resonator), then we model the HIS (High Impedance Surfaces), and finally, we present the model of the CPW (Coplanar Wave Guide). In order to validate models, we compare the results obtained by an equivalent circuit models with numerical simulation.

Keywords: metamaterials, SRR, HIS, CPW, IDC

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Authors: M. M. Wagh, V. V. Kulkarni

Abstract:

The rising economic activities, growing population and improving living standards of world have led to a steady growth in its appetite for quality and quantity of energy services. As the economy expands the electricity demand is going to grow further, increasing the challenges of the more generation and stresses on the utility grids. Appropriate energy model will help in proper utilization of the locally available renewable energy sources such as solar, wind, biomass, small hydro etc. to integrate in the available grid, reducing the investments in energy infrastructure. Further to these new technologies like smart grids, decentralized energy planning, energy management practices, energy efficiency are emerging. In this paper, the attempt has been made to study and review the recent energy planning models, energy forecasting models, and renewable energy integration models. In addition, various modeling techniques and tools are reviewed and discussed.

Keywords: energy modeling, integration of renewable energy, energy modeling tools, energy modeling techniques

Procedia PDF Downloads 349

Authors: In-Sung Lee, Un-Hwan Park, Jun-Hyeok Heo, Tae-Hyeon Oh, Dae-Gyu Park

Abstract:

Statistical Energy Analysis is to be the most effective CAE Method for air-born noise analysis in the Automotive area. This study deals with a method to predict the noise level inside of the car under the steady-state condition using the SEA model of car for air-born noise analysis. We can identify weakened part due to the acoustic material properties using it. Therefore, it is useful for the material structural design.

Keywords: air-born noise, material structural design, acoustic material properties, absorbing

Procedia PDF Downloads 426