Search results for: estimation of properties of the model
Commenced in January 2007
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Edition: International
Paper Count: 24938

Search results for: estimation of properties of the model

21518 Physics-Informed Machine Learning for Displacement Estimation in Solid Mechanics Problem

Authors: Feng Yang

Abstract:

Machine learning (ML), especially deep learning (DL), has been extensively applied to many applications in recently years and gained great success in solving different problems, including scientific problems. However, conventional ML/DL methodologies are purely data-driven which have the limitations, such as need of ample amount of labelled training data, lack of consistency to physical principles, and lack of generalizability to new problems/domains. Recently, there is a growing consensus that ML models need to further take advantage of prior knowledge to deal with these limitations. Physics-informed machine learning, aiming at integration of physics/domain knowledge into ML, has been recognized as an emerging area of research, especially in the recent 2 to 3 years. In this work, physics-informed ML, specifically physics-informed neural network (NN), is employed and implemented to estimate the displacements at x, y, z directions in a solid mechanics problem that is controlled by equilibrium equations with boundary conditions. By incorporating the physics (i.e. the equilibrium equations) into the learning process of NN, it is showed that the NN can be trained very efficiently with a small set of labelled training data. Experiments with different settings of the NN model and the amount of labelled training data were conducted, and the results show that very high accuracy can be achieved in fulfilling the equilibrium equations as well as in predicting the displacements, e.g. in setting the overall displacement of 0.1, a root mean square error (RMSE) of 2.09 × 10−4 was achieved.

Keywords: deep learning, neural network, physics-informed machine learning, solid mechanics

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21517 Nanostructured Multi-Responsive Coatings for Tuning Surface Properties

Authors: Suzanne Giasson, Alberto Guerron

Abstract:

Stimuli-responsive polymer coatings can be used as functional elements in nanotechnologies, such as valves in microfluidic devices, as membranes in biomedical engineering, as substrates for the culture of biological tissues or in developing nanomaterials for targeted therapies in different diseases. However, such coatings usually suffer from major shortcomings, such as a lack of selectivity and poor environmental stability. The study will present multi-responsive hierarchical and hybrid polymer-based coatings aiming to overcome some of these limitations. Hierarchical polymer coatings, consisting of two-dimensional arrays of thermo-responsive cationic PNIPAM-based microgels and surface-functionalized with non-responsive or pH-responsive polymers, were covalently grafted to substrates to tune the surface chemistry and the elasticity of the surface independently using different stimuli. The characteristic dimensions (i.e., layer thickness) and surface properties (i.e., adhesion, friction) of the microgel coatings were assessed using the Surface Forces Apparatus. The ability to independently control the swelling and surface properties using temperature and pH as triggers were investigated for microgels in aqueous suspension and microgels immobilized on substrates. Polymer chain grafting did not impede the ability of cationic PNIPAM microgels to undergo a volume phase transition above the VPTT, either in suspension or immobilized on a substrate. Due to the presence of amino groups throughout the entirety of the microgel polymer network, the swelling behavior was also pH dependent. However, the thermo-responsive swelling was more significant than the pH-triggered one. The microgels functionalized with PEG exhibited the most promising behavior. Indeed, the thermo-triggered swelling of microgel-co-PEG did not give rise to changes in the microgel surface properties (i.e., surface potential and adhesion) within a wide range of pH values. It was possible for the immobilized microgel-co-PEG to undergo a volume transition (swelling/shrinking) with no change in adhesion, suggesting that the surface of the thermal-responsive microgels remains rather hydrophilic above the VPTT. This work confirms the possibility of tuning the swelling behavior of microgels without changing the adhesive properties. Responsive surfaces whose swelling properties can be reversibly and externally altered over space and time regardless of the surface chemistry are very innovative and will enable revolutionary advances in technologies, particularly in biomedical surface engineering and microfluidics, where advanced assembly of functional components is increasingly required.

Keywords: responsive materials, polymers, surfaces, cell culture

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21516 Electrical and Optical Properties of Polyaniline: Cadmium Sulphide Quantum Dots Nanocomposites

Authors: Akhtar Rasool, Tasneem Zahra Rizvi

Abstract:

In this study, a series of the cadmium sulphide quantum dots/polyaniline nanocomposites with varying compositions were prepared by in-situ polymerization technique and were characterized using X-ray diffraction and Fourier transform infrared spectroscopy. The surface morphology was studied by scanning electron microscopy. UV-Visible spectroscopy was used to find out the energy band gap of the nanoparticles and the nanocomposites. Temperature dependence of DC electrical conductivity and temperature and frequency dependence of AC conductivity were investigated to study the charge transport mechanism in the nanocomposites. DC conductivity was found to be a typical for a semiconducting behavior following Mott’s 1D variable range hoping model. The frequency dependent AC conductivity followed the universal power law.

Keywords: conducting polymers, nanocomposites, polyaniline composites, quantum dots

Procedia PDF Downloads 243
21515 Conceptual Model for Logistics Information System

Authors: Ana María Rojas Chaparro, Cristian Camilo Sarmiento Chaves

Abstract:

Given the growing importance of logistics as a discipline for efficient management of materials flow and information, the adoption of tools that permit to create facilities in making decisions based on a global perspective of the system studied has been essential. The article shows how from a concepts-based model is possible to organize and represent in appropriate way the reality, showing accurate and timely information, features that make this kind of models an ideal component to support an information system, recognizing that information as relevant to establish particularities that allow get a better performance about the evaluated sector.

Keywords: system, information, conceptual model, logistics

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21514 Automatic Flood Prediction Using Rainfall Runoff Model in Moravian-Silesian Region

Authors: B. Sir, M. Podhoranyi, S. Kuchar, T. Kocyan

Abstract:

Rainfall-runoff models play important role in hydrological predictions. However, the model is only one part of the process for creation of flood prediction. The aim of this paper is to show the process of successful prediction for flood event (May 15–May 18 2014). The prediction was performed by rainfall runoff model HEC–HMS, one of the models computed within Floreon+ system. The paper briefly evaluates the results of automatic hydrologic prediction on the river Olše catchment and its gages Český Těšín and Věřňovice.

Keywords: flood, HEC-HMS, prediction, rainfall, runoff

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21513 Classification of Generative Adversarial Network Generated Multivariate Time Series Data Featuring Transformer-Based Deep Learning Architecture

Authors: Thrivikraman Aswathi, S. Advaith

Abstract:

As there can be cases where the use of real data is somehow limited, such as when it is hard to get access to a large volume of real data, we need to go for synthetic data generation. This produces high-quality synthetic data while maintaining the statistical properties of a specific dataset. In the present work, a generative adversarial network (GAN) is trained to produce multivariate time series (MTS) data since the MTS is now being gathered more often in various real-world systems. Furthermore, the GAN-generated MTS data is fed into a transformer-based deep learning architecture that carries out the data categorization into predefined classes. Further, the model is evaluated across various distinct domains by generating corresponding MTS data.

Keywords: GAN, transformer, classification, multivariate time series

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21512 Implementation of IWA-ASM1 Model for Simulating the Wastewater Treatment Plant of Beja by GPS-X 5.1

Authors: Fezzani Boubaker

Abstract:

The modified activated sludge model (ASM1 or Mantis) is a generic structured model and a common platform for dynamic simulation of varieties of aerobic processes for optimization and upgrading of existing plants and for new facilities design. In this study, the modified ASM1 included in the GPS-X software was used to simulate the wastewater treatment plant (WWTP) of Beja treating domestic sewage mixed with baker‘s yeast factory effluent. The results of daily measurements and operating records were used to calibrate the model. A sensitivity and an automatic optimization analysis were conducted to determine the most sensitive and optimal parameters. The results indicated that the ASM1 model could simulate with good accuracy: the COD concentration of effluents from the WWTP of Beja for all months of the year 2012. In addition, it prevents the disruption observed at the output of the plant by injecting the baker‘s yeast factory effluent at high concentrations varied between 20 and 80 g/l.

Keywords: ASM1, activated sludge, baker’s yeast effluent, modelling, simulation, GPS-X 5.1 software

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21511 The Future of Insurance: P2P Innovation versus Traditional Business Model

Authors: Ivan Sosa Gomez

Abstract:

Digitalization has impacted the entire insurance value chain, and the growing movement towards P2P platforms and the collaborative economy is also beginning to have a significant impact. P2P insurance is defined as innovation, enabling policyholders to pool their capital, self-organize, and self-manage their own insurance. In this context, new InsurTech start-ups are emerging as peer-to-peer (P2P) providers, based on a model that differs from traditional insurance. As a result, although P2P platforms do not change the fundamental basis of insurance, they do enable potentially more efficient business models to be established in terms of ensuring the coverage of risk. It is therefore relevant to determine whether p2p innovation can have substantial effects on the future of the insurance sector. For this purpose, it is considered necessary to develop P2P innovation from a business perspective, as well as to build a comparison between a traditional model and a P2P model from an actuarial perspective. Objectives: The objectives are (1) to represent P2P innovation in the business model compared to the traditional insurance model and (2) to establish a comparison between a traditional model and a P2P model from an actuarial perspective. Methodology: The research design is defined as action research in terms of understanding and solving the problems of a collectivity linked to an environment, applying theory and best practices according to the approach. For this purpose, the study is carried out through the participatory variant, which involves the collaboration of the participants, given that in this design, participants are considered experts. For this purpose, prolonged immersion in the field is carried out as the main instrument for data collection. Finally, an actuarial model is developed relating to the calculation of premiums that allows for the establishment of projections of future scenarios and the generation of conclusions between the two models. Main Contributions: From an actuarial and business perspective, we aim to contribute by developing a comparison of the two models in the coverage of risk in order to determine whether P2P innovation can have substantial effects on the future of the insurance sector.

Keywords: Insurtech, innovation, business model, P2P, insurance

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21510 Modelling Enablers of Service Using ISM: Implications for Quality Improvements in Healthcare Sector of UAE

Authors: Flevy Lasrado

Abstract:

Purpose: The purpose of this paper is to show the relationship between the service quality dimensions and model them to propose quality improvements using interpretive structural modelling (ISM). Methodology: This paper used an interpretive structural modelling (ISM). The data was collected from the expert opinions that included a questionnaire. The detailed method of using ISM is discussed in the paper. Findings: The present research work provides an ISM based model to understand the relationships among the service quality dimensions. Practical implications or Original Value: An ISM based model has been developed for healthcare facility for improving customer satisfaction and increasing market share. Although there is lot of research on SERVQUAL model adapted to healthcare sector, no study has been done to understand the interactions among these dimensions. So the major contribution of this research work is the development of contextual relationships among identified variables through a systematic framework. The present research work provides an ISM based model to understand the relationships among the service quality dimensions.

Keywords: SERQUAL, healthcare, quality, service quality

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21509 Supply, Trade-offs, and Synergies Estimation for Regulating Ecosystem Services of a Local Forest

Authors: Jang-Hwan Jo

Abstract:

The supply management of ecosystem services of local forests is an essential issue as it is linked to the ecological welfare of local residents. This study aims to estimate the supply, trade-offs, and synergies of local forest regulating ecosystem services using a land cover classification map (LCCM) and a forest types map (FTM). Rigorous literature reviews and Expert Delphi analysis were conducted using the detailed variables of 1:5,000 LCCM and FTM. Land-use scoring method and Getis-Ord Gi* Analysis were utilized on detailed variables to propose a method for estimating supply, trade-offs, and synergies of the local forest regulating ecosystem services. The analysis revealed that the rank order (1st to 5th) of supply of regulating ecosystem services was Erosion prevention, Air quality regulation, Heat island mitigation, Water quality regulation, and Carbon storage. When analyzing the correlation between defined services of the entire city, almost all services showed a synergistic effect. However, when analyzing locally, trade-off effects (Heat island mitigation – Air quality regulation, Water quality regulation – Air quality regulation) appeared in the eastern and northwestern forest areas. This suggests the need to consider not only the synergy and trade-offs of the entire forest between specific ecosystem services but also the synergy and trade-offs of local areas in managing the regulating ecosystem services of local forests. The study result can provide primary data for the stakeholders to determine the initial conditions of the planning stage when discussing the establishment of policies related to the adjustment of the supply of regulating ecosystem services of the forests with limited access. Moreover, the study result can also help refine the estimation of the supply of the regulating ecosystem services with the availability of other forms of data.

Keywords: ecosystem service, getis ord gi* analysis, land use scoring method, regional forest, regulating service, synergies, trade-offs

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21508 Predicting Financial Distress in South Africa

Authors: Nikki Berrange, Gizelle Willows

Abstract:

Business rescue has become increasingly popular since its inclusion in the Companies Act of South Africa in May 2011. The Alternate Exchange (AltX) of the Johannesburg Stock Exchange has experienced a marked increase in the number of companies entering business rescue. This study sampled twenty companies listed on the AltX to determine whether Altman’s Z-score model for emerging markets (ZEM) or Taffler’s Z-score model is a more accurate model in predicting financial distress for small to medium size companies in South Africa. The study was performed over three different time horizons; one, two and three years prior to the event of financial distress, in order to determine how many companies each model predicted would be unlikely to succeed as well as the predictive ability and accuracy of the respective models. The study found that Taffler’s Z-score model had a greater ability at predicting financial distress from all three-time horizons.

Keywords: Altman’s ZEM-score, Altman’s Z-score, AltX, business rescue, Taffler’s Z-score

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21507 Interconnected Market Hypothesis: A Conceptual Model of Individualistic, Information-Based Interconnectedness

Authors: James Kinsella

Abstract:

There is currently very little understanding of how the interaction between in- vestors, consumers, the firms (agents) affect a) the transmission of information, and b) the creation and transfer of value and wealth between these two groups. Employing scholarly ideas from multiple research areas (behavioural finance, emotional finance, econo-biology, and game theory) we develop a conceptual the- oretic model (the ‘bow-tie’ model) as a framework for considering this interaction. Our bow-tie model views information transfer, value and wealth creation, and transfer through the lens of “investor-consumer connection facilitated through the communicative medium of the ‘firm’ (agents)”. We confront our bow-tie model with theoretical and practical examples. Next, we utilise consumer and business confidence data alongside index data, to conduct quantitative analy- sis, to support our bow-tie concept, and to introduce the concept of “investor- consumer connection”. We highlight the importance of information persuasiveness, knowledge, and emotional categorization of characteristics in facilitating a communicative relationship between investors, consumers, and the firm (agents), forming academic and practical applications of the conceptual bow-tie model, alongside applications to wider instances, such as those seen within the Covid-19 pandemic.

Keywords: behavioral finance, emotional finance, economy-biology, social mood

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21506 Academic Staff Recruitment in Islamic University: A Proposed Holistic Model

Authors: Syahruddin Sumardi, Indra Fajar Alamsyah, Junaidah Hashim

Abstract:

This study attempts to explore and presents a proposed recruitment model in Islamic university which aligned with holistic role. It is a conceptual paper in nature. In turn, this study is designed to utilize exploratory approach. Literature and document review that related to this topic are used as the methods to analyse the content found. Recruitment for any organization is fundamental to achieve its goal effectively. Staffing in universities is vital due to the importance role of lecturers. Currently, Islamic universities still adopt the common process of recruitment for their academic staffs. Whereas, they have own characteristics which are embedded in their institutions. Furthermore, the FCWC (Foundation, Capability, Worldview and Commitment) model of recruitment proposes to suit the holistic character of Islamic university. Further studies are required to empirically validate the concept through systematic investigations. Additionally, measuring this model by a designed means is appreciated. The model provides the map and alternative tool of recruitment for Islamic universities to determine the process of recruitment which can appropriate their institutions. In addition, it also allows stakeholders and policy makers to consider regarding Islamic values that should inculcate in the Islamic higher learning institutions. This study initiates a foundational contribution for an early sequence of research.

Keywords: academic staff, Islamic values, recruitment model, university

Procedia PDF Downloads 157
21505 DFT Study of Secondary Phase of Cu2ZnSnS4 in Solar Cell: Cu2SnS3

Authors: Mouna Mesbahi, M. Loutfi Benkhedir

Abstract:

In CZTS films solar cell, the preferable reaction between Cu and sulfur vapor was likely to be induced by out diffusion of the bottom Cu component to the surface; this would lead to inhomogeneous distribution of the Cu component to form the Cu2SnS3 secondary phase and formation of many voids and crevices in the resulting CZTS film; which is also the cause of the decline in performance. In this work we study the electronic and optical properties of Cu2SnS3. For this purpose we used the Wien2k code based on the theory of density functional theory (DFT) with the modified Becke-Johnson exchange potential mBJ and the Hubbard potential individually or combined. We have found an energy gap 0.92 eV. The results are in good agreement with experimental results.

Keywords: Cu2SnS3, DFT, electronic and optical properties, mBJ+U, WIEN2K

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21504 Physicochemical and Sensory Properties of Gluten-Free Semolina Produced from Blends of Cassava, Maize and Rice

Authors: Babatunde Stephen Oladeji, Gloria Asuquo Edet

Abstract:

The proximate, functional, pasting, and sensory properties of semolina from blends of cassava, maize, and rice were investigated. Cassava, maize, and rice were milled and sieved to pass through a 1000 µm sieve, then blended in the following ratios to produce five samples; FS₁ (40:30:30), FS₂ (20:50:30), FS₃ (25:25:50), FS₄ (34:33:33) and FS₅ (60:20:20) for cassava, maize, and rice, respectively. A market sample of wheat semolina labeled as FSc served as the control. The proximate composition, functional properties, pasting profile, and sensory characteristics of the blends were determined using standard analytical methods. The protein content of the samples ranged from 5.66% to 6.15%, with sample FS₂ having the highest value and being significantly different (p ≤ 0.05). The bulk density of the formulated samples ranged from 0.60 and 0.62 g/ml. The control (FSc) had a higher bulk density of 0.71 g/ml. The water absorption capacity of both the formulated and control samples ranged from 0.67% to 2.02%, with FS₃ having the highest value and FSc having the lowest value (0.67%). The peak viscosity of the samples ranged from 60.83-169.42 RVU, and the final viscosity of semolina samples ranged from 131.17 to 235.42 RVU. FS₅ had the highest overall acceptability score (7.46), but there was no significant difference (p ≤ 0.05) from other samples except for FS₂ (6.54) and FS₃ (6.29). This study establishes that high-quality and consumer-acceptable semolina that is comparable to the market sample could be produced from blends of cassava, maize, and rice.

Keywords: semolina, gluten, celiac disease, wheat allergies

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21503 Leadership Process Model: A Way to Provide Guidance in Dealing with the Key Challenges Within the Organisation

Authors: Rawaa El Ayoubi

Abstract:

Many researchers, academics and practitioners have developed leadership theories during the 20th century. This substantial effort has built more leadership theories, generating considerable organisational research on leadership models in contemporary literature. This paper explores the stages and drivers of leadership theory evolution based on the researcher’s personal conclusions and review of leadership theories. The purpose of this paper is to create a Leadership Process Model (LPM) that can provide guidance in dealing with the key challenges within the organisation. This integrative model of organisational leadership is based on inner meaning, leader values and vision. It further addresses the relationships between leadership theory, practice and development, exploring why challenges exist within the field of leadership theory and how these challenges can be mitigated.

Keywords: leadership challenges, leadership process model, leadership |theories, organisational leadership, paradigm development

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21502 Procedure Model for Data-Driven Decision Support Regarding the Integration of Renewable Energies into Industrial Energy Management

Authors: M. Graus, K. Westhoff, X. Xu

Abstract:

The climate change causes a change in all aspects of society. While the expansion of renewable energies proceeds, industry could not be convinced based on general studies about the potential of demand side management to reinforce smart grid considerations in their operational business. In this article, a procedure model for a case-specific data-driven decision support for industrial energy management based on a holistic data analytics approach is presented. The model is executed on the example of the strategic decision problem, to integrate the aspect of renewable energies into industrial energy management. This question is induced due to considerations of changing the electricity contract model from a standard rate to volatile energy prices corresponding to the energy spot market which is increasingly more affected by renewable energies. The procedure model corresponds to a data analytics process consisting on a data model, analysis, simulation and optimization step. This procedure will help to quantify the potentials of sustainable production concepts based on the data from a factory. The model is validated with data from a printer in analogy to a simple production machine. The overall goal is to establish smart grid principles for industry via the transformation from knowledge-driven to data-driven decisions within manufacturing companies.

Keywords: data analytics, green production, industrial energy management, optimization, renewable energies, simulation

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21501 Comparison of the Distillation Curve Obtained Experimentally with the Curve Extrapolated by a Commercial Simulator

Authors: Lívia B. Meirelles, Erika C. A. N. Chrisman, Flávia B. de Andrade, Lilian C. M. de Oliveira

Abstract:

True Boiling Point distillation (TBP) is one of the most common experimental techniques for the determination of petroleum properties. This curve provides information about the performance of petroleum in terms of its cuts. The experiment is performed in a few days. Techniques are used to determine the properties faster with a software that calculates the distillation curve when a little information about crude oil is known. In order to evaluate the accuracy of distillation curve prediction, eight points of the TBP curve and specific gravity curve (348 K and 523 K) were inserted into the HYSYS Oil Manager, and the extended curve was evaluated up to 748 K. The methods were able to predict the curve with the accuracy of 0.6%-9.2% error (Software X ASTM), 0.2%-5.1% error (Software X Spaltrohr).

Keywords: distillation curve, petroleum distillation, simulation, true boiling point curve

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21500 Study of the Green Composite Jute/Epoxy

Authors: A. Mir, C. Aribi, B. Bezzazi

Abstract:

Work presented is interested in the characterization of the quasistatic mechanical properties and in fatigue of a composite laminated in jute/epoxy. The natural fibers offer promising prospects thanks to their interesting specific properties, because of their low density, but also with their bio deterioration. Several scientific studies highlighted the good mechanical resistance of the vegetable fiber composites reinforced, even after several recycling. Because of the environmental standards which become increasingly severe, one attends the emergence of eco-materials at the base of natural fibers such as flax, bamboo, hemp, sisal, jute. The fatigue tests on elementary vegetable fibers show an increase of about 60% of the rigidity of elementary fibers of hemp subjected to cyclic loading. In this study, the test-tubes manufactured by the method infusion have sequences of stacking of 0/90° and ± 45° for the shearing and tensile tests. The quasistatic tests reveal a variability of the mechanical properties of about 8%. The tensile fatigue tests were carried out for levels of constraints equivalent to half of the ultimate values of the composite. Once the fatigue tests carried out for well-defined values of cycles, a series of static tests of traction type highlights the influence of the number of cycles on the quasi static mechanical behavior of the laminate jute/epoxy.

Keywords: jute, epoxy resin, mechanical, static, dynamic behavior

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21499 Structural Evolution of Electrodeposited Ni Coating on Ti-6Al-4V Alloy during Heat Treatment

Authors: M. Abdoos, A. Amadeh, M. Adabi

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In recent decades, the use of titanium and its alloys due to their high mechanical properties, light weight and their corrosion resistance has increased in military and industry applications. However, the poor surface properties can limit their widely usage. Many researches were carried out to improve their surface properties. The most effective technique is based on solid-state diffusion of elements that can form intermetallic compounds with the substrate. In the present work, inter-diffusion of nickel and titanium and formation of Ni-Ti intermetallic compounds in nickel-coated Ti-6Al-4V alloy have been studied. Initially, nickel was electrodeposited on the alloy using Watts bath at a current density of 20 mA/cm2 for 1 hour. The coated specimens were then heat treated in a tubular furnace under argon atmosphere at different temperatures near Ti β-transus to maximize the diffusion rate for various durations in order to improve the surface properties of the Ti-6Al-4V alloy. The effect of temperature and time on the thickness of diffusion layer and characteristics of intermetallic phases was studied by means of scanning electron microscope (SEM) equipped with energy dispersive X-ray spectrometer (EDS) and microhardness test. The results showed that a multilayer structure was formed after heat treatment: an outer layer of remaining nickel, an area of intermetallic layers with different compositions and solid solution of Ni-Ti. Three intermetallic layers was detected by EDS analysis, namely an outer layer with about 75 at.% Ni (Ni3Ti), an intermediate layer with 50 at.% Ni (NiTi) and finally an inner layer with 36 at.% Ni (NiTi2). It was also observed that the increase in time or temperature led to the formation of thicker intermetallic layers. Meanwhile, the microhardness of heat treated samples increased with formation of Ni-Ti intermetallics; however, its value depended on heat treatment parameters.

Keywords: heat treatment, microhardness, Ni coating, Ti-6Al-4V

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21498 The Non-Uniqueness of Partial Differential Equations Options Price Valuation Formula for Heston Stochastic Volatility Model

Authors: H. D. Ibrahim, H. C. Chinwenyi, T. Danjuma

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An option is defined as a financial contract that provides the holder the right but not the obligation to buy or sell a specified quantity of an underlying asset in the future at a fixed price (called a strike price) on or before the expiration date of the option. This paper examined two approaches for derivation of Partial Differential Equation (PDE) options price valuation formula for the Heston stochastic volatility model. We obtained various PDE option price valuation formulas using the riskless portfolio method and the application of Feynman-Kac theorem respectively. From the results obtained, we see that the two derived PDEs for Heston model are distinct and non-unique. This establishes the fact of incompleteness in the model for option price valuation.

Keywords: Black-Scholes partial differential equations, Ito process, option price valuation, partial differential equations

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21497 Predicting the Effect of Silicon Electrode Design Parameters on Thermal Performance of a Lithium-Ion Battery

Authors: Harika Dasari, Eric Eisenbraun

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The present study models the role of electrode structural characteristics on the thermal behavior of lithium-ion batteries. Preliminary modeling runs have employed a 1D lithium-ion battery coupled to a two-dimensional axisymmetric model using silicon as the battery anode material. The two models are coupled by the heat generated and the average temperature. Our study is focused on the silicon anode particle sizes and it is observed that silicon anodes with nano-sized particles reduced the temperature of the battery in comparison to anodes with larger particles. These results are discussed in the context of the relationship between particle size and thermal transport properties in the electrode.

Keywords: particle size, NMC, silicon, heat generation, separator

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21496 Robustness Analysis of the Carbon and Nitrogen Co-Metabolism Model of Mucor mucedo

Authors: Nahid Banihashemi

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An emerging important area of the life sciences is systems biology, which involves understanding the integrated behavior of large numbers of components interacting via non-linear reaction terms. A centrally important problem in this area is an understanding of the co-metabolism of protein and carbohydrate, as it has been clearly demonstrated that the ratio of these metabolites in diet is a major determinant of obesity and related chronic disease. In this regard, we have considered a systems biology model for the co-metabolism of carbon and nitrogen in colonies of the fungus Mucor mucedo. Oscillations are an important diagnostic of underlying dynamical processes of this model. The maintenance of specific patterns of oscillation and its relation to the robustness of this system are the important issues which have been targeted in this paper. In this regard, parametric sensitivity approach as a theoretical approach has been considered for the analysis of the robustness of this model. As a result, the parameters of the model which produce the largest sensitivities have been identified. Furthermore, the largest changes that can be made in each parameter of the model without losing the oscillations in biomass production have been computed. The results are obtained from the implementation of parametric sensitivity analysis in Matlab.

Keywords: system biology, parametric sensitivity analysis, robustness, carbon and nitrogen co-metabolism, Mucor mucedo

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21495 Allometric Models for Biomass Estimation in Savanna Woodland Area, Niger State, Nigeria

Authors: Abdullahi Jibrin, Aishetu Abdulkadir

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The development of allometric models is crucial to accurate forest biomass/carbon stock assessment. The aim of this study was to develop a set of biomass prediction models that will enable the determination of total tree aboveground biomass for savannah woodland area in Niger State, Nigeria. Based on the data collected through biometric measurements of 1816 trees and destructive sampling of 36 trees, five species specific and one site specific models were developed. The sample size was distributed equally between the five most dominant species in the study site (Vitellaria paradoxa, Irvingia gabonensis, Parkia biglobosa, Anogeissus leiocarpus, Pterocarpus erinaceous). Firstly, the equations were developed for five individual species. Secondly these five species were mixed and were used to develop an allometric equation of mixed species. Overall, there was a strong positive relationship between total tree biomass and the stem diameter. The coefficient of determination (R2 values) ranging from 0.93 to 0.99 P < 0.001 were realised for the models; with considerable low standard error of the estimates (SEE) which confirms that the total tree above ground biomass has a significant relationship with the dbh. The F-test value for the biomass prediction models were also significant at p < 0.001 which indicates that the biomass prediction models are valid. This study recommends that for improved biomass estimates in the study site, the site specific biomass models should preferably be used instead of using generic models.

Keywords: allometriy, biomass, carbon stock , model, regression equation, woodland, inventory

Procedia PDF Downloads 435
21494 Development of Terrorist Threat Prediction Model in Indonesia by Using Bayesian Network

Authors: Hilya Mudrika Arini, Nur Aini Masruroh, Budi Hartono

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There are more than 20 terrorist threats from 2002 to 2012 in Indonesia. Despite of this fact, preventive solution through studies in the field of national security in Indonesia has not been conducted comprehensively. This study aims to provide a preventive solution by developing prediction model of the terrorist threat in Indonesia by using Bayesian network. There are eight stages to build the model, started from literature review, build and verify Bayesian belief network to what-if scenario. In order to build the model, four experts from different perspectives are utilized. This study finds several significant findings. First, news and the readiness of terrorist group are the most influent factor. Second, according to several scenarios of the news portion, it can be concluded that the higher positive news proportion, the higher probability of terrorist threat will occur. Therefore, the preventive solution to reduce the terrorist threat in Indonesia based on the model is by keeping the positive news portion to a maximum of 38%.

Keywords: Bayesian network, decision analysis, national security system, text mining

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21493 Visco-Hyperelastic Finite Element Analysis for Diagnosis of Knee Joint Injury Caused by Meniscal Tearing

Authors: Eiji Nakamachi, Tsuyoshi Eguchi, Sayo Yamamoto, Yusuke Morita, H. Sakamoto

Abstract:

In this study, we aim to reveal the relationship between the meniscal tearing and the articular cartilage injury of knee joint by using the dynamic explicit finite element (FE) method. Meniscal injuries reduce its functional ability and consequently increase the load on the articular cartilage of knee joint. In order to prevent the induction of osteoarthritis (OA) caused by meniscal injuries, many medical treatment techniques, such as artificial meniscus replacement and meniscal regeneration, have been developed. However, it is reported that these treatments are not the comprehensive methods. In order to reveal the fundamental mechanism of OA induction, the mechanical characterization of meniscus under the condition of normal and injured states is carried out by using FE analyses. At first, a FE model of the human knee joint in the case of normal state – ‘intact’ - was constructed by using the magnetron resonance (MR) tomography images and the image construction code, Materialize Mimics. Next, two types of meniscal injury models with the radial tears of medial and lateral menisci were constructed. In FE analyses, the linear elastic constitutive law was adopted for the femur and tibia bones, the visco-hyperelastic constitutive law for the articular cartilage, and the visco-anisotropic hyperelastic constitutive law for the meniscus, respectively. Material properties of articular cartilage and meniscus were identified using the stress-strain curves obtained by our compressive and the tensile tests. The numerical results under the normal walking condition revealed how and where the maximum compressive stress occurred on the articular cartilage. The maximum compressive stress and its occurrence point were varied in the intact and two meniscal tear models. These compressive stress values can be used to establish the threshold value to cause the pathological change for the diagnosis. In this study, FE analyses of knee joint were carried out to reveal the influence of meniscal injuries on the cartilage injury. The following conclusions are obtained. 1. 3D FE model, which consists femur, tibia, articular cartilage and meniscus was constructed based on MR images of human knee joint. The image processing code, Materialize Mimics was used by using the tetrahedral FE elements. 2. Visco-anisotropic hyperelastic constitutive equation was formulated by adopting the generalized Kelvin model. The material properties of meniscus and articular cartilage were determined by curve fitting with experimental results. 3. Stresses on the articular cartilage and menisci were obtained in cases of the intact and two radial tears of medial and lateral menisci. Through comparison with the case of intact knee joint, two tear models show almost same stress value and higher value than the intact one. It was shown that both meniscal tears induce the stress localization in both medial and lateral regions. It is confirmed that our newly developed FE analysis code has a potential to be a new diagnostic system to evaluate the meniscal damage on the articular cartilage through the mechanical functional assessment.

Keywords: finite element analysis, hyperelastic constitutive law, knee joint injury, meniscal tear, stress concentration

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21492 PLA Plastic as Biodegradable Material for 3D Printers

Authors: Juraj Beniak, Ľubomír Šooš, Peter Križan, Miloš Matúš

Abstract:

Within Rapid Prototyping technologies are used many types of materials. Many of them are recyclable but there are still as plastic like, so practically they do not degrade in the landfill. Polylactic acid (PLA) is one of the special plastic materials which are biodegradable and also available for 3D printing within Fused Deposition Modelling (FDM) technology. The question is, if the mechanical properties of produced models are comparable to similar technical plastic materials which are usual for prototype production. Presented paper shows the experiments results for tensile strength measurements for specimens prepared with different 3D printer settings and model orientation. Paper contains also the comparison of tensile strength values with values measured on specimens produced by conventional technologies as injection moulding.

Keywords: 3D printing, biodegradable plastic, fused deposition modeling, PLA plastic, rapid prototyping

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21491 Highly Oriented and Conducting SNO2 Doped Al and SB Layers Grown by Automatic Spray Pyrolysis Method

Authors: A.Boularouk, F. Chouikh, M. Lamri, H. Moualkia, Y. Bouznit

Abstract:

The principal aim of this study is to considerably reduce the resistivity of the SnO2 thin layers. In this order, we have doped tin oxide with aluminum and antimony incorporation with different atomic percentages (0 and 4%). All the pure and doped SnO2 films were grown by simple, flexible and cost-effective Automatic Spray Pyrolysis Method (ASPM) on glass substrates at a temperature of 350 °C. The microstructural, optical, morphological and electrical properties of the films have been studied. The XRD results demonstrate that all films have polycrystalline nature with a tetragonal rutile structure and exhibit the (200) preferential orientation. It has been observed that all the dopants are soluble in the SnO2 matrix without forming secondary phases. However, dopant introduction does not modify the film growth orientation. The crystallite size of the pure SnO2 film is about 36 nm. The films are highly transparent in the visible region with an average transmittance reaching up to 80% and it slightly reduces with increasing doping concentration (Al and Sb). The optical band gap value was evaluated between 3.60 eV and 3.75 eV as a function of doping. The SEM image reveals that all films are nanostructured, densely continuous, with good adhesion to the substrate. We note again that the surface morphology change with the type and concentration dopant. The minimum resistivity is 0.689*10-4, which is observed for SnO2 film doped 4% Al. This film shows better properties and is considered the best among all films. Finally, we concluded that the physical properties of the pure and doped SnO2 films grown on a glass substrate by ASPM strongly depend on the type and concentration dopant (Al and Sb) and have highly desirable optical and electrical properties and are promising materials for several applications.

Keywords: tin oxide, automatic spray, Al and Sb doped, transmittance, MEB, XRD and UV-VIS

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21490 Electro-Hydrodynamic Analysis of Low-Pressure DC Glow Discharge by Lattice Boltzmann Method

Authors: Ji-Hyok Kim, Il-Gyong Paek, Yong-Jun Kim

Abstract:

We propose a numerical model based on drift-diffusion theory and lattice Boltzmann method (LBM) to analyze the electro-hydrodynamic behavior in low-pressure direct current (DC) glow discharge plasmas. We apply the drift-diffusion theory for 4-species and employ the standard lattice Boltzmann model (SLBM) for the electron, the finite difference-lattice Boltzmann model (FD-LBM) for heavy particles, and the finite difference model (FDM) for the electric potential, respectively. Our results are compared with those of other methods, and emphasize the necessity of a two-dimensional analysis for glow discharge.

Keywords: glow discharge, lattice Boltzmann method, numerical analysis, plasma simulation, electro-hydrodynamic

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21489 Unlocking the Potential of Neglected Cereal Resources Waste: Exploring Functional Properties of Algerian Pearl Millet Starch via Wet Milling and Ultrasound Techniques

Authors: Sarra Bouhallel, Sara Legbedj, Rima Messaoud, Sofia Saffarbatti

Abstract:

In the context of global waste management and sustainable resource utilization, millets emerge as a vital yet underutilized cereal resource. Despite their exceptional nutritional profile and resilience to harsh environmental conditions, their potential remains largely untapped. This study aims to contribute to the valorization of seven Algerian pearl millet landraces (Pennisetum glaucum (L.) R. Br) from the southern region by focusing on the characterization of their starches. Utilizing both conventional wet milling, incorporating sodium azide as a microbial growth inhibitor, and a novel green technology—Ultrasound-assisted isolation, we explore avenues for enhancing the functional properties of these starches. Analysis of key functional properties such as swelling power and water solubility index reveals significant enhancements, particularly during heat treatment near the gelatinization temperature [70 - 80 °C]. Furthermore, our investigation into the influence of pre-treatment methods on isolated starches highlights the potential of Ultrasound-assisted isolation in reducing absorbency and water solubility compared to conventional methods. Through rigorous data analysis using SPSS software (Version 23), we ascertain the efficiency of Ultrasound-assisted isolation, underscoring its promising role in the valorization of pearl millet waste. This research not only sheds light on the functional properties of pearl millet starch but also underscores the imperative of sustainable waste management in harnessing the full potential of underutilized cereal resources.

Keywords: isolation, solubility, starch, swelling, ultrasound

Procedia PDF Downloads 45