Search results for: material model

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

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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

Procedia PDF Downloads 117

Authors: Georgia Pozoukidou

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TELUM software is a land use model designed specifically to help metropolitan planning organizations (MPOs) prepare their transportation improvement programs and fulfill their numerous planning responsibilities. In this context obtaining, preparing, and validating socioeconomic forecasts are becoming fundamental tasks for an MPO in order to ensure that consistent population and employment data are provided to travel demand models. Chittenden County Metropolitan Planning Organization of Vermont State was used as a case study to test the applicability of TELUM land use model. The technical insights and lessons learned from the land use model application have transferable value for all MPOs faced with land use forecasting development and transportation modelling.

Keywords: calibration data requirements, land use models, land use planning, metropolitan planning organizations

Procedia PDF Downloads 291

Authors: Xiaohui Wang, Liwei Sun, Guilin Zhang

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Printed circuit board (PCB) is the carrier of electronic components. Its coating is the first barrier for protecting itself. If the coating is damaged, the performance of printed circuit board will decrease rapidly until failure. Therefore, the coating plays an important role in the entire printed circuit board. There are common four kinds of coating of printed circuit board that the material of the coatings are paryleneC, acrylic, polyurethane, silicone. In this paper, we designed an accelerated degradation test of humid and heat for these four kinds of coating. And chose insulation resistance, moisture absorption and surface morphology as its test indexes. By comparing the change of insulation resistance of the coating before and after the test, we estimate failure time of these coatings based on the degradation of insulation resistance. Based on the above, we estimate the service life of the four kinds of PCB.

Keywords: printed circuit board, life assessment, insulation resistance, coating material

Procedia PDF Downloads 532

Authors: M. Z. Raqab, Debasis Kundu, M. A. Meraou

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In this paper, we have analyzed maximum precipitation data during a particular period of time obtained from different stations in the Global Historical Climatological Network of the USA. One important point to mention is that some stations are shut down on certain days for some reason or the other. Hence, the maximum values are recorded by excluding those readings. It is assumed that the number of stations that operate follows zero-truncated Poisson random variables, and the daily precipitation follows a lognormal random variable. We call this model a compound truncated Poisson lognormal model. The proposed model has three unknown parameters, and it can take a variety of shapes. The maximum likelihood estimators can be obtained quite conveniently using Expectation-Maximization (EM) algorithm. Approximate maximum likelihood estimators are also derived. The associated confidence intervals also can be obtained from the observed Fisher information matrix. Simulation results have been performed to check the performance of the EM algorithm, and it is observed that the EM algorithm works quite well in this case. When we analyze the precipitation data set using the proposed model, it is observed that the proposed model provides a better fit than some of the existing models.

Keywords: compound Poisson lognormal distribution, EM algorithm, maximum likelihood estimation, approximate maximum likelihood estimation, Fisher information, skew distribution

Procedia PDF Downloads 108

Authors: J. Naalamle Amissah, Dorcas Osei‐Safo, C. M. Asare, Benjamin Missah‐Assihene, Eric. Y. Danquah, Ivan Addae‐Mensah

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Medicinal plants serve as a reservoir of active ingredients for the treatment of common ailments such as cancer, malaria and diabetes. With the recent wave of health consciousness and reliance on plant based medicines, the demand for medicinal plants has increased considerably. This surge in medicinal plant use has raised great concern amongst key players (herbalist, collectors, conservationist and researchers) along the value chain about the sustainability of the raw material. The over reliance on wild crafting as a means to obtain the raw material spells doom for several of Africa’s native medicinal plant species. In this study domestication protocols for the cultivation of Cryptolepis sanguinolenta (CS), a medicinal plant used in the treatment of malaria were developed. Initial surveys were conducted, using questionnaires comprising of open and close ended questions, to gather information that would inform the domestication and cultivation of the species. A field study was then conducted to determine the plant’s cropping cycle and the effect of staking and plant age on the active ingredient (cryptolepine) concentration in its roots. Results of the survey confirmed the demand for the raw material and threw more light on the harvesting methods and intensity of CS collection from the wild. Cryptolepine concentration was found to be highest (~1.84 mg/100 mg of root material) at 289 days after planting (DAP) which coincided with the peak of root dry weight (52.8 g), signifying the best time for root harvest. Staking was found to be important for seed production. The first 105 DAP were characterized by low yields of root dry weight (13.5 g), followed by a period of rapid growth in which the root dry weight increased almost linearly until 289 DAP. Although dry matter partitioned to the vines increased towards the end of the experimental period (60%), dry matter partitioned to the roots remained fairly constant (30%) throughout the experimental period. Cryptolepine was found to increase as the plant aged and the practice of staking CS promoted pod formation. A suitable cropping cycle for the cultivation of CS was also developed.

Keywords: domestication, staking, conservation, wild harvesting

Procedia PDF Downloads 383

Authors: Po-Ting Chen, Santhanamoorthi Nachimuthu, Jyh-Chiang Jiang

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Classical molecular dynamics (CMD) simulations are highly efficient for material simulations but have limited accuracy. In contrast, ab initio molecular dynamics (AIMD) provides high precision by solving the Kohn–Sham equations yet requires significant computational resources, restricting the size of systems and time scales that can be simulated. To address these challenges, we employed NequIP, a machine learning model based on an E(3)-equivariant graph neural network, to accelerate molecular dynamics simulations of a 1M LiPF6 in EC/EMC (v/v 3:7) for Li battery applications. AIMD calculations were initially conducted using the Vienna Ab initio Simulation Package (VASP) to generate highly accurate atomic positions, forces, and energies. This data was then used to train the NequIP model, which efficiently learns from the provided data. NequIP achieved AIMD-level accuracy with significantly less training data. After training, NequIP was integrated into the LAMMPS software to enable molecular dynamics simulations of larger systems over longer time scales. This method overcomes the computational limitations of AIMD while improving the accuracy limitations of CMD, providing an efficient and precise computational framework. This study showcases NequIP’s applicability to electrolyte systems, particularly for simulating the dynamics of LiPF6 ionic mixtures. The results demonstrate substantial improvements in both computational efficiency and simulation accuracy, highlighting the potential of machine learning models to enhance molecular dynamics simulations.

Keywords: lithium-ion batteries, electrolyte simulation, molecular dynamics, neural network

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Authors: Kevin Giraldo, Juan A. Gallego, Uriel Zapata, Fanny L. Casado

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Compliant mechanisms are designed to deform in a controlled manner in response to external forces, utilizing the flexibility of their components to store potential elastic energy during deformation, gradually releasing it upon returning to its original form. This article explores the design of a knee orthosis intended to assist users during stand-up motion. The orthosis makes use of a compliant mechanism to balance the user’s weight, thereby minimizing the strain on leg muscles during standup motion. The primary function of the compliant mechanism is to store and exchange potential energy, so when coupled with the gravitational potential of the user, the total potential energy variation is minimized. The design process for the semi-rigid knee orthosis involved material selection and the development of a numerical model for the compliant mechanism seen as a spring. Geometric properties are obtained through the numerical modeling of the spring once the desired stiffness and safety factor values have been attained. Subsequently, a 3D finite element analysis was conducted. The study demonstrates a strong correlation between the maximum stress in the mathematical model (250.22 MPa) and the simulation (239.8 MPa), with a 4.16% error. Both analyses safety factors: 1.02 for the mathematical approach and 1.1 for the simulation, with a consistent 7.84% margin of error. The spring’s stiffness, calculated at 90.82 Nm/rad analytically and 85.71 Nm/rad in the simulation, exhibits a 5.62% difference. These results suggest significant potential for the proposed device in assisting patients with knee orthopedic restrictions, contributing to ongoing efforts in advancing the understanding and treatment of knee osteoarthritis.

Keywords: biomechanics, complaint mechanisms, gonarthrosis, orthoses

Procedia PDF Downloads 34

Authors: Mais Khader, Xingjie Wei

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This research sheds light on female entrepreneurs by providing new insights on the survival predictions of companies led by females in the UK. This study aims to build a predictive machine learning model of the survival of female-led & co-led small & medium enterprises (SMEs) in the UK over the period 2000-2020. The predictive model built utilised a combination of financial and non-financial features related to both companies and their directors to predict SMEs' survival. These features were studied in terms of their contribution to the resultant predictive model. Five machine learning models are used in the modelling: Decision tree, AdaBoost, Naïve Bayes, Logistic regression and SVM. The AdaBoost model had the highest performance of the five models, with an accuracy of 73% and an AUC of 80%. The results show high feature importance in predicting companies' survival for company size, management experience, financial performance, industry, region, and females' percentage in management.

Keywords: company survival, entrepreneurship, females, machine learning, SMEs

Procedia PDF Downloads 99

Authors: Nkechinyere Joy Olawuyi, Babajide Samuel Afolabi, Bola Ibitoye

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This study collected a preprocessed dataset of chest radiographs and formulated a deep neural network model for detecting abnormalities. It also evaluated the performance of the formulated model and implemented a prototype of the formulated model. This was with the view to developing a deep neural network model to automatically classify abnormalities in chest radiographs. In order to achieve the overall purpose of this research, a large set of chest x-ray images were sourced for and collected from the CheXpert dataset, which is an online repository of annotated chest radiographs compiled by the Machine Learning Research Group, Stanford University. The chest radiographs were preprocessed into a format that can be fed into a deep neural network. The preprocessing techniques used were standardization and normalization. The classification problem was formulated as a multi-label binary classification model, which used convolutional neural network architecture to make a decision on whether an abnormality was present or not in the chest radiographs. The classification model was evaluated using specificity, sensitivity, and Area Under Curve (AUC) score as the parameter. A prototype of the classification model was implemented using Keras Open source deep learning framework in Python Programming Language. The AUC ROC curve of the model was able to classify Atelestasis, Support devices, Pleural effusion, Pneumonia, A normal CXR (no finding), Pneumothorax, and Consolidation. However, Lung opacity and Cardiomegaly had a probability of less than 0.5 and thus were classified as absent. Precision, recall, and F1 score values were 0.78; this implies that the number of False Positive and False Negative is the same, revealing some measure of label imbalance in the dataset. The study concluded that the developed model is sufficient to classify abnormalities present in chest radiographs into present or absent.

Keywords: transfer learning, convolutional neural network, radiograph, classification, multi-label

Procedia PDF Downloads 125

Authors: Azam Mohammadbagheri, Bahram Fathi

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DEA has become a very popular method of performance measure, but it still suffers from some shortcomings. One of these shortcomings is the issue of having multiple optimal solutions to weights for efficient DMUs. The cross efficiency evaluation as an extension of DEA is proposed to avoid this problem. Lam (2010) is also proposed a mixed-integer linear programming formulation based on linear discriminate analysis and super efficiency method (MILP model) to avoid having multiple optimal solutions to weights. In this study, we modified MILP model to determine more suitable weight sets and also evaluate the energy efficiency of MENA countries as an application of the proposed model.

Keywords: data envelopment analysis, discriminate analysis, cross efficiency, MILP model

Procedia PDF Downloads 685

Authors: Wang Xue, Fan Liwei

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The trust and use of social network platforms by users are instrumental factors that contribute to the platform’s sustainable development. Studying the influential factors of the use of social network platforms is beneficial for developing and maintaining a large user base. This study constructed an extended unified theory of acceptance and use of technology (UTAUT2) moderating model with perceived privacy risks to analyze the factors affecting the trust and use of social network platforms. 444 participants completed our 35 surveys, and we verified the survey results by structural equation model. Empirical results reveal the influencing factors that affect the trust and use of social network platforms, and the extended UTAUT2 model with perceived privacy risks increases the applicability of UTAUT2 in social network scenarios. Social networking platforms can increase their use rate by increasing the economics, functionality, entertainment, and privacy security of the platform.

Keywords: perceived privacy risk, social network, trust, use, UTAUT2 model

Procedia PDF Downloads 98

Authors: Fangfang Wang, Fan Qu

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Polycystic ovary syndrome (PCOS), the most common endocrinopathy among women of reproductive age, is characterized by ovarian dysfunction, hyperandrogenism and reduced fecundity. The aim of this study is to investigate whether the circadian disruption is involved in pathogenesis of PCOS in androgen-induced animal model. We established a rat model of PCOS using single subcutaneous injection with testosterone propionate on the ninth day after birth, and confirmed their PCOS-like phenotypes with vaginal smears, ovarian hematoxylin and eosin (HE) staining and serum androgen measurement. The control group rats received the vehicle only. Gene expression was detected by real-time quantitative PCR. (1) Compared with control group, PCOS model rats of 10-week group showed persistently keratinized vaginal cells, while all the control rats showed at least two consecutive estrous cycles. (2) Ovarian HE staining and histological examination showed that PCOS model rats of 10-week group presented many cystic follicles with decreased numbers of granulosa cells and corpora lutea in their ovaries, while the control rats had follicles with normal layers of granulosa cells at various stages of development and several generations of corpora lutea. (3) In the 10-week group, serum free androgen index was notably higher in PCOS model rats than controls. (4) Disturbed mRNA expression patterns of core clock genes were found in ovaries of PCOS model rats of 10-week group. Abnormal expression of key genes associated with circadian rhythm in ovary may be one of the mechanisms for ovarian dysfunction in PCOS model rats induced by androgen.

Keywords: polycystic ovary syndrome, androgen, animal model, circadian disruption

Procedia PDF Downloads 229

Authors: Karla D. Vazquez-Valdez, Bradley P. Wynne

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In the last decades manufacturing needs have been changing, leading to the study of manufacturing methods that were underdeveloped, such as incremental forming processes like shear forming. These processes use rotating tools in constant local contact with the workpiece, which is often also rotating, to generate shape. This means much lower loads to forge large parts and no need for expensive special tooling. Potential has already been established by demonstrating manufacture of high-value products, e.g., turbine and satellite parts, with high dimensional accuracy from difficult to manufacture materials. Thus, huge opportunities exist for these processes to replace the current method of manufacture for a range of high value components, e.g., eliminating lengthy machining, reducing material waste and process times; or the manufacture of a complicated shape without the development of expensive tooling. However, little is known about the exact deformation conditions during processing and why certain materials are better than others for shear forming, leading to a lot of trial and error before production. Three alloys were used for this study: Ti-54M, Jethete M154, and IN718. General Microscopy and Electron Backscatter Diffraction (EBSD) were used to measure strains and orientation maps during shear forming. A Design of Experiments (DOE) analysis was also made in order to understand the impact of process parameters in the properties of the final workpieces. Such information was the key to develop a reliable Finite Element Method (FEM) model that closely resembles the deformation paths of this process. Finally, the potential of these three materials to be shear spun was studied using the FEM model and their Forming Limit Diagram (FLD) which led to the development of a rough methodology for testing the shear spinnability of various metals.

Keywords: shear forming, damage, principal strains, forming limit diagram

Procedia PDF Downloads 162

Authors: Yoon- Ho Shin, Jin-Seung Choi, Dong-Won Kang, Jeong-Woo Seo, Joo-Hack Lee, Ju-Young Kim, Dae-Hyeok Kim, Seung-Tae Yang, Gye-Rae Tack

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It is difficult to study the effect of various variables on cycle fitting through actual experiment. To overcome such difficulty, the forward dynamics of a musculoskeletal model was applied to cycle fitting in this study. The measured EMG data were compared with the muscle activities of the musculoskeletal model through forward dynamics. EMG data were measured from five cyclists who do not have musculoskeletal diseases during three minutes pedaling with a constant load (150 W) and cadence (90 RPM). The muscles used for the analysis were the Vastus Lateralis (VL), Tibialis Anterior (TA), Bicep Femoris (BF), and Gastrocnemius Medial (GM). Person’s correlation coefficients of the muscle activity patterns, the peak timing of the maximum muscle activities, and the total muscle activities were calculated and compared. BIKE3D model of AnyBody (Anybodytech, Denmark) was used for the musculoskeletal model simulation. The comparisons of the actual experiments with the simulation results showed significant correlations in the muscle activity patterns (VL: 0.789, TA: 0.503, BF: 0.468, GM: 0.670). The peak timings of the maximum muscle activities were distributed at particular phases. The total muscle activities were compared with the normalized muscle activities, and the comparison showed about 10% difference in the VL (+10%), TA (+9.7%), and BF (+10%), excluding the GM (+29.4%). Thus, it can be concluded that muscle activities of model & experiment showed similar results. The results of this study indicated that it was possible to apply the simulation of further improved musculoskeletal model to cycle fitting.

Keywords: musculoskeletal modeling, EMG, cycle fitting, simulation

Procedia PDF Downloads 566

Authors: Preeda Sansakorn, Min An

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In order to be capable of dealing with uncertainties, subjectivities, including vagueness arising in building construction projects, the application of fuzzy reasoning technique based on fuzzy set theory is proposed. This study contributes significantly to the development of a fuzzy reasoning safety risk assessment model for building construction projects that could be employed to assess the risk magnitude of each hazardous event identified during construction, and a third parameter of probability of consequence is incorporated in the model. By using the proposed safety risk analysis methodology, more reliable and less ambiguities, which provide the safety risk management project team for decision-making purposes.

Keywords: safety risk assessment, building construction safety, fuzzy reasoning, construction risk assessment model, building construction projects

Procedia PDF Downloads 489

Authors: Alaa Osman, Sara Elgazzar, Breksal Elmiligy

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The Supply Chain Operation Reference (SCOR) model is considered one of the most widely implemented supply chain performance measurement systems (SCPMSs). Several studies have been proposed on the SCOR model adaptation in developed countries context; while there is a limited availability of previous work on the SCPMSs application generally and the SCOR model specifically in developing nations. This paper presents a research agenda on the SCOR model adaptation in the developing countries. It aims at investigating the challenges of adapting the SCOR model to manage and measure supply chain performance in developing countries. The research will exemplify the system in the Egyptian automotive sector to gain a comprehensive understanding of how the application of the SCOR model can affect the performance of automotive companies in Egypt, with a necessary understanding of challenges and obstacles faced the adaptation of the model in the Egyptian supply chain context. An empirical study was conducted on the Egyptian automotive sector in three companies considering three different classes: BMW, Hyundai and Brilliance. First, in-depth interviews were carried out to gain an insight into the implementation and the relevance of the concepts of supply chain management and performance measurement in the Egyptian automotive industry. Then, a formal survey was designed based on the SCOR model five main processes (plan, source, make, deliver and return) and best practices to investigate the challenges and obstacles faced the adaptation of the SCOR model in the Egyptian automotive supply chain. Finally, based on the survey results, the appropriate best practices for each process were identified in order to overcome the SCOR model adaptation challenges. The results showed that the implementation of the SCOR model faced different challenges and unavailability of the required enablers. The survey highlighted the low integration of end-to-end supply chain, lacks commitment for the innovative ideas and technologies, financial constraints and lack of practical training and support as the main challenges faced the adaptation of the SCOR model in the Egyptian automotive supply chain. The research provides an original contribution to knowledge by proposing a procedure to identify challenges encountered during the process of SCOR model adoption which can pave a way for further research in the area of SCPMSs adaptation, particularly in the developing countries. The research can help managers and organizations to identify obstacles and difficulties of the SCOR model adaptation, subsequently this can facilitate measuring the improved performance or changes in the organizational performance.

Keywords: automotive sector, developing countries, SCOR model, supply chain performance

Procedia PDF Downloads 373

Authors: Wajih Abbassi, Zouhaier Ben Khelifa

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The present research points towards the empirical validation of three options valuation models, the ad-hoc Black-Scholes model as proposed by Berkowitz (2001), the constant elasticity of variance model of Cox and Ross (1976) and the Kou jump-diffusion model (2002). Our empirical analysis has been conducted on a sample of 26,974 options written on three indexes, the S&P 500, Nasdaq 100 and the Russell 2000 that were negotiated during the year 2007 just before the sub-prime crisis. We start by presenting the theoretical foundations of the models of interest. Then we use the technique of trust-region-reflective algorithm to estimate the structural parameters of these models from cross-section of option prices. The empirical analysis shows the superiority of the Kou jump-diffusion model. This superiority arises from the ability of this model to portray the behavior of market participants and to be closest to the true distribution that characterizes the evolution of these indices. Indeed the double-exponential distribution covers three interesting properties that are: the leptokurtic feature, the memory less property and the psychological aspect of market participants. Numerous empirical studies have shown that markets tend to have both overreaction and under reaction over good and bad news respectively. Despite of these advantages there are not many empirical studies based on this model partly because probability distribution and option valuation formula are rather complicated. This paper is the first to have used the technique of nonlinear curve-fitting through the trust-region-reflective algorithm and cross-section options to estimate the structural parameters of the Kou jump-diffusion model.

Keywords: jump-diffusion process, Kou model, Leptokurtic feature, trust-region-reflective algorithm, US index options

Procedia PDF Downloads 427

Authors: A. Amar

Abstract:

Analysis of the elastic scattering of protons on ¹⁰B nuclei has been done in the framework of the optical model and single folding model at the beam energies up to 17 MeV. We could enhance the optical potential parameters using Esis88 Code, as well as SPI GENOA Code. Linear relationship between volume real potential (V₀) and proton energy (E_p) has been obtained. Also, surface imaginary potential W_D is proportional to the proton energy (E_p) in the range 0.400 and 17 MeV. The radiative reaction ¹⁰B(p,γ)¹¹C has been analyzed using potential model. A comparison between ¹⁰B(p,γ)¹¹C and ⁶Li(p,γ)⁷Be has been made. Good agreement has been found between theoretical and experimental results in the whole range of energy. The radiative resonance reaction ⁷Li(p,γ)⁸Be has been studied.

Keywords: elastic scattering of protons on 10B nuclei, optical potential parameters, potential model, radiative reaction

Procedia PDF Downloads 206

Authors: S. Benkraouda, Z. Djelloul-Khedda, B. Yagoubi

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we present a method for early detection of forest fires from a thermal infrared satellite image, using the image matrix of the probability of belonging. The principle of the method is to compare a theoretical mathematical model to an experimental model. We considered that each line of the image matrix, as an embodiment of a non-stationary random process. Since the distribution of pixels in the satellite image is statistically dependent, we divided these lines into small stationary and ergodic intervals to characterize the image by an adequate mathematical model. A standard deviation was chosen to generate random variables, so each interval behaves naturally like white Gaussian noise. The latter has been selected as the mathematical model that represents a set of very majority pixels, which we can be considered as the image background. Before modeling the image, we made a few pretreatments, then the parameters of the theoretical Gaussian model were extracted from the modeled image, these settings will be used to calculate the probability of each interval of the modeled image to belong to the theoretical Gaussian model. The high intensities pixels are regarded as foreign elements to it, so they will have a low probability, and the pixels that belong to the background image will have a high probability. Finally, we did present the reverse of the matrix of probabilities of these intervals for a better fire detection.

Keywords: forest fire, forest fire detection, satellite image, normal distribution, theoretical gaussian model, thermal infrared matrix image

Procedia PDF Downloads 140

Authors: S. Ghorbani, N. I. Polushin

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In this study, an approach to identify factors affecting on surface roughness in a machining process is presented. This study is based on 81 data about surface roughness over a wide range of cutting tools (conventional, cutting tool with holes, cutting tool with composite material), workpiece materials (AISI 1045 Steel, AA2024 aluminum alloy, A48-class30 gray cast iron), spindle speed (630-1000 rpm), feed rate (0.05-0.075 mm/rev), depth of cut (0.05-0.15 mm) and tool overhang (41-65 mm). A single decision tree (SDT) analysis was done to identify factors for predicting a model of surface roughness, and the CART algorithm was employed for building and evaluating regression tree. Results show that a single decision tree is better than traditional regression models with higher rate and forecast accuracy and strong value.

Keywords: cutting condition, surface roughness, decision tree, CART algorithm

Procedia PDF Downloads 371

Authors: S. Apprich, F. Wulle, A. Lechler, A. Pott, A. Verl

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Large-scale machine tools for the manufacturing of large work pieces, e.g. blades, casings or gears for wind turbines, feature pose-dependent dynamic behavior. Small structural damping coefficients lead to long decay times for structural vibrations that have negative impacts on the production process. Typically, these vibrations are handled by increasing the stiffness of the structure by adding mass. That is counterproductive to the needs of sustainable manufacturing as it leads to higher resource consumption both in material and in energy. Recent research activities have led to higher resource efficiency by radical mass reduction that rely on control-integrated active vibration avoidance and damping methods. These control methods depend on information describing the dynamic behavior of the controlled machine tools in order to tune the avoidance or reduction method parameters according to the current state of the machine. The paper presents the appearance, consequences and challenges of the pose-dependent dynamic behavior of lightweight large-scale machine tool structures in production. The paper starts with the theoretical introduction of the challenges of lightweight machine tool structures resulting from reduced stiffness. The statement of the pose-dependent dynamic behavior is corroborated by the results of the experimental modal analysis of a lightweight test structure. Afterwards, the consequences of the pose-dependent dynamic behavior of lightweight machine tool structures for the use of active control and vibration reduction methods are explained. Based on the state of the art on pose-dependent dynamic machine tool models and the modal investigation of an FE-model of the lightweight test structure, the criteria for a pose-dependent model for use in vibration reduction are derived. The description of the approach for a general pose-dependent model of the dynamic behavior of large lightweight machine tools that provides the necessary input to the aforementioned vibration avoidance and reduction methods to properly tackle machine vibrations is the outlook of the paper.

Keywords: dynamic behavior, lightweight, machine tool, pose-dependency

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Authors: Rahul Paliwal, Gulshan Maheshwari, Anant S. Jhaveri, Channamallikarjun S. Mathpati

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Large pumping facility is the necessary requirement of the cooling water systems for power plants, process and manufacturing facilities, flood control and water or waste water treatment plant. With a large capacity of few hundred to 50,000 m3/hr, cares must be taken to ensure the uniform flow to the pump to limit vibration, flow induced cavitation and performance problems due to formation of air entrained vortex and swirl flow. Successful prediction of these phenomena requires numerical method and turbulence model to characterize the dynamics of these flows. In the past years, single phase shear stress transport (SST) Reynolds averaged Navier Stokes Models (like k-ε, k-ω and RSM) were used to predict the behavior of flow. Literature study showed that two phase model will be more accurate over single phase model. In this paper, a 3D geometries simulated using detached eddy simulation (LES) is used to predict the behavior of the fluid and the results are compared with experimental results. Effect of different grid structure and boundary condition is also studied. It is observed that two phase flow model can more accurately predict the mean flow and turbulence statistics compared to the steady SST model. These validate model will be used for further analysis of vortex structure in lab scale model to generate their frequency-plot and intensity at different location in the set-up. This study will help in minimizing the ill effect of vortex on pump performance.

Keywords: grid structure, pump intake, simulation, vibration, vortex

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Authors: Marcela Ondova, Adriana Estokova

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Rapid industrialization results in increased use of natural resources bring along serious ecological and environmental imbalance due to the dumping of industrial wastes. Principles of sustainable construction have to be accepted with regard to the consumption of natural resources and the production of harmful emissions. Cement is a great importance raw material in the building industry and today is its large amount used in the construction of concrete pavements. Concerning raw materials cost and producing CO2 emission the replacing of cement in concrete mixtures with more sustainable materials is necessary. To reduce this environmental impact people all over the world are looking for a solution. Over a period of last ten years, the image of fly ash has completely been changed from a polluting waste to resource material and it can solve the major problems of cement use. Fly ash concretes are proposed as a potential approach for achieving substantial reductions in cement. It is known that it improves the workability of concrete, extends the life cycle of concrete roads, and reduces energy use and greenhouse gas as well as amount of coal combustion products that must be disposed in landfills. Life cycle assessment also proved that a concrete pavement with fly ash cement replacement is considerably more environmentally friendly compared to standard concrete roads. In addition, fly ash is cheap raw material, and the costs saving are guaranteed. The strength properties, resistance to a frost or de-icing salts, which are important characteristics in the construction of concrete pavements, have reached the required standards as well. In terms of human health it can´t be stated that a concrete cover with fly ash could be dangerous compared with a cover without fly ash. Final Multi-criteria analysis also pointed that a concrete with fly ash is a clearly proper solution.

Keywords: life cycle assessment, fly ash, waste, concrete pavements

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Authors: Paul Kenneth D. Luzon, Maria Antonia N. Tanchuling

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The Quezon City Controlled Dumping facility also known as Payatas produces leachate which can contaminate soil and water environment in the area. The goal of this study is to quantify the leachate produced by the QCCDF using the Hydrologic Evaluation of Landfill Performance (HELP) model. Results could be used as input for groundwater contaminant transport studies. The HELP model is based on a simple water budget and is an essential “model requirement” used by the US Environmental Protection Agency (EPA). Annual waste profile of the QCCDF was calculated. Based on topographical maps and estimation of settlement due to overburden pressure and degradation, a total of 10M m^3 of waste is contained in the landfill. The input necessary for the HELP model are weather data, soil properties, and landfill design. Results showed that from 1988 to 2011, an average of 50% of the total precipitation percolates through the bottom layer. Validation of the results is still needed due to the assumptions made in the study. The decrease in porosity of the top soil cover showed the best mitigation for minimizing percolation rate. This study concludes that there is a need for better leachate management system in the QCCDF.

Keywords: help model, landfill, payatas trash slide, quezon city controlled dumping facility

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Authors: Muhammad Anwar, Ameen Ullah, Intakhab Alam Qadri

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This study presents a technique utilizing the Iterative Rational Krylov Algorithm (IRKA) to reduce the order of large-scale descriptor systems. Descriptor systems, which incorporate differential and algebraic components, pose unique challenges in Model Order Reduction (MOR). The proposed method partitions the descriptor system into polynomial and strictly proper parts to minimize approximation errors, applying IRKA exclusively to the strictly adequate component. This approach circumvents the unbounded errors that arise when IRKA is directly applied to the entire system. A comparative analysis demonstrates the high accuracy of the reduced model and a significant reduction in computational burden. The reduced model enables more efficient simulations and streamlined controller designs. The study highlights IRKA-based MOR’s effectiveness in optimizing complex systems’ performance across various engineering applications. The proposed methodology offers a promising solution for reducing the complexity of large-scale descriptor systems while maintaining their essential characteristics and facilitating their analysis, simulation, and control design.

Keywords: model order reduction, descriptor systems, iterative rational Krylov algorithm, interpolatory model reduction, computational efficiency, projection methods, H₂-optimal model reduction

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Authors: Stefanie Rukavina, Sascha Gruss, Steffen Walter, Holger Hoffmann, Harald C. Traue

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OPEN-EmoRecII is an open multimodal corpus with experimentally induced emotions. In the first half of the experiment, emotions were induced with standardized picture material and in the second half during a human-computer interaction (HCI), realized with a wizard-of-oz design. The induced emotions are based on the dimensional theory of emotions (valence, arousal and dominance). These emotional sequences - recorded with multimodal data (mimic reactions, speech, audio and physiological reactions) during a naturalistic-like HCI-environment one can improve classification methods on a multimodal level. This database is the result of an HCI-experiment, for which 30 subjects in total agreed to a publication of their data including the video material for research purposes. The now available open corpus contains sensory signal of: video, audio, physiology (SCL, respiration, BVP, EMG Corrugator supercilii, EMG Zygomaticus Major) and mimic annotations.

Keywords: open multimodal emotion corpus, annotated labels, intelligent interaction

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Authors: Zainab Ajab Mohideen, Kiran Kaur, A. Basheer Ahamadhu, Noor Azlinda Wan Jan, Sukmawati Muhammad

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The corpus in the digital library is to provide an overview and evidence from library automation that can be used to justify the needs of the digital library. This paper disperses the approach and implementation of the digital library as part of best practices by the Automation Division at Hamzah Sendut Library of the University Science Malaysia (USM). The implemented digital library model emphasizes on the entire library collections, technical perspective, and automation solution. This model served as a foundation for digital library services as part of information delivery in the USM digital library. The approach to digital library includes discussion on key factors, design, architecture, and pragmatic model that has been collected, captured, and identified during the implementation stages. At present, the USM digital library has achieved the status of an Institutional Repository (IR).

Keywords: academic digital library, digital information system, digital library best practice, digital library model

Procedia PDF Downloads 551

Authors: Anatoly A. Kuznetsov, Pavel G. Berezhko, Sergey M. Kunavin, Eugeny V. Zhilkin, Maxim V. Tsarev, Vyacheslav V. Yaroshenko, Valery V. Mokrushin, Olga Y. Yunchina, Sergey A. Mityashin

Abstract:

The acoustic emission is caused by short-time propagation of elastic waves that are generated as a result of quick energy release from sources localized inside some material. In particular, the acoustic emission phenomenon lies in the generation of acoustic waves resulted from the reconstruction of material internal structures. This phenomenon is observed at various physicochemical transformations, in particular, at those accompanying hydrogenation processes of metals or intermetallic compounds that make it possible to study parameters of these transformations through recording and analyzing the acoustic signals. It has been known that at the interaction between metals or inter metallides with hydrogen the most intensive acoustic signals are generated as a result of cracking or crumbling of an initial compact powder sample as a result of the change of material crystal structure under hydrogenation. This work is dedicated to the study into changes occurring in metallic titanium samples at their interaction with hydrogen and followed by acoustic emission signals. In this work the subjects for investigation were specimens of metallic titanium in two various initial forms: titanium sponge and fine titanium powder made of this sponge. The kinetic of the interaction of these materials with hydrogen, the acoustic emission signals accompanying hydrogenation processes and the structure of the materials before and after hydrogenation were investigated. It was determined that in both cases interaction of metallic titanium and hydrogen is followed by acoustic emission signals of high amplitude generated on reaching some certain value of the atomic ratio [H]/[Ti] in a solid phase because of metal cracking at a macrolevel. The typical sizes of the cracks are comparable with particle sizes of hydrogenated specimens. The reasons for cracking are internal stresses initiated in a sample due to the increasing volume of a solid phase as a result of changes in a material crystal lattice under hydrogenation. When the titanium powder is used, the atomic ratio [H]/[Ti] in a solid phase corresponding to the maximum amplitude of an acoustic emission signal are, as a rule, higher than when titanium sponge is used.

Keywords: acoustic emission signal, cracking, hydrogenation, titanium specimen

Procedia PDF Downloads 385

Authors: Elmo Thiao Lins Cöuras Ford, Valentina Alessandra Carvalho do Vale, R. M. Nascimento, J. U. L. Mendes

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Now the great majority of the applications of thermal isolation in the strip of drops and averages temperatures (up to 200ºC), it is made being used from aggressive materials to the nature such an as: glass wool, rock wool, polystyrene, EPS among others. Such materials, in spite of the effectiveness in the retention of the flow of heat, possess considerable cost and when discarded they are long years to be to decompose. In that context, trying to adapt the world politics the about of the preservation of the environment, a study began with intention of developing a material composite, with properties of thermal, originating from insulating industrial residues. In this research, the behavior of the composite was analyzed, as submitted the fire. For this, the reaction rehearsals were accomplished to the fire for the composites 2:1; 1:1; 1:2 and for the latex, based in the "con" experiment in agreement with the norm ASTM–E 1334-90. As consequence, in function of the answers of the system, was possible to observe to the acting of each mixture proportion.

Keywords: composite, Latex, reacion to the fire, thermal isolation

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Authors: N. H. S. Mustafa, N. M. Yatim

Abstract:

Thermoelectric materials arrange in segmented design could increase the conversion of heat to electricity performance. This is due to the properties of materials that perform peak at narrow temperature range. Performance of the materials determines by dimensionless figure-of-merit, ZT which consist of thermoelectric properties namely Seebeck coefficient, electrical resistivity, and thermal conductivity. Since different materials were arrange in segmented, determination of ZT cannot be measured using the conventional approach. Therefore, this research used 'open-short circuit' technique to measure the segmented performance. Segmented thermoelectric materials consist of bismuth telluride, and lead telluride was segmented together under cold press technique. The results show thermoelectric properties measured is comparable with calculated based on commercially available of individual material. Performances of segmented sample under different polarity also indicate dependability of material with position and temperature. Segmented materials successfully measured under real condition and optimization of the segmented can be designed from the study of polarity change.

Keywords: thermoelectric, segmented, ZT, polarity, performance

Procedia PDF Downloads 201