Search results for: Newtonian fluid model

Authors: T. Nozu, K. Hibi, T. Nishiie

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This paper discusses the applicability of the numerical model for a damage prediction method of the accidental hydrogen explosion occurring in a hydrogen facility. The numerical model was based on an unstructured finite volume method (FVM) code “NuFD/FrontFlowRed”. For simulating unsteady turbulent combustion of leaked hydrogen gas, a combination of Large Eddy Simulation (LES) and a combustion model were used. The combustion model was based on a two scalar flamelet approach, where a G-equation model and a conserved scalar model expressed a propagation of premixed flame surface and a diffusion combustion process, respectively. For validation of this numerical model, we have simulated the previous two types of hydrogen explosion tests. One is open-space explosion test, and the source was a prismatic 5.27 m3 volume with 30% of hydrogen-air mixture. A reinforced concrete wall was set 4 m away from the front surface of the source. The source was ignited at the bottom center by a spark. The other is vented enclosure explosion test, and the chamber was 4.6 m × 4.6 m × 3.0 m with a vent opening on one side. Vent area of 5.4 m2 was used. Test was performed with ignition at the center of the wall opposite the vent. Hydrogen-air mixtures with hydrogen concentrations close to 18% vol. were used in the tests. The results from the numerical simulations are compared with the previous experimental data for the accuracy of the numerical model, and we have verified that the simulated overpressures and flame time-of-arrival data were in good agreement with the results of the previous two explosion tests.

Keywords: deflagration, large eddy simulation, turbulent combustion, vented enclosure

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Authors: Maziar Ramezani, Thomas Neitzert, Timotius Pasang

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This paper aims at experimental and numerical investigation of springback behavior of sheet metals during L-bending process with emphasis on Stribeck-type friction modeling. The coefficient of friction in Stribeck curve depends on sliding velocity and contact pressure. The springback behavior of mild steel and aluminum alloy 6022-T4 sheets was studied experimentally and using numerical simulations with ABAQUS software with two types of friction model: Coulomb friction and Stribeck friction. The influence of forming speed on springback behavior was studied experimentally and numerically. The results showed that Stribeck-type friction model has better results in predicting springback in sheet metal forming. The FE prediction error for mild steel and 6022-T4 AA is 23.8%, 25.5% respectively, using Coulomb friction model and 11%, 13% respectively, using Stribeck friction model. These results show that Stribeck model is suitable for simulation of sheet metal forming especially at higher forming speed.

Keywords: friction, L-bending, springback, Stribeck curves

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Authors: Minzheong Song

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The purpose of this paper is to see a case of smart energy evolution of the UK along with government projects and smart city project like 'Smart London Plan (SLP)' in 2013 with the logic of business model innovation (BMI). For this, it discusses the theoretical logic and formulates a research framework of evolving smart energy from silo to integrated system. The starting point is the silo system with no connection and in second stage, the private investment in smart meters, smart grids implementation, energy and water nexus, adaptive smart grid systems, and building marketplaces with platform leadership. As results, the UK’s smart energy sector has evolved from smart meter device installation through smart grid to new business models such as water-energy nexus and microgrid service within the smart energy city system.

Keywords: smart city, smart energy, business model, business model innovation (BMI)

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Authors: H. N. Cheung

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Self-compassion encourages one to accept oneself, reduce self-criticism and self-judgment, and see one’s shortcomings and setbacks in a balanced view. Adolescent self-compassion is a crucial protective factor against mental illness. It is, however, affected by gender. Given the scarcity of self-compassion scales for adolescents, the current study evaluates the Self-Compassion Scale for Youth (SCS-Y) in a large cross-cultural sample and investigates how the subscales of SCS-Y relate to the dimensions of depressive symptoms across gender. Through the internet-based Qualtrics, a total of 2881 teenagers aged 12 to 18 years were recruited from Hong Kong (HK), China, and the United Kingdom. A Multiple Indicator Multiple Cause (MIMIC) model was used to evaluate measurement invariance of the SCS-Y, and differential item functioning (DIF) was checked across gender. Upon the establishment of the best model, a multigroup structural equation model (SEM) was built between factors of SCS-Y and Multidimensional depression assessment scale (MDAS) which assesses four dimensions of depressive symptoms (emotional, cognitive, somatic and interpersonal). The SCS-Y was shown to have good reliability and validity. The MIMIC model produced a good model fit for a hypothetical six-factor model (CFI = 0.980; TLI = 0.974; RMSEA = 0.038) and no item was flagged for DIF across gender. A gender difference was observed between SCS-Y factors and depression dimensions. Conclusions: The SCS-Y exhibits good psychometric characteristics, including measurement invariance across gender. The study also highlights the gender difference between self-compassion factors and depression dimensions.

Keywords: self compassion, gender, depression, structural equation modelling, MIMIC model

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Authors: Zhifang Liao, Yanbing Li, Li Xu, Yan Zhang, Xiaoping Fan, Jinsong Wu

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Pull Request (PR) is the primary method for code contributions from the external contributors in Github. PR review is an essential part of open source software developments for maintaining the quality of software. Matching a new PR of an appropriate integrator will make the PR review more effective. However, PR and integrator matching are now organized manually in Github. To reduce this cost, we presented an AIPM model to predict highly relevant integrator of incoming PRs. AIPM uses topic model to extract topics from the PRs, and builds a one-to-one correspondence between topics and integrators. Then, AIPM finds the most suitable integrator according to the maximum entry of the topic-document distribution. On average, AIPM can reach a precision of 60%, and even in some projects, can reach a precision of 80%.

Keywords: pull Request, integrator matching, Github, open source project, topic model

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Authors: Kazuyoshi Mori

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In this paper, we consider the parametrization of Anantharam’s model within the framework of the factorization approach. In the parametrization, we investigate the number of required parameters of Anantharam’s model. We consider single-input single-output systems in this paper. By the investigation, we find three cases that are (1) there exist plants which require only one parameter and (2) two parameters, and (3) the number of parameters is at most three.

Keywords: linear systems, parametrization, coprime factorization, number of parameters

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Authors: Zhidong Zhang

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This study established a mixed method model in assessing statistics learning with Bayesian network models. There are three variants in exploratory sequential designs. There are three linked steps in one of the designs: qualitative data collection and analysis, quantitative measure, instrument, intervention, and quantitative data collection analysis. The study used a scoring model of analysis of variance (ANOVA) as a content domain. The research study is to examine students’ learning in both semantic and performance aspects at fine grain level. The ANOVA score model, y = α+ βx1 + γx1+ ε, as a cognitive task to collect data during the student learning process. When the learning processes were decomposed into multiple steps in both semantic and performance aspects, a hierarchical Bayesian network was established. This is a theory-driven process. The hierarchical structure was gained based on qualitative cognitive analysis. The data from students’ ANOVA score model learning was used to give evidence to the hierarchical Bayesian network model from the evidential variables. Finally, the assessment results of students’ ANOVA score model learning were reported. Briefly, this was a mixed method research design applied to statistics learning assessment. The mixed methods designs expanded more possibilities for researchers to establish advanced quantitative models initially with a theory-driven qualitative mode.

Keywords: exploratory sequential design, ANOVA score model, Bayesian network model, mixed methods research design, cognitive analysis

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Authors: Ibrahim Shaker, Amr El Hossany, Moustafa Osman, Mohamed El Raey

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This paper will explore integration model between GIS–SCADA system and enclosure quantification model to approach the impact of failure-safe event. There are real demands to identify spatial objects and improve control system performance. Nevertheless, the employed methodology is predicting electro-mechanic operations and corresponding time to environmental incident variations. Open processing, as object systems technology, is presented for integration enclosure database with minimal memory size and computation time via connectivity drivers such as ODBC:JDBC during main stages of GIS–SCADA connection. The function of Geographic Information System is manipulating power distribution in contrast to developing issues. In other ward, GIS-SCADA systems integration will require numerical objects of process to enable system model calibration and estimation demands, determine of past events for analysis and prediction of emergency situations for response training.

Keywords: air dispersion model, environmental management, SCADA systems, GIS system, integration power system

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Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

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In this paper, we present the human action recognition method using the variational Bayesian HMM with the Dirichlet process mixture (DPM) of the Gaussian-Wishart emission model (GWEM). First, we define the Bayesian HMM based on the Dirichlet process, which allows an infinite number of Gaussian-Wishart components to support continuous emission observations. Second, we have considered an efficient variational Bayesian inference method that can be applied to drive the posterior distribution of hidden variables and model parameters for the proposed model based on training data. And then we have derived the predictive distribution that may be used to classify new action. Third, the paper proposes a process of extracting appropriate spatial-temporal feature vectors that can be used to recognize a wide range of human behaviors from input video image. Finally, we have conducted experiments that can evaluate the performance of the proposed method. The experimental results show that the method presented is more efficient with human action recognition than existing methods.

Keywords: human action recognition, Bayesian HMM, Dirichlet process mixture model, Gaussian-Wishart emission model, Variational Bayesian inference, prior distribution and approximate posterior distribution, KTH dataset

Procedia PDF Downloads 357

Authors: Chaitanya R. Mali, V. Vinod, Ashwin W. Patwardhan

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Design of long vertical steam generator (SG) tubes in nuclear power plant involves an understanding of different aspects of flow boiling phenomenon such as flow instabilities, flow regimes, dry out, critical heat flux, pressure drop, etc. The knowledge of the prediction of local thermal hydraulic characteristics is necessary to understand these aspects. For this purpose, the methodology has been developed which covers all the flow boiling regimes to model full range flow boiling phenomenon. In this methodology, the vertical tube is divided into four sections based on vapor fraction value at the end of each section. Different modeling strategies have been applied to the different sections of the vertical tube. Computational fluid dynamics simulations have been performed on a vertical SG tube of 0.0126 m inner diameter and 23 m length. The thermal hydraulic parameters such as vapor fraction, liquid temperature, heat transfer coefficient, pressure drop, heat flux distribution have been analyzed for different designed heat duties (1.1 MW (20%) to 3.3 MW (60%)) and flow conditions (10 % to 80 %). The sensitivity of different boiling parameters such as bubble departure diameter, nucleation site density, bubble departure frequency on the thermal hydraulic parameters was also studied. Flow instability has been observed at 20 % designed heat duty and 20 % flow conditions.

Keywords: thermal hydraulics, boiling, vapor fraction, sensitivity

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Authors: Ariful Islam, Showkat Ahmad Lone

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The Mukherjee-Islam Model is commonly used as a simple life time distribution to assess system reliability. The model exhibits a better fit for failure information and provides more appropriate information about hazard rate and other reliability measures as shown by various authors. It is possible to introduce a location parameter at a time (i.e., a time before which failure cannot occur) which makes it a more useful failure distribution than the existing ones. Even after shifting the location of the distribution, it represents a decreasing, constant and increasing failure rate. It has been shown to represent the appropriate lower tail of the distribution of random variables having fixed lower bound. This study presents the reliability computations and probability weighted moment estimation of three parameter model. A comparative analysis is carried out between three parameters finite range model and some existing bathtub shaped curve fitting models. Since probability weighted moment method is used, the results obtained can also be applied on small sample cases. Maximum likelihood estimation method is also applied in this study.

Keywords: comparative analysis, maximum likelihood estimation, Mukherjee-Islam failure model, probability weighted moment estimation, reliability

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Authors: Junjie Peng, Jinbao Chen, Shuai Kong, Danxu Liu

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On the basis of traditional resource allocation strategies, the usage of resources on physical servers in cloud data center is great uncertain. It will cause waste of resources if the assignment of tasks is not enough. On the contrary, it will cause overload if the assignment of tasks is too much. This is especially obvious when the applications are the same type because of its resource preferences. Considering CPU intensive application is one of the most common types of application in the cloud, we studied the optimization strategy for CPU intensive applications on the same server. We used resource preferences to analyze the case that multiple CPU intensive applications run simultaneously, and put forward a model which can predict the execution time for CPU intensive applications which run simultaneously. Based on the prediction model, we proposed the method to select the appropriate number of applications for a machine. Experiments show that the model can predict the execution time accurately for CPU intensive applications. To improve the execution efficiency of applications, we propose a scheduling model based on priority for CPU intensive applications. Extensive experiments verify the validity of the scheduling model.

Keywords: cloud computing, CPU intensive applications, resource optimization, strategy

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Authors: Kholod Hajo

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In this study COMSOL Multiphysics was used to design lateral flow biosensors (LFBs) which provide advantages in low cost, simplicity, rapidity, stability and portability thus making LFBs popular in biomedical, agriculture, food and environmental sciences. This study was focused on simulation model of biosensor based on gold nanoparticles (GNPs) designed using software package (COMSOL Multiphysics), the magnitude of the laminar velocity field in the flow cell, concentration distribution in the analyte stream and surface coverage of adsorbed species and average fractional surface coverage of adsorbed analyte were discussed from the model and couples of suggestion was given in order to functionalize GNPs and to increase the accuracy of the biosensor design, all above were obtained acceptable results.

Keywords: model, gold nanoparticles, biosensor, COMSOL Multiphysics

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Authors: Nai-Chia Chao, Meng-Chi Shih

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Under today’s fast technology and massive data era, the working method start to change. In this study, based under literature meaning of “Co-working” we had implemented the new “Co-working innovation model”. Research concluded that co-working innovation model shall not be limited in co-working space but use under different field when applying multiple art integration stragies. Research show co-working should not be limited in special field or group, should be use or adapt whenever different though or ideas where found, it should be use under different field and plans.

Keywords: arts integration, co-working, children's musical

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Authors: Alper Taner, Yesim Benal Oztekin, Huseyin Duran

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In this study, an Artificial Neural Network (ANN) was developed in order to classify barley varieties. For this purpose, physical properties of barley varieties were determined and ANN techniques were used. The physical properties of 8 barley varieties grown in Turkey, namely thousand kernel weight, geometric mean diameter, sphericity, kernel volume, surface area, bulk density, true density, porosity and colour parameters of grain, were determined and it was found that these properties were statistically significant with respect to varieties. As ANN model, three models, N-l, N-2 and N-3 were constructed. The performances of these models were compared. It was determined that the best-fit model was N-1. In the N-1 model, the structure of the model was designed to be 11 input layers, 2 hidden layers and 1 output layer. Thousand kernel weight, geometric mean diameter, sphericity, kernel volume, surface area, bulk density, true density, porosity and colour parameters of grain were used as input parameter; and varieties as output parameter. R2, Root Mean Square Error and Mean Error for the N-l model were found as 99.99%, 0.00074 and 0.009%, respectively. All results obtained by the N-l model were observed to have been quite consistent with real data. By this model, it would be possible to construct automation systems for classification and cleaning in flourmills.

Keywords: physical properties, artificial neural networks, barley, classification

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Authors: Long Pham, Julia Blanke

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An increasingly popular way of establishing citizen engagement within communities is through ‘city apps’. Currently, most of these mobile applications seem to be extensions of the existing communication media, sometimes merely replicating the information available on the classical city web sites, and therefore provide minimal additional impact on citizen behavior and engagement. In order to overcome this challenge, we propose to use a holistic behavioral model to generate dynamic and contextualized app content based on optimizing well defined city-related performance goals constrained by the proposed behavioral model. In this paper, we will show how the data collected by the CorkCitiEngage project in the Irish city of Cork can be utilized to calibrate aspects of the proposed model enabling the design of a personalized citizen engagement app aiming at positively influencing people’s behavior towards more active participation in their communities. We will focus on the important aspect of intentions to act, which is essential for understanding the reasons behind the common value-action-gap being responsible for the mismatch between good intentions and actual observable behavior, and will discuss how customized app design can be based on a rigorous model of behavior optimized towards maximizing well defined city-related performance goals.

Keywords: city apps, holistic behaviour model, intention to act, value-action-gap, citizen engagement

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Authors: E. Koyuncu

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The problem of Order Acceptance and Scheduling (OAS) is defined as a joint decision of which orders to accept for processing and how to schedule them. Any linear programming model representing real-world situation involves the parameters defined by the decision maker in an uncertain way or by means of language statement. Fuzzy data can be used to incorporate vagueness in the real-life situation. In this study, a fuzzy mathematical model is proposed for a single machine OAS problem, where the orders are defined by their fuzzy due dates, fuzzy processing times, and fuzzy sequence dependent setup times. The signed distance method, one of the fuzzy ranking methods, is used to handle the fuzzy constraints in the model.

Keywords: fuzzy mathematical programming, fuzzy ranking, order acceptance, single machine scheduling

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Authors: Abderazak Guettaf

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The mathematical models of the physical phenomena interacting in inductive plasma were described by the physics equations of the continuous mediums. A 3D model based on magnetic potential vector and electric scalar potential (A, V) formulation is used. The finished volume method is applied to electromagnetic equation, to obtain the field distribution inside the plasma. The numerical results of the method developed on a basic model designed starting from a real three-dimensional model were exposed. From the mathematical model 3D spreading assumptions and boundary conditions, we evaluated the electric field in the load and we have developed a numerical code made under the MATLAB environment, all verifying the effectiveness and validity of this code.

Keywords: electric field, 3D magnetic potential vector and electric scalar potential (A, V) formulation, finished volumes, annular plasma

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Authors: Mohamed Belhorma, Aboubakar S. Bouchikhi, Belkacem Bounab

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This paper addresses modeling a Double A-Arm suspension, a three-dimensional nonlinear model has been developed using the multibody systems formalism. Dynamical study of the different components responses was done, particularly for the wheel assembly. To validate those results, the system was constructed and simulated by RecurDyn, a professional multibody dynamics simulation software. The model has been used as the Objectif function in an optimization algorithm for ride quality improvement.

Keywords: double A-Arm suspension, multibody systems, ride quality optimization, dynamic simulation

Procedia PDF Downloads 139

Authors: Ashvinie Thembiliyagoda, Kasun De Silva, Nimal Wijayaratna

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The lowering of the riverbed level as a result of water erosion is termed as scouring. This phenomenon remarkably undermines the potential stability of the bridge pier, causing a threat of failure or collapse. The formation of vortices in the vicinity of bridges due to the obstruction caused by river flow is the main reason behind this pursuit. Scouring is aggravated by factors including high flow rates, bridge pier geometry, sediment configuration etc. Tackling scour-related problems when they become severe is more costly and disruptive compared to implementing preventive measures based on predicted scour depths. This paper presents a comprehensive investigation of the development of a numerical model that could reproduce the scouring effect around bridge piers and estimate the scour depth. The numerical model was developed for one selected bridge in Sri Lanka, the Kelanisiri Bridge. HEC-RAS two-dimensional (2D) modeling approach was utilized for the development of the model and was calibrated and validated with field data. To further enhance the reliability of the model, a physical model was developed, allowing for additional validation. Results from the numerical model were compared with those obtained from the physical model, revealing a strong correlation between the two methods and confirming the numerical model's accuracy in predicting scour depths. The findings from this study underscore the ability of the HEC-RAS two-dimensional modeling approach for the estimation of scour depth around bridge piers. The developed model is able to estimate the scour depth under varying flow conditions, and its flexibility allows it to be adapted for application to other bridges with similar hydraulic and geomorphological conditions, providing a robust tool for widespread use in scour estimation. The developed two-dimensional model not only offers reliable predictions for the case study bridge but also holds significant potential for broader implementation, contributing to the improved design and maintenance of bridge structures in diverse environments.

Keywords: piers, scouring, HEC-RAS, physical model

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Authors: Marcio Mesquita, Diogo Henrique Morato de Moraes, Henrique Fonseca Elias de Oliveira, Rilner Alves Flores, Mateus Rodrigues Ferreira, Dalva Graciano Ribeiro

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This study aimed to analyze the movement of water in irrigated and non-irrigated rice (Oryza sativa L.) leaves, from the xylem to the stomata, through numerical simulations. Through three-dimensional modeling, it was possible to determine how the spacing of parenchyma cells and the permeability of these cells influence the apoplastic flow and the opening of the stomata. The thickness of the cuticle and the number of vascular bundles are greater in plants subjected to water stress, indicating an adaptive response of plants to environments with water deficit. In addition, numerical simulations revealed that the opening of the stomata, the permeability of the parenchyma cells and the cell spacing have significant impacts on the energy loss and the speed of water movement. It was observed that a more open stoma facilitates water flow, decreasing the resistance and energy required for transport, while higher levels of permeability reduce energy loss, indicating that a more permeable tissue allows for more efficient water transport. Furthermore, it was possible to note that stomatal aperture, parenchyma permeability and cell spacing are crucial factors in the efficient water management of plants, especially under water stress conditions. These insights are essential for the development of more effective agricultural management strategies and for the breeding of plant varieties that are more resistant to adverse growing conditions. Computed fluid dynamics has allowed us to overcome the limitations of conventional techniques by providing a means to visualize and understand the complex hydrodynamic processes within the vascular system of plants.

Keywords: numerical modeling, vascular anatomy, vascular hydrodynamics, xylem, Oryza sativa L.

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Authors: Nicolò Vaiana, Giorgio Serino

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In this paper, an advanced Nonlinear Exponential Model (NEM), able to simulate the uniaxial dynamic behavior of seismic isolators having a continuously decreasing tangent stiffness with increasing displacement in the relatively large displacements range and a hardening or softening behavior at large displacements, is presented. The mathematical model is validated by comparing the experimental force-displacement hysteresis loops obtained during cyclic tests, conducted on a helical wire rope isolator and a recycled rubber-fiber reinforced bearing, with those predicted analytically. Good agreement between the experimental and simulated results shows that the proposed model can be an effective numerical tool to predict the force-displacement relationship of seismic isolation devices within the large displacements range. Compared to the widely used Bouc-Wen model, unable to simulate the response of seismic isolators at large displacements, the proposed one allows to avoid the numerical solution of a first order nonlinear ordinary differential equation for each time step of a nonlinear time history analysis, thus reducing the computation effort. Furthermore, the proposed model can simulate the smooth transition of the hysteresis loops from small to large displacements by adopting only one set of five parameters determined from the experimental hysteresis loops having the largest amplitude.

Keywords: base isolation, hardening behavior, nonlinear exponential model, seismic isolators, softening behavior

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Authors: Merey M. Sarsengeldin, Alexandr S. Kolokhmatov, Galiya Seidaliyeva, Alexandr Ozerov, Sanim T. Imatayeva

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This series of interdisciplinary studies is an attempt to investigate and develop a scalable model of fair socioeconomic relations on the base of blockchain using positive psychology techniques and Machine Learning algorithms for data analytics. In this particular study, we use hyperinteraction approach and intuition to investigate their influence on 'wisdom of crowds' via created mobile application which was created for the purpose of this research. Along with the public blockchain and private Decentralized Autonomous Organization (DAO) which were elaborated by us on the base of Ethereum blockchain, a model of fair financial relations of members of DAO was developed. We developed a smart contract, so-called, Fair Price Protocol and use it for implementation of model. The data obtained from mobile application was analyzed by ML algorithms. A model was tested on football matches.

Keywords: blockchain, Naïve Bayes algorithm, hyperinteraction, intuition, wisdom of crowd, decentralized autonomous organization

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Authors: A. Buruzs, M. F. Hatwágner, L. T. Kóczy

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The aim of the present paper is to develop an integrated method that may provide assistance to decision makers during system planning, design, operation and evaluation. In order to support the realization of Circular Economy (CE), it is essential to evaluate local needs and conditions which help to select the most appropriate system components and resource needs. Each of these activities requires careful planning, however, the model of CE offers a comprehensive interdisciplinary framework. The aim of this research was to develop and to introduce a practical methodology for evaluation of local and regional opportunities to promote CE.

Keywords: circular economy, factors, fuzzy cognitive map, model reduction, sustainability

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Authors: Ana Paula Camelo, Keila Sanches

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The Geographically Weighted Regression (GWR) was proposed in geography literature to allow relationship in a regression model to vary over space. In Brazil, the agricultural exploitation of the Cerrado Biome is the main cause of deforestation. In this study, we propose a methodology using geostatistical methods to characterize the spatial dependence of deforestation in the Cerrado based on agricultural production indicators. Therefore, it was used the set of exploratory spatial data analysis tools (ESDA) and confirmatory analysis using GWR. It was made the calibration a non-spatial model, evaluation the nature of the regression curve, election of the variables by stepwise process and multicollinearity analysis. After the evaluation of the non-spatial model was processed the spatial-regression model, statistic evaluation of the intercept and verification of its effect on calibration. In an analysis of Spearman’s correlation the results between deforestation and livestock was +0.783 and with soybeans +0.405. The model presented R²=0.936 and showed a strong spatial dependence of agricultural activity of soybeans associated to maize and cotton crops. The GWR is a very effective tool presenting results closer to the reality of deforestation in the Cerrado when compared with other analysis.

Keywords: deforestation, geographically weighted regression, land use, spatial analysis

Procedia PDF Downloads 366

Authors: Fong-Zuo Lee, Jihn-Sung Lai, Yung-Bin Lin, Xiaoqin Liu, Kuo-Chun Chang, Zhi-Xian Yang, Wen-Dar Guo, Jian-Hao Hong

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In recent years, climate change is a major factor to increase rainfall intensity and extreme rainfall frequency. The increased rainfall intensity and extreme rainfall frequency will increase the probability of flash flood with abundant sediment transport in a river basin. The floods caused by heavy rainfall may cause damages to the bridge, embankment, hydraulic works, and the other disasters. Therefore, the foundation scouring of bridge pier, embankment and spur dike caused by floods has been a severe problem in the worldwide. This severe problem has happened in many East Asian countries such as Taiwan and Japan because of these areas are suffered in typhoons, earthquakes, and flood events every year. Results from the complex interaction between fluid flow patterns caused by hydraulic works and the sediment transportation leading to the formation of river morphology, it is extremely difficult to develop a reliable and durable sensor to measure river bed degradation and bridge pier scouring. Therefore, an innovative scour monitoring sensor using vibration-based Micro-Electro Mechanical Systems (MEMS) was developed. This vibration-based MEMS sensor was packaged inside a stainless sphere with the proper protection of the full-filled resin, which can measure free vibration signals to detect scouring/deposition processes at the bridge pier. In addition, a friendly operational system includes rainfall runoff model, one-dimensional and two-dimensional numerical model, and the applicability of sediment transport equation and local scour formulas of bridge pier are included in this research. The friendly operational system carries out the simulation results of flood events that includes the elevation changes of river bed erosion near the specified bridge pier and the erosion depth around bridge piers. In addition, the system is developed with easy operation and integrated interface, the system can supplies users to calibrate and verify numerical model and display simulation results through the interface comparing to the scour monitoring sensors. To achieve the forecast of the erosion depth of river bed and main bridge pier in the study area, the system also connects the rainfall forecast data from Taiwan Typhoon and Flood Research Institute. The results can be provided available information for the management unit of river and bridge engineering in advance.

Keywords: flash flood, river bed degradation, bridge pier scouring, a friendly operational system

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Authors: A. Natsir, M. Nadir, S. Syahrir, A. Mujnisa

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In tropical countries such as in Indonesia, rice straw plays an important role in fulfilling the needs of feed for ruminant, especially during the dry season in which the availability of forage is very limited. However, the main problem of using rice straw as a feedstuff is low digestibility due to the existence of the links between lignin and cellulose or hemicellulose, and imbalance of its minerals content. One alternative to solve this problem is by application of biodecomposer (BS) derived from rumen bacterial of the ruminant. This study was designed to assess the effects of BS application on the changes of the chemical composition of rice straw. Four adults local buffalo raised under typical feeding conditions were used as a source of inoculum for BS development. The animal was fed for a month with a diet consisted of rice straw and elephant grass before taking rumen fluid samples. Samples of rumen fluid were inoculated in the carboxymethyl cellulose (CMC) media under anaerobic condition for 48 hours at 37°C. The mixture of CMC media and microbes are ready to be used as a biodecomposer following incubation of the mixture under anaerobic condition for 7 days at 45°C. The effectiveness of BS then assessed by applying the BS on the straw according to completely randomized design consisted of four treatments and three replication. One hundred g of ground coarse rice straw was used as the substrate. The BS was applied to the rice straw substrate with the following composition: Rice straw without BS (P0), rice straw + 5% BS (P1), rice straw +10% BS (P2), and rice straw + 15% BS. The mixture of rice straw and BS then fermented under anaerobic for four weeks. Following the fermentation, the chemical composition of rice straw was evaluated. The results indicated that the crude protein content of rice straw significantly increased (P < 0.05) as the level of BS increased. On the other hand, the concentration of crude fiber of the rice straw was significantly decreased (P < 0.05) as the level of BS increased. Other nutrients such as minerals did not change (P > 0.05) due to the treatments. In conclusion, application of BS developed from rumen bacterial of buffalo has a promising prospect to be used as a biological agent to improve the quality of rice straw as feeding for ruminant.

Keywords: biodecomposer, local buffalo, rumen microbial, chemical composition

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Authors: Reza Miresmaeili, Asghar Heydari Astaraee, Fereshteh Dolati

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In the present study, an analytical model based on dislocation density model was developed to simulate grain refinement in surface mechanical attrition treatment (SMAT). The correlation between SMAT time and development in plastic strain on one hand, and dislocation density evolution, on the other hand, was established to simulate the grain refinement in SMAT. A dislocation density-based constitutive material law was implemented using VUHARD subroutine. A random sequence of shots is taken into consideration for multiple impacts model using Python programming language by utilizing a random function. The simulation technique was to model each impact in a separate run and then transferring the results of each run as initial conditions for the next run (impact). The developed Finite Element (FE) model of multiple impacts describes the coverage evolution in SMAT. Simulations were run to coverage levels as high as 4500%. It is shown that the coverage implemented in the FE model is equal to the experimental coverage. It is depicted that numerical SMAT coverage parameter is adequately conforming to the well-known Avrami model. Comparison between numerical results and experimental measurements for residual stresses and depth of deformation layers confirms the performance of the established FE model for surface engineering evaluations in SMA treatment. X-ray diffraction (XRD) studies of grain refinement, including resultant grain size and dislocation density, were conducted to validate the established model. The full width at half-maximum in XRD profiles can be used to measure the grain size. Numerical results and experimental measurements of grain refinement illustrate good agreement and show the capability of established FE model to predict the gradient microstructure in SMA treatment.

Keywords: dislocation density, grain refinement, severe plastic deformation, simulation, surface mechanical attrition treatment

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Authors: M. Agostini, A. Sonato, G. Greco, M. Travagliati, G. Ruffato, E. Gazzola, D. Liuni, F. Romanato, M. Cecchini

Abstract:

Since their first demonstration in the early 1980s, surface plasmon resonance (SPR) sensors have been widely recognized as useful tools for detecting chemical and biological species, and the interest of the scientific community toward this technology has known a rapid growth in the past two decades owing to their high sensitivity, label-free operation and possibility of real-time detection. Recent works have suggested that a turning point in SPR sensor research would be the combination of SPR strategies with other technologies in order to reduce human handling of samples, improve integration and plasmonic sensitivity. In this light, microfluidics has been attracting growing interest. By properly designing microfluidic biochips it is possible to miniaturize the analyte-sensitive areas with an overall reduction of the chip dimension, reduce the liquid reagents and sample volume, improve automation, and increase the number of experiments in a single biochip by multiplexing approaches. However, as the fluidic channel dimensions approach the micron scale, laminar flows become dominant owing to the low Reynolds numbers that typically characterize microfluidics. In these environments mixing times are usually dominated by diffusion, which can be prohibitively long and lead to long-lasting biochemistry experiments. An elegant method to overcome these issues is to actively perturb the liquid laminar flow by exploiting surface acoustic waves (SAWs). With this work, we demonstrate a new approach for SPR biosensing based on the combination of microfluidics, SAW-induced mixing and the real-time phase-interrogation grating-coupling SPR technology. On a single lithium niobate (LN) substrate the nanostructured SPR sensing areas, interdigital transducer (IDT) for SAW generation and polydimethylsiloxane (PDMS) microfluidic chambers were fabricated. SAWs, impinging on the microfluidic chamber, generate acoustic streaming inside the fluid, leading to chaotic advection and thus improved fluid mixing, whilst analytes binding detection is made via SPR method based on SPP excitation via gold metallic grating upon azimuthal orientation and phase interrogation. Our device has been fully characterized in order to separate for the very first time the unwanted SAW heating effect with respect to the fluid stirring inside the microchamber that affect the molecules binding dynamics. Avidin/biotin assay and thiol-polyethylene glycol (bPEG-SH) were exploited as model biological interaction and non-fouling layer respectively. Biosensing kinetics time reduction with SAW-enhanced mixing resulted in a ≈ 82% improvement for bPEG-SH adsorption onto gold and ≈ 24% for avidin/biotin binding—≈ 50% and 18% respectively compared to the heating only condition. These results demonstrate that our biochip can significantly reduce the duration of bioreactions that usually require long times (e.g., PEG-based sensing layer, low concentration analyte detection). The sensing architecture here proposed represents a new promising technology satisfying the major biosensing requirements: scalability and high throughput capabilities. The detection system size and biochip dimension could be further reduced and integrated; in addition, the possibility of reducing biological experiment duration via SAW-driven active mixing and developing multiplexing platforms for parallel real-time sensing could be easily combined. In general, the technology reported in this study can be straightforwardly adapted to a great number of biological system and sensing geometry.

Keywords: biosensor, microfluidics, surface acoustic wave, surface plasmon resonance

Procedia PDF Downloads 285

Authors: Tory Erickson

Abstract:

The "Bidirectional Spacetime with Spatial Covariance and Wave-Particle Duality in Spacetime Flow" (BST-SCWPDF) Model introduces a framework aimed at unifying general relativity (GR) and quantum mechanics (QM). By proposing a concept of bidirectional spacetime, this model suggests that time can flow in more than one direction, thus offering a perspective on temporal dynamics. Integrated with spatial covariance and wave-particle duality in spacetime flow, the BST-SCWPDF Model resolves long-standing discrepancies between GR and QM. This unified theory has profound implications for quantum gravity, potentially offering insights into quantum entanglement, the collapse of the wave function, and the fabric of spacetime itself. The Bidirectional Spacetime with Spatial Covariance and Wave-Particle Duality in Spacetime Flow" (BST-SCWPDF) Model offers researchers a framework for a better understanding of theoretical physics.

Keywords: astrophysics, quantum mechanics, general relativity, unification theory, theoretical physics

Procedia PDF Downloads 91