Search results for: nonlinear modeling

Authors: F. Clara Fang, Hernan Castaneda

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The Connecticut Department of Transportation (ConnDOT) has constructed four roundabouts in the State of Connecticut within the past ten years. VISSIM traffic simulation software was utilized to analyze these roundabouts during their design phase. The queue length and level of service observed in the field appear to be better than predicted by the VISSIM model. The objectives of this project are to: identify VISSIM input variables most critical to accurate modeling; recommend VISSIM calibration factors; and, provide other recommendations for roundabout traffic operations modeling. Traffic data were collected at these roundabouts using Miovision Technologies. Cameras were set up to capture vehicle circulating activity and entry behavior for two weekdays. A large sample size of filed data was analyzed to achieve accurate and statistically significant results. The data extracted from the videos include: vehicle circulating speed; critical gap estimated by Maximum Likelihood Method; peak hour volume; follow-up headway; travel time; and, vehicle queue length. A VISSIM simulation of existing roundabouts was built to compare both queue length and travel time predicted from simulation with measured in the field. The research investigated a variety of simulation parameters as calibration factors for describing driver behaviors at roundabouts. Among them, critical gap is the most effective calibration variable in roundabout simulation. It has a significant impact to queue length, particularly when the volume is higher. The results will improve the design of future roundabouts in Connecticut and provide decision makers with insights on the relationship between various choices and future performance.

Keywords: driver critical gap, roundabout analysis, simulation, VISSIM modeling

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Authors: Hadi Ardiny, Amir Mohammad Beigzadeh

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Through the utilization of a combination of various sensors and data fusion methods, the detection of potential nuclear threats can be significantly enhanced by extracting more information from different data. In this research, an experimental and modeling approach was employed to track a radioactive source by combining a surveillance camera and a radiation detector (NaI). To run this experiment, three mobile robots were utilized, with one of them equipped with a radioactive source. An algorithm was developed in identifying the contaminated robot through correlation between camera images and camera data. The computer vision method extracts the movements of all robots in the XY plane coordinate system, and the detector system records the gamma-ray count. The position of the robots and the corresponding count of the moving source were modeled using the MCNPX simulation code while considering the experimental geometry. The results demonstrated a high level of accuracy in finding and locating the target in both the simulation model and experimental measurement. The modeling techniques prove to be valuable in designing different scenarios and intelligent systems before initiating any experiments.

Keywords: nuclear threats, radiation detector, MCNPX simulation, modeling techniques, intelligent systems

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Authors: Motalleb Byzedi, Seyedeh Chaman Naderi Korvandan

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Regarding annual statistics of groundwater level resources about current piezometers at Qorveh plains, both ARMA & PARMA modeling methods were applied in this study by the using of SAMS software. Upon performing required tests, a model was used with minimum amount of Akaike information criteria and suitable model was selected for piezometers. Then it was possible to make necessary estimations by using these models for future fluctuations in each piezometer. According to the results, ARMA model had more facilities for modeling of aquifer. Also it was cleared that eastern parts of aquifer had more failures than other parts. Therefore it is necessary to prohibit critical parts along with more supervision on taking rates of wells.

Keywords: qorveh plain, groundwater level, ARMA, PARMA

Procedia PDF Downloads 276

Authors: Serena Gomez, Raeesa Tanseen, Netra Shaligram, Nithin Francis, Sandesh B. J.

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The human gut consists of a community of microbes which has a lot of effects on human health disease. Metabolic modeling can help to predict relative populations of stable microbes and their effect on health disease. In order to study and visualize microbes in the human gut, we developed a tool that offers the following modules: Build a tool that can be used to perform Flux Balance Analysis for microbes in the human gut using the Artificial Bee Colony optimization algorithm. Run simulations for an individual microbe in different conditions, such as aerobic and anaerobic and visualize the results of these simulations.

Keywords: microbes, metabolic modeling, flux balance analysis, artificial bee colony

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Authors: Amin Noor, Roslinda Nazar, Norihan Md. Arifin

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In this paper, a numerical and theoretical study has been performed for the stagnation-point boundary layer flow and heat transfer towards a shrinking sheet in a nanofluid. The mathematical nanofluid model in which the effect of the nanoparticle volume fraction is taken into account is considered. The governing nonlinear partial differential equations are transformed into a system of nonlinear ordinary differential equations using a similarity transformation which is then solved numerically using the function bvp4c from Matlab. Numerical results are obtained for the skin friction coefficient, the local Nusselt number as well as the velocity and temperature profiles for some values of the governing parameters, namely the nanoparticle volume fraction Φ, the shrinking parameter λ and the Prandtl number Pr. Three different types of nanoparticles are considered, namely Cu, Al2O3 and TiO2. It is found that solutions do not exist for larger shrinking rates and dual (upper and lower branch) solutions exist when λ < -1.0. A stability analysis has been performed to show which branch solutions are stable and physically realizable. It is also found that the upper branch solutions are stable while the lower branch solutions are unstable.

Keywords: heat transfer, nanofluid, shrinking sheet, stability analysis, stagnation-point flow

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Authors: Ghasem Sharifi, Hamed Shahmohamadi Ousaloo, Milad Azimi, Mehran Mirshams

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The ever-increasing use of satellites demands a search for increasingly accurate and reliable pointing systems. Reaction wheels are rotating devices used commonly for the attitude control of the spacecraft since provide a wide range of torque magnitude and high reliability. The numerical modeling of this device can significantly enhance the accuracy of the satellite control in space. Modeling the wheel rotation in the presence of the various frictions is one of the critical parts of this approach. This paper presents a Dynamic Model Control of a Reaction Wheel (DMCR) in the current control mode. In current-mode, the required current is delivered to the coils in order to achieve the desired torque. During this research, all the friction parameters as viscous and coulomb, motor coefficient, resistance and voltage constant are identified. In order to model identification of a reaction wheel, numerous varying current commands apply on the particular wheel to verify the estimated model. All the parameters of DMCR are identified by classical Levenberg-Marquardt (CLM) optimization method. The experimental results demonstrate that the developed model has an appropriate precise and can be used in the satellite control simulation.

Keywords: experimental modeling, friction parameters, model identification, reaction wheel

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Authors: Woo Young Jung, Min Ho Kwon, Bu Seog Ju

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A failure of the non-structural component can cause significant damages in critical facilities such as nuclear power plants and hospitals. Historically, it was reported that the damage from the leakage of sprinkler systems, resulted in the shutdown of hospitals for several weeks by the 1971 San Fernando and 1994 North Ridge earthquakes. In most cases, water leakages were observed at the cross joints, sprinkler heads, and T-joint connections in piping systems during and after the seismic events. Hence, the primary objective of this study was to understand the seismic performance of T-joint connections and to develop an analytical Finite Element (FE) model for the T-joint systems of 2-inch fire protection piping system in hospitals subjected to seismic ground motions. In order to evaluate the FE models of the piping systems using OpenSees, two types of materials were used: 1) Steel 02 materials and 2) Pinching 4 materials. Results of the current study revealed that the nonlinear moment-rotation FE models for the threaded T-joint reconciled well with the experimental results in both FE material models. However, the system-level fragility determined from multiple nonlinear time history analyses at the threaded T-joint was slightly different. The system-level fragility at the T-joint, determined by Pinching 4 material was more conservative than that of using Steel 02 material in the piping system.

Keywords: fragility, t-joint, piping, leakage, sprinkler

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Authors: Young Jae Choung, Seoung Bum Kim

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Statistical Process Control (SPC) is a popular technique for process monitoring. A widely used tool in SPC is a control chart, which is used to detect the abnormal status of a process and maintain the controlled status of the process. Traditional control charts, such as Hotelling’s T2 control chart, are effective techniques to detect abnormal observations and monitor processes. However, many complicated manufacturing systems exhibit nonlinearity because of the different demands of the market. In this case, the unregulated use of a traditional linear modeling approach may not be effective. In reality, many industrial processes contain the nonlinear and time-varying properties because of the fluctuation of process raw materials, slowing shift of the set points, aging of the main process components, seasoning effects, and catalyst deactivation. The use of traditional SPC techniques with time-varying data will degrade the performance of the monitoring scheme. To address these issues, in the present study, we propose a parameterless self-organizing map (PLSOM)-based control chart. The PLSOM-based control chart not only can manage a situation where the distribution or parameter of the target observations changes, but also address the nonlinearity of modern manufacturing systems. The control limits of the proposed PLSOM chart are established by estimating the empirical level of significance on the percentile using a bootstrap method. Experimental results with simulated data and actual process data from a thin-film transistor-liquid crystal display process demonstrated the effectiveness and usefulness of the proposed chart.

Keywords: control chart, parameter-less self-organizing map, self-organizing map, time-varying property

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Authors: Donald G. Danmeier, Gian Marco Pizzo, Matthew Brennan

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Although wetlands have been proposed as a green alternative to manage coastal flood hazards because of their capacity to adapt to sea level rise and provision of multiple ecological and social co-benefits, they are often overlooked due to challenges in quantifying the uncertainty and naturally, variability of these systems. This objective of this study was to quantify wave attenuation provided by a natural marsh surrounding a large oil refinery along the US Gulf Coast that has experienced steady erosion along the shoreward edge. The vegetation module of the SWAN was activated and coupled with a hydrodynamic model (DELFT3D) to capture two-way interactions between the changing water level and wavefield over the course of a storm event. Since the marsh response to relative sea level rise is difficult to predict, a range of future marsh morphologies is explored. Numerical results were examined to determine the amount of wave attenuation as a function of marsh extent and the relative contributions from white-capping, depth-limited wave breaking, bottom friction, and flexing of vegetation. In addition to the coupled DELFT3D-SWAN modeling of a storm event, an uncoupled SWAN-VEG model was applied to a simplified bathymetry to explore a larger experimental design space. The wave modeling revealed that the rate of wave attenuation reduces for higher surge but was still significant over a wide range of water levels and outboard wave heights. The results also provide insights to the minimum marsh extent required to fully realize the potential wave attenuation so the changing coastal hazards can be managed.

Keywords: green infrastructure, wave attenuation, wave modeling, wetland

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Authors: Vladimir A. Vinnikov

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The paper proposes a model of an inhomogeneous rock mass with initially random distribution of microcracks on mineral grain boundaries. It describes the behavior of cracks in a medium under the effect of thermal field, the medium heated instantaneously to a predetermined temperature. Crack growth occurs according to the concept of fracture mechanics provided that the stress intensity factor K exceeds the critical value of Kc. The modeling of thermally induced acoustic emission memory effects is based on the assumption that every event of crack nucleation or crack growth caused by heating is accompanied by a single acoustic emission event. Parameters of the thermally induced acoustic emission memory effect produced by cyclic heating and cooling (with the temperature amplitude increasing from cycle to cycle) were calculated for several rock texture types (massive, banded, and disseminated). The study substantiates the adaptation of the proposed model to humidity interference with the thermally induced acoustic emission memory effect. The influence of humidity on the thermally induced acoustic emission memory effect in quasi-homogeneous and banded rocks is estimated. It is shown that such modeling allows the structure and texture of rocks to be taken into account and the influence of interference factors on the distinctness of the thermally induced acoustic emission memory effect to be estimated. The numerical modeling can be used to obtain information about the thermal impacts on rocks in the past and determine the degree of rock disturbance by means of non-destructive testing.

Keywords: degree of rock disturbance, non-destructive testing, thermally induced acoustic emission memory effects, structure and texture of rocks

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Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

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The physics-informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on a strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary conditions to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of the Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful in studying various optical phenomena.

Keywords: deep learning, optical soliton, physics informed neural network, partial differential equation

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Authors: Saeed Zeinali, Nasser Talebbeydokhti, Mehdi Saeidian, Shahrad Vosough

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In this article, bathymetry changes have been studied as a case study for Larak Island, located in The South of Iran. The advanced 2D model of Mike21 has been used for this purpose. A simple procedure has been utilized in this model. First, the hydrodynamic (HD) module of Mike21 has been used to obtain the required output for sediment transport model (ST module). The ST module modeled the area for tidal currents only. Bed level changes are resulted by series of modeling for both HD and ST module in 3 months time step. The final bathymetry in each time step is used as the primary bathymetry for next time step. This consecutive procedure been continued until bathymetry for the year 2020 is obtained.

Keywords: bed level changes, Larak Island, hydrodynamic, sediment transport

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Authors: Jamel Boukhatem, Mouldi Djelassi

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Contrary to the existing literature generally focusing on the role played by Sukuk in enhancing investors' and shareholders' wealth, this paper sheds some light on the Sukuk wealth effect across all economic agents: households, government, and investors by implementing a two-period life-cycle model with overlapping generations to show whether Sukuk is net wealth. The main findings are threefold: i) the effect of a change in Sukuk issuances on the consumers’ utility level will be different from one generation to another, ii) an increase in taxes due to the increase in Sukuk and rents is covered by transfers made by the members of generation 1 in the form of inheritance, and iii) the existence of a positive relationship between the asset prices representative of Sukuk and the real activity.

Keywords: Sukuk, households, investors, overlapping generations model, wealth, modeling

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Authors: S. Behnia, S. Fathizadeh, A. Akhshani

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In the recent decades, DNA has increasingly interested in the potential technological applications that not directly related to the coding for functional proteins that is the expressed in form of genetic information. One of the most interesting applications of DNA is related to the construction of nanostructures of high complexity, design of functional nanostructures in nanoelectronical devices, nanosensors and nanocercuits. In this field, DNA is of fundamental interest to the development of DNA-based molecular technologies, as it possesses ideal structural and molecular recognition properties for use in self-assembling nanodevices with a definite molecular architecture. Also, the robust, one-dimensional flexible structure of DNA can be used to design electronic devices, serving as a wire, transistor switch, or rectifier depending on its electronic properties. In order to understand the mechanism of the charge transport along DNA sequences, numerous studies have been carried out. In this regard, conductivity properties of DNA molecule could be investigated in a simple, but chemically specific approach that is intimately related to the Su-Schrieffer-Heeger (SSH) model. In SSH model, the non-diagonal matrix element dependence on intersite displacements is considered. In this approach, the coupling between the charge and lattice deformation is along the helix. This model is a tight-binding linear nanoscale chain established to describe conductivity phenomena in doped polyethylene. It is based on the assumption of a classical harmonic interaction between sites, which is linearly coupled to a tight-binding Hamiltonian. In this work, the Hamiltonian and corresponding motion equations are nonlinear and have high sensitivity to initial conditions. Then, we have tried to move toward the nonlinear dynamics and phase space analysis. Nonlinear dynamics and chaos theory, regardless of any approximation, could open new horizons to understand the conductivity mechanism in DNA. For a detailed study, we have tried to study the current flowing in DNA and investigated the characteristic I-V diagram. As a result, It is shown that there are the (quasi-) ohmic areas in I-V diagram. On the other hand, the regions with a negative differential resistance (NDR) are detectable in diagram.

Keywords: DNA conductivity, Landauer resistance, negative dierential resistance, Chaos theory, mean Lyapunov exponent

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Authors: Mei-Chun Chang

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Due to digital transformation and social media development in recent years, various real-time interactive digital tools have been developed to meet the design demands for virtual reality avatars, which also promote digital content learners' active participation in the creation process. As a result, new social media design tools have the characteristics of intuitive operation with a simplified interface for fast production, from which works can be simply created. This study carried out observations, records, questionnaire surveys, and interviews on the creation and learning of visual avatars made by students of the National Taiwan University of Science and Technology (NTUST) with the VRoid Studio 3D modeling tool so as to explore their learning effectiveness on the design of visual avatars. According to the results of this study, the VRoid Studio 3D character modeling tool has a positive impact on the learners and helps to improve their learning effectiveness. Students with low academic achievements said that they could complete the conceived modeling with their own thinking by using the design tool, which increased their sense of accomplishment. Conclusions are drawn according to the results, and relevant future suggestions are put forward.

Keywords: virtual avatar, character design, social media, vroid studio, creation, digital learning

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Authors: K. Passbakhsh

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Determination of reinforcement forces is one of the most important and main discussions in designing retaining walls. By determining these forces we refrain from conservative planning. By numerically modeling the reinforced soil retaining walls under dynamic loading reinforcement forces can be calculated. In this study we try to approach the gained forces by pseudo-static method according to FHWA code and gained forces from numerical modeling by finite element method, by selecting seismic horizontal coefficient for different wall height. PLAXIS software was used for numerical analysis. Then the effect of reinforcement stiffness and soil type on reinforcement forces is examined.

Keywords: reinforced soil, PLAXIS, reinforcement forces, retaining walls

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Authors: Maria Amodeo, Pasquale Arpaia, Marco Buzio, Vincenzo Di Capua, Francesco Donnarumma

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Different deep neural network architectures have been compared and tested to predict magnetic hysteresis in the context of pulsed electromagnets for experimental physics applications. Modelling quasi-static or dynamic major and especially minor hysteresis loops is one of the most challenging topics for computational magnetism. Recent attempts at mathematical prediction in this context using Preisach models could not attain better than percent-level accuracy. Hence, this work explores neural network approaches and shows that the architecture that best fits the measured magnetic field behaviour, including the effects of hysteresis and eddy currents, is the nonlinear autoregressive exogenous neural network (NARX) model. This architecture aims to achieve a relative RMSE of the order of a few 100 ppm for complex magnetic field cycling, including arbitrary sequences of pseudo-random high field and low field cycles. The NARX-based architecture is compared with the state-of-the-art, showing better performance than the classical operator-based and differential models, and is tested on a reference quadrupole magnetic lens used for CERN particle beams, chosen as a case study. The training and test datasets are a representative example of real-world magnet operation; this makes the good result obtained very promising for future applications in this context.

Keywords: deep neural network, magnetic modelling, measurement and empirical software engineering, NARX

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Authors: William Chung

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This paper is to study the use of multiple subproblems in Dantzig-Wolfe decomposition of linear programming (DW-LP). Traditionally, the decomposed LP consists of one LP master problem and one LP subproblem. The master problem and the subproblem is solved alternatively by exchanging the dual prices of the master problem and the proposals of the subproblem until the LP is solved. It is well known that convergence is slow with a long tail of near-optimal solutions (asymptotic convergence). Hence, the performance of DW-LP highly depends upon the number of decomposition steps. If the decomposition steps can be greatly reduced, the performance of DW-LP can be improved significantly. To reduce the number of decomposition steps, one of the methods is to increase the number of proposals from the subproblem to the master problem. To do so, we propose to add a quadratic approximation function to the LP subproblem in order to develop a set of approximate-LP subproblems (multiple subproblems). Consequently, in each decomposition step, multiple subproblems are solved for providing multiple proposals to the master problem. The number of decomposition steps can be reduced greatly. Note that each approximate-LP subproblem is nonlinear programming, and solving the LP subproblem must faster than solving the nonlinear multiple subproblems. Hence, using multiple subproblems in DW-LP is the tradeoff between the number of approximate-LP subproblems being formed and the decomposition steps. In this paper, we derive the corresponding algorithms and provide some simple computational results. Some properties of the resulting algorithms are also given.

Keywords: approximate subproblem, Dantzig-Wolfe decomposition, large-scale models, multiple subproblems

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Authors: Furkan Ozkan, M. Selcuk Arslan, Hatice Mercan

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Electric vehicles are becoming increasingly popular asa sustainable alternative to traditional combustion engine vehicles. However, to fully realize the potential of EVs in reducing environmental impact and energy consumption, efficient control strategies are essential. This study explores the application of green wave control using model predictive control for electric vehicles, coupled with energy consumption modeling using neural networks. The use of MPC allows for real-time optimization of the vehicles’ energy consumption while considering dynamic traffic conditions. By leveraging neural networks for energy consumption modeling, the EV's performance can be further enhanced through accurate predictions and adaptive control. The integration of these advanced control and modeling techniques aims to maximize energy efficiency and range while navigating urban traffic scenarios. The findings of this research offer valuable insights into the potential of green wave control for electric vehicles and demonstrate the significance of integrating MPC and neural network modeling for optimizing energy consumption. This work contributes to the advancement of sustainable transportation systems and the widespread adoption of electric vehicles. To evaluate the effectiveness of the green wave control strategy in real-world urban environments, extensive simulations were conducted using a high-fidelity vehicle model and realistic traffic scenarios. The results indicate that the integration of model predictive control and energy consumption modeling with neural networks had a significant impact on the energy efficiency and range of electric vehicles. Through the use of MPC, the electric vehicle was able to adapt its speed and acceleration profile in realtime to optimize energy consumption while maintaining travel time objectives. The neural network-based energy consumption modeling provided accurate predictions, enabling the vehicle to anticipate and respond to variations in traffic flow, further enhancing energy efficiency and range. Furthermore, the study revealed that the green wave control strategy not only reduced energy consumption but also improved the overall driving experience by minimizing abrupt acceleration and deceleration, leading to a smoother and more comfortable ride for passengers. These results demonstrate the potential for green wave control to revolutionize urban transportation by enhancing the performance of electric vehicles and contributing to a more sustainable and efficient mobility ecosystem.

Keywords: electric vehicles, energy efficiency, green wave control, model predictive control, neural networks

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Authors: Mirza Mohibulla Baig, Imil Hamda Imran, Tri Bagus Susilo, Sami El Ferik

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The paper deals with system identification and control a nonlinear model of semi-autonomous underwater vehicle (UUV). The input-output data is first generated using the experimental values of the model parameters and then this data is used to compute the estimated parameter values. In this study, we use the semi-autonomous UUV LAURS model, which is developed by the Sensors and Actuators Laboratory in University of Sao Paolo. We applied three methods to identify the parameters: integral method, which is a classical least square method, recursive least square, and weighted recursive least square. In this paper, we also apply three different inputs (step input, sine wave input and random input) to each identification method. After the identification stage, we investigate the control performance of yaw motion of nonlinear semi-autonomous Unmanned Underwater Vehicle (UUV) using feedback linearization-based controller. In addition, we compare the performance of the control with an integral and a non-integral part along with state feedback. Finally, disturbance rejection and resilience of the controller is tested. The results demonstrate the ability of the system to recover from such fault.

Keywords: system identification, underwater vehicle, integral method, recursive least square, weighted recursive least square, feedback linearization, integral error

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Authors: V. Pourmostaghimi, M. Zadshakoyan

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Efficiency and productivity of the finish hard turning can be enhanced impressively by utilizing accurate predictive models for cutting tool wear. However, the ability of genetic programming in presenting an accurate analytical model is a notable characteristic which makes it more applicable than other predictive modeling methods. In this paper, the genetic equation for modeling of tool flank wear is developed with the use of the experimentally measured flank wear values and genetic programming during finish turning of hardened AISI D2. Series of tests were conducted over a range of cutting parameters and the values of tool flank wear were measured. On the basis of obtained results, genetic model presenting connection between cutting parameters and tool flank wear were extracted. The accuracy of the genetically obtained model was assessed by using two statistical measures, which were root mean square error (RMSE) and coefficient of determination (R²). Evaluation results revealed that presented genetic model predicted flank wear over the study area accurately (R² = 0.9902 and RMSE = 0.0102). These results allow concluding that the proposed genetic equation corresponds well with experimental data and can be implemented in real industrial applications.

Keywords: cutting parameters, flank wear, genetic programming, hard turning

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Authors: Soulayma Smirani, Mourad Aidi, Taoufik Aguili

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Energy harvesting has arisen as a prominent research area for low power delivery to RF devices. Rectennas have become a key element in this technology. In this paper, electromagnetic modeling of a rectenna system is presented. In our approach, a hybrid technique was demonstrated to associate both the method of auxiliary sources (MAS) and MoM-GEC (the method of moments combined with the generalized equivalent circuit technique). Auxiliary sources were used in order to substitute specific electronic devices. Therefore, a simple and controllable model is obtained. Also, it can easily be interconnected to form different topologies of rectenna arrays for more energy harvesting. At last, simulation results show the feasibility and simplicity of the proposed rectenna model with high precision and computation efficiency.

Keywords: computational electromagnetics, MoM-GEC method, rectennas, RF energy harvesting

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Authors: Moumita Sit, Chaitali Ray

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The present article deals with the free vibration analysis of hybrid laminated composite structures with initial stresses developed in the laminates. Generally initial stresses may be developed in the laminates by temperature and moisture effect. In this study, an eight noded isoparametric plate bending element has been used for the finite element analysis of composite plates. A numerical model has been developed to assess the geometric nonlinear response of composite plates based on higher order shear deformation theory (HSDT) considering the Green–Lagrange type nonlinearity. A computer code based on finite element method (FEM) has also been developed in MATLAB to perform the numerical calculations. To validate the accuracy of the proposed numerical model, the results obtained from the present study are compared with those available in published literature. Effects of the side to thickness ratio, different boundary conditions and initial stresses on the natural frequency of composite plates have been studied. The free vibration analysis of a hollow stiffened hybrid laminated panel has also been carried out considering initial stresses and presented as case study.

Keywords: geometric nonlinearity, higher order shear deformation theory (HSDT), hybrid composite laminate, the initial stress

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Authors: S. Boria

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In the last years, the crashworthiness of an automotive body structure can be improved, since the beginning of the design stage, thanks to the development of specific optimization tools. It is well known how the finite element codes can help the designer to investigate the crashing performance of structures under dynamic impact. Therefore, by coupling nonlinear mathematical programming procedure and statistical techniques with FE simulations, it is possible to optimize the design with reduced number of analytical evaluations. In engineering applications, many optimization methods which are based on statistical techniques and utilize estimated models, called meta-models, are quickly spreading. A meta-model is an approximation of a detailed simulation model based on a dataset of input, identified by the design of experiments (DOE); the number of simulations needed to build it depends on the number of variables. Among the various types of meta-modeling techniques, Kriging method seems to be excellent in accuracy, robustness and efficiency compared to other ones when applied to crashworthiness optimization. Therefore the application of such meta-model was used in this work, in order to improve the structural optimization of a bumper for a racing car in composite material subjected to frontal impact. The specific energy absorption represents the objective function to maximize and the geometrical parameters subjected to some design constraints are the design variables. LS-DYNA codes were interfaced with LS-OPT tool in order to find the optimized solution, through the use of a domain reduction strategy. With the use of the Kriging meta-model the crashworthiness characteristic of the composite bumper was improved.

Keywords: composite material, crashworthiness, finite element analysis, optimization

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Authors: Saeed Sayyad Hagh Shomar

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Modeling users’ decisions on departure time choice is the main motivation for this research. In particular, it examines the impact of social-demographic features, household, job characteristics and trip qualities on individuals’ departure time choice. Departure time alternatives are presented as adjacent discrete time periods. The choice between these alternatives is done using a discrete choice model. Since a great deal of early morning trips and traffic congestion at that time of the day comprise work trips, the focus of this study is on the work trip over the entire day. Therefore, this study by using the users’ stated preference in questionnaire models users’ departure time choice affected by congestion pricing schemes in high traffic suburban entrance roads of Tehran. The results demonstrate efficient social-demographic impact on work trips’ departure time. These findings have substantial outcomes for the analysis of transportation planning. Particularly, the analysis shows that ignoring the effects of these variables could result in erroneous information and consequently decisions in the field of transportation planning and air quality would fail and cause financial resources loss.

Keywords: congestion pricing, departure time, modeling, travel timing, time of the day, transportation planning

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Authors: Moustafa Osman Mohammed

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The modeling of a spatial-economic database is crucial in recitation economic network structure to social development. Sustainability within the spatial-economic model gives attention to green businesses to comply with Earth’s Systems. The natural exchange patterns of ecosystems have consistent and periodic cycles to preserve energy and materials flow in systems ecology. When network topology influences formal and informal communication to function in systems ecology, ecosystems are postulated to valence the basic level of spatial sustainable outcome (i.e., project compatibility success). These referred instrumentalities impact various aspects of the second level of spatial sustainable outcomes (i.e., participant social security satisfaction). The sustainability outcomes are modeling composite structure based on a network analysis model to calculate the prosperity of panel databases for efficiency value, from 2005 to 2025. The database is modeling spatial structure to represent state-of-the-art value-orientation impact and corresponding complexity of sustainability issues (e.g., build a consistent database necessary to approach spatial structure; construct the spatial-economic-ecological model; develop a set of sustainability indicators associated with the model; allow quantification of social, economic and environmental impact; use the value-orientation as a set of important sustainability policy measures), and demonstrate spatial structure reliability. The structure of spatial-ecological model is established for management schemes from the perspective pollutants of multiple sources through the input–output criteria. These criteria evaluate the spillover effect to conduct Monte Carlo simulations and sensitivity analysis in a unique spatial structure. The balance within “equilibrium patterns,” such as collective biosphere features, has a composite index of many distributed feedback flows. The following have a dynamic structure related to physical and chemical properties for gradual prolong to incremental patterns. While these spatial structures argue from ecological modeling of resource savings, static loads are not decisive from an artistic/architectural perspective. The model attempts to unify analytic and analogical spatial structure for the development of urban environments in a relational database setting, using optimization software to integrate spatial structure where the process is based on the engineering topology of systems ecology.

Keywords: ecological modeling, spatial structure, orientation impact, composite index, industrial ecology

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Authors: Sina Saadati, Mohammadreza Razzazi

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In this article, we have tried to present an agent-based model of human muscle. A suitable model of muscle is necessary for the analysis of mankind's movements. It can be used by clinical researchers who study the influence of motion sicknesses, like Parkinson's disease. It is also useful in the development of a prosthesis that receives the electromyography signals and generates force as a reaction. Since we have focused on computational efficiency in this research, the model can compute the calculations very fast. As far as it concerns prostheses, the model can be known as a charge-efficient method. In this paper, we are about to illustrate an agent-based model. Then, we will use it to simulate the human gait cycle. This method can also be done reversely in the analysis of gait in motion sicknesses.

Keywords: agent-based modeling and simulation, human muscle, gait cycle, motion sickness

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Authors: Mueller Jann, Hoffmann Christian Hugo

Abstract:

Conventional quantitative risk management in banking is a risk factor of its own, because it rests on assumptions such as independence and availability of data which do not hold when rare events of extreme consequences are involved. There is a growing recognition of the need for alternative risk measures that do not make these assumptions. We propose a novel method for modeling the risk associated with investment products, in particular derivatives, by using a formal language for specifying financial contracts. Expressions in this language are interpreted in the category of values annotated with (a formal representation of) uncertainty. The choice of uncertainty formalism thus becomes a parameter of the model, so it can be adapted to the particular application and it is not constrained to classical probabilities. We demonstrate our approach using a simple logic-based uncertainty model and a case study in which we assess the risk of counter party default in a portfolio of collateralized loans.

Keywords: risk model, uncertainty monad, derivatives, contract algebra

Procedia PDF Downloads 566

Authors: Virendra J. Majarikar, Harikrishnan N. Unni

Abstract:

This paper sets to demonstrate a modeling of electrokinetic mixing employing electroosmotic stationary and time-dependent microchannel using alternate zeta patches on the lower surface of the micromixer in a lab on chip microfluidic device. Electroosmotic flow is amplified using different 2D and 3D model designs with alternate and geometric zeta potential values such as 25, 50, and 100 mV, respectively, to achieve high concentration mixing in the electrokinetically-driven microfluidic system. The enhancement of electrokinetic mixing is studied using Finite Element Modeling, and simulation workflow is accomplished with defined integral steps. It can be observed that the presence of alternate zeta patches can help inducing microvortex flows inside the channel, which in turn can improve mixing efficiency. Fluid flow and concentration fields are simulated by solving Navier-Stokes equation (implying Helmholtz-Smoluchowski slip velocity boundary condition) and Convection-Diffusion equation. The effect of the magnitude of zeta potential, the number of alternate zeta patches, etc. are analysed thoroughly. 2D simulation reveals that there is a cumulative increase in concentration mixing, whereas 3D simulation differs slightly with low zeta potential as that of the 2D model within the T-shaped micromixer for concentration 1 mol/m³ and 0 mol/m³, respectively. Moreover, 2D model results were compared with those of 3D to indicate the importance of the 3D model in a microfluidic design process.

Keywords: COMSOL Multiphysics®, electrokinetic, electroosmotic, microfluidics, zeta potential

Procedia PDF Downloads 231

Authors: Shun-Qi Zhang, Shu-Yang Zhang, Min Chen, , Jing Bai

Abstract:

Piezoelectric laminated smart structures can be subjected to the strong driving electric field, which may result in large displacements and rotations. In one hand, piezoelectric materials usually behave very significant material nonlinear effects under strong electric fields. On the other hand, thin-walled structures undergoing large displacements and rotations exist nonnegligible geometric nonlinearity. In order to give a precise prediction of piezo laminated smart structures under the large electric field, this paper develops a finite element (FE) model accounting for material nonlinearity (piezoelectric part) and geometric nonlinearity based on the first order shear deformation (FSOD) hypothesis. The proposed FE model is first validated by both experimental and numerical examples from the literature. Afterwards, it is applied to simulate for plate and shell structures with multiple piezoelectric patches under the strong applied electric field. From the simulation results, it shows that large discrepancies occur between linear and nonlinear predictions for piezoelectric laminated structures driving at the strong electric field. Therefore, both material and geometric nonlinearities should be taken into account for piezoelectric structures under strong electric.

Keywords: piezoelectric smart structures, finite element analysis, geometric nonlinearity, electroelastic material nonlinearities

Procedia PDF Downloads 309