Search results for: garment simulation

Authors: Yixin Zhu, Lishengsa Yue, Jian Sun, Lanyue Tang

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Modeling driving distraction in microscopic traffic simulation is crucial for enhancing simulation accuracy. Current driving distraction models are mainly derived from physical motion constraints under distracted states, in which distraction-related error terms are added to existing microscopic driver models. However, the model accuracy is not very satisfying, due to a lack of modeling the cognitive mechanism underlying the distraction. This study models driving distraction based on the Queueing Network Human Processor model (QN-MHP). This study utilizes the queuing structure of the model to perform task invocation and switching for distracted operation and control of the vehicle under driver distraction. Based on the assumption of the QN-MHP model about the cognitive sub-network, server F is a structural bottleneck. The latter information must wait for the previous information to leave server F before it can be processed in server F. Therefore, the waiting time for task switching needs to be calculated. Since the QN-MHP model has different information processing paths for auditory information and visual information, this study divides driving distraction into two types: auditory distraction and visual distraction. For visual distraction, both the visual distraction task and the driving task need to go through the visual perception sub-network, and the stimuli of the two are asynchronous, which is called stimulus on asynchrony (SOA), so when calculating the waiting time for switching tasks, it is necessary to consider it. In the case of auditory distraction, the auditory distraction task and the driving task do not need to compete for the server resources of the perceptual sub-network, and their stimuli can be synchronized without considering the time difference in receiving the stimuli. According to the Theory of Planned Behavior for drivers (TPB), this study uses risk entropy as the decision criterion for driver task switching. A logistic regression model is used with risk entropy as the independent variable to determine whether the driver performs a distraction task, to explain the relationship between perceived risk and distraction. Furthermore, to model a driver’s perception characteristics, a neurophysiological model of visual distraction tasks is incorporated into the QN-MHP, and executes the classical Intelligent Driver Model. The proposed driving distraction model integrates the psychological cognitive process of a driver with the physical motion characteristics, resulting in both high accuracy and interpretability. This paper uses 773 segments of distracted car-following in Shanghai Naturalistic Driving Study data (SH-NDS) to classify the patterns of distracted behavior on different road facilities and obtains three types of distraction patterns: numbness, delay, and aggressiveness. The model was calibrated and verified by simulation. The results indicate that the model can effectively simulate the distracted car-following behavior of different patterns on various roadway facilities, and its performance is better than the traditional IDM model with distraction-related error terms. The proposed model overcomes the limitations of physical-constraints-based models in replicating dangerous driving behaviors, and internal characteristics of an individual. Moreover, the model is demonstrated to effectively generate more dangerous distracted driving scenarios, which can be used to construct high-value automated driving test scenarios.

Keywords: computational cognitive model, driving distraction, microscopic traffic simulation, psychological-physical constraints

Procedia PDF Downloads 91

Authors: Mahesh Gupta

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The main goal in the design of a die for extrusion of a complex profile is to obtain a uniform velocity at the die exit. If the velocity at the exit of an extrusion die is not uniform, the shape of the extrudate profile can change significantly after the polymer exits the die. To rectify the extrudate distortion caused by non-uniform exit velocity, calibrators and sizers are often installed along the extrudate cooling system. Furthermore, the profile shape in calibrators and sizers is sometimes gradually changed to intentionally deform the extrudate to the required final product shape. This is exploited to simplify extrusion die design, because a relatively simple profile at the die exit can be modified to obtain a more complex profile by deforming it in calibrators or sizers. The gradual change in the shape of calibrator or sizer profiles can also be used to extrude slightly different profiles from the same die. In the present work, a combined flow, thermal and structural analysis is used to accurately predict distortion of extrudate profile after the polymer leaves a die. Simulations of the flow and extrudate deformation in two different bilayer coextrusion dies with gradually changing profile shape in successive calibrators and sizers will be presented. The effect of non-uniform exit velocity, cooling shrinkage and shape of sizer profiles on extrudate deformation is included in the simulation. The predicted extrudate shape and layer structure is found to match accurately with those in a coextruded product.

Keywords: coextrusion, extrusion die design, finite element method, polymers

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Authors: Aspasia Koutsokosta, Stefanos Katsavounis

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This paper reviews the model-based qualitative and quantitative Operations Management research in the context of Construction Supply Chain Management (CSCM). Construction industry has been traditionally blamed for low productivity, cost and time overruns, waste, high fragmentation and adversarial relationships. The construction industry has been slower than other industries to employ the Supply Chain Management (SCM) concept and develop models that support the decision-making and planning. However the last decade there is a distinct shift from a project-based to a supply-based approach of construction management. CSCM comes up as a new promising management tool of construction operations and improves the performance of construction projects in terms of cost, time and quality. Modeling the Construction Supply Chain (CSC) offers the means to reap the benefits of SCM, make informed decisions and gain competitive advantage. Different modeling approaches and methodologies have been applied in the multi-disciplinary and heterogeneous research field of CSCM. The literature review reveals that a considerable percentage of CSC modeling accommodates conceptual or process models which discuss general management frameworks and do not relate to acknowledged soft OR methods. We particularly focus on the model-based quantitative research and categorize the CSCM models depending on their scope, mathematical formulation, structure, objectives, solution approach, software used and decision level. Although over the last few years there has been clearly an increase of research papers on quantitative CSC models, we identify that the relevant literature is very fragmented with limited applications of simulation, mathematical programming and simulation-based optimization. Most applications are project-specific or study only parts of the supply system. Thus, some complex interdependencies within construction are neglected and the implementation of the integrated supply chain management is hindered. We conclude this paper by giving future research directions and emphasizing the need to develop robust mathematical optimization models for the CSC. We stress that CSC modeling needs a multi-dimensional, system-wide and long-term perspective. Finally, prior applications of SCM to other industries have to be taken into account in order to model CSCs, but not without the consequential reform of generic concepts to match the unique characteristics of the construction industry.

Keywords: construction supply chain management, modeling, operations research, optimization, simulation

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Authors: Rajendra Roul

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The main objective of the project is to bring attention towards the performance of an aerofoil when exposed to the fluid medium inside the wind tunnel. This project aims at involvement of civil as well as mechanical engineering thereby making itself as a multidisciplinary project. The airfoil of desired size is taken into consideration for the project to carry out effectively. An aerofoil is the shape of the wing or blade of propeller, rotor or turbine. Lot of experiment have been carried out through wind-tunnel keeping aerofoil as a reference object to make a future forecast regarding the design of turbine blade, car and aircraft. Lift and drag now become the major identification factor for any design industry which shows that wind tunnel testing along with software analysis (ANSYS) becomes the mandatory task for any researchers to forecast an aerodynamics design. This project is an initiative towards the mitigation of drag, better lift and analysis of wake surface profile by investigating the surface pressure distribution. The readings has been taken on airfoil model in Wind Tunnel Testing Machine (WTTM) at different air velocity 20m/sec, 25m/sec, 30m/sec and different angle of attack 00,50,100,150,200. Air velocity and pressures are measured in several ways in wind tunnel testing machine by use to measuring instruments like Anemometer and Multi tube manometer. Moreover to make the analysis more accurate Ansys fluent contribution become substantial and subsequently the CFD simulation results. Analysis on an Aerofoil have a wide spectrum of application other than aerodynamics including wind loads in the design of buildings and bridges for structural engineers.

Keywords: wind-tunnel, aerofoil, Ansys, multitube manometer

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Authors: Deepak Raj Bhat, Akihiko Wakai, Shigeru Ogita, Yorihiro Tanaka, Kazushige Hayashi, Shinro Abe

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In this study, the newly developed finite element methods are used for numerical analysis ofa landslide triggered by the fluctuations of ground-water levels in different cases I-IV. In case I, the ground-water level is fixed in such a way that the overall factor of safety (Fs) would be greater or equal to 1 (i.e., stable condition). Then, the ground-water level is gradually increased up to 1.0 m for, making the overall factor of safety (Fs) less than one (i.e., stable or moving condition). Then, the newly developed finite element model is applied for numerical simulation of the slope for each case. Based on the numerical analysis results of each Cases I-IV, the details of the deformation pattern and shear strain pattern are compared to each other. Moreover, the change in mobilized shear strength and local factor of safety along the slip surface of the landslide for each case are discussed to understand the triggering behaviors of a landslide due to the increased in ground water level. It is expected that this study will help to better understand the role of groundwater fluctuation for triggering of a landslide or slope failure disasters, and it would be also helpful for the judgment of the countermeasure works for the prevention and mitigation of landslide and slope failure disasters in near future.

Keywords: finite element method, ground water fluctuations, constitutive model, landslides, long-term disaster management system

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Authors: Fatima Ghassan Al-Abtah, Naser Al-Huniti, Elsadig Mahdi

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As the lightest constructional metal on earth, magnesium alloys offer excellent potential for weight reduction in the transportation industry, and it was observed that some magnesium alloys exhibit superior ductility and superplastic behavior at high temperatures. The main limitation of the superplastic forming (SPF) includes the low production rate since it needs a long forming time for each part. Through this study, an SPF process that starts with a mechanical pre-forming stage is developed to promote formability and reduce forming time. A two-dimensional finite element model is used to simulate the process. The forming process consists of two steps. At the pre-forming step (deep drawing), the sheet is drawn into the die to a preselected level, using a mechanical punch, and at the second step (SPF) a pressurized gas is applied at a controlled rate. It is shown that a significant reduction in forming time and improved final thickness uniformity can be achieved when the hybrid forming technique is used, where the process achieved a fully formed part at 400°C. Investigation for the impact of different forming process parameters achieved by comparing forming time and the distribution of final thickness that were obtained from the simulation analysis. Maximum thinning decreased from over 67% to less than 55% and forming time significantly decreased by more than 6 minutes, and the required gas pressure profile was predicted for optimum forming process parameters based on the 0.001/sec target constant strain rate within the sheet.

Keywords: magnesium, plasticity, superplastic forming, finite element analysis

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Authors: Vasujeet Singh, Pruthiviraj Nemalipuri, Vivek Vitankar, Harish Chandra Das

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For the correct prediction of thermal and hydraulic performance (bed voidage, suspension density, pressure drop, heat transfer, and combustion kinetics), one should incorporate the correct parameters in the computational fluid dynamics simulation of a fluidized bed gasifier. Scarcity of fossil fuels, and to fulfill the energy demand of the increasing population, researchers need to shift their attention to the alternative to fossil fuels. The current research work focuses on hydrodynamics behavior and gasification of sawdust inside a 2D industrial scale FBG using the Eulerian-Eulerian multifluid model. The present numerical model is validated with experimental data. Further, this model extended for the prediction of gasification characteristics of sawdust by incorporating eight heterogeneous moisture release, volatile cracking, tar cracking, tar oxidation, char combustion, CO₂ gasification, steam gasification, methanation reaction, and five homogeneous oxidation of CO, CH₄, H₂, forward and backward water gas shift (WGS) reactions. In the result section, composition of gasification products is analyzed, along with the hydrodynamics of sawdust and sand phase, heat transfer between the gas, sand and sawdust, reaction rates of different homogeneous and heterogeneous reactions is being analyzed along the height of the domain.

Keywords: devolatilization, Eulerian-Eulerian, fluidized bed gasifier, mathematical modelling, sawdust gasification

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Authors: Siddhartha Paul, Debabrata Das

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Closed-loop supply chain (CLSC) management focuses on integrating forward and reverse flow of material as well as information to maximize value creation over the entire life-cycle of a product. Bullwhip effect in supply chain management refers to the phenomenon where a small variation in customers’ demand results in larger variation of orders at the upstream levels of supply chain. Since the quality and quantity of products returned to the collection centers (as a part of reverse logistics process) are uncertain, bullwhip effect is inevitable in CLSC. Therefore, in the present study, first, through an extensive literature survey, we identify all the important factors related to forward as well as reverse supply chain which causes bullwhip effect in CLSC. Second, we develop a system dynamics model to study the interrelationship among the factors and their effect on the performance of overall CLSC. Finally, the results of the simulation study suggest that demand forecasting, lead times, information sharing, inventory and work in progress adjustment rate, supply shortages, batch ordering, price variations, erratic human behavior, parameter correcting, delivery time delays, return rate of used products, manufacturing and remanufacturing capacity constraints are the important factors which have a significant influence on system’s performance, specifically on bullwhip effect in a CLSC.

Keywords: bullwhip effect, closed-loop supply chain, system dynamics, variance ratio

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Authors: Mohammed Makki, Milad Showkatbakhsh, Aiman Tabony

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Computational applications of natural evolutionary processes as problem-solving tools have been well established since the mid-20th century. However, their application within architecture and design has only gained ground in recent years, with an increasing number of academics and professionals in the field electing to utilize evolutionary computation to address problems comprised from multiple conflicting objectives with no clear optimal solution. Recent advances in computer science and its consequent constructive influence on the architectural discourse has led to the emergence of multiple algorithmic processes capable of simulating the evolutionary process in nature within an efficient timescale. Many of the developed processes of generating a population of candidate solutions to a design problem through an evolutionary based stochastic search process are often driven through the application of both environmental and architectural parameters. These methods allow for conflicting objectives to be simultaneously, independently, and objectively optimized. This is an essential approach in design problems with a final product that must address the demand of a multitude of individuals with various requirements. However, one of the main challenges encountered through the application of an evolutionary process as a design tool is the ability for the simulation to maintain variation amongst design solutions in the population while simultaneously increasing in fitness. This is most commonly known as the ‘golden rule’ of balancing exploration and exploitation over time; the difficulty of achieving this balance in the simulation is due to the tendency of either variation or optimization being favored as the simulation progresses. In such cases, the generated population of candidate solutions has either optimized very early in the simulation, or has continued to maintain high levels of variation to which an optimal set could not be discerned; thus, providing the user with a solution set that has not evolved efficiently to the objectives outlined in the problem at hand. As such, the experiments presented in this paper seek to achieve the ‘golden rule’ by incorporating a mathematical fitness criterion for the development of an urban tissue comprised from the superblock as its primary architectural element. The mathematical value investigated in the experiments is the standard deviation factor. Traditionally, the standard deviation factor has been used as an analytical value rather than a generative one, conventionally used to measure the distribution of variation within a population by calculating the degree by which the majority of the population deviates from the mean. A higher standard deviation value delineates a higher number of the population is clustered around the mean and thus limited variation within the population, while a lower standard deviation value is due to greater variation within the population and a lack of convergence towards an optimal solution. The results presented will aim to clarify the extent to which the utilization of the standard deviation factor as a fitness criterion can be advantageous to generating fitter individuals in a more efficient timeframe when compared to conventional simulations that only incorporate architectural and environmental parameters.

Keywords: architecture, computation, evolution, standard deviation, urban

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Authors: Mohamed Eltarabily, Abdelazim Negm, Chihiro Yoshimura

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Recently, the pollution of groundwater from the use of nitrogenous fertilizer is at the increase. Also, due to the increase in area under cultivation and regular use of fertilizer in irrigated agriculture, groundwater pollution from agricultural activities is becoming a major concern. Because of the high mobility of Nitrate (NO3-) in soil which is governed by electrostatic processes, particularly anion exclusion, nitrate can be intercepted by shallow subsurface drainage pipe systems and then discharged offsite into streams, rivers, and lakes causing many hazards. In order to solve these environmental problems associated with nitrate, a better understanding of how NO3- moves through the soil profile under flow conditions is required. In the present paper, the results of a comparative study between experimental and numerical modeling of Nitrate transport through a saturated soil column are presented and analyzed. In order to achieve that, three water fluxes densities; 0.008, 0.007, and 0.006 m sec-1 and N concentration rates 10 mol cm-3 were used. The same concentrations were used in the simulation using HYDRUS-2D. The physical and chemical properties of the collected soil samples were calculated. Besides, the soil texture was determined which was silty sand. Results showed that HYDRUS-2D can successfully predict the relative behavior of N transport in the present experiment. Nitrate concentrations will reach deeper depth with the increase in the water flux. Overall, it was overestimated in the final concentration of (NO3-) in the soil by numerical simulation than by experimental column test. The column experiment is a useful tool for assessing the nitrate concentrations in the soil profile.

Keywords: groundwater, nitrate leaching, HYDRUS-2D, soil column

Procedia PDF Downloads 235

Authors: Tahmina Sultana, Yasser Hassan

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Vehicle technologies rapidly evolving due to their multifaceted advantages. Adapted different vehicle technologies like connectivity and automation on the same roads with conventional vehicles controlled by human drivers may increase speed disparity in mixed vehicle technologies. Identifying relationships between speed distribution measures of different vehicles and road geometry can be an indicator of speed disparity in mixed technologies. Previous studies proved that speed disparity measures and traffic accidents are inextricably related. Horizontal curves from three geographic areas were selected based on relevant criteria, and speed data were collected at the midpoint of the preceding tangent and starting, ending, and middle point of the curve. Multiple linear mixed effect models (LME) were developed using the instantaneous speed measures representing the speed of vehicles at different points of horizontal curves to recognize relationships between speed variance (standard deviation) and road geometry. A simulation-based framework (Monte Carlo) was introduced to check the speed disparity on horizontal curves in mixed vehicle technologies when consideration is given to the interactions among connected vehicles (CVs), autonomous vehicles (AVs), and non-connected vehicles (NCVs) on horizontal curves. The Monte Carlo method was used in the simulation to randomly sample values for the various parameters from their respective distributions. Theresults show that NCVs had higher speed variation than CVs and AVs. In addition, AVs and CVs contributed to reduce speed disparity in the mixed vehicle technologies in any penetration rates.

Keywords: autonomous vehicles, connected vehicles, non-connected vehicles, speed variance

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Authors: Yazan M. Alatrash, Han-ok Kang, Hyun-gi Yoon, Shen Zhang, Juhyeon Yoon

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Flow coastdown phenomena are very important to secure nuclear fuel integrity during loss of off-site power accidents. In this study, primary coolant flow coastdown phenomena are investigated for the Jordan Research and Training Reactor (JRTR) using a simulation software package, Modular Modelling System (MMS). Two MMS models are built. The first one is a simple model to investigate the characteristics of the primary coolant pump only. The second one is a model for a simulation of the Primary Coolant System (PCS) loop, in which all the detailed design data of the JRTR PCS system are modelled, including the geometrical arrangement data. The same design data for a PCS pump are used for both models. Coastdown curves obtained from the two models are compared to study the PCS loop coolant inertia effect on a flow coastdown. Results showed that the loop coolant inertia effect is found to be small in the JRTR PCS loop, i.e., about one second increases in a coastdown half time required to halve the coolant flow rate. The effects of different flywheel inertia on the flow coastdown are also investigated. It is demonstrated that the coastdown half time increases with the flywheel inertia linearly. The designed coastdown half time is proved to be well above the design requirement for the fuel integrity.

Keywords: flow coastdown, loop inertia, modelling, research reactor

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Authors: Laura Simmer, Maria Kalt, Oliver Schauer

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Freight transport is growing fast, but many vehicles are empty or just partially loaded. The vision and concepts of the Physical Internet (PI) proposes to eliminate these inefficiencies. Aiming for a radical sustainability improvement, the PI – inspired by the Digital Internet – is a hyperconnected global logistic system, enabling seamless asset sharing and flow consolidation. The implementation of a PI in its full expression will be a huge challenge: the industry needs innovation and implementation support including change management approaches, awareness creation and good practices diffusion, legislative actions to remove antitrust and international commerce barriers, standardization and public incentives policies. In order to take a step closer to this future the project ‘Atropine - Fast Track to the Physical Internet’ funded under the Strategic Economic and Research Program ‘Innovative Upper Austria 2020’ was set up. The two-year research project unites several research partners in this field, but also industrial partners and logistics service providers. With Atropine, the consortium wants to actively shape the mobility landscape in Upper Austria and make an innovative contribution to an energy-efficient, environmentally sound and sustainable development in the transport area. This paper should, on the one hand, clarify the questions what the project Atropine is about and, on the other hand, how a proof of concept will be reached. Awareness building plays an important role in the project as the PI requires a reorganization of the supply chain and the design of completely new forms of inter-company co-operation. New business models have to be developed and should be verified by simulation. After the simulation process one of these business models will be chosen and tested in real life with the partner companies. The developed results - simulation model and demonstrator - are used to determine how the concept of the PI can be applied in Upper Austria. Atropine shall pave the way for a full-scale development of the PI vision in the next few decades and provide the basis for pushing the industry toward a new level of co-operation with more shared resources and increased standardization.

Keywords: Atropine, inter-company co-operation, Physical Internet, shared resources, sustainable logistics

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Authors: Ahmed Boutejdar, Bishoy I. Halim, Soumia El Hani, Larbi Bellarbi, Amal Afyf

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In this paper, a planar monopole antenna for multi band applications is proposed. The antenna structure operates at three operating frequencies at 3.7, 6.2, and 13.5 GHz which cover different communication frequency ranges. The antenna consists of a quasi-modified rectangular radiating patch with a partial ground plane and two parasitic elements (open-loop-ring resonators) to serve as coupling-bridges. A stepped cut at lower corners of the radiating patch and the partial ground plane are used, to achieve the multiband features. The proposed antenna is manufactured on the FR4 substrate and is simulated and optimized using High Frequency Simulation System (HFSS). The antenna topology possesses an area of 30.5 x 30 x 1.6 mm³. The measured results demonstrate that the candidate antenna has impedance bandwidths for 10 dB return loss and operates from 3.80 – 3.90 GHz, 4.10 – 5.20 GHz, 11.2 – 11.5 GHz and from 12.5 – 14.0 GHz, which meet the requirements of the wireless local area network (WLAN), worldwide interoperability for microwave access (WiMAX), C- (Uplink) and Ku- (Uplink) band applications. Acceptable agreement is obtained between measurement and simulation results. Experimental results show that the antenna is successfully simulated and measured, and the tri-band antenna can be achieved by adjusting the lengths of the three elements and it gives good gains across all the operation bands.

Keywords: planar monopole antenna, FR4 substrate, HFSS, WLAN, WiMAX, C and Ku

Procedia PDF Downloads 190

Authors: Dessalegn Abera Waktole, Boru Jia, Zhengxing Zuo, Wei Wang, Nianling Kuang

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A flexible thermoelectric generator is one method for recycling waste heat. This research provides the optimum performance of a flexible thermoelectric generator with optimal geometric parameters and a detailed structural design. In this research, a numerical simulation and experiment were carried out to develop an efficient, flexible thermoelectric generator for energy harvesting from human skin. Heteromorphic electrodes and a polyimide substrate with a copper-printed circuit board were introduced into the structural design of a flexible thermoelectric generator. The heteromorphic electrode was used as a heat sink and component of a flexible thermoelectric generator to enhance the temperature difference within the thermoelectric legs. Both N-type and P-type thermoelectric legs were made of bismuth selenium telluride (Bi1.7Te3.7Se0.3) and bismuth antimony telluride (Bi0.4Sb1.6Te3). The output power of the flexible thermoelectric generator was analyzed under different heat source temperatures and heat dissipation conditions. The COMSOL Multiphysics 5.6 software was used to conduct the simulation, which was validated by experiment. It is recorded that the maximum power output of 232.064μW was obtained by considering different wind speed conditions, the ambient temperature of 20℃, and the heat source temperature of 36℃ under various load resistance conditions, which range from 0.24Ω to 0. 91Ω. According to this finding, heteromorphic electrodes have a significant impact on the performance of the device.

Keywords: flexible thermoelectric generator, optimization, performance, temperature gradient, waste heat recovery

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Authors: Amir Alani, Mojtaba Mahmoodian, Anna Romanova, Asaad Faramarzi

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Pipelines are extensively used engineering structures which convey fluid from one place to another. Most of the time, pipelines are placed underground and are encumbered by soil weight and traffic loads. Corrosion of pipe material is the most common form of pipeline deterioration and should be considered in both the strength and serviceability analysis of pipes. The study in this research focuses on concrete pipes in sewage systems (concrete sewers). This research firstly investigates how to involve the effect of corrosion as a time dependent process of deterioration in the structural and failure analysis of this type of pipe. Then three probabilistic time dependent reliability analysis methods including the first passage probability theory, the gamma distributed degradation model and the Monte Carlo simulation technique are discussed and developed. Sensitivity analysis indexes which can be used to identify the most important parameters that affect pipe failure are also discussed. The reliability analysis methods developed in this paper contribute as rational tools for decision makers with regard to the strengthening and rehabilitation of existing pipelines. The results can be used to obtain a cost-effective strategy for the management of the sewer system.

Keywords: reliability analysis, service life prediction, Monte Carlo simulation method, first passage probability theory, gamma distributed degradation model

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Authors: Byeongcheol Kang, Junyi Kim, Hyungsik Jung, Hyungjun Yang, Jaewoo An, Jonggeun Choe

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It is important to figure out reservoir properties for better production management. Due to the limited information, there are geological uncertainties on very heterogeneous or channel reservoir. One of the solutions is to generate multiple equi-probable realizations using geostatistical methods. However, some models have wrong properties, which need to be excluded for simulation efficiency and reliability. We propose a novel method of model selection scheme, based on distance-based clustering for reliable application of production optimization algorithm. Distance is defined as a degree of dissimilarity between the data. We calculate Hausdorff distance to classify the models based on their similarity. Hausdorff distance is useful for shape matching of the reservoir models. We use multi-dimensional scaling (MDS) to describe the models on two dimensional space and group them by K-means clustering. Rather than simulating all models, we choose one representative model from each cluster and find out the best model, which has the similar production rates with the true values. From the process, we can select good reservoir models near the best model with high confidence. We make 100 channel reservoir models using single normal equation simulation (SNESIM). Since oil and gas prefer to flow through the sand facies, it is critical to characterize pattern and connectivity of the channels in the reservoir. After calculating Hausdorff distances and projecting the models by MDS, we can see that the models assemble depending on their channel patterns. These channel distributions affect operation controls of each production well so that the model selection scheme improves management optimization process. We use one of useful global search algorithms, particle swarm optimization (PSO), for our production optimization. PSO is good to find global optimum of objective function, but it takes too much time due to its usage of many particles and iterations. In addition, if we use multiple reservoir models, the simulation time for PSO will be soared. By using the proposed method, we can select good and reliable models that already matches production data. Considering geological uncertainty of the reservoir, we can get well-optimized production controls for maximum net present value. The proposed method shows one of novel solutions to select good cases among the various probabilities. The model selection schemes can be applied to not only production optimization but also history matching or other ensemble-based methods for efficient simulations.

Keywords: distance-based clustering, geological uncertainty, particle swarm optimization (PSO), production optimization

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Authors: Chen Yong, Bi Wangyang, Zang Libin, Li Jinkai, Cheng Xiaowei, Liu Jinmin, Yu Miao

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New energy vehicle power transmission systems continue to develop in the direction of high torque, high speed, and high efficiency. The cooling and lubrication of the motor and the transmission system are integrated, and new requirements are placed on the lubricants for the transmission system. The effects of traditional lubricants and special lubricants for new energy vehicles on transmission efficiency were studied through experiments and simulation methods. A mathematical model of the transmission efficiency of the lubricating oil in the gearbox was established. The power loss of each part was analyzed according to the working conditions. The relationship between the speed and the characteristics of different lubricating oil products on the power loss of the stirring oil was discussed. The minimum oil film thickness was required for the life of the gearbox. The accuracy of the calculation results was verified by the transmission efficiency test conducted on the two-motor integrated test bench. The results show that the efficiency increases first and then decreases with the increase of the speed and decreases with the increase of the kinematic viscosity of the lubricant. The increase of the kinematic viscosity amplifies the transmission power loss caused by the high speed. New energy vehicle special lubricants have less attenuation of transmission efficiency in the range above mid-speed. The research results provide a theoretical basis and guidance for the evaluation and selection of transmission efficiency of gearbox lubricants for new energy vehicles.

Keywords: new energy vehicles, lubricants, transmission efficiency, kinematic viscosity, test and simulation

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Authors: Tarannom Parhizkar, Halle Bakhteeyar

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This paper presents a feasibility assessment of an expansion system applied to the natural gas transportation process in Iran. Power can be generated from the pressure energy of natural gas along its supply chain at various pressure reduction points by using turboexpanders. This technology is being applied in different countries around the world. The system consists of a turboexpander reducing the natural gas pressure and providing mechanical energy to drive electric generator. Moreover, gas pre-heating, required to prevent hydrate formation, is performed upstream of expansion stage using burner. The city gate station (CGS) has a nominal flow rate in range of 45000 to 270000 cubic meters per hour and a pressure reduction from maximum 62 bar at the upstream to 6 bar. Due to variable feed pressure and temperature in this station sensitivity analysis of generated electricity and required heat is performed. Results show that plant gain is more sensible to pressure variation than temperature changes. Furthermore, using turboexpander to reduce the pressure result in an electrical generation of 2757 to 17574 kW with the value of approximately 4 million US$ per year. Moreover, the required heat range to prevent a hydrate formation is almost 2189 to 14157 kW. To provide this heat, a burner is used with a maximum annual cost of 268,640 $ burner fuel. Therefore, the actual annual benefit of proposed plant modification is approximately over 6,5 million US$.

Keywords: feasibility study, simulation, turboexpander, feed characteristic

Procedia PDF Downloads 501

Authors: Mahdieh Zamzamzadeh, Ahmad Abdullah Saifizul, Rahizar Ramli

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The road accidents involving heavy vehicles have been showing worrying trends and, year after year, have increased the concern and awareness levels on safety of roads and transportations especially in developing countries like Malaysia. Statistics of road crashes continue to show that there are many contributing factors on the capability of a heavy vehicle to stop on safe distance and ultimately prevent traffic crashes. However, changes in the road condition due to weather variations and the vehicle dynamic specifications such as loading conditions and speed are the main risk factors because they will affect a heavy vehicle’s braking performance due to losing control and not being able to stop the vehicle, and in many cases will cause wheel lock up and accordingly skidding. Predicting heavy vehicle skidding distance is crucial for accident reconstruction and roadside safety engineers. Despite this, formal tools to study heavy vehicle skidding distance before stopping completely are totally limited, and most researchers have only considered braking distance in their studies. As a possible new tool, this work presents the iterative use of vehicle dynamic simulations to study heavy vehicle-roadway interaction in order to predict wheel lock up effects on skidding distance and safety. This research addresses the influence of the vehicle and road conditions on skidding distance after wheel lock up and presents a precise analysis of skidding phenomenon. The vehicle speed, vehicle loading condition and road friction parameters were all varied in a simulation-based analysis. In order to simulate the wheel lock up situation, a heavy vehicle model was constructed and simulated using multibody vehicle dynamics simulation software, and careful analysis was made on the conditions which caused the skidding distance to increase or decrease through a method using to predict skidding distance as part of braking distance. By applying many simulations, the results were quite revealing relation between the heavy vehicles loading condition, various sets of speed and road coefficient of friction and their interaction effect on the skidding distance. A number of results are presented which illustrate how the heavy vehicle overloading can seriously affect the skidding distance. Moreover, the results of simulation give the skid mark length, which is a necessary input data during accident reconstruction involving emergency braking.

Keywords: accident reconstruction, Braking, heavy vehicle, skidding distance, skid mark, wheel lock up

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Authors: P. Bhavya, P. R. Jayasree

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This paper presents a low cost transformer isolated boost half bridge micro-inverter for single phase grid connected PV system. Since the output voltage of a single PV panel is as low as 20~50V, a high voltage gain inverter is required for the PV panel to connect to the single-phase grid. The micro-inverter has two stages, an isolated dc-dc converter stage and an inverter stage with a dc link. To achieve MPPT and to step up the PV voltage to the dc link voltage, a transformer isolated boost half bridge dc-dc converter is used. To output the synchronised sinusoidal current with unity power factor to the grid, a pulse width modulated full bridge inverter with LCL filter is used. Variable step size Maximum Power Point Tracking (MPPT) method is adopted such that fast tracking and high MPPT efficiency are both obtained. AC voltage as per grid requirement is obtained at the output of the inverter. High power factor (>0.99) is obtained at both heavy and light loads. This paper gives the results of computer simulation program of a grid connected solar PV system using MATLAB/Simulink and SIM Power System tool.

Keywords: boost-half-bridge, micro-inverter, maximum power point tracking, grid connection, MATLAB/Simulink

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Authors: Vinayak Bassi, Rajpreet Singh

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Over the years, with the emergence of sophisticated computers and algorithms, finance has been quantified using computational prowess. Asset valuation has been one of the key components of quantitative finance. In fact, it has become one of the embryonic steps in determining risk related to a portfolio, the main goal of quantitative finance. This study comprises a drawing comparison between valuation output generated by two stochastic dynamic models, namely Black-Scholes and Dupire’s bi-dimensionality model. Both of these models are formulated for computing the valuation function for a portfolio of European options using Monte Carlo simulation methods. Although Monte Carlo algorithms have a slower convergence rate than calculus-based simulation techniques (like FDM), they work quite effectively over high-dimensional dynamic models. A fidelity gap is analyzed between the static (historical) and stochastic inputs for a sample portfolio of underlying assets. In order to enhance the performance efficiency of the model, the study emphasized the use of variable reduction methods and customizing random number generators to implement parallelization. An attempt has been made to further implement the Dupire’s model on a GPU to achieve higher computational performance. Furthermore, ideas have been discussed around the performance enhancement and bottleneck identification related to the implementation of options-pricing models on GPUs.

Keywords: monte carlo, stochastic models, computational finance, parallel programming, scientific computing

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Authors: Azin Zargham, Gholamreza Rouhi, Allahyar Geramy

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One of the most prevalent types of alveolar bone loss is horizontal bone loss (HBL) in which the bone height around teeth is reduced homogenously. In the presence of HBL the magnitudes of forces during orthodontic treatment should be altered according to the degree of HBL, in a way that without further bone loss, desired tooth movement can be obtained. In order to investigate the appropriate orthodontic force system in the presence of HBL, a three-dimensional numerical model capable of the simulation of orthodontic tooth movement was developed. The main goal of this research was to evaluate the effect of different degrees of HBL on a long-term orthodontic tooth movement. Moreover, the effect of different force magnitudes on orthodontic tooth movement in the presence of HBL was studied. Five three-dimensional finite element models of a maxillary lateral incisor with 0 mm, 1.5 mm, 3 mm, 4.5 mm and 6 mm of HBL were constructed. The long-term orthodontic tooth tipping movements were attained during a 4-weeks period in an iterative process through the external remodeling of the alveolar bone based on strains in periodontal ligament as the bone remodeling mechanical stimulus. To obtain long-term orthodontic tooth movement in each iteration, first the strains in periodontal ligament under a 1-N tipping force were calculated using finite element analysis. Then, bone remodeling and the subsequent tooth movement were computed in a post-processing software using a custom written program. Incisal edge, cervical, and apical area displacement in the models with different alveolar bone heights (0, 1.5, 3, 4.5, 6 mm bone loss) in response to a 1-N tipping force were calculated. Maximum tooth displacement was found to be 2.65 mm at the top of the crown of the model with a 6 mm bone loss. Minimum tooth displacement was 0.45 mm at the cervical level of the model with a normal bone support. Tooth tipping degrees of models in response to different tipping force magnitudes were also calculated for models with different degrees of HBL. Degrees of tipping tooth movement increased as force level was increased. This increase was more prominent in the models with smaller degrees of HBL. By using finite element method and bone remodeling theories, this study indicated that in the presence of HBL, under the same load, long-term orthodontic tooth movement will increase. The simulation also revealed that even though tooth movement increases with increasing the force, this increase was only prominent in the models with smaller degrees of HBL, and tooth models with greater degrees of HBL will be less affected by the magnitude of an orthodontic force. Based on our results, the applied force magnitude must be reduced in proportion of degree of HBL.

Keywords: bone remodeling, finite element method, horizontal bone loss, orthodontic tooth movement.

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Authors: Trevor E. Davis, Isaac Cassar, Yi-Kai Lo, Wentai Liu

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This study models the use of transcutaneous electrical nerve stimulation on skin with a disk electrode in order to simulate tissue damage. The current density distribution above a disk electrode is known to be a dynamic and non-uniform quantity that is intensified at the edges of the disk. The non-uniformity is subject to change through using various electrode geometries or stimulation methods. One of these methods known as edge-retarded stimulation has shown to reduce this edge enhancement. Though progress has been made in modeling the behavior of a disk electrode, little has been done to test the validity of these models in simulating the actual heat transfer from the electrode. This simulation uses finite element software to couple the injection of current from a disk electrode to heat transfer described by the Pennesbioheat transfer equation. An example application of this model is studying an experimental form of stimulation, known as edge-retarded stimulation. The edge-retarded stimulation method will reduce the current density at the edges of the electrode. It is hypothesized that reducing the current density edge enhancement effect will, in turn, reduce temperature change and tissue damage at the edges of these electrodes. This study tests this hypothesis as a demonstration of the capabilities of this model. The edge-retarded stimulation proved to be safer after this simulation. It is shown that temperature change and the fraction of tissue necrosis is much greater in the square wave stimulation. These results bring implications for changes of procedures in transcutaneous electrical nerve stimulation and transcutaneous spinal cord stimulation as well.

Keywords: bioheat transfer, electrode, neuroprosthetics, TENS, transcutaneous stimulation

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Authors: Khadidja Rahmani, Nahla Bouaziz

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The climate change and the economic crisis, which are currently running, are the origin of the emergence of many issues and problems, which are related to the domain of energy and environment in à direct or indirect manner. Since the urban space is the core element and the key to solve the current problem, particular attention is given to it in this study. For this reason, we rented to the later a very particular attention; this is for the opportunities that it provides and that can be invested to attenuate a little this situation, which is disastrous and worried, especially in the face of the requirements of sustainable development. Indeed, the purpose of this work is to develop a method, which will allow us to guide designers towards projects with a certain degree of thermo-aeraulic comfort while requiring a minimum energy consumption. In this context, the architects, the urban planners and the engineers (energeticians) have to collaborate jointly to establish a method based on indicators for the improvement of the urban environmental quality (aeraulic-thermo comfort), correlated with a reduction in the energy demand of the entities that make up this environment, in areas with a sub-humid climate. In order to test the feasibility and to validate the method developed in this work, we carried out a series of simulations using computer-based simulation. This research allows us to evaluate the impact of the use of the indicators in the design of the urban sets, on the economic and ecological plan. Using this method, we prove that an urban design, which carefully considered energetically, can contribute significantly to the preservation of the environment and the reduction of the consumption of energy.

Keywords: comfort, energy consumption, energy mastery, morpho-energetic indicators, simulation, sub-humid climate, urban sets

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Authors: Babak Safaei, Ahmad Ghanbari, Arash Rahmani

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In the present study, the free vibration characteristics of double-walled carbon nanotubes (DWCNTs) are investigated. The small-scale effects are taken into account using the Eringen’s nonlocal elasticity theory. The nonlocal elasticity equations are implemented into the different classical beam theories namely as Euler-Bernoulli beam theory (EBT), Timoshenko beam theory (TBT), Reddy beam theory (RBT), and Levinson beam theory (LBT) to analyze the free vibrations of DWCNTs in which each wall of the nanotubes is considered as individual beam with van der Waals interaction forces. Generalized differential quadrature (GDQ) method is utilized to discretize the governing differential equations of each nonlocal beam model along with four commonly used boundary conditions. Then molecular dynamics (MD) simulation is performed for a series of armchair and zigzag DWCNTs with different aspect ratios and boundary conditions, the results of which are matched with those of nonlocal beam models to extract the appropriate values of the nonlocal parameter corresponding to each type of chirality, nonlocal beam model and boundary condition. It is found that the present nonlocal beam models with their proposed correct values of nonlocal parameter have good capability to predict the vibrational behavior of DWCNTs, especially for higher aspect ratios.

Keywords: double-walled carbon nanotubes, nonlocal continuum elasticity, free vibrations, molecular dynamics simulation, generalized differential quadrature method

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Authors: Gul Nihal Gugul, Merih Aydinalp-Koksal

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In this study, hourly energy consumption model of a single detached house in Ankara, Turkey is developed using ESP-r building energy simulation software. Natural gas is used for space heating, cooking, and domestic water heating in this two story 4500 square feet four-bedroom home. Hourly electricity consumption of the home is monitored by an automated meter reading system, and daily natural gas consumption is recorded by the owners during 2013. Climate data of the region and building envelope data are used to develop the model. The heating energy consumption of the house that is estimated by the ESP-r model is then compared with the actual heating demand to determine the performance of the model. Scenarios are applied to the model to determine the amount of reduction in the total energy consumption of the house. The scenarios are using photovoltaic panels to generate electricity, ground source heat pumps for space heating and solar panels for domestic hot water generation. Alternative scenarios such as improving wall and roof insulations and window glazing are also applied. These scenarios are evaluated based on annual energy, associated CO2 emissions, and fuel expenditure savings. The pay-back periods for each scenario are also calculated to determine best alternative energy source or technology option for this home to reduce annual energy use and CO2 emission.

Keywords: ESP-r, building energy simulation, residential energy saving, CO2 reduction

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Authors: Rabaya Basori, Arup K. Raychaudhuri

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In recent years, a variety of semiconductor nanowires (NWs) has been synthesized and used as basic building blocks for the development of electronic and optoelectronic nanodevices. Dielectrophoresis (DEP) has been widely investigated as a scalable technique to trap and manipulate polarizable objects. This includes biological cells, nanoparticles, DNA molecules, organic or inorganic NWs and proteins using electric field gradients. In this article, we have used DEP force to localize nanowire growth by physical vapor deposition (PVD) method as well as control of NW diameter on field assisted growth of the NWs of CuTCNQ (Cu-tetracyanoquinodimethane); a metal-organic charge transfer complex material which is well known of resistive switching. We report a versatile analysis platform, based on a set of nanogap electrodes, for the controlled growth of nanowire. Non-uniform electric field and dielectrophoretic force is created in between two metal electrodes, patterned by electron beam lithography process. Suspended CuTCNQ nanowires have been grown laterally between two electrodes in the vicinity of electric field and dielectric force by applying external bias. Growth and diameter dependence of the nanowires on external bias has been investigated in the framework of these two forces by COMSOL Multiphysics simulation. This report will help successful in-situ nanodevice fabrication with constrained number of NW and diameter without any post treatment.

Keywords: nanowire, dielectrophoretic force, confined growth, controlled diameter, comsol multiphysics simulation

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Authors: Philippe Larvet

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This paper presents the concept of an object-based programming language where tests (if... then... else) and control structures (while, repeat, for...) disappear and are replaced by conditions on data. According to the object paradigm, by using this concept, data are still embedded inside objects, as variable-value couples, but object methods are expressed into the form of logical propositions (‘conditions on data’ or COD).For instance : variable1 = value1 AND variable2 > value2 => variable3 = value3. Implementing this approach, a central inference engine turns and examines objects one after another, collecting all CODs of each object. CODs are considered as rules in a rule-based system: the left part of each proposition (left side of the ‘=>‘ sign) is the premise and the right part is the conclusion. So, premises are evaluated and conclusions are fired. Conclusions modify the variable-value couples of the object and the engine goes to examine the next object. The paper develops the principles of writing CODs instead of complex algorithms. Through samples, the paper also presents several hints for implementing a simple mechanism able to process this ‘COD language’. The proposed approach can be used within the context of simulation, process control, industrial systems validation, etc. By writing simple and rigorous conditions on data, instead of using classical and long-to-learn languages, engineers and specialists can easily simulate and validate the functioning of complex systems.

Keywords: conditions on data, logical proposition, programming without code, object-oriented programming, system simulation, system validation

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Authors: Weirong Wang, Shenghong Huang, Xisheng Luo, Zhenyu Li

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Material mixing process and related dynamic issues at extreme compressing conditions have gained more and more concerns in last ten years because of the engineering appealings in inertial confinement fusion (ICF) and hypervelocity aircraft developments. However, there lacks models and methods that can handle fully coupled turbulent material mixing and complex fluid evolution under conditions of high energy density regime up to now. In aspects of macro hydrodynamics, three numerical methods such as direct numerical simulation (DNS), large eddy simulation (LES) and Reynolds-averaged Navier–Stokes equations (RANS) has obtained relative acceptable consensus under the conditions of low energy density regime. However, under the conditions of high energy density regime, they can not be applied directly due to occurrence of dissociation, ionization, dramatic change of equation of state, thermodynamic properties etc., which may make the governing equations invalid in some coupled situations. However, in view of micro/meso scale regime, the methods based on Molecular Dynamics (MD) as well as Monte Carlo (MC) model are proved to be promising and effective ways to investigate such issues. In this study, both classical MD and first-principle based electron force field MD (eFF-MD) methods are applied to investigate Richtmyer-Meshkov Instability of metal Lithium and gas Hydrogen (Li-H2) interface mixing at different shock loading speed ranging from 3 km/s to 30 km/s. It is found that: 1) Classical MD method based on predefined potential functions has some limits in application to extreme conditions, since it cannot simulate the ionization process and its potential functions are not suitable to all conditions, while the eFF-MD method can correctly simulate the ionization process due to its ‘ab initio’ feature; 2) Due to computational cost, the eFF-MD results are also influenced by simulation domain dimensions, boundary conditions and relaxation time choices, etc., in computations. Series of tests have been conducted to determine the optimized parameters. 3) Ionization induced by strong shock compression has important effects on Li-H2 interface evolutions of RMI, indicating a new micromechanism of RMI under conditions of high energy density regime.

Keywords: first-principle, ionization, molecular dynamics, material mixture, Richtmyer-Meshkov instability

Procedia PDF Downloads 225