Search results for: rejection simulation method

Authors: Jun Su Park, Byung Kwan Oh, Jin Woo Hwang, Yousok Kim, Hyo Seon Park

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For the structural safety, the maximum stress calculated from the stress distribution of a structure is widely used. The stress distribution can be estimated by deformed shape of the structure obtained from measurement. Although the estimation of stress is strongly affected by the location and number of sensing points, most studies have conducted the stress estimation without reasonable basis on sensing plan such as the location and number of sensors. In this paper, an optimal sensing technique for estimating the stress distribution is proposed. This technique proposes the optimal location and number of sensing points for a 2-D frame structure while minimizing the error of stress distribution between analytical model and estimation by cubic smoothing splines using genetic algorithm. To verify the proposed method, the optimal sensor measurement technique is applied to simulation tests on 2-D steel frame structure. The simulation tests are performed under various loading scenarios. Through those tests, the optimal sensing plan for the structure is suggested and verified.

Keywords: genetic algorithm, optimal sensing, optimizing sensor placements, steel frame structure

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Authors: Daniel Fundi Murithi

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Data from economic, social, clinical, and industrial studies are in some way incomplete or incorrect due to censoring. Such data may have adverse effects if used in the estimation problem. We propose the use of Maximum Likelihood Estimation (MLE) under a progressive type-II censoring scheme to remedy this problem. In particular, maximum likelihood estimates (MLEs) for the location (µ) and scale (λ) parameters of two Parameter Rayleigh distribution are realized under a progressive type-II censoring scheme using the Expectation-Maximization (EM) and the Newton-Raphson (NR) algorithms. These algorithms are used comparatively because they iteratively produce satisfactory results in the estimation problem. The progressively type-II censoring scheme is used because it allows the removal of test units before the termination of the experiment. Approximate asymptotic variances and confidence intervals for the location and scale parameters are derived/constructed. The efficiency of EM and the NR algorithms is compared given root mean squared error (RMSE), bias, and the coverage rate. The simulation study showed that in most sets of simulation cases, the estimates obtained using the Expectation-maximization algorithm had small biases, small variances, narrower/small confidence intervals width, and small root of mean squared error compared to those generated via the Newton-Raphson (NR) algorithm. Further, the analysis of a real-life data set (data from simple experimental trials) showed that the Expectation-Maximization (EM) algorithm performs better compared to Newton-Raphson (NR) algorithm in all simulation cases under the progressive type-II censoring scheme.

Keywords: expectation-maximization algorithm, maximum likelihood estimation, Newton-Raphson method, two-parameter Rayleigh distribution, progressive type-II censoring

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Authors: Chia-Hau Liu, Tai-Yue Wang

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Traditional multivariate control charts assume that measurement from manufacturing processes follows a multivariate normal distribution. However, this assumption may not hold or may be difficult to verify because not all the measurement from manufacturing processes are normal distributed in practice. This study develops a new multivariate control chart for monitoring the processes with non-normal data. We propose a mechanism based on integrating the one-class classification method and the adaptive technique. The adaptive technique is used to improve the sensitivity to small shift on one-class classification in statistical process control. In addition, this design provides an easy way to allocate the value of type I error so it is easier to be implemented. Finally, the simulation study and the real data from industry are used to demonstrate the effectiveness of the propose control charts.

Keywords: multivariate control chart, statistical process control, one-class classification method, non-normal data

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Authors: Zahra Ahmadi, Fazlollah Adibnia

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Scheduling of tasks and the optimal allocation of resources in the cloud are based on the dynamic nature of tasks and the heterogeneity of resources. Applications that are based on the scientific workflow are among the most widely used applications in this field, which are characterized by high processing power and storage capacity. In order to increase their efficiency, it is necessary to plan the tasks properly and select the best virtual machine in the cloud. The goals of the system are effective factors in scheduling tasks and resource selection, which depend on various criteria such as time, cost, current workload and processing power. Multi-criteria decision-making methods are a good choice in this field. In this research, a new method of work planning and resource allocation in a heterogeneous environment based on the modified AHP algorithm is proposed. In this method, the scheduling of input tasks is based on two criteria of execution time and size. Resource allocation is also a combination of the AHP algorithm and the first-input method of the first client. Resource prioritization is done with the criteria of main memory size, processor speed and bandwidth. What is considered in this system to modify the AHP algorithm Linear Max-Min and Linear Max normalization methods are the best choice for the mentioned algorithm, which have a great impact on the ranking. The simulation results show a decrease in the average response time, return time and execution time of input tasks in the proposed method compared to similar methods (basic methods).

Keywords: hierarchical analytical process, work prioritization, normalization, heterogeneous resource allocation, scientific workflow

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Authors: Utsav Swarnkar, Rabi Pathak, Rina Maiti

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This study aims to investigate the thermoregulatory role of sweating by comprehensively analyzing the evaporation process and its thermal cooling impact on local skin temperature at various time intervals. Traditional experimental methods struggle to fully capture these intricate phenomena. Therefore, numerical simulations play a crucial role in assessing sweat production rates and associated thermal cooling. This research utilizes transient computational fluid dynamics (CFD) to enhance our understanding of the evaporative cooling process on human skin. We conducted a simulation employing the k-w SST turbulence model. This simulation includes a scenario where sweat evaporation occurs over the skin surface, and at particular time intervals, temperatures at different locations have been observed and its effect explained. During this study, sweat evaporation was monitored on the skin surface following the commencement of the simulation. Subsequent to the simulation, various observations were made regarding temperature fluctuations at specific points over time intervals. It was noted that points situated closer to the periphery of the droplets exhibited higher levels of heat transfer and lower temperatures, whereas points within the droplets displayed contrasting trends.

Keywords: CFD, sweat, evaporation, multiphase flow, local heat loss

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Authors: Nam Kyu Kim, Hee Jun Cha, Jae Jin Seo, Dong Jun Won

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Output power of a photovoltaic (PV) generator depends on incident solar irradiance. If the clouds pass or the climate condition is bad, the PV output fluctuates frequently. When PV generator is connected to the grid, these fluctuations adversely affect power quality. Thus, ramp rate control with battery energy storage system (BESS) is needed to reduce PV output fluctuations. At the same time, for effective BESS operation and sizing the optimal BESS capacity, managing state of charge (SOC) is the most important part. In addition, managing SOC helps to avoid violating the SOC operating range of BESS when performing renewable integration (RI) continuously. As PV and BESS increase, the SOC management of BESS will become more important in the future. This paper presents the SOC management algorithm which helps to operate effectively BESS, and has focused on method to manage SOC while reducing PV output fluctuations. A simulation model is developed in PSCAD/EMTDC software. The simulation results show that the SOC is maintained within the operating range by adjusting the output distribution according to the SOC of the BESS.

Keywords: battery energy storage system, ramp rate control, renewable integration, SOC management

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Authors: Bale Baidi Blaise, Gilles Marckmann, Liman Kaoye, Talaka Dya, Moustapha Bachirou, Gambo Betchewe, Tibi Beda

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This work highlights the capabilities of particles swarm optimization (PSO) method to identify parameters of hyperelastic models. The study compares this method with Genetic Algorithm (GA) method, Least Squares (LS) method, Pattern Search Algorithm (PSA) method, Beda-Chevalier (BC) method and the Levenberg-Marquardt (LM) method. Four classic hyperelastic models are used to test the different methods through parameters identification. Then, the study compares the ability of these models to reproduce experimental Treloar data in simple tension, biaxial tension and pure shear.

Keywords: particle swarm optimization, identification, hyperelastic, model

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Authors: Christina Klippel, Lucia Pezzi, Silvio Neto, Rafael Bertani, Priscila Mendes, Flavio Machado, Aline Szeliga, Maria Cosendey, Adilson Mariz, Raquel Santos, Lys Bendett, Pedro Velasco, Thalita Rolleigh, Bruna Bellote, Daria Coelho, Bruna Martins, Julia Almeida, Juliana Cerqueira

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This project presents a framework for teaching intracranial pressure monitoring (ICP) concepts using a low-cost experimental model in a neurointensive care education program. Data concerning ICP monitoring contribute to the patient's clinical assessment and may dictate the course of action of a health team (nursing, medical staff) and influence decisions to determine the appropriate intervention. This study aims to present a safe method for teaching ICP monitoring to medical students in a Simulation Center. Methodology: Medical school teachers, along with students from the 4th year, built an experimental model for teaching ICP measurement. The model consists of a mannequin's head with a plastic bag inside simulating the cerebral ventricle and an inserted ventricular catheter connected to the ICP monitoring system. The bag simulating the ventricle can also be changed for others containing bloody or infected simulated cerebrospinal fluid. On the mannequin's ear, there is a blue point indicating the right place to set the "zero point" for accurate pressure reading. The educational program includes four steps: 1st - Students receive a script on ICP measurement for reading before training; 2nd - Students watch a video about the subject created in the Simulation Center demonstrating each step of the ICP monitoring and the proper care, such as: correct positioning of the patient, anatomical structures to establish the zero point for ICP measurement and a secure range of ICP; 3rd - Students train the procedure in the model. Teachers help students during training; 4th - Student assessment based on a checklist form. Feedback and correction of wrong actions. Results: Students expressed interest in learning ICP monitoring. Tests concerning the hit rate are still being performed. ICP's final results and video will be shown at the event. Conclusion: The study of intracranial pressure measurement based on an experimental model consists of an effective and controlled method of learning and research, more appropriate for teaching neurointensive care practices. Assessment based on a checklist form helps teachers keep track of student learning progress. This project offers medical students a safe method to develop intensive neurological monitoring skills for clinical assessment of patients with neurological disorders.

Keywords: neurology, intracranial pressure, medical education, simulation

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Authors: Ruxandra Barbulescu, Daniel Ioan, Gabriela Ciuprina

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The saltatory conduction is the way the action potential is transmitted along a myelinated axon. The potential diffuses along the myelinated compartments and it is regenerated in the Ranvier nodes due to the ion channels allowing the flow across the membrane. For an efficient simulation of populations of neurons, it is important to use reduced order models both for myelinated compartments and for Ranvier nodes and to have control over their accuracy and inner parameters. The paper presents a reduced order model of this neural system which allows an efficient simulation method for the saltatory conduction in myelinated axons. This model is obtained by concatenating reduced order linear models of 1D myelinated compartments and nonlinear 0D models of Ranvier nodes. The models for the myelinated compartments are selected from a series of spatially distributed models developed and hierarchized according to their modeling errors. The extracted model described by a nonlinear PDE of hyperbolic type is able to reproduce the saltatory conduction with acceptable accuracy and takes into account the finite propagation speed of potential. Finally, this model is again reduced in order to make it suitable for the inclusion in large-scale neural circuits.

Keywords: action potential, myelinated segments, nonlinear models, Ranvier nodes, reduced order models, saltatory conduction

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Authors: S. Nandal, R. Bhargava

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The paper contains a numerical study of the unsteady magneto-hydrodynamic natural convection flow of nanofluids within a symmetrical wavy walled trapezoidal enclosure. The length and height of enclosure are both considered equal to L. Two-phase nanofluid model is employed. The governing equations of nanofluid flow along with boundary conditions are non-dimensionalized and are solved using one of Meshfree technique (EFGM method). Meshfree numerical technique does not require a predefined mesh for discretization purpose. The bottom wavy wall of the enclosure is defined using a cosine function. Element free Galerkin method (EFGM) does not require the domain. The effects of various parameters namely time t, amplitude of bottom wavy wall a, Brownian motion parameter Nb and thermophoresis parameter Nt is examined on rate of heat and mass transfer to get a visualization of cooling and heating effects. Such problems have important applications in heat exchangers or solar collectors, as wavy walled enclosures enhance heat transfer in comparison to flat walled enclosures.

Keywords: heat transfer, meshfree methods, nanofluid, trapezoidal enclosure

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Authors: Judson P. LaGrone

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Simulation-based education in curricula was once a luxurious component of nursing programs but now serves as a vital element of an individual’s learning experience. A debriefing occurs after the simulation scenario or clinical experience is completed to allow the instructor(s) or trained professional(s) to act as a debriefer to guide a reflection with a purpose of acknowledging, assessing, and synthesizing the thought process, decision-making process, and actions/behaviors performed during the scenario or clinical experience. Debriefing is a vital component of the simulation process and educational experience to allow the learner(s) to progressively build upon past experiences and current scenarios within a safe and welcoming environment with a guided dialog to enhance future practice. The aim of this integrative review was to assess current practices of debriefing models in simulation-based education for health care professionals and students. The following databases were utilized for the search: CINAHL Plus, Cochrane Database of Systemic Reviews, EBSCO (ERIC), PsycINFO (Ovid), and Google Scholar. The advanced search option was useful to narrow down the search of articles (full text, Boolean operators, English language, peer-reviewed, published in the past five years). Key terms included debrief, debriefing, debriefing model, debriefing intervention, psychological debriefing, simulation, simulation-based education, simulation pedagogy, health care professional, nursing student, and learning process. Included studies focus on debriefing after clinical scenarios of nursing students, medical students, and interprofessional teams conducted between 2015 and 2020. Common themes were identified after the analysis of articles matching the search criteria. Several debriefing models are addressed in the literature with similarities of effectiveness for participants in clinical simulation-based pedagogy. Themes identified included (a) importance of debriefing in simulation-based pedagogy, (b) environment for which debriefing takes place is an important consideration, (c) individuals who should conduct the debrief, (d) length of debrief, and (e) methodology of the debrief. Debriefing models supported by theoretical frameworks and facilitated by trained staff are vital for a successful debriefing experience. Models differed from self-debriefing, facilitator-led debriefing, video-assisted debriefing, rapid cycle deliberate practice, and reflective debriefing. A reoccurring finding was centered around the emphasis of continued research for systematic tool development and analysis of the validity and effectiveness of current debriefing practices. There is a lack of consistency of debriefing models among nursing curriculum with an increasing rate of ill-prepared faculty to facilitate the debriefing phase of the simulation.

Keywords: debriefing model, debriefing intervention, health care professional, simulation-based education

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Authors: Vanessa de Cillos Silva, Fabrício José Piacente, Sônia Maria De Stefano Piedade, Valter Arthur

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The increasing concern in relation to safety and hygiene of food consumption makes it so that food conservation is studied. Food radiation is a technique used for conservation, but many consumers associate this technique with dangers such as environmental contamination and development of diseases. This research had the objective of evaluating the acceptance of radiated products by the consumer market in the city of Piracicaba/SP-Brasil. The methodology adopted was the application of a questionnaire in the city’s supermarkets. After the application, the data was tabulated and analyzed. It was observed that the majority of interviewees would not eat irradiated food. The unfamiliarity and questions about the safety of irradiated food were the main causes of your rejection.

Keywords: irradiation, questionnaire, storage, market acceptance

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Authors: Li-hsing Shih, Wei-Jen Hsu

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Recently, the sale of electrical vehicles (EVs) has increased dramatically due to maturing technology development and decreasing cost. Governments of many countries have made regulations and policies in favor of EVs due to their long-term commitment to net zero carbon emissions. However, due to uncertain factors such as the future price of EVs, forecasting the future market share of EVs is a challenging subject for both the auto industry and local government. This study tries to forecast the market share of EVs using conjoint models and Monte Carlo simulation. The research is conducted in three phases. (1) A conjoint model is established to represent the customer preference structure on purchasing vehicles while five product attributes of both EV and internal combustion engine vehicles (ICEV) are selected. A questionnaire survey is conducted to collect responses from Taiwanese consumers and estimate the part-worth utility functions of all respondents. The resulting part-worth utility functions can be used to estimate the market share, assuming each respondent will purchase the product with the highest total utility. For example, attribute values of an ICEV and a competing EV are given respectively, two total utilities of the two vehicles of a respondent are calculated and then knowing his/her choice. Once the choices of all respondents are known, an estimate of market share can be obtained. (2) Among the attributes, future price is the key attribute that dominates consumers’ choice. This study adopts the assumption of a learning curve to predict the future price of EVs. Based on the learning curve method and past price data of EVs, a regression model is established and the probability distribution function of the price of EVs in 2030 is obtained. (3) Since the future price is a random variable from the results of phase 2, a Monte Carlo simulation is then conducted to simulate the choices of all respondents by using their part-worth utility functions. For instance, using one thousand generated future prices of an EV together with other forecasted attribute values of the EV and an ICEV, one thousand market shares can be obtained with a Monte Carlo simulation. The resulting probability distribution of the market share of EVs provides more information than a fixed number forecast, reflecting the uncertain nature of the future development of EVs. The research results can help the auto industry and local government make more appropriate decisions and future action plans.

Keywords: conjoint model, electrical vehicle, learning curve, Monte Carlo simulation

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Authors: R. Mahmoodi, A. R. Zolfaghari

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In nuclear power plants, loss of coolant from the primary system is the type of reduced removed capacity that is given most attention; such an accident is referred as Loss of Coolant Accident (LOCA). In the current study, investigation of shell and tube THTL heat exchanger behavior during LOCA is implemented by ANSYS CFX simulation software in both steady state and transient mode of turbulent fluid flow according to experimental conditions. Numerical results obtained from ANSYS CFX simulation show good agreement with experimental data of THTL heat exchanger. The results illustrate that in large break LOCA as short term accident, heat exchanger could not fast response to temperature variables but in the long term, the temperature of shell side of heat exchanger will be increase.

Keywords: shell-and-tube heat exchanger, shell-side, CFD, flow and heat transfer, LOCA

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Authors: Hatem Mrad, Alban Notin, Mohamed Bouazara

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Sheet metal forming process has a multiple successive steps starting from sheets fixation to sheets evacuation. Often after forming operation, the sheet has defects requiring additional corrections steps. For example, in the drawing process, the formed sheet may have several defects such as springback, localized thinning and bends. All these defects are directly dependent on process, geometric and material parameters. The prediction and elimination of these defects requires the control of most sensitive parameters. The present study is concerned with a reliable parametric study of deep forming process in order to control the localized thinning. The proposed approach will be based on stochastic finite element method. Especially, the polynomial Chaos development will be used to establish a reliable relationship between input (process, geometric and material parameters) and output variables (sheet thickness). The commercial software Abaqus is used to conduct numerical finite elements simulations. The automatized parametrical modification is provided by coupling a FORTRAN routine, a PYTHON script and input Abaqus files.

Keywords: sheet metal forming, reliability, localized thinning, parametric simulation

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Authors: Christian Angerer, Markus Lienkamp

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Electric vehicles offer a high variety of possible drivetrain topologies with up to 4 motors. Multi-motor-designs can have several advantages regarding traction, vehicle dynamics, safety and even efficiency. With a rising number of motors, the whole drivetrain becomes more complex. All permutations of gearings, drivetrain-layouts, motor-types and –sizes lead up in a very large solution space. Single elements of this solution space can be analyzed by simulation methods. In addition to longitudinal vehicle behavior, which most optimization-approaches are restricted to, also lateral dynamics are important for vehicle dynamics, stability and efficiency. In order to compete large solution spaces and to find an optimal result, genetic algorithm based optimization is state-of-the-art. As lateral dynamics simulation is way more CPU-intensive, optimization takes much more time than in case of longitudinal-only simulation. Therefore, this paper shows an approach how to create meta-models from a 14-degree of freedom vehicle model in order to enable a numerically efficient drivetrain-layout optimization process under consideration of lateral dynamics. Different meta-modelling approaches such as neural networks or DoE are implemented and comparatively discussed.

Keywords: driving dynamics, drivetrain layout, genetic optimization, meta-modeling, lateral dynamicx

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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

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Authors: Herath M. P. C. Jayaweera, Samer Hanoun

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Path planning for on-time obstacle avoidance is an essential and challenging task that enables drones to achieve safe operation in any application domain. The level of challenge increases significantly on the obstacle avoidance technique when the drone is following a ground mobile entity (GME). This is mainly due to the change in direction and magnitude of the GME′s velocity in dynamic and unstructured environments. Force field techniques are the most widely used obstacle avoidance methods due to their simplicity, ease of use, and potential to be adopted for three-dimensional dynamic environments. However, the existing force field obstacle avoidance techniques suffer many drawbacks, including their tendency to generate longer routes when the obstacles are sideways of the drone′s route, poor ability to find the shortest flyable path, propensity to fall into local minima, producing a non-smooth path, and high failure rate in the presence of symmetrical obstacles. To overcome these shortcomings, this paper proposes an on-time three-dimensional obstacle avoidance method for drones to effectively and efficiently avoid dynamic and static obstacles in unknown environments while pursuing a GME. This on-time obstacle avoidance technique generates velocity waypoints for its obstacle-free and efficient path based on the shape of the encountered obstacles. This method can be utilized on most types of drones that have basic distance measurement sensors and autopilot-supported flight controllers. The proposed obstacle avoidance technique is validated and evaluated against existing force field methods for different simulation scenarios in Gazebo and ROS-supported PX4-SITL. The simulation results show that the proposed obstacle avoidance technique outperforms the existing force field techniques and is better suited for real-world applications.

Keywords: drones, force field methods, obstacle avoidance, path planning

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Authors: Nastaran Ahmadpour Samani, Shahram Talebi

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Added mass is an important quantity in analysis of the motion of a submerged object ,which can be calculated by solving the equation of potential flow around the object . Here, we consider systems in which a square object is submerged in a channel of fluid and moves parallel to the wall. The corresponding added mass at a given distance from the wall d and for the object size s (which is the side of square object) is calculated via lattice Blotzmann simulation . By changing d and s separately, their effect on the added mass is studied systematically. The simulation results reveal that for the systems in which d > 4s, the distance does not influence the added mass any more. The added mass increases when the object approaches the wall and reaches its maximum value as it moves on the wall (d -- > 0). In this case, the added mass is about 73% larger than which of the case d=4s. In addition, it is observed that the added mass increases by increasing of the object size s and vice versa.

Keywords: Lattice Boltzmann simulation , added mass, square, variable size

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Authors: Belyayev P. E., Makeyeva I. R., Mastyuk D. A., Pigasov E. E.

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Previously, the phrase ”hydrogen safety” was often used in terms of NPP safety. Due to the rise of interest to “green” and, particularly, hydrogen power engineering, the problem of hydrogen safety at industrial facilities has become ever more urgent. In Russia, the industrial production of hydrogen is meant to be performed by placing a chemical engineering plant near NPP, which supplies the plant with the necessary energy. In this approach, the production of hydrogen involves a wide range of combustible gases, such as methane, carbon monoxide, and hydrogen itself. Considering probable incidents, sudden combustible gas outburst into open space with further ignition is less dangerous by itself than ignition of the combustible mixture in the presence of many pipelines, reactor vessels, and any kind of fitting frames. Even ignition of 2100 cubic meters of the hydrogen-air mixture in open space gives velocity and pressure that are much lesser than velocity and pressure in Chapman-Jouguet condition and do not exceed 80 m/s and 6 kPa accordingly. However, the space blockage, the significant change of channel diameter on the way of flame propagation, and the presence of gas suspension lead to significant deflagration acceleration and to its transition into detonation or quasi-detonation. At the same time, process parameters acquired from the experiments at specific experimental facilities are not general, and their application to different facilities can only have a conventional and qualitative character. Yet, conducting deflagration and detonation experimental investigation for each specific industrial facility project in order to determine safe infrastructure unit placement does not seem feasible due to its high cost and hazard, while the conduction of numerical experiments is significantly cheaper and safer. Hence, the development of a numerical method that allows the description of reacting flows in domains with complex geometry seems promising. The base for this method is the modification of Kuropatenko method for calculating shock waves recently developed by authors, which allows using it in Eulerian coordinates. The current work contains the results of the development process. In addition, the comparison of numerical simulation results and experimental series with flame propagation in shock tubes with orifice plates is presented.

Keywords: CFD, reacting flow, DDT, gas explosion

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Authors: Marine Segui, Ruxandra Mihaela Botez

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OpenVSP is an aerodynamic solver developed by National Aeronautics and Space Administration (NASA) that allows building a reliable model of an aircraft. This software performs an aerodynamic simulation according to the angle of attack of the aircraft makes between the incoming airstream, and its speed. A reliable aerodynamic model of the Cessna Citation X was designed but it required a lot of computation time. As a consequence, a prediction method was established that allowed predicting lift and drag coefficients for all Mach numbers and for all angles of attack, exclusively for stall conditions, from a computation of three angles of attack and only one Mach number. Aerodynamic coefficients given by the prediction method for a Cessna Citation X model were finally compared with aerodynamics coefficients obtained using a complete OpenVSP study.

Keywords: aerodynamic, coefficient, cruise, improving, longitudinal, openVSP, solver, time

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Authors: Aulon Shabani, Denis Panxhi, Orion Zavalani

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This paper presents the modelling and development of a simulator for residential electrical appliances. The simulator is developed on MATLAB providing the possibility to analyze and simulate energy consumption of frequently used home appliances in Albania. Modelling of devices considers the impact of different factors, mentioning occupant behavior and climacteric conditions. Most devices are modeled as an electric circuit, and the electric energy consumption is estimated by the solutions of the guiding differential equations. The provided models refer to devices like a dishwasher, oven, water heater, air conditioners, light bulbs, television, refrigerator water, and pump. The proposed model allows us to simulate beforehand the energetic behavior of the largest consumption home devices to estimate peak consumption and improving its reduction. Simulated home prototype results are compared to real measurement of a considered typical home. Obtained results from simulator framework compared to monitored typical household using EmonTxV3 show the effectiveness of the proposed simulation. This conclusion will help for future simulation of a large group of typical household for a better understanding of peak consumption.

Keywords: electrical appliances, energy management, modelling, peak estimation, simulation, smart home

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Authors: Mazouz Halima, Belghachi Abdrahmane

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Effects of electron irradiation-induced deep level defects have been studied on both n/p and p/n indium phosphide solar cells with very thin emitters. The simulation results show that n/p structure offers a somewhat better short circuit current but the p/n structure offers improved circuit voltage, not only before electron irradiation, but also after 1MeV electron irradiation with 5.1015 fluence. The simulation also shows that n/p solar cell structure is more resistant than that of p/n structure.

Keywords: InP solar cell, p/n and n/p structure, electron irradiation, output parameters

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Authors: M. K. Balyan

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The main principles of X-ray Fourier interferometric holography method are discussed. The object image is reconstructed by the mathematical method of Fourier transformation. The three methods are presented – method of approximation, iteration method and step by step method. As an example the complex amplitude transmission coefficient reconstruction of a beryllium wire is considered. The results reconstructed by three presented methods are compared. The best results are obtained by means of step by step method.

Keywords: dynamical diffraction, hologram, object image, X-ray holography

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Authors: Wael M. Bazzi, Amir Rastegarnia, Azam Khalili

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In this paper we consider the issue of reliability of measurements in distributed adaptive estimation problem. To this aim, we assume a sensor network with different observation noise variance among the sensors and propose new estimation method based on incremental distributed least mean-square (IDLMS) algorithm. The proposed method contains two phases: I) Estimation of each sensors observation noise variance, and II) Estimation of the desired parameter using the estimated observation variances. To deal with the reliability of measurements, in the second phase of the proposed algorithm, the step-size parameter is adjusted for each sensor according to its observation noise variance. As our simulation results show, the proposed algorithm considerably improves the performance of the IDLMS algorithm in the same condition.

Keywords: adaptive filter, distributed estimation, sensor network, IDLMS algorithm

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Authors: N. Guruprasad

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This paper presents a modification of approximation method for transportation problems. The initial basic feasible solution can be computed using either Russel's or Vogel's approximation methods. Russell’s approximation method provides another excellent criterion that is still quick to implement on a computer (not manually) In most cases Russel's method yields a better initial solution, though it takes longer than Vogel's method (finding the next entering variable in Russel's method is in O(n1*n2), and in O(n1+n2) for Vogel's method). However, Russel's method normally has a lesser total running time because less pivots are required to reach the optimum for all but small problem sizes (n1+n2=~20). With this motivation behind we have incorporated a variation of the same – what we have proposed it has TMC (Total Modified Cost) to obtain fast and efficient solutions.

Keywords: computation, efficiency, modified cost, Russell’s approximation method, transportation, Vogel’s approximation method

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Authors: Magdy Roman, Mostafa Shoeib, Mostafa Rostom

Abstract:

Global vision, whether provided by overhead fixed cameras, on-board aerial vehicle cameras, or satellite images can always provide detailed information on the environment around mobile robots. In this paper, an intelligent vision-based method of path planning and obstacle avoidance for mobile robots is presented. The method integrates visual perception with a new proposed field-based path-planning method to overcome common path-planning problems such as local minima, unreachable destination and unnecessary lengthy paths around obstacles. The method proposes an exponential angle deviation field around each obstacle that affects the orientation of a close robot. As the robot directs toward, the goal point obstacles are classified into right and left groups, and a deviation angle is exponentially added or subtracted to the orientation of the robot. Exponential field parameters are chosen based on Lyapunov stability criterion to guarantee robot convergence to the destination. The proposed method uses obstacles' shape and location, extracted from global vision system, through a collision prediction mechanism to decide whether to activate or deactivate obstacles field. In addition, a search mechanism is developed in case of robot or goal point is trapped among obstacles to find suitable exit or entrance. The proposed algorithm is validated both in simulation and through experiments. The algorithm shows effectiveness in obstacles' avoidance and destination convergence, overcoming common path planning problems found in classical methods.

Keywords: path planning, collision avoidance, convergence, computer vision, mobile robots

Procedia PDF Downloads 198

Authors: Bib Paruhum Silalahi, Djihad Wungguli, Sugi Guritman

Abstract:

Steepest descent method is a simple gradient method for optimization. This method has a slow convergence in heading to the optimal solution, which occurs because of the zigzag form of the steps. Barzilai and Borwein modified this algorithm so that it performs well for problems with large dimensions. Barzilai and Borwein method results have sparked a lot of research on the method of steepest descent, including alternate minimization gradient method and Yuan method. Inspired by previous works, we modified the step size of the steepest descent method. We then compare the modification results against the Barzilai and Borwein method, alternate minimization gradient method and Yuan method for quadratic function cases in terms of the iterations number and the running time. The average results indicate that the steepest descent method with the new step sizes provide good results for small dimensions and able to compete with the results of Barzilai and Borwein method and the alternate minimization gradient method for large dimensions. The new step sizes have faster convergence compared to the other methods, especially for cases with large dimensions.

Keywords: steepest descent, line search, iteration, running time, unconstrained optimization, convergence

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Authors: Manikanta Prasad Banda, Che Hua Yang

Abstract:

Anti-symmetric wave propagation along the particle motion of the wedge waves is known as anti-symmetric flexural (ASF) modes which travel along the wedge tips of the mid-plane apex with a small truncation. This paper investigates the characteristics of the ASF modes propagation with the wedge tip crack. The simulation and experimental results obtained by a three-dimensional (3-D) finite element model explained the contact acoustic non-linear (CAN) behavior in explicit dynamics in ABAQUS and the ultrasonic non-destructive testing (NDT) method is used for defect detection. The effect of various parameters on its high and low-level conversion modes are known for complex reflections and transmissions involved with direct reflections and transmissions. The results are used to predict the location of crack through complex transmission and reflection coefficients.

Keywords: ASF mode, crack detection, finite elements method, laser ultrasound technique, wedge waves

Procedia PDF Downloads 141

Authors: Lican Wang, Rongqian Chen, Yancheng You, Ruofan Qiu

Abstract:

In the applications of jet engine, open-jet wind tunnel and airframe, there wildly exists a shear layer formed by the velocity and temperature gradients between jet flow and surrounded medium. The presence of shear layer will refract and reflect the sound path that consequently influences the measurement results in far-field. To investigate and evaluate the shear layer effect, a gradient term suppression and filtering method is adopted to simulate sound propagation through a steady sheared flow in three dimensions. Two typical configurations are considered: one is an incompressible and cold jet flow in wind tunnel and the other is a compressible and hot jet flow in turbofan engine. A numerically linear microphone array is used to localize the position of given sound source. The localization error is presented and linearly fitted.

Keywords: aeroacoustic, linearized Euler equation, acoustic propagation, source localization

Procedia PDF Downloads 208