Search results for: Computational%20Fluid%20Dynamics%20%28CFD%29

Authors: Gaurav Bisht, Rahul Rathnakumar, Ravikumar Duggirala

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Predictive simulations are one of the key focus areas in safety-critical industries such as aerospace and high-performance automotive engineering. The stone-chipping study is one such effort taken up by the industry to predict and evaluate the damage caused due to gravel impact on vehicles. This paper describes a finite elements based method that can simulate the ejection of gravel chips from a vehicle tire. The FE simulations were used to obtain the initial ejection velocity of the stones for various driving conditions using a computational contact mechanics approach. To verify the accuracy of the tire model, several parametric studies were conducted. The FE simulations resulted in stone loft velocities ranging from 0–8 m/s, regardless of tire speed. The stress on the tire at the instant of initial contact with the stone increased linearly with vehicle speed. Mesh convergence studies indicated that a highly resolved tire mesh tends to result in better momentum transfer between the tire and the stone. A fine tire mesh also showed a linearly increasing relationship between the tire forward speed and stone lofting speed, which was not observed in coarser meshes. However, it also highlighted a potential challenge, in that the ejection velocity vector of the stone seemed to be sensitive to the mesh, owing to the FE-based contact mechanical formulation of the problem.

Keywords: abaqus, contact mechanics, foreign object debris, stone chipping

Procedia PDF Downloads 261

Authors: Zwalnan Selfa Johnson, Caleb Nanchen Nimyel, Gideon Duvuna Ayuba

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Air conditioning accounts for a significant share of the overall energy consumed in residential buildings. Solar thermal gains in buildings account for a significant component of the air conditioning load in buildings. This study compares the solar thermal gain and air conditioning load of a proposed building design with a typical conventional building in the climatic conditions of Jos, Nigeria, using a combined experimental and computational method using TRNSYS software. According to the findings of this study, the proposed design building's annual average solar thermal gains are lower compared to the reference building's average solar heat gains. The study case building's decreased solar heat gain is mostly attributable to the lower temperature of the building zones because of the greater building volume and lower fenestration ratio (ratio external opening area to the area of the external walls). This result shows that the proposed building design adjusts to the local climate better than the standard conventional construction in Jos to maintain a suitable temperature within the building. This finding means that the air-conditioning electrical energy consumption per volume of the proposed building design will be lower than that of a conventional building design.

Keywords: solar heat gain, building zone, cooling energy, air conditioning, zone temperature

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Authors: Haifeng Wang, Haili Zhang

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Most movie recommendation systems have been developed for customers to find items of interest. This work introduces a predictive model usable by small and medium-sized enterprises (SMEs) who are in need of a data-based and analytical approach to stock proper movies for local audiences and retain more customers. We used classification models to extract features from thousands of customers’ demographic, behavioral and social information to predict their movie genre preference. In the implementation, a Gaussian kernel support vector machine (SVM) classification model and a logistic regression model were established to extract features from sample data and their test error-in-sample were compared. Comparison of error-out-sample was also made under different Vapnik–Chervonenkis (VC) dimensions in the machine learning algorithm to find and prevent overfitting. Gaussian kernel SVM prediction model can correctly predict movie genre preferences in 85% of positive cases. The accuracy of the algorithm increased to 93% with a smaller VC dimension and less overfitting. These findings advance our understanding of how to use machine learning approach to predict customers’ preferences with a small data set and design prediction tools for these enterprises.

Keywords: computational social science, movie preference, machine learning, SVM

Procedia PDF Downloads 257

Authors: Abderrahim Sidi Mohammed Nekrouf, Sarra Youcefi

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Fluid mixing plays a crucial role in numerous industries as it has a significant impact on the final product quality and performance. In certain cases, the circulation of viscous fluids presents challenges, leading to the formation of stagnant zones. To overcome this issue, stirring devices are employed for fluid mixing. This study focuses on a numerical analysis aimed at understanding the behavior of Newtonian fluids when agitated by a two-blade agitator in a cylindrical vessel. We investigate the influence of the agitator shape on fluid motion. Bi-blade agitators of this type are commonly used in the food, cosmetic, and chemical industries to agitate both viscous and non-viscous liquids. Numerical simulations were conducted using Computational Fluid Dynamics (CFD) software to obtain velocity profiles, streamlines, velocity contours, and the associated power number. The obtained results were compared with experimental data available in the literature, validating the accuracy of our numerical approach. The results clearly demonstrate that modifying the agitator shape has a significant impact on fluid motion. This modification generates an axial flow that enhances the efficiency of the fluid flow. The various velocity results convincingly reveal that the fluid is more uniformly agitated with this modification, resulting in improved circulation and a substantial reduction in stagnant zones.

Keywords: Newtonian fluids, numerical modeling, two blade., CFD

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Authors: Plessen Mogens Graf

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Within the context of multivariate time series segmentation, this paper proposes a method inspired by a posteriori optimal trading. After a normalization step, time series are treated channelwise as surrogate stock prices that can be traded optimally a posteriori in a virtual portfolio holding either stock or cash. Linear transaction costs are interpreted as hyperparameters for noise filtering. Trading signals, as well as trading signals obtained on the reversed time series, are used for unsupervised channelwise labeling before a consensus over all channels is reached that determines the final segmentation time instants. The method is model-free such that no model prescriptions for segments are made. Benefits of proposed approach include simplicity, computational efficiency, and adaptability to a wide range of different shapes of time series. Performance is demonstrated on synthetic and real-world data, including a large-scale dataset comprising a multivariate time series of dimension 1000 and length 2709. Proposed method is compared to a popular model-based bottom-up approach fitting piecewise affine models and to a recent model-based top-down approach fitting Gaussian models and found to be consistently faster while producing more intuitive results in the sense of segmenting time series at peaks and valleys.

Keywords: time series segmentation, model-free, trading-inspired, multivariate data

Procedia PDF Downloads 133

Authors: Akwu N. A., Naidoo Y., Salau V. F., Olofinsan K. A.

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Grewia lasiocarpa E. Mey. ex Harv. (Malvaceae) is a Southern African medicinal plant indigenously used with other plants for birthing problems. The anti-diabetic properties of the hexane, chloroform, and methanol extracts of Grewia lasiocarpa stem bark were assessed using in vitro α-glucosidase enzyme inhibition assay. The predictive in silico drug-likeness and toxicity properties of the phytocompounds were conducted using the pKCSM, ADMElab, and SwissADME computer-aided online tools. The highest α-glucosidase percentage inhibition was observed in the hexane extract (86.76%, IC50= 0.24 mg/mL), followed by chloroform (63.08%, IC50= 4.87 mg/mL) and methanol (53.22%, IC50= 9.41 mg/mL); while acarbose, the standard anti-diabetic drug was (84.54%, IC50= 1.96 mg/mL). The α-glucosidase assay revealed that the hexane extract exhibited the strongest carbohydrate inhibiting capacity and is a better inhibitor than the standard reference drug-acarbose. The computational studies also affirm the results observed in the in vitroα-glucosidaseassay. Thus, the extracts of G. lasiocarpa may be considered a potential plant-sourced compound for treating type 2 diabetes mellitus. This is the first study on the anti-diabetic properties of Grewia lasiocarpa hexane, chloroform, and methanol extracts using in vitro and in silico models.

Keywords: grewia lasiocarpa, α-glucosidase inhibition, anti-diabetes, ADMET

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Authors: Ronal Muresano, Andrea Pagano

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Nowadays, the mathematical/statistical applications are developed with more complexity and accuracy. However, these precisions and complexities have brought as result that applications need more computational power in order to be executed faster. In this sense, the multicore environments are playing an important role to improve and to optimize the execution time of these applications. These environments allow us the inclusion of more parallelism inside the node. However, to take advantage of this parallelism is not an easy task, because we have to deal with some problems such as: cores communications, data locality, memory sizes (cache and RAM), synchronizations, data dependencies on the model, etc. These issues are becoming more important when we wish to improve the application’s performance and scalability. Hence, this paper describes an optimization method developed for Systemic Model of Banking Originated Losses (SYMBOL) tool developed by the European Commission, which is based on analyzing the application's weakness in order to exploit the advantages of the multicore. All these improvements are done in an automatic and transparent manner with the aim of improving the performance metrics of our tool. Finally, experimental evaluations show the effectiveness of our new optimized version, in which we have achieved a considerable improvement on the execution time. The time has been reduced around 96% for the best case tested, between the original serial version and the automatic parallel version.

Keywords: algorithm optimization, bank failures, OpenMP, parallel techniques, statistical tool

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Authors: Zheni S. Stefanova, Kandethody M. Ramachandran

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With the increasing dependency on our computer devices, we face the necessity of adequate, efficient and effective mechanisms, for protecting our network. There are two main problems that Intrusion Detection Systems (IDS) attempt to solve. 1) To detect the attack, by analyzing the incoming traffic and inspect the network (intrusion detection). 2) To produce a prompt response when the attack occurs (intrusion prevention). It is critical creating an Intrusion detection model that will detect a breach in the system on time and also challenging making it provide an automatic and with an acceptable delay response at every single stage of the monitoring process. We cannot afford to adopt security measures with a high exploiting computational power, and we are not able to accept a mechanism that will react with a delay. In this paper, we will propose an intrusion response mechanism that is based on artificial intelligence, and more precisely, reinforcement learning techniques (RLT). The RLT will help us to create a decision agent, who will control the process of interacting with the undetermined environment. The goal is to find an optimal policy, which will represent the intrusion response, therefore, to solve the Reinforcement learning problem, using a Q-learning approach. Our agent will produce an optimal immediate response, in the process of evaluating the network traffic.This Q-learning approach will establish the balance between exploration and exploitation and provide a unique, self-learning and strategic artificial intelligence response mechanism for IDS.

Keywords: cyber security, intrusion prevention, optimal policy, Q-learning

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Authors: Bircan Demiral

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Cognitive radio (CR) is the promising technology that addresses the spectrum scarcity problem for future wireless communications. Orthogonal Frequency Division Multiplexing (OFDM) technology provides more power band ratios for cognitive radio networks (CRNs). While CR is a solution to the spectrum scarcity, it also brings up the capacity problem. In this paper, a novel power allocation algorithm that aims at maximizing the sum capacity in the OFDM based cognitive radio networks is proposed. Proposed allocation algorithm is based on the previously developed water-filling algorithm. To reduce the computational complexity calculating in water filling algorithm, proposed algorithm allocates the total power according to each subcarrier. The power allocated to the subcarriers increases sum capacity. To see this increase, Matlab program was used, and the proposed power allocation was compared with average power allocation, water filling and general power allocation algorithms. The water filling algorithm performed worse than the proposed algorithm while it performed better than the other two algorithms. The proposed algorithm is better than other algorithms in terms of capacity increase. In addition the effect of the change in the number of subcarriers on capacity was discussed. Simulation results show that the increase in the number of subcarrier increases the capacity.

Keywords: cognitive radio network, OFDM, power allocation, water filling

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Authors: William J. Crowther, Conor Marsh

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Object-based flow simulation allows fast computation of arbitrarily complex aerodynamic models made up of simple objects with limited flow interactions. The proposed approach is universally applicable to objects made from arbitrarily scaled ellipsoid primitives at arbitrary aerodynamic attitude and angular rate. The use of a component-based aerodynamic modelling approach increases efficiency by allowing selective inclusion of different physics models at run-time and allows extensibility through the development of new models. Insight into the numerical stability of the model under first order fixed-time step integration schemes is provided by stability analysis of the drag component. The compute cost of model components and functions is evaluated and compared against numerical benchmarks. Model static outputs are verified against theoretical expectations and dynamic behaviour using falling plate data from the literature. The model is applied to a range of case studies to demonstrate the efficacy of its application in extensibility, ease of use, and low computational cost. Dynamically complex multi-body systems can be implemented in a transparent and efficient manner, and we successfully demonstrate large scenes with hundreds of objects interacting with diverse flow fields.

Keywords: aerodynamics, real-time simulation, low-order model, flight dynamics

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Authors: Selin Kunc, Srinivas Koushik Gundimeda, John A. Gallagher, Roselita Fragoudakis

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This study investigates the behavior of Glass Fiber Reinforced Plastic (GFRP) laminated beams additionally reinforced with piezoelectric fibers. The electromechanical behavior of piezoelectric materials coupled with high strength/low weight GFRP laminated beams can have significant application in a wide range of industries. Energy scavenging through mechanical vibrations is the focus of this study, and possible applications can be seen in the automotive industry. This study examines the behavior of such composite laminates using Classical Lamination Theory (CLT) under three-point bending conditions. Fiber orientation is optimized for the desired stiffness and deflection that yield maximum energy output. Finite element models using ABAQUS/CAE are verified through experimental testing. The optimum stacking sequences examined are [0o]s, [ 0/45o]s, and [45/-45o]s. Results show the superiority of the stacking sequence [0/45o]s, providing higher strength at a lower weight, and maximum energy output. Furthermore, laminated GFRP beams additionally reinforced with piezoelectric fibers can be used under bending to not only replace metallic component while providing similar strength at a lower weight but also provide an energy output.

Keywords: classical lamination theory (CLT), energy scavenging, glass fiber reinforced plastics (GFRP), piezoelectric fibers

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Authors: Salah Hassab Elnaby, Omnia Hamdy, Aziza Ahmed Hassan, Salwa Abdelkawi, Ibrahim Abdelhalim

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Laser corneal reshaping has been proposed as a successful treatment of many refraction disorders. However, some physical and chemical demonstrations of the laser effect upon interaction with the corneal tissue are still not fully explained. Therefore, different computational and mathematical models have been implemented to predict the depth of the ablated channel and calculate the ablation threshold and the local temperature rise. In the current paper, we present a modified model that aims to answer some of the open questions about the ablation threshold, the ablation rate, and the physical and chemical mechanisms of that action. The proposed model consists of three parts. The first part deals with possible photochemical reactions between the incident photons and various components of the cornea (collagen, water, etc.). Such photochemical reactions may end by photo-ablation or just the electronic excitation of molecules. Then a chemical reaction is responsible for the ablation threshold. Finally, another chemical reaction produces fragments that can be cleared out. The model takes into account all processes at the same time with different probabilities. Moreover, the effect of applying different laser wavelengths that have been studied before, namely the common excimer laser (193-nm) and the solid state lasers (213-nm & 266-nm), has been investigated. Despite the success and ubiquity of the ArF laser, the presented results reveal that a carefully designed 213-nm laser gives the same results with lower operational drawbacks. Moreover, the use of mode locked laser could also decrease the risk of heat generation and diffusion.

Keywords: UV lasers, mathematical model, corneal ablation, photochemical ablation

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Authors: Asad Islam, Khalid Parvez

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Compressor fans in modern aircraft engines are of considerate importance, as they provide majority of thrust required by the aircraft. Their challenging environment is frequently subjected to non-uniform inflow conditions. These conditions could be either due to the flight operating requirements such as take-off and landing, wake interference from aircraft fuselage or cross-flow wind conditions. So, in highly maneuverable flights regimes of fighter aircrafts affects the overall performance of an engine. Since the flow in compressor of an aircraft application is highly sensitive because of adverse pressure gradient due to different flow orientations of the aircraft. Therefore, it is prone to unstable operations. This paper presents the study that focuses on axial compressor response to inlet flow orientations for the range of angles as 0 to 15 degrees. For this purpose, NASA Rotor-37 was taken and CFD mesh was developed. The compressor characteristics map was generated for the design conditions of pressure ratio of 2.106 with the rotor operating at rotational velocity of 17188.7 rpm using CFD simulating environment of ANSYS-CFX®. The grid study was done to see the effects of mesh upon computational solution. Then, the mesh giving the best results, (when validated with the available experimental NASA’s results); was used for further distortion analysis. The flow in the inlet nozzle was given angle orientations ranging from 0 to 15 degrees. The CFD results are analyzed and discussed with respect to stall margin and flow separations due to induced distortions.

Keywords: axial compressor, distortions, angle, CFD, ANSYS-CFX®, bladegen®

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Authors: Robert Joseph M. Licup

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The deployment of the fifth-generation (5G) mobile system through mmWave frequencies is the new solution in the requirement to provide higher bandwidth readily available for all users. The usage pattern of the mobile users has moved towards either the work from home or online classes set-up because of the pandemic. Previous mobile technologies can no longer meet the high speed, and bandwidth requirement needed, given the drastic shift of transactions to the home. The millimeter-wave (mmWave) underutilized frequency is utilized by the fifth-generation (5G) cellular networks that support multi-gigabit-per-second (Gbps) transmission. However, due to its short wavelengths, high path loss, directivity, blockage sensitivity, and narrow beamwidth are some of the technical challenges that need to be addressed. Different tools, technologies, and scenarios are explored to support network design, accurate channel modeling, implementation, and deployment effectively. However, there is a big challenge on how the consumer will adopt this solution and maximize the benefits offered by the 5G Technology. This research proposes to study the intricacies of technology diffusion, individual attitude, behaviors, and how technology adoption will be attained. The agent based simulation model shaped by the actual applications, technology solution, and related literature was used to arrive at a computational model. The research examines the different attributes, factors, and intricacies that can affect each identified agent towards technology adoption.

Keywords: agent-based model, AnyLogic, 5G O21, 5G mmWave solutions, technology adoption

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Authors: Marcela de Oliveira, Guilherme Giacomini, Allan Felipe Fattori Alves, Ana Luiza Menegatti Pavan, Maria Eugenia Dela Rosa, Fernando Antonio Bacchim Neto, Diana Rodrigues de Pina

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It is estimated that each year one death every 10 seconds (about 2 million deaths) in the world is attributed to tuberculosis (TB). Even after effective treatment, TB leaves sequelae such as, for example, pulmonary fibrosis, compromising the quality of life of patients. Evaluations of the aforementioned sequel are usually performed subjectively by radiology specialists. Subjective evaluation may indicate variations inter and intra observers. The examination of x-rays is the diagnostic imaging method most accomplished in the monitoring of patients diagnosed with TB and of least cost to the institution. The application of computational algorithms is of utmost importance to make a more objective quantification of pulmonary impairment in individuals with tuberculosis. The purpose of this research is the use of computer algorithms to quantify the pulmonary impairment pre and post-treatment of patients with pulmonary TB. The x-ray images of 10 patients with TB diagnosis confirmed by examination of sputum smears were studied. Initially the segmentation of the total lung area was performed (posteroanterior and lateral views) then targeted to the compromised region by pulmonary sequel. Through morphological operators and the application of signal noise tool, it was possible to determine the compromised lung volume. The largest difference found pre- and post-treatment was 85.85% and the smallest was 54.08%.

Keywords: algorithm, radiology, tuberculosis, x-rays exam

Procedia PDF Downloads 417

Authors: Chuan-Wen Liu, Min-Hsien Liu, Chung-Chieh Tai, Bing-Cheng Kuo, Cheng-Lung Chen, Huazhen Shen

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A recent surge in research on magnetic radar absorbing materials (RAMs) has presented researchers with new opportunities and challenges. This study was performed to gain a better understanding of the wave-absorbing phenomenon of magnetic RAMs. First, we hypothesized that the absorbing phenomenon is dependent on the particle shape. Using the Material Studio program and the micro-dot magnetic dipoles (MDMD) method, we obtained results from magnetic RAMs to support this hypothesis. The total MDMD energy of disk-like iron particles was greater than that of spherical iron particles. In addition, the particulate aggregation phenomenon decreases the wave-absorbance, according to both experiments and computational data. To conclude, this study may be of importance in terms of explaining the wave- absorbing characteristic of magnetic RAMs. Combining molecular dynamics simulation results and the theory of magnetization of magnetic dots, we investigated the magnetic properties of iron materials with different particle shapes and degrees of aggregation under external magnetic fields. The MDMD of the materials under magnetic fields of various strengths were simulated. Our results suggested that disk-like iron particles had a better magnetization than spherical iron particles. This result could be correlated with the magnetic wave- absorbing property of iron material.

Keywords: wave-absorbing property, magnetic material, micro-dot magnetic dipole, particulate aggregation

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Authors: Jannes Quer, Amir Niknejad, Marcus Weber

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Computational Drug Design is often based on Molecular Dynamics simulations of molecular systems. Molecular Dynamics can be used to simulate, e.g., the binding and unbinding event of a small drug-like molecule with regard to the active site of an enzyme or a receptor. However, the time-scale of the overall binding event is many orders of magnitude longer than the time-scale of simulation. Thus, there is a need to speed-up molecular simulations. In order to speed up simulations, the molecular dynamics trajectories have to be ”steared” out of local minimizers of the potential energy surface – the so-called metastabilities – of the molecular system. Increasing the kinetic energy (temperature) is one possibility to accelerate simulated processes. However, with temperature the entropy of the molecular system increases, too. But this kind ”stearing” is not directed enough to stear the molecule out of the minimum toward the saddle point. In this article, we give a new mathematical idea, how a potential energy surface can be changed in such a way, that entropy is kept under control while the trajectories are still steared out of the metastabilities. In order to compute the unsteared transition behaviour based on a steared simulation, we propose to use extrapolation methods. In the end we mathematically show, that our method accelerates the simulations along the direction, in which the curvature of the potential energy surface changes the most, i.e., from local minimizers towards saddle points.

Keywords: extrapolation, Eyring-Kramers, metastability, multilevel sampling

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Authors: Su Ying-Ming

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High density of high rise buildings in urban areas lead to a deteriorative Urban Heat Island Effect, gradually. This study focuses on discussing the relationship between urban layout and ventilation comfort in street canyons. This study takes Songjiang Nanjing Rd. area of Taipei, Taiwan as an example to evaluate the wind environment comfort index by field measurement and Computational Fluid Dynamics (CFD) to improve both the quality and quantity of the environment. In this study, different factors including street blocks size, the width of buildings, street width ratio and the direction of the wind were used to discuss the potential of ventilation. The environmental wind field was measured by the environmental testing equipment, Testo 480. Evaluation of blocks sizes, the width of buildings, street width ratio and the direction of the wind was made under the condition of constant floor area with the help of Stimulation CFD to adjust research methods for optimizing regional wind environment. The results of this study showed the width of buildings influences the efficiency of outdoor ventilation; improvement of the efficiency of ventilation with large street width was also shown. The study found that Block width and H/D value and PR value has a close relationship. Furthermore, this study showed a significant relationship between the alteration of street block geometry and outdoor comfortableness.

Keywords: urban ventilation path, ventilation efficiency indices, CFD, building layout

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Authors: Akalu Banbeta, Emmanuel Lesaffre, Reynaldo Martina, Joost Van Rosmalen

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Including data from previous studies (historical data) in the analysis of the current study may reduce the sample size requirement and/or increase the power of analysis. The most common example is incorporating historical control data in the analysis of a current clinical trial. However, this only applies when the historical control dataare similar enough to the current control data. Recently, several Bayesian approaches for incorporating historical data have been proposed, such as the meta-analytic-predictive (MAP) prior and the modified power prior (MPP) both for single control as well as for multiple historical control arms. Here, we examine the performance of the MAP and the MPP approaches for the analysis of (over-dispersed) count data. To this end, we propose a computational method for the MPP approach for the Poisson and the negative binomial models. We conducted an extensive simulation study to assess the performance of Bayesian approaches. Additionally, we illustrate our approaches on an overactive bladder data set. For similar data across the control arms, the MPP approach outperformed the MAP approach with respect to thestatistical power. When the means across the control arms are different, the MPP yielded a slightly inflated type I error (TIE) rate, whereas the MAP did not. In contrast, when the dispersion parameters are different, the MAP gave an inflated TIE rate, whereas the MPP did not.We conclude that the MPP approach is more promising than the MAP approach for incorporating historical count data.

Keywords: count data, meta-analytic prior, negative binomial, poisson

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Authors: Javier A. Maldonado E., Duvert A. Puentes T., Diego F. Villegas B.

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The SLAP lesion (Superior Labral Anterior to Posterior) involves the labrum, causing pain and mobility problems in the glenohumeral joint. This injury is common in athletes practicing sports that requires throwing or those who receive traumatic impacts on the shoulder area. This paper determines the biomechanical behavior of soft tissues of the glenohumeral joint when type II SLAP lesion is present. This pathology is characterized for a tear in the superior labrum which is simulated in a 3D model of the shoulder joint. A 3D model of the glenohumeral joint was obtained using the free software Slice. Then, a Finite Element analysis was done using a general purpose software which simulates a compression test with external rotation. First, a validation was done assuming a healthy joint shoulder with a previous study. Once the initial model was validated, a lesion of the labrum built using a CAD software and the same test was done again. The results obtained were stress and strain distribution of the synovial capsule and the injured labrum. ANOVA was done for the healthy and injured glenohumeral joint finding significant differences between them. This study will help orthopedic surgeons to know the biomechanics involving this type of lesion and also the other surrounding structures affected by loading the injured joint.

Keywords: biomechanics, computational model, finite elements, glenohumeral joint, superior labral anterior to posterior lesion

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Authors: Hicham Gourgue, Ahmed Aharoune, Ahmed Ihlal

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We present in this work our model of road traffic emissions (line sources) and dispersion of these emissions, named DISPOLSPEM (Dispersion of Poly Sources and Pollutants Emission Model). In its emission part, this model was designed to keep the consistent bottom-up and top-down approaches. It also allows to generate emission inventories from reduced input parameters being adapted to existing conditions in Morocco and in the other developing countries. While several simplifications are made, all the performance of the model results are kept. A further important advantage of the model is that it allows the uncertainty calculation and emission rate uncertainty according to each of the input parameters. In the dispersion part of the model, an improved line source model has been developed, implemented and tested against a reference solution. It provides improvement in accuracy over previous formulas of line source Gaussian plume model, without being too demanding in terms of computational resources. In the case study presented here, the biggest errors were associated with the ends of line source sections; these errors will be canceled by adjacent sections of line sources during the simulation of a road network. In cases where the wind is parallel to the source line, the use of the combination discretized source and analytical line source formulas minimizes remarkably the error. Because this combination is applied only for a small number of wind directions, it should not excessively increase the calculation time.

Keywords: air pollution, dispersion, emissions, line sources, road traffic, urban transport

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Authors: O. Afshar

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Unlike other renewable energy sources, tidal current energy is an extremely reliable, predictable and continuous energy source as the current pattern and speed can be predicted throughout the year. A key concern associated with tidal turbines is their long-term reliability when operating in the hostile marine environment. Bio-fouling changes the physical shape and roughness of turbine components, hence altering the overall turbine performance. This paper seeks to employ Computational Fluid Dynamics (CFD) method to quantify the effects of this problem based on the obtained flow field information. The simulation is carried out on a NACA 63-618 aerofoil. The Reynolds Averaged Navier-Stokes (RANS) equations with Shear Stress Transport (SST) turbulent model are used to simulate the flow around the model. Different levels of fouling are studied on 2D aerofoil surface with quantified fouling height and density. In terms of lift and drag coefficient results, numerical results show good agreement with the experiment which was carried out in wind tunnel. Numerical results of research indicate that an increase in fouling thickness causes an increase in drag coefficient and a reduction in lift coefficient. Moreover, pressure gradient gradually becomes adverse as height of fouling increases. In addition, result by turbulent kinetic energy contour reveals it increases with fouling height and it extends into wake due to flow separation.

Keywords: tidal energy, lift coefficient, drag coefficient, roughness

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Authors: M. Hussaina, K. Mahboobb, S. Z. Ilyasa, S. Shaheena

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Plume dispersion modeling is a computational procedure to establish a relationship between emissions, meteorology, atmospheric concentrations, deposition and other factors. The emission characteristics (stack height, stack diameter, release velocity, heat contents, chemical and physical properties of the gases/particle released etc.), terrain (surface roughness, local topography, nearby buildings) and meteorology (wind speed, stability, mixing height, etc.) are required for the modeling of the plume dispersion and estimation of ground and air concentration. During the early phase of Fukushima accident, plume dispersion modeling and decisions were taken for the implementation of protective measures. A difference in estimated results and decisions made by different countries for taking protective actions created a concern in local and international community regarding the exact identification of the safe zone. The current study is focused to highlight the importance of accurate and exact weather data availability, scientific approach for decision making for taking urgent protective actions, compatible and harmonized approach for plume dispersion modeling during a nuclear emergency. As a case study, the influence of meteorological data on plume dispersion modeling and decision-making process has been performed.

Keywords: decision making process, radiation doses, nuclear emergency, meteorological implications

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Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

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The seismic responses-based structural health monitoring system has been performed to reduce seismic damage. The inter-story drift ratio which is the major index of the seismic capacity assessment is employed for estimating the seismic damage of buildings. Meanwhile, seismic response analysis to estimate the structural responses of building demands significantly high computational cost due to increasing number of high-rise and large buildings. To estimate the inter-story drift ratio of buildings from the earthquake efficiently, this paper suggests the estimation method of inter-story drift for buildings using an artificial neural network (ANN). In the method, the radial basis function neural network (RBFNN) is integrated with optimization algorithm to optimize the variable through evolutionary learning that refers to evolutionary radial basis function neural network (ERBFNN). The estimation method estimates the inter-story drift without seismic response analysis when the new earthquakes are subjected to buildings. The effectiveness of the estimation method is verified through a simulation using multi-degree of freedom system.

Keywords: structural health monitoring, inter-story drift ratio, artificial neural network, radial basis function neural network, genetic algorithm

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Authors: Yee Hooi Min, Abdul Hadi, M. N., A. G. Kay Dora

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Form-finding has to be carried out for tensioned fabric structure in order to determine the initial equilibrium shape under prescribed support condition and pre-stress pattern. Tensioned fabric structures are normally designed to be in the form of equal tensioned surface. Tensioned fabric structure is highly suited to be used for realizing surfaces of complex or new forms. However, research study on a new form as a tensioned fabric structure has not attracted much attention. Another source of inspiration minimal surface which could be adopted as form for tensioned fabric structure is very crucial. The aim of this study is to propose initial equilibrium shape of tensioned fabric structures in the form of Monkey Saddle. Computational form-finding is frequently used to determine the possible form of uniformly stressed surfaces. A tensioned fabric structure must curve equally in opposite directions to give the resulting surface a three dimensional stability. In an anticlastic doubly curved surface, the sum of all positive and all negative curvatures is zero. This study provides an alternative choice for structural designer to consider the Monkey Saddle applied in tensioned fabric structures. The results on factors affecting initial equilibrium shape can serve as a reference for proper selection of surface parameter for achieving a structurally viable surface. Such in-sight will lead to improvement of rural basic infrastructure, economic gains, sustainability of built environment and green technology initiative.

Keywords: anticlastic, curvatures, form-finding, initial equilibrium shape, minimal surface, tensioned fabric structure

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Authors: Josif Figueroa, Kush Bubbar, Greg Young-Morris

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The reliability evaluation of composite generation and bulk transmission systems is crucial for ensuring a reliable supply of electrical energy to significant system load points. However, evaluating adequacy indices using probabilistic methods like sequential Monte Carlo Simulation can be computationally expensive. Despite this, it is necessary when time-varying and interdependent resources, such as renewables and energy storage systems, are involved. Recent advances in solving power network optimization problems and parallel computing have improved runtime performance while maintaining solution accuracy. This work introduces CompositeSystems, an open-source Composite System Reliability Evaluation tool developed in Julia™, to address the current deficiencies of commercial and non-commercial tools. This work introduces its design, validation, and effectiveness, which includes analyzing two different formulations of the Optimal Power Flow problem. The simulations demonstrate excellent agreement with existing published studies while improving replicability and reproducibility. Overall, the proposed tool can provide valuable insights into the performance of transmission systems, making it an important addition to the existing toolbox for power system planning.

Keywords: open-source software, composite system reliability, optimization methods, Monte Carlo methods, optimal power flow

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Authors: Tawfiq Chekifi, Brahim Dennai, Rachid Khelfaoui

Abstract:

Over the last few decades, modeling immiscible fluids such as oil and water have been a classical research topic. Droplet-based microfluidics presents a unique platform for mixing, reaction, separation, dispersion of drops, and numerous other functions. For this purpose, several devices were studied, as well as microfluidic oscillator. The latter was obtained from wall attachment microfluidic amplifiers using a feedback loop from the outputs to the control inputs, nevertheless this device have not well used for microdrops applications. In this paper, we suggest a numerical CFD study of a microfluidic oscillator with two different lengths of feedback loop. In order to produce simultaneous microdrops of gasoil on water, a typical geometry that includes double T-junction is connected to the fluidic oscillator. The generation of microdrops is computed by volume-of-fluid method (VOF). Flow oscillations of microdrops were triggered by the Coanda effect of jet flow. The aim of work is to obtain a high oscillation frequency in output of this passive device, the influence of hydrodynamics and physics parameters on the microdrops frequency in the output of our microsystem is also analyzed, The computational results show that, the length of feedback loop, applied pressure on T-junction and interfacial tension have a significant effect on the dispersion of microdrops and its oscillation frequency. Across the range of low Reynold number, the microdrops generation and its dynamics have been accurately controlled by adjusting applying pressure ratio of two phases.

Keywords: fluidic oscillator, microdrops manipulation, VOF (volume of fluid method), microfluidic oscillator

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Authors: Norhan El Dallal

Abstract:

The MENA region is a challenging, rapid urbanizing region, with a special profile; culturally, socially, economically and environmentally. Despite the diversity between different countries of the MENA region they all share similar urban challenges where extensive interventions are crucial. A climate sensitive region as the MENA region requires special attention for development, adaptation and mitigation. Integrating climatic and environmental parameters into the planning process to create a responsive urban form is the aim of this research in which “Parametric Urbanism” as a trend serves as a tool to reach a more sustainable urban morphology. An attempt to parameterize the relation between the climate and the urban form in a detailed manner is the main objective of the thesis. The aim is relating the different passive approaches suitable for the MENA region with the design guidelines of each and every part of the planning phase. Various conceptual scenarios for the network pattern and block subdivision generation based on computational models are the next steps after the parameterization. These theoretical models could be applied on different climatic zones of the dense communities of the MENA region to achieve an energy efficient neighborhood or city with respect to the urban form, morphology, and urban planning pattern. A final criticism of the theoretical model is to be conducted showing the feasibility of the proposed solutions economically. Finally some push and pull policies are to be proposed to help integrate these solutions into the planning process.

Keywords: parametric urbanism, climate responsive, urban form, urban and regional studies

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Authors: Zekang Lan, Yan Xu, Yingkun Huang, Dian Huang, Shengzhong Feng

Abstract:

Jobs on high-performance computing (HPC) clusters can suffer significant performance degradation due to inter-job network interference. Topology-aware job allocation problem (TJAP) is such a problem that decides how to dedicate nodes to specific applications to mitigate inter-job network interference. In this paper, we study the window-based TJAP on a fat-tree network aiming at minimizing the cost of communication hop, a defined inter-job interference metric. The window-based approach for scheduling repeats periodically, taking the jobs in the queue and solving an assignment problem that maps jobs to the available nodes. Two special allocation strategies are considered, i.e., static continuity assignment strategy (SCAS) and dynamic continuity assignment strategy (DCAS). For the SCAS, a 0-1 integer programming is developed. For the DCAS, an approach called neural simulated algorithm (NSA), which is an extension to simulated algorithm (SA) that learns a repair operator and employs them in a guided heuristic search, is proposed. The efficacy of NSA is demonstrated with a computational study against SA and SCIP. The results of numerical experiments indicate that both the model and algorithm proposed in this paper are effective.

Keywords: high-performance computing, job allocation, neural simulated annealing, topology-aware

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Authors: Pooja Rani, G. S. Mahapatra, S. K. Pandey

Abstract:

In this paper, we propose a novel approach of Neural Network and Particle Swarm Optimization methods for software reliability prediction. We first explain how to apply compound function in neural network so that we can derive a Flexible Logistic (S-shaped) Growth Curve (FLGC) model. This model mathematically represents software failure as a random process and can be used to evaluate software development status during testing. To avoid trapping in local minima, we have applied Particle Swarm Optimization method to train proposed model using failure test data sets. We drive our proposed model using computational based intelligence modeling. Thus, proposed model becomes Neuro-Particle Swarm Optimization (NPSO) model. We do test result with different inertia weight to update particle and update velocity. We obtain result based on best inertia weight compare along with Personal based oriented PSO (pPSO) help to choose local best in network neighborhood. The applicability of proposed model is demonstrated through real time test data failure set. The results obtained from experiments show that the proposed model has a fairly accurate prediction capability in software reliability.

Keywords: software reliability, flexible logistic growth curve model, software cumulative failure prediction, neural network, particle swarm optimization

Procedia PDF Downloads 343