Search results for: computational finance

Authors: Ahmed Al-Saadi, Ali Hassanpour, Tariq Mahmud

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The main objective of this study is to investigate ways to reduce the aerodynamic drag coefficient and to increase the stability of the full-size Sport Utility Vehicle using three-dimensional Computational Fluid Dynamics (CFD) simulation. The baseline model in the simulation was the Land Rover Discovery 4. Many aerodynamic devices and external design modifications were used in this study. These reduction aerodynamic techniques were tested individually or in combination to get the best design. All new models have the same capacity and comfort of the baseline model. Uniform freestream velocity of the air at inlet ranging from 28 m/s to 40 m/s was used. ANSYS Fluent software (version 16.0) was used to simulate all models. The drag coefficient obtained from the ANSYS Fluent for the baseline model was validated with experimental data. It is found that the use of modern aerodynamic add-on devices and modifications has a significant effect in reducing the aerodynamic drag coefficient.

Keywords: aerodynamics, RANS, sport utility vehicle, turbulent flow

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Authors: Sakura Ganegama Bogodage, Andrew Yee Tat Leung

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This paper describes experimental, Computational Fluid Dynamics (CFD) and theoretical analysis of a cyclone performance, operated 1.0 g/m3 solid loading rate, at two different inlet velocities (5 m/s and 10 m/s). Comparing experimental results with theoretical and CFD simulation results, it is pronounced that the influence of solid in processing flow is significant than expected. Experimental studies based on gas- solid flows of cyclone separators are complicated as they required advanced sensitive measuring techniques, especially flow characteristics. Thus, CFD modelling and theoretical analysis are economical in analyzing cyclone separator performance but detailed clarifications of the application of these in cyclone separator performance evaluation is not yet discussed. The present study shows the limitations of influencing parameters of CFD and theoretical considerations, comparing experimental results and flow characteristics from CFD modelling.

Keywords: cyclone performance, inlet velocity, pressure drop, solid loading rate

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Authors: Malik I. Al-Amayreh, Mohammad I. Kilani, Ahmed S. Al-Salaymeh

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This works presents a Computational Fluid Dynamics (CFD) simulation of a butterfly valve used to control the flow of combustible gas mixture in an industrial process setting. The work uses CFD simulation to analyze the flow characteristics in the vicinity of the valve, including the velocity distributions, streamlines and path lines. Frequency spectrum of the pressure pulsations downstream the valves, and the vortex shedding allow predicting the torque fluctuations acting on the valve shaft and the possibility of generating mechanical vibration and resonance. These fluctuations are due to aerodynamic torque resulting from fluid turbulence and vortex shedding in the valve vicinity. The valve analyzed is located in a pipeline between two opposing 90o elbows, which exposes the valve and the surrounding structure to the turbulence generated upstream and downstream the elbows at either end of the pipe. CFD simulations show that the best location for the valve from a vibration point of view is in the middle of the pipe joining the elbows.

Keywords: butterfly valve vibration analysis, computational fluid dynamics, fluid flow circuit design, fluctuation

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Authors: Pepur Sandra, Bulog Ivana, Rimac Smiljanić Ana

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During the COVID-19 pandemic, stress and family financial fragility arose worldwide. Economic and health uncertainty created new pressure on the everyday life of families. The work from home, homeschooling, and care of other family members caused an increase in unpaid work and generated a new division of intrahousehold. As many times before, women have taken the higher burden. This paper analyzes family stress and finance during the COVID-19 pandemic. We propose that women's inclusion in paid and unpaid work and their financial literacy influence family finances. We build up our assumptions according to the two theories that explain intrahousehold family decision-making: traditional and barging models. The traditional model assumes that partners specialize in their roles in line with time availability. Consequently, partners less engaged in payable working activities will spend more time on domestic activities and vice versa. According to the bargaining model, each individual has their preferences, and the one with more household bargaining power, e.g., higher income, higher level of education, better employment, or higher financial knowledge, is likely to make family decisions and avoid unpaid work. Our results are based on an anonymous and voluntary survey of 869 valid responses from women older than 18 conducted in Croatia at the beginning of 2021. We found that families who experienced delays in settling current obligations before the pandemic were in a worse financial situation during the pandemic. However, all families reported problems settling current obligations during pandemic times regardless of their financial condition before the crisis. Women from families with financial issues reported higher levels of family and personal stress during the pandemic. Furthermore, we provide evidence that more women's unpaid work negatively affects the family's financial fragility during the pandemic. In addition, in families where women have better financial literacy and are more financially independent, families cope better with finance before and during pandemics.

Keywords: family financial fragility, stress, unpaid work, women's financial literacy

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Authors: Amani Amamou, Sabra Habli, Nejla Mahjoub Saïd, Georges Le Palec

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Round jets have been widely studied due to their important application in industry. Many configurations of round jet were encountered in literature as free jet, co-flow jet, couterflowing jet and cross flow jet. In this paper, we are concerned with turbulent round jet in uniform counterflow stream which is known to enhance mixing and dispersion efficiency owing to flow reversal. This type of flow configuration is a typical application in environmental engineering such as the disposal of wastewater into seas or rivers. A computational study of a turbulent circular jet discharging into a uniform counterflow is conducted in order to investigate the characteristics of the diffusion field of the jet effluent. The investigation is carried out for three different cases of jet-to-current velocity ratios; low, medium and high velocity ratios. The Reynolds Stress Model (RSM) is used in the comparison with available experimental measurements. The decay of the center line velocity and the dynamic proprieties of the flow together with the centerline dilution of the passive scalar and the other characteristics of the concentration field are computationally analyzed in this paper.

Keywords: Counterflow stream, jet, velocity, concentration

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Authors: Yao Jie, Yeo Khoon Seng

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In recent decades, flapping wing aerodynamics has attracted great interest. Understanding the physics of biological flyers such as birds and insects can help improve the performance of micro air vehicles. The present research focuses on the aerodynamics of insect-like flapping wing flight with the approach of numerical computation. Insect model of hawkmoth is adopted in the numerical study with rigid wing assumption currently. The numerical model integrates the computational fluid dynamics of the flow and active control of wing kinematics to achieve stable flight. The computation grid is a hybrid consisting of background Cartesian nodes and clouds of mesh-free grids around immersed boundaries. The generalized finite difference method is used in conjunction with single value decomposition (SVD-GFD) in computational fluid dynamics solver to study the dynamics of a free hovering hummingbird hawkmoth. The longitudinal dynamics of the hovering flight is governed by three control parameters, i.e., wing plane angle, mean positional angle and wing beating frequency. In present work, a PID controller works out the appropriate control parameters with the insect motion as input. The controller is adjusted to acquire desired maneuvering of the insect flight. The numerical scheme in present study is proven to be accurate and stable to simulate the flight of the hummingbird hawkmoth, which has relatively high Reynolds number. The PID controller is responsive to provide feedback to the wing kinematics during the hovering flight. The simulated hovering flight agrees well with the real insect flight. The present numerical study offers a promising route to investigate the free flight aerodynamics of insects, which could overcome some of the limitations of experiments.

Keywords: aerodynamics, flight control, computational fluid dynamics (CFD), flapping-wing flight

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Authors: Derick M. Rakgoale, Topside E. Mathonsi, Vusumuzi Malele

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Cloud computing offers distributed online and on-demand computational services from anywhere in the world. Cloud computing services have grown immensely over the past years, especially in the past year due to the Coronavirus pandemic. Cloud computing has changed the working environment and introduced work from work phenomenon, which enabled the adoption of technologies to fulfill the new workings, including cloud services offerings. The increased cloud computing adoption has come with new challenges regarding data privacy and its integrity in the cloud environment. Previously advanced encryption algorithms failed to reduce the memory space required for cloud computing performance, thus increasing the computational cost. This paper reviews the existing encryption algorithms used in cloud computing. In the future, artificial neural networks (ANN) algorithm design will be presented as a security solution to ensure data integrity, confidentiality, privacy, and availability of user data in cloud computing. Moreover, MATLAB will be used to evaluate the proposed solution, and simulation results will be presented.

Keywords: cloud computing, data integrity, confidentiality, privacy, availability

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Authors: Varun Dongre, Stefan Pirker, Stefan Heinrich

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Over the last decades, the numerical modelling of fluidized bed processes has become feasible even for industrial processes. Commonly, continuous two-fluid models are applied to describe large-scale fluidization. In order to allow for coarse grids novel two-fluid models account for unresolved sub-grid heterogeneities. However, computational efforts remain high – in the order of several hours of compute-time for a few seconds of real-time – thus preventing the representation of long-term phenomena such as heating or particle conversion processes. In order to overcome this limitation, data-based recurrence computational fluid dynamics (rCFD) has been put forward in recent years. rCFD can be regarded as a data-based method that relies on the numerical predictions of a conventional short-term simulation. This data is stored in a database and then used by rCFD to efficiently time-extrapolate the flow behavior in high spatial resolution. This study will compare the numerical predictions of rCFD simulations with those of corresponding full CFD reference simulations for lab-scale and pilot-scale fluidized beds. In assessing the predictive capabilities of rCFD simulations, we focus on solid mixing and secondary gas holdup. We observed that predictions made by rCFD simulations are highly sensitive to numerical parameters such as diffusivity associated with face swaps. We achieved a computational speed-up of four orders of magnitude (10,000 time faster than classical TFM simulation) eventually allowing for real-time simulations of fluidized beds. In the next step, we apply the checkerboarding technique by introducing gas tracers subjected to convection and diffusion. We then analyze the concentration profiles by observing mixing, transport of gas tracers, insights about the convective and diffusive pattern of the gas tracers, and further towards heat and mass transfer methods. Finally, we run rCFD simulations and calibrate them with numerical and physical parameters compared with convectional Two-fluid model (full CFD) simulation. As a result, this study gives a clear indication of the applicability, predictive capabilities, and existing limitations of rCFD in the realm of fluidization modelling.

Keywords: multiphase flow, recurrence CFD, two-fluid model, industrial processes

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Authors: Amir Reza Heydari, Yaser Jenab

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Coronary artery disease, a common cardiovascular disease, is attributed to the accumulation of cholesterol-based plaques in the coronary arteries, leading to atherosclerosis. This disease is associated with risk factors such as smoking, hypertension, diabetes, and elevated cholesterol levels, contributing to severe clinical consequences, including acute coronary syndromes and myocardial infarction. Treatment approaches such as from lifestyle interventions to surgical procedures like percutaneous coronary intervention and coronary artery bypass surgery. These interventions often employ stents, including bare-metal stents (BMS), drug-eluting stents (DES), and bioresorbable vascular scaffolds (BVS), each with its advantages and limitations. Computational tools have emerged as critical in optimizing stent designs and assessing their performance. The aim of this study is to provide an overview of the computational methods of studies based on the finite element (FE) method in the field of coronary stenting and discuss the potential for development and clinical application of stent devices. Additionally, the importance of assessing the ability of computational models is emphasized to represent real-world phenomena, supported by recent guidelines from the American Society of Mechanical Engineers (ASME). Validation processes proposed include comparing model performance with in vivo, ex-vivo, or in vitro data, alongside uncertainty quantification and sensitivity analysis. These methods can enhance the credibility and reliability of in silico simulations, ultimately aiding in the assessment of coronary stent designs in various clinical contexts.

Keywords: atherosclerosis, materials, restenosis, review, validation

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Authors: Priya Arora, Ashutosh Mishra

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Gene identification, towards the pursuit of mutated genes, leading to Parkinson’s disease, puts forward a challenge towards proactive cure of the disorder itself. Computational analysis is an effective technique for exploring genes in the form of protein sequences, as the theoretical and manual analysis is infeasible. The limitations and effectiveness of a particular computational method are entirely dependent on the previous data that is available for disease identification. The article presents a sequence-based classification method for the identification of genes responsible for Parkinson’s disease. During the initiation phase, the physicochemical properties of amino acids transform protein sequences into a feature vector. The second phase of the method employs Jaccard distances to select negative genes from the candidate population. The third phase involves artificial neural networks for making final predictions. The proposed approach is compared with the state of art methods on the basis of F-measure. The results confirm and estimate the efficiency of the method.

Keywords: disease gene identification, Parkinson’s disease, physicochemical properties of amino acid, protein sequences

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Authors: Edwin Cartledge, Jack Clark, Mazaher Molaei-Chalchooghi

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The mixing in the crystallization step of active pharmaceutical ingredient manufacturers was studied via advanced modeling tools to enable a successful scale-up. A virtual representation of the vessel was created, and computational fluid dynamics were used to simulate multiphase flow and, thus, the mixing environment within this vessel. The study identified a significant dead zone in the vessel underneath the impeller and found that increasing the impeller speed and power did not improve the mixing. A series of sensitivity analyses found that to improve mixing, the vessel had to be redesigned, and found that optimal mixing could be obtained by adding two extra cylindrical baffles. The same two baffles from the simulated environment were then constructed and added to the process vessel. By identifying these potential issues before starting the manufacture and modifying the vessel to ensure good mixing, this study mitigated a failed crystallization and potential batch disposal, which could have resulted in a significant loss of high-value material.

Keywords: active pharmaceutical ingredient, baffles, computational fluid dynamics, mixing, modelling

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Authors: R. C. Tyagi

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Quasi-periodicity of frequency intervals observed in Shruti based Absolute Scale of Music has been used to graphically identify the Anchor notes ‘Vadi’ and ‘Samvadi’ which are nodal points for expansion, elaboration and iteration of the emotional theme represented by the characteristic tonic arrangement in Raga compositions. This analysis leads to defining the Tonic parameters in the octave including the key-note frequency, tonic intervals’ anchor notes and the on-set and range of quasi-periodicities as exponents of 2. Such uniformity of representation of characteristic data would facilitate computational analysis and synthesis of music compositions and also help develop noise suppression techniques. Criteria for tuning of strings for compatibility with placement of frets on finger boards is discussed. Natural Rhythmic cycles in music compositions are analytically shown to lie between 3 and 126 beats.

Keywords: absolute scale, anchor notes, computational analysis, frets, innovation, noise suppression, Quasi-periodicity, rhythmic cycle, tonic interval, Shruti

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Authors: Arya Pirooz

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The effects of different fuels (DME, RME B100, and SME B100) on barrel engines were studied as a general, single dimensional investigation for characterization of these types of engines. A base computational model was created as reference point to be used as a point of comparison with different cases. The models were computed using the commercial computational fluid dynamics program, Diesel-RK. The base model was created using basic dimensions of the PAMAR-3 engine with inline unit injectors. Four fuel cases were considered. Optimized models were also considered for diesel and DME cases with respect to injection duration, fuel, injection timing, exhaust and intake port opening, CR, angular offset. These factors were optimized for highest BMEP, combined PM and NOx emissions, and highest SFC. Results included mechanical efficiency (eta_m), efficiency and power, emission characteristics, combustion characteristics. DME proved to have the highest performing characteristics in relation to diesel and RME fuels for this type of barrel engine.

Keywords: DME, RME, Diesel-RK, characterization, inline unit injector

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Authors: Boris Melnikov, Ye Zhang, Dmitrii Chaikovskii

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We continue to consider one of the cybernetic methods in computational biology related to the study of DNA chains. Namely, we are considering the problem of reconstructing the not fully filled distance matrix of DNA chains. When applied in a programming context, it is revealed that with a modern computer of average capabilities, creating even a small-sized distance matrix for mitochondrial DNA sequences is quite time-consuming with standard algorithms. As the size of the matrix grows larger, the computational effort required increases significantly, potentially spanning several weeks to months of non-stop computer processing. Hence, calculating the distance matrix on conventional computers is hardly feasible, and supercomputers are usually not available. Therefore, we started publishing our variants of the algorithms for calculating the distance between two DNA chains; then, we published algorithms for restoring partially filled matrices, i.e., the inverse problem of matrix processing. In this paper, we propose an algorithm for restoring the distance matrix for DNA chains, and the primary focus is on enhancing the algorithms that shape the greedy function within the branches and boundaries method framework.

Keywords: DNA chains, distance matrix, optimization problem, restoring algorithm, greedy algorithm, heuristics

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Authors: Anirudh Lahiri

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Neuromorphic computing, inspired by the intricate operations of biological neural networks, offers a revolutionary approach to overcoming the limitations of traditional computing architectures. This research proposes the integration of spintronics with neuromorphic systems, aiming to enhance computational performance, scalability, and energy efficiency. Traditional computing systems, based on the Von Neumann architecture, struggle with scalability and efficiency due to the segregation of memory and processing functions. In contrast, the human brain exemplifies high efficiency and adaptability, processing vast amounts of information with minimal energy consumption. This project explores the use of spintronics, which utilizes the electron's spin rather than its charge, to create more energy-efficient computing systems. Spintronic devices, such as magnetic tunnel junctions (MTJs) manipulated through spin-transfer torque (STT) and spin-orbit torque (SOT), offer a promising pathway to reducing power consumption and enhancing the speed of data processing. The integration of these devices within a neuromorphic framework aims to replicate the efficiency and adaptability of biological systems. The research is structured into three phases: an exhaustive literature review to build a theoretical foundation, laboratory experiments to test and optimize the theoretical models, and iterative refinements based on experimental results to finalize the system. The initial phase focuses on understanding the current state of neuromorphic and spintronic technologies. The second phase involves practical experimentation with spintronic devices and the development of neuromorphic systems that mimic synaptic plasticity and other biological processes. The final phase focuses on refining the systems based on feedback from the testing phase and preparing the findings for publication. The expected contributions of this research are twofold. Firstly, it aims to significantly reduce the energy consumption of computational systems while maintaining or increasing processing speed, addressing a critical need in the field of computing. Secondly, it seeks to enhance the learning capabilities of neuromorphic systems, allowing them to adapt more dynamically to changing environmental inputs, thus better mimicking the human brain's functionality. The integration of spintronics with neuromorphic computing could revolutionize how computational systems are designed, making them more efficient, faster, and more adaptable. This research aligns with the ongoing pursuit of energy-efficient and scalable computing solutions, marking a significant step forward in the field of computational technology.

Keywords: material science, biological engineering, mechanical engineering, neuromorphic computing, spintronics, energy efficiency, computational scalability, synaptic plasticity.

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Authors: Ahmed E. Hodaib, Mohamed A. Hashem

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In engineering applications, a design has to be as fully perfect as possible in some defined case. The designer has to overcome many challenges in order to reach the optimal solution to a specific problem. This process is called optimization. Generally, there is always a function called “objective function” that is required to be maximized or minimized by choosing input parameters called “degrees of freedom” within an allowed domain called “search space” and computing the values of the objective function for these input values. It becomes more complex when we have more than one objective for our design. As an example for Multi-Objective Optimization Problem (MOP): A structural design that aims to minimize weight and maximize strength. In such case, the Pareto Optimal Frontier (POF) is used, which is a curve plotting two objective functions for the best cases. At this point, a designer should make a decision to choose the point on the curve. Engineers use algorithms or iterative methods for optimization. In this paper, we will discuss the Evolutionary Algorithms (EA) which are widely used with Multi-objective Optimization Problems due to their robustness, simplicity, suitability to be coupled and to be parallelized. Evolutionary algorithms are developed to guarantee the convergence to an optimal solution. An EA uses mechanisms inspired by Darwinian evolution principles. Technically, they belong to the family of trial and error problem solvers and can be considered global optimization methods with a stochastic optimization character. The optimization is initialized by picking random solutions from the search space and then the solution progresses towards the optimal point by using operators such as Selection, Combination, Cross-over and/or Mutation. These operators are applied to the old solutions “parents” so that new sets of design variables called “children” appear. The process is repeated until the optimal solution to the problem is reached. Reliable and robust computational fluid dynamics solvers are nowadays commonly utilized in the design and analyses of various engineering systems, such as aircraft, turbo-machinery, and auto-motives. Coupling of Computational Fluid Dynamics “CFD” and Multi-Objective Evolutionary Algorithms “MOEA” has become substantial in aerospace engineering applications, such as in aerodynamic shape optimization and advanced turbo-machinery design.

Keywords: mathematical optimization, multi-objective evolutionary algorithms "MOEA", computational fluid dynamics "CFD", aerodynamic shape optimization

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Authors: Gururaj Bhajantri

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Financial sector is the backbone of any economy and it plays a crucial role in the mobilisation and allocation of resources. One of the main objectives of financial sector is inclusive growth. The constituents of the financial sector are banks, and financial Institutions, which mobilise the resources from the surplus sector and channelize the same to the different needful sectors in the economy. Micro Small and the Medium Enterprises sector in India cover a wide range of economic activities. These enterprises are divided on the basis of investment on equipment. The micro enterprises are divided into manufacturing and services sector. Micro Service enterprises have investment limit up to ten lakhs on equipment. Hairdresser is one who not only cuts and shaves but also provides different types of hair cut, hairstyles, trimming, hair-dye, massage, manicure, pedicure, nail services, colouring, facial, makeup application, waxing, tanning and other beauty treatments etc., hairdressing salons provide these services with the help of equipment. They need investment on equipment not more than ten lakhs. Hence, they can be considered as Micro service enterprises. Hairdressing salons require more than Rs 2.50,000 to start a moderate salon. Moreover, hairdressers are unable to access the organised finance. Still these individuals access finance from money lenders with high rate of interest to lead life. The socio economic conditions of hairdressers are not known properly. Hence, the present study brings a light on the role of financial institutions in promoting hairdressing salons. The study also focuses the socio-economic background of individuals in hairdressings salons, problems faced by them. The present study is based on primary and secondary data. Primary data collected among hairdressing salons in Davangere city. Samples selected with the help of simple random sampling techniques. Collected data analysed and interpreted with the help of simple statistical tools.

Keywords: micro service enterprises, financial institutions, hairdressing salons, financial sector

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Authors: Zeinab Gharibi, B. Stoevesandt, J. Peinke

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Long term surface erosion of wind turbine blades, especially at the leading edge, impairs aerodynamic performance; therefore, lowers efficiency of the blades mostly in the high-speed rotor tip regions. Blade protection provides significant improvements in annual energy production, reduces costly downtime, and protects the integrity of the blades. However, this protection still influences the aerodynamic behavior, and broadband noise caused by interaction between the impinging turbulence and blade’s leading edge. This paper presents an extensive numerical aeroacoustics approach by investigating the sound power spectra of the eroded and coated NACA 64-618 wind turbine airfoil and evaluates aeroacoustics improvements after the protection procedure. Using computational fluid dynamics (CFD), different quasi 2D numerical grids were implemented and special attention was paid to the refinement of the boundary layers. The noise sources were captured and decoupled with acoustic propagation via the derived formulation of Curle’s analogy implemented in OpenFOAM. Therefore, the noise spectra were compared for clean, coated and eroded profiles in the range of chord-based Reynolds number (1.6e6 ≤ Re ≤ 11.5e6). Angle of attack was zero in all cases. Verifications were conducted for the clean profile using available experimental data. Sensitivity studies for the far-field were done on different observational positions. Furthermore, beamforming studies were done simulating an Archimedean spiral microphone array for far-field noise directivity patterns. Comparing the noise spectra of the coated and eroded geometries, results show that, coating clearly improves aerodynamic and acoustic performance of the eroded airfoil.

Keywords: computational fluid dynamics, computational aeroacoustics, leading edge, OpenFOAM

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Authors: Erika Takidah, Salina Kassim

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Digital transformation has accelerated in the new millennium. It is reshaping the financial services industry from a traditional system to financial technology. Moreover, the number of financial inclusion rates in Indonesia is less than 60%. An innovative model needed to elucidate this national problem. On the other hand, the Islamic financial service industry and financial technology grow fast as a new aspire in economic development. An Islamic bank, takaful, Islamic microfinance, Islamic financial technology and Islamic social finance institution could collaborate to intensify the financial inclusion number in Indonesia. The primary motive of this paper is to examine the strategy of collaboration-based Islamic financial services to enhance financial inclusion in Indonesia, particularly facing the digital era. The fundamental findings for the main problems are the foundations and key ecosystems aspect involved in the development of collaboration-based Islamic financial services. By using the Interpretive Structural Model (ISM) approach, the core problems faced in the development of the models have lacked policy instruments guarding the collaboration-based Islamic financial services with fintech work process and availability of human resources for fintech. The core strategies or foundations that are needed in the framework of collaboration-based Islamic financial services are the ability to manage and analyze data in the big data era. For the aspects of the Ecosystem or actors involved in the development of this model, the important actor is government or regulator, educational institutions, and also existing industries (Islamic financial services). The outcome of the study designates that strategy collaboration of Islamic financial services institution supported by robust technology, a legal and regulatory commitment of the regulators and policymakers of the Islamic financial institutions, extensive public awareness of financial inclusion in Indonesia. The study limited itself to realize financial inclusion, particularly in Islamic finance development in Indonesia. The study will have an inference for the concerned professional bodies, regulators, policymakers, stakeholders, and practitioners of Islamic financial service institutions.

Keywords: collaboration, financial inclusion, Islamic financial services, Islamic fintech

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Authors: Liu Ying-jie, Lu Wen-bo, Peng Cheng-jian

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With the development of the automotive technology and electric vehicle, the contribution of the wind noise on the interior noise becomes the main source of noise. The main transfer path which the exterior excitation is transmitted through is the greenhouse panels and side windows. Simulating the wind noise transmitted into the vehicle accurately in the early development stage can be very challenging. The basic methodologies of this study were based on the Lighthill analogy; the exterior flow field around a passenger car was computed using unsteady Computational Fluid Dynamics (CFD) firstly and then a Finite Element Method (FEM) was used to compute the interior acoustic response. The major findings of this study include: 1) The Sound Pressure Level (SPL) response at driver’s ear locations is mainly induced by the turbulence pressure fluctuation; 2) Peaks were found over the full frequency range. It is found that the methodology used in this study could predict the interior wind noise induced by the exterior aerodynamic excitation in industry.

Keywords: wind noise, computational fluid dynamics, finite element method, passenger car

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Authors: Pragathi Gurumurthy, Christina Hagen, Patricia Ulloa, Martin A. Koch, Thorsten M. Buzug

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Obstructive sleep apnea (OSA) is a sleep disorder where the patient suffers a disturbed airflow during sleep due to partial or complete occlusion of the pharyngeal airway. Recently, numerical simulations have been used to better understand the mechanism of pharyngeal collapse. However, to gain confidence in the solutions so obtained, an experimental validation is required. Therefore, in this study an experimental validation of computational fluid dynamics (CFD) used for the study of human pharyngeal flow patterns during OSA is performed. A stationary incompressible Navier-Stokes equation solved using the finite element method was used to numerically study the flow patterns in a computed tomography-based human pharynx model. The inlet flow rate was set to 250 ml/s and such that a flat profile was maintained at the inlet. The outlet pressure was set to 0 Pa. The experimental technique used for the validation of CFD of fluid flow patterns is phase contrast-MRI (PC-MRI). Using the same computed tomography data of the human pharynx as in the simulations, a phantom for the experiment was 3 D printed. Glycerol (55.27% weight) in water was used as a test fluid at 25°C. Inflow conditions similar to the CFD study were simulated using an MRI compatible flow pump (CardioFlow-5000MR, Shelley Medical Imaging Technologies). The entire experiment was done on a 3 T MR system (Ingenia, Philips) with 108 channel body coil using an RF-spoiled, gradient echo sequence. A comparison of the axial velocity obtained in the pharynx from the numerical simulations and PC-MRI shows good agreement. The region of jet impingement and recirculation also coincide, therefore validating the numerical simulations. Hence, the experimental validation proves the reliability and correctness of the numerical simulations.

Keywords: computational fluid dynamics, experimental validation, phase contrast-MRI, obstructive sleep apnea

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Authors: Konrad Pietrykowski, Michal Bialy, Pawel Karpinski, Radoslaw Maczka

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The nozzle is an element of the rocket engine in which the conversion of the potential energy of gases generated during combustion into the kinetic energy of the gas stream takes place. The design parameters of the nozzle have a decisive influence on the ballistic characteristics of the engine. Designing a nozzle assembly is, therefore, one of the most responsible stages in developing a rocket engine design. The paper presents the results of the simulation of three types of rocket propulsion nozzles. Calculations were made using CFD (Computational Fluid Dynamics) in ANSYS Fluent software. The next types of nozzles differ in shape. The analysis was made of a conical nozzle, a bell type nozzle with a conical supersonic part and a bell type nozzle. Calculation results are presented in the form of pressure, velocity and kinetic energy distributions of turbulence in the longitudinal section. The courses of these values along the nozzles are also presented. The results show that the cone nozzle generates strong turbulence in the critical section. Which negatively affect the flow of the working medium. In the case of a bell nozzle, the transformation of the wall caused the elimination of flow disturbances in the critical section. This reduces the probability of waves forming before or after the trailing edge. The most sophisticated construction is the bell type nozzle. It allows you to maximize performance without adding extra weight. The bell type nozzle can be used as a starter and auxiliary engine nozzle due to its advantages. The project/research was financed in the framework of the project Lublin University of Technology-Regional Excellence Initiative, funded by the Polish Ministry of Science and Higher Education (contract no. 030/RID/2018/19).

Keywords: computational fluid dynamics, nozzle, rocket engine, supersonic flow

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Authors: Amir Reza Radmanesh, Sina Farajzadeh Khosroshahi, Hani Sadr

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The transient catalytic converter performance is governed by complex interactions between exhaust gas flow and the monolithic structure of the catalytic converter. Stringent emission regulations around the world necessitate the use of highly-efficient catalytic converters in vehicle exhaust systems. Computational fluid dynamics (CFD) is a powerful tool for calculating the flow field inside the catalytic converter. Radial velocity profiles, obtained by a commercial CFD code, present very good agreement with respective experimental results published in the literature. However the applicability of CFD for transient simulations is limited by the high CPU demands. In the present work, Geometric modeling ceramic monolith substrate is done with square shaped channel type of Catalytic converter and it is coated platinum and palladium. This example illustrates the effect of flow distribution on thermal response of a catalytic converter and different gas flow velocities, during the critical phase of catalytic converter warm up.

Keywords: catalytic converter, computational fluid dynamic, porous media, velocity distribution

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Authors: Dchieche Amina, Aboulaich Rajae

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Profit and loss sharing suggests an equitable sharing of risks and profits between the parts involved in a financial transaction. Salam is a contract in which advance payment is made for goods to be delivered at a future date. The purpose of this work is to price a new contract for profit and loss sharing based on Salam contract, using Khiyar Al Ghabn which is an agreement of choice in case of misrepresent facts.

Keywords: Islamic finance, shariah compliance, profit and loss sharing, derivatives, risks, hedging, salam contract

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Authors: S. L. Tulasi Devi, Shivam Azad

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The primary objective of this study is to analyze the impact of green bond issuance on the stock prices of respective Indian companies. An event study methodology has been employed to study the effect of green bond issuance. For in-depth study and analysis, this paper used different window frames, including 15-15 days, 10-10 days, 7-7days, 6-6 days, and 5-5 days. Further, for better clarity, this paper also used an uneven window period of 7-5 days. The period of study covered all the companies which issued green bonds during the period of 2017-2022; Adani Green Energy, State Bank of India, Power Finance Corporation, Jain Irrigation, and Rural Electrification Corporation, except Indian Renewable Energy Development Agency and Indian Railway Finance Corporation, because of data unavailability. The paper used all three event study methods as discussed in earlier literature; 1) constant return model, 2) market-adjusted model, and 3) capital asset pricing model. For the fruitful comparison between results, the study considered cumulative average return (CAR) and buy and hold average return (BHAR) methodology. For checking the statistical significance, a two-tailed t-statistic has been used. All the statistical calculations have been performed in Microsoft Excel 2016. The study found that all other companies have shown positive returns on the event day except for the State Bank of India. The results demonstrated that constant return model outperformed compared to the market-adjusted model and CAPM. The p-value derived from all the methods has shown an almost insignificant impact of the issuance of green bonds on the stock prices of respective companies. The overall analysis states that there’s not much improvement in the market efficiency of the Indian Stock Markets.

Keywords: green bonds, event study methodology, constant return model, market-adjusted model, CAPM

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Authors: Seul-Ki Park, Jong-Chun Park, Gyu-Mok Jeon, Dae-Kyung Ock, Seung-Gyu Jeong

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Rogue waves cause frequent accidents of ships and offshore structures, which can result in severe damage to the structures. The Rogue waves, which are also known as big waves, freak waves, extreme waves, monster waves, focused waves, giant waves and abnormal waves, are unexpected and suddenly appearing, and can have a breaking force to destroy the structure even though modern structures are designed to tolerate a breaking wave. In the present study, a series of focused waves are numerically reproduced by concentrating nonlinear multi-directional waves into a target point using a commercial CFD software, Star-CCM+. A flow analysis for investigating the physical characteristics of the focused waves is performed using the Star-CCM+, while it has several difficulties to examine the inner properties of the waves in existing potential theory and experiments. Additionally, the 6-DOF (Degree of Freedom) motion of a floating body interacting with the focused waves are simulated, and the dynamic response of the body are discussed.

Keywords: multidirectional waves, focused waves, rogue waves, wave-structure interaction, numerical wave tank, computational fluid dynamics

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Authors: Francesco Rizzuto, Matthew Stickland, Stephan Hannot

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The simulation of a positive displacement pump system with commercial software for Computer Fluid Dynamics (CFD), will result in an enormous computational effort due to the complexity of the pump system. This drawback restricts the use of it to a specific part of the pump in one simulation. This research focuses on developing an algorithm that provides a suitable result in agreement with experiment data, without that computational effort. The compressible equations are solved with an explicit algorithm. A comparison is presented between the FV method with Monotonic Upwind scheme for Conservative Laws (MUSCL) with slope limiter and experimental results. The source term for cavitation and friction is introduced into the algorithm with a slipping strategy and solved with a 4th order Runge-Kutta scheme (RK4). Different pumps are modeled and analyzed to evaluate the flexibility of the code. The simulation required minimal computation time and resources without compromising the accuracy of the simulation results. Therefore, this algorithm highlights the feasibility of pressure pulsation simulation as a design tool for an industrial purpose.

Keywords: cavitation, diaphragm, DVCM, finite volume, MUSCL, positive displacement pump

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Authors: Thiyam Tamphasana Devi, Bimlesh Kumar

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A Computational Fluid Dynamics (CFD) technique has been applied to simulate the gas-liquid phase in double stirred tank of Rushton impeller. Eulerian-Eulerian model was adopted to simulate the multiphase with standard correlation of Schiller and Naumann for drag co-efficient. The turbulence was modeled by using standard k-ε turbulence model. The present CFD model predicts flow pattern, local gas hold-up, and local specific area. It also predicts local kLa (mass transfer rate) for single impeller. The predicted results were compared with experimental and CFD results of published literature. The predicted results are slightly over predicted with the experimental results; however, it is in reasonable agreement with other simulated results of published literature.

Keywords: Eulerian-Eulerian, gas-hold up, gas-liquid phase, local mass transfer rate, local specific area, Rushton Impeller

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Authors: Javed Mohammed

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Right now, bio-medical infrastructure lags well behind the curve. Our healthcare system is dispersed and disjointed; medical records are a bit of a mess; and we do not yet have the capacity to store and process the crazy amounts of data coming our way from widespread whole-genome sequencing. And then there are privacy issues. Despite these infrastructure challenges, some researchers are plunging into bio medical Big Data now, in hopes of extracting new and actionable knowledge. They are doing delving into molecular-level data to discover bio markers that help classify patients based on their response to existing treatments; and pushing their results out to physicians in novel and creative ways. Computer scientists and bio medical researchers are able to transform data into models and simulations that will enable scientists for the first time to gain a profound under-standing of the deepest biological functions. Solving biological problems may require High-Performance Computing HPC due either to the massive parallel computation required to solve a particular problem or to algorithmic complexity that may range from difficult to intractable. Many problems involve seemingly well-behaved polynomial time algorithms (such as all-to-all comparisons) but have massive computational requirements due to the large data sets that must be analyzed. High-throughput techniques for DNA sequencing and analysis of gene expression have led to exponential growth in the amount of publicly available genomic data. With the increased availability of genomic data traditional database approaches are no longer sufficient for rapidly performing life science queries involving the fusion of data types. Computing systems are now so powerful it is possible for researchers to consider modeling the folding of a protein or even the simulation of an entire human body. This research paper emphasizes the computational biology's growing need for high-performance computing and Big Data. It illustrates this article’s indispensability in meeting the scientific and engineering challenges of the twenty-first century, and how Protein Folding (the structure and function of proteins) and Phylogeny Reconstruction (evolutionary history of a group of genes) can use HPC that provides sufficient capability for evaluating or solving more limited but meaningful instances. This article also indicates solutions to optimization problems, and benefits Big Data and Computational Biology. The article illustrates the Current State-of-the-Art and Future-Generation Biology of HPC Computing with Big Data.

Keywords: high performance, big data, parallel computation, molecular data, computational biology

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Authors: Farshad Ghodoosi

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This article analyzes the effect of supervening events in contracts. Contracts serve an important function: allocation of risks. In spite of its importance, the case law and the doctrine are messy and inconsistent. This article provides a fresh look at excuse doctrines (i.e., force majeure, impracticability, impossibility, and frustration) with a focus on force majeure clauses. The article makes the following contributions: First, it furnishes a new conceptual and theoretical framework of excuse doctrines. By distilling the decisions, it shows that excuse doctrines rests on the triangle of control, foreseeability, and contract language. Second, it analyzes force majeure clauses used by S&P 500 companies to understand the stickiness and similarity of such clauses and the events they cover. Third, using computational and statistical tools, it analyzes US cases since 1810 in order to assess the weight given to the triangle of control, foreseeability, and contract language. It shows that the control factor plays an important role in force majeure analysis, while the contractual interpretation is the least important factor. The Article concludes that it is the standard for control -whether the supervening event is beyond the control of the party- that determines the outcome of cases in the force majeure context and not necessarily the contractual language. This article has important implications on COVID-19-related contractual cases. Unlike the prevailing narrative that it is the language of the force majeure clause that’s determinative, this article shows that the primarily focus of the inquiry will be on whether the effects of COVID-19 have been beyond the control of the promisee. Normatively, the Article suggests that the trifactor of control, foreseeability, and contractual language are not effective for allocation of legal risks in times of crises. It puts forward a novel approach to force majeure clauses whereby that the courts should instead focus on the degree to which parties have relied on (expected) performance, in particular during the time of crisis.

Keywords: contractual risks, force majeure clauses, foreseeability, control, contractual language, computational analysis

Procedia PDF Downloads 144