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Discussion of Simplified Evaluation Methods of Peak Wind Force Coefficients for Designing Cladding/Components of Domed Free Roofs

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Journal of Wind Engineering 2024年第4期49卷 1-10页

作者： Ding, Wei Uematsu, Yasushi National Institute of Technology Akita College Japan New Industry Creation Hatchery Center Tohoku University Japan

The present paper investigates the simplified evaluation methods of positive and negative peak wind force coefficients, Ĉf and Čf, for designing the cladding/components of domed free roofs based on a wind tunnel experiment, in which peak factor method and quasi-steady approach are employed. Focus is on the distribution of wind force coefficients along the centerline parallel to the wind direction. Empirical formulas are provided for the distributions of the mean wind force coefficient C-f, RMS fluctuating wind force coefficient C'f and peak factors, g+f and g-f, for evaluating Ĉf and Čf, as a function of the rise/span ratio f/D of the roof and the turbulence intensities, IuH and IwH, in the along-wind and vertical directions of approach flow at the mean roof height H. The formulas are validated by the experimental results. © 2024 Japan Association for Wind Engineering. All rights reserved.

关键词： computational fluid dynamics

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RESPONSE OF HIGH-RISE BUILDINGS CALCULATED FROM TIME HISTORY ANALYSIS USING WIND FORCE EVALUATED FROM CFD

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AIJ Journal of Technology and Design 2024年第76期30卷 1205-1210页

作者： Okimura, Masahiro Tanaka, Hideyuki Watai, Kazuki Konno, Daisuke Sato, Daiki Sone, Takayuki Azegami, Yasuhiko School of Environment and Society Tokyo Institute of Technology Japan Tokyo Institute of Technology Japan Research & Development Institute Takenaka Corporation Japan Research & Development Institute Takenaka Corporation Japan

Wind forces acting on high-rise buildings are usually evaluated from wind tunnel tests. With recent improvements in computational capabilities, wind forces can also be evaluated from computational fluid dynamics (CFD). In this report, the response of high-rise buildings calculated by time history analysis using wind force from CFD is compared with the response calculated by time history analysis using wind force from wind tunnel tests and the response that can be calculated from the load guideline. The results show the usefulness of using CFD to evaluate wind forces acting on high-rise buildings. © 2024 Architectural Institute of Japan. All rights reserved.

关键词： computational fluid dynamics

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Design of rotation inducing rocket fins and their analysis for aerodynamic stability

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Aerospace Systems 2024年第4期7卷 721-726页

作者： Karlekar, Chinmay Barve, Shivprakash B. Department of Mechanical Engineering Dr. Vishwanath Karad MIT World Peace University Maharashtra Pune411038 India

The stability of a rocket during flight is the one of the most crucial factors from the perspective of a design engineer. Without stability, a rocket is equivalent to an uncontrolled and unpredictable, high-speed projectile. Passive control can stabilize flight in one of two ways: by shifting the center of pressure (CP) behind the center of gravity (CG);or by producing a spin along the axis of flight. This study aims to induce this spin or rotation through the design of fins. This study is a synergistic application of few of the many engineering practices and processes. It has generated airfoil profiles for rotation inducing fins using NACA database;developed a software model using SolidWorks to run analysis using commercial FEA, CFD and stability analysis software;and additively manufactured a prototype model for experimental testing in a subsonic wind tunnel. Pressure, which is responsible for spin, was measured experimentally at different locations across the length of the model and was found to have comparable values as those obtained for CFD study. The experiment also displayed a longitudinally stable spin of the model. © Shanghai Jiao Tong University 2024.

关键词： computational fluid dynamics

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Visualisation of Droplet Flow Induced by Ultrasonic Dental Cleaning

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INTERNATIONAL DENTAL JOURNAL 2024年第4期74卷 876-883页

作者： Shu, Haiyin Yu, Xiaoyan Zhu, Xiankun Zhang, Fan He, Junjie Duan, Xubo Liu, Mingkun Li, Jiachun Yang, Wei Zhao, Jin Guizhou Univ Med Coll Xiahui Rd Guiyang 550025 Guizhou Peoples R China Guiyang Hosp Stomatol Guiyang Guizhou Peoples R China Guizhou Univ Sch Mech Engn Jiaxiu South Rd Guiyang 550025 Guizhou Peoples R China

Introduction: During dental treatment procedures ultrasonic scalers generate droplets containing microorganisms such as bacteria and viruses. Hence, it is necessary to study the dynamic properties of generated droplets in order to investigate the risks associated with the spread of infection. The aim of this study was to visualise the flow state of droplets and to evaluate the impact of droplets generated during the use of an ultrasonic scaler during an oral surgical procedure. Methods: We studied the spatial flow of liquid droplets through a combination of imaging and numeric simulation of a simulated dental treatment processes. First, we photographed the real time images of the ultrasonic scaler and evaluated the images using image-processing software Image J to visualise the flow of liquid droplets. Finally we simulated the flow process of liquid droplets by using the initial velocity of droplet splashing and the angle of the obtained information using computerised fluid dynamics technology. Results: Under different working conditions, the droplet particle splashing velocity, maximum height, and spray angle varied, but the particle trajectory was generally parabolic. The maximum droplet velocity varied between 3.56 and 8.56 m/s, and the splashing height was between 40 and 110 mm. Conclusions: During risk assessment of an ultrasonic scaler usage, difficulties arise due to the insufficient research on droplet velocity and distribution. This study aims to address this gap by visualising the flow trajectories of droplets generated by ultrasonic scalers. The obtained data will assist in developing more effective interventions based on spatial and temporal distribution of droplets. This provides a new approach for droplet particle research and offers new strategies for public health prevention and control. (c) 2023 The Authors. Published by Elsevier Inc. on behalf of FDI World Dental Federation. (http://***/licenses/by-nc-nd/4.0/)

关键词： Respiratory infectious diseases Droplets Flow trajectory computational fluid dynamics

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Uncertainty Quantification for Multidimensional Correlated Flow Field Responses

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JOURNAL OF VERIFICATION, VALIDATION AND UNCERTAINTY QUANTIFICATION 2024年第2期9卷 021002页

作者： Zhao, Wei Lv, Luogeng Zhao, Jiao Xiao, Wei Chen, Jiangtao Wu, Xiaojun China Aerodynam Res & Dev Ctr Computat Aerodynam Inst Mianyang 621000 Sichuan Peoples R China China Aerodynam Res & Dev Ctr 6 South Sect Second Ring Rd Mianyang 621000 Sichuan Peoples R China

The inherent randomness of fluid dynamics problems or human cognitive limitations results in non-negligible uncertainties in computational fluid dynamics (CFD) modeling and simulation, leading to doubts about the credibility of CFD results. Therefore, scientific and rigorous quantification of these uncertainties is crucial for assessing the reliability of CFD predictions and informed engineering decisions. Although mature uncertainty propagation methods have been developed for individual output quantities, the challenges lie in the multidimensional correlated flow field variables. This article proposes an advanced uncertainty propagation modeling approach based on proper orthogonal decomposition (POD) and artificial neural networks (ANN). By projecting the multidimensional correlated responses onto an orthogonal basis function space, the dimensionality of output is significantly reduced, simplifying the subsequent model training process. An artificial neural network that maps the uncertain parameters of the CFD model to the coefficients of the basis functions are established. Due to the bidirectional representation of flow field variables and basis function coefficients through proper orthogonal decomposition, combined with artificial neural network modeling, rapid prediction of flow field variables under any model parameters is achieved. To effectively identify the most influential model parameters, we employ a multi-output global sensitivity analysis method based on covariance decomposition. Through two exemplary cases of NACA0012 airfoil and M6 wing, we demonstrate the accuracy and efficacy of our proposed approach in predicting multidimensional flow field variables under varying model coefficients. Large-scale random sampling is conducted to quantify the uncertainties and identify the key factors that significantly impact the overall flow field.

关键词： Artificial neural networks Wings computational fluid dynamics Pressure Friction Uncertainty quantification Airfoils Modeling Flow (dynamics) Principal component analysis Sensitivity analysis Uncertainty Transonic flow Simulation

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Investigating distributions of inhaled aerosols in the lungs of post-COVID-19 clusters through a unified imaging and modeling approach

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EUROPEAN JOURNAL OF PHARMACEUTICAL SCIENCES 2024年 195卷 106724页

作者： Zhang, Xuan Li, Frank Rajaraman, Prathish K. Comellas, Alejandro P. Hoffman, Eric A. Lin, Ching -Long Univ Iowa IIHR Hydrosci & Engn Iowa City IA 52242 USA Univ Iowa Dept Mech Engn Iowa City IA USA Univ Iowa Roy J Carver Dept Biomed Engn Iowa City IA USA Univ Iowa Dept Internal Med Iowa City IA USA Univ Iowa Dept Radiol Iowa City IA USA

Background: Recent studies, based on clinical data, have identified sex and age as significant factors associated with an increased risk of long COVID. These two factors align with the two post-COVID-19 clusters identified by a deep learning algorithm in computed tomography (CT) lung scans: Cluster 1 (C1), comprising predominantly females with small airway diseases, and Cluster 2 (C2), characterized by older individuals with fibrotic -like patterns. This study aims to assess the distributions of inhaled aerosols in these clusters. Methods: 140 COVID survivors examined around 112 days post -diagnosis, along with 105 uninfected, nonsmoking healthy controls, were studied. Their demographic data and CT scans at full inspiration and expiration were analyzed using a combined imaging and modeling approach. A subject -specific CT -based computational model analysis was utilized to predict airway resistance and particle deposition among C1 and C2 subjects. The cluster -specific structure and function relationships were explored. Results: In C1 subjects, distinctive features included airway narrowing, a reduced homothety ratio of daughter over parent branch diameter, and increased airway resistance. Airway resistance was concentrated in the distal region, with a higher fraction of particle deposition in the proximal airways. On the other hand, C2 subjects exhibited airway dilation, an increased homothety ratio, reduced airway resistance, and a shift of resistance concentration towards the proximal region, allowing for deeper particle penetration into the lungs. Conclusions: This study revealed unique mechanistic phenotypes of airway resistance and particle deposition in the two post-COVID-19 clusters. The implications of these findings for inhaled drug delivery effectiveness and susceptibility to air pollutants were explored.

关键词： Long COVID PASC Computed tomography Clusters computational fluid dynamics

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Projection-Based Dimensional Reduction of Adaptively Refined Nonlinear Models

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Communications on Applied Mathematics and Computation 2024年第3期6卷 1779-1800页

作者： Clayton Little Charbel Farhat Department of Mechanical Engineering Stanford UniversityStanfordUSA Department of Aeronautics and Astronautics Stanford UniversityStanfordUSA Institute for Computational and Mathematical Engineering Stanford UniversityStanfordUSA

Adaptive mesh refinement (AMR) is fairly practiced in the context of high-dimensional, mesh-based computational models. However, it is in its infancy in that of low-dimensional, generalized-coordinate-based computational models such as projection-based reduced-order models. This paper presents a complete framework for projection-based model order reduction (PMOR) of nonlinear problems in the presence of AMR that builds on elements from existing methods and augments them with critical new contributions. In particular, it proposes an analytical algorithm for computing a pseudo-meshless inner product between adapted solution snapshots for the purpose of clustering and PMOR. It exploits hyperreduction—specifically, the energy-conserving sampling and weighting hyperreduction method—to deliver for nonlinear and/or parametric problems the desired computational gains. Most importantly, the proposed framework for PMOR in the presence of AMR capitalizes on the concept of state-local reduced-order bases to make the most of the notion of a supermesh, while achieving computational tractability. Its features are illustrated with CFD applications grounded in AMR and its significance is demonstrated by the reported wall-clock speedup factors.

关键词： Adaptive mesh refinement(AMR) computational fluid dynamics Energy-conserving sampling and weighting(ECSW) Model order reduction Reduced-order model Supermesh

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Low-order modeling approach for the prediction of transverse combustion instabilities in multi-injector engines

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CEAS SPACE JOURNAL 2024年第6期16卷 635-657页

作者： Zolla, Paolo Maria Montanari, Alessandro D'Alessandro, Simone Pizzarelli, Marco Nasuti, Francesco Pellegrini, Rocco Carmine Cavallini, Enrico Sapienza Univ Rome Dept Mech & Aerosp Engn Via Eudossiana 18 I-00184 Rome Italy Italian Space Agcy ASI Via Politecn Snc I-00133 Rome Italy

This paper addresses the prediction of spontaneous self-sustained transverse combustion instabilities in multi-injector engines using a multi-dimensional non-linear low-order Eulerian model. The approach utilizes a physically aware response function that directly links pressure oscillations to fuel mass flow rate, independent of external data. This enables accurate capture of the behavior of shear coaxial injectors that have been proven to show a peculiar dynamics of cyclic fuel accumulation and release in response to acoustic waves. A NASA test case is employed as a reference, and a comprehensive analysis is conducted to investigate the behavior of the model. Firstly, a preliminary analysis is performed within a quasi-one-dimensional framework for a reduced single-injector configuration. This analysis provides insights into the influence of key parameters on the instability onset. Subsequently, the full-scale geometry is considered in a multi-dimensional framework, and the low-order solver is employed to analyze the thermo-acoustic behavior of the engine. The model successfully captures the instability dynamics, including temporal evolution, dominant frequency, and mode shapes. Sensitivity analyses are conducted to examine the impact of the model free parameters on the unstable modes. Additionally, the effect of introducing baffles as damping devices within the combustion chamber is investigated. The results highlight the model predictive capabilities and its potential for guiding the design and optimization of liquid rocket engines.

关键词： Combustion instability Liquid rocket engines computational fluid dynamics Space propulsion Aerospace engineering

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Adaptive wildfire spread prediction for complex terrain: modeling the effectiveness of sprinkler systems

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FIRE ECOLOGY 2024年第1期20卷 75页

作者： Kim, Jaekyoung Ahn, Junghyeon Kang, Junsuk Gangneung Wonju Natl Univ Dept Environm Landscape Architecture Kangnung 25457 South Korea Seoul Natl Univ Res Inst Agr & Life Sci Seoul 08826 South Korea Seoul Natl Univ Dept Civil & Environm Engn Seoul 08826 South Korea Seoul Natl Univ Dept Landscape Architecture & Rural Syst Engn Seoul 08826 South Korea

Background Because the threat of wildfires to global ecosystems and society continues to rise, this study provides an experimental simulation framework that assesses the spread and reduction of wildfires to evaluate the effectiveness of adaptation methods in reducing their impact. The process entails selecting a vulnerable wildfire area and adaptation method, then generating the computational fluid dynamics (CFD) model. Monitoring data are then used to configure the model, set boundary conditions, and simulate the fire. The effectiveness of the adaptation method in minimizing damage in the area of interest is evaluated by comparing simulations with and without the chosen adaptation method. Our focus area was a natural recreational forest in Wonju, Gangwon-do, Korea, and our adaptation method was a water sprinkler system. Results Our framework provides aims to provide an experimental means of assessing the wildfire spread path and spread area based on exogenous variables of wind speed, wind direction, relative humidity, and more. The sprinkler adaptation had a reduction effect of 20% in the wildfire spread rate for the 10-h period, which refers to the time limit of the simulation after ignition. We revealed that at higher wind speeds, the fire primarily follows the wind direction;whereas at lower wind speeds, the fire is more influenced by the topography. Additionally, 60 min after ignition, the adaptation methods can suppress wildfire spread by > 70%. Notably, sprinklers reduce smoke concentrations by up to 50% (ppm) over the affected area. Conclusions This study demonstrates the potential effectiveness of a comprehensive CFD model in mitigating wildfire spread using sprinkler systems as an experimental analysis. Key results include a 20% reduction in wildfire within 10 h of ignition, significant influence of wind speed on spread patterns, and a reduction of smoke concentrations, improving air quality. These findings highlight the potential of CFD-based frameworks t

关键词： CFD computational fluid dynamics Wildfire adaptation Sprinkler Unsteady Reynolds-averaged Navier-Stokes URANS Wildfire monitoring

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Blockage and submersion depth effects on horizontal-axis tidal turbine (HATT) in a shear flow environment with wave–current interaction

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Marine Systems and Ocean Technology 2024年第1-2期19卷 15-34页

作者： Rotor, Mark Anthony Magno, Ivy Liezel Boiser, Christie Claire Hefazi, Hamid Mechanical Engineering Department State University of New York - SUNY Korea Moonhwa-ro Songdo Incheon21985 Korea Republic of Mechanical Engineering Department Ateneo de Davao University Jacinto St. Davao del Sur Davao City8000 Philippines

As one of the promising renewable energies, ocean renewable energy (ORE) in the form of tidal energy can be extracted through a horizontal-axis tidal turbine (HATT). HATT performance relies on various environmental factors, including the presence of waves, shear flow, blockage, and submersion depth. Several studies have been conducted regarding the effects of such factors on HATT’s performance. However, a coupled study on the mentioned environmental factors is yet to be performed. This study determines the effects of blockage and submersion depth on HATT’s performance designed for low-flow velocities experiencing shear flow with wave–current interaction through numerical simulations. The hydrodynamic analysis is done using CFD to determine the performance characteristics of the turbine, specifically the coefficients of thrust and power. For structural performance, a fatigue analysis is done through FEM to study the effects of stress loadings on the turbine. A wet epoxy/E-glass is utilized as the material of the turbine and a stress-life (S-N) analysis as the fatigue model. It is found that an increase in blockage ratio and submersion depth increases the coefficients of thrust and power, thus increasing the forces applied on the turbine blade. This result is due to the variation in fluid flow created by waves and current, which also leads to an increasing accumulation of stress and strain, with safety factors decreasing along with it. The parametric analysis shows a very strong relationship between the hydrodynamic and structural performance of the turbine, with absolute R-values ranging from 0.84 to 1.0. This study shows blockage ratio and submersion depth are essential considerations when designing HATTs. © The Author(s), under exclusive licence to Sociedade Brasileira de Engenharia Naval 2024.

关键词： computational fluid dynamics

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