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Performance improvement for proton exchange membrane fuel cells (PEMFCs) with different parallel flow fields by optimizing ribs arrangement

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ENERGY 2025年 322卷

作者： Wang, Changjiang Yu, Zeting Liu, Wenjing Qiao, Yanjin Wang, Daohan Cui, Bo Gao, Hui Shandong Univ Sch Energy & Power Engn Jinan 250061 Peoples R China Shandong Univ Shandong Engn Res Ctr High efficiency Energy Stora Sch Energy & Power Engn Jinan 250061 Shandong Peoples R China China Three Gorges Renewables Grp Co Ltd Beijing 100053 Peoples R China Shandong Univ Sch Elect Engn Jinan 250061 Peoples R China Shandong Xinguang Energy Saving Technol Co Ltd Yantai 265503 Shandong Peoples R China

The flow field structure plays a significant role in the operation, reliability and durability of PEMFC. This study first investigates and compares the parallel flow field ribs arrangement (namely Left-in-Right-out (LR), Middlein-Middle-out (MM), Left-in-Middle-out (LM) and Middle-in-Right-out (MR)) using the collaborative optimization framework which is integrated with the computational fluid dynamics (cfd), artificial neural network (ANN) surrogate model and non-dominated sorting genetic algorithm-II (NSGA-II). The results show that the net power output (Pnet) of the optimized flow field ribs arrangement is increased compared with the basic case, respectively. Then, two other configurations (named LRM and MLR-OP) are proposed to improve the oxygen distribution non-uniformity. Compared with the LM, the power density of LRM is increased by 3.28 % and the pressure drop is reduced by 13.79%. The power density of the MLR-OP is increased by 15.12% and 11.98%, and the pressure drop is reduced by 52.05 % and 58.03 % compared with the MM and MR. Moreover, it is found the sub-channel pressure changes consistently with the rib distance which is validated by MLR-OP' configuration, the optimized parallel flow fields have excellent mass transfer performance and avoid complex structures, which provide references for the structural design of PEMFC.

关键词： computational fluid dynamics Ribs arrangement Multi-objective optimization Artificial neural network Proton exchange membrane fuel cell

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Two-level dynamic load-balanced p-adaptive discontinuous Galerkin methods for cfd simulations

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COMPUTERS & MATHEMATICS WITH APPLICATIONS 2024年 176卷 165-178页

作者： Jang, Yongseok Martin, Emeric Chapelier, Jean-Baptiste Couaillier, Vincent Polytech Inst Paris French Aerosp Lab DAAA ONERA F-92320 Chatillon France

We present a novel approach utilizing two-level dynamic load balancing for p-adaptive discontinuous Galerkin (DG) methods in compressible computational fluid dynamics (cfd) simulations. The high-order explicit first stage, specifically the singly diagonal implicit Runge-Kutta (ESDIRK) method, is employed for time integration, where the pseudo-transient continuation is integrated with the restarted generalized minimal residual (GMRES) method to handle the solution of nonlinear equations at each stage of ESDIRK, excluding the initial stage. Relying on smoothness indicators, we carry out the refinement/coarsening process for p-adaptation with dynamic load balancing. This approach involves a coarse level (distributed memory) decomposition based on MPI paradigm and a fine level (shared memory) decomposition based on OpenMP paradigm, enhancing parallel efficiency. Dynamic load balancing is achieved by computing weights based on degrees of freedom, ensuring balanced computational loads across processors. The parallel computing framework adopts either a graph-based type (ParMETIS and Zoltan) or space-filling curves type (GeMPa) for coarse level partitioning, and a graph-based type (METIS and Zoltan) for fine level partitioning. The effectiveness of the method is demonstrated through numerical examples, highlighting its potential to significantly improve the scalability and efficiency of compressible flow simulations. The numerical simulations were conducted using the CODA flow solver, a state-of-the-art tool developed collaboratively by the French National Aerospace Center (ONERA), the German Aerospace Center (DLR), and Airbus.

关键词： Dynamic load balancing p-adaptation High-order discontinuous Galerkin method Two-level parallelization cfd

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computational fluid dynamics Analysis of Ballast Water Treatment System Design

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JOURNAL OF MARINE SCIENCE AND ENGINEERING 2025年第4期13卷 743-743页

作者： Rak, Andro Mrakovcic, Tomislav Mausa, Goran Kranjcevic, Lado Univ Rijeka Fac Engn Dept Fluid Mech & Computat Engn Vukovarska 58 Rijeka 51000 Croatia Univ Rijeka Fac Engn Dept Thermodynam & Energy Engn Vukovarska 58 Rijeka 51000 Croatia Univ Rijeka Fac Engn Dept Comp Engn Vukovarska 58 Rijeka 51000 Croatia Univ Rijeka Ctr Adv Comp & Modelling Radmile Matejc 2 Rijeka 51000 Croatia

The effective management of ships' ballast water is critical for preventing the spread of invasive species. Despite advancements in UV-based ballast water treatment systems (BWTSs), achieving a uniform flow distribution within UV reactors (UVRs) remains challenging due to the spatial constraints of ships. This study employs computational fluid dynamics (cfd) to analyze turbulent seawater flow in a real-case BWTS installed on a self-discharging bulk carrier. The flow uniformity at UVR inlets and the volume flow rate (Q) distribution between parallel reactors are evaluated at nominal flow rates of 1000, 1900, and 2000 m3/h. The results indicate significant disparities at maximum capacity (2000 m3/h), with the starboard configuration exceeding the recommended Q per UVR by 4.95%, thus requiring operational adjustments. Six geometric modifications are assessed, revealing that optimized pipeline bends and T-junction designs (e.g., ST_3 and ST_4) improve velocity uniformity and maintain the relative Q distribution errors below 8.5%. This study identifies vortical structures generated by sharp geometrical transitions as primary contributors to flow instability. By bridging cfd insights with practical engineering constraints, this work provides feasible recommendations for retrofitting existing BWTSs and designing future systems, ultimately enhancing treatment efficacy, reducing UV lamp wear, and supporting compliance with International Maritime Organization (IMO) standards.

关键词： computational fluid dynamics (cfd) ballast water treatment (BWT) UV reactors RANS turbulent flow analysis pipeline optimization

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Multiphysics performance evaluation of thermoelectric generator arrays

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APPLIED THERMAL ENGINEERING 2024年 249卷

作者： Gull, Muhammad Naveed Cheema, Taqi Ahmad Imran, Abid Zaman, Naeem Uz Sher, Hadeed Ahmed Park, Cheol Woo GIK Inst Engn Sci & Technol Fac Mech Engn Topi 23460 Pakistan GIK Inst Engn Sci & Technol Fac Elect Engn Topi 23460 Pakistan Kyungpook Natl Univ Sch Mech Engn 80 Daehak Ro Daegu 41566 South Korea

Thermoelectric generators (TEGs) are widely used nowadays in heat recovery and power generation applications. TEGs are connected in series and/or parallel configurations in an array to meet the voltage and/or current requirements of electric load. Therefore, it is necessary to examine the electrical performance of different TEG array configurations employed in TEG systems. In the present study, an experimentally validated hydrothermoelectric multiphysics computational model is employed by integrating the computational fluid dynamics (cfd) approach with the TEG model to test the electrical performance of various TEG array configurations and determined load voltage, current, associated power, and conversion efficiency. Each TEGs array configuration's performance is evaluated by varying the hot water temperature from 27 degrees C to 42 degrees C as well as hot and cold water flowrate from 0.5 L/min to 2 L/min. Various configurations including series and a combination of series and parallel connections were designed. The findings show that the series configuration of the TEGs array generates higher electric power than series and parallel combined configurations whereas the latter achieves the maximum power point at a higher electric current than the series configuration. The comparative analysis of cfd model with the experimental results indicates a maximum discrepancy of 7 %. For thermoelectric powergenerating systems, the proposed model might serve as a benchmark for optimizing TEGs array configurations according to the electric load requirements.

关键词： TEGs array Hydro -thermoelectric Multiphysics computational model TEG system Maximum power point

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Voxelization of Moving Deformable Geometries on GPU 23

Voxelization of Moving Deformable Geometries on GPU

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23rd International Symposium on parallel and Distributed Computing (ISPDC)

作者： Kumar, Ronith Deep, Raman Banerjee, Dip Sankar Arora, Nipun Indian Inst Technol Jodhpur Dept Comp Sci & Engn Jodhpur Rajasthan India Indian Inst Technol Jodhpur Dept Mech Engn Jodhpur Rajasthan India

ISBN: (纸本)9798350369205;9798350369199

Voxelization is a standard technique to represent arbitrary shaped geometries on a Cartesian grid. It is often utilized in pre-processing stage of any computational fluid dynamics (cfd) simulation for distinguishing the fluid and solid domain. In addition, identification of boundary fluid nodes in the immediate vicinity of the solid body is extremely crucial for proper imposition of boundary conditions and force evaluation. These nodes are therefore tagged separately and is often termed as surface voxelization. However, this procedure becomes non-trivial and computationally expensive as the complexity of geometry increases, especially if it is deformable and moving. Here voxelization needs to be performed in the solid volume as well, as the nodes keep switching from solid to fluid and vice versa at every iteration. For fluid-structure interaction problems, the analysis of flow behaviour requires an additional operation where the point of intersection of the lattice links connecting the fluid boundary nodes and solid bound nodes need to be further calculated. This ensures that deformation of geometry is properly captured and the correct boundary velocity is enforced onto the fluid (no slip). In this work we present techniques for GPU acceleration of voxelization for moving deformable geometries intended for cfd solvers based on the lattice Boltzmann method (LBM). The proposed techniques show speed-ups of up to 5.1x over equivalent parallel implementations.

关键词： computational fluid dynamics

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Research on fast prediction of boiling flow parameters in rod bundle of NPP based on efficient cfd-ROM methods

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PROGRESS IN NUCLEAR ENERGY 2025年 184卷

作者： Mo, Jinhong Dong, Xiaomeng Xu, Yujie Xu, Anqi Yu, Yang Yang, Ming Shenzhen Univ China Inst Nucl Energy & Safety Coll Phys & Optoelect Engn Shenzhen Key Lab Nucl & Radiat Safety Nanhai St 3688 Nanshan Dist Shenzhen 518060 Peoples R China Natl Univ Def Technol Natl Key Lab Parallel & Distributed Comp Changsha 410073 Peoples R China Nucl Power Inst China Chengdu 610041 Peoples R China

Historically, computational fluid dynamics (cfd) has been widely used to verify the flow dynamics in rod bundle channels. Nevertheless, the iterative calculation and time consumption make it impractical for the application of digital twin that require efficiency. In order to tackle this difficulty, we suggest utilizing a datadriven order reduced model (ROM) to rapidly predict flow fields of rod bundle channels. Previous research on Reduced Order Models (ROM) for rod bundle channel has primarily focused on the single-phase state, with little emphasis on the two-phase state. Thus, the study focuses on the ROM of rod bundle channel in a two-phase state. First, a computational fluid dynamics (cfd) data set is processed using the Proper Orthogonal Decomposition (POD) algorithm to identify important modes. Then, a Back-Propagation Neural Network (BPNN) model is trained as the agent model, due to its strong ability to fit non-linear relationship between input and output. The structure of BPNN is optimized. Ultimately, the ROM model is utilized to predict the flow field of a rod bundle channel under new boundary conditions. The comparison with cfd calculation confirms the effectiveness of the Reduced Order Model (ROM), showcasing its high precision in predicting the temperature, velocity, and void fraction fields within the rod bundle channel. In addition, the ROM model reaches a computation speed that is roughly 10<^>4 times quicker than standard cfd simulations. Nonetheless, it is noted that the model's predictive accuracy diminishes under conditions of slight subcooled boiling, due to the lack of samples under the condition. An improvement strategy: Subdivide the sampling space region according to various change stages, implement partition sampling.

关键词： POD algorithm BPNN model Boiling flow cfd numerical simulation Rod bundle channel model

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Vortex-induced vibration characteristics of parallel II-shaped composite girders

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JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AEROdynamics 2024年 252卷

作者： Qin, Chuan Zhou, Qiang Wu, Weihong Li, Mingshui Southwest Jiaotong Univ Res Ctr Wind Engn Chengdu 610031 Peoples R China Wind Engn Key Lab Sichuan Prov Chengdu 610031 Peoples R China State Key Lab Bridge Intelligent & Green Construct Chengdu 611756 Peoples R China Traff Planning Survey & Design Inst Co Ltd Gansu P Lanzhou 730030 Peoples R China

A series of sectional model testing were conducted to investigate the vortex-induced vibration (VIV) characteristics of parallel II-shaped composite girders under different spacing ratios and wind attack angles. To enhance the understanding of the aerodynamic interference effects on the VIV, particular attention is devoted to the vibration amplitude, lock-in wind speed, phase difference, and spectrum characteristics of the upstream and downstream girders. Results showed that the aerodynamic interference has significant effects on the downstream girder, resulting in the VIV amplitude amplified obviously. Nevertheless, the upstream girder is less affected, with its amplitude slightly smaller or almost equivalent to that of a single-II-shaped girder. The lock-in range and vortex shedding frequency of the upstream and downstream girders are almost unaffected by aerodynamic interference. The phase difference phi between the vibrations of upstream and downstream girders diminishes in a nearly linear manner as wind speed rises in the lock-in region for all spacing ratios investigated, except at the end of the lock-in region. Additionally, the initial phase difference is directly related to the spacing ratio. In addition, the fluid mechanism of VIV was analyzed by computational fluid dynamics (cfd) technique. It was found that the downstream girder experiences the alternating flow fields ' ZS ' and ' S2 ' generated by the upstream wake vortices, leading to VIV amplitude amplification of downstream girder.

关键词： parallel II-shaped girders Aerodynamic interference Vortex-induced vibration (VIV) Wind tunnel testing cfd simulation

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computationally effective machine learning approach for modular thermal energy storage design

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APPLIED ENERGY 2025年 377卷

作者： Singh, Davinder Rugamba, Tanguy Katara, Harsh Grewal, Kuljeet Singh Univ Toronto Dept Chem Chem Phys Theory Grp Toronto ON M5S 3H6 Canada Univ Toronto Ctr Quantum Informat & Quantum Control Toronto ON M5S 3H6 Canada Univ Prince Edward Isl Fac Sustainable Design Engn FSDE Future Urban & Energy Lab Sustainabil FUEL S Charlottetown PE C1A 4P3 Canada Indian Inst Technol IIT Guwahati Dept Comp Sci & Engn Gauhati 781039 Assam India

This research presents an innovative approach that integrates computational fluid dynamics (cfd) and machine learning (ML) for the design and optimization of thermal energy storage (TES) systems. Heat discharging parametric analyses conducted using cfd serve as the basis for training ML models, including linear regression, K-nearest neighbor (KNN) regression, gradient boost regression (GBR), XGBoost, LightGBM, and neural network (NN). NN emerges as the most suitable for predicting time-dependent variations of concrete and heat transfer fluid (HTF) temperatures. The trained ML models offer an efficient alternative to traditional cfd simulations, enabling the prediction of temperatures in concrete thermal energy storage (CTES) modules under varying inlet conditions, velocities, and time. Leveraging these ML models, the research demonstrates the design of modular CTES cascaded systems with multiple modules in series and parallel configurations, significantly reducing computational cost and time by over 99% compared to full-scale cfd simulations. For instance, in predicting 4-hour time-dependent thermal behavior, cfd takes 97 s per data point and 238,500 s for a single module, compared to ML models' 16-20 ms per data point and around 290 s per module, indicating their efficiency and scalability in predicting thermal discharge, especially for modular CTES system design and optimization. ML models also demonstrate computational efficiency for designing CTES systems involving multiple modules, taking approximately 765 s - 1047 s for various CTES system configurations, indicating their effectiveness over cfd in predicting thermal discharge for modular CTES systems. The integration of cfd and ML provides a streamlined workflow for designing and optimizing CTES systems, reducing computational efforts, cost, and time. Moreover, this workflow can be updated with additional training data to implement it for unique modular designs with different conditions. Such a generalization

关键词： Machine learning Deep learning Supervised learning Neural network Thermal energy storage computational and cost effectiveness

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Research on wake interval of paired departure at closely spaced parallel runways

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QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL 2023年第5期39卷 1935-1951页

作者： Gao, Haoran Liu, Cheng Chen, Yaqing He, Xin Civil Aviat Flight Univ China Inst Off Guanghan Peoples R China YAITAI Int Airport CO LTD Shandong Airport Management Grp Yantai Peoples R China Civil Aviat Flight Univ China CAAC Key Lab Flight Technol & Safety Guanghan Peoples R China Civil Aviat Flight Univ China Air Traff Management Coll Guanghan Peoples R China

To assess and improve the operation system of paired takeoff separation and reduce the risk of wake turbulence encounters during paired takeoff, a computational fluid dynamics (cfd) method is used to study the operational conditions and wake turbulence safety intervals of paired takeoff separation mode. Firstly, the safe area of wake turbulence under the paired takeoff separation mode is analyzed, and a safety interval model is constructed. Secondly, the SST k-omega turbulence model is selected, and a numerical simulation method for the wake flow of the leading aircraft before the pairing is established based on cfd. Finally, a calculation method for the safety interval of paired takeoff separation is established. Taking Hongqiao Airport as an example, A320-200 and B737-800 are selected as the leading and trailing aircraft, and the wake flow field is simulated at 0, -1, and -2 m/s crosswind conditions. The simulation results are then used to analyze the operational conditions and safety intervals of paired takeoff separation mode. The results provide data support for the implementation of the paired takeoff separation mode and demonstrate the applicability of the cfd method in studying aircraft wake turbulence.

关键词： closely spaced parallel runways computational fluid dynamics (cfd) paired departure wake interval

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Massively parallel simulations of multi-stage compressors on Sunway TaihuLight

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JOURNAL OF SUPERCOMPUTING 2024年第8期80卷 11089-11128页

作者： Wang, Ziwei Li, Bin Deng, Liang Cao, Jie Wang, Jiantao Lu, Fengshun Fan, Zhaolin Jiang, Xiong Natl Univ Def Technol Hyperson Technol Lab Changsha 410073 Hunan Peoples R China China Aerodynam Res & Dev Ctr Mianyang 621000 Sichuan Peoples R China

ASPAC is an in-house computational fluid dynamics (cfd) software for the simulation of flow in turbomachinery. In this paper, with a dual-level hybrid and heterogeneous programming method, we optimized the ASPAC software and ran it on the Sunway TaihuLight supercomputer. Then the unsteady implicit simulation of the 13-stage twin-spool compressor with 6.116 billion grid cells was realized using 611,000 cores. This is an important step closer to solving one of the four challenges mentioned in the "cfd Vision 2030 Study" proposed by NASA. A general solution method for the twin-spool compressor was first proposed. In addition, an efficient large-scale parallel processing method of row interface data exchange was proposed. After that, a series of optimization methods, such as DMA transmission, data packaging, and linear equation system solving process reconstruction, were explored. The test results show that the proposed parallel processing method of row interface data exchange greatly reduces the memory occupation, and the speed of establishing the row interface exchange relationship is increased by two orders of magnitude. Strong scalability testing in the twin-spool 13-stage compressor showed that for 0.765 billion grid cells, ASPAC can achieve 85.0% parallel efficiency when the cores are increased from 10,400 to 624,000;for 6.161 billion grid cells, ASPAC can achieve nearly 100% parallel efficiency when the cores are increased from 208,000 to 611,000. The test shows that the heterogeneous parallel modification of ASPAC on Sunway does not affect the calculation accuracy, and has high scalability, which can play a major role in the large-scale simulation of compressors.

关键词： Sunway TaihuLight Twin-spool 13-Stage compressor Scalability Billions of grid

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