Progressive augmentation of Reynolds stress tensor models for secondary flow prediction by computational fluid dynamics driven surrogate optimisation DOI Creative Commons
Mario Javier Rincón, Ali Amarloo, Martino Reclari

и другие.

arXiv (Cornell University), Год журнала: 2023, Номер unknown

Опубликована: Янв. 1, 2023

Generalisability and the consistency of a posteriori results are most critical points view regarding data-driven turbulence models. This study presents progressive improvement models using simulation-driven surrogate optimisation based on Kriging. We aim for augmentation secondary-flow reconstruction capability in linear eddy-viscosity model without violating its original performance canonical cases e.g. channel flow. Explicit algebraic Reynolds stress correction (EARSCMs) $k-\omega$ SST obtained to predict secondary flow which standard fails capture. The is achieved by multi-objective approach duct quantities, numerical verification developed performed various test cases. testing new guarantee that preserve model. Regarding generalisability models, unseen demonstrate significant prediction flows streamwise velocity. These highlight potential enhance fluid simulation while preserving robustness stability solver.

Язык: Английский

An Overview of Computational Fluid Dynamics as a Tool to Support Ultrasonic Flow Measurements DOI Creative Commons
Guilherme Siqueira de Aquino, Ramon Silva Martins, Márcio Ferreira Martins

и другие.

Metrology, Год журнала: 2025, Номер 5(1), С. 11 - 11

Опубликована: Фев. 5, 2025

Ultrasonic flow meters (UFMs) by transit time are ubiquitous in industrial applications, mainly for their versatility and practicality. They widely used gas liquid installations, such as the oil industry or feedwater systems nuclear power plants. Computational fluid dynamics (CFD) techniques can be a tool to potentially improve ultrasonic measurements. CFD may contribute predicting velocity profile factor disturbed flows, integrating acoustic ray, improving calibration of UFMs, assisting design optimization. This communication presents working principle UFM, discusses how support improvements, shows relevant trending fields that deserve further investigation promote significance on this subject.

Язык: Английский

Процитировано

1

Log-law recovery through reinforcement-learning wall model for large eddy simulation DOI Creative Commons
Aurélien Vadrot, Xiang I. A. Yang, H. Jane Bae

и другие.

Physics of Fluids, Год журнала: 2023, Номер 35(5)

Опубликована: Май 1, 2023

This paper focuses on the use of reinforcement learning (RL) as a machine-learning (ML) modeling tool for near-wall turbulence. RL has demonstrated its effectiveness in solving high-dimensional problems, especially domains such games. Despite potential, is still not widely used turbulence and primarily flow control optimization purposes. A new wall model (WM) called VYBA23 developed this work, which uses agents dispersed near wall. The trained single Reynolds number (Reτ=104) does rely high-fidelity data, backpropagation process based reward rather than an output error. states RLWM, are representation environment by agents, normalized to remove dependence number. tested compared another RLWM (BK22) equilibrium model, half-channel at eleven different numbers {Reτ∈[180;1010]}. effects varying agents' parameters, actions range, time step, spacing, also studied. results promising, showing little effect average field but some wall-shear stress fluctuations velocity fluctuations. work offers positive prospects developing RLWMs that can recover physical laws extending type ML models more complex flows future.

Язык: Английский

Процитировано

14

Progressive augmentation of Reynolds stress tensor models for secondary flow prediction by computational fluid dynamics driven surrogate optimisation DOI Creative Commons
Mario Javier Rincón, Ali Amarloo, Martino Reclari

и другие.

International Journal of Heat and Fluid Flow, Год журнала: 2023, Номер 104, С. 109242 - 109242

Опубликована: Ноя. 7, 2023

Generalisability and the consistency of a posteriori results are most critical points view regarding data-driven turbulence models. This study presents progressive improvement models using simulation-driven Bayesian optimisation with Kriging surrogates where is achieved by multi-objective approach based on duct flow quantities. We aim for augmentation secondary-flow prediction capability in linear eddy-viscosity model k−ω SST without violating its original performance canonical cases e.g. channel flow. Progressively data-augmented explicit algebraic Reynolds stress (PDA-EARSMs) obtained enabling secondary flows that standard fails to predict. The new tested guaranteeing they preserve successful model. Subsequently, numerical verification performed various test cases. Regarding generalisability models, unseen demonstrate significant streamwise velocity. These highlight potential enhance fluid simulation while preserving robustness stability solver.

Язык: Английский

Процитировано

9

Improved flow prediction of non-ideal sonic nozzles by CFD-based surrogate modelling DOI Creative Commons
S. Weiß,

Bodo Mickan,

Kilian Oberleithner

и другие.

Engineering Applications of Computational Fluid Mechanics, Год журнала: 2025, Номер 19(1)

Опубликована: Май 6, 2025

Язык: Английский

Процитировано

0

Laminarization through annular gap injection in turbulent pipe flows: A large eddy simulation study DOI
Sina Nozarian, Christoffer Hansen, Pourya Forooghi

и другие.

Physics of Fluids, Год журнала: 2025, Номер 37(5)

Опубликована: Май 1, 2025

This study employs wall-resolving large eddy simulations (LES) to investigate whether and how laminarization occurs in turbulent pipe flows through annular gap fluid injection. The investigations focus on the effects of injection velocity ratio (Uratio) inflow bulk Reynolds number (ReB) flow dynamics, examining key characteristics such as mean profiles, stresses, production, friction factors. Sustained laminar was observed at ReB=3700 for Uratio values between 1.8 2.6 over a length 100D, achieving significant 45% reduction factor Uratio=2.6. is attributed suppression turbulence regeneration cycle, evidenced by pronounced downstream peak streamwise fluctuations, shear stress, production. Conversely, ReB=5500, sustained unattainable any tested Uratio, persisted due suboptimal conditions or adverse effects. Nonetheless, these cases with non-laminarizing still exhibited reductions coefficient—up 30%, ReB=5500 Uratio=1.6—over certain before ultimately reverting fully state further downstream. Our LES results demonstrate good qualitative agreement experimental findings Kühnen et al. (Flow Turbul. Combustion, 100(4), 2018, pp. 919–943), effectively capturing dynamics regeneration.

Язык: Английский

Процитировано

0

Progressive augmentation of turbulence models for flow separation by multi-case computational fluid dynamics driven surrogate optimization DOI Open Access
Ali Amarloo, Mario Javier Rincón, Martino Reclari

и другие.

Physics of Fluids, Год журнала: 2023, Номер 35(12)

Опубликована: Дек. 1, 2023

In the field of data-driven turbulence modeling, consistency a posteriori results and generalizability are most critical aspects new models. this study, we combine multi-case surrogate optimization technique with progressive augmentation approach to enhance performance popular k−ω shear stress transport (SST) model in prediction flow separation. We introduce separation factor into equation turbulent specific dissipation rate (ω) correct underestimation viscosity by SST case for two-dimensional cases. The is optimized based on their training cases including periodic hills curved backward-facing step flow. Simulation channel likewise included process guarantee that original preserved absence verified multiple unseen different Reynolds numbers geometries. Results show significant improvement recirculation zone, velocity components, distribution friction coefficient both testing cases, where expected. models test no shows they preserve successful when not

Язык: Английский

Процитировано

5

Flow investigation of two-stand ultrasonic flow meters in a wide dynamic range by numerical and experimental methods DOI Creative Commons
Mario Javier Rincón, Anders Caspersen, Nicolai Thorenfeldt Ingwersen

и другие.

Flow Measurement and Instrumentation, Год журнала: 2024, Номер 96, С. 102543 - 102543

Опубликована: Янв. 20, 2024

The enhancement of two-stand ultrasonic flow meters relies upon obtaining a precise understanding and prediction their complex physics throughout entire dynamic range operation. This study provides comprehensive numerical experimental investigation the typical meter by industry standards. Predictions based on computational fluid dynamics simulations are employed to obtain results, which validated through experiments laser Doppler velocimetry static pressure drop. Results indicate that no qualitative changes occur beyond an inflow Reynolds number 104 in terms coherent structures dynamics. Analysis distribution across cross-sections reveals stands most influential areas contributing In cases with turbulent inflow, there is noticeable recovery following significant gradients stands, while such absent scenarios laminar inflow. Both approaches yield excellent agreement outcomes, accurately estimating axial velocity within meter's measurement volume drop it, deviations uncertainty ranges 1 3 standard respectively. developed methodology demonstrates its potential evaluate internal-flow systems similar features ranges. for wide operation shown detail both regimes, displaying rolling vortices, detached flow, recirculation zones.

Язык: Английский

Процитировано

1

Comparison of model-driven soft measurement methods for compressor air flow in gas-steam combined cycle power units DOI

Zengmeng Le,

Ying Liang,

Bo Xiong

и другие.

Flow Measurement and Instrumentation, Год журнала: 2023, Номер 94, С. 102462 - 102462

Опубликована: Сен. 15, 2023

Язык: Английский

Процитировано

2

On the development of opensource 3D printed impeller flowmeters for open channels DOI Creative Commons
Tom Rowan, Yiling Lu, Alex Colyer

и другие.

Flow Measurement and Instrumentation, Год журнала: 2023, Номер 94, С. 102469 - 102469

Опубликована: Окт. 15, 2023

Commercial flowmeters are often costly and complex but crucial to mapping flows calculating contamination flux. Sampling is an easy method for determining concentration, without flow rates, it impossible find total loading. This work devised a simplified circuit innovative 3D prints produce low-cost meter. Interchangeable impellers compensate the electronics' limitations allowing device be highly accurate widely applicable. The opensource impeller/propeller design software OpenProp was used build several variations different conditions. enabled optimisation of design. blades tested here in open channel (though impeller designed fit inside 2" pipe). paper also describes optimise both physical electrical flowmeter. Characteristics including stability, sensitivity accuracy were studied. flowmeter River Eden, Cumbria, UK. robust reproduce, opensource, community educational groups.

Язык: Английский

Процитировано

2

Optimization of cavitation characteristics of aviation fuel centrifugal pump inducer based on surrogate model DOI
Jiangfeng Fu, Xianwei Liu, Junjie Yang

и другие.

Structural and Multidisciplinary Optimization, Год журнала: 2023, Номер 66(11)

Опубликована: Ноя. 1, 2023

Язык: Английский

Процитировано

2