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Related papers: Toward a chaotic adjoint for LES

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Within the domain of Computational Fluid Dynamics, Direct Numerical Simulation (DNS) is used to obtain highly accurate numerical solutions for fluid flows. However, this approach for numerically solving the Navier-Stokes equations is…

Fluid Dynamics · Physics 2021-03-16 Pranshu Pant , Amir Barati Farimani

We present a new software system PETSc TSAdjoint for first-order and second-order adjoint sensitivity analysis of time-dependent nonlinear differential equations. The derivative calculation in PETSc TSAdjoint is essentially a high-level…

Mathematical Software · Computer Science 2021-10-28 Hong Zhang , Emil M. Constantinescu , Barry F. Smith

Solving flow-related inverse problems such as topology optimization problems is intricate but significant in various engineering fields. The lattice Boltzmann method (LBM) and the related adjoint method are highly suitable to perform…

Numerical Analysis · Mathematics 2025-06-10 Ji-Wang Luo , Li Chen , Kentaro Yaji , Wen-Quan Tao

An innovative \textit{deep learning} approach has been adopted to formulate the eddy-viscosity for large eddy simulation (LES) of wall-bounded turbulent flows. A deep neural network (DNN) is developed which learns to evaluate the…

Fluid Dynamics · Physics 2019-05-31 Anikesh Pal

When simulating multiscale systems, where some fields cannot be fully prescribed despite their effects on the simulation's accuracy, closure models are needed. This phenomenon is observed in turbulent fluid dynamics, where Large Eddy…

Fluid Dynamics · Physics 2025-12-01 Eduardo Vital , Jean-Marc Gratien , Yassine Ayoun , Thibault Faney , Julien Bohbot

Hybrid Reynolds-averaged Navier Stokes large eddy simulation (RANS LES) methods have become popular for simulation of massively separated flows at high Reynolds numbers due to their reduced computational cost and good accuracy. The current…

Fluid Dynamics · Physics 2021-02-19 Gaurav Kumar , Ashoke De , Harish Gopalan

We propose an end-to-end trained neural networkarchitecture to robustly predict the complex dynamics of fluid flows with high temporal stability. We focus on single-phase smoke simulations in 2D and 3D based on the incompressible…

Graphics · Computer Science 2020-03-20 Steffen Wiewel , Byungsoo Kim , Vinicius C. Azevedo , Barbara Solenthaler , Nils Thuerey

Approximate computing is an effective computing paradigm for improving the energy efficiency of error-tolerant applications. Approximate logic synthesis (ALS) is an automatic process to generate approximate circuits with reduced area,…

Emerging Technologies · Computer Science 2026-01-22 Chang Meng , Weikang Qian , Giovanni De Micheli

This work presents the Second-Order Sensitivity Analysis Methodology (2nd-ASAM) for nonlinear systems. This methodology yields exactly and efficiently the second-order functional derivatives of system responses (associated with physical,…

Optimization and Control · Mathematics 2016-01-26 Dan Gabriel Cacuci

The least trimmed squares (LTS) estimator is a renowned robust alternative to the classic least squares estimator and is popular in location, regression, machine learning, and AI literature. Many studies exist on LTS, including its…

Machine Learning · Statistics 2025-01-10 Yijun Zuo

A nonlocal subgrid-scale stress (SGS) model is developed based on the convolution neural network (CNN), a powerful supervised data-driven approach. The CNN is an ideal approach to naturally consider nonlocal spatial information in…

Fluid Dynamics · Physics 2023-01-27 Bo Liu , Huiyang Yu , Haibo Huang , Xi-Yun Lu

A sensitive porosity adjoint method (SPAM) for optimizing the topology of fluid machines has been proposed. A sensitivity function with respect to the porosity has been developed. In the first step of the optimization process, porous media…

Fluid Dynamics · Physics 2015-12-29 B. Philippi , Y. Jin

A well-behaved adjoint sensitivity technique for chaotic dynamical systems is presented. The method arises from the specialisation of established variational techniques to the unstable periodic orbits of the system. On such trajectories,…

Chaotic Dynamics · Physics 2018-03-12 Davide Lasagna

In this study, we explore the application of an artificial recurrent neural network (RNN) called Long Short-Term Memory (LSTM) as an alternative to a turbulent Reynolds-Averaged Navier-Stokes (RANS) model. The LSTM models are utilized to…

Fluid Dynamics · Physics 2023-07-27 Hugo D. Pasinato , Nicólas F. Moguilner Reh

We propose a constraint-based flow-sensitive static analysis for concurrent programs by iteratively composing thread-modular abstract interpreters via the use of a system of lightweight constraints. Our method is compositional in that it…

Programming Languages · Computer Science 2017-10-02 Markus Kusano , Chao Wang

In turbulence research and flow applications, turbulence models like RaNS (Reynolds averaged Navier-Stokes) models and LES (Large Eddy Simulation) are used. Both models filter the governing flow equations. Thus a scale separation approach…

Fluid Dynamics · Physics 2015-06-17 Christoph Glawe , Heiko Schmidt , Alan R. Kerstein , Rupert Klein

Adjoint method is widely used in aerodynamic design because only once solution of flow field is required for adjoint method to obtain the gradients of all design variables. However, the calculation cost of adjoint vector is approximately…

Fluid Dynamics · Physics 2021-01-01 Mengfei Xu , Shufang Song , Xuxiang Sun , Wengang Chen , Weiwei Zhang

A key part of planning CO2 storage sites is to devise a monitoring strategy. The aim of this strategy is to fulfill the requirements of legislations and lower cost of the operation by avoiding operational problems. If CCS is going to be a…

Numerical simulations of atmospheric circulation models are limited by their finite spatial resolution, and so large eddy simulation (LES) is the preferred approach to study these models. In LES a low-pass filter is applied to the flow…

Fluid Dynamics · Physics 2016-04-27 Leila N. Azadani , Anne E. Staples

This paper presents a parallel-in-time adjoint sensitivity analysis which combines a transient adjoint sensitivity analysis with the parareal approach in order to significantly speed up the simulation. The adjoint method is the method of…

Numerical Analysis · Mathematics 2023-07-04 Julian Sarpe , Andreas Klaedtke , Herbert De Gersem
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