•Novel, “degenerate” version of the proximal policy optimization (PPO) algorithm to train a neural network in optimizing system.•Combining deep reinforcement learning DRL and Computational Fluid ...Dynamics CFD.•Control and optimization of two and three dimension conjugate heat transfer applications.•Data efficiency, simplicity of implementation and reliable performance.
This research gauges the ability of deep reinforcement learning (DRL) techniques to assist the control of conjugate heat transfer systems governed by the coupled Navier–Stokes and heat equations. It uses a novel, “degenerate” version of the proximal policy optimization (PPO) algorithm, intended for situations where the optimal policy to be learnt by a neural network does not depend on state, as is notably the case in optimization and open-loop control problems. The numerical reward fed to the neural network is computed with an in-house stabilized finite elements environment combining variational multi-scale (VMS) modeling of the governing equations, immerse volume method, and multi-component anisotropic mesh adaptation. Several test cases of natural and forced convection in two and three dimensions are used as testbed for developing the methodology. The approach successfully alleviates the natural convection induced enhancement of heat transfer in a two-dimensional, differentially heated square cavity controlled by piece-wise constant fluctuations of the sidewall temperature. It also proves capable of improving the homogeneity of temperature across the surface of two and three-dimensional hot workpieces under impingement cooling. Various cases are tackled, in which the position of multiple cold air injectors is optimized relative to a fixed workpiece position. The flexibility of the numerical framework makes it tractable to solve also the inverse problem, i.e., to optimize the workpiece position relative to a fixed injector distribution. The obtained results showcase the potential of the method for black-box optimization of practically meaningful computational fluid dynamics (CFD) conjugate heat transfer systems. More significantly, they stress how DRL can reveal unanticipated solutions or parameter relations (as the optimal workpiece position under symmetrical actuation turns to be offset from the symmetry axis), in addition to being a tool for optimizing searches in large parameter spaces.
This paper proposes a novel way to solve transient linear, and non-linear solid dynamics for compressible, nearly incompressible, and incompressible material in the updated Lagrangian framework for ...tetrahedral unstructured finite elements. It consists of a mixed formulation in both displacement and pressure, where the momentum equation of the continuum is complemented with a pressure equation that handles incompressibility inherently. It is obtained through the deviatoric and volumetric split of the stress, that enables us to solve the problem in the incompressible limit. A linearization of the deviatoric part of the stress is implemented as well. The Variational Multi-Scale method (VMS) is developed based on the orthogonal decomposition of the variables, which damps out spurious pressure fields for piece wise linear tetrahedral elements. Various numerical examples are presented to assess the robustness, accuracy and capabilities of our scheme in bending dominated problems, and for complex geometries.
•Simulation of transient solid dynamics in the updated Lagrangian framework.•Ability to handle arbitrary geometries through tetrahedral unstructured finite elements.•Deviatoric and volumetric split of the stress to be able to handle materials in the incompressible regime.•Variational Multi-Scale stabilization for piece-wise linear finite elements to avoid pressure locking.•The framework is tested successfully on several numerical simple and complex 2D and 3D examples.
This papers considers the topology optimization of duct flows governed by the three-dimensional steady state Navier-Stokes equations, using anisotropic mesh adaptation to achieve a high-fidelity ...description of all fluid-solid interfaces. The numerical framework combines an immersed volume method solving stabilized, linear equal-order finite element formulations cast in the Variational Multiscale (VMS) framework, and level set representations of the interface, used as a posteriori anisotropic error estimator to minimize the interpolation error under the constraint of a prescribed number of nodes in the mesh. Both the resolution and remeshing steps are performed in a massively parallel framework allowing for the optimization of large-scale systems. In particular, an original parallelization strategy is used for mesh adaptation, that combines local remeshing performed sequentially and independently on each subdomain with blocked interfaces, and constrained repartitioning to optimally move the interfaces between subdomains in an optimal way, both iterated until a satisfying mesh and partition are obtained. The proposed approach reduces the computational burden related to the call of the finite element solver, compared to classical optimization schemes working on uniform grids with similar mesh refinement. For a given number of nodes, it improves the accuracy in the geometric description of all layouts. Finally, it has the potential to alleviates the end user from most of the post-processing step aiming at extracting the final layout, due to ability of anisotropic adapted meshes to generate intrinsically smooth designs. Numerical results are provided for several three-dimensional problems of power dissipation minimization involving several dozen million state degrees of freedom, for which the optimal designs agree well with reference results from the literature, while providing superior accuracy over prior studies solved on isotropic meshes (in the sense that the flow is better resolved, especially in the near-wall regions, and the layouts are more smooth). The potential of the method for engineering problems of practical interest is eventually exposed by optimizing the distributor section conveying the cold fluid within the plates of a plate fin heat exchanger.
This research gauges the capabilities of deep reinforcement learning (DRL) techniques for direct optimal shape design in computational fluid dynamics (CFD) systems. It uses policy based optimization, ...a single-step DRL algorithm intended for situations where the optimal policy to be learnt by a neural network does not depend on state. The numerical reward fed to the neural network is computed with an in-house stabilized finite elements environment combining variational multi-scale modeling of the governing equations, immerse volume method, and multi-component anisotropic mesh adaptation. Several cases are tackled in two and three dimensions, for which shapes with fixed camber line, angle of attack, and cross-sectional area are generated by varying a chord length and a symmetric thickness distribution (and possibly extruding in the off-body direction). At a zero incidence, the proposed DRL-CFD framework successfully reduces the drag of the equivalent cylinder (i.e., the cylinder of same cross-sectional area) by 48% at a Reynolds numbers in the range of a few hundreds. At an incidence of 30°, it increases the lift to drag ratio of the equivalent ellipse by 13% in two dimensions and 5% in three dimensions at a chord Reynolds numbers in the range of a few thousands. Although the low number of degrees of freedom inevitably constrains the range of attainable shapes, the optimal is systematically found to perform just as well as a conventional airfoil, despite DRL starting from the ground up and having no a priori knowledge of aerodynamic concepts. Such results showcase the potential of the method for black-box shape optimization of practically meaningful CFD systems. Since the resolution process is agnostic to details of the underlying fluid dynamics, they also pave the way for a general evolution of reference shape optimization strategies for fluid mechanics and any other domain where a relevant reward function can be defined.
Developing new capabilities to predict the risk of intracranial aneurysm rupture and to improve treatment outcomes in the follow-up of endovascular repair is of tremendous medical and societal ...interest, both to support decision-making and assessment of treatment options by medical doctors, and to improve the life quality and expectancy of patients. This study aims at identifying and characterizing novel flow-deviator stent devices through a high-fidelity computational framework that combines state-of-the-art numerical methods to accurately describe the mechanical exchanges between the blood flow, the aneurysm, and the flow-deviator and deep reinforcement learning algorithms to identify a new stent concepts enabling patient-specific treatment via accurate adjustment of the functional parameters in the implanted state.
Viscoplastic dam-breaks Valette, R.; Pereira, A.; Riber, S. ...
Journal of non-Newtonian fluid mechanics,
January 2021, 2021-01-00, 20210101, 2021-01, Letnik:
287
Journal Article
Recenzirano
Odprti dostop
We analyse through numerical simulations, experiments, and scaling laws the dam-break problem for viscoplastic materials. Numerically, both two and three-dimensional (2D and 3D) scenarios are ...considered thanks to a proposed adaptive stabilized finite element framework able to compute efficiently free surface flows of highly viscoplastic materials. We choose to focus on the Bingham model. Momentum and mass equations are solved by using the Variational MultiScale method coupled with a regularization technique and anisotropic mesh adaptation. A convective self-reinitialization Level-Set method is used to describe the interface evolution. The obtained 2D multiphase results on viscoplastic column collapses show good agreement with literature. Additionally, new 3D simulations for both cylindrical and prismatic columns are explored through energy budget and new scaling laws based on which the collapse process is divided into three regimes: (1) viscous; (2) visco-plastic (mixed); and (3) plastic. These regimes are stressed for a wide range of initial column aspect ratio (1–20) and Bingham number (0.003–0.3). Lastly, the simulations are compared to experiments either taken from existing literature or performed using tailings, mineral suspensions, Carbopol, Mayonnaise, and Ketchup for cylindrical and conical columns.
•We analyse both numerically and experimentally the viscoplastic dam-break problem.•We choose to focus on the Bingham model.•An adaptive stabilized finite element framework is presented and used.•Three collapse regimes are shown: viscous; visco-plastic (mixed); and plastic.•Scaling laws related to the identified spreading regimes are presented.
•A new convective-reactive level-set method coupled with a conservative mesh adaptation technique is presented.•A new level-set method is designed that associates both re-initialization and ...convection steps in an implicit manner.•The method is validated using several time-dependent test cases with two-fluid flows.
In this paper, we present a high fidelity conservative and adaptive level-set method for the simulation of two-fluid flows. A new level-set method is designed that associates both re-initialization and convection steps in an implicit manner. Thus the new obtained convection-reaction problem is solved using a stabilized finite element method. The accuracy, the time scheme and the mass conservation are thoroughly analyzed. Anisotropic meshing with conservative interpolation is implemented and tested on several benchmarks including splashes, sloshing and complex bubble dynamics.
This paper proposes a Computational Fluid Dynamics (CFD) framework with the aim of combining consistency and efficiency for the numerical simulation of high Reynolds number flows encountered in ...engineering applications for aerodynamics. The novelty of the framework is the combination of a Reynolds-Averaged Navier–Stokes (RANS) model with an anisotropic mesh adaptation strategy handling arbitrary immersed geometries by building the corresponding boundary layer meshes. The numerical algorithm consists of robust and accurate solution of the unsteady incompressible Navier–Stokes equations supplemented with a Spalart–Allmaras turbulence model and boundary layer remeshing relying on a specifically designed metric. The flow solver is formulated as a Variational Multiscale (VMS) finite element method for the momentum balance and the incompressibility constraint, and as an upwind Petrov–Galerkin method for the nonlinear turbulent equation. The boundary layer remeshing strategy is flexible as it allows the adaptation of arbitrary coarse meshes by modifying the size and the orientation of elements along the immersed boundary to ensure a smooth gradation along the curvature of the body's geometry. The solver is capable of handling highly stretched anisotropic elements and is shown to successfully predict both mean and fluctuating drag/lift coefficients. Laminar and turbulent test cases in 2D and 3D are presented to assess the performance of this framework against experimental results relevant to external aerodynamics, including an airship and a flying drone.
Abstract Introduction Existing radical cystectomy (RC) perioperative mortality estimates may underestimate the contemporary rates due to more advanced age, more baseline comorbidities and potentially ...broader inclusion criteria for RC, relative to past criteria. Methods Within the most recent Surveillance, Epidemiology, and End Results (SEER)-Medicare database we identified clinically non-metastatic, muscle-invasive (T2–T4a) urothelial carcinoma of the urinary bladder (UCUB) patients, who underwent RC between 1991 and 2009. Mortality at 30- and 90-day after RC was quantified. Multivariable logistic regression analyses tested predictors of 90-day mortality. Results Within 5207 assessable RC patients 30- and 90-day mortality rates were 5.2 and 10.6%, respectively. According to age 65–69, 70–79 and ≥80 years, 90-day mortality rates were 6.4, 10.1 and 14.8% ( p < 0.001). Additionally, 90-day mortality rates increased with increasing Charlson Comorbidity Index (CCI, 0, 1, 2 and ≥3): 6.3, 10.3, 12.6 and 15.9% ( p < 0.001). 90-day mortality rate in unmarried patients was 13.0 vs. 9.3% in married individuals ( p < 0.001). In multivariable logistic regression analyses, advanced age, higher CCI, low socioeconomic status, unmarried status and non organ-confined stage were independent predictors of 90-day mortality (all p < 0.05). Conclusions The contemporary SEER-Medicare derived 90-day mortality rates are substantially higher than previously reported estimates from centers of excellence, and even exceed previous SEER reports. More advanced age, higher CCI score, and other patient characteristics that distinguish the current population from others account for these differences.
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