Deep Probabilistic Surrogate Networks for Universal Simulator Approximation

We present a framework for automatically structuring and training fast, approximate, deep neural surrogates of existing stochastic simulators. Unlike traditional approaches to surrogate modeling, our surrogates retain the interpretable structure of the reference simulators. The particular way we achieve this allows us to replace the reference simulator with the surrogate when undertaking amortized inference in the probabilistic programming sense. The fidelity and speed of our surrogates allow for not only faster "forward" stochastic simulation but also for accurate and substantially faster inference. We support these claims via experiments that involve a commercial composite-materials curing simulator. Employing our surrogate modeling technique makes inference an order of magnitude faster, opening up the possibility of doing simulator-based, non-invasive, just-in-time parts quality testing; in this case inferring safety-critical latent internal temperature profiles of composite materials undergoing curing from surface temperature profile measurements

Accelerating urban scale simulations leveraging local spatial 3D structure

[EN] This paper presents a hybrid methodology for accelerating Computational Fluid Dynamics (CFD) simulations intertwining inferences from deep neural networks (DNN). The strategy leverages the local spatial data of the velocity field to leverage three-dimensional convolutional kernels within DNN. The hybrid workflow is composed of two-step cycles where CFD solvers calculations are utilized to feed predictive models, whose inferences, in turn, accelerate the simulation of the fluid evolution compared with traditional CFD. This approach has proved to reduce 30% time-to-solution in an urban scale study case, which leads to generating massive datasets at a fraction of the cost.Researcher S. Iserte was supported by postdoctoral fellowship APOSTD/2020/026 from GVA-ESF. While researcher A. Macias was supported by predoctoral fellowship FDGENT from GVA. CTE-Power cluster of the Barcelona Supercomputing Center, and Tirant III cluster of the Servei d'Informatica of the University of Valencia were leveraged in this research. Authors want to thank the anonymous reviewers whose suggestions significantly improved the quality of this manuscript.Iserte, S.; Macías, A.; Martínez-Cuenca, R.; Chiva, S.; Paredes Palacios, R.; Quintana-Ortí, ES. (2022). Accelerating urban scale simulations leveraging local spatial 3D structure. Journal of Computational Science. 62:1-11. https://doi.org/10.1016/j.jocs.2022.1017411116

7th International Conference on Nonlinear Vibrations, Localization and Energy Transfer: Extended Abstracts

International audienceThe purpose of our conference is more than ever to promote exchange and discussions between scientists from all around the world about the latest research developments in the area of nonlinear vibrations, with a particular emphasis on the concept of nonlinear normal modes and targeted energytransfer

SOLID-SHELL FINITE ELEMENT MODELS FOR EXPLICIT SIMULATIONS OF CRACK PROPAGATION IN THIN STRUCTURES

Crack propagation in thin shell structures due to cutting is conveniently simulated using explicit finite element approaches, in view of the high nonlinearity of the problem. Solidshell elements are usually preferred for the discretization in the presence of complex material behavior and degradation phenomena such as delamination, since they allow for a correct representation of the thickness geometry. However, in solid-shell elements the small thickness leads to a very high maximum eigenfrequency, which imply very small stable time-steps. A new selective mass scaling technique is proposed to increase the time-step size without affecting accuracy. New ”directional” cohesive interface elements are used in conjunction with selective mass scaling to account for the interaction with a sharp blade in cutting processes of thin ductile shells

Two-phase model for simulating current-induced scour beneath subsea pipelines at different initial elevations

When a subsea pipeline is laid on an uneven seabed, the pipeline can have an initial elevation, potentially compromising its on-bottom stability; scouring due to flow conditions around the pipe can further exacerbate the problem. We assess the capability of the two-phase Eulerian-Eulerian OpenFOAM solver, twoPhaseEulerFoam, in terms of predicting the equilibrium scour depth beneath a pipe at different initial elevations under a steady current for the live bed condition. The predictions were found to be in good agreement with published experimental and numerical results; however, similar to a recent study involving another two-phase Eulerian-Eulerian model, the scour time scale was under-predicted. The predicted equilibrium scour depth was seen to decrease with an increase in the initial pipe elevation. The numerical results were also compared to predictions that were made using previous empirical equations. The most comprehensive equation to date showed a good agreement with the present numerical results. We conclude that this open-source solver, twoPhaseEulerFoam, can be used to predict the equilibrium scour depth beneath subsea pipelines, with short computation times and negligible mesh dependency

Large space structures and systems in the space station era: A bibliography with indexes (supplement 03)

Bibliographies and abstracts are listed for 1221 reports, articles, and other documents introduced into the NASA scientific and technical information system between January 1, 1991 and June 30, 1991. Topics covered include large space structures and systems, space stations, extravehicular activity, thermal environments and control, tethering, spacecraft power supplies, structural concepts and control systems, electronics, advanced materials, propulsion, policies and international cooperation, vibration and dynamic controls, robotics and remote operations, data and communication systems, electric power generation, space commercialization, orbital transfer, and human factors engineering