arXiv subjects

H. -J. Bungartz

Publications and source records attributed to H. -J. Bungartz.

3 recordsLinked to original sources

arXiv2022

A trust-region method for derivative-free nonlinear constrained stochastic optimization

In this work we introduce the stochastic nonlinear constrained derivative-free optimization method (S)NOWPAC (Stochastic Nonlinear Optimization With Path-Augmented Constraints). The method extends the derivative-free optimizer NOWPAC to be applicable for optimization under uncertainty. It is based on a trust-region framework, utilizing local fully quadratic surrogate models combined with Gaussian process surrogates to mitigate the noise in the objective function and constraint evaluations. We show the performance of our algorithm on a variety of robust optimization problems from the CUTEst benchmark suite by comparing to other state-of-the-art optimization methods. Although we focus on robust optimization benchmark problems to demonstrate (S)NOWPAC's capabilities, the optimizer can be applied to a broad range of applications in nonlinear constrained stochastic optimization.

math.OC↗

arXiv2017

Enabling Radiative Transfer on AMR grids in CRASH

We introduce CRASH-AMR, a new version of the cosmological Radiative Transfer (RT) code CRASH, enabled to use refined grids. This new feature allows us to attain higher resolution in our RT simulations and thus to describe more accurately ionisation and temperature patterns in high density regions. We have tested CRASH-AMR by simulating the evolution of an ionised region produced by a single source embedded in gas at constant density, as well as by a more realistic configuration of multiple sources in an inhomogeneous density field. While we find an excellent agreement with the previous version of CRASH when the AMR feature is disabled, showing that no numerical artifact has been introduced in CRASH-AMR, when additional refinement levels are used the code can simulate more accurately the physics of ionised gas in high density regions. This result has been attained at no computational loss, as RT simulations on AMR grids with maximum resolution equivalent to that of a uniform cartesian grid can be run with a gain of up to 60% in computational time.

astro-ph.CO↗

arXiv2016

Modelling social identification and helping in evacuation simulation

Social scientists have criticised computer models of pedestrian streams for their treatment of psychological crowds as mere aggregations of individuals. Indeed most models for evacuation dynamics use analogies from physics where pedestrians are considered as particles. Although this ensures that the results of the simulation match important physical phenomena, such as the deceleration of the crowd with increasing density, social phenomena such as group processes are ignored. In particular, people in a crowd have social identities and share those social identities with the others in the crowd. The process of self categorisation determines norms within the crowd and influences how people will behave in evacuation situations. We formulate the application of social identity in pedestrian simulation algorithmically. The goal is to examine whether it is possible to carry over the psychological model to computer models of pedestrian motion so that simulation results correspond to observations from crowd psychology. That is, we quantify and formalise empirical research on and verbal descriptions of the effect of group identity on behaviour. We use uncertainty quantification to analyse the model's behaviour when we vary crucial model parameters. In this first approach we restrict ourselves to a specific scenario that was thoroughly investigated by crowd psychologists and where some quantitative data is available: the bombing and subsequent evacuation of a London underground tube carriage on July 7th 2005.

physics.soc-ph↗