Visual Analytics for Complex Engineering Systems: Hybrid Visual Steering of Simulation Ensembles

Abstract

In this paper we propose a novel approach to hybrid visual steering of simulation ensembles. A simulation ensemble is a collection of simulation runs of the same simulation model using different sets of control parameters. Complex engineering systems have very large parameter spaces so a naïve sampling can result in prohibitively large simulation ensembles. Interactive steering of simulation ensembles provides the means to select relevant points in a multi-dimensional parameter space (design of experiment). Interactive steering efficiently reduces the number of simulation runs needed by coupling simulation and visualization and allowing a user to request new simulations on the fly. As system complexity grows, a pure interactive solution is not always sufficient. The new approach of hybrid steering combines interactive visual steering with automatic optimization. Hybrid steering allows a domain expert to interactively (in a visualization) select data points in an iterative manner, approximate the values in a continuous region of the simulation space (by regression) and automatically find the "best" points in this continuous region based on the specified constraints and objectives (by optimization). We argue that with the full spectrum of optimization options, the steering process can be improved substantially. We describe an integrated system consisting of a simulation, a visualization, and an optimization component. We also describe typical tasks and propose an interactive analysis workflow for complex engineering systems. We demonstrate our approach on a case study from automotive industry, the optimization of a hydraulic circuit in a high pressure common rail Diesel injection system.

Visualization System Requirements for Data Processing Pipeline Design and Optimization

“…The support ranges from iterative user-defined selection of model parameters [42], [46], to automated parameter selection (e.g., by random or regular sampling [12], [13], [29]). Moreover, hybrid approaches combine user steering and automatic parameter value sampling [63].…”

“…One notable exemplar is a system that pre-computes heterogeneity information (e.g., gradients), to provide hints about the most promising paths in time and parameter scale, from which users interactively make specific choices for refinement [63]. In another approach, users explore one or two parameters at a time, by interactively calculating the output variation in those parameter dimensions [9].…”

“…Alternatively, inputs and outputs can be shown in linked views with brushing and filtering [63]. The Influence Explorer allows correspondences to be investigated from opposite perspectives, via a Parameters Window (an input perspective) and a Performances Window (an output perspective) [73].…”

Interactive visual analysis of large simulation ensembles

“…Computational steering and interactive visualization are visualization paradigms for the computational sciences (Chen, Rine, and Simon 1996) enabling users to interactively steer computations, change simulation parameters and instantly see the simulation results. In this paper we deal with the ensemble steering Hauser 2008, Matković, Gračanin, Splechtna, Jelović, Stehno, Hauser, andPurgathofer 2014). We do not steer a single simulation, but the creation of an entire ensemble.…”

“…In this paper, we describe our experience with the ensemble simulation of injection systems (Konyha, Matković, Gračanin, Jelović, and Hauser 2006), (Matković, Gračanin, Jelović, and Hauser 2008), (Matković, Gračanin, Splechtna, Jelović, Stehno, Hauser, and Purgathofer 2014). We describe how interactive visual analysis helps to exploit opportunities that emerge from advanced ensemble simulation.…”