Toward Quantifying Uncertainties in Large-Scale Simulations of Engineering Flows

Author: Niclas Jansson, KTH
Understanding the complex physics of wall-bounded turbulent flows is of utmost importance, considering the presence of this type of flows in various engineering applications. To this end, the use of high-fidelity approaches such as DNS (Direct Numerical Simulation) and LES (Large Eddy Simulation) has proven to be advantageous. There are, however, at least two main challenges that these approaches have to deal with.

Fig. 1. Error isolines of mean velocity profile (top) and turbulent kinetic energy profile (bottom) of turbulent channel flow at friction-based Reynold number 300 simulated by Nek5000

The first is the high computational cost imposed by the requirement of accurately resolving the near-wall region. As a result of the large growth rate of the cost with flow Reynolds (Re) numbers, scale-resolving approaches for many industrial applications are expected to be still out of reach over the future couple of decades, see [1]. Despite this, in moderate range of Re-number, scale-resolving approaches can be successfully employed for complex flows, thanks to the development of the HPC technologies and availability of techniques such as AMR (adaptive mesh refinement) [2] for efficient computing.

In general, the numerical solutions of the Navier-Stokes equations for turbulent flows can be contaminated by some level of uncertainties and errors originating from different sources. These include, but are not limited to, the projection and discretization of the Navier-Stokes Continue reading “Toward Quantifying Uncertainties in Large-Scale Simulations of Engineering Flows”

Enabling the future of CFD for external aerodynamics optimization with exascale systems

Author: Claudio Arlandini, CINECA

The design of the car of the future requires going over the usual RANS approach, since it fails to predict with an acceptable prediction accuracy features like transitional flows, instabilities, noise gneration, combustion efficiency. This in turn requires exascale systems, to sustain more high-fidelity simulations techniques, like LES or DES. EXCELLERAT paves the way to this transition.

Five years ago, a report1 sponsored by NASA documented the results of a study to address the long range, strategic planning required in the area of computational fluid dynamics (CFD), Continue reading “Enabling the future of CFD for external aerodynamics optimization with exascale systems”

Enabling Engineering for the next generation of safety applications using CFD prediction tools

Author: Gabriel Staffelbach, CERFACS
On June 11th, 2019 In Norway, a hydrogen refuelling station exploded. The whole hydrogen refueling station network had to be shut down. Toyota and Hyundai are both halting fuel cell sales in Norway. Elektrek – Hydrogen Station expoldes

As transportation companies struggle to find the way out of fossil fuels,  this event illustrates how safety aspects can become a brutal showstopper. In particular, accelerating too much the release Continue reading “Enabling Engineering for the next generation of safety applications using CFD prediction tools”

Importance of Data Transfer in the Use of High Performance Computing

Author: Janik Schüssler, SSC
One part of EXCELLERAT’s vision is to provide the engineering community with easy access to relevant services and knowledge around high performance computing. The keyword here is ‘Access’.

The idea that HPC centers can offer data calculation and simulation as a service, and thus expand the use of HPC in the industry, is based on transferring data online to HPC centers Continue reading “Importance of Data Transfer in the Use of High Performance Computing”

New analysis methods facilitate the evaluation of complex engineering data

Author: Veronika Scheuer, Fraunhofer SCAI
A further increase in the performance of supercomputers is expected over the next few years. So-called exascale computers will be able to deliver more precise simulations. This leads to considerably more data. Fraunhofer SCAI develops efficient data analysis methods for this purpose, which provide the engineer with detailed insights into the complex technical contexts. Continue reading “New analysis methods facilitate the evaluation of complex engineering data”