Impact

The ultimate benefits of ground-breaking research like the one proposed in NUMEXAS is hard to predict. After all, the impact of the application of any new class of computer hardware only materializes once the software codes have been developed for it. However, one can already discern clearly the following benefits of the research proposed. Namely:

  • Development of new numerical algorithms and computational techniques along the complete simulation pipeline for large-scale multidisciplinary problems: pre-processing, grid generation, domain splitting, domain renumbering, field solvers, optimized designs and post-processing;
  • Pushing the state-of-the-art in high-end scientific and industrial computing; enabling for example:
    • Basic research: Turbulent Flows (e.g. LES calculation around an airplane or car); Chemically Reacting Flows (e.g. LES calculation of mixing and combustion in an engine); Cell and DNA studies, etc.
    • Applied research: Detailed blast simulations with dispersed liquids; Dispersion in urban environments; Analysis of constructions to natural hazards; Magnetohydrodynamics (e.g. physical phenomena in fusion technology); Acoustics (e.g. noise generation/coupling to structures for cars or airplanes); Molecular Design; Virtual Human simulations, etc.

More specifically, we can detail these benefits according to the different audiences: academic, industrial and social.

Academic impact

There is a large need of new software that is specifically designed and targeted to be used in high performance computers platforms, and more precisely for the upcoming exascale generation infrastructures.

This need spans along the entire simulation pipeline (from pre-processing to solvers and post-processing), since most of today’s available software was developed to run on scalar machines. Porting all these codes to run on parallel machines (and particularly at the exascale range) is not just a matter of scalability. In most of the cases it requires a new reformulation of the routines and numerical methods, which have to be designed to perform at its best under the new infrastructure paradigm.

The following list describes the scientific impact of the numerical methods and tools developed in NUMEXAS:

  • New pre-processing tools for large-scale real application problems, addressing problems with large number of surfaces
  • New grid generation methods, both structured and unestructred, including remeshing capabilities and mesh expliting
  • New field solvers designed to be run for grids over billions of elements, both implicit and explicit,  considering uncertainty and optimization
  • New efficient, reduced-order post-processing tools including minimization of data transferring

Industrial impact

Industry has a dual role in high-end computing: firstly, supplying systems, technologies and software services for HPC; and secondly, using HPC to innovate in products, processes and services. Both are important in making Europe more competitive. Especially for SMEs, access to HPC, modelling, simulation, product prototyping services and consulting is important to remain competitive. The PRACE Action Plan advocates for a dual approach: strengthening both the industrial demand and supply of HPC.

The actions carried out in NUMEXAS are clearly aligned with the first approach mentioned, and the impacts that the project will have on industries are numerous. In a generic way, the outcome of NUMEXAS will be a set of new numerical methods and codes that will allow industries to solve large-scale problem of high added economic value.

Specific industrial impact

The following list enumerates some of the identified specific industrial problems/areas where the outcomes of the project can result in an important leap in their respective fields. Some of them will be explicitly treated within the framework of the project (WP9), but many other are on the list, waiting for the necessary tools to take the final leap towards solving real-scale problems.

  • New techniques for computer-aided optimum design of new engineering materials
  • New techniques for computer-aided optimum design of engineering systems considering uncertainties
  • New methods for enhanced performance constructions against natural hazards, involving outstanding particulate water flows
  • Prediction of noise generated by vehicles (cars, trains, airplanes) and machinery
  • Study of the SAR of an object, accounting for all the electromagnetics-thermal-mechanical couplings
  • Computation of the radar-cross-section of a ship or an airplane at realistic Reynolds- numbers
  • Study of the hydrodynamic and structural performance of ships, offshore platforms and wind turbines structures in open sea
  • Optimum design of selected industrial forming processes: Sheet Metal Forming, Casting, Metal Deposition and Welding

Quantech will lead the industrial vision within the Numexas consortium, as company developer of software for the stamping and casting sectors, two of the most relevant ones in the economy of the countries.

Social impact

From the social point of view, High-Performance Computing (HPC) will lead us to Enhanced design and manufacturing of economic, safer and environmental friendly industrial products and structures in many engineering sectors: Aero-Space Engineering, Civil Engineering, Naval and Marine Engineering and Surface Transport Vehicles.

Of particular social impact is the development of new simulation methods able to solve problems of interest for predictive safety of civil constructions to natural hazards. These constructions include: buildings, bridges, harbours, dams, dykes, breakwaters, and similar infrastructure under extraordinary forces due to water hazards such as floods, sea waves and tsunamis, water spills due to the collapse of dams, dykes and reservoirs induced by landslides and earthquakes, among others. The output of this research is essential for enhanced analysis, risk assessment and performance-based design of constructions, to protect population and infrastructure against natural hazards.


Monday, November 20, 2017
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The research leading to these results has received funding from the European Community's Seventh Framework Programme under grant agreement n° 611636