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HPC4E Report Summary

Project ID: 689772
Funded under: H2020-EU.2.1.1.

Periodic Reporting for period 1 - HPC4E (HPC for Energy)

Reporting period: 2015-12-01 to 2016-11-30

Summary of the context and overall objectives of the project

HPC4E is appling the new exascale HPC techniques to energy industry simulations, customizing them, and going beyond the state-of-the-art in the required HPC exascale simulations for different energy sources: wind energy production and design, efficient combustion systems for biomass-derived fuels (biogas), and exploration geophysics for hydrocarbon reservoirs.
For wind energy industry HPC is a must. The competitiveness of wind farms can be guaranteed only with accurate wind resource assessment, farm design and short-term micro-scale wind simulations to forecast the daily power production. The use of CFD LES models to analyse atmospheric flow in a wind farm capturing turbine wakes and array effects requires exascale HPC systems.
Biogas, i.e. biomass-derived fuels by anaerobic digestion of organic wastes, is attractive because of its wide availability, renewability and reduction of CO2 emissions, contribution to diversification of energy supply, rural development, and it does not compete with feed and food feedstock. However, its use in practical systems is still limited since the complex fuel composition might lead to unpredictable combustion performance and instabilities in industrial combustors. The next generation of exascale HPC systems will be able to run combustion simulations in parameter regimes relevant to industrial applications using alternative fuels, which is required to design efficient furnaces, engines, clean burning vehicles and power plants.

One of the main HPC consumers is the oil & gas (O&G) industry. The computational requirements arising from full wave-form modelling and inversion of seismic and electromagnetic data is ensuring that the O&G industry will be an early adopter of exascale computing technologies. By taking into account the complete physics of waves in the subsurface, imaging tools are able to reveal information about the Earth’s interior with unprecedented quality.

HPC4E project has three general objectives, what we are working, and a large list of specific technical objectives related with research in each technology:
1. Develop beyond-the-state-of-the-art high performance simulation tools that can help the energy industry to respond future energy demands and also to carbon-related environmental issues using the state-of-the-art HPC systems.
The project is successfully advancing in the deployment of complete simulation environments with a high scalability and industrial use.
2. Improve the cooperation between energy industries from EU and Brazil.
The industrial partners of the project are successfully involved in the use of the technology generated in the project.
3. Improve the cooperation between the leading research centers in EU and Brazil in HPC.
The sharing use of supercomputing infrastructures between Brazil and EU has been started. This includes the main production computers (MareNostrum in Europe, Santos Dumont and Lobo Carneiro in Brazil), some exascale prototypes like Mont-Blanc or Deep and platforms as PlaFRIM.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

During this first period of Project some work has been done at the level of computational kernels and at the level of whole applications. Computational kernels have been ported and optimized for symmetric multi-core processors and accelerators (Xeon Phi and GPUs). This allows us to evaluate the different architecture proposals. In WP3 new parallel algorithms for linear solvers were deployed and tested. Progress has also been made in other tasks in WP3: high order numerical schemes, adaption in time and space, Big Data management for numerical simulations.
In wind energy, the final objective is to improve the forecast of power produc-tion in a wind farm. Two different strategies are going to be tested: dynamical and statistical downscaling. During this period both strategies have been advanced.
In the use of biomass-derived fuels, we aim to characterize completely the combustion process for different fuel compositions. This characterization is done in two steps: creation of data for the tabulated chemistry and the comparison of flame simulation with empirical data. In this period, all the data for the tabulated chemistry was created. The required software to create these data was completely validated.
In exploration geophysics to compare the performace of different full wave-form modelling and inversion codes, we create a synthetic benchmark data set. It is available at the project web site. The integration of different kernels in the industrial codes and the development of strategies for uncertainty quantification are progressing in this period.

More specific technical progress at first year Project:
In HPC and simulation technology, new collaboration opportunities were developed among the partners. Harnessing of computational resources for developing tasks on porting and optimization for HPC novel architectures.
Cutting-edge basic research contributed to the four main aspects involved in the construction of computational simulators, named: numerical schemes for partial differential equations, sparse linear solvers, adaptivity, and data management. Prototype developments/extensions were performed.
During this first year, the main work performed has been the implementation in ALYA of an atmospheric boundary layer (ABL) module for atmospheric flows based on the Reynolds-Averaged Navier-Stokes (RANS) equations together with different modifications of the standard κ-ε turbulence model, considering different physical complexity levels.
We validated the software Cantera for biofuels applications. Other of the work performed has been:
-Assessment of chemical kinetic reduction using Cantera
-Comparison of different detailed schemes for biofuels oxidation
-Comparison of different detailed schemes for biofuels oxidation
-Effects of fuel variability in biogas and bio-syngas thermochemical structures
One of the main goals of geophysics for energy at HPC4E is to develop a public test suite where anyone can test their own geophysical modeling algorithms. The test suites are readily available at the website and they represent challenging scenarios as have been devised by our industrial partners.
As well, we have presented 56 publications on different conferences and journals.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

HPC4E is improving the science at:
1) A new algorithm scheme for high order finite diference stencils on GPUs
2) A new type of high order finite difference for free surface boundary condition on elastic forward modeling
3) A detailed scheme for biogas oxidation
4) A synthetic benchmarch for exascale comparison of FWI codes
5) A new downscaling strategy to connect mesoscale wind data with atmospheric CFD at microscale

The general impacts derived from the efficient use of exascale HPC andsimulation technology are:
• Vast improvement in simulation efficiency in terms of Watts needed per execution and reduced time-to-solution. This will be applied to critical aspects of the energy value chain, with rapid deployment in the partner’ current production systems.
• Establishing transnational “numerical laboratories”, which are cheaper, safer and faster than real-life experiments.
As well, derived from the collaboration between EU-Brazil, we are reinforcing the ties between EU and Brazil in critical aspects for society such as energy.

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