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Modern supercomputers allow the simulation of complex phenomena with increased accuracy. Eventually, this requires finer geometric discretizations with larger numbers of mesh elements. In this context, and extrapolating to the Exascale paradigm, meshing operations such as generation, adaptation or partition, become a critical issue within the simulation workflow. In this paper, we focus on mesh partitioning. In particular, we present some improvements carried out on an in-house parallel mesh partitioner based on the Hilbert Space-Filling Curve. Additionally, taking advantage of its performance, we present the application of the SFC-based partitioning for dynamic load balancing. This method is based on the direct monitoring of the imbalance at runtime and the subsequent re-partitioning of the mesh. The target weights for the optimized partitions are evaluated using a least-squares approximation considering all measurements from previous iterations. In this way, the final partition corresponds to the average performance of the computing devices engaged. ; This work is partially supported by the BSC-IBM Deep Learning Research Agreement, under JSA "Application porting, analysis and optimization for POWER and POWERAI". It has also been partially supported by the EXCELLERAT project funded by the European Commission's ICT activity of the H2020 Programme under grant agreement number: 823691. It has also received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement number: 846139 (Exa-FireFlows). This paper expresses the opinions of the authors and not necessarily those of the European Commission. The European Commission is not liable for any use that may be made of the information contained in this paper. This work has also been financially supported by the Ministerio de Economia, Industria y Competitividad, of Spain (TRA2017-88508-R). The computing experiments of this paper have been performed on the resources of the Barcelona Supercomputing Center. ; Peer Reviewed ; Postprint (author's final draft)

Computational Fluid and Particle Dynamics (CFPD) simulations are of paramount importance for studying and improving drug effectiveness. Computational requirements of CFPD codes demand high-performance computing (HPC) resources. For these reasons we introduce and evaluate in this paper system software techniques for improving performance and tolerate load imbalance on a state-of-the-art production CFPD code. We demonstrate benefits of these techniques on Intel-, IBM-, and Arm-based HPC technologies ranked in the Top500 supercomputers, showing the importance of using mechanisms applied at runtime to improve the performance independently of the underlying architecture. We run a real CFPD simulation of particle tracking on the human respiratory system, showing performance improvements of up to 2x, across different architectures, while applying runtime techniques and keeping constant the computational resources. ; This work is partially supported by the Spanish Government (SEV-2015-0493), by the Spanish Ministry of Science and Technology project (TIN2015-65316-P), by the Generalitat de Catalunya (2017-SGR-1414), and by the European Mont-Blanc projects (288777, 610402 and 671697). ; Peer Reviewed ; Preprint

Computational Fluid and Particle Dynamics (CFPD) simulations are of paramount importance for studying and improving drug effectiveness. Computational requirements of CFPD codes demand high-performance computing (HPC) resources. For these reasons we introduce and evaluate in this paper system software techniques for improving performance and tolerate load imbalance on a state-of-the-art production CFPD code. We demonstrate benefits of these techniques on Intel-, IBM-, and Arm-based HPC technologies ranked in the Top500 supercomputers, showing the importance of using mechanisms applied at runtime to improve the performance independently of the underlying architecture. We run a real CFPD simulation of particle tracking on the human respiratory system, showing performance improvements of up to 2x, across different architectures, while applying runtime techniques and keeping constant the computational resources. ; This work is partially supported by the Spanish Government (SEV-2015-0493), by the Spanish Ministry of Science and Technology project (TIN2015-65316-P), by the Generalitat de Catalunya (2017-SGR-1414), and by the European Mont-Blanc projects (288777, 610402 and 671697). ; Peer Reviewed ; Preprint

This work addresses the prediction of the reacting flow field in a swirl stabilized gas turbine model combustor using large-eddy simulation. The modeling of the combustion chemistry is based on laminar premixed flamelets and the effect of turbulence-chemistry interaction is considered by a presumed shape probability density function. The prediction capabilities of the presented combustion model for perfectly premixed and partially premixed conditions are demonstrated. The effect of partial premixing for the prediction of the reacting flow field is assessed by comparison of a perfectly premixed and partially premixed simulation. Even though significant mixture fraction fluctuations are observed, only small impact of the non-perfect premixing is found on the flow field and flame dynamics. Subsequently, the effect of heat loss to the walls is assessed assuming perfectly premixing. The adiabatic baseline case is compared to heat loss simulations with adiabatic and non-adiabatic chemistry tabulation. The results highlight the importance of considering the effect of heat loss on the chemical kinetics for an accurate prediction of the flow features. Both heat loss simulations significantly improve the temperature prediction, but the non-adiabatic chemistry tabulation is required to accurately capture the chemical composition in the reacting layers. ; The research leading to these results has received funding through the People Program (Marie Curie Actions) of the European Union's Seventh Framework Program (FP7, 2007-2013) for the project COPA-GT (grant agreement No. FP7-290042) as well as the European Union's Horizon 2020 Program (2014-2020) and the Brazilian Ministry of Science, Technology and Innovation through Rede Nacional de Pesquisa (RNP) under the HPC4E Project (grant agreement No. 689772). Furthermore, computer resources and technical assistance has been provided by the Red Española de Supercomputación (RES) (grant numbers FI-2015-1-0002, FI-2015-3-0013, FI-2016-1-0001). ; Peer Reviewed ; Postprint (published version)

This work addresses the prediction of the reacting flow field in a swirl stabilized gas turbine model combustor using large-eddy simulation. The modeling of the combustion chemistry is based on laminar premixed flamelets and the effect of turbulence-chemistry interaction is considered by a presumed shape probability density function. The prediction capabilities of the presented combustion model for perfectly premixed and partially premixed conditions are demonstrated. The effect of partial premixing for the prediction of the reacting flow field is assessed by comparison of a perfectly premixed and partially premixed simulation. Even though significant mixture fraction fluctuations are observed, only small impact of the non-perfect premixing is found on the flow field and flame dynamics. Subsequently, the effect of heat loss to the walls is assessed assuming perfectly premixing. The adiabatic baseline case is compared to heat loss simulations with adiabatic and non-adiabatic chemistry tabulation. The results highlight the importance of considering the effect of heat loss on the chemical kinetics for an accurate prediction of the flow features. Both heat loss simulations significantly improve the temperature prediction, but the non-adiabatic chemistry tabulation is required to accurately capture the chemical composition in the reacting layers. ; The research leading to these results has received funding through the People Program (Marie Curie Actions) of the European Union's Seventh Framework Program (FP7, 2007-2013) for the project COPA-GT (grant agreement No. FP7-290042) as well as the European Union's Horizon 2020 Program (2014-2020) and the Brazilian Ministry of Science, Technology and Innovation through Rede Nacional de Pesquisa (RNP) under the HPC4E Project (grant agreement No. 689772). Furthermore, computer resources and technical assistance has been provided by the Red Española de Supercomputación (RES) (grant numbers FI-2015-1-0002, FI-2015-3-0013, FI-2016-1-0001). ; Peer Reviewed ; Postprint (published version)

The present work addresses the coupling of a flamelet database, to a low-Mach approximation of the Navier–Stokes equations using scalar controlling variables. The model is characterized by the chemistry tabulation based on laminar premixed flamelets in combination with an optimal choice of the reaction progress variable, which is determined based on the computational singular perturbation (CSP) method. The formulation of the model focuses on turbulent premixed flames taking into account the effect of heat losses, but it is easily extended to partially premixed and non-premixed regimes. The model is designed for applications in both, Reynolds-averaged Navier–Stokes (RANS) as well as large-eddy simulations (LES) and results for the two methods are compared. A priori analysis of the database is presented to demonstrate the influence of the reaction progress definition and the chemistry tabulation is validated against a one-dimensional premixed laminar flame. The validation of the turbulent case is performed using a tur- bulent premixed confined jet flame subject to strong heat losses, in which the model shows a good overall performance. ; The research leading to these results has received funding through the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7, 2007– 2013) under the grant agreement No. FP7-290042 for the project COPA-GT. The authors thankfully acknowledge the computer resources, technical expertise and assistance provided by the Red Española de Supercomputación (RES). Finally, the authors would like to thank O. Lammel for kindly providing the data for comparison. ; Peer Reviewed ; Postprint (author's final draft)

The present work addresses the coupling of a flamelet database, to a low-Mach approximation of the Navier–Stokes equations using scalar controlling variables. The model is characterized by the chemistry tabulation based on laminar premixed flamelets in combination with an optimal choice of the reaction progress variable, which is determined based on the computational singular perturbation (CSP) method. The formulation of the model focuses on turbulent premixed flames taking into account the effect of heat losses, but it is easily extended to partially premixed and non-premixed regimes. The model is designed for applications in both, Reynolds-averaged Navier–Stokes (RANS) as well as large-eddy simulations (LES) and results for the two methods are compared. A priori analysis of the database is presented to demonstrate the influence of the reaction progress definition and the chemistry tabulation is validated against a one-dimensional premixed laminar flame. The validation of the turbulent case is performed using a tur- bulent premixed confined jet flame subject to strong heat losses, in which the model shows a good overall performance. ; The research leading to these results has received funding through the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7, 2007– 2013) under the grant agreement No. FP7-290042 for the project COPA-GT. The authors thankfully acknowledge the computer resources, technical expertise and assistance provided by the Red Española de Supercomputación (RES). Finally, the authors would like to thank O. Lammel for kindly providing the data for comparison. ; Peer Reviewed ; Postprint (author's final draft)

This study is focused on the numerical investigation of reduced chemical schemes for high pressure spray flames of oxymethylene ethers (OMEx). A reduced mechanism using Path Flux Analysis (PFA) technique is tested using an a priori and a posteriori evaluation under the ECN Spray A nominal conditions. The global flame metrics for spray A along with the flame shape are well reproduced by the reduced mechanism, which encourages its use for practical applications. ; The research leading to these results has received funding through the ENERXICO project from the European Union's Horizon 2020 Programme, grant agreement n 828947, and from the Mexican Department of Energy, CONACYT-SENER Hidrocarburos grant agreement n B-S-69926 and the Spanish Ministry of Economy and Competitiveness in the frame of the CHEST project (TRA2017-89139-C2-2- R). The authors thankfully acknowledge the computer resources at MareNostrum and the technical support provided by Barcelona Supercomputing Center (IM- 2021-1-0014, IM-2020-3-0029, IM-2020-2-0023,IM- 2020-1-0013). ; Peer Reviewed ; Postprint (published version)

The presented work addresses the investigation of the heat loss of a confined turbulent jet flame in a lab-scale combustor using a conjugate-heat transfer approach and large-eddy simulation. The analysis includes the assessment of the principal mechanisms of heat transfer in this combustion chamber: radiation, convection and conduction of heat over walls. A staggered approach is used to couple the reactive flow field to the heat conduction through the solid and both domains are solved using two implementations of the same code. Numerical results are compared against experimental data and an assessment of thermal boundary conditions to improve the prediction of the reactive flow field is given. ; The research leading to these results has received funding through the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7, 2007–2013) under the Grant agreement No. FP7-290042 for the project COPA-GT as well as the European Union's Horizon 2020 Programme (2014–2020) and from Brazilian Ministry of Science, Technology and Innovation through Rede Nacional de Pesquisa (RNP) under the HPC4E Project, Grant agreement No. 689772. The authors thankfully acknowledge the computer resources, technical expertise and assistance provided by the Red Española de Supercomputación (RES). Finally, the authors would like to thank O. Lammel for the useful discussions and kindly providing the data for the comparison. ; Peer Reviewed ; Postprint (published version)

The presented work addresses the investigation of the heat loss of a confined turbulent jet flame in a lab-scale combustor using a conjugate-heat transfer approach and large-eddy simulation. The analysis includes the assessment of the principal mechanisms of heat transfer in this combustion chamber: radiation, convection and conduction of heat over walls. A staggered approach is used to couple the reactive flow field to the heat conduction through the solid and both domains are solved using two implementations of the same code. Numerical results are compared against experimental data and an assessment of thermal boundary conditions to improve the prediction of the reactive flow field is given. ; The research leading to these results has received funding through the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7, 2007–2013) under the Grant agreement No. FP7-290042 for the project COPA-GT as well as the European Union's Horizon 2020 Programme (2014–2020) and from Brazilian Ministry of Science, Technology and Innovation through Rede Nacional de Pesquisa (RNP) under the HPC4E Project, Grant agreement No. 689772. The authors thankfully acknowledge the computer resources, technical expertise and assistance provided by the Red Española de Supercomputación (RES). Finally, the authors would like to thank O. Lammel for the useful discussions and kindly providing the data for the comparison. ; Peer Reviewed ; Postprint (published version)

The presented work addresses the investigation of the heat loss of a confined turbulent jet flame in a lab-scale combustor using a conjugate-heat transfer approach and large-eddy simulation. The analysis includes the assessment of the principal mechanisms of heat transfer in this combustion chamber: radiation, convection and conduction of heat over walls. A staggered approach is used to couple the reactive flow field to the heat conduction through the solid and both domains are solved using two implementations of the same code. Numerical results are compared against experimental data and an assessment of thermal boundary conditions to improve the prediction of the reactive flow field is given. © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CCBY license (http://creativecommons.org/licenses/by/4.0/). ; The research leading to these results has received funding through the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7, 2007–2013) under the Grant agreement No. FP7-290042 for the project COPA-GT as well as the European Union's Horizon 2020 Programme (2014–2020) and from Brazilian Ministry of Science, Technology and Innovation through Rede Nacional de Pesquisa (RNP) under the HPC4E Project, Grant agreement No. 689772. The authors thankfully acknowledge the computer resources, technical expertise and assistance provided by the Red Española de Super-computación (RES). Finally, the authors would like to thank O. Lammel for the useful discussions and kindly providing the data for the comparison. ; Peer Reviewed

The main computing tasks of a finite element code(FE) for solving partial differential equations (PDE's) are the algebraic system assembly and the iterative solver. This work focuses on the first task, in the context of a hybrid MPI+X paradigm. Although we will describe algorithms in the FE context, a similar strategy can be straightforwardly applied to other discretization methods, like the finite volume method. The matrix assembly consists of a loop over the elements of the MPI partition to compute element matrices and right-hand sides and their assemblies in the local system to each MPI partition. In a MPI+X hybrid parallelism context, X has consisted traditionally of loop parallelism using OpenMP. Several strate- gies have been proposed in the literature to implement this loop parallelism, like coloring or substructuring techniques to circumvent the race condition that appears when assembling the element system into the local system. The main drawback of the first technique is the decrease of the IPC due to bad spatial locality. The second technique avoids this issue but requires extensive changes in the implementation, which can be cumbersome when several element loops should be treated. We propose an alternative, based on the task parallelism of the element loop using some extensions to the OpenMP programming model. The task- ification of the assembly solves both aforementioned problems. In addition, dynamic load balance will be applied using the DLB library, especially efficient in the presence of hybrid meshes, where the relative costs of the different elements is impossible to estimate a priori. This paper presents the proposed methodology, its implementation and its validation through the solution of large computational mechanics problems up to 16k cores. ; The use of large part of a supercomputer, even more in normal conditions of use, is never an innocuous exercise. The research leading to these results has received funding from: the European Union's Horizon 2020 Programme (2014–2020) and from Brazilian Ministry of Science, Technology and Innovation through Rede Nacional de Pesquisa (RNP), HPC4E Project, grant agreement 689772; the Energy oriented Centre of Excellence (EoCoE), grant agreement number 676629, funded within the Horizon2020 framework of the European Union; The Spanish Government (grant SEV2015-0493 of the Severo Ochoa Program); the Spanish Ministry of Science and Innovation (contract TIN2015-65316-P); the Generalitat de Catalunya (contract 2014-SGR-1051); the Intel-BSC Exascale Lab collaboration project. Comissió Interdepartamental de Recerca i Innovació Tecnológica(Interdepartmental Commission for Research and Technological Innovation) ; Sí ; Post-print (author's final draft)

Larger supercomputers allow the simulation of more complex phenomena with increased accuracy. Eventually this requires finer and thus also larger geometric discretizations. In this context, and extrapolating to the Exascale paradigm, meshing operations such as generation, deformation, adaptation/regeneration or partition/load balance, become a critical issue within the simulation workflow. In this paper we focus on mesh partitioning. In particular, we present a fast and scalable geometric partitioner based on Space Filling Curves (SFC), as an alternative to the standard graph partitioning approach. We have avoided any computing or memory bottleneck in the algorithm, while we have imposed that the solution achieved is independent (discounting rounding off errors) of the number of parallel processes used to compute it. The performance of the SFC-based partitioner presented has been demonstrated using up to 4096 CPU-cores in the Blue Waters supercomputer. ; The research leading to these results has received funding from the European Union Horizon 2020 Programme (2014-2020) and the Brazilian Ministry of Science, Technology and Innovation through Rede Nacional de Pesquisa (RNP) under the HPC4E Project (grant agreement No. 689772). This work is also part of the PRAC "Simulations of Aircraft Engines" supported by the National Science Foundation. It has also been financially supported by the PRACE preparatory access projects funded in part by the EU Horizon 2020 research and innovation programme (2014-2020) under grant agreement 653838. J.C. Cajas acknowledges the nancial sup- port of the `Consejo Nacional de Ciencia y Tecnolog a (CONACyT, M exico)' grant number 231588 290790. Ricard Borrell and Daniel Mira acknowledge the Juan de la Cierva postdoctoral grants with codes IJCI-2014-21034 and IJCI-2015-26686, respectively. ; Postprint (author's final draft)

Larger supercomputers allow the simulation of more complex phenomena with increased accuracy. Eventually this requires finer and thus also larger geometric discretizations. In this context, and extrapolating to the Exascale paradigm, meshing operations such as generation, deformation, adaptation/regeneration or partition/load balance, become a critical issue within the simulation workflow. In this paper we focus on mesh partitioning. In particular, we present a fast and scalable geometric partitioner based on Space Filling Curves (SFC), as an alternative to the standard graph partitioning approach. We have avoided any computing or memory bottleneck in the algorithm, while we have imposed that the solution achieved is independent (discounting rounding off errors) of the number of parallel processes used to compute it. The performance of the SFC-based partitioner presented has been demonstrated using up to 4096 CPU-cores in the Blue Waters supercomputer. ; The research leading to these results has received funding from the European Union Horizon 2020 Programme (2014-2020) and the Brazilian Ministry of Science, Technology and Innovation through Rede Nacional de Pesquisa (RNP) under the HPC4E Project (grant agreement No. 689772). This work is also part of the PRAC "Simulations of Aircraft Engines" supported by the National Science Foundation. It has also been financially supported by the PRACE preparatory access projects funded in part by the EU Horizon 2020 research and innovation programme (2014-2020) under grant agreement 653838. J.C. Cajas acknowledges the nancial sup- port of the `Consejo Nacional de Ciencia y Tecnolog a (CONACyT, M exico)' grant number 231588 290790. Ricard Borrell and Daniel Mira acknowledge the Juan de la Cierva postdoctoral grants with codes IJCI-2014-21034 and IJCI-2015-26686, respectively. ; Postprint (author's final draft)

The primary purpose of this study is to evaluate the ability of LES, with a turbulent combustion model based on steady flamelets, to predict the flame stabilization mechanisms in an industrial can combustor at full load conditions. The test case corresponds to the downscaled Siemens can combustor tested in the high pressure rig at the DLR. The effects of the wall temperature on the prediction capabilities of the codes is investigated by imposing several heat transfer conditions at the pilot and chamber walls. The codes used for this work are Alya and OpenFOAM, which are well established CFD codes in the fluid mechanics community. Prior to the simulation, results for 1-D laminar flames at the operating conditions of the combustor are compared with the detailed solutions. Subsequently, results from both codes at the mid-plane are compared against the experimental data available. Acceptable results are obtained for the axial velocity, while discrepancies are more evident for the mixture fraction and the temperature, particularly with Alya. However, both codes showed that the heat losses influence the size and length of the pilot and main flame. ; The research leading to these results has received funding through the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7, 2007-2013) under the grant agreement No. FP7-290042 for the project COPA-GT and the European Union's Horizon 2020 Programme (2014-2020) and from Brazilian Ministry of Science, Technology and Innovation through Rede Nacional de Pesquisa (RNP) under the HPC4E Project, grant agreement No. 689772. The authors thankfully acknowledge the computer resources, technical expertise and assistance provided by the Red Española de Supercomputación (RES). ; Peer Reviewed ; Postprint (author's final draft)