arXiv subjects

Daniel Mira

Publications and source records attributed to Daniel Mira.

13 recordsLinked to original sources

arXiv2026

Preferential and differential diffusion in RANS simulation of lean hydrogen flames with tabulated chemistry

Lean hydrogen flames are prone to thermo-diffusive instabilities due to preferential and differential diffusion effects, posing significant challenges for their modeling in computational fluid dynamics simulations. This work extends a tabulated-chemistry (TC) model that includes preferential and differential diffusion effects to a Reynolds-averaged Navier-Stokes (RANS) framework and assesses its performance for a lean premixed $\mathrm{H_2}$-air slot burner at two Reynolds numbers ($\mathrm{Re}=5500$ and $11000$) using direct numerical simulation (DNS) as a reference. The approach is based on transport equations for the progress variable and mixture fraction derived from the species mass transport equations considering mixture-averaged diffusion and Soret effect, and incorporates turbulence--chemistry interaction via a presumed probability density function (PDF) approach. RANS simulations including preferential-differential diffusion are able to correctly reproduce the DNS flame length, heat-release distribution, and the characteristic equivalence-ratio and super-adiabatic temperature branches of the slot flame. Comparisons with (i) a unity-Lewis-number variant and (ii) a model including thermo-diffusive effects only in the flamelet table show the impact of preferential and differential diffusion on the TC model at both the thermochemical and transport levels. Finally, the impact of the turbulence closures for turbulent diffusion, scalar dissipation rate, and Reynolds stresses is assessed. The results presented in this paper demonstrate the capability of the model to include preferential and differential diffusion effects in cost-effective RANS simulations of lean hydrogen flames.

physics.flu-dyn↗

arXiv2026

Large-eddy simulations of a lean hydrogen premixed turbulent jet flame with tabulated chemistry

Large-eddy simulations (LES) of a planar turbulent lean hydrogen-air jet flame at Re = 11000 are performed using a tabulated flamelet model based on mixture-averaged diffusion that incorporates detailed transport, including differential and preferential diffusion, wall heat loss, and thermodiffusion. The approach is extended to turbulent combustion in LES using a presumed-shape probability density function formulation that accounts for sub-filter effects. The flame exhibits a highly corrugated front, driven by local variations of mixture fraction induced by strong thermodiffusive transport. These effects significantly alter both the flame structure and morphology. The LES results are systematically compared to a reference direct numerical simulation across varying LES filters through different mesh resolutions to evaluate the predictive capability of the model. The LES accurately reproduces instantaneous flow structures and thermodiffusive effects. Global flame characteristics including flame length, surface area, and consumption speed, are well captured and show limited sensitivity to mesh resolution. The role of thermodiffusion is also examined, showing that its incorporation leads to a more reactive flame and should not be neglected in the formulation. Heat losses are incorporated into the tabulated chemistry framework for completeness but are found to have a negligible impact, consistent with the walls weak influence in the present configuration. Overall, the results demonstrate that the proposed approach provides reliable predictions of the main flame characteristics, with remaining discrepancies primarily associated with unresolved sub-filter effects that deserve further investigation.

physics.flu-dyn↗

arXiv2026

On the spatial structure and intermittency of soot in a lab-scale gas turbine combustor: Insights from large-eddy simulations

This work presents a numerical investigation of soot formation in the Cambridge lab-scale gas turbine combustor. Large-eddy simulations (LES) of a swirl-stabilized ethylene flame are performed using the flamelet generated manifold method coupled with a discrete sectional model to account for soot formation, growth, and oxidation. The study aims to elucidate the mechanism governing the spatial structure and intermittency of soot, supported by comparisons with experimental data. The predicted soot distribution agrees well with measurements, with peak concentrations near the bluff body. Flow recirculation is identified as the key mechanism driving soot accumulation in fuel-rich regions, where surface reactions dominate soot mass growth. Soot intermittency arises from fluctuations in the flow field driven by interactions between the flame front and the recirculation vortex. Two soot modeling approaches are evaluated, differing in their treatment of soot model quantities: the first approach employs on-the-fly computation of source terms (FGM-C), while the second uses fully pre-tabulated source terms (FGM-T). Their predictive performance and computational cost are compared in the context of unsteady, sooting flames in swirl-stabilized combustors.

physics.flu-dyn↗

arXiv2025

Projection-based stabilization for high-order incompressible flow solvers

This work presents a novel stabilization strategy for the Galerkin formulation of the incompressible Navier-Stokes equations, developed to achieve high accuracy while ensuring convergence and compatibility with high-order elements on unstructured meshes. The numerical algorithm employs a fractional step method with carefully defined boundary conditions to obtain a consistent pressure field, enabling high-order temporal accuracy. The proposed stabilization is seamlessly integrated into the algorithm and shares the same underlying principle as the natural stabilization inherent in the fractional step method, both rely on the difference between the gradient operator and its projection. The numerical dissipation associated to the stabilization term is found to diminish with increasing polynomial order of the elements. Numerical test cases confirm the effectiveness of the method, demonstrating convergence under mesh refinement and increasing polynomial order.

math.NA↗

arXiv2024

Analysis of thermodiffusive instabilities in hydrogen premixed flames using a tabulated flamelet model

Preferential diffusion plays a critical role in the evolution of lean premixed hydrogen flames, influencing flame surface corrugation and overall flame behavior. Simulating such flames with tabulated chemistry (TC) methods remains challenging due to the complexity of flame dynamics. A detailed assessment of flamelet-based manifolds for capturing these dynamics is still needed. This work incorporates preferential diffusion via mixture-averaged molecular diffusion within TC to study the propagation and structure of freely propagating hydrogen flames influenced by intrinsic instabilities. Model performance is evaluated against detailed chemistry (DC) calculations, focusing on linear and non-linear regimes and sensitivity to pressure and temperature variations. The impact of mesh resolution on flame response is also examined to assess the method's capabilities without subgrid models. The linear regime is analyzed through the dispersion relation, revealing that higher temperature or pressure extends the range of wave numbers accurately predicted by the model, although some overprediction of flame wrinkling in stable regions is observed. The nonlinear regime is assessed by comparing global flame parameters and flame structure to reference solutions, showing that the model captures key flame descriptors with relative errors under 20%. Overall, the model effectively reproduces key effects governing flames with thermodiffusive instabilities, offering a viable alternative to DC at a significantly reduced computational cost.

physics.flu-dyn↗

arXiv2024

Analysis of soot formation in a lab-scale Rich-Quench-Lean combustor using LES with tabulated chemistry

A numerical study of the effects of air dilution on soot formation and particle dynamics in a lab-scale rich-quench-lean (RQL) combustor is presented using large-eddy simulations (LES) with tabulated chemistry. The modelling approach comprises a flamelet generated manifold (FGM) turbulent combustion model and an efficient discrete sectional method with clustering of sections (CDSM) to model soot formation. Three operating conditions are studied including a reference case without secondary air dilution and two cases with varying air dilution levels. For the latter, the split between primary and dilution air is varied from 80:20 to 60:40 expressed in percentage values. The study aims to investigate the effect of air dilution on the formation and oxidation of soot for various air splits using a direct comparison with the available experimental data. The results show a good correlation between predicted flame topology and spatial distribution of the soot volume fraction with the experimental observations. The introduction of air dilution is found to limit the production of soot with a more drastic reduction for the 40% dilution case compared to the 20% condition. Predicted particle size distributions (PSD) from the case without secondary air dilution correlate well with scanning mobility particle sizer (SMPS) measurements although fewer and smaller particles are predicted with air dilution. Leaner mixtures and enhanced oxidation, resulting from the interaction with air dilution jets, favor the decrease in soot formation.

physics.flu-dyn↗

arXiv2023

Assessment of the Flamelet Generated Manifold method with preferential diffusion modelling for the prediction of partially premixed hydrogen flames

This study presents a systematic analysis of the capabilities of a flamelet model based on Flamelet Generated Manifolds (FGM) to reproduce preferential diffusion effects in partially premixed hydrogen flames. Detailed transport effects are accounted for by including a mixture-averaged transport model when building the flamelet database. This approach adds new terms to the transport equations of the controlling variables in the form of diffusive fluxes where the coefficients can be computed from the information contained in the manifold and saved in the flamelet database. The manifold is constructed from the solution of a set of premixed unstretched adiabatic one-dimensional flames with mixture-averaged transport for a range of mixture fraction within the flammability range. Special attention is given to the numerical aspects related to the construction of the chemical manifold to reduce the numerical error in evaluating the new terms derived from the preferential diffusion of certain species. Finally, a systematic application of the method to simulate laminar hydrogen flames in various canonical configurations is presented from premixed to stratified flames, including the case of a triple flames with different mixing lengths. The results demonstrate that the method describes accurately the flame structure and propagation velocities at a low cost, showing a remarkable agreement with the detailed chemistry solutions for flame structure and propagation velocity.

physics.flu-dyn↗

arXiv2022

A portable coding strategy to exploit vectorization on combustion simulations

The complexity of combustion simulations demands the latest high-performance computing tools to accelerate its time-to-solution results. A current trend on HPC systems is the utilization of CPUs with SIMD or vector extensions to exploit data parallelism. Our work proposes a strategy to improve the automatic vectorization of finite element-based scientific codes. The approach applies a parametric configuration to the data structures to help the compiler detect the block of codes that can take advantage of vector computation while maintaining the code portable. A detailed analysis of the computational impact of this methodology on the different stages of a CFD solver is studied on the PRECCINSTA burner simulation. Our parametric implementation has proven to help the compiler generate more vector instructions in the assembly operation: this results in a reduction of up to 9.3 times of the total executed instruction maintaining constant the Instructions Per Cycle and the CPU frequency. The proposed strategy improves the performance of the CFD case under study up to 4.67 times on the MareNostrum 4 supercomputer.

cs.DC↗

arXiv2022

Dynamic load balance of chemical source term evaluation in high-fidelity combustion simulations

This paper presents a load balancing strategy for reaction rate evaluation and chemistry integration in reacting flow simulations. The large disparity in scales during combustion introduces stiffness in the numerical integration of the PDEs and generates load imbalance during the parallel execution. The strategy is based on the use of the DLB library to redistribute the computing resources at node level, lending additional CPU-cores to higher loaded MPI processes. This approach does not require explicit data transfer and is activated automatically at runtime. Two chemistry descriptions, detailed and reduced, are evaluated on two different configurations: laminar counterflow flame and a turbulent swirl-stabilized flame. For single-node calculations, speedups of 2.3x and 7x are obtained for the detailed and reduced chemistry, respectively. Results on multi-node runs also show that DLB improves the performance of the pure-MPI code similar to single node runs. It is shown DLB can get performance improvements in both detailed and reduced chemistry calculations.

physics.flu-dyn↗

arXiv2022

Evaporation of volatile droplets subjected to flame-like conditions

This work assesses Lagrangian droplet evaporation models frequently used in spray combustion simulations, with the purpose of identifying the influence of modeling decisions on the single droplet behavior. Besides more simplistic models, the evaluated strategies include a simple method to incorporate Stefan flow effects in the heat transfer (Bird's correction), a method to consider the interaction of Stefan flow with the heat and mass transfer films (Abramzon-Sirignano model), and a method to incorporate non-equilibrium thermodynamics (Langmuir-Knudsen model). The importance of each phenomena is quantified analytically and numerically under various conditions. Evaporation models ignoring Stefan flow are found to be invalid under the studied conditions. The Langmuir-Knudsen model is also deemed inadequate for high temperature evaporation, while Bird's correction and the Abramzon-Sirignano model are identified as the most relevant for numerical studies of spray combustion systems. Latter is the most elaborate model studied here, as it considers Reynolds number effects beyond the empirical correlation of Ranz and Marshall derived for low-transfer rates. Thus, the Abramzon-Sirignano model is identified as the state of the art alternative in the scope of this study.

physics.flu-dyn↗

arXiv2021

Prediction of liquid fuel properties using machine learning models with Gaussian processes and probabilistic conditional generative learning

Accurate determination of fuel properties of complex mixtures over a wide range of pressure and temperature conditions is essential to utilizing alternative fuels. The present work aims to construct cheap-to-compute machine learning (ML) models to act as closure equations for predicting the physical properties of alternative fuels. Those models can be trained using the database from MD simulations and/or experimental measurements in a data-fusion-fidelity approach. Here, Gaussian Process (GP) and probabilistic generative models are adopted. GP is a popular non-parametric Bayesian approach to build surrogate models mainly due to its capacity to handle the aleatory and epistemic uncertainties. Generative models have shown the ability of deep neural networks employed with the same intent. In this work, ML analysis is focused on a particular property, the fuel density, but it can also be extended to other physicochemical properties. This study explores the versatility of the ML models to handle multi-fidelity data. The results show that ML models can predict accurately the fuel properties of a wide range of pressure and temperature conditions.

stat.ML↗

arXiv2021

Performance assessment of CUDA and OpenACC in large scale combustion simulations

GPUs have climbed up to the top of supercomputer systems making life harder to many legacy scientific codes. Nowadays, many recipes are being used in such code's portability, without any clarity of which is the best option. We present a comparative analysis of the two most common approaches, CUDA and OpenACC, into the multi-physics CFD code Alya. Our focus is the combustion problems which are one of the most computing demanding CFD simulations. The most computing-intensive parts of the code were analyzed in detail. New data structures for the matrix assembly step have been created to facilitate a SIMD execution that benefits vectorization in the CPU and stream processing in the GPU. As a result, the CPU code has improved its performance by up to 25%. In GPU execution, CUDA has proven to be up to 2 times faster than OpenACC for the assembly of the matrix. On the contrary, similar performance has been obtained in the kernels related to vector operations used in the linear solver, where there is minimal memory reuse.

cs.DC↗

arXiv2014

Alya: Towards Exascale for Engineering Simulation Codes

Alya is the BSC in-house HPC-based multi-physics simulation code. It is designed from scratch to run efficiently in parallel supercomputers, solving coupled problems. The target domain is engineering, with all its particular features: complex geome- tries and unstructured meshes, coupled multi-physics with exotic coupling schemes and Physical models, ill-posed problems, flexibility needs for rapidly including new models, etc. Since its conception in 2004, Alya has shown scaling behaviour in an increasing number of cores. In this paper, we present its performance up to 100.000 cores in Blue Waters, the NCSA supercomputer. The selected tests are representative of the engineering world, all the problematic features included: incompressible flow in a hu- man respiratory system, low Mach combustion problem in a kiln furnace and coupled electro-mechanical problem in a heart. We show scalability plots for all cases, discussing all the aspects of such kind of simulations, including solvers convergence.

physics.comp-ph↗