Accelerating moderately stiff chemical kinetics in reactive-flow simulations using GPUs

The chemical kinetics ODEs arising from operator-split reactive-flow simulations were solved on GPUs using explicit integration algorithms. Nonstiff chemical kinetics of a hydrogen oxidation mechanism (9 species and 38 irreversible reactions) were computed using the explicit fifth-order Runge-Kutta-Cash-Karp method, and the GPU-accelerated version performed faster than single- and six-core CPU versions by factors of 126 and 25, respectively, for 524,288 ODEs. Moderately stiff kinetics, represented with mechanisms for hydrogen/carbon-monoxide (13 species and 54 irreversible reactions) and methane (53 species and 634 irreversible reactions) oxidation, were computed using the stabilized explicit second-order Runge-Kutta-Chebyshev (RKC) algorithm. The GPU-based RKC implementation demonstrated an increase in performance of nearly 59 and 10 times, for problem sizes consisting of 262,144 ODEs and larger, than the single- and six-core CPU-based RKC algorithms using the hydrogen/carbon-monoxide mechanism. With the methane mechanism, RKC-GPU performed more than 65 and 11 times faster, for problem sizes consisting of 131,072 ODEs and larger, than the single- and six-core RKC-CPU versions, and up to 57 times faster than the six-core CPU-based implicit VODE algorithm on 65,536 ODEs. In the presence of more severe stiffness, such as ethylene oxidation (111 species and 1566 irreversible reactions), RKC-GPU performed more than 17 times faster than RKC-CPU on six cores for 32,768 ODEs and larger, and at best 4.5 times faster than VODE on six CPU cores for 65,536 ODEs. With a larger time step size, RKC-GPU performed at best 2.5 times slower than six-core VODE for 8192 ODEs and larger. Therefore, the need for developing new strategies for integrating stiff chemistry on GPUs was discussed.Comment: 27 pages, LaTeX; corrected typos in Appendix equations A.10 and A.1

Mechanism reduction for multicomponent surrogates: a case study using toluene reference fuels

Strategies and recommendations for performing skeletal reductions of multicomponent surrogate fuels are presented, through the generation and validation of skeletal mechanisms for a three-component toluene reference fuel. Using the directed relation graph with error propagation and sensitivity analysis method followed by a further unimportant reaction elimination stage, skeletal mechanisms valid over comprehensive and high-temperature ranges of conditions were developed at varying levels of detail. These skeletal mechanisms were generated based on autoignition simulations, and validation using ignition delay predictions showed good agreement with the detailed mechanism in the target range of conditions. When validated using phenomena other than autoignition, such as perfectly stirred reactor and laminar flame propagation, tight error control or more restrictions on the reduction during the sensitivity analysis stage were needed to ensure good agreement. In addition, tight error limits were needed for close prediction of ignition delay when varying the mixture composition away from that used for the reduction. In homogeneous compression-ignition engine simulations, the skeletal mechanisms closely matched the point of ignition and accurately predicted species profiles for lean to stoichiometric conditions. Furthermore, the efficacy of generating a multicomponent skeletal mechanism was compared to combining skeletal mechanisms produced separately for neat fuel components; using the same error limits, the latter resulted in a larger skeletal mechanism size that also lacked important cross reactions between fuel components. Based on the present results, general guidelines for reducing detailed mechanisms for multicomponent fuels are discussed.Comment: Accepted for publication in Combustion and Flam

Recent progress and challenges in exploiting graphics processors in computational fluid dynamics

The progress made in accelerating simulations of fluid flow using GPUs, and the challenges that remain, are surveyed. The review first provides an introduction to GPU computing and programming, and discusses various considerations for improved performance. Case studies comparing the performance of CPU- and GPU- based solvers for the Laplace and incompressible Navier-Stokes equations are performed in order to demonstrate the potential improvement even with simple codes. Recent efforts to accelerate CFD simulations using GPUs are reviewed for laminar, turbulent, and reactive flow solvers. Also, GPU implementations of the lattice Boltzmann method are reviewed. Finally, recommendations for implementing CFD codes on GPUs are given and remaining challenges are discussed, such as the need to develop new strategies and redesign algorithms to enable GPU acceleration.Comment: In press in the Journal of Supercomputin

Reduced chemistry for butanol isomers at engine-relevant conditions

Butanol has received significant research attention as a second-generation biofuel in the past few years. In the present study, skeletal mechanisms for four butanol isomers were generated from two widely accepted, well-validated detailed chemical kinetic models for the butanol isomers. The detailed models were reduced using a two-stage approach consisting of the directed relation graph with error propagation and sensitivity analysis. During the reduction process, issues were encountered with pressure-dependent reactions formulated using the logarithmic pressure interpolation approach; these issues are discussed and recommendations made to avoid ambiguity in its future implementation in mechanism development. The performance of the skeletal mechanisms generated here was compared with that of detailed mechanisms in simulations of autoignition delay times, laminar flame speeds, and perfectly stirred reactor temperature response curves and extinction residence times, over a wide range of pressures, temperatures, and equivalence ratios. The detailed and skeletal mechanisms agreed well, demonstrating the adequacy of the resulting reduced chemistry for all the butanol isomers in predicting global combustion phenomena. In addition, the skeletal mechanisms closely predicted the time-histories of fuel mass fractions in homogeneous compression-ignition engine simulations. The performance of each butanol isomer was additionally compared with that of a gasoline surrogate with an antiknock index of 87 in a homogeneous compression-ignition engine simulation. The gasoline surrogate was consumed faster than any of the butanol isomers, with tert-butanol exhibiting the slowest fuel consumption rate. While n-butanol and isobutanol displayed the most similar consumption profiles relative to the gasoline surrogate, the two literature chemical kinetic models predicted different orderings.Comment: 39 pages, 16 figures. Supporting information available via https://doi.org/10.1021/acs.energyfuels.6b0185

Fighting obesity by targeting factors regulating beige adipocytes.

Purpose of reviewThe current review provides an update on secreted factors and mechanisms that promote a thermogenic program in beige adipocytes, and their potential roles as therapeutic targets to fight obesity.Recent findingsWe outline recent studies revealing unrecognized mechanisms controlling beige adipocyte physiology, and summarize in particular those that underlie beige thermogenesis independently of classical uncoupling. We also update strategies aimed at fostering beige adipogenesis and white-to beige adipocyte conversion. Finally, we summarize newly identified endogenous secreted factors that promote the thermogenic activation of beige adipocytes and discuss their therapeutic potential.SummaryThe identification of novel endogenous factors that promote beiging and regulate beige adipocyte-specific physiological pathways opens up new avenues for therapeutic engineering targeting obesity and related metabolic disorders

Computing Aggregate Properties of Preimages for 2D Cellular Automata

Computing properties of the set of precursors of a given configuration is a common problem underlying many important questions about cellular automata. Unfortunately, such computations quickly become intractable in dimension greater than one. This paper presents an algorithm --- incremental aggregation --- that can compute aggregate properties of the set of precursors exponentially faster than na{\"i}ve approaches. The incremental aggregation algorithm is demonstrated on two problems from the two-dimensional binary Game of Life cellular automaton: precursor count distributions and higher-order mean field theory coefficients. In both cases, incremental aggregation allows us to obtain new results that were previously beyond reach

Pik3r1 Is Required for Glucocorticoid-Induced Perilipin 1 Phosphorylation in Lipid Droplet for Adipocyte Lipolysis.

Glucocorticoids promote lipolysis in white adipose tissue (WAT) to adapt to energy demands under stress, whereas superfluous lipolysis causes metabolic disorders, including dyslipidemia and hepatic steatosis. Glucocorticoid-induced lipolysis requires the phosphorylation of cytosolic hormone-sensitive lipase (HSL) and perilipin 1 (Plin1) in the lipid droplet by protein kinase A (PKA). We previously identified Pik3r1 (also called p85α) as a glucocorticoid receptor target gene. Here, we found that glucocorticoids increased HSL phosphorylation, but not Plin1 phosphorylation, in adipose tissue-specific Pik3r1-null (AKO) mice. Furthermore, in lipid droplets, the phosphorylation of HSL and Plin1 and the levels of catalytic and regulatory subunits of PKA were increased by glucocorticoids in wild-type mice. However, these effects were attenuated in AKO mice. In agreement with reduced WAT lipolysis, glucocorticoid- initiated hepatic steatosis and hypertriglyceridemia were improved in AKO mice. Our data demonstrated a novel role of Pik3r1 that was independent of the regulatory function of phosphoinositide 3-kinase in mediating the metabolic action of glucocorticoids. Thus, the inhibition of Pik3r1 in adipocytes could alleviate lipid disorders caused by excess glucocorticoid exposure