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Grout, Ray W

Publications and source records attributed to Grout, Ray W.

12 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Numerical Simulations of the Supercritical Carbon Dioxide Round Turbulent Jet

We explore the fundamental connection between properties of a supercritical fluid and observed behavior of the flow by comparing simulations of a supercritical carbon dioxide (sCO2) round jet to canonical simulations using an ideal gas model. sCO2 has desirable behavior that can improve power density compared to traditional fluids for applications involving closed-cycle gas turbines, heat transmission, and hydraulic fracturing while facilitating carbon sequestration. While literature exists focusing on the prospects of sCO2 in various industries, the quantities of interest studied tend to be application specific whereas our investigation generalizes across multiple applications. The Soave-Redlich-Kwong equation of state is utilized to close our system of equations; we use a second order finite volume method in conjunction with adaptive mesh refinement as implemented in PeleC. The jet is at p=10 MPa and T=600 K in order to maintain a single-phase fluid. Quantities of interest for this study include the mean axial velocity and Reynolds stresses.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

A Bayesian approach to calibrating hydrogen flame kinetics using many experiments and parameters

First-principles Markov Chain Monte Carlo sampling is used to investigate uncertainty quantification and uncertainty propagation in parameters describing hydrogen kinetics. Specifically, we sample the posterior distribution for thirty-one parameters focusing on the H 2 O 2 and HO 2 reactions resulting from conditioning on ninety-one experiments. Established literature values are used for the remaining parameters in the mechanism as well as other thermodynamic and transport data needed to specify fluid properties. The samples are computed using an affine invariant sampler starting with broad, noninformative priors. Autocorrelation analysis shows that O(1M) samples are sufficient to obtain a reasonable sampling of the posterior. The resulting distribution identifies strong positive and negative correlations and several non-Gaussian characteristics. Using samples drawn from the posterior, we investigate the impact of parameter uncertainty on the prediction of two more complex flames: a 2D premixed flame kernel and the ignition of a hydrogen jet issuing into a heated chamber. The former represents a combustion regime similar to the target experiments used to calibrate the mechanism and the latter represents a different combustion regime. For the premixed flame, the net amount of product after a given time interval has a standard deviation of less than 2% whereas the standard deviation of the ignition time for the jet is more than 10%. The samples used for these studies are posted online. These results indicate the degree to which parameters consistent with the target experiments constrain predicted behavior in different combustion regimes. Finally, this process provides a framework for both identifying reactions for further study from candidate mechanisms as well as combining uncertainty quantification and propagation to, ultimately, tie uncertainty in laboratory flame experiments to uncertainty in end-use numerical predictions of more complicated scenarios.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Impingement of a Supercritical Carbon Dioxide Jet on a Planar Surface

A laminar slot jet of supercritical CO2 entering a supercritical CO2 ambient environment is simulated with a computational fluid dynamics package using incorporating a thermodynamically consistent equation of state and high-fidelity transport coefficient models. For a jet at 8 MPa, at a temperature varying from 600 to 1000 K, entering an ambient at 8 MPa and a temperature of 1000 K, the flow structure is sensitive to the difference in operating temperature. Because there is very little heat transfer to the core of the jet, these results may be caused by both the density difference in the fluids, and momentum and heat transfer at the edge of the jet.

42 ENGINEERING↗
DOE OSTI2018

Fuel Property Characterization and Prediction

This presentation describes the progress made over the last year on the Fuel Property Characterization and Prediction tasks as part of the CoOptima program under the Vehicle Technologies Office. The tasks reviewed are: Fuel Property Blending Model (F.1.2.2 and F.1.2.3), the Heat of Vaporization Measurement for Full Boiling Range Fuels (F.1.3.2), and the Flow Reactor Autoignition Kinetic Mechanism Development and Validation (F.2.1.4) tasks.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

An Adaptive Timestepping Algorithm for Particle Time Integration in Coupled CFD-DEM Simulations

Coupled Computational Fluid Dynamics(CFD) - Discrete Element Method (DEM) models provide an accurate description of multiphase physical systems where a granular phase exists in an underlying continuous medium. The time integration of the granular phase in these simulations are typically handled using an explicit time integration scheme with a global time step that is much smaller than fluid time scales, in order to resolve inter-particle collisions. An adapative time integration technique that avoids this global constraint for the granular phase is presented in this work. The algorithm involves the use of a local time stepping approach to resolve collisional time scales for only a subset of particles that are in close proximity to potential collision partners, thereby resulting in substantial reduction of computational cost. This approach is observed to be 2-3X faster than traditional explicit methods for problems that involve both dense and dilute regions, while maintaining the same level of accuracy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Optimizing Performance of Combustion Chemistry Solvers on Intel's Many Integrated Core (MIC) Architectures

This work investigates novel algorithm designs and optimization techniques for restructuring chemistry integrators in zero and multidimensional combustion solvers, which can then be effectively used on the emerging generation of Intel's Many Integrated Core/Xeon Phi processors. These processors offer increased computing performance via large number of lightweight cores at relatively lower clock speeds compared to traditional processors (e.g. Intel Sandybridge/Ivybridge) used in current supercomputers. This style of processor can be productively used for chemistry integrators that form a costly part of computational combustion codes, in spite of their relatively lower clock speeds. Performance commensurate with traditional processors is achieved here through the combination of careful memory layout, exposing multiple levels of fine grain parallelism and through extensive use of vendor supported libraries (Cilk Plus and Math Kernel Libraries). Important optimization techniques for efficient memory usage and vectorization have been identified and quantified. These optimizations resulted in a factor of ~ 3 speed-up using Intel 2013 compiler and ~ 1.5 using Intel 2017 compiler for large chemical mechanisms compared to the unoptimized version on the Intel Xeon Phi. The strategies, especially with respect to memory usage and vectorization, should also be beneficial for general purpose computational fluid dynamics codes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Accelerating the Computation of Detailed Chemical Reaction Kinetics for Simulating Combustion of Complex Fuels

Combustion of hydrocarbon fuels has been a very challenging scientific and engineering problem due to the complexity of turbulent flows and hydrocarbon reaction kinetics. There is an urgent need to develop an efficient modeling capability to accurately predict the combustion of complex fuels. Detailed chemical kinetic models for the surrogates of fuels such as gasoline, diesel and JP-8 consist of thousands of chemical species and Arrhenius reaction steps. Oxygenated fuels such as bio-fuels and heavier hydrocarbons, such as from newer fossil fuel sources, are expected to have a much more complex chemistry requiring increasingly larger chemical kinetic models. Such models are beyond current computational capability, except for homogeneous or partially stirred reactor type calculations. The advent of highly parallel multi-core processors and graphical processing units (GPUs) promises a steep increase in computational performance in the coming years. This paper will present a software framework that translates the detailed chemical kinetic models to high- performance code targeted for GPU accelerators.

02 PETROLEUM↗