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Open Access Publications from the University of California

Scholarly Works (35 results)

  • Article
  • Peer Reviewed
LBL Publications (2020)
Fluorinated gases are critical to a number of high-technology industries including semiconductor manufacturing and related processes such as flat panel display, LED, and photovoltaic manufacturing. These fluorinated gases have very high global warming potentials (GWPs) and, unfortunately are chemically very stable, in some cases lasting for thousands of years in the atmosphere. For environmental reasons, it is imperative that the release of these gases be minimized, but existing methods to destroy them requires a significant amount of energy. The goal of this project was to develop a more energy efficient method of destroying these high GWP gases using computational fluid dynamics, bringing together resources available at the national labs, including high-performance computing hardware and modern computational methods, in order to explore an industrially important problem with key environmental and economic impact. This exploratory project has demonstrated that HPC can indeed provide a unique view into a complex engineering problem - one that is simply inaccessible by any other means. The tools allow one to explore the details of the chemical process, and construct ``what-if'' scenarios to address shortcomings of the physical device in its current operating modes. However, as with many sources of completely new information, many new questions are illuminated with this capability. It will take considerable time, effort and experience before we learn to probe the solutions, pose operating scenarios and confirm modifications to the device that lead to real engineering advances.
    Cover page: Improving Gas Reactor Design with Complex Non-Standard Reaction Mechanisms in a Reactive Flow Model
    • Article
    • Peer Reviewed
    Lawrence Berkeley National Laboratory (2004)

    The evolution of an Inertial Fusion Energy (IFE) chamber involves a repetition of short, intense depositions of energy (from target ignition) into a reaction chamber, followed by the turbulent relaxation of that energy through shock waves and thermal conduction to the vessel walls. We present an algorithm for 2D simulations of the fluid inside an IFE chamber between fueling repetitions. Our finite-volume discretization for the Navier-Stokes equations incorporates a Cartesian grid treatment for irregularly-shaped domain boundaries. The discrete conservative update is based on a time-explicit Godunov method for advection, and a two-stage Runge-Kutta update for diffusion accommodating state-dependent transport properties. Conservation is enforced on cut cells along the embedded boundary interface using a local redistribution scheme so that the explicit time step for the combined approach is governed by the mesh spacing in the uniform grid. The test problems demonstrate second-order convergence of the algorithm on smooth solution profiles, and the robust treatment of discontinuous initial data in an IFE-relevant vessel geometry.

      Cover page: An embedded boundary method for viscous, conducting compressible flow
      • Article
      LBL Publications (2003)

      This conference paper considers how to use reaction path diagrams to better understand the output of reacting flow simulations. Briefly, these diagrams have long been used to depict the reactants and products in networks of chemical reactions. The diagrams can be generated in several ways from computer simulations of chemically reacting fluids to depict how the fluid moderates the chemistry by determining which species are brought into contact to react in quantity. The concept of a conditional diagram is introduced which depicts the reactions occurring in only a portion of the fluid domain, thus enabling comparisons between different regions of the fluid and the overall reaction network. Several examples are provided of the paths occurring in methane diffusion flames.

        Cover page: Conditional and opposed reaction path diagrams for the analysis of fluid-chemistry interactions
        • Article
        • Peer Reviewed
        Lawrence Berkeley National Laboratory (2004)
          Cover page: A taxonomy of integral reaction path analysis
          • Article
          Lawrence Berkeley National Laboratory (2001)

          In this paper we study the behavior of a premixed turbulent methane flame in three dimensions using numerical simulation. The simulations are performed using an adaptive time-dependent low Mach number combustion algorithm based on a second-order projection formulation that conserves both species mass and total enthalpy. The species and enthalpy equations are treated using an operator-split approach that incorporates stiff integration techniques for modeling detailed chemical kinetics. The methodology also incorporates a mixture model for differential diffusion. For the simulations presented here, methane chemistry and transport are modeled using the DRM-19 (19-species, 84-reaction) mechanism derived from the GRIMech-1.2 mechanism along with its associated thermodynamics and transport databases. We consider a lean flame with equivalence ratio 0.8 for two different levels of turbulent intensity. For each case we examine the basic structure of the flame including turbulent flame speed and flame surface area. The results indicate that flame wrinkling is the dominant factor leading to the increased turbulent flame speed. Joint probability distributions are computed to establish a correlation between heat release and curvature. We also investigate the effect of turbulent flame interaction on the flame chemistry. We identify specific flame intermediates that are sensitive to turbulence and explore various correlations between these species and local flame curvature. We identify different mechanisms by which turbulence modulates the chemisry of the flame.

            Cover page: Numerical simulation of premixed turbulent methane combustion
            • Article
            • Peer Reviewed
            LBL Publications (2019)
            We present a parallel multi-implicit time integration scheme for the advection-diffusion-reaction systems arising from the equations governing low-Mach number combustion with complex chemistry. Our strategy employs parallelisation across the method to accelerate the serial Multi-Implicit Spectral Deferred Correction (MISDC) scheme used to couple the advection, diffusion, and reaction processes. In our approach, the diffusion solves and the reaction solves are performed concurrently by different processors. Our analysis shows that the proposed parallel scheme is stable for stiff problems and that the sweeps converge to the fixed-point solution at a faster rate than with serial MISDC. We present numerical examples to demonstrate that the new algorithm is high-order accurate in time, and achieves a parallel speedup compared to serial MISDC.
              Cover page: Concurrent implicit spectral deferred correction scheme for low-Mach number combustion with detailed chemistry
              • Article
              • Peer Reviewed
              LBL Publications (2018)
              We present a numerical approach for low Mach number combustion that conserves both mass and energy while remaining on the equation of state to a desired tolerance. We present both unconfined and confined cases, where in the latter the ambient pressure changes over time. Our overall scheme is a projection method for the velocity coupled to a multi-implicit spectral deferred corrections (SDC) approach to integrate the mass and energy equations. The iterative nature of SDC methods allows us to incorporate a series of pressure discrepancy corrections naturally that lead to additional mass and energy influx/outflux in each finite volume cell in order to satisfy the equation of state. The method is second order, and satisfies the equation of state to a desired tolerance with increasing iterations. Motivated by experimental results, we test our algorithm on hydrogen flames with detailed kinetics. We examine the morphology of thermodiffusively unstable cylindrical premixed flames in high-pressure environments for confined and unconfined cases. We also demonstrate that our algorithm maintains the equation of state for premixed methane flames and non-premixed dimethyl ether jet flames.
                Cover page: A conservative, thermodynamically consistent numerical approach for low Mach number combustion. Part I: Single-level integration
                • Article
                • Peer Reviewed
                LBL Publications (2020)
                We propose an algorithm for low Mach number reacting flows subjected to electric field that includes the chemical production and transport of charged species. This work is an extension of a multi-implicit spectral deferred correction (MISDC) algorithm designed to advance the conservation equations in time at scales associated with advective transport. The fast and nontrivial interactions of electrons with the electric field are treated implicitly using a Jacobian-Free Newton Krylov approach for which a preconditioning strategy is developed. Within the MISDC framework, this enables a close and stable coupling of diffusion, reactions and dielectric relaxation terms with advective transport and is shown to exhibit second-order convergence in space and time. The algorithm is then applied to a series of steady and unsteady problems to demonstrate its capability and stability. Although developed in a one-dimensional case, the algorithmic ingredients are carefully designed to be amenable to multi-dimensional applications.
                  Cover page: A spectral deferred correction strategy for low Mach number reacting flows subject to electric fields
                  • Article
                  • Peer Reviewed
                  UC San Diego Previously Published Works (2019)
                  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 H2O2 and HO2 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. 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.
                    Cover page: A Bayesian approach to calibrating hydrogen flame kinetics using many experiments and parameters
                    • Article
                    Lawrence Berkeley National Laboratory (2007)

                    Type Ia supernovae (SNe Ia) are the largest thermonuclear explosions in the Universe. Their light output can be seen across great stances and has led to the discovery that the expansion rate of the Universe is accelerating. Despite the significance of SNe Ia, there are still a large number of uncertainties in current theoretical models. Computational modeling offers the promise to help answer the outstanding questions. However, even with today's supercomputers, such calculations are extremely challenging because of the wide range of length and time scales. In this paper, we discuss several new algorithms for simulations of SNe Ia and demonstrate some of their successes.

                      Cover page: New approaches for modeling type Ia supernovae
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