Improving the accuracy of reaction rates [Slides]
Abstract not provided.
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Engineering topics
Holland, Troy Michael
Publications and source records attributed to Holland, Troy Michael.
Kinetic isotope effects for dissociative recombination of tritiated ketenyl ion ( 3 HCCO + ): A surface-hopping ab initio molecular dynamics study
Dissociative recombination (DR) reactions are important when modeling charged species in the presence of free electrons. While experimental measurements of DR reaction rates are challenging, surface hopping ab initio molecular dynamics (SH-AIMD) simulations provide an attractive alternative. SH-AIMD is especially well-suited for estimating branching ratios, i.e., the relative rates of competing production channels, for DR reactions. Although the radiolysis of diatomic tritium has been studied experimentally, previous attempts to model these systems have failed to account for isotope effects in DR reactions. Previous SH-AIMD studies have also not investigated tritium isotope effects for the branching ratios of DR reactions. In this study, we compute the DR branching ratios of the protiated and tritiated ketenyl ion. Comparison with literature values for the protiated branching ratios provides confidence in the reliability of our SH-AIMD results. Our simulations predict a significant increase of the HC + CO branching ratio for the tritiated system.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Verification and Validation of High Explosive Reactive Burn Models Implemented in LANL's EAP and LAP Code Base
Reactive burn models represent a significant leap in high explosive (HE) modeling capability. The first generation of engineering models of HE detonation are called programmed burn models and they are largely based on the distance between a prescribed detonation point and each zone in a simulation. There have been many advancements to programmed burn models over the years and when the assumptions upon which they are based are met, a properly tuned programmed burn model can be highly accurate but if any of their assumptions is not met, as is the case for corner turning or weakly initiated HE burn, they will give the wrong answer. Reactive burn models represent an entirely new way of modeling HE burn. They use the local conditions of a zone – e.g. temperature, pressure or density – as calculated by a hydrocode to determine if and when the zone is going to detonate and if so, how rapidly. This difference opens up an entirely new set of capabilities for HE modeling. It makes it possible to accurately and predictively model phenomena like the effect of confinement and the formation of dead zones. Reactive burn models have seen sustained development effort at LANL for at least the last decade but several recent developments make it timely to transition reactive burn models from a research topic to a production tool. The main goal of this milestone is to facilitate and accelerate the adoption of reactive burn as a commonly available modeling option, with recommendations on the resolution that will be required and uncertainties associated with their modeling choices. To achieve this, we have performed verification, validation, and uncertainty quantification (UQ) assessments of AWSD and SURF/SURFplus in xRage and FLAG on a variety of different problems.
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Verification and Validation of High Explosive Reactive Burn Models Implemented in LANL's EAP and LAP Code Base (FY2020 L2 Milestone MRT 7129) [Slides]
Advanced reactive burn models enable phenomena to be modeled that aren’t possible with programmed burn. Programmed burn propagates a burn front at a prescribed speed from a prescribed initiation point. Reactive burn uses the hydro variables (pressure, temperature, etc.) to determine when, how rapidly, and to what extent a zone detonates. This enables a completely new set of problems to be simulated. Our goal in this milestone has been to improve the usability of reactive burn modes. Thus, the closure criteria are: 1. Perform code and solution verification of the reactive burn models using appropriate solutions and simplified HE setups. 2. Perform validation assessments using small-scale experiments. 3. Evaluate sensitivities and quantify uncertainties due to model form variations and mesh dependencies.
45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
Predicting Emission Source Terms in a Reduced-Order Fire Spread Model—Part 1: Particulate Emissions
A simple, easy-to-evaluate, surrogate model was developed for predicting the particle emission source term in wildfire simulations. In creating this model, we conceptualized wildfire as a series of flamelets, and using this concept of flamelets, we developed a one-dimensional model to represent the structure of these flamelets which then could be used to simulate the evolution of a single flamelet. A previously developed soot model was executed within this flamelet simulation which could produce a particle size distribution. Executing this flamelet simulation 1200 times with varying conditions created a data set of emitted particle size distributions to which simple rational equations could be tuned to predict a particle emission factor, mean particle size, and standard deviation of particle sizes. These surrogate models (the rational equation) were implemented into a reduced-order fire spread model, QUIC-Fire. Using QUIC-Fire, an ensemble of simulations were executed for grassland fires, southeast U.S. conifer forests, and western mountain conifer forests. Resulting emission factors from this ensemble were compared against field data for these fire classes with promising results. Also shown is a predicted averaged resulting particle size distribution with the bulk of particles produced to be on the order of 1 μm in size.
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