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Trapped Radiation Model Uncertainties: Model-Data and Model-Model Comparisons
The standard AP8 and AE8 models for predicting trapped proton and electron environments have been compared with several sets of flight data to evaluate model uncertainties. Model comparisons are made with flux and dose measurements made on various U.S. low-Earth orbit satellites (APEX, CRRES, DMSP. LDEF, NOAA) and Space Shuttle flights, on Russian satellites (Photon-8, Cosmos-1887, Cosmos-2044), and on the Russian Mir space station. This report gives the details of the model-data comparisons -- summary results in terms of empirical model uncertainty factors that can be applied for spacecraft design applications are given in a companion report. The results of model-model comparisons are also presented from standard AP8 and AE8 model predictions compared with the European Space Agency versions of AP8 and AE8 and with Russian trapped radiation models.
Trapped Radiation Model Uncertainties: Model-Data and Model-Model Comparisons
The standard AP8 and AE8 models for predicting trapped proton and electron environments have been compared with several sets of flight data to evaluate model uncertainties. Model comparisons are made with flux and dose measurements made on various U.S. low-Earth orbit satellites (APEX, CRRES, DMSP, LDEF, NOAA) and Space Shuttle flights, on Russian satellites (Photon-8, Cosmos-1887, Cosmos-2044), and on the Russian Mir Space Station. This report gives the details of the model-data comparisons-summary results in terms of empirical model uncertainty factors that can be applied for spacecraft design applications are given in a combination report. The results of model-model comparisons are also presented from standard AP8 and AE8 model predictions compared with the European Space Agency versions of AP8 and AE8 and with Russian-trapped radiation models.
Rainier Mesa/Shoshone Mountain Hydrostratigraphic Framework Model-Prime Model Model Development Process and Model Description, Revision 0
This document presents the results of revisions to the Rainier Mesa/Shoshone Mountain (RM/SM) hydrostratigraphic framework model (HFM) that was constructed for Corrective Action Unit (CAU) 99: Rainier Mesa/Shoshone Mountain. The revised HFM is described as the “RM/SM HFM-Prime” and serves as the base HFM. The modeling efforts and the revisions described in this report have been performed as part of the Underground Test Area (UGTA) Activity that was initiated by the U.S. Department of Energy (DOE), National Nuclear Security Administration Nevada Field Office (NNSA/NFO) to assess and evaluate the effects of the underground nuclear tests on groundwater at the Nevada National Security Site (NNSS) and vicinity. This document builds on the content of the internal Hydrostratigraphic Framework Model of the Rainier Mesa Area Phase I' - Base Model: Model Development Process & Data Package Description (N-I, 2014a) and specific document review comments from the UGTA RM/SM CAU Preemptive Review members (Zavarin, 2015). This document provides, where necessary, the justifications and rationale for interpretations and revisions to the hydrostratigraphic framework of the RM/SM CAU. The fundamental objective of the effort described in this report was to revise the RM/SM HFM, particularly in the areas and vicinity of the sub-CAU models, in order to incorporate some of the higher-resolution hydrogeologic interpretations used to construct several of the sub-CAU scale flow and transport models.
D-RM Builder: A software tool for generating fast and accurate nonlinear dynamic reduced models from high-fidelity models
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Kinetic Modeling of Secondary Organic Aerosol in a Weather-Chemistry Model: Parameterizations, Processes, and Predictions for GOAmazon
Secondary organic aerosol (SOA) forms and evolves in the atmosphere through many pathways and processes, over diverse spatial and time scales. Hence, there is a need to represent these widely-varying kinetic processes in large-scale atmospheric models to allow for accurate predictions of the abundance, properties, and impacts of SOA. In this work, we integrated a kinetic, process-level model (simpleSOM-MOSAIC) into a weather-chemistry model (WRF-Chem) to simulate the oxidation chemistry and microphysics of atmospheric SOA. simpleSOM-MOSAIC simulates multigenerational gas-phase chemistry, autoxidation reactions, heterogeneous oxidation, oligomerization, and phase-state-influenced gas/particle partitioning of SOA. As a case study, the integrated WRF-Chem-simpleSOM-MOSAIC (WC-SSM) model was used to simulate the photochemical evolution downwind of a large city (Manaus, Brazil) in the Amazon and, in turn, study the anthropogenic and biogenic interactions in an otherwise pristine environment. Consistent with previous work, we found that OA was enhanced by up to a factor of four in the urban plume due to elevated hydroxyl radical (OH) concentrations, relative to the background, and that this OA was dominated by SOA from biogenic precursors (80%). Further, in addition to accurately simulating the OA enhancement in the urban plume, the model reproduced the magnitude of the OA oxygen-to-carbon (O:C) ratio and broadly tracked the evolution of the aerosol size distribution. Our work highlights the importance of including an integrated, kinetic representation of SOA processes in an atmospheric model
Supersymmetry approach to delocalization transitions in a network model of the weak-field quantum Hall effect and related models
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WEC-SIM Phase 1 Validation Testing -- Numerical Modeling of Experiments: Preprint
The Wave Energy Converter Simulator (WEC-Sim) is an open-source code jointly developed by Sandia National Laboratories and the National Renewable Energy Laboratory. It is used to model wave energy converters subjected to operational and extreme waves. In order for the WEC-Sim code to be beneficial to the wave energy community, code verification and physical model validation is necessary. This paper describes numerical modeling of the wave tank testing for the 1:33-scale experimental testing of the floating oscillating surge wave energy converter. The comparison between WEC-Sim and the Phase 1 experimental data set serves as code validation. This paper is a follow-up to the WEC-Sim paper on experimental testing, and describes the WEC-Sim numerical simulations for the floating oscillating surge wave energy converter.
FVCOM-plume – A Three-dimensional Lagrangian Outfall Plume Dilution and Transport Model for Dynamic Tidal Environments: Model Development
Although numerous steady-state effluent plume dilution models are in use, their application in tidal environments remains a challenge. Three-dimensional dynamic circulation models are also inadequate, often due to the lack of required resolution and simplifying assumptions. To overcome these limitations, we present FVCOM-plume—an outfall plume dilution and transport model that operates within the Finite Volume Coastal Ocean Model (FVCOM) framework. It provides simultaneous inclusion of near-field dilution and far-field plume transport processes. The near-field is based on UM3 model using Lagrangian Control Volume approach to compute buoyant plume trajectory and dilution from multiport diffusers. The far-field uses neutrally buoyant particles with point masses and the random walk method to solve unsteady advection-diffusion processes. A density kernel approach is used to compute concentrations at point locations and analyze far-field plume characteristics. The results demonstrate the ability of FVCOM-plume to simultaneously capture near-field and far-field effluent plume dynamics in tidal environments.
A framework for modeling and optimizing dynamic systems under uncertainty
Algebraic modeling languages (AMLs) have drastically simplified the implementation of algebraic optimization problems. However, there are still many classes of optimization problems that are not easily represented in most AMLs. These classes of problems are typically reformulated before implementation, which requires significant effort and time from the modeler and obscures the original problem structure or context. In this work we demonstrate how the Pyomo AML can be used to represent complex optimization problems using high-level modeling constructs. We focus on the operation of dynamic systems under uncertainty and demonstrate the combination of Pyomo extensions for dynamic optimization and stochastic programming. We use a dynamic semibatch reactor model and a large-scale bubbling fluidized bed adsorber model as test cases.
Lithium-ion battery cell-level control using constrained model predictive control and equivalent circuit models
Not Available
Discrete models of fluids: spatial averaging, closure and model reduction
We consider semidiscrete ODE models of single-phase fluids and two-fluid mixtures. In the presence of multiple fine-scale heterogeneities, the size of these ODE systems can be very large. Spatial averaging is then a useful tool for reducing computational complexity of the problem. The averages satisfy exact balance equations of mass, momentum, and energy. These equations do not form a satisfactory continuum model because evaluation of stress and heat flux requires solving the underlying ODEs. To produce continuum equations that can be simulated without resolving microscale dynamics, we recently proposed a closure method based on the use of regularized deconvolution. Here we continue the investigation of deconvolution closure with the long term objective of developing consistent computational upscaling for multiphase particle methods. The structure of the fine-scale particle solvers is reminiscent of molecular dynamics. For this reason we use nonlinear averaging introduced for atomistic systems by Noll, Hardy, and Murdoch-Bedeaux. We also consider a simpler linear averaging originally developed in large eddy simulation of turbulence. We present several simple but representative examples of spatially averaged ODEs, where the closure error can be analyzed. Based on this analysis we suggest a general strategy for reducing the relative error of approximate closure. For problems with periodic highly oscillatory material parameters we propose a spectral boosting technique that augments the standard deconvolution and helps to correctly account for dispersion effects. We also conduct several numerical experiments, one of which is a complete mesoscale simulation of a stratified two-fluid flow in a channel. In this simulation, the operation count per coarse time step scales sublinearly with the number of particles.
Next generation models of carbonate mineral growth and dissolution: Modeling and Analysis: Next generation models of carbonate mineral growth and dissolution
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Modeling turbulence–chemistry interaction in lean premixed hydrogen flames with a strained flamelet model
Premixed flames in the thin and broken reaction zones regime exhibit strong non-linear turbulence–chemistry interactions and are hence challenging to model. In the present study, a direct numerical simulation (DNS) database for a hydrogen–air flame is used to understand the effect of turbulence–chemistry interactions on the flame speed. To this end, statistics of the local flame front displacement speed are investigated and the roles of flame stretch due to curvature and strain are analyzed. The local flame speed is found to be on average around 30% lower than the laminar burning velocity, which is shown to be a consequence of strain. Strain effects are then modeled by a recently proposed strained flamelet model, which is validated a priori against the DNS in terms of the flame speed and the reaction source term. The strained flamelet model leads to a moderate improvement of the flame speed prediction and is able to reproduce the decrease of the local flame speed. Moreover, it significantly improves the source term closure, which is demonstrated on the basis of the optimal estimator approach and, overall, describes the investigated DNS flame with very good accuracy.
Value of model enhancements: quantifying the benefit of improved transmission planning models
Not provided.