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DOE OSTI2016

Investigation of boundary-layer wind predictions during nocturnal low-level jet events using the Weather Research and Forecasting model

Simulations of two periods featuring three consecutive low level jet (LLJ) events in the US Upper Great Plains during the autumn of 2011 were conducted to explore the impacts of various setup configurations and physical process models on simulated flow parameters within the lowest 200 m above the surface, using the Weather Research and Forecasting (WRF) model. Sensitivities of simulated flow parameters to the horizontal and vertical grid spacing, planetary boundary layer (PBL) and land surface model (LSM) physics options, were assessed. Data from a Light Detection and Ranging (lidar) system, deployed to the Weather Forecast Improvement Project (WFIP; Finley et al. 2013) were used to evaluate the accuracy of simulated wind speed and direction at 80 m above the surface, as well as their vertical distributions between 120 and 40 m, covering the typical span of contemporary tall wind turbines. All of the simulations qualitatively captured the overall diurnal cycle of wind speed and stratification, producing LLJs during each overnight period, however large discrepancies occurred at certain times for each simulation in relation to the observations. 54-member ensembles encompassing changes of the above discussed configuration parameters displayed a wide range of simulated vertical distributions of wind speed and direction, and potential temperature, reflecting highly variable representations of stratification during the weakly stable overnight conditions. Root mean square error (RMSE) statistics show that different ensemble members performed better and worse in various simulated parameters at different times, with no clearly superior configuration . Simulations using a PBL parameterization designed specifically for the stable conditions investigated herein provided superior overall simulations of wind speed at 80 m, demonstrating the efficacy of targeting improvements of physical process models in areas of known deficiencies. However, the considerable magnitudes of the RMSE values of even the best performing simulations indicate ample opportunities for further improvements.

Mirocha, Jeff D.↗

DOE OSTI2019

Nalu-Wind and OpenFAST: A high-fidelity modeling and simulation environment for wind energy. Milestone ECP-Q2-FY19

The goal of the ExaWind project is to enable predictive simulations of wind farms comprised of many megawatt-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources. The primary physics codes in the ExaWind project are Nalu-Wind, which is an unstructured-grid solver for the acoustically incompressible Navier-Stokes equations, and OpenFAST, which is a whole-turbine simulation code. The Nalu-Wind model consists of the mass-continuity Poisson-type equation for pressure and a momentum equation for the velocity. For such modeling approaches, simulation times are dominated by linear-system setup and solution for the continuity and momentum systems. For the ExaWind challenge problem, the moving meshes greatly affect overall solver costs as reinitialization of matrices and recomputation of preconditioners is required at every time step. This milestone represents the culmination of several parallel development activities towards the goal of establishing a full-physics simulation capability for modeling wind turbines operating in turbulent atmospheric inflow conditions. The demonstration simulation performed in this milestone is the first step towards the "ground truth" simulation and includes the following components: neutral atmospheric boundary layer inflow conditions generated using a precursor simulation, a hybrid RANS/LES simulation of the wall-resolved turbine geometry, hybridization of the turbulence equations using a blending function approach to transition from the atmospheric scales to the blade boundary layer scales near the turbine, fluid-structure interaction (FSI) that accounts for the complete set of blade deformations (bending, twisting and pitch motion, yaw and tower displacements) by coupling to a comprehensive turbine dynamics code (OpenFAST). The use of overset mesh methodology for the simulations in this milestone presents a significant deviation from the previous efforts where a sliding mesh approach was employed to model the rotation of the turbine blades. The choice of overset meshes was motivated by the need to handle arbitrarily large deformations of the blade and to allow for blade pitching in the presence of a controller and the ease of mesh generation compared to the sliding mesh approach. FSI and the new timestep algorithm used in the simulations were developed in partnership with the A2e High-Fidelity Modeling project. The individual physics components were verified and validated (V%V) through extensive code-to-code comparisons and with experiments where possible. The detailed V&V efforts provide confidence in the final simulation where these physics models were combined together even though no detailed experimental data is available to perform validation of the final configuration. Taken together, this milestone successfully demonstrated the most advanced simulation to date that has been performed with Nalu-Wind.

17 WIND ENERGY↗

DOE OSTI2019

Modeling and simulation functional needs for molten salt reactor licensing

The modeling and simulation functional needs to license and design molten salt reactor concepts were assessed and an evaluation methodology was developed using a licensing-focused approach considering the modeling and simulation components that contribute to a molten salt reactor safety analysis report. These functional needs were prioritized by identifying the relationships between functional needs and using a quantitative weighting method to identify the most critical components to build a licensing case. This novel weighting method provided a list of functional needs prioritized relative to key advanced reactor licensing outcomes. In addition, functional need inputs were ranked to reveal those that feed the most modeling and simulation components. The findings from this prioritization effort were used to inform the modeling and simulation goals of the US Department of Energy Office of Nuclear Energy (DOE-NE) Molten Salt Reactor campaign.Modeling and simulation needs were grouped into three main categories: (1) source term definition, material accountancy, and radiological consequences, (2) safety analysis, and (3) steady-state neutronics and thermal hydraulics. Here, five near-term goals were identified among these focus areas that add value: (1) deploying a systems and safeguards analysis computational tool, (2) defining source terms for molten salt reactor analysis and interfacing with the US Nuclear Regulatory Commission on accident progression analysis, (3) developing point designs for liquid-fueled thermal-spectrum and fast-spectrum molten salt reactors, (4) building safety analysis specifications and reference solutions for Molten Salt Reactor Experiment transients, and (5) interfacing with the thermophysical and thermodynamic salt chemistry databases.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

VALIDATION, VERIFICATION, AND CALIBRATION THROUGH A CAUSAL LENS

This paper presents an alternative method based on causal inference to perform validation, verification, and calibration of simulation models. While classical validation and verification approaches focus on the identification of the associations between data elements using statistical and machine learning methods, the novel methods in this paper focus instead on the identification of causal relationships between data elements. Statistical and machine learning-based approaches are strictly data-driven, meaning that they provide quantitative comparison measures between datasets without explicitly considering the hypotheses behind them. This can lead to the erroneous conclusion that, if two data sets are close enough, then the models that generated them are similar. In addition, when experimental and simulated data differ to an extent that fails to meet the acceptance criteria, calibration techniques are used to tweak simulation model parameters to reduce the gap between the two types of data. This produces the false expectation that a simulation model will match reality. The methods presented in this paper move away from these strictly data-driven methods for validation and calibration toward more robust, model-driven methods based on causal inference. Causal inference aims to identify the possible mechanisms that might have generated data. Thus, this analysis targets the prediction of the effects when one (or more) of the identified mechanisms are altered. There are many approaches to identify, quantify and illustrate causal relationships. For the scope of this paper, directed graphs are employed as causal models. If the directed graph lacks cycles it is known as a directed acyclic graph (DAG). A node in such a graph represents an observed data element while a directed edge connecting two nodes represents a causal relationship between two variables. The developed causal methods are designed to extract causal models from simulation models and from experimental data. Causal models capture the causal relationships between data elements (e.g., simulated and experimental data). In this context, validation and verification are performed by comparing causal models. The proposed approach does not only inform system analysts on how a simulation model matches real-world data, but also identifies elements of the simulation model that should be revised when discrepancies between simulation and experimental data are observed. Through these causal methods, analysts have a means to identify the portion of the model equation(s) that are behind an edge connecting two variables. Hence, once the structural differences between causal models have been determined, model calibration can occur by changing only those model parameters that impact the identified causal relationships.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Emission or atmospheric processes? An attempt to attribute the source of large bias of aerosols in eastern China simulated by global climate models

Here, global climate models often underestimate aerosol loadings in China, and these biases can have significant implications for anthropogenic aerosol radiative forcing and climate effects. The biases may be caused by either the emission inventory or the treatment of aerosol processes in the models, or both, but so far no consensus has been reached. In this study, a relatively new emission inventory based on energy statistics and technology, Multi-resolution Emission Inventory for China (MEIC), is used to drive the Community Atmosphere Model version 5 (CAM5) to evaluate aerosol distribution and radiative effects against observations in China. The model results are compared with the model simulations with the widely used Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5) emission inventory. We find that the new MEIC emission improves the aerosol optical depth (AOD) simulations in eastern China and explains 22–28 % of the AOD low bias simulated with the AR5 emission. However, AOD is still biased low in eastern China. Seasonal variation of the MEIC emission leads to a better agreement with the observed seasonal variation of primary aerosols than the AR5 emission, but the concentrations are still underestimated. This implies that the atmospheric loadings of primary aerosols are closely related to the emission, which may still be underestimated over eastern China. In contrast, the seasonal variations of secondary aerosols depend more on aerosol processes (e.g., gas- and aqueous-phase production from precursor gases) that are associated with meteorological conditions and to a lesser extent on the emission. It indicates that the emissions of precursor gases for the secondary aerosols alone cannot explain the low bias in the model. Aerosol secondary production processes in CAM5 should also be revisited. The simulation using MEIC estimates the annual-average aerosol direct radiative effects (ADREs) at the top of the atmosphere (TOA), at the surface, and in the atmosphere to be –5.02, –18.47, and 13.45 W m –2 , respectively, over eastern China, which are enhanced by –0.91, –3.48, and 2.57 W m –2 compared with the AR5 emission. The differences of ADREs by using MEIC and AR5 emissions are larger than the decadal changes of the modeled ADREs, indicating the uncertainty of the emission inventories. This study highlights the importance of improving both the emission and aerosol secondary production processes in modeling the atmospheric aerosols and their radiative effects. Yet, if the estimations of MEIC emissions in trace gases do not suffer similar biases to those in the AOD, our findings will help affirm a fundamental error in the conversion from precursor gases to secondary aerosols as hinted in other recent studies following different approaches.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

A Simple Evacuation Modeling and Simulation Tool for First Responders

Although modeling and simulation of mass evacuations during a natural or man-made disaster is an on-going and vigorous area of study, tool adoption by front-line first responders is uneven. Some of the factors that account for this situation include cost and complexity of the software. For several years, Oak Ridge National Laboratory has been actively developing the free Incident Management Preparedness and Coordination Toolkit (IMPACT) to address these issues. One of the components of IMPACT is a multi-agent simulation module for area-based and path-based evacuations. The user interface is designed so that anyone familiar with typical computer drawing tools can quickly author a geospatially-correct evacuation visualization suitable for table-top exercises. Since IMPACT is designed for use in the field where network communications may not be available, quick on-site evacuation alternatives can be evaluated to keep pace with a fluid threat situation. Realism is enhanced by incorporating collision avoidance into the simulation. Statistics are gathered as the simulation unfolds, including most importantly time-to-evacuate, to help first responders choose the best course of action.

data fusion↗

DOE OSTI2017

Nuclear Energy Advanced Modeling and Simulation (NEAMS) Accident Tolerant Fuels High Impact Problem: Engineering Scale Models and Analysis

As part of the Department of Energy's Nuclear Energy Advanced Modeling and Simulation program, an Accident Tolerant Fuel High Impact Problem was initiated at the beginning of fiscal year 2015 to investigate the behavior of \usi\ fuel and iron-chromium-aluminum (FeCrAl) cladding under normal operating and accident reactor conditions. The High Impact Problem was created in response to the United States Department of Energy's renewed interest in accident tolerant materials after the events that occurred at the Fukushima Daiichi Nuclear Power Plant in 2011. The High Impact Problem is a multinational laboratory and university collaborative research effort between Idaho National Laboratory, Los Alamos National Laboratory, Argonne National Laboratory, and the University of Tennessee, Knoxville. This report summarizes the latest recommended material models to be used for engineering scale simulations based upon lower length scale analyses described elsewhere. Comparative analyses between traditional fuel rods (U 3 Si 2 /Zircaloy-4) and the proposed accident tolerant fuel rods (UO 2 /FeCrAl and U 3 Si 2 /Zircaloy-4) under normal operation, loss of coolant, and reactivity insertion conditions have been revisited using the latest state-of-the-art models implemented into the Bison fuel performance code. Sensitivity analyses have also been redone to take into account the latest knowledge on uncertain parameters.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2016

A Modal Model to Simulate Typical Structural Dynamic Nonlinearity [PowerPoint]

Some initial investigations have been published which simulate nonlinear response with almost traditional modal models: instead of connecting the modal mass to ground through the traditional spring and damper, a nonlinear Iwan element was added. This assumes that the mode shapes do not change with amplitude and there are no interactions between modal degrees of freedom. This work expands on these previous studies. An impact experiment is performed on a structure which exhibits typical structural dynamic nonlinear response, i.e. weak frequency dependence and strong damping dependence on the amplitude of vibration. Use of low level modal test results in combination with high level impacts are processed using various combinations of modal filtering, the Hilbert Transform and band-pass filtering to develop response data that are then fit with various nonlinear elements to create a nonlinear pseudo-modal model. Simulations of forced response are compared with high level experimental data for various nonlinear element assumptions.

42 ENGINEERING↗

DOE OSTI2015

A Modal Model to Simulate Typical Structural Dynamic Nonlinearity

42 ENGINEERING↗

DOE OSTI2015

Modeling and Simulation for Safeguards and Nonproliferation Workshop

The Modeling and Simulation for Safeguards and Nonproliferation Workshop was held December 15–18, 2014, at Oak Ridge National Laboratory. This workshop was made possible by the Next Generation Safeguards Initiative Human Capital Development (NGSI HCD) Program. The idea of the workshop was to move beyond the tried-and-true boot camp training of nonproliferation concepts to spend several days on the unique perspective of applying modeling and simulation (M&S) solutions to safeguards challenges.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2012

Plant-Level Modeling and Simulation of Used Nuclear Fuel Dissolution

Plant-level modeling and simulation of a used nuclear fuel prototype dissolver is presented. Emphasis is given in developing a modeling and simulation approach to be explored by other processes involved in the recycle of used fuel. The commonality concepts presented in a previous communication were used to create a model and realize its software module. An initial model was established based on a theory of chemical thermomechanical network transport outlined previously. A software module prototype was developed with the required external behavior and internal mathematical structure. Results obtained demonstrate the generality of the design approach and establish an extensible mathematical model with its corresponding software module for a wide range of dissolvers. Scale up numerical tests were made varying the type of used fuel (breeder and light-water reactors) and the capacity of dissolution (0.5 t/d to 1.7 t/d). These tests were motivated by user requirements in the area of nuclear materials safeguards. A computer module written in high-level programing languages (MATLAB and Octave) was developed, tested, and provided as open-source code (MATLAB) for integration into the Separations and Safeguards Performance Model application in development at Sandia National Laboratories. The modeling approach presented here is intended to serve as a template for a rational modeling of all plant-level modules. This will facilitate the practical application of the commonality features underlying the unifying network transport theory proposed recently. In addition, by example, this model describes, explicitly, the needed data from sub-scale models, and logical extensions for future model development. For example, from thermodynamics, an off-line simulation of molecular dynamics could quantify partial molar volumes for the species in the liquid phase; this simulation is currently at reach for high-performance computing. From fluid mechanics, a hold-up capacity function is needed for the dissolver device; this simulation is currently at reach for computational fluid mechanics given the existing CAD geometry. From chemical transport phenomena, a simulation of the particle-scale dissolution front is needed to derive an improved solid dissolution kinetics law by predicting the local surface area change; an example was provided in this report. In addition, the associated reaction mechanisms for dissolution are presently largely untested and simplified, hence even a parallel experimental program in reaction kinetics is needed to support modeling and simulation efforts. Last but not least, a simple account of finite rates of solid feed and transfer can be readily introduced via a coupled delayed model. These are some of the theoretical benefits of a rational plant-level modeling approach which guides the development of smaller length and time scale modeling. Practical, and other theoretical benefits have been presented on a previous report.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2012

Techniques and Issues in Agent-Based Modeling Validation

Validation of simulation models is extremely important. It ensures that the right model has been built and lends confidence to the use of that model to inform critical decisions. Agent-based models (ABM) have been widely deployed in different fields for studying the collective behavior of large numbers of interacting agents. However, researchers have only recently started to consider the issues of validation. Compared to other simulation models, ABM has many differences in model development, usage and validation. An ABM is inherently easier to build than a classical simulation, but more difficult to describe formally since they are closer to human cognition. Using multi-agent models to study complex systems has attracted criticisms because of the challenges involved in their validation [1]. In this report, we describe the challenge of ABM validation and present a novel approach we recently developed for an ABM system.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2014

Pair dynamics and the intermolecular nuclear Overhauser effect (NOE) in liquids analysed by simulation and model theories: Application to an ionic liquid

Combining simulation and model theories, this paper analyses the impact of pair dynamics on the intermolecular nuclear Overhauser effect (NOE) in liquids. For the first time, we give a distance resolved NOE. When applied to the ionic liquid 1-ethyl-3-methyl-imidazolium tetrafluoroborate the NOE turns out to be of long-range nature. This behaviour translates to the experimentally measured cross- and longitudinal relaxation rates. We were able to calculate the heteronuclear NOE from simulation data, despite the high computational effort. Model theories are computationally less demanding and cover the complete frequency range of the respective spectral density function, they are usually based on a very simple pair distribution function and the solution of the diffusion equation. In order to model the simulated data sufficiently, these simplifications in structure and dynamics have to be generalised considerably.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Surface temperature dependence of tropical cyclone-permitting simulations in a spherical model with uniform thermal forcing

Tropical cyclone (TC)-permitting general circulation model simulations are performed with spherical geometry and uniform thermal forcing, including uniform sea surface temperature (SST) and insolation. The dependence of the TC number and TC intensity on SST is examined in a series of simulations with varied SST. The results are compared to corresponding simulations with doubly periodic f -plane geometry, rotating radiative convective equilibrium. The turbulent equilibria in simulations with spherical geometry have an inhomogenous distribution of TCs with the density of TCs increasing from low to high latitudes. The preferred region of TC genesis is the subtropics, but genesis shifts poleward and becomes less frequent with increasing SST. In conclusion, both rotating radiative convective equilibrium and spherical geometry simulations have decreasing TC number and increasing TC intensity as SST is increased.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Localizing Clinical Patterns of Blast Traumatic Brain Injury Through Computational Modeling and Simulation

Blast traumatic brain injury is ubiquitous in modern military conflict with significant morbidity and mortality. Yet the mechanism by which blast overpressure waves cause specific intracranial injury in humans remains unclear. Reviewing of both the clinical experience of neurointensivists and neurosurgeons who treated service members exposed to blast have revealed a pattern of injury to cerebral blood vessels, manifested as subarachnoid hemorrhage, pseudoaneurysm, and early diffuse cerebral edema. Additionally, a seminal neuropathologic case series of victims of blast traumatic brain injury (TBI) showed unique astroglial scarring patterns at the following tissue interfaces: subpial glial plate, perivascular, periventricular, and cerebral gray-white interface. The uniting feature of both the clinical and neuropathologic findings in blast TBI is the co-location of injury to material interfaces, be it solid-fluid or solid-solid interface. This motivates the hypothesis that blast TBI is an injury at the intracranial mechanical interfaces. In order to investigate the intracranial interface dynamics, we performed a novel set of computational simulations using a model human head simplified but containing models of gyri, sulci, cerebrospinal fluid (CSF), ventricles, and vasculature with high spatial resolution of the mechanical interfaces. Simulations were performed within a hybrid Eulerian—Lagrangian simulation suite (CTH coupled via Zapotec to Sierra Mechanics). Because of the large computational meshes, simulations required high performance computing resources. Twenty simulations were performed across multiple exposure scenarios—overpressures of 150, 250, and 500 kPa with 1 ms overpressure durations—for multiple blast exposures (front blast, side blast, and wall blast) across large variations in material model parameters (brain shear properties, skull elastic moduli). All simulations predict fluid cavitation within CSF (where intracerebral vasculature reside) with cavitation occurring deep and diffusely into cerebral sulci. These cavitation events are adjacent to high interface strain rates at the subpial glial plate. Larger overpressure simulations (250 and 500kPa) demonstrated intraventricular cavitation—also associated with adjacent high periventricular strain rates. Additionally, models of embedded intraparenchymal vascular structures—with diameters as small as 0.6 mm—predicted intravascular cavitation with adjacent high perivascular strain rates. The co-location of local maxima of strain rates near several of the regions that appear to be preferentially damaged in blast TBI (vascular structures, subpial glial plate, perivascular regions, and periventricular regions) suggest that intracranial interface dynamics may be important in understanding how blast overpressures leads to intracranial injury.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Roadmap for IES Modeling and Simulation Activities

Since inception of the DOE-NE Integrated Energy Systems (IES) program, several program and modeling visions and roadmaps have been published. In 2017, the last modeling and simulation capability development plan was published. In 2020, a comprehensive roadmap for the DOE-NE Integrated Energy Systems program has been published. The current report is meant to update the 2017 modeling and simulation capability roadmap and complement the IES overall program roadmap published in 2020. The role of modeling and simulation within IES is to support the demonstration of new coupled integrated technologies along every step of the technology maturation from the strategic analysis of preferred system architecture to preliminary design, to laboratory testing, up to full commercial testing and integration. To achieve this role, modeling and simulation must be able to assess the technical performance and the economic viability of potential IES. Also, modeling and simulation must provide support for experimental evaluations, i.e., support component design and real time operations of experimental demonstration systems. Finally, modeling and simulation can help scale-up experimental systems to the final commercial systems. This report details the current state of the modeling and simulation efforts within IES for the above-mentioned areas, provides a gap analysis and proposes next steps for a time horizon over the next 4 to 5 years.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2017

Notes on modeling and simulation

These notes present a high-level overview of how modeling and simulation are carried out by practitioners. The discussion is of a general nature; no specific techniques are examined but the activities associated with all modeling and simulation approaches are briefly addressed. There is also a discussion of validation and verification and, at the end, a section on why modeling and simulation are useful.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Development and validation of an enhanced filtered drag model for simulating gas-solid fluidization of Geldart A particles in all flow regimes

Coarse-grid two-fluid simulation of gas-solid fluidized bed reactors based on the kinetic theory of granular flow exhibits a significant dependence on drag models, especially for Geldart A particles. Many drag models are available in the literature, which have been reported to work for different systems. This work focused on the evaluation of an enhanced filtered drag model along with other different drag models derived from different methods for three-dimensional two-fluid model simulations of gas-solid fluidized beds of Geldart A particles covering a broad range of fluidization regimes, including bubbling fluidization, turbulent fluidization, fast fluidization, and dilute phase transport regimes. Eight drag models were selected, which included five heterogeneous drag models and three homogeneous drag models. Comparison with the available experimental data demonstrates the need for modification of homogeneous drag models to account for the effect of mesoscale structures (i.e., bubbles and clusters). The enhanced filtered drag model and energy-minimization multi-scale (EMMS) drag models were found to achieve superior predictions in all fluidization regimes, while the other drag models were only capable of predicting certain fluidization regimes. Finally, the results of this work provide a guideline for choosing appropriate drag models for simulating Geldart A particles and suggestions on developing more reliable and general drag models applicable in all flow regimes.

42 ENGINEERING↗