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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Simulation and Modeling of Time-Resolved X-Ray Detector for the Saturn Accelerator

In this work, we present the technology-aided computer design (TCAD) device simulation and modeling of a silicon p-i-n diode for detecting time-dependent X-ray radiation. We show that the simulated forward and reverse breakdown current–voltage characteristics agree well with the measured data under nonradiation environment by only calibrating carrier lifetimes for the forward bias case and avalanche model critical fields for the reverse bias condition. Using the calibrated parameters and other nominal material properties, we simulated the radiation responses of the p-i-n diode and compared with experimental data when the diode was exposed to X-ray radiation at Sandia’s Saturn facility and the Idaho State University (ISU) TriMeV facility. For Saturn’s Gaussian dose-rate pulses, we show three findings from TCAD simulations. First, the simulated photocurrents are in excellent agreement with the measured data for two dose-rate pulses with peak values of 1.16×10 10 and 1.88×10 10 rad(Si)/s. Second, the simulation results of high dose-rate pulses predict increased delayed photocurrents with longer time tails in the diode electrical responses due to excess carrier generation. Third, simulated peak values of diode radiation responses versus peak dose rates at different bias conditions provide useful guidance to determine the dose-rate range that the p-i-n diode can reliably detect in experiment. For TriMeV’s non-Gaussian dose-rate pulse, our simulated diode response is in decent agreement with the measured data without further calibration. We also studied the effects of device geometry, recombination process, and dose-rate enhancement via TCAD simulations to understand the higher measured response in the time after the peak dose-rate radiation for the p-i-n diode exposed to TriMeV irradiation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

IMPLEMENTATION OF DETAILED CHEMISTRY MECHANISMS IN ENGINE SIMULATIONS

The stiffness of large chemistry mechanisms has been proved to be a major hurdle toward predictive engine simulations. As a result, detailed chemistry mechanisms with a few thousand species need to be reduced based on target conditions so that they can be accommodated within the available computational resources. The computational cost of simulations typically increases super-linearly with the number of species and reactions. This work aims to bring detailed chemistry mechanisms within the realm of engine simulations by coupling the framework of unsteady flamelets and fast chemistry solvers. A previously developed tabulated flamelet model (TFM) framework for nonpremixed combustion was used in this study. The flamelet solver consists of the traditional operator-splitting scheme with variable coefficient ordinary differential equation (ODE) solver (VODE) and a numerical Jacobian for solving the chemistry. In order to use detailed mechanisms with thousands of species, a new framework with the Livermore solver for ODEs in sparse form (LSODES) chemistry solver and an analytical Jacobian was implemented in this work. Results from 1D simulations show that with the new framework, the computational cost is linearly proportional to the number of species in a given chemistry mechanism. As a result, the new framework is 2-3 orders of magnitude faster than the conventional variable coefficient ODE (VODE) solver for large chemistry mechanisms. This new framework was used to generate unsteady flamelet libraries for ndodecane using a detailed chemistry mechanism with 2755 species and 11,173 reactions. The engine combustion network (ECN) spray A experiments, which consist of an igniting n-dodecane spray in turbulent, high-pressure engine conditions are simulated using large eddy simulations (LES) coupled with detailed mechanisms. A grid with 0.06 mm minimum cell size and 22 x 10(6) peak cell count was implemented. The framework is validated across a range of ambient temperatures against ignition delay and liftoff lengths (LOLs). Qualitative results from the simulations were compared against experimental OH and CH2O planar laser-induced fluorescence (PLIF) data. The models are able to capture the spatial and temporal trends in species compared to those observed in the experiments. Quantitative and qualitative comparisons between the predictions of the reduced and detailed mechanisms are presented in detail. The main goal of this study is to demonstrate that detailed reaction mechanisms (similar to 1000 species) can now be used in engine simulations with a linear increase in computation cost with number of species during the tabulation process and a small increase in the 3D simulation cost.

Kundu, Prithwish↗
DOE OSTI2015

A computational model to generate simulated three-dimensional breast masses

Purpose: To develop algorithms for creating realistic three-dimensional (3D) simulated breast masses and embedding them within actual clinical mammograms. The proposed techniques yield high-resolution simulated breast masses having randomized shapes, with user-defined mass type, size, location, and shape characteristics. Methods: The authors describe a method of producing 3D digital simulations of breast masses and a technique for embedding these simulated masses within actual digitized mammograms. Simulated 3D breast masses were generated by using a modified stochastic Gaussian random sphere model to generate a central tumor mass, and an iterative fractal branching algorithm to add complex spicule structures. The simulated masses were embedded within actual digitized mammograms. The authors evaluated the realism of the resulting hybrid phantoms by generating corresponding left- and right-breast image pairs, consisting of one breast image containing a real mass, and the opposite breast image of the same patient containing a similar simulated mass. The authors then used computer-aided diagnosis (CAD) methods and expert radiologist readers to determine whether significant differences can be observed between the real and hybrid images. Results: The authors found no statistically significant difference between the CAD features obtained from the real and simulated images of masses with either spiculated or nonspiculated margins. Likewise, the authors found that expert human readers performed very poorly in discriminating their hybrid images from real mammograms. Conclusions: The authors’ proposed method permits the realistic simulation of 3D breast masses having user-defined characteristics, enabling the creation of a large set of hybrid breast images containing a well-characterized mass, embedded within real breast background. The computational nature of the model makes it suitable for detectability studies, evaluation of computer aided diagnosis algorithms, and teaching purposes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Simulating the Impact of Dynamic Rerouting on Metropolitan-scale Traffic Systems

The rapid introduction of mobile navigation aides that use real-time road network information to suggest alternate routes to drivers is making it more difficult for researchers and government transportation agencies to understand and predict the dynamics of congested transportation systems. Computer simulation is a key capability for these organizations to analyze hypothetical scenarios; however, the complexity of transportation systems makes it challenging for them to simulate very large geographical regions, such as multi-city metropolitan areas. In this article, we describe enhancements to the Mobiliti parallel traffic simulator to model dynamic rerouting behavior with the addition of vehicle controller actors and vehicle-to-controller reroute requests. The simulator is designed to support distributed-memory parallel execution using discrete event simulation and be scalable on high-performance computing platforms. We demonstrate the potential of the simulator by analyzing the impact of varying the population penetration rate of dynamic rerouting on the San Francisco Bay Area road network. Using high-performance parallel computing, we can simulate a day in the San Francisco Bay Area with 19 million vehicle trips with 50 percent dynamic rerouting penetration over a road network with 0.5 million nodes and 1 million links in less than three minutes. We present a sensitivity study on the dynamic rerouting parameters, discuss the simulator’s parallel scalability, and analyze system-level impacts of changing the dynamic rerouting penetration. Furthermore, we examine the varying effects on different functional classes and geographical regions and present a validation of the simulation results compared to real-world data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A protocol and analysis of year-long simulations of global storm-resolving models and beyond

We propose a protocol to evaluate and analyze year-long simulations of global storm-resolving models (GSRMs). The proposed protocol complements an earlier 40-day simulation protocol under the DYAMOND (DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains) project to allow the analysis of the seasonal cycle and associated climatic relevant phenomena. This intercomparison aims to reveal how GSRMs, which can simulate mesoscale convective systems (MCSs) in the global domain, reproduce atmospheric large-scale structures related to convection beyond month-long simulations. The intercomparison for one-year simulations is conducted by either atmosphere-only models or atmosphere–ocean coupled models with atmospheric horizontal mesh sizes less than 5 km. We recommend the continuous four seasons from March 2020 to February 2021 as a target period for the intercomparison but with options for many groups to join more flexibly. The output variables are collected at 0.25° resolution, and archives of a small set of native grid variables are encouraged to analyze tropical cyclones and MCSs. Through the proposed global storm-resolving simulation, we will evaluate the climatological distributions of the atmospheric large-scale circulations, such as the Intertropical Convergence Zone (ITCZ), monsoon, midlatitude jets, their time evolution, and the upscale impacts on them. We present sample analyses from a one-year simulation using the 3.5 km mesh Nonhydrostatic Icosahedral Atmospheric Model (NICAM), revealing the realistic zonal contrast of tropical precipitation, no double ITCZ structure, the reasonable midlatitude jet position and intensity but a weak bias of storm track activities, and a warm bias over the Eurasia during boreal winter. We also clarify the cross-scale interaction, such as the effects of cold pools on mean precipitation over the Maritime Continent through the precipitation diurnal cycle and the effects of resolved gravity waves on midlatitude mean flows. The proposed one-year simulation protocol is referred to as the “Sendai Protocol.” This protocol is not unique or definite for evaluating GSRMs; we prospect a hierarchical set of experiments from short-term to multi-year simulations as GSRM intercomparisons.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Validating quantum-classical programming models with tensor network simulations

The exploration of hybrid quantum-classical algorithms and programming models on noisy near-term quantum hardware has begun. As hybrid programs scale towards classical intractability, validation and benchmarking are critical to understanding the utility of the hybrid computational model. In this paper, we demonstrate a newly developed quantum circuit simulator based on tensor network theory that enables intermediate-scale verification and validation of hybrid quantum-classical computing frameworks and programming models. We present our tensor-network quantum virtual machine (TNQVM) simulator which stores a multi-qubit wavefunction in a compressed (factorized) form as a matrix product state, thus enabling single-node simulations of larger qubit registers, as compared to brute-force statevector simulators. Our simulator is designed to be extensible in both the tensor network form and the classical hardware used to run the simulation (multicore, GPU, distributed). The extensibility of the TNQVM simulator with respect to the simulation hardware type is achieved via a pluggable interface for different numerical backends (e.g., ITensor and ExaTENSOR numerical libraries). We demonstrate the utility of our TNQVM quantum circuit simulator through the verification of randomized quantum circuits and the variational quantum eigensolver algorithm, both expressed within the eXtreme-scale ACCelerator (XACC) programming model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

ELM model simulations of Plum Island Ecosystems LTER low marsh site 2018-2020

Model simulations using the Department of Energy's Energy Exascale Earth System Model (E3SM) land model (ELM) with improved capabilities to represent vegetation response to salinity and inundation. The simulations were conducted for a tidal salt marsh at Plum Island Ecosystems Long Term Ecological Research (LTER) site near Rowley, Massachusetts, USA; the site is a low marsh dominated by Spartina alterniflora. The model was forced with site-specific meteorology, salinity and tidal cycles from 2018-2020. Four sets of model simulations are included and described below:1. Parameterization of the salinity response function. These simulations tested different combinations of values for optimal salinity and salinity tolerance.2. Model evaluation. This comparison conducted simulations using the default model, the salinity function only, the submergence function only, and both the salinity and submergence functions. 3. Salinity scenarios. These simulations used the 2018 salinity input data varied by -5 to +10 ppt salinity.4. Water level scenarios. These simulations used the tide height varied by -10 to +50 cm. These simulations were used to demonstrate how the salinity and submergence functions better represent carbon uptake by tidal salt marshes.The data package includes netCDF files used as forcing files for tide height and salinity, one for each year 2018-2020 at observed salinity concentrations, and an additional three forcing files in which salinity concentrations were varied 5 ppt lower, 5 ppt higher, and 10 ppt higher than the measured 2018 time series. Also included are python scripts for creating forcing files, plain text parameter and command files for running simulations, model outputs in netCDF format, and python scripts for visualizing outputs. Code for the modified E3SM model is archived in Sulman et al 2023 at doi:10.15485/1991625. More detail about files is provided in the README.md file.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

FATES size- and age-dependent mortality simulation output analysis scripts

This dataset contains python scripts to analyse outputs from the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) and accompanies the paper “Needham, J.F., Chambers, J., Fisher, R., Knox, R., and Koven, C. D., Forest responses to simulated elevated CO2 under alternate hypotheses of size- and age-dependent mortality, 2020, Global Change Biology”. These scripts process FATES outputs from size- and age-dependent mortality simulations which were run to test the effect of different mechanisms of mortality on forest response to elevated CO2 (eCO2). Specifically, these scripts will process single plant functional type (PFT) simulations in which mortality is either a constant background rate, size-dependent or age-dependent. In each case, a simulation with constant woody NPP is compared to a simulation in which woody NPP increases by 25% to simulate the growth response of forests to eCO2. In addition, the data package contains scripts to analyse ensemble simulations with size- and age-dependent mortality and two PFTs, that were run to test the impact of different demographic rates on coexistence and the forest response to eCO2. Finally, the dataset includes scripts for processing simulations testing the sensitivity of results to allometry and to the recruitment scheme.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

FATES size- and age-dependent mortality simulation outputs, 2019

This dataset contains outputs from the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) and accompanies the paper “Needham, J.F., Chambers, J., Fisher, R., Knox, R., and Koven, C. D., Forest responses to simulated elevated CO2 under alternate hypotheses of size- and age-dependent mortality, 2020, Global Change Biology”. Data are unprocessed FATES outputs from size- and age-dependent mortality simulations which were run to test the effect of different mechanisms of mortality on forest response to elevated CO2 (eCO2). Specifically, this data package contains single plant functional type (PFT) simulations in which mortality is either a constant background rate, size-dependent or age-dependent. In each case, a simulation with constant woody NPP is compared to a simulation in which woody NPP increases by 25% to simulate the growth response of forests to eCO2. Ensemble simulations with size- and age-dependent mortality and two PFTs test the impact of different demographic rates on coexistence and the forest response to eCO2. Finally, the dataset includes simulations testing the sensitivity of results to allometry and to the recruitment scheme.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

FATES crown damage simulation outputs 2022

This dataset contains outputs from the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) and accompanies the paper "Needham, J.F., Arellano, A., Davies, S.J., Fisher, R.A., Hammer, V., Knox, R., Mitre, D., Muller-Landau, H.C., Zuleta, D., Koven, C.D. Tree crown damage and its effects on forest carbon cycling in a tropical forest, 2022, Global Change Biology". Data are unprocessed netcdf file outputs from simulations that were run to test the effect of a new crown damage module in FATES. Specifically, this data package contains a sensitivity analysis to the carbon cushion parameter damage_Ccushion_ensemble_e1b5bd9_bf013ef_2021-09-02.h0.ensemble.sofar.nc, a sensitivity analysis to the root nitrogen stoichiometry parameter damage_Nstoich_ensemble_e1b5bd9_bf013ef_2021-09-02.h0.ensemble.sofar.nc, a sensitivity analysis to parameters controlling crown damage and recovery damage_recovery_ensemble_e1b5bd9_354f0b0_2021-09-02.h0.ensemble.sofar.nc, and a sensitivity analysis to the number of crown damage bins elm_fates_bci_*_damagebins.Eac53ccb80b-F8f994c29.2022-04-19.elm.h0.fullrun.nc. This data package also contains a high root nitrogen configuration of FATES, including both a control, and a crown damage simulation high_root_N_control_e1b5bd9_354f0b0_2021-09-02.clm2.h0.fullrun.nc and high_root_N_damage_e1b5bd9_354f0b0_2021-09-02.clm2.h0.fullrun.nc. There is an analogous low root nitrogen configuration of FATES, including a control, low_root_N_control_e1b5bd9_bf013ef_2021-09-02.clm2.h0.fullrun.nc a damage only simulation low_root_N_damageonly_e1b5bd9_bf013ef_2021-09-02.clm2.h0.fullrun.nc, a damage plus mortality simulation low_root_N_damage_mort_e1b5bd9_bf013ef_2021-09-02.clm2.h0.fullrun.nc, and a mortality only simulation low_root_N_mort_only_e1b5bd9_ef845c8_2021-09-02.clm2.h0.fullrun.nc. Finally, there is a two PFT simulation in which we test the effect of recovery on competitive dynamics, low_root_N_damage_two_pfts_stoichastic_e1b5bd9_bf013ef_2021-09-10.clm2.h0.fullrun.nc. These simulations test the effect of representing crown damage in FATES, compared with simulations that have an equivalent increase in mortality. Jupyter notebooks to analyse these files can be found at https://github.com/JessicaNeedham/Needham_etal_GCB_2022_FATES_crown_damage.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Understanding and Improving CRM and GCM Simulations of Cloud Systems with ARM Observations

The works supported by this ASR project lay the solid foundation for improving the parameterization of convection and clouds in the NCAR CCSM and the climate simulations. We have made a significant use of CRM simulations and ARM observations to produce thermodynamically and dynamically consistent multi-year cloud and radiative properties; improve the GCM simulations of convection, clouds and radiative heating rate and fluxes using the ARM observations and CRM simulations; and understand the seasonal and annual variation of cloud systems and their impacts on climate mean state and variability. We conducted multi-year simulations over the ARM SGP site using the CRM with multi-year ARM forcing data. The statistics of cloud and radiative properties from the long-term CRM simulations were compared and validated with the ARM measurements and value added products (VAP). We evaluated the multi-year climate simulations produced by the GCM with the modified convection scheme. We used multi-year ARM observations and CRM simulations to validate and further improve the trigger condition and revised closure assumption in NCAR GCM simulations that demonstrate the improvement of climate mean state and variability. We combined the improved convection scheme with the mosaic treatment of subgrid cloud distributions in the radiation scheme of the GCM. The mosaic treatment of cloud distributions has been implemented in the GCM with the original convection scheme and enables the use of more realistic cloud amounts as well as cloud water contents in producing net radiative fluxes closer to observations. A physics-based latent heat (LH) retrieval algorithm was developed by parameterizing the physical linkages of observed hydrometeor profiles of cloud and precipitation to the major processes related to the phase change of atmospheric water.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Annual Report: Carbon Capture Simulation Initiative (CCSI) (30 September 2013)

The Carbon Capture Simulation Initiative (CCSI) is a partnership among national laboratories, industry and academic institutions that is developing and deploying state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technologies from discovery to development, demonstration, and ultimately the widespread deployment to hundreds of power plants. The CCSI Toolset will provide end users in industry with a comprehensive, integrated suite of scientifically validated models, with uncertainty quantification (UQ), optimization, risk analysis and decision making capabilities. The CCSI Toolset incorporates commercial and open-source software currently in use by industry and is also developing new software tools as necessary to fill technology gaps identified during execution of the project. Ultimately, the CCSI Toolset will (1) enable promising concepts to be more quickly identified through rapid computational screening of devices and processes; (2) reduce the time to design and troubleshoot new devices and processes; (3) quantify the technical risk in taking technology from laboratory-scale to commercial-scale; and (4) stabilize deployment costs more quickly by replacing some of the physical operational tests with virtual power plant simulations. CCSI is led by the National Energy Technology Laboratory (NETL) and leverages the Department of Energy (DOE) national laboratories’ core strengths in modeling and simulation, bringing together the best capabilities at NETL, Los Alamos National Laboratory (LANL), Lawrence Berkeley National Laboratory (LBNL), Lawrence Livermore National Laboratory (LLNL), and Pacific Northwest National Laboratory (PNNL). The CCSI’s industrial partners provide representation from the power generation industry, equipment manufacturers, technology providers and engineering and construction firms. The CCSI’s academic participants (Carnegie Mellon University, Princeton University, West Virginia University, Boston University and the University of Texas at Austin) bring unparalleled expertise in multiphase flow reactors, combustion, process synthesis and optimization, planning and scheduling, and process control techniques for energy processes. During Fiscal Year (FY) 13, CCSI announced the initial release of its first set of computational tools and models during the October 2012 meeting of its Industry Advisory Board. This initial release led to five companies licensing the CCSI Toolset under a Test and Evaluation Agreement this year. By the end of FY13, the CCSI Technical Team had completed development of an updated suite of computational tools and models. The list below summarizes the new and enhanced toolset components that were released following comprehensive testing during October 2013. 1. FOQUS. Framework for Optimization and Quantification of Uncertainty and Sensitivity. Package includes: FOQUS Graphic User Interface (GUI), simulation-based optimization engine, Turbine Client, and heat integration capabilities. There is also an updated simulation interface and new configuration GUI for connecting Aspen Plus or Aspen Custom Modeler (ACM) simulations to FOQUS and the Turbine Science Gateway. 2. A new MFIX-based Computational Fluid Dynamics (CFD) model to predict particle attrition. 3. A new dynamic reduced model (RM) builder, which generates computationally efficient RMs of the behavior of a dynamic system. 4. A completely re-written version of the algebraic surrogate model builder for optimization (ALAMO). The new version is several orders of magnitude faster than the initial release and eliminates the MATLAB dependency. 5. A new suite of high resolution filtered models for the hydrodynamics associated with horizontal cylindrical objects in a flow path. 6. The new Turbine Science Gateway (Cluster), which supports FOQUS for running multiple simulations for optimization or UQ using a local computer or cluster. 7. A new statistical tool (BSS-ANOVA-UQ) for calibration and validation of CFD models. 8. A new basic data submodel in Aspen Plus format for a representative high viscosity capture solvent, 2-MPZ system. 9. An updated RM tool for CFD (REVEAL) that can create a RM from MFIX. A new lightweight, stand-alone version will be available in late 2013. 10. An updated RM integration tool to convert the RM from REVEAL into a CAPE-OPEN or ACM model for use in a process simulator. 11. An updated suite of unified steady-state and dynamic process models for solid sorbent carbon capture included bubbling fluidized bed and moving bed reactors. 12. An updated and unified set of compressor models including steady-state design point model and dynamic model with surge detection. 13. A new framework for the synthesis and optimization of coal oxycombustion power plants using advanced optimization algorithms. This release focuses on modeling and optimization of a cryogenic air separation unit (ASU). 14. A new technical risk model in spreadsheet format. 15. An updated version of the sorbent kinetic/equilibrium model for parameter estimation for the 1st generation sorbent model. 16. An updated process synthesis superstructure model to determine optimal process configurations utilizing surrogate models from ALAMO for adsorption and regeneration in a solid sorbent process. 17. Validation models for NETL Carbon Capture Unit utilizing sorbent AX. Additional validation models will be available for sorbent 32D in 2014. 18. An updated hollow fiber membrane model and system example for carbon capture. 19. An updated reference power plant model in Thermoflex that includes additional steam extraction and reinjection points to enable heat integration module. 20. An updated financial risk model in spreadsheet format.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2015

First-Principles Petascale Simulations for Predicting Deflagration to Detonation Transition in Hydrogen-Oxygen Mixtures

Hydrogen has emerged as an important fuel across a range of industries as a means of achieving energy independence and to reduce emissions. DDT and the resulting detonation waves in hydrogen-oxygen can have especially catastrophic consequences in a variety of industrial and energy producing settings related to hydrogen. First-principles numerical simulations of flame acceleration and DDT are required for an in-depth understanding of the phenomena and facilitating design of safe hydrogen systems. The goals of this project were (1) to develop first-principles petascale reactive flow Navier-Stokes simulation code for predicting gaseous high-speed combustion and detonation (HSCD) phenomena and (2) demonstrate feasibility of first-principles simulations of rapid flame acceleration and deflagration-to-detonation transition (DDT) in stoichiometric hydrogen-oxygen mixture (2H 2 + O 2 ). The goals of the project have been accomplished. We have developed a novel numerical simulation code, named HSCD, for performing first-principles direct numerical simulations of high-speed hydrogen combustion. We carried out a series of validating numerical simulations of inert and reactive shock reflection experiments in shock tubes. We then performed a pilot numerical simulation of flame acceleration in a long pipe. The simulation showed the transition of the rapidly accelerating flame into a detonation. The DDT simulations were performed using BG/Q Mira at the Argonne National Laboratory, currently the fourth fastest super-computer in the world.

08 HYDROGEN↗
DOE OSTI2015

Stand-Alone Dynamic System Simulation of a Fissile Solution System

Dynamic system simulations (DSS) of fissile solution systems (FSS) have been performed at Los Alamos National Laboratory (LANL) for several years. DSS have been designed and executed using the DESIRE (Direct Executing Simulation in Real Time) system, a platform ideal for expert system modelers, as it allows for direct mathematical specification of a model, and facilities for performing experiments and analyses with the model. Models built in DESIRE have been compared to historical data from several historic aqueous homogeneous reactors (AHR) showing close agreement between experimental data and model estimates. Historical systems modeled include: SUPO (Super Power), an AHR that operated at Los Alamos National Laboratory from 1951 to 1974; SILENE, which was operated by CEA at Valduc, France until 2011; KEWB (Kinetics Experiment Water Boiler) A-2 and B-5 cores, operated by North American Atomics during the 1960’s and 1970’s. SUPO is considered a benchmark for steady-state operations, SILENE for pulse, and KEWB as confirmatory for both modes. However, there are some simulation tasks that are not well-suited to DESIRE model implementation. These tasks include engineering design and analysis and providing a hardware simulator backend. It has been determined that executable simulation models would better suit these purposes, hence a process for converting DESIRE simulation models to executable simulation models was designed and implemented, and several models have been converted. DESIRE simulation models are converted to C++ executable models by an automated process. The conversion process is quick, accurate and repeatable, giving confidence that converted models will perform as well as the original DESIRE models. Extensive testing on the SUPO and accelerator driven subcritical system models has shown that the executable models perform almost identically to the DESIRE models. All major trends and events are simulated with excellent agreement and the steady-state results typically agree within a small fraction of a percent (always better than 0.1% and generally better than 0.01% agreement).

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

High Fidelity Simulations of Large-Scale Wireless Networks

The worldwide proliferation of wireless connected devices continues to accelerate. There are 10s of billions of wireless links across the planet with an additional explosion of new wireless usage anticipated as the Internet of Things develops. Wireless technologies do not only provide convenience for mobile applications, but are also extremely cost-effective to deploy. Thus, this trend towards wireless connectivity will only continue and Sandia must develop the necessary simulation technology to proactively analyze the associated emerging vulnerabilities. Wireless networks are marked by mobility and proximity-based connectivity. The de facto standard for exploratory studies of wireless networks is discrete event simulations (DES). However, the simulation of large-scale wireless networks is extremely difficult due to prohibitively large turnaround time. A path forward is to expedite simulations with parallel discrete event simulation (PDES) techniques. The mobility and distance-based connectivity associated with wireless simulations, however, typically doom PDES and fail to scale (e.g., OPNET and ns-3 simulators). We propose a PDES-based tool aimed at reducing the communication overhead between processors. The proposed solution will use light-weight processes to dynamically distribute computation workload while mitigating communication overhead associated with synchronizations. This work is vital to the analytics and validation capabilities of simulation and emulation at Sandia. We have years of experience in Sandia’s simulation and emulation projects (e.g., MINIMEGA and FIREWHEEL). Sandia’s current highly-regarded capabilities in large-scale emulations have focused on wired networks, where two assumptions prevent scalable wireless studies: (a) the connections between objects are mostly static and (b) the nodes have fixed locations.

Onunkwo, Uzoma↗
DOE OSTI2017

Large Scale Simulation Platform for NODES Validation Study

This report summarizes the Large Scale (LS) simulation platform created for the Eaton NODES project. The simulation environment consists of both wholesale market simulator and distribution simulator and includes the CAISO wholesale market model and a PG&E footprint of 25-75 feeders to validate the scalability under a scenario of 33% RPS in California with additional 17% of DERS coming from distribution and customers. The simulator can generate hourly unit commitment, 5-minute economic dispatch, and 4-second AGC regulation signals. The simulator is also capable of simulating greater than 10k individual controllable devices. Simulated DERs include water heaters, EVs, residential and light commercial HVAC/buildings, and residential-level battery storage. Feeder-level voltage regulators and capacitor banks are also simulated for feeder-level real and reactive power management and Vol/Var control.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Simulant Development for LAWPS Testing

This report describes simulant development work that was conducted to support the technology maturation of the LAWPS facility. Desired simulant physical properties (density, viscosity, solids concentration, solid particle size), sodium concentrations, and general anion identifications were provided by WRPS. The simulant recipes, particularly a “nominal” 5.6M Na simulant, are intended to be tested at several scales, ranging from bench-scale (500 mL) to full-scale. Each simulant formulation was selected to be chemically representative of the waste streams anticipated to be fed to the LAWPS system, and used the current version of the LAWPS waste specification as a formulation basis. After simulant development iterations, four simulants of varying sodium concentration (5.6M, 6.0M, 4.0M, and 8.0M) were prepared and characterized. The formulation basis, development testing, and final simulant recipes and characterization data for these four simulants are presented in this report.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Expanding the computational frontier of multi-scale atmospheric simulation to advance understanding of low cloud / climate feedbacks: Final Technical Report

Marine boundary layer clouds are a challenge for climate models. They cover much of the oceans, but they are driven by small-scale turbulent eddies only a few hundred meters across, which in turn respond to the cloud formation. Global climate models have a grid spacing that is far too large to simulate such fluid motions, so they parameterize these cloud formation processes. Different climate modeling groups have designed different parameterizations in which the clouds turn out to be differently sensitive to a warming climate. This drives uncertainties in our best guess at the sensitivity of global warming to greenhouse gas increases. If these cloud-forming eddies could be directly simulated using the well-known equations of fluid motion, they would no longer need to be parameterized, removing a major source of climate modeling uncertainty. In this project, we overcame software engineering challenges to successfully implemented ‘ultraparameterization’ (UP), the first global model that does this, and we tested how well it works. We simulated five-year periods with present-day temperatures and with a warmer climate, and we investigated how the UP-simulated clouds responded to climate – the ‘cloud feedback’ problem. We found little response of clouds at all latitudes to the imposed climate change, which is within the range of predictions of conventional global climate models. UP is a variation on superparameterization, in which small cloud-resolving models (CRMs) are embedded in each column of the global model. In UP, the CRM grid is fine enough (250 m horizontal × 20 m vertical) to explicitly capture boundary-layer turbulent eddies and associated clouds. Because only one small columnar patch is simulated within each climate model grid cell, this is a million-fold more efficient than simulating the entire globe on this same CRM grid., but achieves much of the same effect for the cloud properties. It doesn’t work perfectly. For instance, like conventional climate models, UP simulates too little subtropical stratocumulus cloud, a bias that we are continuing to work to reduce. However, because it directly simulates the turbulent cloud-forming processes, UP is inherently more plausible for simulating how clouds will change in a perturbed climate. In future, we hope to apply UP to another key climate modeling issue: cloud-aerosol interaction and the effect of human-produced aerosols on the climate change we have already experienced and that which is likely to come.

54 ENVIRONMENTAL SCIENCES↗