Results for “Advanced Modeling and Simulation” — Page 96

DOE OSTI2022

Simulated wind speed and initial conditions over the WFIP2 region: Cold-front (D02)

The purpose of this work is to assess the sensitivity of the forecast for turbine height wind speed to initial condition (IC) uncertainties over the Columbia River Gorge and Columbia River Basin for two typical weather phenomena: a local thermal gradient induced by a marine air intrusion and passage of a cold front. The Weather Research and Forecasting (WRF) model data assimilation system (WRFDA) was used to generate ensemble ICs from the North American Regional Analysis (NARR) for the WRF model initialization. The simulated turbine-height wind speeds were categorized into four types using the self-organizing map (SOM) technique. This work advances understanding of IC uncertainties impacts on wind speed forecasts and locates the high-impact regions.

17 WIND ENERGY↗

DOE OSTI2022

Simulated wind speed and initial conditions over the WFIP2 region: Sea-breeze (D01)

The purpose of this work is to assess the sensitivity of the forecast for turbine height wind speed to initial condition (IC) uncertainties over the Columbia River Gorge and Columbia River Basin for two typical weather phenomena: a local thermal gradient induced by a marine air intrusion and passage of a cold front. The Weather Research and Forecasting (WRF) model data assimilation system (WRFDA) was used to generate ensemble ICs from the North American Regional Analysis (NARR) for the WRF model initialization. The simulated turbine-height wind speeds were categorized into four types using the self-organizing map (SOM) technique. This work advances understanding of IC uncertainties impacts on wind speed forecasts and locates the high-impact regions.

17 WIND ENERGY↗

DOE OSTI2022

Simulated wind speed and initial conditions over the WFIP2 region: Sea-breeze (D02)

The purpose of this work is to assess the sensitivity of the forecast for turbine height wind speed to initial condition (IC) uncertainties over the Columbia River Gorge and Columbia River Basin for two typical weather phenomena: a local thermal gradient induced by a marine air intrusion and passage of a cold front. The Weather Research and Forecasting (WRF) model data assimilation system (WRFDA) was used to generate ensemble ICs from the North American Regional Analysis (NARR) for the WRF model initialization. The simulated turbine-height wind speeds were categorized into four types using the self-organizing map (SOM) technique. This work advances understanding of IC uncertainties impacts on wind speed forecasts and locates the high-impact regions.

17 WIND ENERGY↗

DOE OSTI2023

PyFLEXTRKR: a flexible feature tracking Python software for convective cloud analysis

Abstract. This paper describes the new open-source framework PyFLEXTRKR (Python FLEXible object TRacKeR), a flexible atmospheric feature tracking software package with specific capabilities to track convective clouds from a variety of observations and model simulations. This software can track any atmospheric 2D objects and handle merging and splitting explicitly. The package has a collection of multi-object identification algorithms, scalable parallelization options, and has been optimized for large datasets including global high-resolution data. We demonstrate applications of PyFLEXTRKR on tracking individual deep convective cells and mesoscale convective systems from observations and model simulations ranging from large-eddy resolving (∼100s m) to mesoscale (∼10s km) resolutions. Visualization, post-processing, and statistical analysis tools are included in the package. New Lagrangian analyses of convective clouds produced by PyFLEXTRKR applicable to a wide range of datasets and scales facilitate advanced model evaluation and development efforts as well as scientific discovery.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Peer Review Lessons Learned - DOE and Regulator Perspectives - 17140

The DOE NNSA Nevada Field Office (NFO) Underground Test Area (UGTA) Activity requires an external peer review to complete an extensive stage of site characterization and groundwater flow and contaminant transport model(s) development. The external peer review evaluates whether assumptions, methods, and conclusions derived from model(s) outputs are based on sound scientific principles and examines the scientific appropriateness of the model(s) outputs for informing the regulatory decision. The regulatory decision which is made by the Nevada Division of Environmental Protection (NDEP) is whether the model is acceptable to advance to the next UGTA strategy stage. Depending on the specific corrective action unit, the next stage is a Corrective Action Decision Document/Corrective Action Plan or Closure Stage. Three external peer reviews have taken place to date for the UGTA Activity. The first one resulted in a second phase of characterization and model development. The second external peer review resulted in advancement to the next UGTA strategy stage. While advancement to the next strategy stage was recommended by the third external peer review, a series of supplemental data collection and analyses and model simulation activities to address external peer review comments, including drilling three new wells and sampling multiple wells, occurred before moving into the next UGTA strategy stage. Twelve participants representing different aspects of the peer reviews (NDEP, NNSA/NFO, science advisors, presenters, and external peer reviewers) were interviewed to generate a combined lessons learned. Questions were asked regarding their experience with the process including panel selection, focused questions, presentations, interactions between UGTA Activity participants and reviewers, and results. The interview results were combined with the outcome of a published lessons learned report developed following the first external peer review. In general, those interviewed believed that all three external peer reviews were satisfactory and met the goals of the FFACO process. The following seven lessons learned were identified: (1) Ensure the panel is not biased and has a balance of technical and regulatory background; (2) Clearly state the review objective(s) at the start of the review; (3) Ask focused questions that support the peer review objective(s) but that do not ask the specific regulatory question; (4) Establish a peer review panel earlier in the strategy process; (5) Establish one point of contact for the entire review and conduct periodic meetings with the peer review panel to ensure focus remains on the review objective(s) and to ensure that pertinent information is provided; (6) Ensure that presentations are well coordinated, anomalous data or analysis results are addressed, and are focused on supporting the peer review objective(s); and (7) Carefully consider the panel's recommendations prior to embarking on a particular path forward. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2015

Benchmark of numerical tools simulating beam propagation and secondary particles in ITER NBI

Injection of high energy beams of neutral particles is a method for plasma heating in fusion devices. The ITER injector, and its prototype MITICA (Megavolt ITER Injector and Concept Advancement), are large extrapolations from existing devices: therefore numerical modeling is needed to set thermo-mechanical requirements for all beam-facing components. As the power and charge deposition originates from several sources (primary beam, co-accelerated electrons, and secondary production by beam-gas, beam-surface, and electron-surface interaction), the beam propagation along the beam line is simulated by comprehensive 3D models. This paper presents a comparative study between two codes: BTR has been used for several years in the design of the ITER HNB/DNB components; SAMANTHA code was independently developed and includes additional phenomena, such as secondary particles generated by collision of beam particles with the background gas. The code comparison is valuable in the perspective of the upcoming experimental operations, in order to prepare a reliable numerical support to the interpretation of experimental measurements in the beam test facilities. The power density map calculated on the Electrostatic Residual Ion Dump (ERID) is the chosen benchmark, as it depends on the electric and magnetic fields as well as on the evolution of the beam species via interaction with the gas. Finally the paper shows additional results provided by SAMANTHA, like the secondary electrons produced by volume processes accelerated by the ERID fringe-field towards the Cryopumps.

43 PARTICLE ACCELERATORS↗

DOE OSTI2015

From documentation to prediction: Raising the bar for thermokarst research

Here we report that to date the majority of published research on thermokarst has been directed at documenting its form, occurrence, and rates of occurrence. The fundamental processes driving thermokarst have long been largely understood. However, the detailed physical couplings between, water, air, soil, and the thermal dynamics governing freeze-thaw and soil mechanics is less understood and not captured in models aimed at predicting the response of frozen soils to warming and thaw. As computational resources increase more sophisticated mechanistic models can be applied; these show great promise as predictive tools. These models will be capable of simulating the response of soil deformation to thawing/freezing cycles and the long-term, non-recoverable response of the land surface to the loss of ice. At the same time, advances in remote sensing of permafrost environments also show promise in providing detailed and spatially extensive estimates in the rates and patterns of subsidence. These datasets provide key constraints to calibrate and evaluate the predictive power of mechanistic models. In conclusion, in the coming decade, these emerging technologies will greatly increase our ability to predict when, where, and how thermokarst will occur in a changing climate.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Accelerating the rate of discovery: toward high-repetition-rate HED science

As high-intensity short-pulse lasers that can operate at high-repetition-rate (HRR) (>10 H z ) come online around the world, the high energy density (HED) science they enable will experience a radical paradigm shift. The >10 3 increase in shot rate over today's shot-per-hour drivers translates into dramatically faster data acquisition, more experiments, and the ability to exploit machine learning, and thus the potential to significantly accelerate the advancement of HED science. A wide range of HED experiments, from opacity investigations to secondary source generation to plasma nuclear physics, will benefit from the increased statistics, precision, and exploration of phase space. Besides increasing the rate at which scientific experiments can be performed, HRR also allows for the rapid delivery of optimal experiments supported by simulations and modeling augmented by close coupling to empirical data. To fully realize such an HRR framework, numerous subsystems must be developed and brought together, including feedback laser control loops, high-throughput targetry and diagnostics, cognitive simulation, enhanced HED codes, and advanced data analytics. This paper describes the vision for an integrated HRR laser experimental HED system and outlines some of the major considerations and challenges for realizing it.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2015

Quantifying Supply Risk at a Cellulosic Biorefinery

In order to increase the sustainability and security of the nation’s energy supply, the U.S. Department of Energy through its Bioenergy Technology Office has set a vision for one billion tons of biomass to be processed for renewable energy and bioproducts annually by the year 2030. The Renewable Fuels Standard limits the amount of corn grain that can be used in ethanol conversion sold in the U.S, which is already at its maximum. Therefore making the DOE’s vision a reality requires significant growth in the advanced biofuels industry where currently three cellulosic biorefineries convert cellulosic biomass to ethanol. Risk mitigation is central to growing the industry beyond its infancy to a level necessary to achieve the DOE vision. This paper focuses on reducing the supply risk that faces a firm that owns a cellulosic biorefinery. It uses risk theory and simulation modeling to build a risk assessment model based on causal relationships of underlying, uncertain, supply driving variables. Using the model the paper quantifies supply risk reduction achieved by converting the supply chain from a conventional supply system (bales and trucks) to an advanced supply system (depots, pellets, and trains). Results imply that the advanced supply system reduces supply system risk, defined as the probability of a unit cost overrun, from 83% in the conventional system to 4% in the advanced system. Reducing cost risk in this nascent industry improves the odds of realizing desired growth.

09 BIOMASS FUELS↗

DOE OSTI2024

Bridging New Observational Capabilities and Process-Level Simulation: Insights into Aerosol Roles in the Earth System

The spatial distribution of ambient aerosol particles significantly impacts aerosol–radiation–cloud interactions, which contribute to the largest uncertainty in global anthropogenic radiative forcing estimations. However, the atmospheric boundary layer and lower free troposphere have not been adequately sampled in terms of spatiotemporal resolution, hindering a comprehensive characterization of various atmospheric processes and impeding our understanding of the Earth system. To address this research data gap, we have leveraged the development of uncrewed aerial systems (UAS) and advanced measurement techniques to obtain mesoscale spatial data on aerosol microphysical and optical properties around the U.S. Southern Great Plains (SGP) atmospheric observatory. Our study also benefits from state-of-the-art laboratory facilities that include three-dimensional molecular imaging techniques enabled by secondary ion mass spectrometry and nanogram-level chemical composition analysis via micronebulization aerosol mass spectrometry. Through our study, we have developed a framework for observation–modeling integration, enabling an examination of how various assumptions about the organic–inorganic components mixing state, inferred from chemical analysis, affect clouds and radiation in observation-constrained model simulations. By integrating observational constraints (derived from offline chemical analysis of the aerosol surface using collected samples) with in situ UAS observations, we have identified a prominent role of organic-enriched nanometer layers located at the surface of aerosol particles in determining profiles of aerosol optical and hygroscopic properties over the SGP observatory. Furthermore, we have improved the agreement between predicted clouds and ground-based cloud lidar measurements. This UAS–model–laboratory integration exemplifies how these new advanced capabilities can significantly enhance our understanding of aerosol–radiation–cloud interactions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Frozen Freedom: Unleashing Grocery Store Demand Flexibility: Preprint

Grocery stores consumed approximately 3% of total electricity used by commercial buildings in the U.S. in 2018 (EIA 2018), representing a unique end-use load profile characterized by the critical use of refrigerated display cases. Exploring demand response (DR) scenarios in grocery stores presents an opportunity to enhance the efficiency and sustainability of surrounding communities. In addition, recent studies demonstrate that implementing control algorithms considering demand flexibility strategies can lead to load and peak reductions in standalone refrigerated display cases. Because small business grocery stores operate on thin margins, the energy bill cost savings DR might provide could make a positive difference toward continued operations. Still, uncertainty remains about the extent of demand flexibility potential controls could provide when coupling refrigeration with whole building operation. To enhance economic viability and grid stability, it is essential to quantify the load flexibility capability of grocery stores. Advanced controls can optimize energy consumption by responding to load shedding, shifting, and DR events, as well as daily Time-of-Use (TOU) rates without compromising food safety. Using both quantitative data and interviews with community-based organizations, we developed a full-size store model and two small store models with controlled refrigerated cases, HVAC, and lighting systems based on actual grocery store properties. Through simulations, we have assessed load flexibility strategies with varied DR events. The results highlight potential for energy and peak reduction with advanced or basic controls. However, interviews and data indicate that more support is needed to make DR strategies consistently accessible to small grocery stores.

demand flexibility↗

DOE OSTI2018

Development and validation of two-phase flow models and critical heat flux prediction for the highly-scalable CFD code NEK-2P

A project is underway to develop, verify and validate an advanced two-phase flow modeling capability for the highly-scalable high-performance CFD code NEK5000[1]. The goal of the project is to develop a new two-phase version of the NEK5000code, named NEK-2P, to simulate the two-phase flow and heat transfer phenomena that occur in a Boiling Water Reactor (BWR) fuel bundle under various operating conditions. The NEK-2P two-phase flow models follow the approach used for the Extended Boiling Framework [2-3] previously developed at Argonne, but include more fundamental physical models of boiling phenomena and advanced numerical algorithms for improved computational accuracy, robustness, and computational speed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Quality Control Methods for Advanced Metering Infrastructure Data

While urban-scale building energy modeling is becoming increasingly common, it currently lacks standards, guidelines, or empirical validation against measured data. Empirical validation necessary to enable best practices is becoming increasingly tractable. The growing prevalence of advanced metering infrastructure has led to significant data regarding the energy consumption within individual buildings, but is something utilities and countries are still struggling to analyze and use wisely. In partnership with the Electric Power Board of Chattanooga, Tennessee, a crude OpenStudio/EnergyPlus model of over 178,000 buildings has been created and used to compare simulated energy against actual, 15-min, whole-building electrical consumption of each building. In this study, classifying building type is treated as a use case for quantifying performance associated with smart meter data. This article attempts to provide guidance for working with advanced metering infrastructure for buildings related to: quality control, pathological data classifications, statistical metrics on performance, a methodology for classifying building types, and assess accuracy. Advanced metering infrastructure was used to collect whole-building electricity consumption for 178,333 buildings, define equations for common data issues (missing values, zeros, and spiking), propose a new method for assigning building type, and empirically validate gaps between real buildings and existing prototypes using industry-standard accuracy metrics.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Release on the Virtual Test Bed of an MSRE thermal hydraulics model

The nuclear industry is taking leaps in innovations with companies seeking a sustainable energy future through advanced nuclear reactors. The \gls{DOE}’s \gls{neams} program seeks to substantiate and bolster the deployment of advanced reactors through flexible multifidelity, multiphysics simulations of advanced nuclear reactors. Applications like SAM for one-dimensional systems thermal-hydraulics, and Pronghorn for multidimensional coarse mesh thermal-hydraulics, are geared to support innovations in industry by facilitating design, optimization, and licensing of advanced nuclear reactors. Coupling systems thermal-hydraulics and computational fluid dynamics codes can be difficult as the pressure coupling converges slowly; however, it is important to obtain the desired accuracy in each part of the primary loop. The authors of this model created an \gls{odc}~\cite{Mau23} approach to coupling SAM and Pronghorn. Leveraging this coupling technique, a \gls{msre} model was developed and released to the \gls{neams}/\gls{nric} \gls{vtb}. The \gls{msre} was chosen to be modeled because of the wealth of experimental data available and because of the strong physics coupling between the core and primary circuit \cite{doi:10.13182/NT8-2-118}. This document contextualizes the history of the \gls{msre}, describes the thermal hydraulics models used, and detail the implementation of multidimensional thermal-hydraulics and system codes based on the \gls{odc} method~\cite{Penn} for the \gls{msre} model. Finally, this document presents how other modelers could apply the SAM-Pronghorn \gls{odc} for other advanced reactor models. Current item is the set of slides for ANS Winter 23. The release of the model and the ANS summary have already been approved

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Release on the Virtual Test Bed of an MSRE thermal hydraulics model

The nuclear industry is taking leaps in innovations with companies seeking a sustainable energy future through advanced nuclear reactors. The \gls{DOE}’s \gls{neams} program seeks to substantiate and bolster the deployment of advanced reactors through flexible multifidelity, multiphysics simulations of advanced nuclear reactors. Applications like SAM for one-dimensional systems thermal-hydraulics, and Pronghorn for multidimensional coarse mesh thermal-hydraulics, are geared to support innovations in industry by facilitating design, optimization, and licensing of advanced nuclear reactors. Coupling systems thermal-hydraulics and computational fluid dynamics codes can be difficult as the pressure coupling converges slowly; however, it is important to obtain the desired accuracy in each part of the primary loop. The authors of this model created an \gls{odc}~\cite{Mau23} approach to coupling SAM and Pronghorn. Leveraging this coupling technique, a \gls{msre} model was developed and released to the \gls{neams}/\gls{nric} \gls{vtb}. The \gls{msre} was chosen to be modeled because of the wealth of experimental data available and because of the strong physics coupling between the core and primary circuit \cite{doi:10.13182/NT8-2-118}. This document contextualizes the history of the \gls{msre}, describes the thermal hydraulics models used, and detail the implementation of multidimensional thermal-hydraulics and system codes based on the \gls{odc} method~\cite{Penn} for the \gls{msre} model. Finally, this document presents how other modelers could apply the SAM-Pronghorn \gls{odc} for other advanced reactor models.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

Quantitative measurements of dislocations in metals for advancing predictive simulations

LLNL applications require scientists to predict how materials evolve under various thermomechanical conditions. While this is achieved through physics-based simulations, uncertainty in the predictions of mechanical properties remains a serious challenge that limits the predictive capabilities of models because we lack methods to compare predictions of atomic-scale defects (dislocations) with experimental measurements. High energy X-ray diffraction (HEXRD) is the most relevant technique that can provide the necessary statistical information on dislocations. However, this technique is not yet quantitative because we lack a precise understanding of the relationship between X-ray diffraction patterns and the underlying material dislocation content and arrangements. To address this need, we used our novel computational X-ray diffraction method to simulate the effect of dislocations on the diffraction patterns. We compared virtual and experimental diffraction patterns. Results allowed us to clearly establish the relationship between X-ray diffraction patterns and the underlying dislocation structures, proving that it is feasible to quantitatively measure dislocation statistics with HEXRD. This project delivered a method that can provide the missing piece to LLNL’s mechanical property simulations in advanced metals by obtaining experimentally long-needed quantitative dislocation data, which could fully enable predictive capabilities.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Interaction between S100P and the anti-allergy drug cromolyn

Highlights: • The interaction between S100P–cromolyn was investigated by fluorescence spectroscopy. • The interfacial residues on S100P and cromolyn contact surface were mapped by {sup 1}H-{sup 15}N HSQC experiments. • S100P–cromolyn complex model was generated from NMR restraints using HADDOCK program. • The stability of the S100P–cromolyn complex was studied using molecular dynamics simulations. - Abstract: The S100P protein has been known to mediate cell proliferation by binding the receptor for advanced glycation end products (RAGE) to activate signaling pathways, such as the extracellular regulated kinase (ERK) and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) pathways. S100P/RAGE signaling is involved in a variety of diseases, such as cancer, metastasis, and diabetes. Cromolyn is an anti-allergy drug that binds S100P to block the interaction between S100P and RAGE. In the present study, we characterized the properties of the binding between cromolyn and calcium-bound S100P using various biophysical techniques. The binding affinity for S100P and cromolyn was measured to be in the millimolar range by fluorescence spectroscopy. NMR-HSQC titration experiments and HADDOCK modeling was employed to determine the spatial structure of the proposed heterotetramer model of the S100P–cromolyn complex. Additional MD simulation results revealed the important properties in the complex stability and conformational flexibility of the S100P–cromolyn complex. This proposed model has provided an understanding of the molecular level interactions of S100P–cromolyn complex.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Code Release for “Unlocking Extreme Space Weather through Advanced Modeling of Legacy Vela Spacecraft” ER

The software being developed for this project has two mains aims. First, a Bayesian Model Calibration (BMC) procedure is being developed to calibrate a spallation model that simulates protons hitting a spacecraft orbiting earth to real data. The procedure will be developed for general data (there is no data release requested as part of this code release). Second, an inverse physics modeling task is being undertaken to map the number of resulting neutrons observed from this process to the expected number of protons that hit the model. This second task is of statistical interest; to publish on it, the code will need to be open source.

Murph, Alexander↗