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DOE OSTI2024

Differentiable Multiphysics Codes: A Breakthrough Technology for Simulation and Computing

This document summarizes the findings of a strategic planning exercise commissioned by the Weapons Simulation and Computing, Computational Physics (WSC/CP) program at the Lawrence Livermore National Laboratory (LLNL) in FY24. During the year, the committee met with multiple stakeholder communities to gather input, opinions, suggestions and concerns which have been incorporated throughout this document. The key findings from this exercise are summarized: • The development of multiphysics modelling and simulation (mod/sim) codes and software technologies, their deployment on exascale compute platforms, and their broad adoption across the NNSA is a major success of the Advanced Simulation and Computing (ASC) program and the Exascale Computing Project (ECP). Sustained investment in these core technologies is essential. • Today’s state of the art involves running ensembles of O(100K) simulations to perform uncertainty quantification (UQ) and design studies using multiple statistical methods such as Bayesian optimization to understand sensitivities of our models and explore parameterized design spaces. Even with exascale computing, we are practically limited to O(10) parameters in these studies since the number of simulations required to sample the space scales exponentially with the number of design parameters. • The data from these simulation ensembles is increasingly being used to train machine learned (ML) surrogates (or reduced order models, ROMs) which can then be used for optimization or real time design exploration. However, the trained surrogates are still limited in the number of parameters they can represent due to the sampling limitations previously noted. • Augmenting our suite of integrated multiphysics simulation codes, both current and emerging, with the ability to compute gradients (solution derivatives) of arbitrary simulation outputs with respect to (some or all) simulation inputs would be a breakthrough technology, opening the door to a new era of efficient and automated inverse design based on verified and validated mod/sim capabilities. • This capability, which we refer to as differentiable multiphysics codes (DMCs), would revolutionize both UQ and optimization studies by breaking the curse of dimensionality that presently limits our “gradient-free” ensemble based computing approach. A similar breakthrough occurred in the AI/ML community once the ability to compute gradients of arbitrary loss functions using back-propagation became commonplace. Gradient information from the multiphysics codes can also be used to dramatically improve the efficiency and scale of training of ML/ROM surrogates for rapid assessments. • Achieving this in our suite of codes will be a grand challenge, similar to the amount of effort that was required to transition from CPU to GPU computing. It will require buy-in from the entire WSC/CP program and beyond, including all integrated codes, physics and engineering models, third-party library dependencies and performance portability abstractions. It will also require investment in research and development of numerical methods for computing adjoints of coupled physics across multiple adaptively refined moving meshes and of stochastic (Monte Carlo) and mesh free (SPH) methods. • New software and numerical techniques, largely pioneered by the AI/ML community, make this feasible. Chief among these is automatic differentiation (AD), the ability to employ AD at point-wise locations in a physics calculation (instead of traditional black-box approaches) and the ability to perform “back-propagation in time” (or reverse mode AD) for non-linear partial differential equations (PDEs). Fundamentally, the conclusion of this strategic planning exercise is that the time is right to undertake a large scale effort in WSC, centered on the existing integrated codes, to continue the natural evolution of mod/sim in the age of AI/ML. Instead of attempting to replace mod/sim with purely data driven AI/ML models, we believe the key to success is to integrate AI/ML by building on top of the decades of hard-won knowledge and the verified/validated multiphysics modelling capability that is the hallmark of the ASC program.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

FY2019 Analysis Program Annual Progress Report

The VTO Analysis Program supports mission-critical technology, economic, and interdisciplinary analyses to assist in prioritizing VTO technology investments and to inform research portfolio planning. These efforts provide essential vehicle and market data, modeling and simulation, and integrated and applied analyses, using the unique capabilities, analytical tools, and expertise resident in the national laboratory system.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRSDate not supplied

TPSAS-NF1676L-10726-DND

The principal component radiative transfer model PCRTM (Xu 2006) simulates spectral longwave radiance at a 0.5cm-1 resolution over the wavelengths (50-2760cm-1) using 280 principal components. The CERES product SSF containing CERES field-of-view (FOV) cloud properties based on MODIS pixel information are used as inputs. NASA GMAO(Global Modeling and Assimilation Office)Geos-4 temperature and humidity profiles, as well as SMOBA (Stratosphere Monitoring Ozone Blended Analysis) ozone profiles allow computations for five years (Jan 2001- Dec 2006) of FOV nadir spectral radiance. The approximately twice daily FOV PCRTM simulations along with CERES broadband measurements are time-space averaged to 10deg zonal monthly data. Analysis of monthly seasonal and deseasonalized interannual variability in terms of brightness temperature are presented. Comparison of interannual variability in the portions of the spectrum seen by the AIRS instrument are shown. Comparisons of spectral integrated PCRTM simulations to CERES broadband longwave radiance measurements are made. In order to study the sensitivity of the spatially and temporally averaged TOA spectrum to various atmospheric properties, we perturbed atmospheric and surface temperatures, humidity, cloud height, cloud fraction, and particle size. The sensitivity of the spectrum to these properties depends on region and seasons. Month to month variability of the longwave spectra to these perturbations is 10 to 20% of the global monthly mean perturbation response. In addition, it depends on time period and size of the area used for averaging spectra. In this poster, the magnitude of sensitivity variability and how the sensitivity changes depending on temporal and spatial scale of averaging will be discussed.

Fred G. Rose↗

NASA NTRS2017

Development and Validation of an Automated Simulation Capability in Support of Integrated Demand Management

Integrated Demand Management (IDM) is a near- to mid-term NASA concept that proposes to address mismatches in air traffic system demand and capacity by using strategic flow management capabilities to pre-condition demand into the more tactical Time-Based Flow Management System (TBFM). This paper describes an automated simulation capability to support IDM concept development. The capability closely mimics existing human-in-the-loop (HITL) capabilities, while automating both the human components and collaboration between operational systems, and speeding up the real-time aircraft simulations. Such a capability allows for parametric studies to be carried out that can inform the HITL simulations, identifying breaking points and parameter values at which significant changes in system behavior occur. The paper describes the initial validation of the automated simulation capability against results from previous IDM HITL experiments, quantifying the differences. The simulator is then used to explore the performance of the IDM concept under the simple scenario of a capacity constrained airport under a wide range of wind conditions.

Traffic Flow Management↗

DOE OSTI2010

Model choice considerations and information integration using analytical hierarchy process

Using the theory of information-gap for decision-making under severe uncertainty, it has been shown that model output compared to experimental data contains irrevocable trade-offs between fidelity-to-data, robustness-to-uncertainty and confidence-in-prediction. We illustrate a strategy for information integration by gathering and aggregating all available data, knowledge, theory, experience, similar applications. Such integration of information becomes important when the physics is difficult to model, when observational data are sparse or difficult to measure, or both. To aggregate the available information, we take an inference perspective. Models are not rejected, nor wasted, but can be integrated into a final result. We show an example of information integration using Saaty's Analytic Hierarchy Process (AHP), integrating theory, simulation output and experimental data. We used expert elicitation to determine weights for two models and two experimental data sets, by forming pair-wise comparisons between model output and experimental data. In this way we transform epistemic and/or statistical strength from one field of study into another branch of physical application. The price to pay for utilizing all available knowledge is that inferences drawn for the integrated information must be accounted for and the costs can be considerable. Focusing on inferences and inference uncertainty (IU) is one way to understand complex information.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2018

C–S–H gel densification: The impact of the nanoscale on self-desiccation and sorption isotherms

The relationship between humidity and water content in a hydrating cement paste is largely controlled by the nanostructure of the C–S–H gel. Current hydration models do not describe this nanostructure, thus sorption isotherms and self-desiccation are given as constitutive inputs instead of being predicted from microstructural evolution. To address this limitation, this work combines a C–S–H gel description from nanoscale simulations with evolving capillary pore size distributions from a simple hydration model. Results show that a progressive densification of the C–S–H gel must be considered in order to explain the self-desiccation of low-alkali pastes. The impact of C–S–H densification on the evolution of microstructure and sorption isotherms is then discussed, including the effect of water-to-cement ratio, cement powder fineness, and curing temperature. Overall, this work identifies an area where nanoscale simulations can integrate larger-scale models of cement hydration and poromechanics.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Preface to the Special Issue on TOUGH Symposium 2015

The TOUGH Symposium 2015 was held in Berkeley, California, September 28-30, 2015. The TOUGH family of codes, developed at the Energy Geosciences Division of Lawrence Berkeley National Laboratory (LBNL), is a suite of computer programs for the simulation of multiphase and multicomponent fluid and heat flows in porous and fractured media with applications in many geosciences fields, such as geothermal reservoir engineering, nuclear waste disposal, geological carbon sequestration, oil and gas reservoirs, gas hydrate research, vadose zone hydrology and environmental remediation. Since the first release in the 1980s, many modifications and enhancements have been continuously made to TOUGH and its various descendants (iTOUGH2, TOUGH+, TOUGH-MP, TOUGHREACT, TOUGH+HYDRATE, TMVOC...), at LBNL and elsewhere. Today, these codes are used worldwide in academia, government organizations and private companies in problems involving coupled hydrological, thermal, biogeochemical and geomechanical processes. The Symposia, organized every 2-3 years, bring together developers and users for an open exchange on recent code enhancements and applications. In 2015, the Symposium was attended by one hundred participants, representing thirty-four nationalities. This Special Issue in Computers & Geosciences gathers extended versions of selected Symposium proceedings related to (i) recent enhancements to the TOUGH family of codes and (ii) coupled flow and geomechanics processes modeling. In this special issue, a paper by Jung et al. provides a new base version of TOUGH, TOUGH3. This latest version addresses the computational robustness and efficiency needed for the increasing complexity of the simulated processes and the growing size of model domains. Moreover, it consolidates the serial and parallel versions into a single code, hence, inconsistencies between different versions are less likely to occur, and code maintenance and development become more efficient. Finsterle et al. present a review of the capabilities of iTOUGH2 and illustrate the workflow of an integrated simulation-optimization framework. Liu et al. present an approach to reduce the computational cost of performing Bayesian inverse modeling and demonstrate their approach using a synthetic experiment simulated with TOUGH2. Regarding the mesh generation process, the paper by Doughty presents a generalization of the grid-generation algorithm embedded in TOUGH2 (MESHMAKER) to create one-column grids with fractal dimension, useful for representing flow through fractures or highly heterogeneous media with fractal geometry, and also for inverse methods. Sentís and Gable present a module to interface the open source code Lagrit with TOUGH2, that assists in the processes of mesh generation and model setup, and that can be particularly useful for complex geometries and large models. Bonduà et al. present a pre-processing tool (VORO2MESH) that features a full 3D Voronoi approach for structured and unstructured grids, and an enhanced post-processor (TOUGH2Viewer) for the visualization of 3D Voronoi grids. The literature review shows that coupled fluid flow and geomechanics has gained increasing attention in the last years in many geosciences fields. In this context, several codes of the TOUGH family have been successfully coupled with geomechanics software. The paper by Rutqvist presents a review of some of these TOUGH-based geomechanics models, of which the TOUGH-FLAC simulator – presented for the first time in the TOUGH Symposium 2003 – is well-known worldwide and has been used in a large variety of applications, encompassing the application domains of the TOUGH codes. Blanco-Martín et al. present an extension of TOUGH-FLAC to the finite strain framework, motivated by the existence of large strains associated with rock salt deformation in the context of heat-generating nuclear waste disposal. Following a paper published in the Special Issue of the TOUGH Symposium 2012 in this journal, Kim et al. present the current status of the TOUGH-RSBN simulator for coupled hydro-mechanical modeling of hydraulic fracturing using a discrete fracture network approach, and present some validation and demonstration cases. Rinaldi and Nespoli present TOUGH-SEED, an injection-induced seismicity modeling approach using TOUGH2 and a geomechanics stochastic model, and apply it to the Basel EGS project. Finally, Rinaldi et al. use the PEST protocol implemented in iTOUGH2, combined with TOUGH-FLAC as the forward model, to perform inverse modeling for the In Salah CO2 demonstration site in Algeria. Using pore pressures and InSAR displacements as observations, this approach allows for a multi-physics joint inversion and takes advantage of the inverse capabilities of iTOUGH2 (parameter estimation, sensitivity analysis, uncertainty estimation …), applied to coupled fluid flow and geomechanics. On behalf of the members of the TOUGH Symposium 2015 Organizing Committee, I hope that this collection of papers will provide the readers of Computers & Geosciences with a recent view of the capabilities of the TOUGH family of codes, as well as with current modeling research domains in the geosciences. Last but not least, I would like to express my gratitude to all the reviewers who kindly contributed to this Special Issue, as well as the Journal staff who have made this publication possible.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2010

Bringing Water into an Integrated Assessment Framework

We developed a modeling capability to understand how water is allocated within a river basin and examined present and future water allocations among agriculture, energy production, other human requirements, and ecological needs. Water is an essential natural resource needed for food and fiber production, household and industrial uses, energy production, transportation, tourism and recreation, and the functioning of natural ecosystems. Anthropogenic climate change and population growth are anticipated to impose unprecedented pressure on water resources during this century. Pacific Northwest National Laboratory (PNNL) researchers have pioneered the development of integrated assessment (IA) models for the analysis of energy and economic systems under conditions of climate change. This Laboratory Directed Research and Development (LDRD) effort led to the development of a modeling capability to evaluate current and future water allocations between human requirements and ecosystem services. The Water Prototype Model (WPM) was built in STELLA®, a computer modeling package with a powerful interface that enables users to construct dynamic models to simulate and integrate many processes (biological, hydrological, economics, sociological). A 150,404-km2 basin in the United States (U.S.) Pacific Northwest region served as the platform for the development of the WPM. About 60% of the study basin is in the state of Washington with the rest in Oregon. The Columbia River runs through the basin for 874 km, starting at the international border with Canada and ending (for the purpose of the simulation) at The Dalles dam. Water enters the basin through precipitation and from streamflows originating from the Columbia River at the international border with Canada, the Spokane River, and the Snake River. Water leaves the basin through evapotranspiration, consumptive uses (irrigation, livestock, domestic, commercial, mining, industrial, and off-stream power generation), and streamflow through The Dalles dam. Water also enters the Columbia River via runoff from land. The model runs on a monthly timescale to account for the impact of seasonal variations of climate, streamflows, and water uses. Data for the model prototype were obtained from national databases and ecosystem model results. The WPM can be run from three sources: 1) directly from STELLA, 2) with the isee Player®, or 3) the web version of WPM constructed with NetSim® software. When running any of these three versions, the user is presented a screen with a series of buttons, graphs, and a table. Two of the buttons provide the user with background and instructions on how to run the model. Currently, there are five types of scenarios that can be manipulated alone or in combination using the Sliding Input Devices: 1) interannual variability (e.g., El Niño), 2) climate change, 3) salmon policy, 4) future population, and 5) biodiesel production. Overall, the WPM captured the effects of streamflow conditions on hydropower production. Under La Niña conditions, more hydropower is available during all months of the year, with a substantially higher availability during spring and summer. Under El Niño conditions, hydropower would be reduced, with a total decline of 15% from normal weather conditions over the year. A policy of flow augmentation to facilitate the spring migration of smolts to the ocean would also reduce hydropower supply. Modeled hydropower generation was 23% greater than the 81 TWh reported in the 1995 U.S. Geological Survey (USGS) database. The modeling capability presented here contains the essential features to conduct basin-scale analyses of water allocation under current and future climates. Due to its underlying data structure iv and conceptual foundation, the WPM should be appropriate to conduct IA modeling at national and global scales.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Taking a fresh look at boiling heat transfer on the road to improved nuclear economics and efficiency

Here, in the effort to reinvigorate innovation in the way we design, build, and operate the nuclear power generating stations of today and tomorrow, nothing can be taken for granted. Not even the seemingly familiar physics of boiling water. The Consortium for the Advanced Simulation of Light Water Reactors, or CASL, is focused on the deployment of advanced modeling and simulation capabilities to enable the nuclear industry to reduce uncertainties in the prediction of multi-physics phenomena and continue to improve the performance of today’s Light Water Reactors and their fuel. An important part of the CASL mission is the development of a next generation thermal hydraulics simulation capability, integrating the history of engineering models based on experimental experience with the computing technology of the future.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2011

Steady-state simulation and optimization of an integrated gasification combined cycle power plant with CO2 capture

Integrated gasification combined cycle (IGCC) plants are a promising technology option for power generation with carbon dioxide (CO2) capture in view of their efficiency and environmental advantages over conventional coal utilization technologies. This paper presents a three-phase, top-down, optimization-based approach for designing an IGCC plant with precombustion CO2 capture in a process simulator environment. In the first design phase, important global design decisions are made on the basis of plant-wide optimization studies with the aim of increasing IGCC thermal efficiency and thereby making better use of coal resources and reducing CO2 emissions. For the design of an IGCC plant with 90% CO2 capture, the optimal combination of the extent of carbon monoxide (CO) conversion in the water-gas shift (WGS) reactors and the extent of CO2 capture in the SELEXOL process, using dimethylether of polyethylene glycol as the solvent, is determined in the first phase. In the second design phase, the impact of local design decisions is explored considering the optimum values of the decision variables from the first phase as additional constraints. Two decisions are made focusing on the SELEXOL and Claus unit. In the third design phase, the operating conditions are optimized considering the optimum values of the decision variables from the first and second phases as additional constraints. The operational flexibility of the plant must be taken into account before taking final design decisions. Two studies on the operational flexibility of the WGS reactors and one study focusing on the operational flexibility of the sour water stripper (SWS) are presented. At the end of the first iteration, after executing all the phases once, the net plant efficiency (HHV basis) increases to 34.1% compared to 32.5% in a previously published study (DOE/NETL-2007/1281; National Energy Technology Laboratory, 2007). The study shows that the three-phase, top-down design approach presented is very useful and effective in a process simulator environment for improving efficiency and flexibility of IGCC power plants with CO2 capture. In addition, the study identifies a number of key design variables that has strong impact on the efficiency of an IGCC plant with CO2 capture.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2016

Material Protection, Accounting, and Control Technologies (MPACT) Advanced Integration Roadmap

The development of sustainable advanced nuclear fuel cycles is a long-term goal of the Office of Nuclear Energy’s (DOE-NE) Fuel Cycle Technologies program. The Material Protection, Accounting, and Control Technologies (MPACT) campaign is supporting research and development (R&D) of advanced instrumentation, analysis tools, and integration methodologies to meet this goal (Miller, 2015). This advanced R&D is intended to facilitate safeguards and security by design of fuel cycle facilities. The lab-scale demonstration of a virtual facility, distributed test bed, that connects the individual tools being developed at National Laboratories and university research establishments, is a key program milestone for 2020. These tools will consist of instrumentation and devices as well as computer software for modeling, simulation and integration.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Modeling Yield, Biogenic Emissions, and Carbon Sequestration in Southeastern Cropping Systems With Winter Carinata

Sustainable aviation fuel (SAF) production from lipids is a technologically mature approach for replacing conventional fossil fuel use in the aviation sector, and there is increasing demand for such feedstocks. The oilseed Brassica carinata (known as Ethiopian mustard or simply carinata) is a promising SAF feedstock that can be grown as a supplemental cash crop over the winter fallow season of various annual crop rotations in the Southeast US, avoiding land use changes and potentially achieving some of the soil carbon sequestration and ecosystem service benefits of winter cover crops. However, carinata may require more intensive management than traditional cover crops, potentially leading to additional soil greenhouse gas (GHG) emissions through increased carbon losses from soil tillage and nitrous oxide (N 2 O) emissions from nitrogen fertilizer application. In this work, the 2017 version of the process-based DayCent ecosystem model was used to establish initial expectations for the total regional SAF production potential and associated soil GHG emissions when carinata is integrated as a winter crop into the existing crop rotations across its current suitability range in southern Alabama, southern Georgia, and northern Florida. Using data from academic and industry carinata field trials in the region, DayCent was calibrated to reproduce carinata yield, nitrogen response, harvest index, and biomass carbon-to-nitrogen ratio. The resulting model was then used to simulate the integration of carinata every third winter across all 2.1 Mha of actively cultivated cropland in the study area. The model predicted regional average yields of 2.9–3.0 Mg carinata seed per hectare depending on crop management assumptions. That results in the production of more than two million Mg of carinata seed annually across the study area, enough to supply approximately one billion liters of SAF. Conventional management of carinata led to only modest increases in soil carbon storage that were largely offset by additional N2O emissions. Climate-smart management via adopting no-till carinata establishment or using poultry litter as a nitrogen source resulted in a substantial net soil GHG sink (0.23–0.31 Mg CO 2 e ha -1 y -1 , or 0.24–0.32 Mg CO2e per Mg of seed produced) at the farms where carinata is cultivated.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

A Systems Approach to AI Model Integration and Performance Evaluation for the Generic UAM Simulation Framework

This paper introduces py-guam, an open-source experimentation framework developed for the NASA Generic Urban Air Mobility simulation (GUAM) environment, facilitating the integration and evaluation of advanced artificial intelligence (AI) algorithms. We present a systems approach which enables the seamless incorporation of data-driven models, including off-nominal and failure state detection, into the GUAM’s Cognitive Architecture (CA). The framework supports customizable experimentation parameters, derives Safety Performance Indicators (SPIs) from UL 4600 safety case analyses, and employs rapid UAM simulations to assess AI impacts on flight performance across diverse scenarios. Through comprehensive testing and validation experiments, we demonstrate GUAM’s capability to enhance safety and efficiency in urban air mobility operations. Additionally, the open-source nature of py-guam fosters community collaboration, ensuring continuous improvement and adaptability to evolving technological advancements. This work establishes a robust tool for developing and testing AI-driven urban air mobility (UAM) systems, advancing the safety and reliability of autonomous urban air vehicles.

Artificial Intelligence↗

DOE OSTI2013

U.S. Patent Pending, Information Security Analysis Using Game Theory and Simulation, U.S. Patent Application No.: 14/097,840

Vulnerability in security of an information system is quantitatively predicted. The information system may receive malicious actions against its security and may receive corrective actions for restoring the security. A game oriented agent based model is constructed in a simulator application. The game ABM model represents security activity in the information system. The game ABM model has two opposing participants including an attacker and a defender, probabilistic game rules and allowable game states. A specified number of simulations are run and a probabilistic number of the plurality of allowable game states are reached in each simulation run. The probability of reaching a specified game state is unknown prior to running each simulation. Data generated during the game states is collected to determine a probability of one or more aspects of security in the information system.

Availablity↗

DOE OSTI2019

Initial Performance Evaluation and Ranking of Thermal Energy Storage Options for Light Water Reactor Integration to Support Modeling and Simulation

This report provides an in-depth analysis of current thermal storage technologies in the marketplace as of 2019 and develops a phenomenological identification ranking table (PIRT) and Figure of Merit (FOM) study for near-term thermal energy storage technologies with light water reactor technology. Particular focus was given the NuScale reactor as part of the Joint Use Modular Plant (JUMP) program between INL, NuScale, and the Utah Associated Municipal Project (UAMPs). Ancillary service industries and technologies are explored in detail to ascertain thermodynamic requirements for integration with thermal energy storage technologies. These industries include steel manufacturing, hydrogen production, desalination, pulp and paper manufacturing. It was determined that a large percentage of these industries can make use of existing nuclear output temperatures and pressures. Storage technologies that can maintain these values are advantageous for coupling purposes. The report then analyzes ten thermal energy storage technologies, with thirteen specific systems discussed in detail regarding their potential to integrate with LWR technology. A ranking tool identified important characteristics of thermal storage and ranked each of the technologies. Concrete, molten salt, and thermal oil sensible heat storages, and steam accumulators evaluated highly. After including cost estimations and qualitatively comparing these technologies, it is recommended that either molten salt or thermal oil is used for implementation with the JUMP module. The TES project cost will likely cost between $14,000,000 and $50,000,000. The potential flexibility of a two-tank sensible heat storage system should be able to demonstrate various new uses for nuclear heat. From power peaking via steam or liquid air heat topping to process heat applications, a two-tank system should be able to best provide a constant power transfer capability to the auxiliary energy consumer. Through commencement of this work, a more refined thermal storage selection process for Nuscale and existing nuclear power plants can be conducted. The ranking system developed here can be used to re-evaluate the energy storage options periodically depending on the projected installation dates. Current results suggest two-tank thermal energy storage is the most relevant technology in the near-term.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Task 2.1: Adsorption-Based ISPR for BETO-Relevant Bioproducts

This task focuses on the development of adsorption-based in situ product recovery (ISPR) integrated with simulated moving bed chromatography for the recovery and purification of carboxylate products that are relevant to BETO. ISPR has been pursued previously in the Separations Consortium to recover carboxylic acids near or below their pKa values with liquid-liquid extraction coupled to downstream distillation. However, there are many acid products in the BETO portfolio that require neutralization well above their pKa values wherein ISPR could still be a major benefit to the bioprocess performance, including muconic acid, beta-ketoadipic acid, 3-hydroxypropionic acid, itaconic acid, butyric acid, and others. In this task, we are combining dynamic filtration with a rotating ceramic disk, resin capacity measurements, tailored resin synthesis, and simulated moving bed chromatography into an ISPR system that can be used to recover BETO-relevant carboxylates from bioreactor cultivations. We are working across process scales and using computational modeling where applicable alongside techno-economic analysis and life cycle assessment to understand major cost, energy, and GHG emissions drivers. The impact of this project will be a bench-scale integrated approach to recover carboxylate products in situ, which will reduce the waste generation from biological carboxylate production processes and improve the productivities of biological systems.

bio-based acid↗

DOE OSTI2021

An Integrated Transmission-Distribution Co-Simulation for a Distribution System with High Renewable Penetration

Traditionally, transmission and distribution system dynamic simulations are performed independently. However, dynamic co-simulation of transmission-distribution systems can be beneficial in analyzing distribution systems with high penetration of distributed renewable resources. The authors describe a framework for conducting transmission-distribution dynamic co-simulation (TDDS). A model of a real network including detailed models of solar photovoltaic units in the distribution system is constructed. The initial operating point of the network is validated against field measurements. The TDDS tool is used to simulate a single line-to-ground fault on the distribution system, highlighting the need for conducting transmission-distribution co-simulations.

14 SOLAR ENERGY↗

DOE OSTI2024

An integrated modeling framework with open architecture for phase field simulation of multi-component alloys

An integrated modeling framework (PanPhaseField) has been developed, which enables a direct and fast coupling between CALPHAD calculations and large-scale phase field simulations for multi-component alloys. Further, it adopts an open architecture allowing for integration of user-defined phase field models in a plug-and-play manner by taking full advantage of the user-friendly graphical interface of Pandat software. The developed modeling platform becomes an enabling tool that can be used to simulate the evolution of spatially varying microstructures of industrial complex alloys for various engineering applications.

36 MATERIALS SCIENCE↗