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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Individual Component Map of Rotatory Strength and Rotatory Strength Density Plots As Analysis Tools of Circular Dichroism Spectra of Complex Systems

We introduce Individual Component Maps of Rotatory Strength (ICM-RS) and Rotatory Strength Density (RSD) plots as analysis tools of chiro-optical linear response spectra deriving from time-dependent density functional theory (TDDFT) simulations. ICM-RS and RSD allow one to visualize the origin of chiral response in momentum or real space, including signed contributions and therefore highlighting cancellation terms that are ubiquitous in chiral phenomena, and should be especially useful in analyzing the spectra of complex systems. As test cases, we use ICM-RS and RSD to analyze circular dicroism spectra of selected (Ag-Au)30(SR)18 monolayer-protected metal nanoclusters, showing the potential of the proposed tools to derive insight and understanding, and eventually rational design, in chiro-optical studies of complex systems.

Chang, Le↗
DOE OSTI2025

Technology readiness assessment of magnetohydrodynamic stability control

The technology readiness level scale is revised with clear definitions for magnetohydrodynamic stability control technologies for magnetic confinement fusion. The definitions are in the form of a sentence with three dimensions, which are the system complexity, the test environment, and the cost. A clear and simple definition is sought after to make an assessment based on the evidence which is agreeable to the fusion energy development community. A sample technology readiness assessment (TRA) for the electron cyclotron current drive-based control of neoclassical tearing mode for ST Advanced Reactor, using the proposed scale, reveals that the risk of a TRA being misinterpreted is high, which can only be avoided with an understanding of the procedure described in this paper.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

A framework for evaluating power electronic systems for grid integration

As power electronic systems (PESs) grow increasingly complex, integrating and testing these systems in the development stages is becoming more crucial and more challenging. New modes and resource integration strategies are in development and must be tested before pilot demonstrations and mass production. This paper proposes a framework for testing of PES technologies including early validation with integration of simulated resources. The framework is demonstrated to work in two example configurations as proof of principle.

Dean, Ben↗
DOE OSTI2025

Testing convolutional neural network based deep learning systems: a statistical metamorphic approach

Machine learning technology spans many areas and today plays a significant role in addressing a wide range of problems in critical domains,i.e., healthcare, autonomous driving, finance, manufacturing, cybersecurity,etc. Metamorphic testing (MT) is considered a simple but very powerful approach in testing such computationally complex systems for which either an oracle is not available or is available but difficult to apply. Conventional metamorphic testing techniques have certain limitations in verifying deep learning-based models (i.e., convolutional neural networks (CNNs)) that have a stochastic nature (because of randomly initializing the network weights) in their training. In this article, we attempt to address this problem by using a statistical metamorphic testing (SMT) technique that does not require software testers to worry about fixing the random seeds (to get deterministic results) to verify the metamorphic relations (MRs). We propose seven MRs combined with different statistical methods to statistically verify whether the program under test adheres to the relation(s) specified in the MR(s). We further use mutation testing techniques to show the usefulness of the proposed approach in the healthcare space and test two CNN-based deep learning models (used for pneumonia detection among patients). The empirical results show that our proposed approach uncovers 85.71% of the implementation faults in the classifiers under test (CUT). Furthermore, we also propose an MRs minimization algorithm for the CUT, thus saving computational costs and organizational testing resources.

Computer Science↗
DOE OSTI2019

Transmission Expansion Planning Test System for AC/DC Hybrid Grid With High Variable Renewable Energy Penetration

Test systems are important tools and benchmark for power system research. Currently, there is a lack of standard test systems for modern transmission expansion planning (TEP) research, especially under high variable renewable energy (VRE) penetrations. This article describes a 38-bus test system named the HRP-38 system dedicated to TEP. “HRP” stands for high renewable penetration. The objective of establishing such a system is to provide a consistent platform for different TEP methods to be tested and compared. The test system considers high VRE penetration of more than 30% energy share, which will be an important feature in many power systems in the future. Both AC and DC candidate lines are given to provide sufficient transmission planning alternatives. The complexity of the test system is well balanced considering calculation tractability and the ability to test the performance of the TEP planning model. The network topology, generation mix and load characteristics are described in detail. Year-round time series of VRE (wind power and PV) output and load curves for each bus are provided to facilitate a detailed evaluation of the transmission grid configuration under high VRE penetration. Finally, four benchmark results with different optimization settings are provided for the HRP-38 system.

AC/DC hybrid↗
DOE OSTI2023

Dataset for SIAM MPI23 Project "Model inversion for complex physical systems using low-dimensional surrogates"

Training and testing data for the SIAM MPI23 workshop "Model inversion for complex physical systems using low-dimensional surrogates". The data consists of ensembles of input and output pairs corresponding to queries of a 2D saturated groundwater flow model. The inputs consist of random vectors which map to discretized model parameter fields via a Kosambi-Karhunen-Loève expansion. Output corresponds to discretized pressure fields.

basis adaptation, conditional Karhunen-Loève expan↗
DOE OSTI2022

The Ground Truth Program: Simulations as Test Beds for Social Science Research Methods.

Social systems are uniquely complex and difficult to study, but understanding them is vital to solving the world’s problems. The Ground Truth program developed a new way of testing the research methods that attempt to understand and leverage the Human Domain and its associated complexities. The program developed simulations of social systems as virtual world test beds. Not only were these simulations able to produce data on future states of the system under various circumstances and scenarios, but their causal ground truth was also explicitly known. Research teams studied these virtual worlds, facilitating deep validation of causal inference, prediction, and prescription methods. The Ground Truth program model provides a way to test and validate research methods to an extent previously impossible, and to study the intricacies and interactions of different components of research.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Computational Bayesian Framework for Quantification and Reduction of Predictive Uncertainty in Subsurface Environmental Modeling

Subsurface environmental systems are open and complex, in which intricate hydrologic, microbiologic, and geochemical processes occur and interact at multiple scales. Understanding and predicting system responses to natural forces (e.g., climate changes) and human activities (e.g., contaminant remediation and CO 2 sequestration) is indispensable for managing water resources, cleaning subsurface contamination at many sites of the Department of Energy (DOE), and providing expert analysis to inform policy-making on long-term stewardship of nuclear waste disposal and CO 2 storage sites. Groundwater reactive transport modeling is necessary for understanding and predicting the complex subsurface environmental system. However, as complex systems are never completely predictable, model predictions of the subsurface system are inherently uncertain, and uncertainty is one of the greatest obstacles in simulating the subsurface environment. Quantifying predictive uncertainty of the complex system is critical to test model predictive power, support decision-making, and guide experimental design and data collection for uncertainty reduction. This project tackled two major obstacles to efficient and effective quantification and reduction of predictive uncertainty in simulating the complex subsurface environment. One obstacle is that existing methods of uncertainty quantification are too fragmented and incomplete for understanding and predicting the complex subsurface environment as a whole. The other obstacle is that existing methods of uncertainty quantification are computationally demanding and may not be applicable to groundwater reactive transport modeling that is always computationally expensive. The above two obstacles to uncertainty quantification directly affect the design of data collection schemes for uncertainty reduction. In this project, we developed a comprehensive Bayesian framework to remove the first obstacle. The second obstacle was tackled by using the sparse grid methods, which were originally developed and analyzed for numerical integration in the field of applied mathematics. We integrated the sparse grid methods into the Bayesian framework seamlessly, which led to a sparse-grid-based method of Bayesian uncertainty analysis. The developed computational Bayesian framework has been applied to a number of subsurface environmental problems through collaborating with scientists at the Pacific Northwest National Laboratory and Oak Ridge National Laboratory. The applications demonstrated that the computational Bayesian framework is general and compatible with any models and numerical codes of subsurface modeling. It is thus can be applied to gain insights for subsurface environmental modeling. This project helped the PI achieve his career goal to advance the state-of-the-art computational methods in uncertainty quantification for subsurface environmental modeling. This project supported two doctoral students, two master students, and one post-doc. The two doctoral students, after their graduation, worked as post-docs at the Pacific Northwest National Laboratory and the Oak Ridge National Laboratory. The project produced a total of 29 journal articles (four under review), one book chapter, and a number of conference proceedings and abstracts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Testing of an Iodine and Tritium Capture System for an NO₂-Based Tritium Pretreatment Process

The reprocessing of used nuclear fuel would release volatile radionuclides into the off-gas streams of a processing plant, including ³H, ¹⁴C, ⁸⁵Kr, and ¹²⁹I. One potential simplification to the management of the off-gas streams could be achieved through an efficient tritium pretreatment (TPT) step in which the UO₂ fuel is oxidized by either air or NO₂ before dissolution. The oxidation of the UO₂ fuel matrix will result in the release of tritium from the fuel. Upfront release of tritium from the fuel in a pretreatment step with subsequent tritium abatement can minimize or eliminate the distribution of tritium throughout a plant. This can decrease or eliminate the need for tritium capture on multiple off-gas streams and prevent distribution to the aqueous inventory. The use of NO₂ as the oxidant in an advanced tritium pretreatment (ATPT) allows for the oxidation to be performed at lower temperatures and may also result in the quantitative release of iodine from the fuel. The ATPT off-gas will contain up to 75 vol% NO₂ gas. Spencer et al. identified the most promising iodine sorbent as silver nitrate-impregnated alumina (AgA) and the most promising tritium sorbents as 3Å molecular sieve (3Å MS) and silica gel for radionuclide capture from ATPT off-gas streams. An initial series of tests were conducted in fiscal years 2017–2018 with the intent of demonstrating the recovery of iodine and tritium using these sorbents from a recirculating gas stream that simulated the NO₂ recycle loop envisioned for the ATPT system. These initial tests showed low tritium recoveries and significant variations in the iodine recovery on the AgA. Ultimately it was concluded, following disassembly of the system, that corrosion within the system was partially the cause of the poor recovery of both species. All components of that system were disposed of at the end of the analysis. One of the conclusions drawn from the initial tests pointed to the reconsideration of the materials of construction. Based on that recommendation a new test bed for the advanced TPT off-gas system, that addresses the issues identified in the fiscal years 2017 and 2018 scoping tests, was designed and constructed. The test bed used high nickel alloys wherever possible to address the previously observed corrosion issues, a redesigned surge tank to permit ease of purging, an improved feed injection system and a more modular system design that allowed testing of incremental increases in system complexity to allow the isolation of any element that results in changes to recovery of target species. Accompanying that design, a multifaceted test plan was completed. The overarching goals of this test series were two-fold. The first goal was to demonstrate the ability to recover both the iodine and tritium that would be released during TPT in a manner that the releases from the fuel can be quantified. The second goal was to demonstrate that the combined recovery system could operate in any of the three proposed TPT modes (once-through air or O₂, recirculating air or O₂, or recirculating NO x ). A total of 22 tests were completed. Ten tests examined tritium behavior under varying operating parameters, 8 tests examined iodine behavior under varying operating parameters, and 4 tests examined both tritium and iodine behavior. Silica gel was used for the tritium sorbent, and AgA or Ag-mordenite (AgZ) was used as the iodine sorbent. The following conclusions were drawn: Full recovery is achieved for both sorbates when no sorbent is in place indicating no accumulation within the test system. In even the simplest of the configurations (i.e., no sorbents in the columns), iodine is more difficult to transport and recover from the system than tritium. Analysis of the AgA iodine sorbent beds from the integrated tritium and iodine tests indicate quantitative iodine recovery can be achieved (within anticipated experimental errors). This system may provide a means for the quantification of the iodine released by the ATPT process within the experimental uncertainties. This would support 0.33 to 1.00 kg demonstrations of the ATPT process with actual used nuclear fuel. Iodine penetrated further into AgZ than into AgA when operated in gas recirculation mode. Tritium adsorbs to and cannot be fully recovered from the 10-cm column of silica gel at regeneration temperatures up to 140 °C.; Tritium adsorbs to and cannot be recovered from the 10-cm column of AgA at desorption temperatures up to 200 °C. Co-adsorbed tritium was recovered to a greater extent from AgZ than from AgA, but recovery was not complete. No visible corrosion was observed in the test system.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Self-optimized construction of transition rate matrices from accelerated atomistic simulations with Bayesian uncertainty quantification

Here, a massively parallel method to build large transition rate matrices from temperature-accelerated molecular dynamics trajectories is presented. Bayesian Markov model analysis is used to estimate the expected residence time in the known state space, providing crucial uncertainty quantification for higher-scale simulation schemes such as kinetic Monte Carlo or cluster dynamics. The estimators are additionally used to optimize where exploration is performed and the degree of temperature acceleration on the fly, giving an autonomous, optimal procedure to explore the state space of complex systems. The method is tested against exactly solvable models and used to explore the dynamics of C15 interstitial defects in iron. Our uncertainty quantification scheme allows for accurate modeling of the evolution of these defects over timescales of several seconds.

36 MATERIALS SCIENCE↗
DOE OSTI2025

System Engineers and Decisions: It?s All about Knowledge

In order to guarantee that a system meets adequate levels of reliability and availability, system performances are continuously monitored and analyzed thanks to the technological advancements driving the Industry 4.0 revolution. An Industry 4.0 approach is typically based on advanced statistical, big data mining, machine learning, and internet-of-things methods designed to detect anomalies in the behavior of system, detect the most likely failure modes, and provide indications to system engineers on when maintenance activities should be performed before system performance are deemed unacceptable (which can be generated by diagnostic and prognostic methods). However, these analyses, which are designed to automatize and increase the efficacy of the system maintenance program, require large amount of data which can come in various forms: numeric, textual, images, sounds etc. Such data constitutes the historic knowledge benchmark to track system performances and support system engineer decisions. Here we claim that data is not sufficient to support this kind of analyses when applied to systems characterized by complex architectures and behaviors. Robust system engineer decisions require the ability to understand the system operational context that lies behind the observed data elements. In this respect, system models are in fact necessary to “put data in context” and capture relationships between data elements. Industry 4.0 methods require in fact contextual knowledge as a basis upon which hypotheses can be generated and assumptions tested. In our view, for complex systems, model-based system engineering (MBSE) models can afford this contextual knowledge, as they are typically used to describe systems architecture and dynamic behaviors. System knowledge is here intended as the blending of collected data and system architecture which takes the form of a “knowledge graph”. A knowledge graph is a database which consists of a large set of nodes (in our case an entity can be either a data or an MBSE element) which are linked to each other. The types of nodes and links follow a pre-defined topology, sometimes also refers as an ontology, that is designed to fit the actual decisions that needs to be performed. We show here how a knowledge graph can be defined to support system engineer maintenance decisions and how the same graph can be built based on system MBSE models and pre-processed data from numeric (through anomaly detections and diagnostic methods) and textual elements (through technical language processing TLP).

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Multiphysics Modeling of Microreactors with NEAMS codes, and Validation Based on KRUSTY Reactivity Insertion

The NEAMS Multiphysics Applications team continues to assess code usability and functionality for microreactor design and safety analyses, while demonstrating that NEAMS tools capture both steady-state and transient behavior across distinct microreactor concepts. In FY2025, the team advanced full-core, high-fidelity, multiphysics models that solve more complex problems and strengthen verification/validation for several microreactor systems: heat-pipe microreactor (HPMR), gas-cooled microreactor (GCMR), and the KRUSTY experiment. These models employ the MOOSE MultiApp/Transfers architecture with Griffin for neutronics, BISON for heat conduction/thermomechanics, Sockeye for heat pipes, SAM/THM for coolant channels and loops, and SWIFT for hydride behavior, with meshes generated via the MOOSE Reactor Module. The graphite models available in the Grizzly code were also investigated for future analyses. For the HPMR, a Na-HPMR variant was constructed to align with recently validated heat-pipe experiments and Sockeye’s LCVF capability, enabling mechanistic heat-pipe transients and startup modeling. The Na-HPMR will serve as the primary model for HPMR investigations in upcoming tasks. The load-following and single heat-pipe failure scenarios (Griffin/BISON/Sockeye), which were previously modeled for the K-HPMR, were replicated for the Na-HPMR, showing strong negative temperature feedback and highly localized thermal effects, respectively, while the startup case captured vapor-front progression and heat-removal activation. Solid mechanics was added to the previously built K-HPMR full-core model in BISON, showing minimal impact on steady-state reactivity yet enabling stress-field predictions that prepare the path for full-core TRISO performance analyses. For the GCMR, automated steady-state and four transient scenarios were executed using Griffin/BISON/SAM/SWIFT. Results confirm robust inherent safety: power collapses promptly in loss-of-cooling events, the inlet-temperature drop settles to a new equilibrium, and a single-channel blockage yields only a ~30 K local fuel-temperature rise with <0.4% power decrease. SWIFT-predicted hydrogen redistribution affects reactivity during both steady-state and transient conditions, underscoring its importance. A Brayton-cycle balance of plant (BOP) model in SAM/THM demonstrated stable startup behavior, and xenon-driven reactivity during load following was analyzed. To improve TRISO-compact temperature fidelity, a fast multiscale Heat Source Decomposition (HSD) treatment was implemented. Against heterogeneous benchmarks, HSD reduces underprediction of kernel temperatures and lowers predicted peak powers in reactivity-insertion transients compared to previous homogenized models. KRUSTY warm-critical validation progressed from FY2024 baselines: the 15Ȼ insertion shows excellent agreement in peak power (~2% high) and temperature trends, and the 30Ȼ case was automated via a feedback controller that maintained power near 3 kW for ~150 s with close agreement to data. The successful modeling of the warm critical tests has laid a strong foundation for simulating more complex nuclear system tests in the years ahead. Throughout FY2025, developer feedback was provided (e.g., MOOSE batch mesh generation, distributed pre-split meshes, Griffin sweeper on displaced meshes), several new models were contributed to the Virtual Test Bed, and an OECD-NEA WPRS multiphysics benchmark based on the HPMR was initiated to enable broader cross-comparison and best-practice development with the nuclear community at large.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Deuteron off-resonance rotating frame relaxation for the characterization of slow motions in rotating and static solid-state proteins

Here, we demonstrate the feasibility of deuterium solid-state NMR off-resonance rotating frame relaxation measurements for studies of slow motions in biomolecular solids. The pulse sequence, which includes adiabatic pulses for magnetization alignment, is illustrated for static and magic-angle spinning conditions away from rotary resonances. We apply the measurements for three systems with selective deuterium labels at methyl groups: a) a model compound, Fluorenylmethyloxycarbonyl methionine-D 3 amino acid, for which the principles of the measurements and corresponding motional modeling based on rotameric interconversions are demonstrated; b) amyloid-β 1-40 fibrils labeled at a single alanine methyl group located in the disordered N-terminal domain. This system has been extensively studied in prior work and here serves as a test of the method for complex biological systems. The essential features of the dynamics consist of large-scale rearrangements of the disordered N-terminal domain and the conformational exchange between the free and bound forms of the domain, the latter one due to transient interactions with the structured core of the fibrils. and c) a 15-residue helical peptide which belongs to the predicted α-helical domain near the N-terminus of apolipoprotein B. The peptide is solvated with triolein and incorporates a selectively labeled leucine methyl groups. The method permits model refinement, indicating rotameric interconversions with a distribution of rate constants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Mapping Local Dissipation and Entropy Production in Complex and Active Fluids

While global entropy production provides a measure of irreversibility, its partitioning into contributions from local regions is key to understanding the mechanisms underlying time-reversal symmetry breaking in complex systems and active matter. Here, by analyzing local heat flows and fluxes, we propose a framework that enables the mapping of local dissipation and entropy production in a nonequilibrium system. We test this approach in simulations of fluids driven through complex environments and active systems. We connect the results across the local and global scales by showing that local dissipation and entropy production satisfy a local version of the usual (global) fluctuation theorem, which accounts for the correlations between the local region and its surroundings. Interestingly, in the case of the active fluid, our analysis reveals that these correlations are of opposite signs for the active (stochastic) and passive (deterministic) contributions to local dissipation.

Entropy↗
DOE OSTI2021

A Communication Testbed for Testing Power Electronic Agent Systems

Power electronic systems (PES) incorporate complex intra-system communication, which are of vital importance for the successful operation of these systems. This paper proposes and outlines a communication testbed that will help in the development and testing of the communications between the components of PES. It allows for the comparison and evaluation of different communication methods, such as MQTT, Modbus, or User Datagram Protocol (UDP), and for the characterization of how these communication protocols perform.

Dean, Ben↗
DOE OSTI2019

Emergent magnetic ordering and topological frustration in quasicrystal artificial spin ices

Artificial spin ices (ASIs) are nanoscale geometrically engineered arrays of magnetic bars or islands that display magnetic frustration and provide a fertile system for modeling and testing many complex statistical mechanics theories and emergent phenomena. Aperiodic ASIs display spatially varying magnetic frustration as a result of the aperiodicity. We have explored the magnetization reversal of quasicrystalline ASIs (QC-ASIs) patterned on P2 and P3 Penrose tilings, using a statistical graph-theory approach that enables quantitative comparison between the two tilings. Our approach offers insight into the QC-ASIs. We show that the P2 tiling leads to enhanced topological frustration compared to the P3 tiling, and we elucidate the emergence of local antiferromagnetic ordering as well as disordered states in these ferromagnetic aperiodic lattices. Furthermore our method enables quantitative exploration of frustration behavior on any periodic or aperiodic lattice, thereby opening pathways to study collective behavior in various topologically frustrated systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Experimental test of model predictive control in a variable air volume system

Model predictive control (MPC) has been widely studied as a promising approach for improving energy efficiency and operational flexibility in buildings, yet its real-world performance for commercial variable air volume (VAV) systems remains insufficiently characterized. In particular, the impacts of model mismatch on control robustness, real-time computational burden, and device-level operation are rarely evaluated using long-term field data. Here, this study presents a comprehensive experimental evaluation of MPC applied to a full-scale VAV system in Oak Ridge National Laboratory’s Flexible Research Platform-2 building with constant cooling/heating temperature setpoints and no occupancy. The study offers three key advantages over existing work: (1) it uses a representative building in a full-scale experimental test, capturing realistic system dynamics and complexity; (2) it evaluates a relatively sophisticated MPC formulation using two different optimization solvers (Gurobi and PSO), fully accounting for computational complexity and methodological diversity; and (3) it systematically assesses potential negative impacts on various building devices, benchmark against a well-established baseline, ASHRAE Guideline 36 (G36). To isolate zone- and air-handling-unit–level supervisory control effects, the supply fan was operated with a fixed static pressure setpoint under all strategies, and the trim-and-response static pressure reset in G36 was not enabled. Results show that MPC maintained thermal comfort while improving energy efficiency. Abrupt solar radiation variations degraded performance. Computation times ranged from ∼1 s (Gurobi) to ∼ 70 s (PSO). Compared with G36, MPC achieves 33% energy savings and reduces median reheat coil output by approximately a factor of 5–10 for a representative cooling day under matched weather conditions. However, it increases the maximum discomfort deviation from 0.5 to 1°C and results in a 32% increase in staging frequency. In addition, PSO-based MPC introduced damper oscillations, also affecting actuator longevity.

ASHRAE guideline 36↗
DOE OSTI2025

Flow Enhanced Electrochemical Sensor Performance in Complex Salt Systems

To advance MSR MC&A practices, Argonne National Laboratory developed and optimized robust flow enhanced electrochemical sensors (FEES) and multielectrode array voltammetry sensors (MAVS) which provide accurate near-real time measurements of actinides in molten salts. Flow-enhanced electrochemical sensors are installed directly into MSR flow conduits for inline salt chemistry measurement, while MAVS are deployed in quiescent salt conditions enabling online species concentration determination in stationary salt vessels. This report summarizes efforts to improve electrochemical sensor technological readiness through (1) sensor testing in complex, high concentration molten salt systems to demonstrate low uncertainty actinide measurements in MSR-representative solutions and (2) demonstrations of sensor performance in challenging real-world conditions in collaboration with partner MSR institutions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗