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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

ExaSAT: An exascale co-design tool for performance modeling

One of the emerging challenges to designing HPC systems is understanding and projecting the requirements of exascale applications. In order to determine the performance consequences of different hardware designs, analytic models are essential because they can provide fast feedback to the co-design centers and chip designers without costly simulations. However, current attempts to analytically model program performance typically rely on the user manually specifying a performance model. Here we introduce the ExaSAT framework that automates the extraction of parameterized performance models directly from source code using compiler analysis. The parameterized analytic model enables quantitative evaluation of a broad range of hardware design trade-offs and software optimizations on a variety of different performance metrics, with a primary focus on data movement as a metric. Finally, we demonstrate the ExaSAT framework’s ability to perform deep code analysis of a proxy application from the Department of Energy Combustion Co-design Center to illustrate its value to the exascale co-design process. ExaSAT analysis provides insights into the hardware and software trade-offs and lays the groundwork for exploring a more targeted set of design points using cycle-accurate architectural simulators.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Active Learning Meets Foundation Models: Fast Remote Sensing Data Annotation for Object Detection

Object detection in remote sensing demands extensive, high-quality annotations—a process that is both labor-intensive and time-consuming. In this work, we introduce a real-time active learning and semi-automated labeling framework that leverages foundation models to streamline dataset annotation for object detection in remote sensing imagery. For example, by integrating a Segment Anything Model (SAM), our approach generates mask-based bounding boxes that serve as the basis for dual sampling: (a) uncertainty estimation to pinpoint challenging samples, and (b) diversity assessment to ensure broad data coverage. Furthermore, our Dynamic Box Switching Module (DBS) addresses the well-known cold start problem for object detection models by replacing its suboptimal initial predictions with SAM-derived masks, thereby enhancing early-stage localization accuracy. Extensive evaluations on multiple remote sensing datasets plus a real-world user study, demonstrate that our framework not only reduces annotation effort, but also significantly boosts detection performance compared to traditional active learning sampling methods. The code for training and the user interface will be made available.

Burges, Marvin [ORNL] (ORCID:0000000312690769)↗
DOE OSTI2011

Intent, Capability and Opportunity: A Holistic Approach to Addressing Proliferation as a Risk Management Issue

Currently, proliferation risk assessment models are designed to evaluate only a portion of the overall risk, focusing exclusively on either technological or social factors to determine the extent of a threat. Many of these models are intended to act as a means of predicting proliferation potential rather than assessing the system as a whole, ignoring the ability to enhance mitigating factors and manage, rather just establish the presence of, the threat. While the information garnered through these forms of analysis is necessary, it remains incomplete. By incorporating political, social, economic and technical capabilities as well as human factors such as intent into a single, multi-faceted risk management model, proliferation risk can be evaluated more effectively. Framing this information around how to improve and expand the Regime already in place and establishing where there are gaps in the system allows for a more complete approach to risk management, mitigation and resource allocation. The research conducted here seeks to combine all three elements (intent, capability and opportunity) in a comprehensive evaluation which incorporates an assessment of state-level variables, possible proliferation pathways and technical capability. Each portion of the analysis is carried out independently then combined to illustrate the full scope of a State's nuclear infrastructure while showing areas of weakness in the institutional framework.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

Microgrid Conceptual Design Guidebook | 2022

This guide is meant to assist communities – from residents to energy experts to decision makers – in developing a conceptual microgrid design that meets site-specific energy resilience goals. Using the framework described in this guidebook, stakeholders can come together and start to quantify site-specific vulnerabilities, identify the most significant risks to delivery of electricity, and establish electric outage tolerances across the community. In addition to establishing minimum service needs, this framework encourages communities to consider broader sustainability goals and policy constraints and begin to estimate up-front costs associated with the installation of alternative microgrid solutions. The framework guides a community through data collection and a high-level assessment of its needs, constraints, and priorities, prior to engaging engineers, vendors, and contractors. The first sections of this guidebook provide a high-level primer on electric systems. The latter sections include guidance for step-by-step data gathering and analysis of site conditions. The ultimate product resulting from the stepwise approach is a conceptual microgrid design. A conceptual design is defined as an initial design (10%-20% complete) that considers the specific threats, needs, limitations, and investment options for a given location. Going through this exercise and developing the conceptual microgrid design as a community ensures the same community members who will ultimately live with the solution are the developers of its foundational design. Often, these are also the very same people who understand system tolerances and needs the best and are therefore the ideal candidates for establishing these criteria. Especially when it comes to evaluating critical infrastructure, it is the community that best understands the most critical services. The framework is intended to facilitate a systematic approach to planning for resilience and provide a deeper understanding of how to use a framework to make decisions around microgrid solutions. Like many processes where tradeoffs need to be considered, this is often an iterative process. If this guide serves to help educate and empower communities who are beginning the process of deploying a microgrid, it has met the goal of its authors.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Optimal Mitigation Planning For Adversarial Scenarios

We propose a generalized framework which performs an optimal partitioning of a limited budget into various organizational sectors in order to improve the cybersecurity of a smart device or component in the Cyber Physical Energy System (CPS). The framework identifies the adversarial threats and possible attack sequences which can be performed to exploit cyber vulnerabilities of the component. Thereafter, we formulate an Mixed Integer Linear Programming (MILP) optimization problem which aims to evaluate the optimal budget partitions in order to minimize the number of highly likely attack sequences. Though we provide results for using the framework in CPES, the proposed methodology can be extended for multiple domains with a set of known adversarial and mitigation actions.

Purohit, Sumit [Pacific Northwest National Laborat↗
DOE OSTI2022

Data-centric framework for crystal structure identification in atomistic simulations using machine learning

Atomic-level modeling performed at large scales enables the investigation of mesoscale materials properties with atom-by-atom resolution. The spatial complexity of such cross-scale simulations renders them unsuitable for simple human visual inspection. Instead, specialized structure characterization techniques are required to aid interpretation. These have historically been challenging to construct, requiring significant intuition and effort. Here we propose an alternative framework for a fundamental structural characterization task: classifying atoms according to the crystal structure to which they belong. Our approach is data-centric and favors the employment of Machine Learning over heuristic rules of classification. A group of data-science tools and simple local descriptors of atomic structure are employed together with an efficient synthetic training set. We also introduce the first standard and publicly available benchmark data set for evaluation of algorithms for crystal-structure classification. Further, it is demonstrated that our data-centric framework outperforms all of the most popular heuristic methods—especially at high temperatures when lattices are the most distorted—while introducing a systematic route for generalization to new crystal structures. Moreover, through the use of outlier detection algorithms our approach is capable of discerning between amorphous atomic motifs (i.e., noncrystalline phases) and unknown crystal structures, making it uniquely suited for exploratory materials synthesis simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A Methodology for Evaluating Operator Usage of Machine Learning Recommendations for Power Grid Contingency Analysis

This work presents the application of a methodology to measure domain expert trust and workload, elicit feedback, and understand the technological usability and impact when a machine learning assistant is introduced into contingency analysis for real-time power grid simulation. The goal of this framework is to rapidly collect and analyze a broad variety of human factors data in order to accelerate the development and evaluation loop for deploying machine learning applications. We describe our methodology and analysis, and we discuss insights gained from a pilot participant about the current usability state of an early technology readiness level (TRL) artificial neural network (ANN) recommender.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2013

GEOS Code Development Road Map

GEOS is a massively parallel computational framework designed to enable HPC-based simulations of subsurface reservoir stimulation activities with the goal of optimizing current operations and evaluating innovative stimulation methods. GEOS will enable coupling of different solvers associated with the various physical processes occurring during reservoir stimulation in unique and sophisticated ways, adapted to various geologic settings, materials and stimulation methods. The overall architecture of the framework includes consistent data structures and will allow incorporation of additional physical and materials models as demanded by future applications. Along with predicting the initiation, propagation and reactivation of fractures, GEOS will also generate a seismic source term that can be linked with seismic wave propagation codes to generate synthetic microseismicity at surface and downhole arrays. Similarly, the output from GEOS can be linked with existing fluid/thermal transport codes. GEOS can also be linked with existing, non-intrusive uncertainty quantification schemes to constrain uncertainty in its predictions and sensitivity to the various parameters describing the reservoir and stimulation operations. We anticipate that an implicit-explicit 3D version of GEOS, including a preliminary seismic source model, will be available for parametric testing and validation against experimental and field data by Oct. 1, 2013.

02 PETROLEUM↗
DOE OSTI2016

Interface Control Document for the EMPACT Module that Estimates Electric Power Transmission System Response to EMP-Caused Damage

The EPREP code is designed to evaluate the effects of an Electro-Magnetic Pulse (EMP) on the electric power transmission system. The EPREP code embodies an umbrella framework that allows a user to set up analysis conditions and to examine analysis results. The code links to three major physics/engineering modules. The first module describes the EM wave in space and time. The second module evaluates the damage caused by the wave on specific electric power (EP) transmission system components. The third module evaluates the consequence of the damaged network on its (reduced) ability to provide electric power to meet demand. This third module is the focus of the present paper. The EMPACT code serves as the third module. The EMPACT name denotes EMP effects on Alternating Current Transmission systems. The EMPACT algorithms compute electric power transmission network flow solutions under severely damaged network conditions. Initial solutions are often characterized by unacceptible network conditions including line overloads and bad voltages. The EMPACT code contains algorithms to adjust optimally network parameters to eliminate network problems while minimizing outages. System adjustments include automatically adjusting control equipment (generator V control, variable transformers, and variable shunts), as well as non-automatic control of generator power settings and minimal load shedding. The goal is to evaluate the minimal loss of customer load under equilibrium (steady-state) conditions during peak demand.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Ligand Control of Oxidation and Crystallographic Disorder in the Isolation of Hexavalent Uranium Mono-Oxo Complexes

Here, the development of high-valent transuranic chemistry requires robust methodologies to access and fully characterize reactive species. We have recently demonstrated that the reducing nature of imidophosphorane ligands supports the two-electron oxidation of U 4+ to U 6+ and established the use of this ligand to evaluate the inverse-trans-influence (ITI) in actinide metal-ligand multiple bond (MLMB) complexes. To extend this methodology and analysis to transuranic complexes, new small-scale synthetic strategies and lower-symmetry ligand derivatives are necessary to improve crys-tallinity and reduce crystallographic disorder. To this end, the synthesis of two new imidophosphorane ligands, [N=P t Bu(pip) 2 ]¯ (NPC 1 ) and [N=P t Bu(pyrr) 2 ]¯ (NPC 2 ) (pip = piperidinyl; pyrr = pyrrolidinyl) is presented, which break pseudo-C 3 axes in the tetravalent complexes, U[NPC 1 ] 4 and U[NPC 2 ] 4 . The reaction of these complexes with two-electron oxygen atom transfer reagents (N 2 O, trimethylamine N-oxide (TMAO) and 2,3:5,6-dibenzo-7-azabicyclo[2.2.1]hepta-2,5-diene (dbabhNO)) yields the U 6+ mono-oxo complexes U(O)[NPC 1 ] 4 and U(O)[NPC 2 ] 4 . This methodology is optimized for direct translation to transuranic elements. Of the two ligands, the NPC 2 framework is most suitable for facilitating detailed bonding analysis and assessment of the ITI. Theoretical evaluation of the U–(NPC) bonding confirms a substantial difference between axially and equatorially-bonded N atoms, revealing mark-edly more covalent U–N ax interactions. The U 6d+5f combined contribution for U–N ax is nearly double that of U–N eq , accounting for ITI shortening and increased bond order of the axial bond. Two distinct N-atom hybridizations in the pyrrolidine/piperidine rings are noted across the complexes, with approximate sp 2 and sp 3 configurations describing the slightly shorter P–N “planar” and slightly longer P–N “pyramidal” bonds, respectively. In all complexes, the NPC 2 ligands feature more planar N atoms than NPC 1 , in accordance with a higher electron-donating capacity of the former.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Combined impact of lead, cadmium, polychlorinated biphenyls and non-chemical risk factors on blood pressure in NHANES

High blood pressure is associated with exposure to multiple chemical and non-chemical risk factors, but epidemiological analyses to date have not assessed the combined effects of both chemical and non-chemical stressors on human populations in the context of cumulative risk assessment. We developed a novel modeling approach to evaluate the combined impact of lead, cadmium, polychlorinated biphenyls (PCBs), and multiple non-chemical risk factors on four blood pressure measures using data for adults aged ≥20 years from the National Health and Nutrition Examination Survey (1999–2008). We developed predictive models for chemical and other stressors. Structural equation models were applied to account for complex associations among predictors of stressors as well as blood pressure. Models showed that blood lead, serum PCBs, and established non-chemical stressors were significantly associated with blood pressure. Lead was the chemical stressor most predictive of diastolic blood pressure and mean arterial pressure, while PCBs had a greater influence on systolic blood pressure and pulse pressure, and blood cadmium was not a significant predictor of blood pressure. The simultaneously fit exposure models explained 34%, 43% and 52% of the variance for lead, cadmium and PCBs, respectively. The structural equation models were developed using predictors available from public data streams (e.g., U.S. Census), which would allow the models to be applied to any U.S. population exposed to these multiple stressors in order to identify high risk subpopulations, direct intervention strategies, and inform public policy. - Highlights: • We evaluated joint impact of chemical and non-chemical stressors on blood pressure. • We built predictive models for lead, cadmium and polychlorinated biphenyls (PCBs). • Our approach allows joint evaluation of predictors from population-specific data. • Lead, PCBs and established non-chemical stressors were related to blood pressure. • Framework allows cumulative risk assessment in specific geographic settings.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Predicting on-site environmental impacts of municipal engineering works

The research findings fill a gap in the body of knowledge by presenting an effective way to evaluate the significance of on-site environmental impacts of municipal engineering works prior to the construction stage. First, 42 on-site environmental impacts of municipal engineering works were identified by means of a process-oriented approach. Then, 46 indicators and their corresponding significance limits were determined on the basis of a statistical analysis of 25 new-build and remodelling municipal engineering projects. In order to ensure the objectivity of the assessment process, direct and indirect indicators were always based on quantitative data from the municipal engineering project documents. Finally, two case studies were analysed and found to illustrate the practical use of the proposed model. The model highlights the significant environmental impacts of a particular municipal engineering project prior to the construction stage. Consequently, preventive actions can be planned and implemented during on-site activities. The results of the model also allow a comparison of proposed municipal engineering projects and alternatives with respect to the overall on-site environmental impact and the absolute importance of a particular environmental aspect. These findings are useful within the framework of the environmental impact assessment process, as they help to improve the identification and evaluation of on-site environmental aspects of municipal engineering works. The findings may also be of use to construction companies that are willing to implement an environmental management system or simply wish to improve on-site environmental performance in municipal engineering projects. -- Highlights: • We present a model to predict the environmental impacts of municipal engineering works. • It highlights significant on-site environmental impacts prior to the construction stage. • Findings are useful within the environmental impact assessment process. • They also help contractors to implement environmental management systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The Molecular Path Approaching the Active Site in Catalytic Metal–Organic Frameworks

How molecules approach, bind at, and release from catalytic sites is key to heterogeneous catalysis, including for emerging metal-organic framework (MOF)-based catalysts. Here, we use in situ synchrotron X-ray scattering analysis to evaluate the dominant binding sites for reagent and product molecules in the vicinity of catalytic Ni-oxo clusters in NU-1000 with different surface functionalization under conditions approaching those used in catalysis. The locations of the reagent and product molecules within the pores can be linked to the activity for ethylene hydrogenation. For the most active catalyst, ethylene reagent molecules bind close to the catalytic clusters, but only at temperatures approaching experimentally observed onset of catalysis. The ethane product molecules favor a different binding location suggesting that the product is readily released from the active site. An unusual guest-dependence of the framework negative thermal expansion is documented. We hypothesize that reagent and product binding sites reflect the pathway through the MOF to the active site and can be used to identify key factors that impact the catalytic activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Systematic Bayesian evaluation of resonance parameters in 19 Ne for the 15 O ⁡(𝛼, 𝛾)⁢ 19 Ne and 18 F ⁡(𝑝, 𝛼)⁢ 15 O reactions

Here, we present a comprehensive evaluation of the nuclear structure properties of 19 Ne using a novel and rigorous Bayesian statistical framework. Precise characterization of 19 Ne resonance parameters is critical for accurately determining reaction rates of the astrophysically significant 15 O ⁡(𝛼, 𝛾)⁢ 19 Ne and 18 F ⁡(𝑝, 𝛼)⁢ 15 O reactions, which govern breakout from the hot CNO cycle in x-ray bursts and influence 𝛾-ray emission in novae, respectively. By reconstructing likelihood functions from published experimental data—including asymmetric uncertainties and upper or lower limits—we derive posterior distributions for resonance energies, decay widths, and branching ratios. Our Bayesian approach systematically incorporates previously reported discrepancies among measurements, providing a statistically robust and consistent treatment of these uncertainties. The evaluated resonance parameters and associated uncertainties provide crucial input for stellar nucleosynthesis modeling, contributing to a refined understanding of explosive astrophysical phenomena.

Kim, Sohyun H. [Sungkyunkwan Univ., Suwon (Republi↗
DOE OSTI2022

Regulatory Treatment of Non-Core Sources of Radioactivity for Advanced Reactor Designs

The recent resurgence in advance (non-light water) reactor development has been paralleled by the development of risk-informed performance-based (RIPB) licensing pathways. Specifically, the creation of the RIPB Licensing Modernization Project (LMP) approach and subsequent endorsement by the U.S. Nuclear Regulatory Commission (NRC) now provides advanced reactor vendors with a defined RIPB method to develop an affirmative safety case for licensing. In addition, the Technology Inclusive Content of Applications Project (TICAP) has published guidance on developing a license application based on the LMP approach. To support the utilization of risk information as part of advanced reactor design and licensing efforts, the American Society of Mechanical Engineers (ASME)/American Nuclear Society (ANS) Joint Committee on Nuclear Risk Management (JCNRM) has developed a probabilistic risk assessment (PRA) standard for advanced reactors. The standard, which was formerly approved by the American National Standards Institute (ANSI) in 2021 and recently endorsed by the NRC in trial use Regulatory Guide (RG) 1.247, is an integral standard, covering from initiating events to offsite consequence. A major feature of the standard is that it permits the inclusion of any source of radioactivity material at the site within the plant PRA. Therefore, non-core sources of radioactivity, such as fuel storage, fuel processing, and purification systems, can be included within a single comprehensive plant PRA. For those advanced reactor vendors utilizing a RIPB licensing approach, there is an opportunity to include the non-core sources of radioactivity within the RIPB framework for licensing decision-making, such as the categorization of events, classification of structures, systems, and components (SSCs), and evaluation of the adequacy of defense-in-depth (DID). For advanced reactor designs that contain multiple non-core sources of radioactivity, or for monolithic plant sites that include associated fuel facilities, this approach could potentially simplify licensing applications through the use of a single, uniform, and consistent decision-making framework across all radioactive sources at the site. In addition, a RIPB approach could provide additional insights regarding plant behavior, flexibility regarding licensing decision-making, and potentially allow the use of risk information as part of the plant oversight process. Risk-informing these aspects of advanced reactor licensing would also be consistent with the NRC’s risk policy statement. However, there is diverse regulation and guidance regarding the licensing of non-core sources of radioactivity and generally limited experience using RIPB approaches for the evaluation as part of licensing.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2011

Efficient uncertainty quantification methodologies for high-dimensional climate land models

In this report, we proposed, examined and implemented approaches for performing efficient uncertainty quantification (UQ) in climate land models. Specifically, we applied Bayesian compressive sensing framework to a polynomial chaos spectral expansions, enhanced it with an iterative algorithm of basis reduction, and investigated the results on test models as well as on the community land model (CLM). Furthermore, we discussed construction of efficient quadrature rules for forward propagation of uncertainties from high-dimensional, constrained input space to output quantities of interest. The work lays grounds for efficient forward UQ for high-dimensional, strongly non-linear and computationally costly climate models. Moreover, to investigate parameter inference approaches, we have applied two variants of the Markov chain Monte Carlo (MCMC) method to a soil moisture dynamics submodel of the CLM. The evaluation of these algorithms gave us a good foundation for further building out the Bayesian calibration framework towards the goal of robust component-wise calibration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

An integrated boundary approach for colloidal suspensions simulated using smoothed dissipative particle dynamics

We report that in particle-based continuum solvers such as smoothed particle hydrodynamics (SPH) and smoothed dissipative particle dynamics (SDPD), one of the most significant challenges is the treatment of solid boundaries like walls and colloidal particles, whose presence leads to a truncation of the integral approximation, and hence, error in the numerical solution. In this work, we describe an integrated boundary framework for modeling colloidal suspensions composed of rigid spherical particles. The integral corresponding to the colloid's contribution is analytically evaluated, giving a simple and computationally inexpensive approach relative to conventional boundary particle techniques. We formulate a thermodynamically-consistent version of this top-down method for mesoscale simulations, in which the fluid exchanges momentum with the suspended particles due to thermal fluctuations, giving a framework for modeling the dynamics of colloids at arbitrary Reynolds and Péclet numbers. The resulting evolution equations are validated for a single colloidal particle in a fluid at constant temperature. This simple approach requires ~ N c (p/m) R$2\atop{c}$ fewer pair force calculations relative to traditional boundary particle strategies, where N c is the number of colloids in the system, R c is the colloid radius, ρ is the colloid mass density, and m is the mass of the SDPD particles. Additionally, the use of integrated boundaries removes the need for rigid body constraint dynamics, giving an elegant and efficient basis for large-scale simulations of colloidal suspensions that is general and does not make any physical assumptions about the flow.

42 ENGINEERING↗
DOE OSTI2024

Unraveling the Threads of Environmental Justice in Critical Mineral Extraction: A Framework for Regionalized Life Cycle Data

As we transition to a more sustainable energy system, the extraction and processing of critical minerals becomes increasingly important. However, these industries often raise concerns about environmental and social impacts, particularly in disadvantaged communities. To address these concerns, our research focuses on regionalizing environmental life cycle data to connect it with communities affected by mineral extraction. A framework was developed for collecting life cycle background data that supports the Justice40 Toolset, a market-based approach to evaluating net benefits and costs of critical mineral material recovery pathways. A goal was to alleviate public skepticism around mineral extraction processes, including secondary and unconventional feedstocks, by highlighting both environmental and social impacts. To achieve this, computational analysis and geospatial data science techniques were employed, such as within-scale and across-scale methods and proxy dataset usage. By doing so, we were able to develop a framework for identifying and disaggregating data down to regions small enough to support Justice40 goals. Our approach not only provides valuable tools fo insight into the environmental implications of mineral extraction but also helps policymakers evaluate the social impacts on local communities. This research contributes to a more just and equitable transition to a sustainable energy system, ensuring that marginalized voices are heard in decision-making process.

Davis, Tyler [NETL Site Support Contractor, Nation↗