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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Methodology for Estimating the Energy and Moisture Budget of the Convective Boundary Layer Using Continuous Ground-Based Infrared Spectrometer Observations

Abstract Land–atmosphere interactions play a critical role in both the atmospheric water and energy cycles. Changes in soil moisture and vegetation alter the partitioning of surface water and energy fluxes, influencing diurnal evolution of the planetary boundary layer (PBL). The mixing-diagram framework has proven useful in understanding the evolution of the heat and moisture budget within the convective boundary layer (CBL). We demonstrate that observations from the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains site provide all of the needed inputs needed for the mixing-diagram framework, allowing us to quantify the impact from the surface fluxes, advection, radiative heating, encroachment, and entrainment on the evolution of the CBL. Profiles of temperature and humidity retrieved from the ground-based infrared spectrometer [Atmospheric Emitted Radiance Interferometer (AERI)] are a critical component in this analysis. Large-eddy simulation results demonstrate that mean mixed-layer values derived are shown to be critical to close the energy and moisture budgets. A novel approach demonstrated here is the use of network of AERIs and Doppler lidars to quantify the advective fluxes of heat and moisture. The framework enables the estimation of the entrainment fluxes as a residual, providing a way to observe the entrainment fluxes without using multiple lidar systems. The high temporal resolution of the AERI observations enables the morning, midday, and afternoon evolution of the CBL to be quantified. This work provides a new way to use observations in this framework to evaluate weather and climate models. Significance Statement The energy and moisture budget of the planetary boundary layer (PBL) is influenced by multiple sources, and accurately representing this evolution in numerical models is critical for weather forecasts and climate predictions. The mixing-diagram approach, driven by profiling observations as illustrated here, provides a powerful way to quantify the contributions from each of these sources. In particular, the energy and moisture mixed into the PBL from above the PBL can be determined accurately from ground-based remote sensors using this approach.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Evaluation of Rail Decarbonization Alternatives: Framework and Application

The Northwestern University Freight Rail Infrastructure & Energy Network Decarbonization (NUFRIEND) framework is a comprehensive industry-oriented tool for simulating the deployment of new energy technologies including biofuels, e-fuels, battery-electric, and hydrogen locomotives. By classifying fuel types into two categories based on deployment requirements, the associated optimal charging/fueling facility location and sizing problem are solved with a five-step framework. Life-cycle analysis (LCA) and techno-economic analysis (TEA) are used to estimate carbon reduction, capital investments, cost of carbon reduction, and operational impacts, enabling sensitivity analysis with operational and technological parameters. Here, the framework is illustrated on lower-carbon drop-in fuels as well as battery-electric technology deployments for the US Eastern and Western Class I railroad networks. Drop-in fuel deployments are modeled as admixtures with diesel in existing locomotives, while battery-electric deployments are shown for varying technology penetration levels and locomotive ranges. When mixed in a 50% ratio with diesel, results show biodiesel’s capacity to reduce emissions at 36% with a cost of $\$$ 0.13 per kilogram of CO 2 reduced, while e-fuels offer a potential reduction of 50% of emissions at a cost of $\$$ 0.22 per kilogram of CO 2 reduced. Battery-electric results for 50% deployment over all ton-miles highlight the value of future innovations in battery energy densities as scenarios assuming 800-mi range locomotives show an estimated emissions reduction of 46% with a cost of $\$$ 0.06 per kilogram of CO 2 reduced, compared with 16% emissions reduction at a cost of $\$$ 0.11 per kilogram of CO 2 reduced for 400-mi range locomotives. The NUFRIEND framework provides a systematic method for comparing different alternative energy technologies and identifying potential challenges and benefits in their future deployments.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Airport Ground Support Equipment Analysis

Ground support equipment (GSE) plays a critical role in providing services to aircraft at arrival and departure gates, ensuring smooth and efficient airport operations. As the airline industry seeks to reduce costs and expand energy options, electric GSE (eGSE) is emerging as a promising solution. This project examines the integration of eGSE into airport operations, addressing key considerations such as vehicle deployment, charging infrastructure, and grid impacts. We developed a flexible, bottom-up modeling framework to evaluate energy demands and infrastructure requirements across more than 300 U.S. airports, providing actionable insights to support electrification planning and implementation. The study focuses on eight major types of GSE with commercially available electric counterparts: aircraft tractors, ground power units, baggage tractors, belt loaders, cargo loaders, catering trucks, lavatory trucks, and water trucks. Project results include annual charging load profiles, total energy consumption, and the charger and fleet requirements for each airport.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Beam loss modeling and mitigation due to intra-beam stripping

Intra-Beam Stripping (IBS) is a critical beam loss mechanism in high-intensity H- linacs and presents a significant limitation to increasing beam power. This work presents a computational framework to evaluate and mitigate IBS-induced beam loss along the Spallation Neutron Source (SNS) LINAC. Our calculation is based on an analytic theory and involves evaluation of a 9D integral using the Monte-Carlo technique. We first benchmarked our calculations against simplified, analytically solvable cases. We then applied our algorithm to Gaussian bunches with a known probability density function (PDF). We next expanded our algorithm to arbitrary bunch distributions using the Neural Spline Flow (NSF) models trained on PyORBIT tracking data. In the future, we plan to validate our algorithm experimentally and apply it to design IBS mitigation strategies.

Nln, Shivam [ORNL]↗
DOE OSTI2020

Why does cyber deterrence fail and when might it succeed? A framework for cyber scenario analysis

Through cyberattacks on information technology and digital communications systems, antagonists have increasingly been able to alter the strategic balance in their favor without provoking serious consequences. Conflict within and through the cyber domain is inherently different from conflict in other domains that house our critical systems. These differences result in new challenges for defending and creating resilient systems, and for deterring those who would wish to disrupt or destroy them. The purpose of this paper is to further examine the question of whether or not deterrence can be an effective strategy in cyber conflict, given our broad and varied interests in cyberspace. We define deterrence broadly as the creation of conditions that dissuade antagonists from taking unwanted actions because they believe that they will incur unacceptably high costs and/or receive insufficient benefits from taking that action. Deterrence may or may not be the most credible or effective strategy for achieving our desired end states in cybersecurity. Regardless of the answer here, however, it is important to consider why deterrence strategies might succeed under certain conditions, and to understand why deterrence is not effective within the myriad contexts that it appears fail. Deterrence remains a key component of U.S. cyber strategy, but there is little detail on how to operationalize or implement this policy, how to bring a whole-of-government and whole-of- private-sector approach to cyber deterrence, which types of antagonists can or should be deterred, and in which contexts. Moreover, discussion about how nations can and should respond to significant cyber incidents largely centers around whether or not the incident constitutes a "use of force," which would justify certain types of responses according to international law. However, we believe the "use of force" threshold is inadequate to describe the myriad interests and objectives of actors in cyberspace, both attackers and defenders. In this paper, we propose an approach to further examine if deterrence is an effective strategy and under which conditions. Our approach includes systematic analysis of cyber incident scenarios using a framework to evaluate the effectiveness of various activities in influencing antagonist behavior. While we only examine a single scenario for this paper, we propose that additional work is needed to more fully understand how various alternative thresholds constrain or unleash options for actors to influence one another's behavior in the cyber domain.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2020

Power-to-Gas System Valuation. Final Report

To provide a framework for evaluating the technical and financial benefits of a power-to-gas (P2G) system deployed in the Holyoke Gas and Electric (HG&E) system, Pacific Northwest National Laboratory modified its energy storage valuation tools to run a one-year simulation of P2G operations. The simulation was used to evaluate the benefits of P2G for multiple grid and industrial applications over the economic life of the unit, or units, depending on the asset configuration.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Nu Tools: Exploring Practical Roles for Neutrinos in Nuclear Energy and Security

For decades, physicists have used neutrinos from nuclear reactors to advance basic science. These pursuits have inspired many ideas for application of neutrino detectors in nuclear energy and security. While developments in neutrino detectors are now making some of these ideas technically feasible, their value in the context of real needs and constraints has been unclear. This report seeks to help focus the picture of where neutrino technology may find practical roles in nuclear energy and security. This report is the final product of the Nu Tools study, commissioned in 2019 by the DOE National Nuclear Security Administration (NNSA) Office of Defense Nuclear Nonproliferation Research and Development (DNN R&D). The study was conducted over two years by a group of neutrino physicists and nuclear engineers. A central theme of the study and this report is that useful application of neutrinos will depend not only on advancing physics and technology but also on understanding the needs and constraints of potential end-users. The Study Approach emphasized broad end-user engagement. The major effort, undertaken from May to December 2020, was a series of engagements with the wider nuclear energy and security communities. Interviews with 41 experts revealed points of common understanding, which this report captures in three Cross-Cutting Findings, a Framework for Evaluating Utility, and seven Use Case Findings. The report concludes with two Recommendations. The findings and recommendations are summarized below. The respective ordering within each category does not represent a prioritization or implied value judgement.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Pulse Strengthened and Laser Edge Sealed Vacuum Insulation Glazing

A scalable, low-cost processing strategy for glass strengthening and sealing is proposed to improve the thermal performance of insulating glass units and develop innovative window technologies. In this project, a combination of large area photonic processing, additive manufacturing, and laser encapsulation techniques is reported to realize a vacuum glazing technology to meet the cost, performance, reliability, and throughput demands. A modeling framework for evaluating the mechanical and thermal response was established to verify the structural deformation and thermal conductance. Micro-size glass frits in printing ink and a continuous-wave laser curing were employed to allow the formation of a hermetic bonding layer and led to improvement of glass edge sealing. Various sealing parameters, including laser traveling speed, spot diameter, and laser power were optimized. The water seepage and mechanical strength of the resulting glass-to-glass bonding were examined as well. These results showcase the development of a practical vacuum insulating glazing with several unique features through a combination of photonic processing, laser encapsulation, and additive manufacturing.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Development of an MC&A toolbox for liquid-fueled molten salt reactors with online reprocessing (Final Report)

A critical barrier to the deployment of MSRs is the absence of a well-defined nuclear material control and accounting (MC&A) approach, a vital prerequisite to meet NRC licensing requirements as well as facilitating future international exports. Liquid-fueled MSR variants (especially those incorporating online refueling or reprocessing) present a unique set of challenges to traditional nuclear material control and accountancy. Unlike solid-fueled light-water reactors, traditional item-counting methods cannot be applied as an accountancy strategy. Rather, MC&A approaches to MSR variants (including both uranium and thorium fueled designs) are more analogous to bulk material handling facilities (e.g., enrichment and reprocessing); yet further complicating matters is the fact that fuel medium is also highly radioactive. Meanwhile, the space of MSRs covers a broad range of design parameters, including thermal and fast spectra designs; operation in actinide breeder or burner modes, choice of actinide fuel used (e.g., 235 U, 232 Th / 233 U, denatured 233 U, etc.), pool or loop-type configuration, and even different salt chemistry. Each of these design choices introduce significant challenges to MC&A approaches within MSR facilities. We propose to bridge this gap for liquid-fueled MSRs by developing a modular, component-based test framework for evaluating viable process monitoring and MC&A techniques specifically suited to liquid-fueled MSR system variants employing online refueling or reprocessing. This test platform will consist of a toolbox of independent process modules representing discrete physical units (such as the reactor core, off-gas processing, decay tanks, and actinide separation units), each with its own self-contained physics responsive to the input mass flow, along with appropriate measurement models that can be coupled to key flow points. These dynamic physical signatures thus afford the ability to test the viability and efficacy of potential accountancy techniques under the full range of reactor operating conditions. As process modules are connected via mass flows, the result is a reconfigurable, generic MSR mass flow model capable of serving as an MC&A test platform for a broad spectrum of possible MSR configurations. The resulting MSR MC&A toolbox will enable robust assessment of accountancy strategies for this unique facility type, including analysis of physical feedbacks arising both from depletion of the fuel over time as well as from potential off-normal events, including those introduced by equipment failures (e.g., a pump failure) as well as by malicious action (i.e., attempts to divert material). The proposed toolbox both addresses a critical needs area for the MPACT analysis toolkit while leveraging existing MPACT-sponsored tools, especially with respect to simulation of measurement and accountancy techniques for advanced fuel cycle facilities. Beyond enabling new analysis capabilities for MSR systems, the design of this toolbox will be to such to maximize compatibility with existing MPACT tools, such to enhance existing facility MC&A analysis capabilities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Application of Proliferation Resistance Optimization (PRO-X) Methodology to a Generic Research Reactor

The Proliferation Resistance Optimization Program (PRO-X) has been established by the NNSA to provide a framework for evaluating and integrating proliferation resistance into nuclear reactor system (core, fuel, and auxiliary facilities) designs that also maintain the safety and peaceful use missions of those systems. The research reactor (PRO-RR) area is the component of PRO-X that supports the program objectives by applying state-of-the-art analysis methods to research reactor systems. This report details the results of using a defined set of analytical tools to evaluate the neutronics, thermal hydraulics and proliferation risk characteristics of a set of parametric cores based on a generic 10 MW materials test reactor that uses a plate-type low enriched uranium (LEU) fuel. The analysis shows that by suitable adjustment of the core size, reflector configuration and power level, mission performance and safety margins can be maintained or improved while reducing the potential for production of special nuclear material.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Exploration of Domain Aware Machine Learning for Grid Analytics: Transfer-Learnt Energy Models to Assist Buildings Control with Sparse Field Data

Buildings are a primary consumer of energy in the United States and are also increasingly being perceived as providers of grid services such as load shifting, shedding and modulation. High fidelity models of building energy consumption are needed to set appropriate baselines for measurement and verification (M&V) of controllers designed for energy efficient operation of buildings and to enable buildings to provide grid services via. participation in demand response programs. State-of-the-art building energy modeling techniques either rely on Physics based models, or extensive instrumentation of the building envelope to gather “big” data to train machine learning based models such as deep neural networks. While Physics based models are often limited by their accuracy, it is not always feasible to gather a significant amount of field data required to train machine learning based models with sufficient accuracy. In this paper, we explore the use of transfer learning-based strategies to address unsatisfactory accuracy of models for estimating building energy consumption when available field data for training is sparse or of unacceptable quality. In particular, we transfer knowledge in the form of data and parameters, from Physics based simulation frameworks to the field to improve the model accuracy, thus resulting in a Physics-informed Machine Learning framework. We evaluated the efficacy of our approach on field data collected from six commercial buildings and our results indicate that the proposed transfer learning based models provide comparative (and in some cases better) accuracy than state-of-the-art machine learning and deep learning solutions, with just one month of field data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

A Framework for Non-Pipeline Alternatives Analysis and Review of Existing Approaches

States are increasingly interested in gas distribution system planning and the role that demand-side resources can play in maintaining an affordable, reliable, equitable, and low-carbon energy system. In particular, public utility commissions and utilities are exploring the role of non-pipeline alternatives (NPA) – an investment or activity that defers, reduces, or avoids the need to construct or replace a pipeline – in gas distribution system planning. NPAs are an emerging cost and risk mitigation tool that can provide gas utilities with an opportunity to reduce emissions, gas system costs, and customer risk by avoiding unnecessary infrastructure spending. Rather than address system issues with more costly and long-lived traditional capital projects, utilities can leverage demand-side NPA resources such as energy efficiency and electrification as well as supply-side NPA resources to meet system needs. However, there is limited guidance on performing an NPA and even fewer lessons learned. To fill this gap, the U.S. Department of Energy funded two reports on NPAs. The first report is a literature review that focuses on four states' NPA policies. The second report offers a framework for evaluating NPAs that states can adapt to meet their policy needs.

03 NATURAL GAS↗
DOE OSTI2024

Arctic Critical Infrastructure: Assessing and Predicting the Risk to Critical Permafrost Infrastructure from Climate Change: A New Thermomechanical Approach

This study presents the development of a computational framework designed to predict the interaction between permafrost and infrastructure, addressing potential failure modes and mitigation strategies in the context of climate change. The framework, rooted in advanced modeling and simulation (mod/sim) techniques, integrates thermomechanical coupling to account for the complex interplay between heat flow, ice content, and mechanical behavior in permafrost. Existing models fail to fully capture these dynamics, particularly as they relate to the effects of ice saturation on structural integrity. Our innovative Arctic Coastal Erosion (ACE) framework fills this gap by coupling thermal and mechanical models to accurately simulate subsidence and deformation in permafrost environments. We applied the ACE framework to a representative runway, demonstrating its capability to predict settlement due to rising temperatures and subsequent permafrost thaw. This proof-of-concept showcases the potential of the framework to evaluate risks to Arctic infrastructure, which supports over four million people and 70% of existing permafrost-based structures. By simulating various infrastructure types and environmental conditions, our research offers insights into failure mechanisms and evaluates structural solutions to mitigate risk. The anticipated deliverables, including a prototype runway exemplar, position this project as a critical advancement in permafrost infrastructure modeling, with applications in national security and resilience planning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Application of Cyber-Informed Engineering for Protecting BESS

This white paper synthesizes an array of crucial grid services provided by BESS technology, assesses its architecture and communications, and presents a case study for analysis against the principles introduced by Cyber-Informed Engineering (CIE). Furthermore, in walking through the analysis, this paper presents a framework to evaluate risks and solutions when considering BESS components. Asset owners and buyers could perform this analysis to assess their BESS product implementations, alternative inverter-based resources (IBR), and energy management systems (EMS). Battery systems fulfill various roles contingent on the unique market demands and the specific challenges presented by regional grid infrastructures. These roles also vary due to the differing utility models for ownership and operation, which are adapted to meet regional and local capabilities and requirements. Concerns have been raised regarding the potential for adversaries to exploit knowledge of battery operational patterns to orchestrate decisive attacks. However, the security of operational data for these systems may not be the primary vulnerability, as much of this information is already well-understood within the community. Applying a modest degree of subject matter expertise can often yield valuable predictions regarding how a battery will respond under certain conditions, such as grid emergencies, high or low-temperature days, Public Safety Power Shutoff (PSPS) events, and outages. The operational characteristics of batteries are well-documented, and their capabilities, including the risks associated with misoperation and the resulting consequences, are published and understood within the industry. CIE practices represent the next step in gaining functional assurance and providing an acceptable level of risk, regardless of whether a battery vendor can support a trusted and validated supply chain. While this issue has exacerbated supply chain challenges, it is not an isolated condition. This foreign supply route is the primary source of BESS for the U.S. market. Significant efforts are underway through the Bipartisan Infrastructure Law (BIL) to change that. Still, strategic short-term operational mitigations are needed to ensure the security of our operational technology (OT) systems, which are enhanced by instilling trust and are separate from vendors implementing CIE principles.

25 ENERGY STORAGE↗
DOE OSTI2025

Optimal Operation and Impact Assessment of Distributed Wind for Improving Efficiency and Resilience of Rural Electricity Systems

This project aims to empower rural utilities by developing advanced optimization models and algorithms for effectively integrating distributed wind energy alongside battery storage and other distributed energy resources (DERs). The primary objectives are to reduce peak demand, ensure reliable emergency power supply, and regulate voltage and frequency. To address operational challenges, the project introduces innovative mitigation strategies and ultrafast assessment frameworks to evaluate the impacts of distributed wind and DERs on rural grids, offering actionable solutions to potential issues. Economic viability is assessed through cost-benefit analysis using real rural utility data, ensuring the practical application of the project outcomes.

17 WIND ENERGY↗
DOE OSTI2025

Water Sorption Study of Various Polymers and Polymeric Composites

In the formulations of many composite materials, polymeric materials are often used as binder materials to enhance processability, functionality, and safety during manufacturing. For instance, poly(ester urethane), such as Estane® 5703, is used in the formulation of PBX 9501, and vinyl copolymer elastomer (VCE) is used in the formulation of VCE/filler compos ites. The stability of these binders directly impacts the overall stability and performance of their composites. Estane and VCE are prone to hydrolytic degradation, with water sorption behavior playing a significant role in their long-term stability and aging behavior. Hence, it is critical to study their water sorption behavior under various humidity and tempera ture conditions. To improve the accuracy and reduce labor-intensive work involved in water sorption experiments, an automated Dynamic Vapor Sorption (DVS) system was employed, which can generate large datasets. To efficiently process and analyze these datasets, Python scripts were developed. These scripts not only streamlined data processing, but also accu rately derived the Arrhenius parameters related to water diffusion and sorption properties for the tested materials. This approach offers a robust framework for evaluating water trans port and sorption processes in polymeric materials and adds valuable capabilities to future water sorption testing efforts.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Nine Canyon Long-Duration Energy Storage: A Feasibility Study

The Nine Canyon Long Duration Energy Storage (LDES) Feasibility Study explores the technical and economic viability of deploying advanced energy storage technologies at Energy Northwest's (EN) Nine Canyon (9C) Wind Project site in Benton County, Washington. Supported by the Washington State Department of Commerce and the U.S. Department of Energy’s Office of Electricity under its LDES Voucher Program, the study represents a collaborative effort between EN, Pacific Northwest National Laboratory (PNNL), and ARES North America. At the core of this effort is the development of a generalized techno-economic modeling framework and evaluation tool designed to assess the value proposition of LDES projects across a variety of contexts. The modeling tool is technology-agnostic and accommodates user-defined parameters such as rated power, energy duration, round-trip efficiency, capital and operational costs, and dispatch constraints. It also integrates economic inputs, including market prices, energy revenue structures, and financing parameters to evaluate performance through key metrics. The tool provides utilities with a transparent, adaptable platform to support decision-making, investment prioritization, and portfolio planning for various storage technologies. To guide scenario design and interpretation, the study first surveyed the LDES technology landscape, including lithium-ion batteries, flow batteries, non-hydro gravity storage, and thermo-mechanical systems, comparing cost trajectories, technical performance, safety and hazards, materials sourcing and recyclability, and spatial/siting considerations. This literature-grounded review highlights technology trade-offs and reinforces the need to align technology choice with site characteristics, use cases, and project objectives. A companion chapter examines ownership structures (EN ownership, third-party ownership, shared models) and offtake options (energy marketing, capacity/energy PPAs, time-of-use PPAs, block-delivery PPAs, and tolling), where PPAs (power purchase agreements) represent contractual arrangements for buying and selling electricity. The chapter also highlights implications for risk allocation, capital access, operational control, and revenue certainty. The study also evaluates supervisory control and data acquisition (SCADA) and transmission interconnection pathways, options include upgrading the existing SCADA or deploying a dedicated LDES controller, with attention to protection schemes, data telemetry, cybersecurity, and regulatory coordination with BPA. In addition, an ARES-specific geotechnical and hydrology assessment presented in the appendix screens multiple corridors for slope stability, bearing capacity, cut-and-fill magnitude, and stormwater behavior.

25 ENERGY STORAGE↗
DOE OSTI2025

A CHIL Validation of Machine Learning-Assisted Methods for Real-Time Controls of Solar PV for Grid Services

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been proposed; however, these technologies lack comprehensive validation under real-world application scenarios. This paper addresses this gap by designing and developing a controller-hardware-in-the-loop framework to evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. Simulation results indicate the superior performance of an ML-based approach compared to the conventional reference-control grouping-based approach, showcasing its potential to support grid stability and operational efficiency.

14 SOLAR ENERGY↗