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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 OSTI2024

Cybersecurity for Energy Delivery Systems

The Cyber Resilient Energy Delivery Consortium (CREDC) started operations on October 1, 2015. The original period of performance ended September 30, 2020. During this span, CREDC developed projects with significant and measurable sector impact, achieved by involving industry partners (asset owners, equipment vendors, and technology providers) early and often, from helping us to identify critical sector needs, to performing pilot deployment and technology adoption. The central project goal was to create a research and development ecosystem where research results lead directly to development of applications and methodologies which are then validated in realistic contexts.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Resilient Energy Delivery and Control Systems (REDCS) (Final Technical Report)

US critical infrastructure is increasingly the target of cyberattacks, where disturbances could cause considerable damage and disruption. To help provide a new layer of cyber-physical protection for one key energy delivery system, natural gas pipelines, GE Vernova Advanced Research along with partners Florida State University and Intel Corporation created an innovative technology called "Resilient Energy Delivery and Control Systems" (REDCS). This cybersecurity package helps detect anomalies caused by cyberattacks, isolate the subsystem being impacted by the attack, and provide functions that can allow for resiliency – giving better situational awareness to the operators and cybersecurity specialists or in the future perform closed loop control for continued operation while compromised.

03 NATURAL GAS↗
DOE OSTI2025

Development of a Discrepancy Checker for the Digital Twin in a Supervisory Control System for a Thermal Energy Delivery System

Defined as a virtual representation of a physical object, process, or service, and used to support real-world decision-making, a digital twin (DT) can be utilized to combine classical and novel frameworks in sensors, state predictions, and multi-input/multi-output systems, and to enable optimal autonomous operations. However, a DT’s usefulness largely depends on its ability to adequately mirror the state of its physical counterpart, and this adequacy should be reflected by the level of uncertainty in the underlying simulation models when estimating and predicting quantities of interest (QOIs). Moreover, simulation models in a DT may involve multiple fidelities of representations—ranging from physics-based models to data-driven ones—but classical uncertainty quantification (UQ) methods struggle to handle numerous uncertainty sources, nor are they designed for real-time applications. This work presents a UQ-based discrepancy checking and diagnosis tool for a DT-based supervisory control system applied to a thermal energy delivery system (TEDS) at Idaho National Laboratory. The discrepancy checker was developed using metadata from an automated DT development process, and these metadata included different combinations of physical model forms and model parameters, training data and hyperparameters for surrogate models, and design parameters for supervisory control systems. Next, correlations between the uncertainty results and the metadata were established and then applied to the DT operations. The discrepancy checker evaluates the discrepancies between model predictions from virtual and sensor measurements and backtraces them to the corresponding major sources of uncertainty. The discrepancy checker showed reasonable performance in detecting discrepancies and diagnosing sources of uncertainty in testing scenarios.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Hybrid Power Purchase Agreements for Flexible 24/7 Energy Delivery – A Comprehensive Review of Current Practices and Research Pathways

Power Purchase Agreements (PPAs) are becoming increasingly preferred among large energy consumers, such as data centers, to secure cost-effective energy and meet accelerating demand growth. Traditionally, variable renewable energy (VRE)-based PPAs operate on a pay-as-produced basis, balancing supply and demand for a relatively longer duration (e.g., annually). However, the focus is shifting toward matching supply and demand on an hourly basis to fully meet energy needs. This shift requires the integration of flexible energy resources, such as hydropower, thermal generation, and energy storage, to complement VRE sources like wind and solar, forming the foundation for 24/7 PPA. This work contributes by: (i) reviewing emerging market trends and current practices in PPA procurement, supported by data on PPA prices and technology portfolios; (ii) synthesizing the existing literature on modeling approaches for contract pricing, quantities, hybrid resource procurement, and risk management in 24/7 PPA design, while identifying key research gaps; and (iii) proposing an integrated 24/7 PPA design framework along with two contracting mechanisms from the perspectives of both PPA providers and consumers. The proposed framework highlights critical modeling challenges, risk-allocation issues, and future research opportunities for 24/7 PPA design.

24/7↗
DOE OSTI2025

Optimizing Energy For Delivery Drones - A Comprehensive Tool Set For Drone Energy Calculation And Drone Fleet Optimization

This tool is intended to be deployed for potential customers to compare the energy profiles across various drone types/classes. The primary factors considered were design of the drone, the weight of the drone, the weight of the payload, and how the drone is flown. It has energy comparison metrics like "Drone (A) vs Drone (B) ", "Drone vs Ground Vehicle", "Drone Energy from delivery via landing versus hovering". It also includes the ability to determine the number of drones and batteries needed to optimally deliver goods from a chosen location to a set of destinations.

Mendadhala, Rohit [Idaho National Laboratory (INL)↗
DOE OSTI2024

Organizational Influence on Supply Chain for Digital Energy Infrastructure: Business Models, and Policy Landscape

Significant investment is driving the essential modernization and digitization of U.S. energy infrastructure, but the United States faces a key challenge in this grid transformation: our renewable and clean energy supply chains have limited capacity to source necessary digital assets through U.S. or allied sources. Batteries and their associated power electronic interfaces are key components to delivering clean and more resilient energy delivery, providing much-needed fast ramping, emergency discharge, generation, and operations support to the electric grid. These services have grown to be invaluable over the past 10 years and will soon be an irreplaceable component of energy delivery. While there have been significant strides to move supply chains for raw and critical materials to U.S. and allied nations, the control and power electronic industry has lagged, in part because of lower cost margins. For example, the United States now has growing capacity to manufacture solar photovoltaic (PV) panels, but 90% of the inverters—which are essential to the conversion of DC to AC for grid connection and controls—are made in or source parts from the People’s Republic of China (PRC). While a global supply chain is beneficial for many economic and supply diversification reasons, presence of foreign entities of concern (FEOC) in a dominant role in this supply chain brings additional concerns for national security of infrastructure. The BESS relationship and new clean energy have features that warrant discussions and additional focus on impact for technology security, given their critical role. This review considers the impact and solutions for complex business and policy landscapes in clean energy supply chain, and the benefit trade-offs, focusing on the Battery Energy Storage System case study, and its complex organizational relationships across both the US, Allied countries and Foreign Entities of Concern. While many examples in this paper are presented on PRC focused manufacture, this could apply to any potentially adversarial relationship

25 - ENERGY STORAGE↗
DOE OSTI2026

An Uncertainty-Informed and High-Fidelity Performance Forecasting Framework for Heliostat Fields

Concentrating Solar Thermal (CST) tower systems employ heliostat fields to direct solar energy to a central receiver, which then transfers the heat either directly to a thermal process (e.g., steam production) or to a thermal energy storage system for future use. Heliostat fields compose a significant proportion of the project costs of a CST tower system and the performance of the heliostats determines a plant's productivity at a given location. While CST characterization tools such as SolarPILOT and System Advisor Model (SAM) include a large collection of inputs that influence the performance of a CST tower system, many are uncertain prior to the development of the project and may have a significant impact on the overall energy delivery and profitability of a project; moreover, the fidelity of these models under default conditions may be insufficient to determine the value of component improvements such as those under development in the Heliostat Consortium. This work introduces a Monte Carlo simulation framework that incorporates uncertainty in key performance parameters to generate confidence intervals and percentile estimates for a CST solar field's energy delivery.

14 SOLAR ENERGY↗
NASA NTRS1984

Performance and cost of energy transport and storage systems for dish applications using reversible chemical reactions

The use of reversible chemical reactions for energy transport and storage for parabolic dish networks is considered. Performance and cost characteristics are estimated for systems using three reactions (sulfur-trioxide decomposition, steam reforming of methane, and carbon-dioxide reforming of methane). Systems are considered with and without storage, and in several energy-delivery configurations that give different profiles of energy delivered versus temperature. Cost estimates are derived assuming the use of metal components and of advanced ceramics. (The latter reduces the costs by three- to five-fold). The process that led to the selection of the three reactions is described, and the effects of varying temperatures, pressures, and heat exchanger sizes are addressed. A state-of-the-art survey was performed as part of this study. As a result of this survey, it appears that formidable technical risks exist for any attempt to implement the systems analyzed in this study, especially in the area of reactor design and performance. The behavior of all components and complete systems under thermal energy transients is very poorly understood. This study indicates that thermochemical storage systems that store reactants as liquids have efficiencies below 60%, which is in agreement with the findings of earlier investigators.

Schredder, J. M.↗
DOE OSTI2025

Explainable discrepancy checker and diagnosis for digital Twin-based supervisory control system

By virtually representing a physical object and process, a digital twin (DT) enables optimal autonomous operations by combining classical and novel frameworks in sensors, state predictions, and multi-input/multi-output systems. A DT’s values depend on how well models estimate quantities of interest and on how uncertainty is handled. Moreover, DTs often combine physics-based and data-driven models with mixed fidelities, where classical uncertainty quantification (UQ) struggles with many sources of uncertainty and real-time constraints. Here, this work presents a UQ-based discrepancy checking and diagnosis tool for a DT-based supervisory control system. The tool is developed using metadata from an automated DT development process to learn correlations between sources of uncertainties and outcomes. During operation, it compares predictions with measurements, attributes discrepancies to dominant sources, and recommends parameter and configuration updates. We verify the workflow on a synthetic temperature-control problem and deploy it on a virtual Thermal Energy Delivery System, reducing mismatch and improving control robustness.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Cyber Resilience and Social Equity: Twin Pillars of a Sustainable Energy Future

This paper examines the intersection of security and accessibility within energy systems amidst the rise of grid modernization and digitization, especially considering the regulatory changes and the imperatives of inclusive energy strategies. It addresses the dual need for secure, resilient infrastructure and a commitment to mitigate energy poverty while maintaining equitable access to energy. Amid escalating cybersecurity and physical threats, the paper advocates for sustainable energy delivery systems that ensure robust defenses without compromising the goals of reducing energy poverty and ensuring energy security. This paper identifies the pressing need for Cyber-Informed Engineering (CIE) and Secure-by-Design (SbD) principles, highlighting how these strategies can protect critical infrastructure and democratize access to secure energy, particularly for disadvantaged communities. The analysis underscores the challenges presented by the expansion of attack surfaces, interoperability requirements, and grid-edge analytics, offering innovative solutions that leverage advanced technologies and data-driven insights. Furthermore, this paper addresses the workforce development gap, emphasizing the necessity for public-private partnerships and vendor engagement in creating a skilled cybersecurity workforce. This paper has a dual focus on both the technological aspect of cybersecurity and the social dimension of equity within the context of sustainable energy development. It suggests a comprehensive examination of how these two critical elements interact and support the overarching goal of a sustainable energy future.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1998

A Method for Sizing Booster Charges in Pyrotechnic Mechanisms

Since no generally accepted guidelines exist on sizing booster charges to assure functional margins in pyrotechnically actuated devices, a study was conducted to provide an approach to meet this need. An existing pyrovalve was modified from a single cartridge input to a dual-cartridge input with a booster charge. The objectives of this effort were to demonstrate an energy-based functional margin approach for sizing booster charges, and to determine booster charge energy delivery characteristics in this valve. Functional margin was demonstrated by determining the energy required to actuate the valve through weight drop tests for comparison to the energy delivered by the cartridge and booster charge in firings in the modified valve. The results of this study indicated that this energy-based approach fully met the study objectives, showing its usefulness for this and possibly other pyrotechnic devices.

Bement, Laurence J.↗
NASA NTRS1998

A Method for Sizing Booster Charges in Pyrotechnic Mechanisms

Since no generally accepted guidelines exist on sizing booster charges to assure functional margins in pyrotechnically actuated devices, a study was conducted to provide an approach to meet this need. An existing pyrovalve was modified from a single cartridge input to a dual-cartridge input with a booster charge. The objectives of this effort were to demonstrate an energy-based functional margin approach for sizing booster charges, and to determine booster charge energy delivery characteristics in this valve. Functional margin was demonstrated by determining the energy required to actuate the valve through weight drop tests for comparison to the energy delivered by the cartridge and booster charge in firings in the modified valve. The results of this study indicated that this energy-based approach fully met the study objectives, showing its usefulness for this and possibly other pyrotechnic devices.

Bement, Laurence J.↗
DOE OSTI2024

Component-to-Optimization Workflow Demonstration

This report aims to demonstrate workflow-generating algorithms for optimizing dispatch across a broad range of Integrated Energy System applications using the Framework for Optimization of Resources and Economics (FORCE) tool suite. The optimization is performed at two different time scales. In the coarse time scale, the optimization focuses on a class of energy sources and consumers and aims to find the optimal combinations and flows of energy based on real-time price data information. In the fine time scale, the optimization focuses on a specific thermal energy delivery system and aims to find the optimal setpoints of components in order to meet the energy demands from coarse-time-scale optimizations. In this demonstration, the coarse-scale optimization is implemented using the newly developed Dispatch Optimization Variable Engine (DOVE), while the fine-scale optimization used Optimization of Real-Time Capacity Allocation (ORCA).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Component Criticality in BESS for Cybersecurity

Battery energy storage systems (BESS), inverters, and associated digital equipment are integral pieces of interdependent energy delivery systems. When considering the supply chain security of such systems, there is often a misplaced focus on the origin of energy generation and storage materials like battery cells, overlooking the more significant cyber risks that stem from digital power electronics control systems. Part of this misplaced focus is due to the relative costs of these components, with more attention given to expensive raw materials rather than the impactful digital elements themselves. The Idaho National Laboratory (INL) is addressing this gap in supply chain security through a systems-of-systems approach that considers the impact various components in digital energy systems can have should misoperation occur. Therefore, INL assigns a cyber criticality score based on quantitative analysis, which enables informed prioritization of mitigations and allows operators to reduce risk in light of the prevalence of a BESS and associated systems foreign supply chain.

25 ENERGY STORAGE↗
DOE OSTI2024

BESSIE: Battery & Energy Storage Supply Chain Analysis, Mitigation Deployment, and Tools

Battery energy storage systems (BESS) and their associated power electronic interfaces are key components to delivering clean and more resilient energy, providing much-needed fast-ramping, emergency discharge, generation, and operations support to the electric grid. These services have grown to be invaluable over the past ten years and will soon be an irreplaceable element of energy delivery. The Idaho National Laboratory (INL) strives to address these challenges through a strategic approach to supply chain risk assessment and mitigation for BESS and related digital energy equipment through the BESSIE project under the Center for Securing Digital Energy Technology. Recognizing that decreasing dependence on a foreign supply chain will take significant time and investment, BESSIE’s focus is strategically addressing battery supply chain risks by pairing short-term steps to operate securely through today’s risks with long-term steps to shape the supply chain over the coming years.

25 ENERGY STORAGE↗
DOE OSTI2025

Pointing stabilization of a 1 Hz high-power laser via machine learning

Abstract High-power lasers are vital for particle acceleration, imaging, fusion and materials processing, requiring precise control and high-energy delivery. Laser plasma accelerators (LPAs) demand laser positional stability at focus to ensure consistent electron beams in applications such as X-ray free-electron lasers and high-energy colliders. Achieving this stability is especially challenging for the low-repetition-rate lasers in current LPAs. We present a machine learning method that predicts and corrects laser pointing instabilities in real-time using a high-frequency pilot beam. By preemptively adjusting a correction mirror, this approach overcomes traditional feedback limits. Demonstrated on the BELLA petawatt laser operating at the terawatt level (30 mJ amplification), our method achieved root mean square pointing stabilization of 0.34 and 0.59 $\unicode{x3bc} \mathrm{rad}$ in the x and y directions, reducing jitter by 65% and 47%, respectively. This is the first successful application of predictive control for shot-to-shot stabilization in low-repetition-rate laser systems, paving the way for full-energy petawatt lasers and transformative advances across science, industry and security.

Amodio, Alessio↗
DOE OSTI2025

Typical Use Cases for Energy Storage in Rural Areas

Public power utilities and cooperatives play a crucial role in delivering reliable and affordable electricity to remote and sparsely populated regions. Unlike their urban counterparts, these utilities often face a unique set of challenges that can complicate their operations and service delivery. One of the primary challenges is the vast geographical area they must cover, which often results in higher transmission and distribution costs per customer. Additionally, public power utilities in rural areas often cannot afford the investments required to maintain and upgrade aging grid infrastructure to provide reliable and resilient power or withstand the impacts of recurring, severe weather events, which can cause extended outages and disrupt service delivery. Energy storage has emerged as a promising tool to help public power utilities meet these challenges. By enabling the storage of excess energy during low demand periods and providing a source of backup electricity during outages, energy storage systems can help utilities balance supply and demand more effectively. Additionally, they can help integrate a portfolio of various energy sources, reduce the need for expensive peak power purchases and provide ancillary services that stabilize the grid. This white paper describes potential use cases for energy storage in rural areas as well as documents a set of relevant example projects by project types.

24 POWER TRANSMISSION AND DISTRIBUTION↗