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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 OSTI2026

Autonomous elemental characterization enabled by a low cost robotic platform built upon a generalized software architecture

Despite the rapidly growing applications of robots in industry, the use of robots to automate tasks in scientific laboratories is less prolific due to the lack of generalized methodologies and the high cost of hardware. This paper focuses on the automation of characterization tasks necessary for reducing cost while maintaining generalization and proposes a software architecture for building robotic systems in scientific laboratory environments. A dual-layer (Socket.IO and ROS) action server design is the basic building block, which facilitates the implementation of a web-based front end for user-friendly operation and the use of ROS Behavior Trees for convenient task planning and execution. A robotic platform for automating mineral and material sample characterization is built upon the architecture, with an open-source, low-cost three-axis computer numerical control gantry system serving as the main robot. A handheld laser induced breakdown spectroscopy (LIBS) analyzer is integrated with a 3D printed adapter, enabling (1) automated 2D chemical mapping and (2) autonomous sample measurement (with the support of an RGB-Depth camera). We demonstrate the utility of automated chemical mapping by scanning the surface of a spodumene-bearing pegmatite core sample with a 1071-point dense hyperspectral map acquired at a rate of 1520 bits per second. Furthermore, we showcase the autonomy of the platform in terms of perception, dynamic decision-making, and execution, through a case study of LIBS measurement of multiple mineral samples. The platform enables controlled and autonomous chemical quantification in the laboratory that complements field-based measurements acquired with the same handheld device, linking resource exploration and processing steps in the supply chain for lithium-based battery materials.

Cao, Xuan [Lawrence Berkeley National Laboratory (↗
DOE OSTI2025

A cost–benefit framework to evaluate capacity upgrade options in overhead line transmission planning

This paper presents the methodology behind the new Reconductoring Economic and Financial Analysis (REFA) tool, an open-access software, used by transmission utilities to evaluate transmission capacity enhancement options. The proposed methodology is intended to be used in a new planning stage, after the capacity expansion and prior to the individual transmission project engineering, allowing capacity upgrade options (reconductoring, rebuild or voltage upgrade), and respective conductor selection, to be compared under the same economic basis. Furthermore, the REFA tool implements a methodology to rank project options and conductor types based on economic criteria, considering an approximation of the ampacity and sag constraints. Results, using 5 real transmission lines in the US, show that least-cost combinations of project and conductor types can be very diverse, which emphasizes the need for the proposed methodology and tool.

Advanced conductors↗
DOE OSTI2025

Grid Architecture Mapping to Understand Transformation (GAMUT): Concept Definition

The electric power system is undergoing significant transformation driven by changes in the generation mix, increasing reliance on information and communication technologies, evolving customer expectations, and a dynamic cyber-physical environment. To address these challenges, substantial investments will be made over the next decade to create a flexible, affordable, secure, reliable, and resilient electric system. In response, the U.S. Department of Energy's Office of Electricity is developing knowledge management tools aimed at systematically documenting technology pilots and demonstration projects. This initiative seeks to improve understanding of operating contexts, planning steps, and integration requirements for innovative grid technologies. The Department of Energy project leverages Grid Architecture principles to collect and organize insights into the interdependencies, requirements, and capabilities of various grid solutions. By employing a systematic approach, the project aims to perform a feasibility study for the development of a software tool that will support stakeholders, including regulators, transmission and distribution system operators, distributed energy resources aggregators, and technology providers. By offering a systematic, software-based framework to document technologies, understand their benefits and impacts, and inform deployment strategies, the proposed Grid Architecture Mapping to Understand Transformation (GAMUT) Tool is intended to reduce costs, enhance decision-making, and facilitate scaling and effective deployment of new technologies. The feasibility study will evaluate the technical and financial viability of the GAMUT Tool, identifying stakeholder needs and assessing risks and mitigation strategies. Ultimately, the GAMUT team aims to develop an initial minimal viable product, followed by staged improvements, to aid in the modernization of the electric grid, contributing to a more sustainable and resilient energy future.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Discerning structure sensitivity of Ni-core Pd-shell nanoparticles for enhanced nitrite reduction

Denitrification using Pd-based catalysts converts N-oxyanions into harmless products. However, the metal cost and scarcity are barriers to application. In this work, we synthesize water-suspended, structure-controlled Ni-core/Pd-shell nanoparticles (Ni@Pd NPs) that show Pd-catalyzed nitrite (NO 2 − ) reduction catalysis promoted by Ni. The NPs immobilized on Al 2 O 3 (0.47 wt % Pd and 0.74 wt % Ni) have higher NH 4 + selectivity and higher catalytic activity than wet-impregnated Pd/Al 2 O 3 (1.0 wt % Pd), i.e., 315.4 vs. 132.1 Lg surface Pd −1 min −1 . X-ray photoelectron spectroscopy (XPS) and CO-diffuse reflectance infrared Fourier transform spectroscopy (CO-DRIFTS) analyses show that Ni increases Pd electron density, which is proposed to lower the bond dissociation energy barrier for nitric oxide surface intermediate. Low-coordinated Pd atoms correlate to high activity and low NH 4 + selectivity. Using CatCost software, we estimate Ni@Pd/Al 2 O 3 to have a ∼40% lower manufacturing cost compared to wet-impregnated Pd/Al 2 O 3 . This rationally designed catalyst illustrates how nickel promotes Pd catalysis and how Pd usage can be lowered for denitrification and other hydrogenation reactions.

CO-DRIFTS↗
DOE OSTI2025

Determining Levels of Detail for Simulators of Parallel and Distributed Computing Systems via Automated Calibration

There are two sources of inaccuracy when simulating parallel and distributed computing systems: (i) a simulator implemented at an insufficient level of detail; and (ii) incorrectly calibrated simulation parameter values. Increasing the simulator’s level of detail can improve accuracy, but at the cost of higher space, time, and/or software complexity. Furthermore, evaluating the intrinsic accuracy of a simulator requires that its parameters be well-calibrated. Making decisions regarding the level of detail is thus challenging. We propose a methodology for instantiating the simulation calibration process and a framework for automating this process, which makes it possible to pick appropriate levels of detail for any simulator. We demonstrate the usefulness of our approach via two case studies for two different domains.

McDonald, Jessie [University of Hawaii at Manoa, H↗
DOE OSTI2026

Generalizable Web User Interface for Scalable and Streamlined Deployment of Building Energy Management Systems in Small and Medium-Sized Commercial Buildings

Small and medium-sized commercial buildings (SMCBs) comprise 94% of US commercial buildings yet face significant barriers to implementing building energy management systems despite advances in smart device technology. Existing solutions present critical limitations: cloud-based API solutions simplify deployment but create vendor lock-in constraints; commercial integrated software solutions ensure compatibility via standardized protocols but require substantial cost and technical expertise; open-source IoT platforms offer cost-effective vendor independence but provide insufficient standardized protocol support for commercial building automation. This research presents a generalizable web user interface framework that bridges the gap between evolving smart device capabilities and lagging software infrastructure for SMCBs. The proposed system integrates VOLTTRON open-source middleware with an automated configuration converter that transforms unified specifications written in YAML, a human-readable data-serialization format, into system-specific files, streamlining manual setup processes. The vendor-agnostic architecture supports industry-standard protocols (BACnet and Modbus) and semantic building models while providing adaptive web interfaces that dynamically adjust to various building configurations. Demonstrations through simulation-based testing and a field deployment show automatic interface adaptation across heterogeneous HVAC systems and multizone monitoring. The automated configuration converter also substantially reduces labor-intensive setup.

Chung, Jihoon [ORNL] (ORCID:0000000184880815)↗
DOE OSTI2024

Integration and Optimization of a Waste Heat Driven Organic Rankine Cycle for Power Generation in Wastewater Treatment Plants

The study focuses on achieving energy self-sufficiency in Wastewater Treatment Plants by proposing a comprehensive model for integrating, sizing, and optimizing an Organic Rankine Cycle system. The Organic Rankine Cycle system is designed to utilize waste heat from the gensets at As Samra Wastewater Treatment Plant in Jordan, where it will contribute to the overall electrical energy supply of the plant. Real data from As Samra Wastewater Treatment Plant is used to model and calculate the available waste heat using TRNSYS® software. The Organic Rankine Cycle model is then developed using ASPEN PLUS® software to explore the impact of operational parameters and determine their optimal values for maximizing the plant's energy profile. An economic analysis is conducted to assess the feasibility of the proposed model, considering system components, installation, operation, and maintenance costs. To optimize the Organic Rankine Cycle system, the study employs the Multi-Output Support Vector Regression technique to capture nonlinear relationships between independent variables (fluid type, turbine inlet pressure, turbine inlet temperature, turbine outlet pressure, and mass flow rate) and dependent variables (pump power input, waste heat input, and turbine specific work). The Osprey optimization algorithm is used to address the multi-objective optimization problem, with the proposed Pareto-based Osprey Optimization Algorithm and the Multi-Objective Particle Swarm Optimization technique being employed to evaluate critical performance and economic parameters such as system thermal efficiency, net power output, and the levelized cost of electricity. The results of the optimization strategies indicate that the M-SVR model's prediction accuracy is significantly improved after parameter optimization, with the model returning high R 2 and low Mean Square Error values of 0.991 and 0.00216, respectively. The Pareto-Based Osprey Optimization Algorithm optimizer identifies the best working fluid as Isobutane/Isopentane in a ratio of 66:34, with optimal turbine inlet pressure and temperature of 15 bars and 218 °C, respectively. In conclusion, the Organic Rankine Cycle model at these optimal conditions achieves a cycle efficiency of 19.93% and an Levelized Cost of Electricity value of 0.0353 USD/kWh.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Testbed Demonstration of a Microgrid Building Block Prototype

With the adoption of ambitious climate action goals, the penetration level of distributed energy resources (DERs) is rapidly increasing. Microgrids are an efficient way to integrate these DERs, facilitating their operation and control. Additionally, microgrids enhance the overall resilience of the distribution system by serving critical loads both within and outside their boundaries. However, the need for substantial customized engineering leads to a high cost of development, installation and maintenance of microgrids. To address this challenge, Microgrid Building Blocks (MBB) are proposed to reduce the deployment cost of microgrids through modular, standardized design and implementation. This work presents a testbed demonstrating the integrated power conversion, control, and communication functionalities of an MBB. The testbed is formed by a real-time electromagnetic transient (EMT) simulation combined with a hardware and software prototype of MBB. The use cases supported by the MBB testbed are enumerated. The islanded operation, voltage regulation, and optimal dispatch capabilities of an MBB-based microgrid controller are validated through a case study.

Somda, Baza [Virginia Tech]↗
DOE OSTI2026

Integrated System Planning: Emerging Software Requirements in the Power Industry

Power system planning software remains fragmented across organizational boundaries, with specialized tools for capacity expansion, production cost modeling, power flow, and dynamic analysis operating on incompatible data models and assumptions. This article argues that the fragmentation is not merely a technical problem but a predictable consequence of Conway's law: software architectures mirror the departmental structures within which they are developed. Regulatory milestones like Federal Energy Regulatory Commission (FERC) Order 888 formalized these divisions, but the roots trace back to the distinct engineering disciplines-mechanical, chemical, and electrical-that staffed generation and transmission planning departments in vertically integrated utilities. As the industry moves toward integrated system planning (ISP) that coordinates generation, transmission, and distribution investment decisions, the software ecosystem must evolve accordingly. We identify five categories of software requirements to enable this transition: coherent data inputs decoupled from individual applications, unified and extensible data schemas, modular component representations that support multiple abstraction levels, lifecycle management of planning datasets, and well-defined application programming interface (API) contracts that separate data exchange from algorithmic control. We examine how these requirements interact with three common workflow patterns-serial gate clearing, sequential multiapplication, and convergence oriented-and discuss the interface design principles each demands. We then outline a vision for platform-based planning architectures where specialized analytical services compose through standardized interfaces and where artificial intelligence (AI)/machine learning (ML) tools augment decision support within a disciplined software infrastructure. The practices proposed here offer a path from today's siloed tool collections toward collaborative planning ecosystems capable of handling the complexity of modern power system transformation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Multi-Rigor Agile Verification and Rapid Prototyping for Formally Verified Software

We propose a novel approach to developing formally verified systems through Multi-rigor Agile Verification. Multi-rigor Agile Verification is rooted in the hypothesis of Rigor Independence, that a system’s specification and verification architecture depend primarily on the system requirements to be verified, and they depend very little on the rigor level of the methods used to verify those requirements. Due to its iterative nature, Multi-rigor Agile Verification promises to mitigate many of the high upfront design costs experienced by formally verified systems and to deliver a better-architected, and thus better-trusted, system in the end. We then discuss the tooling needed to perform Multi-rigor Agile Verification and go in depth to build one of those tools, which directly generates executable prototype code from declarative formal specifications using the Maude rewrite-logic framework.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Stereo-vision thermal imaging system for tracking flying animals in wind farm areas (CRADA #763) Abstract

CRADA 763: abstract ThermalTracker-3D (TT3D) is a stereo vision thermal imaging system that provides 3D flight information on detected birds, bats, and other flying targets. The system was initially developed for use in the siting and monitoring of offshore wind projects to establish pre-construction and operation collision risk data but can be applied to terrestrial wind energy projects as well as national security monitoring. This technology will reduce monitoring cost, decrease processing time, and provide more accurate data for wind energy developers/operators and regulatory agencies. While the current technology is at a high level of readiness, Technology Readiness Level (TRL) 7, there remain several barriers to commercialization, particularly around ease-of-use, that result in a low Adoption Readiness Level (ARL). The proposed work will advance commercialization readiness by streamlining calibration methods for built systems. This work will:1. 1. develop a software package for factory and dynamic calibration processes 2. test that package with existing prototype TT3D systems, and 3. conduct outreach with industry end-users.

ThermalTracker↗
DOE OSTI2024

ByzSec — A Multi-layered Byzantine Resilient Architecture for Bulk Power System Protective Relays

Reliability, selectivity, and sensitivity are the fundamental attributes of any protection system, acting as the main drivers in the selection of schemes, and equipment. In high-voltage systems, microprocessor-based relays represent the industry’s preferred solution, providing engineers with a vast array of benefits. However, they remain vulnerable to cybersecurity events that may compromise their functionality. To help mitigate against potential cybersecurity risks, this paper presents a fault-tolerant, Byzantine Resilient (BR) architecture that significantly increases the cybersecurity attributes of a protection system while minimizing the amount of performance impacts and integration overheads introduced. The solution relies on an array of independent relays that utilize robust consensus methods (based on Spire [1], [2]) to ensure correct system behavior is achieved even when a relay has been compromised. Furthermore, the solution has been complemented with a custom-built Situational Awareness engine that can be used to detect and identify potential threats. The implemented solution has been developed in consultation with three hardware vendors and has been tested to comply with the performance requirements of a 345kV differential protection scheme (87T). The results indicate that the proposed architecture is a comprehensive solution that: supports the strict correctness and performance requirements of the bulk power grid while providing a cost-effective alternative that offers a seamless, long-term solution.

byzantine security, Fault Tolerant Application Sof↗
DOE OSTI2025

Impact of representative ground motion level on seismic PSA with the boundary between overestimation and underestimation

One commonly used approach in seismic probabilistic safety assessment (PSA) is the discrete method. This method follows the standard PSA framework and can be applied to various models, such as multi-unit models, while reducing computational costs using standard software. However, due to the inability to subdivide intervals infinitely, the discrete method approximates with a finite number of subintervals. In practice, different numbers of subintervals are applied, and the representative ground motion level is selected based on expert judgment. When employing a smaller number of subintervals, it is important to take caution to prevent underestimation. This study analyzes the impact of the representative ground motion level on seismic risk. It confirms that underestimation can occur with a small number of subintervals depending on the representative ground motion level. This study also proposes a method for determining the boundary of underestimation and overestimation. The method is demonstrated through examples, providing a mathematical foundation for selecting appropriate representative ground motion levels. By avoiding underestimation, this research helps prevent the oversight of significant risk contributors and enhances the understanding of seismic risk.

99 - GENERAL AND MISCELLANEOUS↗
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 OSTI2025

On the optimal sizing of power take-off systems for wave energy converters

The power take-off (PTO) system in a wave energy converter (WEC) is the means by which the energy in an ocean wave is converted into useful energy. There has been a general lack of technology convergence in the wave energy industry and PTO design has been largely device-specific with the design process determined by the WEC developer. An optimized PTO design can significantly affect the efficiency, reliability, performance, and overall cost and viability of a device. There remains a need in the marine energy industry for best practices and efficient design processes to be identified as it could greatly benefit developers and researchers in designing an optimal WEC PTO. This research utilizes the open-source Matlab-Simulink based software, WEC-Sim, which was developed by the National Renewable Energy Laboratory, and the Eagle, a high-performance computing system, to model and optimize two WECs of different archetypes and then investigates if any trends exist that can be exploited for greater efficiency in optimal PTO design. The results from this research indicate that there may be an optimal sizing for WEC PTOs for both power and PTO force rating and that substantial reductions can be made in the cost of a device without significant loss in the energy produced. Furthermore this optimal sizing may be independent of WEC type and deployment location. With an optimal, or near optimal, approach to WEC PTO sizing demonstrated, a methodology is proposed to address the challenge of nameplate ratings in the wave energy industry.

13 HYDRO ENERGY↗
DOE OSTI2026

Optimizing pressurized-water reactor equilibrium cycle using a novel loading pattern encoding and rule-based genetic crossover operators

This work presents an extended multi-batch approach applied in shuffling scheme optimization for equilibrium cycle for pressurized water reactors using Genetic Algorithms (GAs). A new ruled based GA crossover operator called Inherited Location and Batch (ILB) was introduced to enhance offsprings reproduction efficiency specialized for equilibrium cycle optimization problem. This approach was implemented within the Plant ReLoad Optimization (PRLO) framework and validated using a generic reactor model based on the AP1000 design, with core parameters calculated via the CASMO/SIMULATE software package. The ILB approach is then applied for both single and multi-objective problems in maximizing cycle length and core average exposure while minimizing the average enrichment of the 57 fresh fuel assemblies (FAs) per cycle. The optimal solutions are selected based on their dominance to the objectives from all feasible solutions. This research identified three optimal solutions satisfied safety constraints: The first solution minimizes feed enrichment costs with a cycle length of 338.8 days and core exposure of 25.39 MWd/MT; the second solution extends cycle length to 361.2 days, with the highest core exposure of 26.84 MWd/MT, using 3.75 wt% average fuel enrichment; the third solution balances both objectives with a cycle length of 349.6 days, core exposure of 25.82 MWd/MT with a slight enrichment increase compared to the first solution. Collectively, these findings underscore the efficiency and effectiveness of the proposed approach in achieving practical multi-objective optimal equilibrium cycle designs using GAs optimizer.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Optimal Operation of Residential High Performance Water Heater for Reduction of Electricity Cost and Peak Demand Through Field Validation

Water heating accounts for about 18% of a typical US home’s energy use. Modern water heaters have enabled control options through APIs, offering customers the opportunity to reduce their energy cost and peak demand by dynamically adjusting settings. A water heater’s capacity to store energy using its storage tank makes it an asset for peak demand reduction and energy cost savings. For this reason, a mixed-integer linear programming model is proposed to minimize the energy cost of a high-performance water heater while also reducing the peak demand of the residential household under a time-of-use utility rate by dynamically changing the water heater’s running mode. Specifically, a multi-objective optimization model is formulated to determine the mode settings of the water heater considering hot water use, time-of-use rate, and peak demand limit of the residential household. The mode settings are associated with different dead bands of water temperature for triggering on/off action of the heat pump and heating element. A 66-gal hybrid electric high performance water heater was used for numerical simulation and practical experiments. The simulation results were well aligned with measurements of practical experiments, validating the soundness of the thermodynamic model. In addition, reductions of energy cost, enabling affordability, and reducing peak demand are demonstrated. The research team also developed a software framework with dashboards to automatically and continuously monitor and manage devices.

Liu, Guodong [ORNL] (ORCID:0000000213498608)↗
DOE OSTI2024

Integrate Latimer Controls' Solution into RTAC (CRADA Final Report, CRD-23-24672)

Latimer Controls, Inc. was awarded two vouchers under the Department of Energy's American-Made Solar Prize Round 6 to conduct collaborative research at a national laboratory. The National Renewable Energy Laboratory (NREL) was selected as a partner to assist Latimer Controls in the performance evaluation of its photovoltaic (PV) control software. This collaboration focuses on developing a hardware-in-the-loop (HIL) testbed at NREL, which will be used to test and validate the Latimer PV control technology in a realistic yet de-risked environment. Both Latimer and NREL teams will work together to analyze the collected test data, derive insights, and disseminate the scientific findings. Recent studies underscore the potential of solar energy as a zero-marginal-cost and zero-emission flexibility resource within the bulk power system, particularly when integrated with advanced control systems. To enhance the performance of such systems, Latimer Controls has developed leading-edge technologies, including machine learning (ML) algorithms and hierarchical inverter set-point allocation methods. These innovations are designed to estimate the operational headroom of large PV plants for grid integration and control. However, comprehensive validation under real-world conditions remains necessary. To address this gap, the concurrent CRADA project proposes the real-world application and validation of the Latimer Control solution within a HIL environment. Initially, the Latimer algorithm was developed and tested within MATLAB Simulink, a platform suitable for research-level simulations and iterative development. However, transitioning this technology to a real solar site as an industry-ready solution necessitates implementation in a format compatible with widely used solar power plant controllers. In this additional CRADA work, the MATLAB Simulink-based logic will be translated into Structured Text, a programming language compliant with IEC 61131 standards, which is commonly used for custom logic implementations in industry-leading programmable logic controllers (PLCs), such as the Schweitzer SEL real-time automation controller (RTAC). This transition will facilitate the deployment of the Latimer Control solution in real-world solar power plants, thereby advancing the technology towards commercialization.

14 SOLAR ENERGY↗