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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

Metallization of diamond

Experimental discovery of ultralarge elastic deformation in nanoscale diamond and machine learning of its electronic and phonon structures have created opportunities to address new scientific questions. Can diamond, with an ultrawide bandgap of 5.6 eV, be completely metallized, solely under mechanical strain without phonon instability, so that its electronic bandgap fully vanishes? Through first-principles calculations, finite-element simulations validated by experiments, and neural network learning, we show here that metallization/demetallization as well as indirect-to-direct bandgap transitions can be achieved reversibly in diamond below threshold strain levels for phonon instability. We identify the pathway to metallization within six-dimensional strain space for different sample geometries. We also explore phonon-instability conditions that promote phase transition to graphite. These findings offer opportunities for tailoring properties of diamond via strain engineering for electronic, photonic, and quantum applications.

36 MATERIALS SCIENCE↗

Integration of Multiple Real-time Simulation Platforms with AIO for Scalability

This paper introduces a practical and scalable approach to extend interoperability of Controller Hardware in the Loop (CHIL) validations for large scale microgrids, networked microgrids, and power electronics-based feeders. The work focuses on integrating multiple real-time simulators using Analog Input/Output (AIO) interface techniques in heterogeneous CHIL environment. It explores interfacing methods, highlighting key challenges related to dynamic accuracy and maintaining bidirectional power balance. A comparative evaluation of the Ideal Transformer Method is presented, assessing its effectiveness in multi-CHIL integration scenarios. The feasibility of this setup is demonstrated through a real-time use case involving multiple Typhoon HIL and Opal-RT platforms, showcasing its applicability for distributed system studies.

Khalid, Mohammad [ORNL] (ORCID:0000000179208805)↗

Multimodal Prediction of Tearing Instabilities in a Tokamak

Tokamak is a torus-shaped nuclear fusion device that uses magnetic fields to confine fusion fuel in the form of plasma. Tearing instability in plasma is a major issue in which the magnetic field breaks and recombines in tokamak. Here, this instability can lead to plasma disruption that terminates the fusion power generation and damages the plasma-facing wall materials. For a successful steady operation of a large-scale tokamak without disruption, it is required to predict and alarm the tearing instabilities well in advance to avoid them. In this work, we develop and validate a deep neural network-based multimodal prediction system that estimates the future tearing instability likelihood from multi-diagnostics signals in the DIII-D tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Learning Optimal Power Flow Solutions using Linearized Models in Power Distribution Systems

Solving nonlinear optimal power flow (OPF) problem is computationally expensive, and poses scalability challenges for power distribution networks. An alternative to solving the original nonlinear OPF is the linear approximated OPF models. Although, these linear approximated OPF models are fast, the resulting solutions may result in significant optimality gap. Lately, the application of machine learning (ML) methods in successfully solving the nonlinear OPF has been reported. These methods learn and estimate the nonlinear control policies using a purely data-driven approach. In this paper, we propose an approach to complements the ML based approach to solving OPF using solutions from known linearized OPF model. Specifically, we use supervised learning to map the solutions of linear OPF to nonlinear control variables. Unlike, the traditional ML based methods for OPF that approximate the full distribution feeder model using function approximation, our approach uses a two-node approximation of radial networks. The proposed approach is validated using IEEE 123 bus test system for OPF solutions obtained using the nonlinear OPF models.

optimal power flow, power distribution systems, su↗

Development of HELICS-Based High-Performance Cyber-Physical Co-Simulation Framework for Distributed Energy Resources Applications

The rapid growth of distributed energy resources (DERs) has prompted increasing interest in the monitoring and control of DERs through hybrid smart grid communications resulting in the typical smart grid cyber-physical system. To fully understand the interdependency between them, we propose to integrate the Network Simulator 3 (NS3) into the High Engine for Large-Scale Infrastructure Co-Simulation (HELICS), a new open-source, cyber-physical-energy co-simulation platform. This paper aims to the development and case study of the HELICS-based high performance distribution-communication co-simulation framework for the DER coordination. The novel co-simulation framework for the NS3 integrating into the HELICS is developed. The DER monitoring application about hybrid smart grid communication network design is simulated and validated on this proposed HELICS-based cyber-physical co-simulation platform.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Switching Device-Cognizant Sequential Distribution System Restoration

This paper presents an optimization framework for sequential reconfiguration using an assortment of switching devices and repair process in distribution system restoration. Compared to existing studies, this paper considers types, capabilities and operational limits of different switching devices, making it applicable in practice. We develop a novel multi-phase method to find the optimal sequential operation of various switching devices and repair faulted areas. We consider circuit breakers, reclosers, sectionalizers, load breaker switches, and fuses. The switching operation problem is decomposed into two mixed-integer linear programming (MILP) subproblems. The first subproblem determines the optimal network topology and estimates the number of steps to reach that topology, while the second subproblem generates a sequence of switching operations to coordinate the switches. For repairing the faults, we design an MILP model that dispatches repair crews to clear faults and replace melted fuses. After clearing a fault, we update the topology of the network by generating a new sequence of switching operations, and the process continues until all faults are cleared. To improve the computational efficiency, a network reduction algorithm is developed to group line sections, such that only switchable sections are present in the reduced network. The proposed method is validated on the IEEE 123-bus and 8500-bus systems.

distribution system↗

Isochronous Architecture-Based Voltage-Active Power Droop for Multi-Inverter Systems

This article proposes an isochronous architecture for parallel inverters with only voltage-active power droop (VP-D) control for improving active power sharing as well as plug-and-play of multi-inverter-based distributed energy resources (DERs). The isochronous framework obviates the need for an explicit regulation of the frequency while allowing for sharing of reactive power. The article shows that the detrimental effects of circulating currents between inverters can be addressed in the framework developed. The isochronous architecture is implemented by employing a GPS to disseminate clock timing signals that enable the microgrid to maintain the nominal system frequency. Small signal eigenvalue analysis of a Multi-inverter Microgrid system near the steady-state operating point is presented to evaluate the system stability. Moreover, unlike traditional droop-based methods, the isochronous strategy lends itself to analytical guarantees which are developed in the article. Furthermore, the effect of delays in receiving GPS clock signals by an inverter is experimentally characterized and an inverter isolation mechanism is proposed that disconnects inverters facing large GPS communication delays. Hardware experiments on an 1.2 kVA-prototype and controller-hardware-in-the-loop validation on the CIGRE distribution network are conducted to demonstrate the effectiveness of the proposed architecture towards active and reactive power sharing between inverters with load scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗

REDLY

SAND2025-11838O REDLY provides a framework for designing, training, and validating physics-informed neural networks for power system applications. It trains surrogates for Alternating Current Power Flow prediction and general economic dispatch problems, such as Alternating Current Optimal Power Flow and Direct Current Power Flow. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Blakely, Logan↗

Quantum nonlocal modulation cancelation with distributed clocks

We demonstrate nonlocal modulation of entangled photons with truly distributed radio frequency (RF) clocks. Leveraging a custom radio-over-fiber (RFoF) system characterized via classical spectral interference, we validate its effectiveness for quantum networking by multiplexing the RFoF clock with one photon from a frequency-bin-entangled pair and distributing the coexisting quantum-classical signals over fiber. Phase modulation of the two photons reveals nonlocal correlations in excellent agreement with theory: in-phase modulation produces additional sidebands in the joint spectral intensity, while out-of-phase modulation is nonlocally canceled. Our simple, feedback-free design attains subpicosecond synchronization—namely, drift less than ~0.5 ps in a 5.5 km fiber over 30 min (fractionally only ~2×10 -8 of the total fiber delay)—and should facilitate frequency-encoded quantum networking protocols such as high-dimensional quantum key distribution and entanglement swapping, unlocking frequency-bin qubits for practical quantum communications in deployed metropolitan-scale networks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Development of Approaches to Model Excited State Charge and Energy Transfer in Solution

The development of next generation energy conversion and catalytic systems requires fundamental understanding of the interplay between photo-excitation and the resulting proton and electron transfer processes that occur in solution. To address these challenges requires accurate and efficient methods to compute ground and excited states, as well as the ability to treat the dynamics of energy transfer in the presence of solvent fluctuations. Our team is developing accurate and efficient theoretical models for solution phase reactions. These developments provide an improved understanding of photo-initiated excitations, electron transfer, and proton coupled electron transfer processes. Our research team brings together expertise in electron and nuclear dynamics (classical and quantum), electronic structure, and analysis of solvation networks. We are developing and validating techniques for modeling condensed phase charge and energy transfer and to simulate the methods to monitor them using optical and vibrational spectroscopy.

74 ATOMIC AND MOLECULAR PHYSICS↗

Deep Green: Structural and Functional Genomic Characterization of Conserved Unannotated Green Lineage Proteins

Our overall objective is to improve and increase functional and structural predictions for a growing number of plant proteins of unknown structure and function (the Deep Green proteins), and to make our predictive data useful and accessible to the larger research community. The project is divided into five major objectives which include 1) Assembly and curation of Deep Green candidate protein sets; 2) in silico structural and functional predictions and network analyses; 3) assembly and validation of reverse genetic resources in Chlamydomonas reinhardtii (Chlamydomonas); 4) high throughput functional genomics characterization and prioritization in Chlamydomonas; and 5) structural validation of selected candidates and functional validation in two important reference plant species, Arabidopsis thaliana (Arabidopsis) and Setaria viridis (Setaria).

59 BASIC BIOLOGICAL SCIENCES↗

Modifications to Solar Titan-130 Combustion Systems for Efficient, High Turndown Operation

The project team of Southwest Research Institute® (SwRI®), Solar Turbines Incorporated (Solar), the Electric Power Research Institute (EPRI), the University of California, Irvine (UCI), and the Georgia Institute of Technology (Georgia Tech) investigated methods to allow higher efficiency part-load operation of a Solar Titan 130 gas turbine. The objective was to develop a low-emission combustion system capable of sustaining combustion and avoiding lean blowout during high turndown operation, which would allow the gas turbine to operate as efficiently as possible at part load. Currently, electric utility markets are beginning to experience substantial increases in renewable energy generation. Some of these renewable energy sources have highly variable output in an uncontrolled manner. In order to maintain grid stability, there is a need for power plants to ramp up power to the grid rapidly to make up for drops in renewable generation. This is often termed spinning reserve, but the size of this reserve may need to increase as renewable penetration into the electric utility market increases. Small combined heat and power (CHP) power plants provide a promising option for meeting this spinning reserve requirement. In order to operate in spinning reserve while still meeting the heat requirements for the CHP, the gas turbine needs to operate efficiently at very low loads. Efficient, high turndown operations in this engine are limited by the lean flammability limit of the premixed combustion system. This project sought enhance the lean operability range of the Titan 130 combustor. First, the project team participated in a brainstorming activity and ultimately selected two concepts to explore: fuel augmentation with hydrogen (H2) to improve the stability at lean operating conditions and modifications to the fuel nozzle to improve the emissions performance at lean operating conditions. Analytical and laboratory investigations were accomplished by UCI to investigate the efficacy of H2 addition at improving lean blow out (LBO) limits and the resulting emissions. These investigations used a variety of chemical reactor network (CRN) and CFD models, validated against laboratory data, to model the impact of H 2 and inform the experimental efforts accomplished by SwRI and Solar. Ultimately, both the CRN and CFD models yielded generally good agreement with the experimental data below a particular temperature threshold. Atmospheric tests of a full-scale T130 annular combustor were performed at SwRI facilities in San Antonio, Texas, to investigate the use of H 2 addition. For these tests, the T130 combustion system remained largely unchanged; minor modifications were performed to the fuel ducting to allow for the safe use of H 2 . The test ultimately demonstrated that the addition of H 2 to the fuel mixture significantly increased the AFR ratio at which the combustor could operate. This improvement to the LBO limit should allow for less use of compressor bleed and less throttling needed by the inlet guide vanes (IGV). This in turn could result in more efficient operation of the gas turbine at lower load points. The second modification explored in this work was a direct modification to the T130 injector. The project team hypothesized that modifications to the pilot of the T130 injector could provide lower emissions at high turn-down operations. These modifications were manufactured and explored by the team at Solar. High pressure rig tests, originally slated to occur at SwRI, were ultimately accomplished by Solar to maintain overall project budget and mitigate cost growth attributable to supply chain issues and inflation. The pressurized rig tests ultimately showed that the SwRI Project No. 18.24153 - DE-EE0008415 Page 2 Final Technical Report January 24, 2024 modifications did not significantly alter the performance of the combustion system at the high turn-down conditions; both the modified injectors and the baseline configuration exhibited elevated emissions comparted to the full-load operating condition. A final set of studies performed by EPRI investigated the benefit-cost of flexible CHP as well as a grid interconnection study for the California Independent System Operator (CAISO) grid. These studies considered: traditional CHP with no spinning reserve available for on-demand grid support, 50% flexible CHP where 50% of the machine’s capacity is consumed by on-site baseload operations while providing an additional 50% capacity for on-demand grid support, and 70% flexible CHP where 70% of capacity is consumed on-site by baseload operations and 30% is available for on-demand grid support. In all cases, the analyses showed a benefit-to-cost ratio greater than unity implying a positive net present value for all configurations. However, the traditional CHP showed the most economic benefit. These results are sensitive to several factors, many of which are not fully known and may vary over time. Thus site owners must be convinced that taking up the increased costs and risks from flexible CHP would be worth implementing. As the grid in California and across the country transition to incorporate larger renewable energy generation, flexible CHP can provide much needed operating reserves and dispatchability. Alternative fuel options, such as hydrogen blending and biofuels, may also lower carbon intensities of CHP. Flexible CHP should be examined in the evolving market to understand innovative business models, changes market rules and services, and new technologies.

20 FOSSIL-FUELED POWER PLANTS↗

Survey of Use Cases and Scenarios on the Open Energy Data Initiative Solar Systems Integration (OEDI SI) Platform

The Open Energy Data Initiative Solar Systems Integration (OEDI SI) Data and Modeling Platform offers a comprehensive set of use cases tailored for power systems analysis. Each use case is centered around a specific power system analysis problem, supported by composite input data and reference algorithms. These composite input datasets are meticulously assembled using OEDI SI's data preprocessing tools, which integrate raw data from various sources. The primary objectives of the OEDI SI Platform include facilitating access to composite input data through widely accepted input/output formats and verified results. This accessibility enables power system network researchers and developers to validate their algorithms and showcase their applications' capabilities to the broader community. Moreover, the platform strives to promote reproducible, robust, replicable, and generalizable solar systems integration research.

14 SOLAR ENERGY↗

Optimization of Canister Loading Patterns in Dual Purpose Canisters for Criticality Suppression

This report documents work performed in support of the US Department of Energy Office of Nuclear Energy (NE) Spent Fuel and Waste Disposition, Spent Fuel and Waste Science and Technology, under work breakdown structure element 1.08.01.03.05, “Direct Disposal of Dual Purpose Canisters.” In particular, this report fulfills milestone M3SF-22PN010305094, “Application of AI/ML techniques to optimize DPC loading,” within work package SF-22PN01030509, “Direct Disposal of Dual Purpose Canisters - PNNL.” This report continues the process of examining the potential for using loading optimization as a disposal criticality suppression technique. This latest update to the report added: 1. A validation of the artificial neural network (ANN) reactivity prediction tool against as-loaded dual-purpose canisters from the UNF-ST&DARDS database 2. Refinement of the algorithm to incorporate an additional DPC design to improve the predictions 3. Investigation of a storage and transportation focused loading optimization algorithm. A key result from this year’s work is that the ANN performance was significantly improved by including the additional model for the NUHOMS canisters and it is apparent that fuel type specific modeling considerations should be incorporated into the ANN in future work. The GRASP-enabled adaptive multi-objective memetic algorithm with partial clustering (GAMMA-PC) algorithm was evaluated as a tool for storage and transportation oriented optimization. The GAMMA-PC optimization routine considers decay heat at loading, the time between loading and when the canister is eligible for transportation and minimizes the number of casks loaded. Future work will develop a dose minimization optimization routine.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Machine Learning-Enabled Wearable Piezoelectric Acoustic Sensor for Real-Time Breast Abnormality Detection

In contemporary society, breast health has become a significant public health concern, particularly among women. According to statistics from the World Health Organization, both the incidence and mortality rates of breast tumors have steadily increased in recent years. Therefore, effective early-stage screening and postoperative monitoring are essential for maintaining breast health. However, conventional clinical diagnostic modalities are typically bulky, operationally complex, and unsuitable for continuous real-time monitoring, which limits their use in portable and everyday health management applications. To address these limitations, this study proposes a machine learning-integrated wearable piezoelectric sensing platform as an auxiliary tool for breast health assessment. The device consists of a PDMS matching layer embedded with flexible silver nanowires, a P(VDF-TrFE) piezoelectric layer, and a multi-channel low-noise signal acquisition circuit. It is capable of acquiring acoustic echo signals from tissue-mimicking environments and automatically evaluating signal validity using a convolutional neural network (CNN). By integrating piezoelectric sensing with deep learning-based signal analysis, the proposed system achieves a signal-to-noise ratio exceeding 70 dB and a real-time classification accuracy above 96% under controlled conditions. These results demonstrate that the platform provides a compact, portable, and intelligent approach for wearable sensing of mechanical heterogeneity and highlight its potential for future development in continuous biomedical monitoring technologies.

He, Shuaitong↗

A strategy for reducing turnaround time in design optimization using a distributed computer system

There is a need to explore methods for reducing lengthly computer turnaround or clock time associated with engineering design problems. Different strategies can be employed to reduce this turnaround time. One strategy is to run validated analysis software on a network of existing smaller computers so that portions of the computation can be done in parallel. This paper focuses on the implementation of this method using two types of problems. The first type is a traditional structural design optimization problem, which is characterized by a simple data flow and a complicated analysis. The second type of problem uses an existing computer program designed to study multilevel optimization techniques. This problem is characterized by complicated data flow and a simple analysis. The paper shows that distributed computing can be a viable means for reducing computational turnaround time for engineering design problems that lend themselves to decomposition. Parallel computing can be accomplished with a minimal cost in terms of hardware and software.

Young, Katherine C.↗

Interoperability through standardization: Electronic mail, and X Window systems

Since the introduction of computing machines, there has been continual advances in computer and communication technologies and approaching limits. The user interface has evolved from a row of switches, character based interface using teletype terminals and then video terminals, to present day graphical user interface. It is expected that next significant advances will come in the availability of services, such as electronic mail and directory services, as the standards for applications are developed and in the 'easy to use' interfaces, such as Graphical User Interface for example Window and X Window, which are being standardized. Various proprietary electronic mail (email) systems are in use within organizations at each center of NASA. Each system provides email services to users within an organization, however the support for email services across organizations and across centers exists at centers to a varying degree and is often easy to use. A recent NASA email initiative is intended 'to provide a simple way to send email across organizational boundaries without disruption of installed base.' The initiative calls for integration of existing organizational email systems through gateways connected by a message switch, supporting X.400 and SMTP protocols, to create a NASA wide email system and for implementation of NASA wide email directory services based on OSI standard X.500. A brief overview of MSFC efforts as a part of this initiative are described. Window based graphical user interfaces make computers easy to use. X window protocol has been developed at Massachusetts Institute of Technology in 1984/1985 to provide uniform window based interface in a distributed computing environment with heterogenous computers. It has since become a standard supported by a number of major manufacturers. Z Windows systems, terminals and workstations, and X Window applications are becoming available. However impact of its use in the Local Area Network environment on the network traffic are not well understood. It is expected that the use of X Windows systems will increase at MSFC especially for Unix based systems. An overview of X Window protocol is presented and its impact on the network traffic is examined. It is proposed that an analytical model of X Window systems in the network environment be developed and validated through the use of measurements to generate application and user profiles.

Amin, Ashok T.↗

Computer Aided Modeling to Determine the Effectiveness of Resistive Exercises as Countermeasures for Bone Mineral Density Loss

Due to the loss of gravitational loading, astronauts have a tendency to lose bone mineral density in their lumbar spine and lower extremities on orbit. NASA requires astronauts to perform exercises during space flight to help reduce the amount of demineralization. To test these exercises on earth, 17 week bed rest studies are conducted that consist of specific diet and exercise regimes. Developing a finite element model of these exercises will help to quantify the stress distribution imposed by of each of these exercises. To help develop this model, MRI images are acquired from individuals participating in the bed rest studies. The MRIs can be used to create a subject specific model of each individual for testing. The MRIs are processed in the Magnetic Resonance Imaging Data Transfer System program to develop a three-dimensional finite element model of the femur for evaluation. Modifications were made to the MRIDTS that simplified the model creation process. These modifications made it possible to construct two separate models of different portions of a bone simultaneously and then later connect them manually. This helped alleviate the warping problem associated with the drastic changes in geometry found in some body parts, such as the joints. The code was also modified to incorporate material properties of various bone components into the model. Interior meshing was also incorporated into the program to allow for both the cortical shell and the entire bone to be modeled. A prototype model of the right femur of an adult female is being constructed and tested to determine the feasibility of finite element analysis as a tool for evaluating exercise effectiveness. The model is being run through the ANSYS finite element program on the Alabama Super Computer Network. After the model is validated, models of bedrest subjects can be generated to investigate exercise countermeasures.

Murphy, Benjamin M.↗