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DOE OSTI2024

Investigating explainable transfer learning for battery lifetime prediction under state transitions

Battery lifetime prediction at early cycles is crucial for researchers and manufacturers to examine product quality and promote technology development. Machine learning has been widely utilized to construct data-driven solutions for high-accuracy predictions. However, the internal mechanisms of batteries are sensitive to many factors, such as charging/discharging protocols, manufacturing/storage conditions, and usage patterns. These factors will induce state transitions, thereby decreasing the prediction accuracy of data-driven approaches. Transfer learning is a promising technique that overcomes this difficulty and achieves accurate predictions by jointly utilizing information from various sources. Hence, we develop two transfer learning methods, Bayesian Model Fusion and Weighted Orthogonal Matching Pursuit, to strategically combine prior knowledge with limited information from the target dataset to achieve superior prediction performance. From our results, our transfer learning methods reduce root-mean-squared error by 41% through adapting to the target domain. Furthermore, the transfer learning strategies identify the variations of impactful features across different sets of batteries and therefore disentangle the battery degradation mechanisms and the root cause of state transitions from the perspective of data mining. These findings suggest that the transfer learning strategies proposed in our work are capable of acquiring knowledge across multiple data sources for solving specialized issues.

25 ENERGY STORAGE↗

DOE OSTI2025

Device-independent Quantum Position Verification

We propose and implement a device-independent protocol for quantum position verification against unentangled adversaries. Our experiment achieves provable localization to a 1-dimensional region that is 40.7(7) % the size of the smallest theoretical region achievable with classical protocols.

Kavuri, Gautam A. [NIST Boulder]↗

NASA NTRS1990

Synchronizing computer clocks using a local area network

Researchers completed the first tests of a method to synchronize the clocks of networked computers to the National Institute of Standards and Technology (NIST) time scale. The method uses a server computer to disseminate the time to other clients on the same local-area network. The server is synchronized to NIST using the ACTS protocol over a dial-up telephone line. The software in both the server and the parameters of this model are used to adjust the time of the local clock and the interval between calibration requests in a statistically optimum way. The algorithm maximizes the time between calibrations while at the same time keeping the time of the local clock correct within a specific tolerance. The method can be extended to synchronize computers linked over wide-area networks, and an experiment to test the performance of the algorithms over such networks is being planned.

Levine, Judah↗

NASA NTRS2011

Fatigue Management in Spaceflight Operations

Sleep loss and fatigue remain an issue for crewmembers working on the International Space Station, and the ground crews who support them. Schedule shifts on the ISS are required for conducting mission operations. These shifts lead to tasks being performed during the biological night, and sleep scheduled during the biological day, for flight crews and the ground teams who support them. Other stressors have been recognized as hindering sleep in space; these include workload, thinking about upcoming tasks, environmental factors, and inadequate day/night cues. It is unknown if and how other factors such as microgravity, carbon dioxide levels, or increased radiation, may also play a part. Efforts are underway to standardize and provide care for crewmembers, ground controllers and other support personnel. Through collaborations between research and operations, evidenced-based clinical practice guidelines are being developed to equip flight surgeons with the tools and processes needed for treating circadian desynchrony (and subsequent sleep loss) caused by jet lag and shift work. The proper implementation of countermeasures such as schedules, lighting protocols, and cognitive behavioral education can hasten phase shifting, enhance sleep and optimize performance. This panel will focus on Fatigue Management in Spaceflight Operations. Speakers will present on research-based recommendations and technologies aimed at mitigating sleep loss, circadian desynchronization and fatigue on-orbit. Gaps in current mitigations and future recommendations will also be discussed.

Whitmire, Alexandra↗

DOE OSTI2025

Performance Evaluation of Intelligent Solar Control Software Through Hardware-in-the-Loop (CRADA Final Report)

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 developed by Latimer Controls, Inc. to estimate the headroom of large PV plants for grid operation and control; however, these technologies lack comprehensive validation under real-world application scenarios. Latimer Controls, Inc. received two voucher awards for research at a national laboratory from the Department of Energy American Made Solar Prize Round 6. The National Renewable Energy Laboratory (NREL) was selected to collaborate with Latimer staff to conduct a performance evaluation of Latimer PV control software. The NREL team will develop a hardware-in-the-loop (HIL) testbed to perform testing and validation of the Latimer PV control technology in a de-risked yet realistic testbed environment. Latimer and NREL worked together to analyze the test data, draw conclusions from the results, and disseminate the resulting scientific findings. In this CRADA work, we propose to test and validate the real-world application of the Latimer Control solution in an HIL environment. We evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. In particular, a data-driven potential high limit (PHL) estimation is developed for large solar plants to accurately estimate their headroom so that they have fast and short-time regulation and control capability to participate in grid services and respond to grid signals in real time (e.g., AGC). This PHL estimation algorithm is embedded in a hardware power plant controller (PPC) and tested with an IEEE-39 bus system model developed in RTDS. To account for the varying cloud conditions and diverse inverter dispatches, we developed a 135-MW PV plant with detailed modeling of 27 individual PV modules and inverters using RTDS. The real-world communications used in such big plants, such as ModBus TCP/IP for inverter level and DNP3 for plant level, were developed to emulate the real-world applications in big PV plants. The ML-based PHL estimation method is tested under nine separate weather scenarios against the ‘reference-control’ solution, hereafter referred to as the baseline solution. The baseline method reserves a subset of inverters (reference group) to operate at their PHL at all times and dispatches only the remaining inverters (control group) at curtailed levels to fulfill the flexibility need. Despite being successfully piloted by NREL in California in 2017 and Chile in 2020, there exist two gaps in the state of the art to fully unlock the flexibility of PV plants: a. There is a trade-off between the PHL estimation accuracy and the flexibility range. b. There lacks granularity in the PHL estimation to capture the variation across inverters. The Latimer solution seeks to address these gaps by applying machine learning methods to improve PHL estimation accuracy while accounting for variability at every inverter. Performance metrics were taken from the 2023 Georgia Power CARES utility-scale RFP. The results demonstrate that the ML-based approach outperforms the traditional baseline method in PHL estimation accuracy for 7 of 9 scenarios. The average PHL error across the nine scenarios was 7.40% for the ML-based method, 2.06% less than the 9.46% PHL error average across scenarios that was exhibited by the baseline method. Additionally, the PHL error was below 5% for at least 95% of the testing interval for 3 of 9 tested intervals with the ML approach, whereas it did not achieve this metric for any of the baseline tests. Overall, simulation results indicate the superior performance of an ML-based approach compared to the conventional baseline reference-control approach, showcasing its potential to support grid stability and operational efficiency. This laboratory HIL testing using real PPC, representative power system simulation models in real-time with detailed PV plant and inverter models, and real-world communication protocols gives us confidence that this machine learning based PHL estimation algorithm works well in the hardware PPC and therefore de-risks future field commissioning. The end goal of this project is to advance grid technology to address the grid operation challenges brought by solar plant’s variability and uncertainties in power generation.

14 SOLAR ENERGY↗

DOE OSTI2024

Real-Time Protocol Engineering with the B Language

It is an invariant that critical cyberphysical systems should not fail. Mission assurance requires systems to behave with predictability, especially in their ability to satisfy real-time constraints. The NIST standard for Engineering Trustworthy Secure Systems, National Institute of Standards and Technology (NIST) Special Publication (SP) 800-160v1r1 states that formal methods are the highest level for meeting assurance requirements. There is a tension between the formal method software development process (Figure 1), which does not introduce time specificity until the latter stages of the development process (concrete model), and the need to gain confidence that time constraints will be satisfied. This paper formalizes the practical application of temporal entities e.g. Propositional Temporal Logic (PTL), Temporal Logic of Actions Plus (TLA+), etc. to critical systems.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2009

Research on the International Space Station - An Overview

The International Space Station (ISS) celebrates ten years of operations in 2008. While the station did not support permanent human crews during the first two years of operations November 1998 to November 2000 it hosted a few early science experiments months before the first international crew took up residence. Since that time and simultaneous with the complicated task of ISS construction and overcoming impacts from the tragic Columbia accident science returns from the ISS have been growing at a steady pace. As of this writing, over 162 experiments have been operated on the ISS, supporting research for hundreds of ground-based investigators from the U.S. and international partners. This report summarizes the experimental results collected to date. Today, NASA's priorities for research aboard the ISS center on understanding human health during long-duration missions, researching effective countermeasures for long-duration crewmembers, and researching and testing new technologies that can be used for future exploration crews and spacecraft. Through the U.S. National Laboratory designation, the ISS is also a platform available to other government agencies. Research on ISS supports new understandings, methods or applications relevant to life on Earth, such as understanding effective protocols to protect against loss of bone density or better methods for producing stronger metal alloys. Experiment results have already been used in applications as diverse as the manufacture of solar cell and insulation materials for new spacecraft and the verification of complex numerical models for behavior of fluids in fuel tanks. A synoptic publication of these results will be forthcoming in 2009. At the 10-year point, the scientific returns from ISS should increase at a rapid pace. During the 2008 calendar year, the laboratory space and research facilities were tripled with the addition of ESA's Columbus and JAXA's Kibo scientific modules joining NASA's Destiny Laboratory. All three laboratories, together with external payload accommodations, support a wide variety of research racks and science and technology experiments. In 2009, the number of crewmembers will increase from three to six, greatly increasing the time available for research. The realization of the international scientific partnership provides new opportunities for scientific collaboration and broadens the research potential on the ISS. Engineers and scientists from around the world are working together to refine their operational relationships and build from their experiences conducting early science to ensure maximum utilization of the expanded capabilities aboard ISS. This paper will summarize science results and accomplishments, and discuss how the early science utilization provides the foundation for continuing research campaigns aboard the ISS that will benefit future exploration programs.

Evans, Cynthia A.↗

DOE OSTI2025

Toward accelerating rare-earth metal extraction using equivariant neural networks

The separation of rare-earth metals, vital for numerous advanced technologies, is hampered by their similar chemical properties, making ligand discovery a significant challenge. Traditional experimental and quantum chemistry approaches for identifying effective ligands are often resource-intensive. We introduce a machine learning protocol based on an equivariant neural network, Allegro, for the rapid and accurate prediction of binding energies in rare-earth complexes. Key to this work is our newly curated dataset of rare-earth metal complexes—made publicly available to foster further research—systematically generated using the Architector program. This dataset distinctively features functionalized derivatives of proven rare-earth-chelating scaffolds, hydroxypyridinone (HOPO), catecholamide (CAM), and their thio-analogues, selected for their established efficacy in binding these elements. Trained on this valuable resource, our Allegro models demonstrate excellent performance, particularly when trained to directly predict DFT-level binding energies, yielding highly accurate results that closely correlate with theoretical calculations on a diverse test set. Furthermore, this strategy exhibited strong out-of-sample generalization, accurately predicting binding energies for an isomeric HOPO-derivative ligand not seen during training. By substantially reducing computational demands, this machine learning framework, alongside the provided dataset, represent powerful tools to accelerate the high-throughput screening and rational design of novel ligands for efficient rare-earth metal separation.

Gupta, Ankur K. [Lawrence Berkeley National Labora↗

DOE OSTI2025

SF6 / Acetone Separation & Purification

Sulfur hexafluoride (SF₆) is recognized as the most potent greenhouse gas used in the power transmission and semiconductor sectors. In the past decade, its global emissions have increased sharply, largely due to the absence of effective disposal and recovery pathways. This concern was formally addressed under the Kyoto Protocol, which urged participating nations to adopt measures to limit SF₆ emissions and mitigate its role in climate change. In recent years, various abatement strategies have been explored, including non-thermal plasma (NTP) technologies such as radio frequency, microwave, dielectric barrier discharge, and electron beam systems. While these methods can decompose SF₆, they also produce hazardous by-products like sulfur oxyfluorides, sulfur dioxide, hydrofluoric acid, and fluorine gas. Because these compounds pose both environmental and health risks, replacing traditional disposal practices with modern, more effective treatment methods has become an urgent priority.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Large Scale Field Demonstration Evaluation Plan

This Evaluation Plan defines practical, commissioning-oriented test protocols for in-field assessment of grid-forming (GFM) inverter-based resources (IBRs) deployed under the UNIFI Consortium Field Demonstration. The demonstration’s overarching objective is to validate multi vendor GFM technologies at impactful unit/plant scale, assess interoperability and grid-service performance, and evaluate the applicability of the UNIFI Specifications for Grid-forming Inverter-based Resources in real utility environments, including integration with operational systems and protection schemes.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2007

Middleware Trade Study for NASA Domain

This presentation presents preliminary results of a trade study designed to assess three distributed simulation middleware technologies for support of the NASA Constellation Distributed Space Exploration Simulation (DSES) project and Test and Verification Distributed System Integration Laboratory (DSIL). The technologies are: the High Level Architecture (HLA), the Test and Training Enabling Architecture (TENA), and an XML-based variant of Distributed Interactive Simulation (DIS-XML) coupled with the Extensible Messaging and Presence Protocol (XMPP). According to the criteria and weights determined in this study, HLA scores better than the other two for DSES as well as the DSIL

Bowman, Dan↗

NASA NTRS2008

NASA Constellation Distributed Simulation Middleware Trade Study

This paper presents the results of a trade study designed to assess three distributed simulation middleware technologies for support of the NASA Constellation Distributed Space Exploration Simulation (DSES) project and Test and Verification Distributed System Integration Laboratory (DSIL). The technologies are the High Level Architecture (HLA), the Test and Training Enabling Architecture (TENA), and an XML-based variant of Distributed Interactive Simulation (DIS-XML) coupled with the Extensible Messaging and Presence Protocol (XMPP). According to the criteria and weights determined in this study, HLA scores better than the other two for DSES as well as the DSIL.

Hasan, David↗

NASA NTRS1997

Design Protocols and Analytical Strategies that Incorporate Structural Reliability Models

Ceramic matrix composites (CMC) and intermetallic materials (e.g., single crystal nickel aluminide) are high performance materials that exhibit attractive mechanical, thermal, and chemical properties. These materials are critically important in advancing certain performance aspects of gas turbine engines. From an aerospace engineers perspective the new generation of ceramic composites and intermetallics offers a significant potential for raising the thrust/weight ratio and reducing NO(sub x) emissions of gas turbine engines. These aspects have increased interest in utilizing these materials in the hot sections of turbine engines. However, as these materials evolve and their performance characteristics improve a persistent need exists for state-of-the-art analytical methods that predict the response of components fabricated from CMC and intermetallic material systems. This need provided the motivation for the technology developed under this research effort. Continuous ceramic fiber composites exhibit an increase in work of fracture, which allows for 'graceful' rather than catastrophic failure. When loaded in the fiber direction these composites retain substantial strength capacity beyond the initiation of transverse matrix cracking despite the fact that neither of its constituents would exhibit such behavior if tested alone. As additional load is applied beyond first matrix cracking, the matrix tends to break in a series of cracks bridged by the ceramic fibers. Any additional load is born increasingly by the fibers until the ultimate strength of the composite is reached. Thus modeling efforts supported under this research effort have focused on predicting this sort of behavior. For single crystal intermetallics the issues that motivated the technology development involved questions relating to material behavior and component design. Thus the research effort supported by this grant had to determine the statistical nature and source of fracture in a high strength, NiAl single crystal turbine blade material; map a simplistic future strength envelope of the material; develop a statistically based reliability computer algorithm; verify the reliability model and computer algorithm-, and model stator vanes for rig tests. Thus establishing design protocols that enable the engineer to analyze and predict the mechanical behavior of ceramic composites and intermetallics would mitigate the prototype (trial and error) approach currently used by the engineering community. The primary objective of the research effort supported by this short term grant is the continued creation of enabling technologies for the macro-analysis of components fabricated from ceramic composites and intermetallic material systems. The creation of enabling technologies aids in shortening the product development cycle of components fabricated from the new high technology materials.

Duffy, Stephen F.↗

NASA NTRS1997

Design Protocols and Analytical Strategies that Incorporate Structural Reliability Models

Ceramic matrix composites (CMC) and intermetallic materials (e.g., single crystal nickel aluminide) are high performance materials that exhibit attractive mechanical, thermal and chemical properties. These materials are critically important in advancing certain performance aspects of gas turbine engines. From an aerospace engineer's perspective the new generation of ceramic composites and intermetallics offers a significant potential for raising the thrust/weight ratio and reducing NO(x) emissions of gas turbine engines. These aspects have increased interest in utilizing these materials in the hot sections of turbine engines. However, as these materials evolve and their performance characteristics improve a persistent need exists for state-of-the-art analytical methods that predict the response of components fabricated from CMC and intermetallic material systems. This need provided the motivation for the technology developed under this research effort. Continuous ceramic fiber composites exhibit an increase in work of fracture, which allows for "graceful" rather than catastrophic failure. When loaded in the fiber direction, these composites retain substantial strength capacity beyond the initiation of transverse matrix cracking despite the fact that neither of its constituents would exhibit such behavior if tested alone. As additional load is applied beyond first matrix cracking, the matrix tends to break in a series of cracks bridged by the ceramic fibers. Any additional load is born increasingly by the fibers until the ultimate strength of the composite is reached. Thus modeling efforts supported under this research effort have focused on predicting this sort of behavior. For single crystal intermetallics the issues that motivated the technology development involved questions relating to material behavior and component design. Thus the research effort supported by this grant had to determine the statistical nature and source of fracture in a high strength, NiAl single crystal turbine blade material; map a simplistic failure strength envelope of the material; develop a statistically based reliability computer algorithm, verify the reliability model and computer algorithm, and model stator vanes for rig tests. Thus establishing design protocols that enable the engineer to analyze and predict the mechanical behavior of ceramic composites and intermetallics would mitigate the prototype (trial and error) approach currently used by the engineering community. The primary objective of the research effort supported by this short term grant is the continued creation of enabling technologies for the macroanalysis of components fabricated from ceramic composites and intermetallic material systems. The creation of enabling technologies aids in shortening the product development cycle of components fabricated from the new high technology materials.

Duffy, Stephen F.↗

NASA NTRS2011

Automatic Facial Expression Recognition and Operator Functional State

The prevalence of human error in safety-critical occupations remains a major challenge to mission success despite increasing automation in control processes. Although various methods have been proposed to prevent incidences of human error, none of these have been developed to employ the detection and regulation of Operator Functional State (OFS), or the optimal condition of the operator while performing a task, in work environments due to drawbacks such as obtrusiveness and impracticality. A video-based system with the ability to infer an individual's emotional state from facial feature patterning mitigates some of the problems associated with other methods of detecting OFS, like obtrusiveness and impracticality in integration with the mission environment. This paper explores the utility of facial expression recognition as a technology for inferring OFS by first expounding on the intricacies of OFS and the scientific background behind emotion and its relationship with an individual's state. Then, descriptions of the feedback loop and the emotion protocols proposed for the facial recognition program are explained. A basic version of the facial expression recognition program uses Haar classifiers and OpenCV libraries to automatically locate key facial landmarks during a live video stream. Various methods of creating facial expression recognition software are reviewed to guide future extensions of the program. The paper concludes with an examination of the steps necessary in the research of emotion and recommendations for the creation of an automatic facial expression recognition program for use in real-time, safety-critical missions.

Blanson, Nina↗

NASA NTRS2012

Remotely Powered Reconfigurable Receiver for Extreme Environment Sensing Platforms

Wireless sensors connected in a local network offer revolutionary exploration capabilities, but the current solutions do not work in extreme environments of low temperatures (200K) and low to moderate radiation levels (<50 krad). These sensors (temperature, radiation, infrared, etc.) would need to operate outside the spacecraft/ lander and be totally independent of power from the spacecraft/lander. Flash memory field-programmable gate arrays (FPGAs) are being used as the main signal processing and protocol generation platform in a new receiver. Flash-based FPGAs have been shown to have at least 100 reduced standby power and 10 reduction operating power when compared to normal SRAM-based FPGA technology.

Sheldon, Douglas J.↗

NASA NTRS2012

Automatic Facial Expression Recognition and Operator Functional State

Blanson, Nina↗

NASA NTRS2018

Enabling Technologies for Deep Space Imaging

From the beginning of the Space Age, imagery, particularly motion imagery, has been a part of crewed and un-crewed missions. As technologies have evolved the imagery gets better, more compelling, and more useful for operations and monitoring of systems, crew, and spacecraft. As we look forward now to crewed missions beyond low-Earth orbit, such as the Lunar Orbiting Platform-Gateway being considered as a pre-cursor to future crewed Mars missions, there are both opportunities and challenges in implementing a multi-faceted imaging system that advances mission capabilities and technology. This paper will present a vision for an imaging system that is relevant for operations of the ISS and future crewed missions in deep space, with a detailed look at some of the key innovative technologies required to enable such a system. Specific enabling technologies included are: Innovative camera systems capable of providing a 360deg field-of-view without moving parts; Ultra-high Definition (or higher) resolution; High Efficiency Video Coding compression; Compatibility with Delay Tolerant Network protocols; and Intelligent systems capable of monitoring the field-of-view for un-crewed missions. Opportunities where Standardization can enable interoperability are also identified.

Grubbs, Rodney↗