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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Wildfire-Power Grid Interactions: Feedback, Impacts, Monitoring, Modeling, and Mitigation Strategies

Wildfires are increasingly interacting with electric power systems through a two-way hazard chain: fires damage grid assets and trigger cascading outages, while grid faults can ignite new fires under hot, dry, and windy conditions. This review synthesizes the state of knowledge across five domains: (i) physical impacts of flames, heat, and smoke on lines, towers, insulators, and substations; (ii) power-infrastructure-initiated ignitions via conductor clash, high-impedance faults, and corona discharge; (iii) widespread blackouts and disproportionate societal impacts; (iv) multi-scale monitoring spanning laboratory tests, in-situ and grid-integrated sensors, and Earth observation; (v) coupled modeling that links fire behavior with grid operations; and (vi) technological and strategic mitigation pathways spanning prevention, response, and recovery. We integrate these domains into a novel 'feedback-aware' socio-technical framework. Through a longitudinal analysis (2005-2025) of global incidents, we identify that while vegetation contact remains the most frequent ignition source, aging infrastructure failure has emerged as a critical driver of catastrophic 'mega-fires'. We further identify persistent gaps, including limited interoperability of high-frequency grid and environmental data, scarce real-time data assimilation, and under-developed equity metrics for outage management. We conclude by outlining a research agenda to (1) deploy interoperable sensing architectures, (2) advance feedback-coupled fire-grid simulations, and (3) evaluate mitigation portfolios through techno-economic and fairness lenses. Recognizing wildfire-grid interactions as coupled socio-technical systems is essential for protecting infrastructure and communities and for ensuring reliable, sustainable electricity in a changing world.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Integrating Electromagnetic Acoustic Transducers in a Modular Robotic Gripper for Inspecting Tubular Components

Tubular structures are critical components in infrastructure such as power plants. Throughout their life, they are subjected to extreme conditions or suffer from defects such as corrosion and cracks. Although regular inspection of these components is necessary, such inspection is limited by safety-related risks and limited access for human inspection. Robots can provide a solution for automatic inspection. The main challenge, however, lies in integrating sensors for nondestructive evaluation with robotic platforms. As part of developing a versatile lizard-inspired tube inspector robot, in this study the authors propose to integrate electromagnetic acoustic transducers into a modular robotic gripper for use in automated ultrasonic inspection. In particular, spiral coils with cylindrical magnets are integrated into a novel friction-based gripper to excite Lamb waves in thin cylindrical structures. To evaluate the performance of the integrated sensors, the gripper was attached to a robotic arm manipulator and tested on pipes of different outer diameters. Two sets of tests were carried out on both defect-free pipes and pipes with simulated defects, including surface partial cracking and corrosion. The inspection results indicated that transmitted and received signals could be acquired with an acceptable signal-to-noise ratio in the time domain. Moreover, the simulated defects could be successfully detected using the integrated robotic sensing system.

Materials Science↗
DOE OSTI2022

Additively manufactured tamper evident container

A tamper evident container includes a container body having walls surrounding a cavity. The walls are composed of a non-electrically conductive material and at least one integrity sensor that is embedded in the non-electrically conductive material. A monitoring circuit is configured to monitor the tamper evident container using the at least one integrity sensor and determine a state-of-health of the tamper evident container.

Bernardin, John D.↗
DOE OSTI2021

Microfluidic Liquid-Liquid Extraction Chip with Integrated Raman Sensors (Phase I and Phase II Final Report)

As demand for electricity continues to increase worldwide, the world’s nuclear power generating capacity will continue to grow. Nuclear power is the most environmentally benign way of producing electricity on a large scale. The long-term successful use of nuclear power, however, is critically dependent upon adequate and safe processing and disposal of spent nuclear fuels. A very important feature of nuclear energy is that spent fuels can be reprocessed to recover fissile and fertile materials that can then be used as fresh fuel for nuclear power plants. The DOE-NE Fuel Cycle Research and Development (FCR&D) is currently developing nuclear material reprocessing technologies. In a typical nuclear fuel reprocessing system, centrifugal contactors are used as liquid-liquid extraction devices where two immiscible liquids are mixed at high speeds using a rotor, which creates a fine dispersion of droplets of organic phase in an aqueous phase that contains the analyte. Understanding the extraction efficiency at these contactors through modeling and simulation is important in the development of reprocessing technologies and the optimization of current technologies such as the PUREX process. The outcome of this program will be a liquid-liquid microfluidic flow cell chip with embedded spectroscopic sensors for the analysis of extracted analytes. This device will be useful in the optimization of new fuel reprocessing schemes as well as existing reprocessing processes by providing a microfluidic modeling platform to optimize extraction parameters. The Phase I and Phase II work developed a microfluidic chip design that allows integration of Raman and absorption fiber optic probes and successfully demonstrated the feasibility of using Raman and absorption probes to detect key analytes that partition into the aqueous and organic phases.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Building-Integrated Microscale Sensors for CO 2 -Level Monitoring

This research effort enabled the development of new classes of small-scale sensing systems that use mass and/or electrochemical sensors to detect the presence of carbon dioxide (CO 2 ). The concentration of this gas within the indoor environment is an important metric, as it can help enable the use of variable speed ventilation fans in commercial and governmental buildings, thus saving a significant amount of energy. Furthermore, there is a pressing need for enhanced CO 2 sensing to improve the comfort and productivity of people in commercial and government buildings, including academic spaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Modular Subsurface Sensors and Integrated Software for Advanced Subsurface Characterization and Monitoring using Unoccupied Vehicles

The advent and subsequent proliferation of autonomous airborne, waterborne, and groundbased vehicles (i.e., “drones”) promises to broadly transform the geosciences and associated industries, including fossil energy exploration and development, mineral resource exploration and development, water-resource management, and environmental remediation. For geophysical characterization and monitoring, the prospect of programming highly repeatable and low-cost drone missions for subsurface imaging will allow for deployments in hazardous and previously inaccessible areas. Coupled with autonomous workflows for data processing, management, and visualization, drone-based geophysical characterization and monitoring will enable unprecedented, real-time insight into diverse subsurface properties and processes of scientific and engineering importance. Toward this end, the objectives of this Lab Directed Research and Development (LDRD) project were to develop new (1) instrumentation for dronebased electromagnetic induction (EMI) geophysical imaging, including separated transmitter and receivers and associated electronics, (2) software for real-time data telemetry, processing, management, and visualization. Although EMI has been previously deployed using unoccupied aerial systems (UASs), these applications failed to capitalize on the game-changing capabilities of drone platforms. Whereas drone-based data acquisition allows for collection of rich, three-dimensional (3D) multi-offset/multi-angle configurations between transmitters and receivers, past efforts have relied on conventional instrumentation that was designed for ground-based data collection with the transmitter and a single receiver housed in the same unit; nor did these previous applications demonstrate real-time delivery of results to support rapid management decisions in the field. In this 1-year project, we (1) designed and constructed new lightweight independent transmitter and receiver antenna platforms that communicate with a laptop computer; (2) developed software to control data acquisition, manage/transfer data, and visualize data as its collected; and (3) demonstrated the operation of the new hardware and software systems in a ground-based field test. Our work entails major technological advances for EMI and established a foundation on which to build a new drone-based, real-time geophysical EMI imaging capability to support diverse challenges facing the nation.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Low-cost Retrofit Kit for Integral Reciprocating Compressors (IRCs) to Reduce Emissions and Enhance Efficiency

Methane emissions from natural gas engines within the oil and gas industry pose a significant environmental challenge, contributing approximately 34.1 MMTCO2 eq to the total of 239 MMTCO2 eq of methane emissions in 2021, according to the EPA report. In response to this pressing issue, a collaborative effort involving the University of Oklahoma and key industry partners—WAGO Automation, Mid Continental Rental, Elipsa, and Perscient—has resulted in the development of a retrofit kit designed to reduce emissions from integral reciprocating compressors (IRCs), which are integrated compressors and engines. The retrofit kit developed comprises an Air Management System (AMS), Integrated Sensors, and a Cloud-Connected Control Unit with Graphical User Interface (GUI)/Human-Machine Interface (HMI). This solution enhances operational efficiency, reduces emissions, and expands the operational envelope of IRCs in the natural gas industry. The project successfully completed all tasks, including the installation of a full-size IRC at a designated site in Oklahoma, the development of an optimized AMS, integration of sensors, and implementation of a data acquisition system. Significant achievements include a notable reduction in CH 4 emissions, up to 84% at specific loads, and the successful deployment of the retrofit kit in diverse field conditions. The system's capabilities were enhanced through the creation of a feedback control algorithm for the AMS using a correlation matrix illustrating relationships between engine parameters, and the design of a predictive and preventive maintenance platform. The project concluded with the deployment of the entire retrofit kit to another location, confirming its effectiveness in reducing emissions and enhancing IRC performance. The comprehensive solution offers valuable benefits for IRCs, making them invaluable assets in the natural gas industry.

03 NATURAL GAS↗
DOE OSTI2025

Integrated soft snake robot for gamma spectroscopy of radiologically contaminated ducting

Anticipated growth in the number and complexity of nuclear facilities entering the decommissioning phase of their lifespan requires innovative methods of mitigating radiological and safety hazards for workers. Advancements in robotics provide opportunities for remote characterization of radiologically contaminated ducts and pipes, reducing worker exposure. However, the nuclear decommissioning industry has shown a hesitancy in adopting new technology due to concerns regarding capital costs and a lack of demonstration data in representative environments. This work aims to leverage novel soft robotics to develop and demonstrate a sensor-integrated characterization tool for contaminated ducting systems. Two gamma spectrometers – one scintillation-based and one solid-state – were selected and integrated into a pneumatically-actuated snake-like soft robot using stretchable electronic cabling. The robot was then demonstrated at the Idaho National Laboratory’s Critical Infrastructure Test Range Complex. The robot maneuvered through a pseudo-constrained corridor containing several sealed sources and the integrated spectrometers collected spectra at various points along the path of travel. Both spectrometers successfully collected spectra with identifiable, isotope-specific peaks. To evaluate the effect of contamination buildup on the collected spectra, the robot with the integrated scintillation detector was tested using a liquid radioactive source. The resulting spectra showed little detection interference from the liquid contamination; however, a short-lived isotope was used which may not be representative of longer-lived contamination.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Selection of Components for the Remote, Canister-Monitoring System

This report documents the selection of components as part of the efforts initiated to develop a remote, canister-monitoring system (RCMS) for determining and monitoring environmental conditions within dry fuel storage canisters containing aluminum clad spent nuclear fuel (ASNF) at the Idaho National Laboratory (INL). These efforts are in support of Department of Energy Office of Environmental Management (DOE-EM) investigations into technical issues associated with extended dry storage (50+ years) of ASNF. The capability to establish and monitor the performance of ASNF in situ provides the opportunity to (1) evaluate the appropriate technologies for monitoring, (2) collect canister environment conditions as soon as possible, (3) verify and validate current laboratory-based study results and analytic modeling approaches, and (4) potentially identify additional dry storage options for ASNF at the INL site. The improved understanding of ASNF behavior gained by performing this work would also contribute to the safety basis for extended dry storage in current and future configurations as well as to provide information for future transportation, conditioning, and disposal of ASNF. The parameters to be monitored by the RCMS include temperature, relative humidity, hydrogen gas concentration and radiation environment (dose). Components are selected based on the expected environmental conditions within the canister and fuel storage area, and the desired performance of the RCMS. Several of these components have been purchased and received. Future activities include component testing and calibration, software development for operation of the integrated sensor module and fabrication of a representative test volume. The results of these tests and changes to desired performance characteristics will inform subsequent activities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Assessment of the Impact of Realistic Sensor Physics and the Integration of Ex-Core Sensors on Reactor Power Synthesis

In the work documented in this report, a weighting function–based core power synthesis method was applied to multiple Monte Carlo N-Particle (MCNP) reactor models, which are informed based on simulated self-powered neutron detector (SPND) responses. The weighting function method used has been coined the point-based iterative (PBI) method. The goal of this application is to assess the impact of considering realistic sensor physics in the generation of the simulated SPND outputs as well as to consider how the synthesis is impacted based on the inclusion of ex-core detectors in the model. The NuScale small modular reactor (SMR) and Westinghouse AP1000 pressurized water reactor (PWR) are the models that served as the testbeds for the assessment of realistic sensor physics; this was achieved by using Geant4 SPND models in comparison with analytical models, such that the effect of electron transport in realistic SPND geometries in the Geant4 model can be understood in terms of synthesis error and convergence time. The comparison was considered for fuel burnup–induced perturbations, for a range of sensor string densities and synthesized power distribution axial fidelities. The Texas A&M Testing, Research, Isotopes, General Atomics Reactor (TAMU TRIGA) reactor MCNP model was used to assess the impact of ex-core sensors; this was done by performing synthesis with and without the ex-core detectors and by quantifying the synthesis error and number of iterations associated with Gaussian-type perturbations in many locations in the core. The TAMU TRIGA model was particularly pertinent for this study because of the interest in future experimental tests with SPNDs in this reactor, as well as the ease of modifying the MCNP model to include ex-core detectors with heterogeneously described response functions. Results from the comparison between the Geant4 and analytical SPND models indicate that similar average and maximum synthesis errors were obtained for burnup-induced perturbations in both the NuScale SMR and the AP1000. This was true for a range of sensor string densities and axial fidelities. However, there were marked differences between both the Geant4 and analytically informed models in terms of the iterations required to converge on the synthesized power distribution. Namely, the Geant4-informed models tended to lead to fewer iterations, except for a few sensor–core configurations that had particularly numerous iterations. Results from the ex-core sensor assessment with the TAMU TRIGA model indicate that the inclusion of ex-core sensors drastically reduces the synthesis error of Gaussian-type perturbations close to the edge of the core, and it slightly reduces synthesis errors for perturbations closer to the center of the core. This was achieved with a minimal increase in computational cost—that is, the number of iterations required for convergence. The errors were identified to be in the same location as the perturbation in the core, indicating that the methodology remains robust for unperturbed regions of the core. A secondary result from this study with the TAMU TRIGA was yielded by analysis of the neutron flux levels in the in-core and ex-core sensor locations of the core; these flux levels indicate that SPNDs could be used as both in-core and ex-core sensors, so long as the emitter material is sensitive to thermal neutrons. The results from these studies provide a quantitative understanding of the importance of considering realistic sensor physics and including ex-core sensors to perform accurate and timely power distribution synthesis of a reactor core.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Hierarchical Tactile Sensation Integration from Prosthetic Fingertips Enables Multi-Texture Surface Recognition

Multifunctional flexible tactile sensors could be useful to improve the control of prosthetic hands. To that end, highly stretchable liquid metal tactile sensors (LMS) were designed, manufactured via photolithography, and incorporated into the fingertips of a prosthetic hand. Three novel contributions were made with the LMS. First, individual fingertips were used to distinguish between different speeds of sliding contact with different surfaces. Second, differences in surface textures were reliably detected during sliding contact. Third, the capacity for hierarchical tactile sensor integration was demonstrated by using four LMS signals simultaneously to distinguish between ten complex multi-textured surfaces. Four different machine learning algorithms were compared for their successful classification capabilities: K-nearest neighbor (KNN), support vector machine (SVM), random forest (RF), and neural network (NN). The time-frequency features of the LMSs were extracted to train and test the machine learning algorithms. The NN generally performed the best at the speed and texture detection with a single finger and had a 99.2 ± 0.8% accuracy to distinguish between ten different multi-textured surfaces using four LMSs from four fingers simultaneously. The capability for hierarchical multi-finger tactile sensation integration could be useful to provide a higher level of intelligence for artificial hands.

Abd, Moaed A. (ORCID:0000000284954244)↗
DOE OSTI2022

Agency Recognized for Integrated Controls for HVAC and Lighting Systems - Case Study: Denver Water

This case study highlights the strategies Denver Water used at its Administration Building for integrating HVAC and lighting systems. They employed advanced lighting controls, integrated with building automation systems, as well as lighting system occupancy sensors integrated with HVAC controls. The project was recognized by DOE's Integrated Lighting Campaign.

integrated lighting, lighting, controls, HVAC, bui↗
DOE OSTI2023

Technical Challenges and Gaps in Integration of Advanced Sensors, Instrumentation, and Communication Technologies with Digital Twins for Nuclear Application

This paper explores integrating advanced sensor, instrumentation, and communication technologies with digital twin technologies for nuclear energy application. Digital twins and digital-twin-enabling technologies are expected to integrate with future nuclear reactor designs and have the potential to impact currently operating nuclear power plants. Greater digital integration, advanced instrumentation and control systems, and advanced operations and maintenance practices are all associated with digital-twin-enabling technologies. Advanced sensors, instrumentation, and communication technology are expected to comprise important elements of the infrastructure required to develop and operate a nuclear digital twin system. This paper identifies and discusses challenges and gaps in developing and implementing advanced sensors and instrumentation and communication technology to be integrated with a digital twin in current and advanced reactor applications. It is important to address some challenge and gap to enable a successful near-term deploying advanced sensors, instrumentation, and communication technologies integrated with digital twins.

Yadav, Vaibhav↗
DOE OSTI2025

Embedded Sensing in Additive Manufacturing Metal and Polymer Parts: A Comparative Study of Integration Techniques and Structural Health Monitoring Performance

This study presents a comparative evaluation of post-process sensor integration in additively manufactured (AM) metal and the in-situ process for polymer structures for structural health monitoring (SHM), with an emphasis on embedded sensors. Geometrically identical specimens were fabricated using copper via metal fused filament fabrication (FFF) and PLA via polymer FFF, with piezoelectric transducers (PZTs) inserted into internal cavities to assess the influence of material and placement on sensing fidelity. Mechanical testing under compressive and point loads generated signals that were transformed into time–frequency spectrograms using a Short-Time Fourier Transform (STFT) framework. An engineered RGB representation was developed, combining global amplitude scaling with an amplitude-envelope encoding to enhance contrast and highlight subtle wave features. These spectrograms served as inputs to convolutional neural networks (CNNs) for classification of load conditions and detection of damage-related features. Results showed reliable recognition in both copper and PLA specimens, with CNN classification accuracies exceeding 95%. Embedded PZTs were especially effective in PLA, where signal damping and environmental sensitivity often hinder surface-mounted sensors. This work demonstrates the advantages of embedded sensing in AM structures, particularly when paired with spectrogram-based feature engineering and CNN modeling, advancing real-time SHM for aerospace, energy, and defense applications.

additive manufacturing↗
DOE OSTI2021

Small footprint optoelectrodes using ring resonators for passive light localization

The combination of electrophysiology and optogenetics enables the exploration of how the brain operates down to a single neuron and its network activity. Neural probes are in vivo invasive devices that integrate sensors and stimulation sites to record and manipulate neuronal activity with high spatiotemporal resolution. State-of-the-art probes are limited by tradeoffs involving their lateral dimension, number of sensors, and ability to access independent stimulation sites. Here, we realize a highly scalable probe that features three-dimensional integration of small-footprint arrays of sensors and nanophotonic circuits to scale the density of sensors per cross-section by one order of magnitude with respect to state-of-the-art devices. For the first time, we overcome the spatial limit of the nanophotonic circuit by coupling only one waveguide to numerous optical ring resonators as passive nanophotonic switches. With this strategy, we achieve accurate on-demand light localization while avoiding spatially demanding bundles of waveguides and demonstrate the feasibility with a proof-of-concept device and its scalability towards high-resolution and low-damage neural optoelectrodes.

42 ENGINEERING↗
DOE OSTI2021

The Influence of Communication on the Complexity of Connected Lighting Systems

Experience in the Next Generation Lighting Systems (NGLS) ”Living Lab” at the Parsons School of Design, has clearly shown the impacts of communication on the configuration complexity of the connected lighting systems installed there. Since 2017, NGLS has invited manufacturers to submit connected lighting systems for assessment against a set of specifications. To date, 14 systems of wirelessly connected LED luminaires and controls have been installed in classrooms with existing lighting. In nine of the rooms, new LED linear pendants or recessed troffers replaced existing luminaires; in the other rooms, LED “kits” were retrofitted into the existing troffers. Eleven of the installations featured sensors integrated in the luminaires or retrofit kits; the others used ceiling mounted sensors. All systems provided wall control devices for manual operation. For half of the installations, the complete systems were furnished by single companies; for the other half, luminaires and controls were furnished by separate companies. A total of 18 different companies provided products, with four of these located outside the United States including, Korea, Poland, Germany, and the Netherlands. In addition, two different electrical contractors in New York City provided multiple installation teams totaling 10 individuals, none of whom were familiar with any of the systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗