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At least 307 records · Page 17

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DOE OSTI2025

High-Speed and High-Quality Field Welding Repair Based on Advanced Non-Destructive Evaluation and Numerical Modeling

Creep strength-enhanced ferritic (CSEF) steels such as Grade 91 (9Cr-1Mo-V) and Grade 92 (Fe-9Cr-2W-0.5Mo) steels are widely used in the fossil-fuel-fired and nuclear power plants. The weld integrity of these steels is crucial for power plants' safe and reliable operations. Due to harsh service conditions, the steel weld can become susceptible to environmental degradation. Field welding repair is used to restore the degraded weld’s performance where a controlled temper-bead welding technique is commonly used to temper the freshly formed martensite during welding. However, knowledge of weld repairability is limited and experimental trial and error optimization to achieve desired microstructure and joint properties is expensive and time-consuming. Many existing computational models, e.g., finite element models, are limited to solving heat conduction equation and ignoring convective heat transfer due to molten metal flow. These models can result in over-prediction of peak temperatures of weld pool and heat-affected zone (HAZ), which in turn can affect the accuracy of tempering prediction. Moreover, these finite element models require an input of the deposit profiles in advance and thus limits the usability of these models. Here, a molten pool-based, multi-pass multi-layer model has been developed based on computational fluid dynamics (CFD) approach with the Volume of Fluid (VOF) method. The model calculates the bead formation, thereby eliminating the need for pre-determined bead profiles required by finite element models. For computational efficiency, a coordinate system attached to the moving heat source is utilized. A subroutine is developed to convert the temperature profiles in the reference frame stationary to the heat source to that stationary to the workpiece. The converted thermal cycles are then imported into a microstructure model to compute the tempering kinetics and resultant hardness using a Johnson-Mehl-Avrami-Kolmogorov (JMAK), and modified Grange-Baughman parameter. The modeling approach is first developed and validated on single- and multi-pass deposition of stainless steel filler metal onto a SA-533 high strength steel substrate. The models are then applied to a multi-pass V-groove repair weld of Grade 91 steel plate as well as directed energy deposition of Grade 92 steel. Non-destructive characterization of microstructures was performed on Grade 91 and 92 steel welds. Two welding processes, cold metal transfer (CMT) and flux-cored arc welding (FCAW), were investigated for the Grade 91 steel weld samples. For the Grade 92 weld samples, three different heat inputs (low, medium, and high) of gas tungsten arc welding (GTAW) were utilized to replicate traditional field welding processes. The non-destructive evaluation (NDE) method used for this research was immersion ultrasonic testing (UT) using a micro-resolution ultrasonic imaging methodology specifically designed to operate in the through-transmission configuration operating at 20 MHz of frequency. The system used a focused ultrasonic beam spot size diameter between 250-300 μm, and a 6 μm laser vibrometer spot size for detection, to produce highly defined images with longitudinal and mode-converted shear waves. From the micro-resolution ultrasonic C-scan images, three microstructural regions, i.e., weld metal (WM), HAZ, and base metal (BM), were clearly identifiable. Various levels of ultrasonic amplitudes distributed over the three regions were correlated with electron beam backscattered diffraction (EBSD) images using grain size, grain boundaries, and dislocation densities. The results showed that areas with relatively higher ultrasonic amplitude levels were associated with smaller grains and higher dislocation densities, while areas with lower amplitude levels were associated with larger grains and lower dislocation densities. In addition, ultrasonic velocity data obtained across the three different weld microstructural regions of Grade 91 test samples were correlated with optical metallographic images and hardness measurements. The results showed distinctive decreases in ultrasonic velocity and hardness over the HAZ region, where weld failures often occur during service.

36 MATERIALS SCIENCE↗

NASA NTRS2008

Technical Aspects of the Space Telescope Imaging Spectrograph Repair (STIS-R)

In August 2004, the Hubble Space Telescope (HST) Space Telescope Imaging Spectrograph (STIS) ceased operation, due to a failure in the Side 2 Low Voltage Power Supply (LVPS2). The LVPS2 provided power to the entire instrument, including all detectors and mechanisms. The failure precluded movement of any STIS mechanism, leaving the instrument fully shuttered. The fault analysis team concluded that by replacing a board containing a new LVPS2 power supply, STIS could be brought back to full functionality. During Servicing Mission 4 (SM4), STIS-R will replace this board. STIS-R will restore full function of the instrument with one of the two redundant sides of the instrument.

Rinehart, Stephen A.↗

NASA NTRS2002

Restoring Redundancy to the MAP Propulsion System

The Microwave Anisotropy Probe (MAP) is a follow-on to the Differential Microwave Radiometer (DMR) instrument on the Cosmic Background Explorer (COBE). Due to the MAP project's limited mass, power, and financial resources, a traditional reliability concept including fully redundant components was not feasible. The MAP design employs selective hardware redundancy, along with backup software modes and algorithms, to improve the odds of mission success. In particular, MAP's propulsion system, which is used for orbit maneuvers and momentum management, uses eight thrusters positioned and oriented in such a way that its thruster-based attitude control modes can maintain three-axis attitude control in the event of the failure of any one thruster.

O'Donnell, James R., Jr.↗

DOE OSTI2026

Safe Deep Reinforcement Learning for Robust Frequency and Voltage-Constrained Networked Microgrid Restoration

Here, this paper proposes a safe soft actor-critic reinforcement learning (RL) algorithm–based controller for networked microgrid restoration. It formulates the post black-start start as a finite-horizon constrained Markov decision process. The RL agent co-optimizes real and reactive power set-points for both grid-forming and grid-following inverters under explicit voltage and frequency constraints, while enforcing proper power sharing via the Mean Active Power Sharing Index (MPSI) and Mean Reactive Power Sharing Index (MQSI). Numerical results obtained on the IEEE 123-bus distribution system show that the proposed method achieves a mean voltage build-up time of 0.01 s without breaching the 5% sharing-violation budget under various load scenarios, considering MPSI and MQSI indices. These findings demonstrate that the proposed method yields fast and safe black-start schedules without resorting to heuristic penalties.

Selim, Alaa [Dartmouth College, Hanover, NH (Unite↗

DOE OSTI2025

Recyclable Design for Retaining High Solar Absorptivity of the Media in CSP

Efficient thermal energy storage is pivotal to lowering the levelized cost of electricity (LCOE) for Concentrating Solar Power (CSP) plants. In solid-particle systems, however, prolonged high-temperature service degrades particle solar absorptivity, eroding overall efficiency. This project demonstrates a hydrogen-assisted recovery process that reliably restores absorptivity to >90 %, offering a practical route to sustain long-term CSP performance. Bench-scale investigations mapped the reduction kinetics of optically faded particles across hydrogen concentrations, temperatures, and residence times. Coupling mass-spectrometric monitoring with machine-learning optimization minimized energy demand while maximizing absorptivity gain. The resulting process window—moderate hydrogen partial pressures, 15–30 min dwell times, and temperatures well below initial calcination levels—cuts energy consumption well below that of incumbent re-blackening methods. A prototype recovery reactor processed multiple 2 kg batches with repeatable outcomes, confirming scalability and operational robustness. Integrated techno-economic analysis indicates material and operating cost reductions exceeding 15 % relative to conventional particle replacement or chemical re-coating, translating directly into lower LCOE for next-generation CSP facilities. By uniting fundamental reaction-kinetics insight with pragmatic engineering, this work advances the solid-particle pathway, delivering a cost-effective, field-deployable solution to one of CSP’s key durability challenges and strengthening the commercial outlook for high-temperature renewable power.

14 SOLAR ENERGY↗

DOE OSTI2026

Conserving asphalt resources: Rethinking rejuvenator performance evaluation through peptizing efficiency

Timely rejuvenation and restoration of asphalt are essential conservation practices that help preserve and extend the service life of roads, bridges, driveways, and parking lots. The performance of asphalt rejuvenators is often assessed based on their diffusion rates and softening power, yet these metrics alone fail to capture true rejuvenation potential. Here, this study integrates density functional theory (DFT) modeling with experimental analysis to show that rejuvenation effectiveness is primarily governed by molecular interactions with oxidized asphaltene nanoaggregates. DFT results revealed that amide- and unsaturated-chain compounds, such as hexadecanamide, oleic acid, and 9,17-octadecadienal, act cooperatively to disrupt π–π stacking and exfoliate asphaltene layers, reducing binding strength and enhancing dispersion. Unlike bulky, rigid molecules that remain trapped, these components remain mobile and repeatedly interact with multiple aggregation sites. Experimental validation using rheometry and FTIR confirmed that such molecularly compatible rejuvenators restore the binder flexibility and polydispersity, even when diffusion is relatively slow. Building on this mechanistic foundation, six rejuvenators (A2, A5, A7, A8, A9, and A10) were evaluated using a three-metric performance framework encompassing cracking resistance (Glover–Rowe parameter), UV stability, and surface hydrophobicity. Among the six rejuvenators evaluated, A9 exhibited the highest overall performance, reducing the Glover–Rowe cracking parameter by 85% (from 351 kPa to 53 kPa), demonstrating the greatest resistance to UV-induced aging with a stability index of 4.17 h·kPa⁻¹, and increasing surface hydrophobicity to a contact angle of 103.6°. Its superior performance is primarily attributed to its amide- and unsaturated-chain components, which act cooperatively to disrupt π–π stacking interactions and exfoliate asphaltene layers, thereby promoting molecular deagglomeration and enhancing long-term durability. These results shift the criteria for selecting rejuvenators: effective candidates must pair the electronic capability to unlock aged asphaltenes with sufficient structural stability to resist secondary aging and restore hydrophobicity. Restoring hydrophobicity is critical, as aging reduces the asphalt’s water repellency and increases water diffusion, which in turn accelerates moisture-related damage; consequently, a high-performing rejuvenator must effectively restore the binder’s hydrophobic characteristic. Collectively, these findings provide a framework for the rational design of next-generation of bio-based rejuvenators that enhance pavement longevity and promote long-term sustainability.

Aging↗

DOE OSTI2023

Storm-DEPART (Damage Estimate Prediction and Recovery Tool)

Storm-DEPART (Damage Estimate Prediction and Restoration Tool): Each year hurricanes and tropical storms in the United States damage critical infrastructure assets, disrupt the services they provide, and cause millions to billions of dollars in economic impacts due to extended recovery times. The Storm-DEPART tool and analytical output enable more impactful data-driven decision-making capabilities and strengthen national-level disaster preparedness, response, and recovery. Storm-DEPART, built through multi-month collaboration between Entergy and INL, combines Entergy’s critical infrastructure inventory data with weather forecasts to predict damages to Electric utility’s assets due to natural disasters and the estimated recovery support needed, including time, materials, and resource allocation. In the event of an approaching hurricane, this innovative solution can assess potential damage to power generation capacity, transmission grids, distribution networks, and communications assets from wind bands, storm surge, and flooding. With more effective predictions, Entergy can more efficiently allocate resources to mitigate impacts and optimize recovery for customers. Storm-DEPART also allows Electric utilities the ability to apply a planning scenario and model expected damage to better inform infrastructure restoration needs leading to enhance system resiliency. The technology is fully transferrable to other electric utilities with the same damage estimating challenges. The INL team is working on the evolution of Storm-DEPART to include ice event damage prediction framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Post-extreme-event restoration using linear topological constraints and DER scheduling to enhance distribution system resilience

In this paper, a post-extreme-event restoration (PEER) algorithm is proposed to improve distribution system resilience. Linear topological constraints are proposed to ensure radial topology after N-k contingencies, possibly in multiple islands. The approach is made comprehensive by considering dispatchable distributed energy resources (DERs), non-dispatchable DERs, and demand responses, as well as on-load tap changers (OLTCs) and shunt capacitors. The goal is to minimize the accumulative expense caused by load reduction payment or penalty, as well as DER operation cost. As a result, the overall system will survive longer with higher resilience during an extreme event. To verify the effectiveness of the PEER algorithm, we proposed a resilience evaluation algorithm using Monte Carlo simulation (MCS) with reduced scenarios. This is based on a probabilistic model for generating random scenarios which consider the uncertainty of line faults and solar irradiance. Combined with the proposed PEER algorithm, this reduced-scenario MCS can evaluate the expected energy not served (EENS) which is an essential index for distribution system resilience. Case studies of the IEEE 33-bus and 123-bus test systems validate the proposed algorithm in reducing EENS.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Post-Disaster Microgrid Formation for Enhanced Distribution System Resilience

This paper proposes a deep reinforcement learning (DRL) based approach for post-disaster critical load restoration in active distribution systems to form microgrids through network reconfiguration to minimize critical load curtailments. Distribution networks are represented as graph networks, and optimal network configurations with microgrids are obtained by searching for the optimal spanning forest. The constraints to the research question being explored are the radial topology and power balance. Unlike existing analytical and population-based approaches, which necessitate the repetition of entire analyses and computation for each outage scenario to find the optimal spanning forest, the proposed approach, once properly trained, can quickly determine the optimal, or near-optimal, spanning forest even when outage scenarios change. When multiple lines fail in the system, the proposed approach forms microgrids with distributed energy resources in active distribution systems to reduce critical load curtailment. The proposed DRL-based model learns the action-value function using the REINFORCE algorithm, which is a model-free reinforcement learning technique based on stochastic policy gradients. A case study was conducted on a 33-node distribution test system, demonstrating the effectiveness of the proposed approach for post-disaster critical load restoration.

active distribution systems↗

DOE OSTI2023

Storm-DEPART (Damage Estimate Prediction and Recovery Tool)

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2005

Rehabilitation of the Rocket Vehicle Integration Test Stand at Edwards Air Force Base

Since initial use in 1958 for the X-15 rocket-powered research airplane, the Rocket Engine Test Facility has proven essential for testing and servicing rocket-powered vehicles at Edwards Air Force Base. For almost two decades, several successful flight-test programs utilized the capability of this facility. The Department of Defense has recently demonstrated a renewed interest in propulsion technology development with the establishment of the National Aerospace Initiative. More recently, the National Aeronautics and Space Administration is undergoing a transformation to realign the organization, focusing on the Vision for Space Exploration. These initiatives provide a clear indication that a very capable ground-test stand at Edwards Air Force Base will be beneficial to support the testing of future access-to-space vehicles. To meet the demand of full integration testing of rocket-powered vehicles, the NASA Dryden Flight Research Center, the Air Force Flight Test Center, and the Air Force Research Laboratory have combined their resources in an effort to restore and upgrade the original X-15 Rocket Engine Test Facility to become the new Rocket Vehicle Integration Test Stand. This report describes the history of the X-15 Rocket Engine Test Facility, discusses the current status of the facility, and summarizes recent efforts to rehabilitate the facility to support potential access-to-space flight-test programs. A summary of the capabilities of the facility is presented and other important issues are discussed.

Jones, Daniel S.↗

DOE OSTI2025

Energy Justice Through Energy Storage: Supporting Energy Resilience in Disadvantaged Communities

This paper reviews energy storage technologies as a possible solution to address power outages and mitigate the impacts, enhancing vulnerable communities’ resilience to climate change. More frequent and severe extreme weather events are one of the main consequences of climate change. These events, coupled with the nation’s aging and frail energy infrastructure, are causing many communities throughout the United States to experience more frequent and longer power outages, resulting in economic, health, and social impacts. Impacts from power outages are not equally felt across communities, with disproportionate impacts across communities representing a matter of energy justice. From an energy justice standpoint, programs and policies that facilitate energy storage technologies should be intentionally designed to include distributive, procedural, recognition, and restorative justice.

25 ENERGY STORAGE↗

DOE OSTI2021

Resilience-Motivated Distribution System Restoration Considering Electricity-Water-Gas Interdependency

A major outage in the electricity distribution system may affect the operation of water and natural gas supply systems, leading to an interruption of multiple services to critical customers. Therefore, enhancing resilience of critical infrastructures requires joint efforts of multiple sectors. In this paper, a distribution system service restoration method considering the electricity-water-gas interdependency is proposed. The objective is maximizing the supply of electricity, water, and gas to critical customers after an extreme event. The operational constraints of electricity, water, and natural gas networks are considered. Additionally, the characteristics of electricity-driven coupling components, including water pumps and gas compressors, are also modeled. Relaxation techniques are applied to non convex constraints posed by physical laws of those networks. Consequently, the restoration problem is formulated as a mixed-integer second-order cone program, which can readily be solved by the off-the-shelf solvers. The proposed method is validated by numerical simulations on an electricity-water-gas integrated system, developed based on benchmark models of the subsystems. The results indicate that considering the interdependency refines the allocation of limited generation resources and demonstrate the exactness of the proposed convex relaxation

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Adaptive Deep Reinforcement Learning Algorithm for Distribution System Cyber Attack Defense With High Penetration of DERs

With grid modernization, smart inverters are increasingly used to execute advanced controls for distribution network reliability. However, this also increases the cyber-attack space. Here this paper focuses on the defense approaches to restore the system to normal operation circumstances in the presence of cyber-attacks. A unique deep reinforcement learning (DRL) method is developed to minimize voltage violations and reduce power losses for impacted feeders. The defense problem is reformulated as a Markov decision-making process to dynamically control DERs while minimizing load shedding. This is achieved via an improved soft actor-critic (SAC)-based DRL algorithm, which can govern DER set points and load-shedding scenarios in discrete and continuous modes via the auto-tune entropy and Gaussian policy features. Numerical comparison results on the modified IEEE 123-node system with other control approaches, such as Volt-VAR (VV), Volt-Watt (VW), and model predictive control (MPC) show that the proposed method can eliminate voltage violations and provide feasible control actions that perform complete mitigation of cyber-threats.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1981

SMM attitude control recovery

A description is given of the way in which the Modular Attitude Control System (MACS) onboard computer of the NASA Solar Maximum Mission (SMM) laboratory was reprogrammed, to restore attitude control for the SMM, after fuse failures permanently disabled all three of the MACS primary reaction wheels. Algorithms were developed which provided both a thermal- and power-safe, spin-stabilized mode and three-axis sun pointing, using the damaged primary wheels' backup skew wheel in a momentum-bias control scheme. Magnetic torquing was used in these algorithms for angular momentum vector magnitude and directional control.

Hoffman, H. C.↗

NASA NTRS1987

An integrated approach to space station power system autonomous control

Space Station electrical power management must be accomplished autonomously in order to decrease both airborne and ground support costs. Attention is presently given to the augmentation of terrestrial utility algorithmic decision aids for power dispatching for space station use, using expert systems to direct power demand analyses and the integration of results into operational decisions. Functions to be thus managed encompass power scheduling, energy allocation, failure cause diagnoses, goal proposal and plan preparation, consequence evaluation, and execution plan selection. The operating states of the system are normal, preventive, emergency, and restorative.

Dolce, James L.↗

DOE OSTI2025

Microgrid Black Start Challenges: The Role of Grid-Forming Inverters

Grid-forming (GFM) inverters are becoming increasingly important for future power systems, particularly in establishing and restarting microgrids after blackouts. The use of GFM inverters enables microgrids to operate independently of utility power and provide key advantages over synchronous generators in black start scenarios, including rapid startup and stable voltage and frequency support for critical loads. However, inverter-driven black start introduces unique challenges and operational considerations. This article examines key challenges and solutions, emphasizing inverter design, control strategies, and microgrid system requirements. Drawing on analysis, simulation, and experimental results, this article highlights the central role of GFM inverters in ensuring reliable and resilient microgrid operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1996

Fault Diagnosis of Power Systems Using Intelligent Systems

The power system operator's need for a reliable power delivery system calls for a real-time or near-real-time Al-based fault diagnosis tool. Such a tool will allow NASA ground controllers to re-establish a normal or near-normal degraded operating state of the EPS (a DC power system) for Space Station Alpha by isolating the faulted branches and loads of the system. And after isolation, re-energizing those branches and loads that have been found not to have any faults in them. A proposed solution involves using the Fault Diagnosis Intelligent System (FDIS) to perform near-real time fault diagnosis of Alpha's EPS by downloading power transient telemetry at fault-time from onboard data loggers. The FDIS uses an ANN clustering algorithm augmented with a wavelet transform feature extractor. This combination enables this system to perform pattern recognition of the power transient signatures to diagnose the fault type and its location down to the orbital replaceable unit. FDIS has been tested using a simulation of the LeRC Testbed Space Station Freedom configuration including the topology from the DDCU's to the electrical loads attached to the TPDU's. FDIS will work in conjunction with the Power Management Load Scheduler to determine what the state of the system was at the time of the fault condition. This information is used to activate the appropriate diagnostic section, and to refine if necessary the solution obtained. In the latter case, if the FDIS reports back that it is equally likely that the faulty device as 'start tracker #1' and 'time generation unit,' then based on a priori knowledge of the system's state, the refined solution would be 'star tracker #1' located in cabinet ITAS2. It is concluded from the present studies that artificial intelligence diagnostic abilities are improved with the addition of the wavelet transform, and that when such a system such as FDIS is coupled to the Power Management Load Scheduler, a faulty device can be located and isolated from the rest of the system. The benefit of these studies provides NASA with the ability to quickly restore the operating status of a space station from a critical state to a safe degraded mode, thereby saving costs in experimentation rescheduling, fault diagnostics, and prevention of loss-of-life.

Momoh, James A.↗