Search NASA⌕ Search

SEARCH · Search NASA

Results for “Testing and Performance”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Demonstration of Electroreduction Technology to Convert GNF Uranium Oxide Powder to Metal

Global Nuclear Fuel – Americas LLC (GNF) has partnered with Argonne National Laboratory to demonstrate electroreduction of uranium oxides produced by deconversion of UF 6 to uranium metal through the Gateway for Accelerated Innovation in Nuclear (GAIN) program under the U.S. Department of Energy to accelerate the domestic production of metallic advanced reactor fuels. Electroreduction of uranium oxide was first demonstrated and patented by Argonne in the early 2000s as a technology to convert used oxide nuclear fuel from light water reactors to metal for further fuel reprocessing. More recently, electroreduction has been proposed as a front-end technology for metallization of uranium oxides produced by deconversion of UF 6 and for scrap recovery of oxide materials. During the electroreduction process, UO 2 powder is contained in a stainless-steel mesh basket with a cathode lead located in the center of the UO 2 bed. The basket is immersed in lithium chloride molten salt electrolyte containing 1 wt% lithium oxide along with a platinum anode and a nickel/nickel oxide (Ni/NiO) reference electrode. Current is applied to the cell between the cathode and anode to reduce the UO 2 to metallic uranium via a solid-state reduction reaction. Oxide ions released from the UO 2 during reduction are transported through the salt to the anode where oxygen gas is evolved. Once reduction is complete, the basket containing the metallicized uranium is removed from the salt and can be processed to remove the salt and consolidate the uranium into an ingot for use in metallic fuel fabrication. This project was performed to provide evidence of the electroreduction technology readiness level for metallization of UO 2 powder, identify and retire technical risks for industrialization of electroreduction, and accelerate the path to commercialization for metallic fast reactor fuel production. To that end, five electroreduction tests were performed with UO 2 provided by GNF and the resulting product was analyzed for the extent of conversion to metal and for impurity contents of the metal product to verify that electroreduction does not introduce impurities that would prevent use of the product in metallic fuel fabrication.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Uniaxial compressive creep tests by spark plasma sintering of 70% theoretical density α -uranium and U-10Zr

Metallic fuels hold numerous advantages over conventional uranium dioxide fuels and are a key component of several liquid metal-cooled advanced reactor concepts including sodium fast reactors. These fuels undergo rapid swelling during early burnup; consequently, they spend most of their reactor lifetime in a porous state. The presence of this porosity alters many of the mechanical properties of the fuel including creep impacting fuel deformation during axial swelling. This work investigates the creep behavior of the porous fuel using a spark plasma sintering technique. Creep tests were performed for the first time on porous α-phase uranium and uranium with 10 wt. % zirconium (U-10Zr) samples. The samples of α-phase uranium and U-10Zr were fabricated from depleted uranium by spark plasma sintering and subjected to uniaxial compressive creep testing. Calculated stress exponents were found to be 2.6±1.6 and 5.7±1.4 for α-U and U-10Zr, respectively, and calculated activation energies were found to be 61.6±1.1kJ/mol for α-U. The creep data were also used to evaluate existing porosity inclusive in creep models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Dispersal of high-burnup fuel fragment surrogate particles during and after loss-of-coolant accident tests

The issue of fuel fragmentation, relocation, and dispersal is critical in the licensing and use of high-burnup (>62 GWd/MTU) nuclear fuel in light water reactors (LWRs). In this work, two test series are reported that examine the fragment dispersal during a burst event and an additional dispersal following the burst due to vibrations in the rod, such as those induced by accident recovery systems. To examine dispersal during the balloon and burst portion of a Loss-of-Coolant Accident event, HfO 2 fragments and yttria-stabilized zirconia pellets were filled into an as-fabricated cladding tube, which was then pressurized and subjected to loss-of-coolant accident testing in steam. Results from this test were found to be highly non-prototypic, and dispersal was both significantly more violent and significantly greater in magnitude than identified for actual fuel tests. These findings were attributed to the conservative (more dispersive) nature of the particles chosen for dispersal and to the details of the test conditions used that led to particularly wide bursts. Further, the second set of tests examined dispersal following the burst when vibrations were induced in the rod, primarily via recovery activities such as Emergency Core Cooling System actuation leading to rapid water addition. Post-burst dispersal testing was performed by inducing sinusoidal oscillations with 2–25 nm peak-to-peak amplitude and 2–5 Hz frequencies in pre-burst rods that had been refilled with HfO 2 fragments or high-burnup fragment surrogate mixture of HfO 2 fragments and yttria-stabilized zirconia sands. Testing revealed that rods with large burst openings (7 mm wide in this work) led to unmitigated dispersal from above the burst zone but that smaller bursts (5 mm wide), although still much larger than the mean fragment size of 3 mm, led to effectively no dispersal because of interparticle locking. Additionally, mixture and moisture were found to impact the amount of dispersal: mixtures increased dispersal, and moisture drastically reduced it. The implications of these findings on likely dispersal from actual fuel are discussed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Removal of Antibiotics from Swine Wastewater Using an Environmentally Friendly Biochar: Performance and Mechanisms

Antibiotics used in the swine industry to treat diseases and improve animal growth are poorly absorbed by swine and have been classified as micropollutants due to their occurrence in surface water, wastewater, and soil. This study investigated the capacity of biochar produced from eastern red cedar to remove target antibiotics that have been extensively used in the swine industry. Biochar was produced by pyrolysis from eastern red cedar at 450 °C. The sorption tests were performed by mixing biochar and a solution (1:10 ratio) containing each antibiotic in 100, 300, 600, and 900 μg L –1 concentrations. The results indicate that red cedar biochar was able to effectively remove up to 99.93% tetracycline, 96.23% oxytetracycline, 98.28% chlortetracycline, 76.4% sulfadiazine, and 78.6% sulfamethazine at the lowest concentrations. The removal efficiencies at higher concentrations declined up to 83.52, 47.23, 64.16, 69.8, and 58.4% for tetracycline, oxytetracycline, chlortetracycline, sulfadiazine, and sulfamethazine, respectively. The biochar exhibited stronger adsorption capacity for chlortetracycline and sulfamethazine compared to the other antibiotics. The likely adsorption mechanisms driving the removal of tetracyclines and sulfonamides are hydrogen-bonding and π–π electron-donor–acceptor, supported by FTIR analyses of the biochar itself. Overall, the results highlighted the potential utilization of eastern red cedar biochar for practical applications, mitigating antibiotic residues from swine wastewater in a cost-effective and environmentally friendly manner due to its relatively low pyrolysis temperature (450 °C) and sustainable repurposing of an invasive tree species.

09 BIOMASS FUELS↗
DOE OSTI2025

Operation of Argonne's Liquid Salt-Liquid Metal Separation Testbed for U/TRU Product Processing

Argonne National Laboratory has constructed a liquid salt-liquid metal separation testbed for use in the development and advancement of cathode processing of U/TRU co‑deposits generated by pyroprocessing of used nuclear fuel. The U/TRU product recovered from the electrorefiner contains adhered and entrained salt that must be removed prior to consolidation of the U/TRU alloy for use in advanced reactor fuel fabrication. The bottom pour operation utilizes the low melting points of U/TRU co‑deposits and higher densities of molten metals compared to molten salts to separate and consolidate the U/TRU product. Argonne’s testbed is designed to support the development and optimization of bottom-pouring configurations for batch and semi-continuous operations, integration of process monitoring and control technologies, and determination of operational requirements for implementing in an industrial setting. Scoping tests were performed to demonstrate operational aspects of the testbed, including operation using single-pour spout and dual-pour spout configurations, effectiveness of salt containment and extent of salt vaporization, and the use of sensor probes to detect the location of the interface between the metal and salt phases during pouring. Recommendations for process optimization testing for further development of bottom pour processing to separate U/TRU alloys from adhered salt were made based on the results of scoping tests. Completing the recommended activities will increase the technical readiness level (TRL) of the liquid salt-liquid metal separation operation and consolidation of U/TRU alloys to support industrialization of pyroprocessing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

CABLE Stage 3 – Ultra‐High Strength/Highly Conductive Al Alloys

This work is to be conducted in support of the CABLE Conductor Manufacturing Prize Program awarded by NREL. The intent is to connect competitor teams with national laboratories that can help accelerate the development of innovative solutions and products. Teams who receive CABLE Prize awards are eligible to utilize vouchers at national laboratories to advance their ideas. NanoAL LLC has been awarded a voucher to utilize at Ames National Laboratory. Ames National Laboratory will perform a scale‐up trial of Nano 6000‐T9 to evaluate and optimize the heat treatment and other processing variables to validate the lab‐scale work done at NanoAL. The final processing schedule will be used to fabricate the submission samples for the Stage 3 contest. All work will be supported by mechanical and electrical conductivity testing be performed by Ames.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Initial Testing of an In Situ Load Retention Aging Vessel

A thermal aging vessel instrumented with load cells was fabricated. The primary function of the vessel is to continuously monitor the in situ load retention of up to three compressed polymer coupons undergoing thermally accelerated aging under nitrogen. A secondary function is to enable gas sampling of the vessel headspace during thermal aging. Heating of the vessel is achieved using a custom heater jacket. To improve upon our conventional aging study methods which require periodic interruption of aging to perform load testing in an Instron machine at room temperature, this technology aims to automate/facilitate data acquisition/analysis, improve data quality, and enable uninterrupted compression of the polymer which represents the service condition. As an example case to assess functionality of the in situ vessel, the load retention of a siloxane elastomer material additively manufactured by direct-ink-writing (DIW) was measured at three different isothermal aging temperatures for ~1 month. Initial compression of the coupons while near the aging temperature was achieved by temporarily opening the heated vessel to access the interior chamber and manually tightening four nuts to drive the heated compression plate down onto the heated coupons. Initial testing demonstrated achievement of the primary load retention monitoring function. Unfortunately, the vessel leaked which prevented gas sampling; an active purge was used to maintain a nitrogen atmosphere. Welded or otherwise sealed joints, which could be implemented in a future design, would likely eliminate leak paths. To apply time-temperature superposition (TTS), a technique used to provide long-term prediction of the load retention from short-term isothermal data, the load retention needed to be calculated relative to the load at an estimated “equilibrium” time, after most of the transient viscoelastic physical relaxation occurred. The peak load immediately after compression could not be used as the load retention basis for two reasons: (1) age-related changes must be isolated from non-age-related physical relaxation before applying TTS and (2) the manual mechanism used to compress the specimens at the aging temperature was neither smooth nor repeatable which affected the peak load value. To better understand the effect of the mode of initial compression on the measured load, and possibly better estimate “equilibrium” physical relaxation times, systematic stress relaxation experiments were performed using an Instron machine with a thermal chamber. At a given temperature, the DIW polymer was compressed to a fixed strain in either a stepped or continuous manner at two different rates, then held at that strain for 24 hrs. The results indicated that, at a given temperature, the different stress relaxation curves appeared to converge to the same curve at some “equilibrium” time when the non-age-related physical relaxation was mostly complete. Though this observation suggests that the discontinuous manual compression employed by the vessel is feasible, a compression mechanism that is rapid, smooth, and repeatable would enhance its use.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Machine learning framework for predicting uranium enrichments from M400 CZT gamma spectra

A machine learning framework was developed for predicting uranium enrichments from M400 CZT gamma spectra. This framework leverages the availability of a large amount of measured M400 gamma spectra and uses a recently updated version of Gamma Detector Response and Analysis Software (GADRAS) for gamma spectrum analysis and generation. It also leverages the existing machine learning modules in Python for gamma spectrum data processing, curation, model training, benchmarking, and optimization of the deep machine learning models. The framework is used to develop a deep learning model to analyze gamma spectra from a set of U 3 O 8 samples with enrichments ranging from 0.31 to 93.17% and UF 6 cylinders with enrichments ranging from 0.2 to 4.95%, and the model performance is tested using a set of measured spectra and the respective declared enrichment values. Results show that the model can correctly classify 99.35% of the U 3 O 8 sample enrichments, and can predict the samples’ enrichments within an average absolute error of 0.099% (in percentage points of enrichment). For the UF 6 cylinders, the average absolute error was approximately 0.03%, with an accuracy of 98% in classifying discrete enrichment values of UF 6 samples. Finally, the results also show that the model has performed significantly better in terms of predicting enrichments in UF 6 cylinders based on measured gamma spectra than the GEM code, with a standard deviation (of the relative errors) of 2.23% (compared with the 11.51% value for the GEM code) based on results from a set of test data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

A meshing framework for digital twins for extrusion based additive manufacturing

Additive manufacturing (AM) allows for manufacturing of complex three-dimensional geometries not typically realizable with standard manufacturing practices. The internal microstructure of AM components has a significant impact on mechanical, vibrational, and shock properties and permits richer design space when this is controllable. Due to complex interactions of internal geometry of an extrusion-based AM component, it is common practice to assume homogeneous behavior or to perform characterization testing on specific toolpath configurations. To avoid testing or material waste, it is necessary to develop a consistently accurate numerical simulation framework with relevant boundary value problems that can handle the complicated geometry of internal material microstructure present in AM components. Herein, a framework is proposed to directly create computational meshes suitable for finite element analysis (FEA) of the fine-scale features generated from extrusion-based AM tool paths to maintain a strong process–structure–property-performance linkage. This mesh can be manually or automatically analyzed using standard FEA simulations such as quasi-static preloading or modal analysis. The framework allows an in-silico assessment of a target AM geometry where fine-scale features greatly impact quantities of design interest such as in soft elastomeric lattices where toolpath infill can greatly influence the self-contact of a structure in compression, which we use as a motivating exemplar. This approach greatly reduces both time and resource waste present in traditional build and test design cycles for non-intuitive design spaces, and acts as a tool for use in the production of a key component of a digital twin, a mesh suitable for finite element analysis. In conclusion, it also further allows for the exploration of toolpath infill to optimize component properties beyond simple linear properties such as density and stiffness.

Additive manufacturing↗
DOE OSTI2024

GAINN: The Galaxy Assembly and Interaction Neural Networks for High-redshift JWST Observations

We present the Galaxy Assembly and Interaction Neural Networks (Gainn), a series of artificial neural networks for predicting the redshift, stellar mass, halo mass, and mass-weighted age of simulated galaxies based on James Webb Space Telescope (JWST) photometry. Our goal is to determine the best neural network for predicting these variables at 11 < z < 15. The parameters of the optimal neural network can then be used to estimate these variables for real, observed galaxies. The inputs of the neural networks are JWST filter magnitudes of a subset of five broadband filters (F150W, F200W, F277W, F356W, and F444W) and two medium-band filters (F162M and F182M). We compare the performance of the neural networks using different combinations of these filters, as well as different activation functions and numbers of layers. The best neural network predicted redshift with a normalized rms error of $0.010^{+0.003}_{-0.001}$, stellar mass with rms = $0.089^{+0.044}_{-0.022}$, halo mass with a mean-squared error of $0.022^{+0.014}_{-0.008}$, and mass-weighted age with rms = $12.466^{+5.065}_{-2.408}$. We also test the performance of Gainn on real data from MACS0647JD, an object observed by JWST. Predictions from Gainn for the first projection of the object (JD1) have normalized bias $\langle$Δz$\rangle$ < 0.00228, which is significantly smaller than found with template-fitting methods. We find that the optimal filter combination is F277W, F356W, F162M, and F200W when considering both theoretical accuracy and observational resources from JWST.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Testing and Analysis of Grid Forming Inverter Control for Achieving Resilient and Economic Operation of an Islanded Microgrid

This investigation examines the feasibility of operating a battery energy storage system (BESS) in parallel with synchronous generation by using grid forming (GFM) control in order to achieve frequency control objectives while mitigating increases to operating costs in the context of an islanded microgrid. The BESS GFM control system, which is based on conventional droop techniques, is modeled along with the overall microgrid using the Real Time Digital Simulator (RTDS) to allow for integration of genset controller hardware. A series of simulations are performed to test the voltage and frequency regulation capability of the BESS control system when the primary frequency regulating genset is tripped offline. The results of the simulations suggest that the GFM control scheme will successfully maintain frequency and voltage stability, which will enable operation without a back-up genset while not compromising the microgrid resiliency to contingencies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Next generation retrofit wall panels with integrated vacuum insulation panels

Approximately two-thirds of residential buildings in the United States were constructed before the Department of Energy established energy conservation measures. These buildings present major opportunities for improving energy efficiency, though retrofitting them remains technically and economically challenging. This study presents the development and the durability evaluation of an innovative retrofit panel system that integrates vacuum insulation panels (VIP) with a nail-base panel (called a retrofit insulated panel) to enhance thermal performance with minimal disruption to occupants and without altering standard nail-based panel installation practices. Hygrothermal simulations were conducted to assess the moisture behavior of wall assemblies before and after retrofit installation under varying water vapor control strategies and climate conditions. Results indicate that, with appropriate moisture control strategy, the retrofit system effectively prevents moisture accumulation, keeping mold index values and relative humidity levels below critical thresholds. Additionally, Guarded Hot Box testing was performed to compute the effective R-value of the panel under different coverage areas that demonstrates its effectiveness in enhancing both thermal and moisture performance in existing residential buildings.

Iffa, Emishaw [ORNL]↗
DOE OSTI2025

Versatile & Intelligent Biodetection via Environmental Sensing (VIBES)

Reactive health monitoring strategies during events like the COVID-19 pandemic highlighted the need for predictive, threat-agnostic diagnostics that can detect both known diseases and novel chemical or biological threats. To address this, we investigated an optical biosensor as a breath volatile organic compound (VOC) analyzer, aiming to emulate biological olfaction. We assembled and validated the device with thin film metal coated substrate-based sensors. We immobilized small biological recognition elements on the substrates and delivered controlled concentrations of target VOCs. The sensor was irradiated with a visible laser and the sensor signal was recorded. We characterized the laser performance and tested 3 recognition elements for 2 VOCs with varying concentrations (1-100 ppm). We also evaluated enhancement of the signal using nanostructures on the metal film in comparison with planar film substrate. We demonstrated detecting ethanol reliably at concentrations as low as ~2 ppm along with preliminary detection of acetone (<100 ppm). We also found several unexpected factors that influence the sensor behavior that should be addressed to further refine the device’s performance. The nanostructures were, as expected, found to amplify the sensor signals. These findings demonstrate the feasibility of the optical bio-sensing modality for breath VOC monitoring at physiologically relevant levels. This positions LLNL to develop a low-cost, scalable, broad-spectrum health monitoring capability aligned with the Early Detection thrust of the Bioresilience Mission Focus Area and attract external funding.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

High-Performance Computing Based EMT Simulation: Power Grid with IBRs

Electromagnetic transient (EMT) simulation of power grids with high-fidelity models of inverter-based resources (IBRs) is time-consuming and difficult to scale. The necessity for high-fidelity models of IBRs that incorporate the dynamics of individual inverters within IBRs has been showcased in recent studies. These studies focused on events with partial power reduction in each IBR during a transmission line fault in the power grid. These types of events have been documented in multiple North American Electric Reliability Council (NERC) reports in the past decade. It is imperative then to find solutions to speed-up EMT simulations and scale the size of the region with IBRs studied in EMT simulations. In this paper, a combination of numerical simulation algorithms with high-performance computing techniques are employed in discretization and linear solvers employed in the proposed RE-INTEGRATE EMT simulation platform for power grid with IBRs. For ease of scalability, modular and object-oriented programming is used as these techniques are implemented. Additionally, automation software is developed to convert legacy software codes to the proposed RE-INTEGRATE EMT simulation platform. Thereafter, this platform is evaluated on multi-core central processing units (CPUs). Finally, scale-up tests are performed to showcase the scalability that is possible.

Marthi, Phani Ratna Vanamali [ORNL] (ORCID:0000000↗
DOE OSTI2025

Deep Neural Network Assisted Distributed Strain and Temperature Fiber Sensor System for Natural Gas Pipeline Monitoring

Natural gas pipeline integrity monitoring is crucial to detect potential leaks, find structural issues, and prevent environmental damage. This article presents a system of natural gas pipeline monitoring that uses a specialized double Brillouin peak sensing fiber along with the Brillouin optical time domain analysis (BOTDAs) technique. The calibrated sensing fiber coefficients for strain and temperature are 41.8 kHz/ με and 0.9 MHz/°C for peak 1; and 47.2 kHz/ με , and 1.11 MHz/°C for peak 2, respectively. Initially, lab tests were performed by installing a short section of double Brillouin peak fiber (DBPF) on a 1-in steel pipe under pressure up to 1000 per square inch (psi) at elevated temperatures. Simultaneous distributed measurements of temperature and pressure-induced hoop strain were successfully measured. Considering the long processing speed to extract Brillouin frequency shift (BFS), we employ a novel probabilistic deep neural network (PDNN) framework for rapid BFS prediction. Additionally, using the Finite Element Method, the effects of the pipeline pressure on hoop strain were modeled and compared to the experimental hoop strain under the same set of pipeline conditions. Finally, an actual 4-in outer diameter steel natural gas pipeline was used for pilot-scale tests, where hoop strain was measured at various pressure levels. Leaks were simulated to demonstrate accurate pipeline integrity monitoring. At an internal pipe pressure of 1000 psi, hoop strain of approximately 300 με was observed, and the sensitivity was calculated as 0.28 με /psi. The results of this pilot-scale study demonstrated that the system is capable of performing distributed monitoring sufficient to detect pipeline pressure and the presence of leaks to ensure the safe operation of gas pipelines in the field.

03 NATURAL GAS↗
DOE OSTI2024

Doping liquid argon with xenon in ProtoDUNE Single-Phase: effects on scintillation light

Doping of liquid argon TPCs (LArTPCs) with a small concentration of xenon is a technique for light-shifting and facilitates the detection of the liquid argon scintillation light. In this paper, we present the results of the first doping test ever performed in a kiloton-scale LArTPC. From February to May 2020, we carried out this special run in the single-phase DUNE Far Detector prototype (ProtoDUNE-SP) at CERN, featuring 720 t of total liquid argon mass with 410 t of fiducial mass. A 5.4 ppm nitrogen contamination was present during the xenon doping campaign. The goal of the run was to measure the light and charge response of the detector to the addition of xenon, up to a concentration of 18.8 ppm. The main purpose was to test the possibility for reduction of non-uniformities in light collection, caused by deployment of photon detectors only within the anode planes. Light collection was analysed as a function of the xenon concentration, by using the pre-existing photon detection system (PDS) of ProtoDUNE-SP and an additional smaller set-up installed specifically for this run. In this paper we first summarize our current understanding of the argon-xenon energy transfer process and the impact of the presence of nitrogen in argon with and without xenon dopant. We then describe the key elements of ProtoDUNE-SP and the injection method deployed. Two dedicated photon detectors were able to collect the light produced by xenon and the total light. The ratio of these components was measured to be about 0.65 as 18.8 ppm of xenon were injected. We performed studies of the collection efficiency as a function of the distance between tracks and light detectors, demonstrating enhanced uniformity of response for the anode-mounted PDS. We also show that xenon doping can substantially recover light losses due to contamination of the liquid argon by nitrogen.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Mechanical properties and strain localization of WA-DED printed P91 steel

This paper discusses a P91 steel block that was additively manufactured by wire arc direct energy deposition (WA-DED) followed by two types of post-process heat treatment (PPHT). Vickers microhardness and digital image correlation tensile tests were performed along the building direction. The global mechanical properties (i.e., microhardness and tensile properties) and the local mechanical responses (i.e., hardness fluctuation and strain localization) were systematically investigated. Results showed that (1) all P91 specimens showed higher strengths than American Society of Mechanical Engineers standard requirements for wrought P91 steel, (2) the as-printed P91 exhibited much higher average hardness and fluctuations than that after PPHT, (3) PPHT reduced P91 strengths but improved the ductility significantly, and (4) strain localization presented in the as-printed specimen during uniform deformation in tensile tests. The hardness fluctuation and strain localization along the building direction of the AP P91 were caused by different thermal histories received during WA-DED. The study indicated that PPHT, ideally tempering-only heat treatment, is necessary for the WA-DED printed P91 steel.

Mechanical properties↗
DOE OSTI2025

Smart Contracts for Power Grid Applications Using the Advanced DLT Cyber Grid Guard Testbed

In this study is presented two power system applications with distributed ledger technology (DLT) and smart contracts (SC) that were assessed in a Cyber-Grid-Guard System (CGGS) advanced testbed, with protective relays, power meters, communication devices, DLT devices, synchronized time source, clock displays and real time simulator. This CGGS testbed was set in the Advanced Protection Lab, 252 lab space of the Grid Research Integration and Deployment Center (GRID- C), at Oak Ridge National Laboratory. In power grids, customer-owned distributed energy resources (DERs) are more frequent than in the past, and the numbers of points of interconnection (POI) with customer-owned DERs have increased. Disruptive operation from DERs presents a risk to grid operations, and protective relays located at the POI are used to isolate out-of-tolerance or poorly behaving of DERs. Ensuring the integrity of data from the relays at the POI, and DLT could enhance the security of the power grids. The first application is a SC to define and control the allowable total power factor (TPF) of the DER (wind farm) output, and the terms of the SC are implemented using DLT with a CGGS for a customer-owned DER. The TPF SC was implemented by the CGGS using DLT. The experimental model was performed with a real-time simulator using a CGGS and relay in-the-loop. The data collected from the CGGS were used to execute the TPF SC. The TPF limits were between +0.9 and +1.0, and the breakers’ operation in the POI was controlled by the relay using the SC. The events were collected from the real-time simulator, CGGS, and SEL 700GT relay to validate a successful application of the TPF SC using DLT. The second application is a SC to measure and control the allowable voltage service limits (VSL) by the CGGS using DLT. The tests were performed by using a real-time simulator, CGGS and relay in-the-loop. The data was collected from the CGGS that executed the SC. The main constraints were defined based on ANSI C84.1 service voltage limits, and the operation of the breakers in the POI. The events were collected from the CGGS, and SEL 700GT relay to assess a successful operation of the VSL SC using DLT.

24 POWER TRANSMISSION AND DISTRIBUTION↗