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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A Secondary Control Framework for Microgrid Interoperability With Vendor-Agnostic Grid-Forming Units: Design, Implementation, and Demonstration via Large-Scale Hardware Setup

The reliable operation of islanded microgrids increasingly depends on secondary controls that restore voltage and frequency to nominal values and ensure accurate active and reactive power sharing. Centralized secondary control architectures achieve high accuracy through global coordination at the cost of single-point failures and limited scalability compared with decentralized/distributed approaches. But a critical gap remains in addressing the interoperability and vendor-agnostic operation of secondary controls in real-world microgrids where heterogeneous diesel generator(s) and grid-forming (GFM) inverter(s) from multiple manufacturers always coexist. Practical and vendor-agnostic interoperability guidelines for the secondary control architecture of microgrids with multiple GFM units have not yet been developed; therefore, this paper proposes an interoperable and vendor-agnostic secondary control framework that operates seamlessly across GFM units from different vendors without relying on proprietary controls and protocols, hardware, or lock-ins. The framework leverages existing communication infrastructures (e.g., Modbus TCP/IP) to enable cost-effective deployment while addressing practical challenges, such as packet loss and quantization errors. Mitigation strategies-including data averaging, situational event-triggered control, and finite-iteration execution-are introduced to enhance reliability under real-world conditions. A generalized modeling and design framework is also presented, supported by robustness analysis to demonstrate independence from vendor-specific implementations. The proposed framework is validated through a large-scale hardware demonstration using a 3-$\phi$, 480-V, 60-Hz, 713-kVA laboratory hardware microgrid involving a heterogeneous diesel generator and multiple GFM inverters, showcasing its effectiveness in achieving stable voltage and frequency restoration and accurate power sharing under practical constraints. The results highlight the framework's potential as a scalable and practical solution for next-generation microgrids requiring openness, standard framework, and interoperability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Unsupervised learning-enabled pulsed infrared thermographic microscopy of subsurface defects in stainless steel

Metallic structures produced with laser powder bed fusion (LPBF) additive manufacturing method (AM) frequently contain microscopic porosity defects, with typical approximate size distribution from one to 100 microns. Presence of such defects could lead to premature failure of the structure. In principle, structural integrity assessment of LPBF metals can be accomplished with nondestructive evaluation (NDE). Pulsed infrared thermography (PIT) is a non-contact, one-sided NDE method that allows for imaging of internal defects in arbitrary size and shape metallic structures using heat transfer. PIT imaging is performed using compact instrumentation consisting of a flash lamp for deposition of a heat pulse, and a fast frame infrared (IR) camera for measuring surface temperature transients. However, limitations of imaging resolution with PIT include blurring due to heat diffusion, sensitivity limit of the IR camera. We demonstrate enhancement of PIT imaging capability with unsupervised learning (UL), which enables PIT microscopy of subsurface defects in high strength corrosion resistant stainless steel 316 alloy. PIT images were processed with UL spatial–temporal separation-based clustering segmentation (STSCS) algorithm, refined by morphology image processing methods to enhance visibility of defects. The STSCS algorithm starts with wavelet decomposition to spatially de-noise thermograms, followed by UL principal component analysis (PCA), fine-tuning optimization, and neural learning-based independent component analysis (ICA) algorithms to temporally compress de-noised thermograms. The compressed thermograms were further processed with UL-based graph thresholding K-means clustering algorithm for defects segmentation. The STSCS algorithm also includes online learning feature for efficient re-training of the model with new data. For this study, metallic specimens with calibrated microscopic flat bottom hole defects, with diameters in the range from 203 to 76 µm, were produced using electro discharge machining (EDM) drilling. While the raw thermograms do not show any material defects, using STSCS algorithm to process PIT images reveals defects as small as 101 µm in diameter. To the best of our knowledge, this is the smallest reported size of a sub-surface defect in a metal imaged with PIT, which demonstrates the PIT capability of detecting defects in the size range relevant to quality control requirements of LPBF-printed high-strength metals.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Novel Lightweight, Low-Cost Heliostat for Concentrating Solar Power (SBIR Phase I Final Report)

The overall goal of this Department of Energy (DOE) SBIR Phase I project was to demonstrate the feasibility of the L.Garde, Inc. heliostat mirror facet for use in concentrated solar power applications. Prior to this Phase I project, L.Garde, Inc. developed a design for a lightweight and low cost mirror facet and successfully fabricated small scale (0.667 m 2 ) with a mirror surface flatness of 0.7 mrad. Therefore, the focus of the Phase I effort was to (1) demonstrate scalability by fabricating larger size mirrors while retaining the same mirror surface flatness, (2) demonstrate the design can withstand operating environment conditions through field testing, and (3) perform cost analysis to show the heliostat mirror facet design can meet DoE goals of < 12 kg/m2 and <$30/m 2 . During the Phase I project, L.Garde successfully fabricated large area (1.395 m 2 ) heliostat mirror facets, with a mass per unit area of 8 kg/m 2 and a cost of $29.80/m 2 . Surface flatness measurements (using contact probe technique) were performed on the mirror surface and results showed a flatness of 0.68 mrad, which were in agreement with previously fabricated small scale mirror facets. Slope error measurements was also performed on the mirror surface and results showed a slope error of 0.77 mrad which also was in agreement with previously fabricated small scale mirror facets. One large area mirror facet was subjected to a three (3) month field test. Surface flatness and slope error measurements were performed on the mirror surface after the field test and results were 0.663 mrad and 0.58 mrad respectively. The large scale heliostat mirror facets were also subjected to accelerated aging. However, during this exposure we observed failure due to the breaking of the mirror facets. Further investigation into the source of the failure showed that the mirror component alone showed signs of degradation during the same accelerated aging test. We believe that moisture ingress is occurring when subjected to high humidity, leading to buildup of water with the layers of protective paints and resulting in mirror breakage when water expands in freezing conditions. In order to mitigate or eliminate this issue, a new weatherproofing strategy may be implemented or a new mirror component may be used that is able to survive accelerated aging conditions.

14 SOLAR ENERGY↗
DOE OSTI2023

Utah FORGE: Fault Reactivation Through Fluid Injection Induced Seismicity Laboratory Experiments

Included are results from shear reactivation experiments on laboratory faults pre-loaded close to failure and reactivated by the injection of fluid into the fault. The sample comprises a single-inclined-fracture (SIF) transecting a cylindrical sample of Westerly granite. All experiments are conducted at ambient temperature and follow a similar protocol: (i) application of confining stresses (3MPa) on the fault fully saturated with DI water, (ii) shear-mobilization through the increase of axial loading at a constant displacement rate until a post-peak steady-state condition is reached, (iii) reduction of axial loading and related shear stress to a prescribed fraction of the peak steady-state frictional strength (typically 60% to 90%, representing intermediate to high magnitudes) and (iv), fault reactivation triggered by a stepwise increase of pore pressure on the fault in 0.1 MPa increments held constant for 1-5 minutes. Mechanical data from three ISCO pumps connected to a Temco pressure vessel measure axial, confining, and fault-related parameters, including fluid pressure (kPa), fluid flow rate (mL/min), and axial displacement (mm). See included code for initial data analysis and visualization for select experiments. Resource names represent experiment numbers found in the "Read Me" file, which describes each experimental setup and parameters.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Online thermal profile prediction for large format additive manufacturing: A hybrid CNN-LSTM based approach

Large format additive manufacturing (LFAM) is an advanced 3D printing technique that efficiently fabricates large-scale components through a layer-by-layer extrusion and deposition process. Accurate surface layer temperature monitoring is essential to prevent manufacturing failures and ensure final product quality. Traditional physics-based offline approaches for simulating thermal behavior are often inefficient and complex, posing challenges on real-time, in-situ monitoring. Here, to address this, we propose a data-driven hybrid CNN-LSTM model to predict sequential thermal images of arbitrary length using real-time infrared thermal imaging. In this approach, a Convolutional Neural Networks (CNN) is trained offline to capture spatial features, reduce dimensional complexity, and enhance time efficiency, while a stacked Long Short-Term Memory (LSTM) is applied online to capture temporal information for improved prediction of future thermal behavior in subsequent printing layers. Model performance is evaluated using MSE, SSIM, and PSNR metrics and is benchmarked against stacked LSTM and convolutional LSTM models, demonstrating superior accuracy and applicability. Additionally, to mitigate noise from moving extruders and gantry backgrounds in thermal images, a fine-tuned semantic segmentation model is implemented offline to extract printing geometry, enabling precise temperature tracking along the tool path for further thermal analysis. The frameworks developed in this study significantly advance temperature monitoring, thermal analysis, and in-situ manufacturing control for LFAM, bridging the gap between theoretical modeling and practical application.

Geometry extraction↗
DOE OSTI2024

Decision-making based on Markov decision process in integrated artificial reasoning framework—Part I: Theory

This paper presents a decision-making framework based on an integrated artificial reasoning framework and Markov decision process (MDP). The integrated artificial reasoning framework provides a physics-based approach that converts system information into state transition models, and the analysis result will be represented by the transition probabilities that can be used with an MDP to find a traceable and explainable optimal pathway. A dynamic Bayesian network (DBN) is well suited for representing the structure of an MDP. The causality information among process variables (or among subsystems) is mathematically represented in a DBN by the conditional probabilities of the node’s states provided different probabilities of the parent node’s states. To define node states in a physically understandable manner, we used multilevel flow modeling (MFM). An MFM follows the fundamental energy and mass conservation laws and supports the selection of process variables that represent the system of interest so that causal relations among process variables are properly captured. An MFM-based DBN supports developing state transition models in an MDP to capture the effect of process variables of system having physical relations. The operators of the target system can capture stochastic system dynamics as multiple subsystem state transitions based on their physical relations and uncertainties coming from component degradation or random failures. We analyzed a simplified exemplary system to illustrate an optimal operational policy using the suggested approach.

Markov decision process↗
DOE OSTI2022

AGR-5/6/7 Final Release-to-Birth Ratio Data Analysis

AGR-5/6/7 is the last of a series of Advanced Gas Reactor (AGR) experiments conducted in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) in support of development and qualification of tristructural isotropic (TRISO) low-enriched fuel for use in the high-temperature gas cooled reactor (HTGR). AGR configuration and irradiation conditions are based on prismatic HTGR technology that is distinguished primarily through the use of helium coolant, a low-power-density ceramic core capable of withstanding very high temperatures, and TRISO-coated particle fuel. The AGR tests provide valuable irradiation-performance data to support fuel process development, qualify fuel for normal operation and accident conditions, and support development and validation of fuel performance and fission-product (FP) transport models and codes. Each AGR test consists of multiple independently controlled and monitored capsules containing fuel compacts placed in a graphite cylinder shrouded by a steel shell. Release-to-birth ratios (R/B) for fission-gas isotopes released from each capsule are calculated from release rates, measured by germanium detectors in the Fission Product Monitoring System (FPMS) installed downstream from each capsule, and birth rates calculated using numerical models of FG generation. The R/Bs are a critical measure of the ability of the fuel kernel, the particle coating layers, and the compact matrix to retain fission-gas atoms, preventing their release into the sweep-gas flow, and the impact of initially defective particles and/or particle-coating failures that occur during irradiation. For fission-gas isotopes, particle failure is defined as failure of all coating layers, allowing gaseous fission atoms to escape from a particle. During the first five cycles (162B ? 165A), R/Bs were stable in the 10-8?10-6 range, and no in-pile particle failures were observed, based on the gross gamma counts. The maximum R/B value of around 2 ? 10-6 for Kr-85m resulted from the presence of as-fabricated exposed kernels (based on the high exposed kernel fraction), the dispersed uranium, and high fuel particle temperatures in Capsule 1. Comparison of capsule-measured R/Bs from these early cycles to predictions using the previously developed AGR R/B model demonstrated FG release from the AGR-5/6/7 TRISO fuel was comparable to that of previous experiments. In addition, the Kr-85m R/B per-exposed-kernel values are comparable to R/B values obtained in AGR-3/4 irradiation experiment and four irradiation experiments performed during 1980s: (1) HRB-17/18, (2) COMEDIE-BD1, (3) HFR B1, and (4) HRB-21. In contrast, all measured R/B values are lower than predictions by the commonly used Richards and German models, which are intentionally conservative. A large number of in-pile particle failures occurred in Capsule 1 by the end of Cycle 166A. During the final four cycles (166A ? 168A), apparent damage to the Capsule 1 gas line appeared to cause FG leakage from that capsule into the other four capsules, resulting in an increase in fission gas (FG) detected in the effluent for all capsules. Isolation of the Capsule 1 gas line during the last three cycles also prevented measurement of its FG release. Thus, R/Bs in all capsules after Cycle 166A are highly uncertain because of undefined amount of leakage from Capsule 1, especially for long-lived isotopes. A few hundred in-pile particle failures were estimated for Capsule 1 before the end of Cycle 166A, but the total number of failures is unknown due to the lack of FG release data in the later cycles. Based primarily on evidence from the gross gamma counts during Cycle 168A, approximately 15 particles failed in Capsule 3 and four particles failed in Capsule 2. In-pile failures in Capsule 3 were anticipated because this capsule was designed to operate beyond the HTGR normal operating temperature range. In contrast, no in-pile failures were identified in the top two capsules (4 and 5) based on the absence of the typical spikes in gross gamma counts and low failure estimates using the AGR model, developed in INL/EXT-14-32970, for R/B of the short-lived isotopes (Kr-89 and Xe-137) with minimal leakage from Capsule 1.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Towards Commercialization of Low-Cost, Crack-Tolerant, Screen-Printable Metallization by Full-Size Module Testing and Field Characterization

This project is motivated by the need to develop a materials engineering solution to reduce solar module degradation caused by cell cracks. The cell-crack-induced power loss is a long-term degradation mechanism and one of the main causes of solar panel field failures. Cell cracks can occur during module fabrication, transportation, installation, and long-term operation due to thermomechanical stressors. Our team’s internal estimation – based on the national weather pattern, frequency of severe weather, and 39- GW asset survey by Heliolytics – reveals that the cell-crack-induced module degradation translates to lost revenues >$17B over an average 5-year period for solar farm owners and to reduced reliability (<25 years panel lifetime) for solar energy consumers. In response to this challenge, the prime recipient offers a metal matrix composite (MMC) silver paste that is tailor-engineered for screen-printing gridlines and busbars, which serve as the electrical contacts on solar cells. We formulate our MMC paste by adding low-cost (∼0.02¢/WDC for research grade), surface-engineered carbon nanotubes to commercially available silver paste. The MMC paste offers a drop-in, cost-effective solution to cell cracks for solar cell and module manufacturers. The main goal of this project was to conduct field-relevant, module-level analysis and qualification of MMC metallization.

14 SOLAR ENERGY↗
DOE OSTI2024

A hardware-in-the-loop (HIL) testbed for cyber-physical energy systems in smart commercial buildings

In recent years, there has been a growing trend toward the development of smart buildings that rely on cyber-physical systems (CPS) to optimize occupant comfort, safety, and energy efficiency. To ensure the reliable and efficient operation of CPS with designed control strategies, it is important to evaluate their performance under various scenarios before deploying them in the real world. This is where a Hardware-in-the-loop (HIL) testbed designed for studying sensor and control-related studies in smart buildings can be highly valuable. With the growing threat of cyber-attacks and physical faults targeting smart buildings, it is essential to ensure the security of building operations. A HIL testbed can emulate cyber-attack and physical fault scenarios, allowing researchers to develop and test threat detection and mitigation algorithms. This enables researchers to identify potential issues and optimize the algorithms in a safe and controlled environment before they are deployed in real-world settings, reducing the risk of failures that can negatively impact occupant comfort, safety, and energy efficiency. Therefore, this paper developed a HIL testbed designed for cyber-physical energy systems (e.g. buildings automation system (BAS)) in smart commercial buildings. The HIL testbed is comprised of a real-time building and Heating, Ventilation, and Air-Conditioning (HVAC) emulator using Modelica-based dynamic models, a set of BAS controllers, and a BAS computer server. The data generation capability of the HIL testbed is demonstrated by tracking normal and faulty operating data in the BAS, as well as monitoring detailed network traffic in the local BAS network. Here, this study further demonstrates the HIL testbed’s capability by conducting case studies on real-time physical fault and cyber-attack experiments using a Department of Energy (DOE) prototype commercial building. It is anticipated that the fully functional HIL testbed will be utilized for a variety of sensor and control-related studies, including but not limited to testing, developing, validating of different HVAC control strategies, fault detection & diagnosis, energy monitoring and analysis, cyber security study, etc.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Reducing Uncertainty of Fielded Photovoltaic Performance (Final Technical Report)

Improved analysis and reporting of photovoltaic (PV) field performance increases the certainty of owners and financiers that systems will perform as expected. Advanced module technologies (e.g., PERC, HJT, and bifacial) introduce new degradation mechanisms and performance characteristics. The FY19-21 Reducing Uncertainty project leveraged data from the ever-increasing PV fleet to develop models and understanding of the field performance of existing and new technologies. Specifically, we accomplished: report on field performance and degradation rates for high-efficiency silicon (HJT, PERC, IBC) and more conventional technologies; developed automated analysis techniques to quantify system performance (performance ratio, energy yield) and production shortfalls (soiling, degradation, availability); refined the RdTools software toolkit to bring standard, validated analysis techniques to bear on third-party data; analyzed and reported on large datasets including Treasury data and Lawrence Berkeley National Laboratory's Utility-Scale dataset to expand the high-quality degradation-rate histogram published previously; worked with industry partners and the DuraMAT data hub to enable private parties to share and aggregate PV production data anonymously, leveraging cloud-based data analysis infrastructure and publishing on US fleet-scale performance comprising over 7GW of operating systems. (https://www.nrel.gov/pv/fleet-performance-data-initiative.html). Through our industry collaborations we have engaged in NDA-covered data transfer with twelve PV fleet owners as of January 2022, with more agreements in negotiation. Our scalable cloud-based time series database contains over 30 billion rows (20TB) of PV time series data, representing over 1700 commercial and utility-scale systems, and over 7.2 GW of DC capacity (Fig 1). Initial field performance results have been distributed in several public reports. Because our fleet composition and data quality methods are continually improving, annual updates to these results are published to our PV Fleet webpage [ https://www.nrel.gov/pv/fleet-performance-data-initiative.html ] and DuraMAT data hub [DOI: 10.21948/1842958]. Another existing dissemination channel used for observed soiling losses is a map we maintain for soiling losses. Additional products developed include a report detailing fleet-wide performance index, availability, startup loss and snow loss factors, a detailed report on the 1603 grant dataset comprising over 100,000 PV systems with failure and performance details and a utility-scale report coauthored with LBNL on 31 GW of system performance.

14 SOLAR ENERGY↗
DOE OSTI2021

Computational Fluid Dynamics Simulation of Compressible Non-Newtonian Biomass in a Compression-Screw Feeder

Compression-screw feeders play a critical role in biorefineries to transport lignocellulosic biomass feedstocks from the feeding hoppers to biomass-conversion reactors in order to pretreat and convert biomass to hydrocarbon liquid biofuels and other power and energy resources. One of the main challenges in the operation of screw feeder is plugging and jamming of compressed biomass with high concentration of insoluble solids. The focus of this paper is to numerically investigate the screw feeder at these challenging operating conditions and help with the optimization of the screw feeder design to avoid operation failure. In this work a customized CFD model based on open-source OpenFOAM package [1] was developed to simulate the concentrated biomass as a highly viscous non-Newtonian fluid in the screw feeder. The biomass is modeled as a single-phase compressible Bingham fluid with a plastic viscosity as well as a density-dependent yield stress. The compressibility formulation (pressure-dependent density) and the density-dependent yield stress formulation in the governing equations follow the suggestions from a recent study by Duncan et al. [2]. A pilot-scale hopper/screw feeding system at NREL [3] is used to compare the experimental observations with our simulation results. The auger is 280 mm long and tapered with outer diameter changing from 80 mm to 35 mm. The auger rotates from 10 to 60 rpm in a conical throat which contains anti-rotational bars. The simulations predicted the required torque for the screw feeder and the pressure increase at the exit for biomass feedstocks with various fluid viscosity properties and auger rotating speeds. The analysis of the stress forces helped to identify the critical conditions were the screw feeder excessive wear or jamming could occur.

biofuels↗
DOE OSTI2022

Multicomponent gas mixture parametric CFD study of condensation heat transfer in small modular reactor system safety

Safety is always the primary concern for designing and analyzing nuclear reactor systems. The requirements for the safety margin for advanced small modular reactor (SMR) systems are targeted even higher than the conventional commercial large-scale nuclear reactors incorporating the passive and inherent safety systems. The SMR systems are designed with the condensation passive containment cooling system (PCCS), which plays a critical role in removing reactor heat during a steam release accident case. However, the presence of non-condensable gas (NCG), like air, reduces the heat transfer performance. This physics phenomenon becomes multifactorial for nuclear reactor containment during a fuel failure accident case that releases hydrogen gas. Besides, the mixture component of steam-air-hydrogen varies in reactor accident cases, which need simulation and validation keeping parameters of importance. Reviews showed that previous studies for SMR’s PCCCS did not cover the condensation heat transfer (CHT) in the presence of multicomponent NCG mixture parametric computational fluid dynamics (CFD) simulation and validation, making a research gap in the SMR design safety. A comprehensive CHT parametric CFD study was performed for SMR PCCS to fill this research gap. This study used experimental data as simulation 3D physics domain inlet and outlet boundary conditions. However, the wall boundary conditions were constant temperature, curve-fit, and annular coolant for verifying the turbulence models. Parametric simulations were performed, verified, and optimized for steam-NCGs mixtures. The multicomponent gases, multiphase mixtures, and fluid film condensation models were applied with associated turbulence models. The results of the parametric study were evaluated for realistic reactor conditions. Results showed that parametric study provided critical insight about the dependency of multicomponent gas mixture parameters that supports reactor safety design, analysis, and licensing.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Source term analysis of FeCrAl accident tolerant fuel using MELCOR

It has been established that incremental improvements in beyond design basis accident performance can be achieved through accident tolerant fuel (ATF). However, they have the potential to recover margin with respect to conventional fuel and therefore enhance plant economics through uprate or cycle length increase. To realize this potential, it is necessary to quantify the reduction in source term due to use of ATF, and correspondingly how this is affected by increasing the cycle length and/or burnup. This requires development of a risk informed analysis methodology for ATF under high burnup conditions, which is being developed within LWRS. To this end, a MELCOR simulation of FeCrAl ATF in a recovered Large Break LOCA (LBLOCA) scenario has been developed, using a model based on the Zion Pressurized Water Reactor (PWR). The new user defined material capability, along with the inclusion of detailed neutronics- and depletion-derived parameters such as core power distribution, decay heat behavior, and fission product inventories, allows a more detailed simulation of FeCrAl clad material properties and behavior than has previously been possible using MELCOR. These detailed FeCrAl results were compared with a zircaloy clad model to investigate the differences between the two clad types and quantify the benefits of FeCrAl ATF with an 18-month cycle. Next, the fuel cycle with ATF was extended to 24 months, to determine whether any additional safety margin provided by FeCrAl ATF could be leveraged to implement high burnup FeCrAl-clad fuel while retaining the same operating and safety limits as current zircaloy-clad fuel. For the particular scenario analyzed, the delay to fuel failure from using ATF was of the same order as the LOCA recovery time, and hence significant in reducing fission product release, with the 24-month FeCrAl core performing better than the 18-month zircaloy core. It is noted that for other transients, the reduction in release due to using FeCrAl may be less significant. Furthermore, the material model developed here can be used in such further studies in support of determining the overall source term.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Effect of laminae count and manufacturing methods on mechanical properties of thin‐ply woven composites

Abstract Thin‐ply woven composites exhibit exceptional mechanical performance by delaying the onset of damage, making them suitable for high‐performance structural applications. This study outlines the impact of manufacturing techniques (vacuum bagging and hot pressing), ply count, and fiber waviness on the mechanical properties of aromatic thermosetting copolyester/carbon‐fiber (ATSP/CF) composites. The analysis encompasses several different ply counts, evaluating their effects on the in‐plane elastic modulus (0°–90°) and tensile strength. Results demonstrate that reducing the waviness (or crimp) ratio significantly enhances the in‐plane elastic modulus, with improvements up to 188%, highlighting the importance of fiber alignment. Vacuum bagging produced ply thicknesses from 128 to 58 μm for 1–36 plies, with in‐plane elastic moduli from 30.3 to 87.2 GPa, and 4‐ and 8‐ply samples showed approximately 40% higher stiffness than those made by hot pressing. ATSP resin with high thermal stability (up to 400°C) and recyclability was used. Furthermore, this study highlights the microstructural enhancements achieved through vacuum bagging, as revealed by scanning electron and optical microscopy, and micro‐computed tomography imaging. This paper provides insights into damage mitigation and achieving enhanced mechanical properties by controlling fiber waviness using vacuum bagging and higher ply count in thin‐ply ATSP/CF composites. Highlights Crimp ratio reduction enhances elastic in‐plane elastic modulus up to 188%. Vacuum bagging increases modulus over the hot pressing manufacturing method by 40%. Lowering thickness‐per‐ply increases failure strain from 0.8% to 1.2%. Explored the performance of a novel ATSP matrix with high recyclability and thermal stability.

Kushwaha, Shashank [The Grainger College of Engine↗
DOE OSTI2022

Deformation and Fracture Behaviors of Cylindrical Battery Shell During Thermal Runaway

Thermal runaway is one of the catastrophic failure modes of lithium-ion cells. During thermal runaway in cylindrical cells, sidewall shell rupture has been identified as a contributing factor for thermal runaway propagation in battery packs. Herein, the deformation and fracture behaviors of the battery shell during thermal runaway are investigated based on in-situ and ex-situ characterization as well as physics-based modeling. The deformation and fracture modes of the battery shell with/without Carbon Fiber Reinforced Polymer (CFRP) sleeves are identified. In the simulation, the strain introduced by thermal expansion of the system is considered, as well as the thermal and strain rate effects on the plastic stage. The final cell shell modeling is validated by cell thermal runaway tests. Results reveal the quantitative relation between shell deformation behaviors and the pressure and temperature distribution. Both the experiment and model demonstrate the effectiveness of adding a tight-fitting CFRP sleeve around the cell in limiting the side-wall rupture of the shell. The use of CFRP tubes introduces a novel phenomenon in the context of uneven temperature distribution. Results shed light on the mechanistic analysis of a cell side-wall rupture during thermal runaway and provide essential guidance for the next-generation safe battery design.

battery casing↗
DOE OSTI2021

Fixed Bit Rotary Drilling Failure Criteria Effect on Drilling Vibration

Polycrystalline diamond compact (PDC) bit use has been expanded to geothermal drilling applications due to their improved performance in drilling compared to roller cone bits. Multiple vibration models have been developed yet and there are limited use of field data to study the ability of numerical vibration model to predict recorded vibration in the field. The objective of this paper is to evaluate the capabilities of two different rock-bit interaction models with two different ROP formulations for predicting the actual behavior seen in the field. The first model (Model-I) considers the rock-bit interaction, incorporating the effect of subsurface formation characteristics. The second model (Model-II) is a PDC bit model that uses calculated threshold weight-on-cutter (WOCt) to study the interaction of the bit with the rock surface. The models, which couple the drill stem axial and torsional motions, are solved numerically using the fourth-order Runge-Kutta method and compared with recorded downhole drilling data from the Chocolate Mountain Aerial Gunnery Range (CMAGR) geothermal well located in California. An 8–½" PDC bit with 8 blades was modeled and vibration simulation was performed to investigate stick-slip vibrations at 1400 ft. depth. Simulation results using field data indicate that Model-II encounters a low range of stick-slip severity (SSV) as compared to Model-I, which is in the moderate range. Comparison with the field value for SSV shows Model-II is the best representative of the field case for this depth. The sensitivity analysis shows that results are sensitive to model constants making prediction of SSV from models uncertain.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Enhanced Component Performance Study: Motor Driven Pumps 1998-2024

This report presents an enhanced performance evaluation of motor-driven pumps (MDPs) at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience failure reports from calendar year 1998 through 2024 as reported in the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS). The MDP failure modes considered for standby systems are fail to start (FTS), fail to run (FTR) for one hour of operation (FTR=1H), FTR after one hour of operation (FTR>1H), and for normally running systems FTS and FTR. An eight-hour unreliability estimate is also calculated and trended. The component reliability estimates and the reliability data are trended for the most recent 10-year period while yearly estimates for reliability are provided for the entire study period.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Full core LOCA safety analysis for a PWR containing high burnup fuel

For economic reasons, the US nuclear industry is renewing efforts to build a technical basis to extend peak rod average burnup limits above the current regulatory burnup limit of 62 GWd/MTU. The primary driver of these efforts is to economically increase pressurized water reactor (PWR) cycle lengths to 24 months, reduce the number of fresh fuel assemblies, increase time online, thereby reducing number of outages and their associated cost, higher fuel utilization, and possibly reduce core design constraints. In order for US nuclear utilities to leverage these economic efficiencies, the US Nuclear Regulatory Commission (NRC) will likely require nuclear power plants (NPPs) to analyze a number of potential operational occurrences and their potential consequences with each new core design prior to resuming normal operation. Potential operational occurrences can be divided into three primary regimes: (1) normal operation, (2) anticipated operation occurrences (AOOs), and (3) design basis accidents (DBAs). Normal plant operation is an operating regime in which the plant operates within specified operational limits until the end of the cycle, whereas AOOs are events that result in the NPP deviating outside the normal operating regime. A key attribute of an AOO is that the occurrence should be expected. However, by definition, the occurrence of an AOO does not result in significant impact to critical safety functions. The last potential operational occurrence is a DBA. From the fuel performance point-of-view, DBAs can be subdivided into two bounding categories: (1) loss of coolant accidents (LOCAs), and (2) reactivity insertion accidents (RIAs). Unlike AOOs, DBAs may result in fuel rod failure. The NRC imposes fundamental acceptance criteria to minimize radiological consequences to the public and onsite staff. Furthermore, safety criteria are typically linked to the fulfillment of other acceptance criteria related to reactor safety equipment designed to mitigate DBAs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗