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At least 1,009 records · Page 56

Severe weather, utility spending, and the long-term reliability of the U.S. power system

There has been a limited amount of peer-reviewed literature on long-term trends in electricity reliability including the underlying factors that impact reliability across the United States. In this analysis, we considered up to 16 years of data from 203 U S. utilities—representing about 70% of electricity sales. Annual frequency of interruptions for an average customer—at the regional and U.S. national-level—has generally decreased over this timeframe. But we do not find that there is a statistically significant trend in the annual duration of interruptions for an average customer. We find that more explicit measures of severe weather are correlated with reliability. We are able to explain 7% and 16% of past variation in the reliability metrics system average interruption duration and frequency indices, respectively, is due to severe weather—a significant improvement over earlier studies. We find that current year spending by utilities is correlated with worse reliability and that cumulative spending over the preceding three years is correlated with better reliability. Finally, we demonstrate that using a statistical instrument to represent the annual frequency of interruptions for an average customer can greatly improve analysis of trends in the annual duration of interruptions for an average customer.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Space Transportation Booster Engine Configuration Study. Volume 3: Program Cost estimates and work breakdown structure and WBS dictionary

The objective of the Space Transportation Booster Engine Configuration Study is to contribute to the ALS development effort by providing highly reliable, low cost booster engine concepts for both expendable and reusable rocket engines. The objectives of the Space Transportation Booster Engine (STBE) Configuration Study were: (1) to identify engine development configurations which enhance vehicle performance and provide operational flexibility at low cost; and (2) to explore innovative approaches to the follow-on Full-Scale Development (FSD) phase for the STBE.

Source record↗

Convergent Manufacturing of Large-Scale Components for Nuclear Applications, via Additive Manufacturing and Powder Metallurgy Hot Isostatic Pressing

Powder metallurgy (PM)–hot isostatic pressing (PM-HIP) has long been recognized as a powerful route for producing fully dense, near net shape metallic components. By consolidating powders under high temperature and pressure, HIP provides isotropic properties, uniform microstructures, and scalability to complex geometries that are vital for sectors such as aerospace, energy, and nuclear power. Yet despite these advantages, the technology has remained constrained by costly trial and error canister fabrication, limitations of conventional forging, and incomplete knowledge about how the canister design influences final part properties. Additive manufacturing (AM), by contrast, thrives on design freedom and geometric flexibility but struggles with speed, scalability, and cost when applied to very large structures. The research presented in this report investigated how a convergent manufacturing approach, combining AM with PM-HIP, can merge the strengths of both technologies, leveraging AM’s flexibility for canister design and HIP’s consolidation capability to deliver reliable, large, and complex parts. The work progressed through three case studies that built on one another in scale and complexity. Small cylindrical canisters fabricated by conventional methods, laser powder bed fusion, and directed energy deposition were filled with stainless steel powders and subjected to HIP. The resulting parts demonstrated near-full density and mechanical properties on par with wrought stainless steel, showing for the first time that AM canisters can be a direct substitute for conventional ones without sacrificing quality. The next step involved a medium-scale, noncentrosymmetric T-valve, which is an enclosed, multibranch geometry that tested the limits of AM + PM-HIP integration. The T-valve achieved predictable shrinkage and uniform densification, confirming feasibility for enclosed designs. However, this study also revealed oxide inclusions and interfacial challenges at the AM + HIP boundary, underscoring the critical importance of controlling interface chemistry and employing robust, in situ strategies, such as melt pool monitoring and thermal monitoring, coupled with nondestructive evaluation techniques such as x-ray computed tomography. Finally, the effort culminated in fabricating a large-scale impeller weighing nearly 2000 lb and spanning 5 ft in diameter. Produced via multirobot wire arc AM and hot isostatic pressed to near-full density, the impeller validated industrial-scale feasibility. Predictive models closely matched experimental shrinkage, tensile properties were spatially uniform across the component, and the AM + PM-HIP interface proved mechanically sound despite the presence of oxide-decorated prior particle boundaries. This large-scale demonstration is a major milestone, showing that hybrid AM + PM‑HIP can reliably deliver components at reactor-relevant scales. Collectively, these studies charted a logical pathway: small-scale work built scientific confidence, medium-scale work highlighted opportunities and challenges, and large-scale work proved industrial impact. The overarching conclusion of this report is that AM + PM-HIP should not be seen as a replacement for forging but as a complementary pathway that provides the US with flexibility, resilience, and new options for manufacturing nuclear-grade components. Looking ahead, several directions emerge as critical to sustaining progress. Predictive modeling must become faster, more accessible, and more accurate, with digital twins and machine learning reducing reliance on trial and error. Powders and alloys must be optimized for HIP, with improved cleanliness, reduced oxides, and tailored chemistries that enhance creep, fatigue, and irradiation resistance. Interfaces between AM and HIP regions must be better engineered through coatings, machining strategies, and surface treatments to mitigate oxide formation and ensure reliable bonding to explore opportunities for HIP of targeted compositional parts, as well as multimaterial HIP cladding applications. Monitoring and nondestructive evaluation need to expand, incorporating multimodal sensors, x-ray computed tomography, and real-time data integration through platforms such as Pelican. At the same time, the pathway to industrial adoption requires techno-economic analysis, machinability studies, and qualification frameworks aligned with industry and regulatory standards. Finally, workforce and academic engagement must be strengthened. Programs that train technicians and engineers for US Navy and US Department of Energy manufacturing challenges should be paired with academic partnerships to support fundamental research, with open sharing of non-export-controlled data to accelerate innovation and build the next generation of experts. In conclusion, this report demonstrates that hybrid AM + PM-HIP is scientifically viable and strategically important. By combining the design agility of AM with the consolidation strength of HIP and embedding modeling, monitoring, and workforce development, this approach provided a transformative new capability for US manufacturing. The path forward is clear: hybrid AM + PM-HIP is not just a promising research direction but is also potentially an industrially relevant pathway that can reshape how nuclear-grade components are designed, qualified, and deployed.

36 MATERIALS SCIENCE↗

NASA Reference Motor Designs for Electric Vertical Takeoff and Landing Vehicles

Electric and hybrid electric vertical takeoff and landing vehicles require high performance and high reliability electric motor drivetrains. Failure analysis of NASA’s Revolutionary Vertical Lift Technologies’ reference vehicles pointed to current electric motor drivetrain reliability being below what is needed to meet the expected stringent reliability requirements for Urban Air Mobility vehicles. In this paper, design studies are carried out for UAM vehicle electric motors to produce reference designs. The primary intent of these reference motor designs is to provide guidance for UAM motor reliability model development and technology advancement. They additionally provide high fidelity motor sizing information for vehicle designers and references for different technologies or motor topologies to be traded against.

Electric Motor Urban Air Mobility↗

System Architectural Considerations on Reliable Guidance, Navigation, and Control (GN and C) for Constellation Program (CxP) Spacecraft

This final report summarizes the results of a comparative assessment of the fault tolerance and reliability of different Guidance, Navigation and Control (GN&C) architectural approaches. This study was proactively performed by a combined Massachusetts Institute of Technology (MIT) and Draper Laboratory team as a GN&C "Discipline-Advancing" activity sponsored by the NASA Engineering and Safety Center (NESC). This systematic comparative assessment of GN&C system architectural approaches was undertaken as a fundamental step towards understanding the opportunities for, and limitations of, architecting highly reliable and fault tolerant GN&C systems composed of common avionic components. The primary goal of this study was to obtain architectural 'rules of thumb' that could positively influence future designs in the direction of an optimized (i.e., most reliable and cost-efficient) GN&C system. A secondary goal was to demonstrate the application and the utility of a systematic modeling approach that maps the entire possible architecture solution space.

Dennehy, Cornelius J.↗

Performance Analysis and Simulaion of the Hydraulic Scram System in TREAT Reactor

The Transient Reactor Test Facility (TREAT) at Idaho National Laboratory (INL) serves a vital role in nuclear fuel safety research, enabling transient experiments that simulate reactivity excursions and accident scenarios. Central to these operations is the transient control rod drive system (TCRDS), which drives rapid motion of the transient control rods such that TREAT can simulate rapid power changes typical of reactor accidents. The reliability and performance of this system are critical for protecting both fuel specimens and reactor infrastructure. This study presents the initial phase of a two-year investigation into the dynamics and reliability of the TREAT hydraulic TCRDS. Conducted in collaboration with INL, the research employs a combined computational and experimental approach to analyze the system's response time, pressure transients, and potential failure modes. Emphasis is placed on understanding how fluid characteristics influence the TCRDS’s ability to achieve both rapid power changes and mechanical stability. The TRDS and the skid that powers it will be analyzed throughout this investigation. Computational modeling using computational fluid dynamics (CFD) will simulate the hydraulic response under varying conditions. In parallel, experimental testing planned at INL will validate these models and capture key performance metrics. This paper outlines the system design, analytical framework, and modeling strategies that form the foundation for later testing. Ultimately, this work aims to support improvements to the TCRDS’s design and reliability, contributing to the broader goal of enhancing nuclear fuel safety and sustaining TREAT’s mission as a premier nuclear fuel test facility.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Tracking and Data Relay Satellite (TDRS) Orbit Estimation Using an Extended Kalman Filter

Alternatives to the Tracking and Data Relay Satellite (TDRS) orbit estimation procedure were studied to develop a technique that both produces more reliable results and is more amenable to automation than the prior procedure. The Earth Observing System (EOS) Terra mission has TDRS ephemeris prediction 3(sigma) requirements of 75 meters in position and 5.5 millimeters per second in velocity over a 1.5-day prediction span. Meeting these requirements sometimes required reruns of the prior orbit determination (OD) process, with manual editing of tracking data to get an acceptable solution. After a study of the available alternatives, the Flight Dynamics Facility (FDF) began using the Real-Time Orbit Determination (RTOD(Registered TradeMark)) Kalman filter program for operational support of TDRSs in February 2007. This extended Kalman filter (EKF) is used for daily support, including within hours after most thrusting, to estimate the spacecraft position, velocity, and solar radiation coefficient of reflectivity (C(sub R)). The tracking data used are from the Bilateration Ranging Transponder System (BRTS), selected TDRS System (TDRSS) User satellite tracking data, and Telemetry, Tracking, and Command (TT&C) data. Degraded filter results right after maneuvers and some momentum unloads provided incentive for a hybrid OD technique. The results of combining EKF strengths with the Goddard Trajectory Determination System (GTDS) Differential Correction (DC) program batch-least-squares solutions, as recommended in a 2005 paper on the chain-bias technique, are also presented.

Ward, Douglas T.↗

An Approach to Dynamic Human Reliability Analysis Using the EMRALD Dynamic Risk Assessment Tool

There is a need for research into dynamic human reliability analysis (HRA) (i.e., simulation- or computation-based HRA), as many researchers have emphasized the importance of applying dynamic approaches to probabilistic safety assessments (PSAs). This study proposes the Procedure-based Investigation Method of EMRALD Risk Assessment – Human Reliability Analysis (PRIMERA-HRA), a dynamic HRA approach based on the Event Modeling Risk Assessment Using Linked Diagram (EMRALD) software developed by Idaho National Laboratory (INL). This study suggests how this software can be used to model human actions and evaluate error probabilities. The applicability of this approach is also be investigated in light of an extended loss of AC power (ELAP) scenario. This paper then discusses the major insights derived by comparing this dynamic HRA approach against the static one.

99 GENERAL AND MISCELLANEOUS↗

Phase Identification in Synchrotron X-ray Diffraction Patterns of Ti–6Al–4V Using Computer Vision and Deep Learning

X-ray diffraction patterns contain information about the atomistic structure and microstructure (defect population) of materials, extracting detailed information from diffraction patterns is complex, demanding and relies on prior knowledge. Here, we hypothesize that deep-learning techniques can help to perform an effective and accurate analysis with high throughput rates. To demonstrate this concept, we applied a novel deep learning framework to determine the evolution of the β-phase volume fraction in a Ti–6Al–4V alloy during heat-treatment from video sequences of 2D diffraction patterns recorded in transmission and with highly monochromatic radiation in a synchrotron beamline. In particular, we studied the impact of network design on prediction reliability and computational performance. Networks of different architectures were trained using 3008 experimental 2D patterns. A well-tuned model was found to reproduce the phase fractions of another experimental data set, consisting of 1100 diffraction patterns, with a mean-square error as small as 2.6 x 10 -4 . The average prediction error of β-phase volume fraction was within 1.6 x 10 -2 (in each diffraction pattern) of the values obtained by conventional methods. Our work demonstrates that convolutional neural networks can evaluate high energy X-ray diffraction patterns with a remarkable level of reliability. Furthermore, it demonstrates the significance of network design on the reliability of predictions and computational performance. The most complex models do not necessarily result in highest accuracy and may even fail to learn from the data.

36 MATERIALS SCIENCE↗

Multi-module-based CVAE to predict HVCM faults in the SNS accelerator

We present a multi-module framework based on Conditional Variational Autoencoder (CVAE) to detect anomalies in the power signals coming from multiple High Voltage Converter Modulators (HVCMs). We condition the model with the specific modulator type to capture different representations of the $\mathcal{normal}$ waveforms and to improve the sensitivity of the model to identify a specific type of fault when we have limited samples for a given module type. We studied several Artificial Neural Network (ANN) architectures for our CVAE model and evaluated the model performance by looking at their loss landscape for stability and generalization. Our results for the Spallation Neutron Source (SNS) experimental data show that the trained model generalizes well to detecting multiple fault types for several HVCM module types. The results of this study can be used to improve the HVCM reliability and overall SNS uptime.

43 PARTICLE ACCELERATORS↗

Passive heat removal in horizontally oriented micro-HTGRs

There are novel, horizontally oriented high-temperature gas-cooled micro-reactor (HTGR) designs under consideration because of their portability, simplicity, and reliable operation. These features of the micro-HTGR design can meet the fission battery attributes, such as economic, standardize, installed, unattended and reliable. Although there have been HTGR related safety studies, micro-HTGRs when horizontally oriented are expected to exhibit significantly different thermal physics. During the unavailability of helium circulation, the internal reactor core is designed to cool by block-to-block conduction and radiation, and the reactor vessel surface is cooled by the ambient air. This scenario is anticipated during the transport of the micro-HTGR in a shipping container. The conduction and radiation between the prismatic micro-HTGR blocks in the core can be influenced by variances in the thermal contacts. This work investigated the conduction within a simulated horizontal HTGR core. An experimental setup was used to validate a numerical model. The experimental setup consisted of a hexagonal assembly with scaled prismatic blocks placed within a high-temperature vacuum environment. The gaps between the blocks were well controlled and monitored. The experimental setup was designed in such a way that the temperature variation in the axial direction was minimal, such that the experiment could be observed as a 2D (r, ) heat transfer problem. The pressurized tube was equipped with Infra-Red (IR) transparent windows, and an IR camera was used to capture the spatio-temporal temperature evolution in the hexagonal block assembly during the cooldown experiments. The experimental scenario was computationally modeled with a finite element analysis (FEA) program. Once validated, the computational model was used to investigate the impact of gap conductance on overall decay heat removal. Using a conservative estimate for gap conductance value (100 W/m 2 -K) between the prismatic blocks, there is a negligible increase in temperature observed during decay heat generation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Material characterization of seven photovoltaic backsheets using seven accelerated test conditions

A variety of polymeric backsheet materials can be found in fielded photovoltaic (PV) modules, mostly based on fluoropolymer and polyethylene terephthalate (PET) materials. Cost reduction and sustainability considerations drive the recent development of alternative backsheet materials and designs [1]. In some fielded PV installations, polymeric materials are susceptible to environmental degradation in the form of backsheet cracking. To prevent backsheet degradation that can result in a module failure, thorough laboratory reliability testing is needed. In this report we studied the durability of seven commercial and experimental PV backsheets through accelerated stress testing using seven photolytic, hygrometric, and custom tests with the goal to understand if novel fluoropolymer-free backsheets are sufficiently environmentally durable to be commercialized. We divided the mechanisms observed during aging into two categories: core degradation and surface degradation. Although core degradation due to hydrolysis was observed in all commercial PET-, and polyamide (PA)-based backsheets aged with 85 degrees C/85% relative humidity, this test is unlikely to be field relevant. Photo-oxidative reactions on the exposed surface during UV weathering affected all seven backsheets regardless of the outer layer polymer material and additives. This degradation was limited to the outermost micrometers of the surface, except for backsheets containing PA-12, which resulted in surface cracking. A custom test combining UV with water spray caused the most severe backsheet degradation, including surface erosion and loss of insulating properties in polyolefin (PO)- and PA-based backsheets. This highlights the importance of combined accelerated stress testing to screen for complex backsheet degradation mechanisms. We also showed that, with material and design optimization, coextruded experimental PO-based backsheets have the potential to be a durable alternative to commercial PET- and fluoropolymer-based PV backsheets.

14 SOLAR ENERGY↗

Detecting onset of lithium plating during fast charging of Li-ion batteries using operando electrochemical impedance spectroscopy

Electrochemical plating of Li metal on the graphite electrode is the key limitation behind slow charging times of Li-ion batteries (LIBs) in electric vehicles (EVs). Currently, electrochemical methods to detect the onset of Li plating while a battery is fast charging are sparse. In this study, we use operando electrochemical impedance spectroscopy to reliably detect the onset of Li plating on graphite electrodes in three-electrode LIBs. An increase in the graphite solid-electrolyte interface (SEI) resistance indicates that Li plating has occurred. By cross-validating with a highly sensitive ex situ chemical titration, we determine that this technique can detect very small amounts of plated Li (<0.6% of the graphite electrode's capacity). We also offer physical explanations for the observed impedance behavior. Finally, we show that this technique can be applied to standard two-electrode LIB systems, making the method an important step toward safely implementing fast charging protocols for LIBs in EVs.

25 ENERGY STORAGE↗

Vertical variation of turbulent entrainment mixing processes in marine stratocumulus clouds using high-resolution digital holography

Marine stratocumulus clouds contribute signi?cantly to the Earth’s radiation budget due to their extensive coverage and high albedo. Yet, subgrid variability in cloud properties such as aerosol concentration, droplet number and precipitation rates lead to considerable errors in global climate models. While these clouds usually have small vertical ex-tent, turbulent entrainment-mixing and precipitation can generate signi?cant variations in droplet number, size and relative dispersion with altitude. In this paper, we analyze turbulent entrainment-mixing processes and the variability in cloud microphysical properties as a function of height within a warm marine stratocumulus cloud layer over the Eastern North Atlantic. We use high resolution airborne holographic measurements and compare them with local turbulence measurements. We ?nd that entrainment-mixing is primarily inhomogeneous near cloud top leading to larger droplet sizes and homogeneous near cloud base leading to smaller droplet sizes. Further analysis of Damk¨ohler number measurements are able to explain the mixing mechanisms at di?erent cloud heights, reinforcing the importance of turbulent mixing and microphysical time scales in deter-mining cloud microphysics.

Desai, Neel↗

Machine learning interatomic potential for silicon-nitride (Si 3 N 4 ) by active learning

Silicon nitride (Si 3 N 4 ) is an extensively used material in the automotive, aerospace, and semiconductor industries. However, its widespread use is in contrast to the scarce availability of reliable interatomic potentials that can be employed to study various aspects of this material on an atomistic scale, particularly its amorphous phase. In this work, we developed a machine learning interatomic potential, using an efficient active learning technique, combined with the Gaussian approximation potential (GAP) method. Our strategy is based on using an inexpensive empirical potential to generate an initial dataset of atomic configurations, for which energies and forces were recalculated with density functional theory (DFT); thereafter, a GAP was trained on these data and an iterative re-training algorithm was used to improve it by learning on-the-fly. When compared to DFT, our potential yielded a mean absolute error of 8 meV/atom in energy calculations for a variety of liquid and amorphous structures and a speed-up of molecular dynamics simulations by 3–4 orders of magnitude, while achieving a first-rate agreement with experimental results. Our potential is publicly available in an open-access repository.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Investigating microstructure evolution in block copolymer membranes

Block copolymer self-assembly in conjunction with nonsolvent-induced phase separation (SNIPS) has been increasingly leveraged to fabricate integral-asymmetric membranes. The large number of formulation and processing parameters associated with SNIPS, however, has prevented the reliable construction of high performance membranes. In this study, we apply dynamical self-consistent field theory to model the SNIPS process and investigate the effect of various parameters on the membrane morphology: solvent selectivity, nonsolvent selectivity, initial film composition, and glass transition composition. We examine how solvent selectivity and concentration of polymers in the film impact the structure of micelles that connect to form the membrane matrix. In particular, we find that preserving the order in the surface layer and forming a connection between the supporting and surface layer are nontrivial and sensitive to each parameter studied. Furthermore, the effect of each parameter is discussed, and suggestions are made for successfully fabricating viable block copolymer membranes.

36 MATERIALS SCIENCE↗

High-Fidelity CFD Assessments of Flow Resistance in a 61-Pin Wire-Wrapped Assembly with Partially Blocked Channels

The examination of thermal-hydraulic behaviors in wire-wrapped rod bundles continues to be an active area of research. The sodium fast reactor, a prominent candidate in next-generation nuclear designs, utilizes a hexagonal configuration of wire-wrapped fuel pins. Here, the potential for channel blockage within this compact arrangement poses a significant safety challenge, spurring a number of recent experimental and computational investigations to evaluate its impact on flow and heat transfer. The present work aims to benchmark the high-fidelity NekRS computational fluid dynamics (CFD) solver in predicting the pressure drops associated with substantial blockages, using available experimental data as a reference. A 61-pin wire-wrapped fuel assembly with two flow blockage configurations has been simulated and investigated at a range of low to moderate Reynolds numbers (487 ≤ Re ≤ 14 600). The NekRS solver demonstrates an exponential reduction of spatial discretization error with increasing polynomial order. The high level of agreement between the numerical results and measured data confirms the accuracy and consistency of the present numerical approach. This benchmark study establishes the capability of NekRS to perform reliable hydrodynamic simulations for sodium fast reactor applications and supports its use in design, licensing, and safety analyses.

CFD Benchmarking↗

Tritium Breeding Ratio Evaluation of Solid Breeder Concepts for the FESS-FNSF

This paper presents a parametric study of the Fusion Energy System Studies-Fusion Nuclear Science Facility’s (FNSF’s) tritium breeding performance for several solid breeder concepts, neutron multiplying materials, and blanket materials, assuming volume fractions based on the most recent FNSF design as a realistically representative fusion facility. In this study, we initially surveyed the tritium breeding ratio (TBR) of several solid breeder concepts by employing a simplified but efficient one-dimensional (1-D) infinite cylinder reduced-order model (ROM). Parametric studies were performed with the ROMs for the full range of breeder-to-multiplier ratios to identify the optimum mixture compositions for each breeder type that would lead to a maximum TBR. These optimized breeder-multiplier combinations were then homogenized with FNSF blanket component materials to estimate their impacts on the TBR. Subsequently, as a validation step for the optimal designs, TBR calculations were performed using a more realistic modified 1-D ROM with inner and outer breeding regions, as well as with a fully detailed 22.5-deg three-dimensional (3-D) sector of the FNSF to assess the impact of geometry details on the TBR. The differences between the two 1-D models were negligible, while the ROMs were able to correctly predict trends and identify the maximum and minimum TBR cases, as well as show consistent biases relative to the results produced by the full 3-D, 22.5-deg sector for specific breeder/multiplier combinations. Solid breeder concepts such as Li 2 O, Li 4 SiO 4 , and Li 8 ZrO 6 outperformed all others in this study in terms of TBR performance when combined with all the neutron multiplier materials selected. Here, an underlying goal of this study was to develop and improve rapid and reliable ROMs to aid designers during parametric optimizations of highly complex and computationally expensive fusion models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗