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DOE OSTI2021

A Discussion of Strength Reduction Factor Development for Thermal Aging Effect on Nuclear Structural Alloys

In consideration of structural alloy property deterioration during long-term exposure to elevated temperatures, the yield and ultimate tensile strength reduction factors are provided in the Boiler and Pressure Vessel Code Section III for nuclear reactor component design and operation analysis. Because the Gen IV reactor requirement of 40 ~ 60 years of service life makes it difficult to acquire such long exposure test data for developing the reduction factors, they must be derived from test data with relatively short exposure by predictive methods considered to be reasonably reliable. A novel approach with a physically-based model has recently been proposed for application to development of reduction factors for 9Cr-1Mo-V. In the model, contributors to the tensile strength are first identified and related to definite microstructural features of the alloy, then some physically-based methods are employed to simulate the microstructural evolution, and finally the model is assembled with test-data-calibrated parameters to generate the yield and ultimate tensile strength reduction factors covering elevated temperature exposure for up to 57 years. The approach is undoubtedly a trailblazing development that will, if proven reliable, lead to a paradigm shift in predicting thermal aging behavior of many other alloys. Its debut application to Section III, however, concerns nuclear safety and naturally warrants objective, impartial, and thorough technical scrutiny. In the present paper, the novel and conventional approaches are discussed. Necessary improvements to the novel approach are recommended for its application to nuclear structural component design and analysis, and for its potential expanded use to other alloys.

Ren, Weiju↗

NASA NTRS2018

Composite Overwrapped Pressure Vessel (COPV) Life Test

Recent attention has been focused on how NASA and its commercial partners have been placing less emphasis on testing and have become more dependent on analytical methods when evaluating design margins for fracture-critical components. Of high concern is the possible misuse of such analytic models for thin-walled metallic liners for composite overwrapped pressure vessels (COPVs). The NASA Engineering and Safety Center (NESC) has initiated an assessment to understand the limitations of linear-elastic fracture mechanics (LEFM) computational methods used to predict fatigue crack growth rate behavior of small cracks in thin metal liners for COPVs. It has been observed that fabrication of some thin metallic liners results in a wide variation in microstructure morphology, which results in varying microscale crack growth mechanisms. The ultimate goal is to develop and demonstrate a test-based methodology validating the safe-life requirements for COPVs with thin, elastically responding metal liners where LEFM methods are not appropriate.

Russell, Richard↗

NASA NTRSDate not supplied

Modeling and Sensitivity Analysis of Sandwich Composite Cylinders with Geometric Imperfections

It is well known that real shell structures can have significantly lower buckling loads and even different mode shapes than the theoretical predictions for perfect structures. Much of this difference can be attributed to geometric and loading imperfections, and geometrically nonlinear effects. The realistic buckling response can be investigated using geometrically nonlinear finite element analyses and including radial imperfections. Such analyses are used in the NASA Engineering and Safety Center Shell Buckling Knockdown Factor Project, which has the goal of developing new analysis-based buckling design recommendations for select classes of cylindrical shell structures under uniaxial compressive load. The approach for modeling several sandwich composite cylinders with two-dimensional general-purpose shell elements and the influence of the element type selection and element size on the buckling load is discussed. The influence of geometric imperfections of various magnitudes on buckling behavior of a sandwich composite cylinder was also investigated.

Structural Modeling↗

NASA NTRSDate not supplied

Modeling and Sensitivity Analysis of Sandwich Composite Cylinders with Geometric Imperfections

It is well known that manufactured shell structures can have significantly lower buckling loads and different mode shapes than the theoretical predictions for perfect structures. Much of this difference can be attributed to geometric and loading imperfections, and geometrically nonlinear effects. The buckling response of cylindrical structures can be investigated using geometrically nonlinear finite element analyses and including radial imperfections. Such analyses are used in the NASA Engineering and Safety Center Shell Buckling Knockdown Factor Project, which has the goal of developing new analysis-based buckling design recommendations for select classes of cylindrical shell structures under uniaxial compressive load. The approach for modeling several sandwich composite cylinders with two-dimensional general-purpose shell elements and the influence of the element type selection and element size on the buckling load is discussed. The influence of geometric imperfections of various magnitudes on buckling behavior of a sandwich composite cylinder was also investigated.

Structural Modeling↗

NASA NTRSDate not supplied

: Modeling and Sensitivity Analysis of Sandwich Composite Cylinders with Geometric Imperfections

Structural Modeling↗

NASA NTRS2023

Metallurgical Factors that Govern ST Properties in Commercial 2219-T87 Thick Plate

This report is contained within a NASA Engineering & Safety Center (NESC) assessment of the variability in short-transverse (ST) mechanical properties of commercial lots of 12.7-cm-thick 2219-T87 plate. The document comprises a review of the potential metallurgical reasons for the variations in ST tensile ductility and fracture behavior observed. Preliminary data from through-thickness mechanical testing and microstructural analyses conducted early in the investigation are referenced. The report concludes with a summary of considerations for the NESC based on the key results of this literature survey.

Aluminum alloy↗

DOE OSTI2022

Transient Analysis of a Micro-reactor using the DireWolf Code Suite

Transient analyses of heat pipe micro-reactors are necessary to ensure that hypothetical accident scenarios do not comprise reactor safety. Due to its small size and reliance on heat-pipes for cooling, the micro-reactor design introduced in this paper is a tightly coupled system which requires multi-physics tools to accurately model transient events. Idaho National Laboratory’s DireWolf code suite based on the MOOSE framework is tailor-built to model heat-pipe reactors. This paper demonstrates DireWolf’s ability to simulate the coupled thermal-neutronics transient behavior of a heat-pipe micro-reactor. The transient events presented here include an inadvertent rotation of all control drums simultaneously and a sudden complete ejection of a single control drum. A detailed description of each event is provided along with simulation results, including time dependent power and temperature distributions, and discussion. This is a Westinghouse Electric Company (WEC) led publication.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2026

Estimation of Fission Product Transport Parameters for Cesium in the AGR-3/4 TRISO Fuel Experiment

A one-dimensional (1D) finite-element model of fission product transport in the AGR-3/4 experiment has been developed using the Multiphysics Object Oriented Simulation Environment (MOOSE) framework and implemented in the fuel performance code, BISON. The model resolves capsule-specific geometries, materials, and temperature histories and simulates radial migration of fission products from the fuel compact through the inner ring, outer ring, and into the sink ring. Model parameters governing diffusion and sorption were estimated for key fission products – cesium (Cs), and europium (Eu) – by simultaneously fitting modeled isotopic concentration profiles and total ring inventories to a post-irradiation experimental measurement. These data include gamma scanning, liquid scintillation for Sr-90, radial deconsolidation leach-burn-leach analysis, tomographic reconstructions, and destructive physical sampling. A mortar-based interfacial sorption framework was implemented to enforce physically consistent mass transfer and flux conservation across gas gaps. Two classes of parameter sets were derived: a least-squares best-fit, and a safety-oriented conservative-fit, what applies strong penalties for underprediction of sink inventories. Across all twelve capsules, the model successfully reproduces the dominant radial transport trends for Cs, Sr, with decreasing concentrations from the compact outward through successive rings. Cs behavior is captured most consistently, while strontium predictions reveal systematic trade-offs between compact accuracy and conservative sink-ring bounding. The results demonstrate that sink ring weighted calibration provides conservative, safety relevant bounds on low temperature fission product transport, but at the cost of underpredicting compact inventories for Sr isotopes. These discrepancies highlight the need for additional physics, including fast-slow diffusion model, incorporating trapping mechanism in the transport behavior. Overall, this work establishes a robust, capsule-specific modeling framework for AGR-3/4 fission product transport and provides a defensible basis for parameter selection in source-term and fuel performance analyses for high temperature gas-cooled reactors.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS2014

Towards Run-time Assurance of Advanced Propulsion Algorithms

This paper covers the motivation and rationale for investigating the application of run-time assurance methods as a potential means of providing safety assurance for advanced propulsion control systems. Certification is becoming increasingly infeasible for such systems using current verification practices. Run-time assurance systems hold the promise of certifying these advanced systems by continuously monitoring the state of the feedback system during operation and reverting to a simpler, certified system if anomalous behavior is detected. The discussion will also cover initial efforts underway to apply a run-time assurance framework to NASA's model-based engine control approach. Preliminary experimental results are presented and discussed.

run time assurance↗

NASA NTRSDate not supplied

Sensor-based Prognostics for Safe Batteries for Electric Aircraft

With a new start awarded under CAS for Fiscal Year 2020, the Sensor-based Prognostics to Avoid Runaway Reactions and Catastrophic Ignition project, or SPARRCI, aims to eliminate safety risks of lithium-ion and next-generation lithium-based batteries. SPARRCI is taking a deeper dive into the inner workings of battery cells by introducing miniature multifunctional sensors within the cells to detect early signs of failure. Combined with nondestructive evaluation techniques to gather complementary battery health data, battery data will be monitored in real-time via prognostics which will ultimately be able to identify when the cell is exhibiting abnormal behavior bordering on failure, with the ability to provide early warning such that the battery may be taken offline prior to catastrophic failure events.

Brianne Demattia↗

DOE OSTI2024

Interplay of intercalation dynamics and lithium plating in monolithic and architectured graphite anodes during fast charging

Fast charging of high-capacity anodes is challenging due to lithium plating reactions, which lead to poor cycling performance and safety concerns. Thus, accurate predictions of plating onset and an understanding of this electrochemical process are crucial for robust battery design. However, the most commonly used models, based on porous electrode theory (e.g., the pseudo-2D model), are notoriously difficult to calibrate due to their complexity, limiting their predictive power. This work studies the process of lithium plating during fast charging of (small-particle) graphite half-cells by measuring local reaction progression and plating behavior using optical operando techniques. These experiments employ a realistic 1D graphite electrode geometry with commercially-relevant mass loading charged at fast charge rates. It is demonstrated that the local reaction progression and plating onset can not only be predicted accurately with a p2D numerical model, but that these processes follow a simple scaling law. Remarkably, the entire reaction histories of different electrodes charged at different rates (e.g., 160 μm thickness at 0.5C, 111 μm at 1C or 66 μm at 4C) were observed to have self-similar intercalation profiles. It is demonstrated that plating onset is in turn governed by the reaction profile which explains why both processes exhibit the same scaling behavior. Finally, operando measurements of local reaction dynamics are conducted for the first time in electrodes with channeled architectures, quantitatively determining how channels affect reaction uniformity and plating onset. Together, these results reveal underlying simplicity in the complex electrochemical environment of fast charging and lithium plating, improving understanding of this process. These fundamental insights are broadly applicable for design processes, modeling and experimental evaluation of lithium ion batteries.

25 ENERGY STORAGE↗

NASA NTRS2003

Transferring Knowledge from Observations and Models to Decision Makers: An Overview and Challenges

Over the last 25 years, a tremendous progress has been made in the Earth science space-based remote sensing observations, technologies and algorithms. Such advancements have improved the predictability by providing lead-time and accuracy of forecast in weather, climate, natural hazards, and natural resources. It has further reduced or bounded the overall uncertainties by partially improving our understanding of planet Earth as an integrated system that is governed by non-linear and chaotic behavior. Many countries such US, European Community, Japan, China and others have invested billions of dollars in developing and launching space-based assets in the low earth (LEO) and geostationary (GEO) orbits. However, the wealth of this scientific knowledge that has potential of extracting monumental socio-economic benefits from such large investments have been slow in reaching to public and decision makers. For instance, there are a number of areas such as energy forecasting, aviation safety, agricultural competitiveness, disaster management, security, air quality and public health can directly take advantage. Nevertheless, we all live in a global economy that depends on access to the best available Earth Science information for all inhabitants of this planet. This paper surveys and examines a number such applications in terms of their architecture, maturity and economic applicability as they apply to the societal needs. A detailed analysis is also presented of various challenges and issues that pertain to a number of areas such as: (1) difficulties in making a speedy transition of data and information from observations and models to relevant Decision Support Systems (DSS) or tools, (2) data and models inter-operability issues, (3) limitations of spatial, spectral and temporal resolution, (4) communication limitations as dictated by the availability of image processing and data compression techniques. Additionally, the most critical element amongst all is the organizational and management boundaries that must be resolved at local, state, national and international levels to implement and realize free flow of such vital information. This paper also makes attempts to address this topic and discuss possible approaches to deal with this quandary.

Habib, Shahid↗

NASA NTRS2008

Development of COPVS for High pressure, In-Space, Cryogenic Fuel Storage

Polymeric composite overwrapped pressure vessels (COPVs) provide an attractive material system to support developing commercial launch business and alternate fuel ventures. However to be able to design with these materials, the mechanical behavior of the materials must be understood with regards to processing, performance, damage tolerance, and environment. For the storage of cryogenic propellants, it is important to evaluate the materials performance and impact damage resistance at cryogenic temperatures in order to minimize weight and to ensure safety and reliability. To evaluate the ultimate performance, various polymeric COPV's have been statically burst tested at cryogenic conditions before and after exposure to irradiation. Materials selected for these COPVs were based on the measured mechanical properties of candidate resin systems and fibers that were also tested at cryogenic conditions before and after exposure to irradiation. The correlation of COPV burst pressures with the constituent material properties has proven to be a valuable screening method for selection of suitable candidate materials with resistance to material degradation due to exposure to temperature and radiation.

DeLay, Tom↗

NASA NTRSDate not supplied

Development of a Digital Twin for Electrified Aircraft Powertrain Health Management

The augmentation of aircraft powertrains with electrical power systems is a promising path to reducing aircraft fuel consumption, emissions, and noise. Like conventional propulsion systems, electrified aircraft propulsion (EAP) systems will be subject to wear and tear throughout their lifecycles. System health management for EAP will enable efficient flight and maintenance scheduling, realizing economic, safety, and reliability benefits. A digital twin is, broadly, a dynamically updated virtual representation of an individual physical asset. This paper presents a Kalman filter-based approach for the development of a digital twin for an electrified powertrain and applies the approach to an EAP controls testbed. Measurements from nominal testbed operations are used to update a nonlinear model of the testbed. A Kalman filter is then created and used to identify and isolate anomalous testbed behavior based on measurements from off- nominal operations. Results show that the Kalman filter-based digital twin can monitor individual powertrain components’ health for degradation or other changes in performance. The applicability of the presented digital twin approach to any hybrid- or fully-electrified powertrain is emphasized.

Electrified Aircraft Propulsion↗

DOE OSTI2012

Standardized Testing Program for Solid-State Hydrogen Storage Technologies

In the US and abroad, major research and development initiatives toward establishing a hydrogen-based transportation infrastructure have been undertaken, encompassing key technological challenges in hydrogen production and delivery, fuel cells, and hydrogen storage. However, the principal obstacle to the implementation of a safe, low-pressure hydrogen fueling system for fuel-cell powered vehicles remains storage under conditions of near-ambient temperature and moderate pressure. The choices for viable hydrogen storage systems at the present time are limited to compressed gas storage tanks, cryogenic liquid hydrogen storage tanks, chemical hydrogen storage, and hydrogen absorbed or adsorbed in a solid-state material (a.k.a. solid-state storage). Solid-state hydrogen storage may offer overriding benefits in terms of storage capacity, kinetics and, most importantly, safety. The fervor among the research community to develop novel storage materials had, in many instances, the unfortunate consequence of making erroneous, if not wild, claims on the reported storage capacities achievable in such materials, to the extent that the potential viability of emerging materials was difficult to assess. This problem led to a widespread need to establish a capability to accurately and independently assess the storage behavior of a wide array of different classes of solid-state storage materials, employing qualified methods, thus allowing development efforts to focus on those materials that showed the most promise. However, standard guidelines, dedicated facilities, or certification programs specifically aimed at testing and assessing the performance, safety, and life cycle of these emergent materials had not been established. To address the stated need, the Testing Laboratory for Solid-State Hydrogen Storage Technologies was commissioned as a national-level focal point for evaluating new materials emerging from the designated Materials Centers of Excellence (MCoE) according to established and qualified standards. Working with industry, academia, and the U.S. government, SwRI set out to develop an accepted set of evaluation standards and analytical methodologies. Critical measurements of hydrogen sorption properties in the Laboratory have been based on three analytical capabilities: 1) a high-pressure Sievert-type volumetric analyzer, modified to improve low-temperature isothermal analyses of physisorption materials and permit in situ mass spectroscopic analysis of the sample’s gas space; 2) a static, high-pressure thermogravimetric analyzer employing an advanced magnetic suspension electro-balance, glove-box containment, and capillary interface for in situ mass spectroscopic analysis of the sample’s gas space; and 3) a Laser-induced Thermal Desorption Mass Spectrometer (LTDMS) system for high thermal-resolution desorption and mechanistic analyses. The Laboratory has played an important role in down-selecting materials and systems that have emerged from the MCoEs.

08 HYDROGEN↗

DOE OSTI2025

Virtual Reality for Shoot/No-Shoot Decision Training in Law Enforcement: A Literature Review and Research Agenda

Virtual reality (VR) can materially improve “shoot / no-shoot” (SNS) training by giving officers realistic, repeatable practice making high-stakes decisions under pressure. Traditional tools—live-fire ranges and video simulators—build basics, but they cannot adapt to each officer in real time or fully mirror the complexity of the field. VR closes that gap by creating immersive scenarios that are safer, more flexible, easier to scale across units, and able to capture objective performance data. SNS decisions are not just about marksmanship; they rely on perception, judgment, memory, and the ability to hold fire when a threat is uncertain. Effective training therefore needs realism, decision complexity, and branching outcomes that reflect the true consequences of choices. These elements strengthen recognition of hostile intent while reducing false positives and building the self-control required in ambiguous situations. VR brings specific advantages: dynamic environments, full-body interaction, and the ability to measure performance with precision—enabling targeted feedback and better transfer of learning to the street. At the same time, responsible deployment must address scenario quality (credible environments and behaviors), lawful decision models, and user wellbeing (appropriate stress levels, comfort, and safety). Sandia’s VIPER Lab is positioned to lead this work. The team combines human-performance science, AI/ML, and VR/AR development with a deep equipment bench (e.g., omnidirectional treadmill, eye-tracking, haptics, multiple HMDs). This ecosystem supports building and validating next-generation SNS training that is immersive, measurable, and trustworthy. Bottom line: Investment in VR-enabled SNS training that blends evidence-based design with careful validation and legal safeguards is expected to pay off in safer, more consistent decision-making and improved community trust, delivered through training that is practical to deploy at scale.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

NASA NTRS2016

Modeling in the State Flow Environment to Support Launch Vehicle Verification Testing for Mission and Fault Management Algorithms in the NASA Space Launch System

Analysis methods and testing processes are essential activities in the engineering development and verification of the National Aeronautics and Space Administration's (NASA) new Space Launch System (SLS). Central to mission success is reliable verification of the Mission and Fault Management (M&FM) algorithms for the SLS launch vehicle (LV) flight software. This is particularly difficult because M&FM algorithms integrate and operate LV subsystems, which consist of diverse forms of hardware and software themselves, with equally diverse integration from the engineering disciplines of LV subsystems. M&FM operation of SLS requires a changing mix of LV automation. During pre-launch the LV is primarily operated by the Kennedy Space Center (KSC) Ground Systems Development and Operations (GSDO) organization with some LV automation of time-critical functions, and much more autonomous LV operations during ascent that have crucial interactions with the Orion crew capsule, its astronauts, and with mission controllers at the Johnson Space Center. M&FM algorithms must perform all nominal mission commanding via the flight computer to control LV states from pre-launch through disposal and also address failure conditions by initiating autonomous or commanded aborts (crew capsule escape from the failing LV), redundancy management of failing subsystems and components, and safing actions to reduce or prevent threats to ground systems and crew. To address the criticality of the verification testing of these algorithms, the NASA M&FM team has utilized the State Flow environment6 (SFE) with its existing Vehicle Management End-to-End Testbed (VMET) platform which also hosts vendor-supplied physics-based LV subsystem models. The human-derived M&FM algorithms are designed and vetted in Integrated Development Teams composed of design and development disciplines such as Systems Engineering, Flight Software (FSW), Safety and Mission Assurance (S&MA) and major subsystems and vehicle elements such as Main Propulsion Systems (MPS), boosters, avionics, Guidance, Navigation, and Control (GN&C), Thrust Vector Control (TVC), liquid engines, and the astronaut crew office. Since the algorithms are realized using model-based engineering (MBE) methods from a hybrid of the Unified Modeling Language (UML) and Systems Modeling Language (SysML), SFE methods are a natural fit to provide an in depth analysis of the interactive behavior of these algorithms with the SLS LV subsystem models. For this, the M&FM algorithms and the SLS LV subsystem models are modeled using constructs provided by Matlab which also enables modeling of the accompanying interfaces providing greater flexibility for integrated testing and analysis, which helps forecast expected behavior in forward VMET integrated testing activities. In VMET, the M&FM algorithms are prototyped and implemented using the same C++ programming language and similar state machine architectural concepts used by the FSW group. Due to the interactive complexity of the algorithms, VMET testing thus far has verified all the individual M&FM subsystem algorithms with select subsystem vendor models but is steadily progressing to assessing the interactive behavior of these algorithms with LV subsystems, as represented by subsystem models. The novel SFE applications has proven to be useful for quick look analysis into early integrated system behavior and assessment of the M&FM algorithms with the modeled LV subsystems. This early MBE analysis generates vital insight into the integrated system behaviors, algorithm sensitivities, design issues, and has aided in the debugging of the M&FM algorithms well before full testing can begin in more expensive, higher fidelity but more arduous environments such as VMET, FSW testing, and the Systems Integration Lab7 (SIL). SFE has exhibited both expected and unexpected behaviors in nominal and off nominal test cases prior to full VMET testing. In many findings, these behavioral characteristics were used to correct the M&FM algorithms, enable better test coverage, and develop more effective test cases for each of the LV subsystems. This has improved the fidelity of testing and planning for the next generation of M&FM algorithms as the SLS program evolves from non-crewed to crewed flight, impacting subsystem configurations and the M&FM algorithms that control them. SFE analysis has improved robustness and reliability of the M&FM algorithms by revealing implementation errors and documentation inconsistencies. It is also improving planning efficiency for future VMET testing of the M&FM algorithms hosted in the LV flight computers, further reducing risk for the SLS launch infrastructure, the SLS LV, and most importantly the crew.

Trevino, Luis↗

DOE OSTI2025

PSA 2025 DPRA for Cyber Optimization

Cyberattacks can have many different attack paths, durations, and goals. There are also many different mitigation options involving hardware, software, and/or humans. Evaluating defense options should include quantitative evaluation of overall effectiveness to make cost and risk-informed decisions. Typical cyberattack modeling methods only provide a qualitative evaluation and have difficulty with time dependent scenarios. The main areas of cybersecurity are confidentiality, integrity, and availability. For companies with cyber-physical systems such as advanced nuclear reactors, cyber-related integrity is a requirement set by the U.S. Nuclear Regulatory Commission. But companies are also concerned about availability or reliability as a business case. As cyber threats are evolving to a business-for-hire structure, more attacks focus on disrupting business success and reliability, causing financial and economic stability risk. Companies want reliability analysis while optimizing cost, which requires more than safety modeling methods. Dynamic-state-based and Markov-based modeling provides a method for better cyber scenario modeling with timing and conditional features not found in other numerical evaluation methods. EMRALD (Event Modeling Risk Assessment using Lined Diagrams) is a dynamic risk analysis modeling and simulation tool and has features that reduce modeling issues such as state-base explosion found in Markov-based tools. It has been used to model different time-dependent events including plant behavior and operator procedures. As a general modeling tool, EMRALD can also be used to model cyberattack scenarios with varying mitigation options and quantify effectiveness, producing numerical data for risk-informed decisions. This paper uses EMRALD to demonstrate that dynamic risk analysis can be used for cyber threat modeling to provide insights for design decision-making and optimize defense strategies.

97 - MATHEMATICS AND COMPUTING↗