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DOE OSTI2026

UL 1741SC Conformance Development, Evaluation, and Proposal [Slides]

V2G AC is a type of grid interconnection by mobile battery that transforms an EV into a DER with the potential to stabilize the grid and lower costs for electricity. UL 1741SC is a critical new standard to enable grid interconnection of V2G AC-capable vehicles, by defining requirements for V2G AC-intended EVSEs as a gatekeeper between the grid and the EV to support grid safety, such as through redundant voltage trip (namely oversight). EVSE manufacturers need a clear set of conformance test cases and criteria by which to evaluate their equipment and confirm the compliance with UL 1741SC, so that the EVSEs performs as intended for the grid safety. Hence, NLR identified necessary conformance tests and performed the tests identified to understand the maturity.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2022

XSP Methane Sensors Test and Evaluation Project “M-Step”

Methane sensor technology is employed in industry sectors from oil and gas to agriculture, landfills, and monitoring of natural emissions. The US oil and gas sector is extensive in scale, critical to fulfilling US energy needs, and deals with commodities presenting enormous challenges for personnel safety and the environment. Thus, it is imperative that they have accurate and responsive sensors to detect hazardous gases such as methane. US space launch systems will increasingly also use liquefied methane and liquefied natural gas (LNG), which is mostly methane, in quantities large and small, as main and auxiliary propulsion and power. Some of these systems will be reusable, which adds the unique challenge of processing a vehicle that has residual commodities and has returned to its launch site to be readied for its next launch. The methane sensors test and evaluation project (M-STEP) began within the context of a reusable launch system, the Defense Advanced Research Projects Agency (DARPA) Experimental Spaceplane (XSP) program, which would have employed a high-pressure gaseous methane and gaseous oxygen reaction control system. Although the XSP partnership between Boeing and DARPA was terminated by Boeing in early 2020, DARPA and KSC have continued to collaborate in the area of gas sensors with the hydrogen sensor test and evaluation project (H-STEP) and with M-STEP. The NASA Launch Services program (LSP) invested in M-STEP in FY 2021 “to evaluate and understand the state-of-the-art in methane gas sensors”. M-STEP and the LSP effort was complementary, pushing in the same direction to understand US launch system stakeholder needs and approaches, requirements internal (NASA) and external, and commercially available or forthcoming methane sensing technologies, practices, and approaches. In addition, M-STEP (as with H-STEP) enhances KSC capabilities and understanding of these technologies, informing agency investments and further research in these areas.

Tracy L. Gibson↗

NASA NTRS2020

Predicting Gate Conflicts at Charlotte Douglas International Airport Using NASA ATD-2 Fused Data Sources

NASA is conducting the Airspace Technology Demonstration-2 to evaluate an Integrated Arrival, Departure, and Surface (IADS) traffic management system. The IADS system is powered by real-time System Wide Information Management feeds which provide an accurate and high fidelity view of the lifecycle of a flight. This data can be leveraged to drive efficiencies in the National Airspace System. For non safety critical applications there is opportunity for third party service providers to offer this type of data-driven prediction service in near real-time. This paper investigates the gate conflict prediction problem as a concrete use case which could help drive efficiencies. We model gate conflicts as a regression problem and describe the iterative process of model building, model validation, and evaluation used to assess the efficacy of our approach. We quantify our predictive accuracy and identify paths for improvement. Through this iterative process we hope to evolve our models and methods to a near real-time prediction service.

Airspace Technology Demonstration 2↗

DOE OSTI2025

Advanced Reactor Designs Security Analysis, Risk, and Recommendations: Risks, Consequences, and Possible by-Design Mitigation Approaches Associated with Select Advanced Reactors

Next-generation advanced reactors (ARs) incorporate enhanced safety systems, have smaller source terms, and feature compact modular designs, which should lessen their collective risk profiles. However, to fully evaluate risk, security needs to be a part of the equation. Without taking security into consideration, safety systems and components in the new ARs may be vulnerable to sabotage. These base attributes, coupled with enhanced security features specific to AR design through sound engineering and security-by-design (SeBD), should provide developers and operators with lower inherent security risk profiles. Building security early into the AR design may remove or passively secure potential critical targets from an adversary’s reach , thereby increasing overall safety and security. An integrated approach and diverse design team that includes engineering, operations, and security experts are fundamental to building security into the design without sacrificing fundamental operational efficiencies and principles. The objective of this project was to evaluate the security and safety interfaces for five classes of reactors, identify potential security vulnerabilities of structures, systems, and components (SSC), and underscore the need to consider security alongside safety in the design o f these concepts. The five reactor classes evaluated in this project and presented in this report are molten-salt reactors (MSR), high temperature gas reactors (HTGR), sodium-fast reactors (SFR), advanced light-water reactors (ALWR), and microreactors. These designs were selected because they reflect the concepts that are closest to market deployment and have received significant resource investments from the public and private sector. This project assesses the inherent security risks posed by common classes of ARs, provides a methodology and framework to assess security along with safety, and offers an analysis of potential mitigation strategies that could be incorporated. For each AR technology, the SSCs that relate to radionuclide source safety functions are discussed to understand the SSC contribution to safety and relative importance in the protective strategy for the design. The assumptions that went into evaluating each reactor concept originated from generic publicly available nonproprietary information and should not directly be used to qualify an absolute risk profile nor to rank specific AR designs. Instead, the purpose of the analysis is to understand and compare the generic inherent security risks of different AR technologies.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗

NASA NTRS1976

A technique for extracting blood samples from mice in fire toxicity tests

The extraction of adequate blood samples from moribund and dead mice has been a problem because of the small quantity of blood in each animal and the short time available between the animals' death and coagulation of the blood. These difficulties are particularly critical in fire toxicity tests because removal of the test animals while observing proper safety precautions for personnel is time-consuming. Techniques for extracting blood samples from mice were evaluated, and a technique was developed to obtain up to 0.8 ml of blood from a single mouse after death. The technique involves rapid exposure and cutting of the posterior vena cava and accumulation of blood in the peritoneal space. Blood samples of 0.5 ml or more from individual mice have been consistently obtained as much as 16 minutes after apparent death. Results of carboxyhemoglobin analyses of blood appeared reproducible and consistent with carbon monoxide concentrations in the exposure chamber.

Bucci, T. J.↗

NASA NTRS2008

Microgravity Flame Spread in Exploration Atmospheres: Pressure, Oxygen, and Velocity Effects on Opposed and Concurrent Flame Spread

Microgravity tests of flammability and flame spread were performed in a low-speed flow tunnel to simulate spacecraft ventilation flows. Three thin fuels were tested for flammability (Ultem 1000 (General Electric Company), 10 mil film, Nomex (Dupont) HT90-40, and Mylar G (Dupont) and one fuel for flame spread testing (Kimwipes (Kimberly-Clark Worldwide, Inc.). The 1g Upward Limiting Oxygen Index (ULOI) and 1g Maximum Oxygen Concentration (MOC) are found to be greater than those in 0g, by up to 4% oxygen mole fraction, meaning that the fuels burned in 0g at lower oxygen concentrations than they did using the NASA Standard 6001 Test 1 protocol. Flame spread tests with Kimwipes were used to develop correlations that capture the effects of flow velocity, oxygen concentration, and pressure on flame spread rate. These correlations were used to determine that over virtually the entire range of spacecraft atmospheres and flow conditions, the opposed spread is faster, especially for normoxic atmospheres. The correlations were also compared with 1g MOC for various materials as a function of pressure and oxygen. The lines of constant opposed flow agreed best with the 1g MOC trends, which indicates that Test 1 limits are essentially dictated by the critical heat flux for ignition. Further evaluation of these and other materials is continuing to better understand the 0g flammability of materials and its effect on the oxygen margin of safety.

Olson, Sandra L.↗

NASA NTRS2015

Who's Got the Bridge? - Towards Safe, Robust Autonomous Operations at NASA Langley's Autonomy Incubator

NASA aeronautics research has made decades of contributions to aviation. Both aircraft and air traffic management (ATM) systems in use today contain NASA-developed and NASA sponsored technologies that improve safety and efficiency. Recent innovations in robotics and autonomy for automobiles and unmanned systems point to a future with increased personal mobility and access to transportation, including aviation. Automation and autonomous operations will transform the way we move people and goods. Achieving this mobility will require safe, robust, reliable operations for both the vehicle and the airspace and challenges to this inevitable future are being addressed now in government labs, universities, and industry. These challenges are the focus of NASA Langley Research Center's Autonomy Incubator whose R&D portfolio includes mission planning, trajectory and path planning, object detection and avoidance, object classification, sensor fusion, controls, machine learning, computer vision, human-machine teaming, geo-containment, open architecture design and development, as well as the test and evaluation environment that will be critical to prove system reliability and support certification. Safe autonomous operations will be enabled via onboard sensing and perception systems in both data-rich and data-deprived environments. Applied autonomy will enable safety, efficiency and unprecedented mobility as people and goods take to the skies tomorrow just as we do on the road today.

Allen, B. Danette↗

DOE OSTI2025

Three‐trophic level food webs support the safety of a biocontrol agent 3 years after release

Biological control (biocontrol) is a powerful tool for managing invasive alien species and assisting the restoration of native ecosystems. Rigorous post‐release monitoring of biocontrol agents is critical to evaluate the success of biocontrol programs; however, this is still rarely implemented. Here, we combined the use of species interaction networks with a Before‐After Control‐Impact design to evaluate the target and non‐target, direct and indirect effects of the Australian gall wasp Trichilogaster acaciaelongifoliae , released to control the invasive plant Acacia longifolia in Portugal. We compared the structure of plant‐galling insect‐parasitoid food webs before and 3 years after the release of the biocontrol agent. Exhaustive sampling did not detect any non‐target effects, either direct (on non‐target plants) or indirect (on other galling insects via shared plants). Additionally, no significant changes were detected in network structure that could be related to the establishment of the biocontrol agent. This study shows that monitoring biocontrol at the community level is possible and that, when carefully planned, biocontrol poses minimal risk of non‐target effects.

López‐Núñez, Francisco A. [Centre for Functional E↗

DOE OSTI2022

Horizontal Split Table Conceptual Design for Validation of Nuclear Data used in Advanced Reactors [Slides]

This presentation discusses a methodology that was developed to create conceptual designs of benchmark critical experiments for advanced reactors and nuclear data testing. A first concept that was explored was a pebble-bed high-temperature gas cooled reactor, based on the HTR-10 reactor. The very high correlation is a proof of concept that the design is similar to the application, and performing such critical experiments would help nuclear data testing and validation. Other concepts could be explored if needed, such as a molten-salt reactor, a sodium-cooled fast reactor, or heat pipe reactors/microreactor.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Advancing Additive Manufacturing Through Artificial Intelligence–Powered, High-Throughput, Nondestructive Characterization and Process Optimization

This Cooperative Research and Development Agreement (CRADA) between Oak Ridge National Laboratory (ORNL) and ZEISS Industrial Metrology has demonstrated the transformative potential of artificial intelligence (AI)-enabled x-ray computed tomography (XCT) to accelerate the qualification and certification of additively manufactured (AM) parts. At the core of this effort is Simurgh, an AI-powered XCT reconstruction framework jointly advanced by ORNL and ZEISS that integrates computer-aided design (CAD) models, physics-based simulations, and deep learning to overcome the long-standing challenges of metal artifact correction, long scan durations, and limited flaw detectability in dense and geometrically complex components. Simurgh enables high-throughput, high-quality 3D reconstruction from sparse and fast scans, which reduces XCT acquisition times by more than an order of magnitude and simultaneously improves defect detection limits by up to fourfold compared with industry-standard approaches. This capability reduces scan costs by more than 50%, lowers labor overhead, and makes XCT characterization economically viable for routine industrial use. By enabling reliable flaw detection in minutes rather than hours, Simurgh facilitates real-time feedback loops for process parameter optimization, which was highlighted in a recent npj Computational Materials (a Nature journal) issue. In the published study, more than 100 alloy coupons were characterized within a single day. This work represents a tenfold acceleration in the development of novel AM alloys and processes compared with conventional workflows. The ZEISS collaboration has also demonstrated the scalability of Simurgh to diverse application domains, including aerospace, nuclear, automotive, and biomedical components; in these applications, ensuring structural integrity is paramount. By drastically reducing barriers to XCT adoption, this partnership has laid the foundation for digital twins and data-driven certification pipelines and directly addressed bottlenecks in qualifying new materials and designs. Together, ORNL and ZEISS have shown that Simurgh advances the state of the art in nondestructive evaluation and aligns with the broader mission of enabling Industry 4.0 manufacturing ecosystems, in which intelligent, cost-effective, rapid quality assurance is integral to accelerating innovation and ensuring safety in critical applications.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Advancing Additive Manufacturing Through Artificial Intelligence–Powered, High-Throughput, Nondestructive Characterization and Process Optimization

36 MATERIALS SCIENCE↗

NASA NTRS1988

Particle cloud combustion in reduced gravity

The prinicipal objectives of this microgravity experiment program are to obtain flame propagation rate and flame extinction limit data for several important premixed, quiescent particle cloud combustion systems under near zero-gravity conditions. The data resulting from these experiments are needed for utilization with currently available and tractable flame propagation and extinction theory. These data are also expected to provide standards for the evaluation of fire hazards in particle suspensions in both Earth-based and space-based applications. Both terrestrial and space-based fire safety criteria require the identification of the critical concentrations of particulate fuels and inerts at the flame extinction conditions.

Berlad, A. L.↗

NASA NTRS2009

Designing a Better Spacecraft: Assessing Flight Operability of Human Rated Spacecraft

The design of a human rated spacecraft is a complex and costly process requiring the integrated assessment of many individual criteria. Historically, it has been difficult to include in that integrated assessment the design s full impact on the flight operations community and its costs. The unique "operability requirements" have not been well understood, nor has there been a well-defined set of criteria for assessing operability. As a result, flight operations organizations and program managers are often faced with difficult and costly operations phase implementations. In response, the Mission Operations Directorate at NASA s Lyndon B. Johnson Space Center has established a formal technique to evaluate and communicate the operational characteristics of spacecraft system designs for the Constellation Program. This process is not intended to replace or replicate other critical assessments such as risk, reliability and safety assessments. Instead, this new technique adds to the assessment toolset a means to address the concerns and potential cost drivers that are unique to the operational phase of a program and the flight operations community. This paper describes the implementation and application of this "Spacecraft Flight Operability Assessment Scale" in supporting vehicle design efforts. The six key factors of flight operability are defined, with guiding principles and goals stated for each factor. A standardized rating technique provides feedback that is useful to both the operations and program management communities. Sample assessments of legacy spacecraft, including the Space Shuttle and International Space Station systems, are provided to provide real world examples of this technique s application.

Crocker, Alan R.↗

NASA NTRS2009

Applying Formal Methods to NASA Projects: Transition from Research to Practice

NASA project managers attempt to manage risk by relying on mature, well-understood process and technology when designing spacecraft. In the case of crewed systems, the margin for error is even tighter and leads to risk aversion. But as we look to future missions to the Moon and Mars, the complexity of the systems will increase as the spacecraft and crew work together with less reliance on Earth-based support. NASA will be forced to look for new ways to do business. Formal methods technologies can help NASA develop complex but cost effective spacecraft in many domains, including requirements and design, software development and inspection, and verification and validation of vehicle subsystems. To realize these gains, the technologies must be matured and field-tested so that they are proven when needed. During this discussion, current activities used to evaluate FM technologies for Orion spacecraft design will be reviewed. Also, suggestions will be made to demonstrate value to current designers, and mature the technology for eventual use in safety-critical NASA missions.

Othon, Bill↗

DOE OSTI2025

Nondestructive Evaluation of Concrete: Elastic Property Imaging Through Full-Waveform Inversion

Concrete is a vital material in construction—especially in the nuclear industry, where it is used in critical structures such as containment vessels. Over time, concrete can degrade due to harsh operational and environmental conditions, necessitating that its elastic properties be accurately evaluated to ensure structural integrity and safety. Traditional nondestructive evaluation methods such as ultrasound-based techniques often rely on simplifying assumptions that may not hold true for concrete. This paper presents an advanced ultrasound-based method that uses elastic full-waveform inversion (EFWI) to create detailed images of concrete’s mechanical properties. By accurately modeling wave behaviors such as scattering and reflection, we aim to overcome the limitations of conventional ultrasonic-based methods. In this work, the imaging problem involved reconstructing the various elastic properties of a heterogenous concrete block with three steel rebars embedded in it. The ultrasonic measurements were synthetically generated from multiple sources and receivers, and the reconstruction process was performed using a gradient-based optimization algorithm. Our approach leveraged EFWI to reconstruct high-resolution images of the pressure wave speed, shear wave speed, and density. Multiple misfit functions—including L2-norm, cross-correlation (CC), and L1-norm—combined with total variation (TV) regularization and parameter constraints using a Sigmoid function—were explored for the reconstruction. The results demonstrated that using the L1-norm misfit function in conjunction with TV regularization and Sigmoid constraints significantly improved the reconstruction quality in comparison to traditional methods. This approach provided clearer images with fewer artifacts and better captured background heterogeneity. Our findings highlight that, when properly designed, EFWI carries great potential for providing comprehensive, more accurate, and more reliable assessments of concrete conditions, as is crucial for the maintenance and safety of nuclear power plant structures.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Considerations regarding the Use of Computer Vision Machine Learning in Safety-Related or Risk-Significant Applications in Nuclear Power Plants

With the advancements made to date in the field of artificial intelligence (AI), significant potential exists to utilize AI capabilities for nuclear power plant (NPP) applications. AI can replicate human decision making and it is usually faster and more accurate than humans. For implementations that impact critical NPP applications (e.g., safety-related or non-safety systems that potentially affect overall plant risk), a deeper safety analysis of the AI methods is necessary. AI applied to NPP operations could resemble the use of digital I&C (DI&C) because such applications involve digital computer hardware and custom-designed software that input plant data, execute complex software algorithms, and output the results to a system or licensed human operator to potentially provoke an action. For AI methods to be compliant with current safety requirements for DI&C, AI compatibility must be evaluated, and AI-related gaps may exist that prevent the prompt deployment of AI in NPPs. This effort aims to evaluate how example AI technologies align with the DI&C safety framework, and discusses how they could be analyzed, modeled, tested, and validated in a manner similar to typical DI&C technologies. Because AI is a broad field that encompasses areas such as machine learning (ML), natural language processing, and computer vision, this research focused on a subset of methods categorized as the computer vision ML (CVML) methods. This report explores two CVML use cases, gauge reading and fire watch, considered relevant to the DI&C standards, as they could play a safety-critical role. For the gauge reading use case, a CVML-enabled technology that can read gauges at oblique angles is utilized. For the fire watch use case, a CVML-enabled technology is utilized that migrates fire watch from a manual (human) approach to automated fire detection. These use cases are mainly intended to give context to the CVML system discussion. This effort assumes the worst-case scenario, with the CVML system being used to replace a safety-related or risk-significant system, thus requiring evaluation. Evaluating CVML against most of the relevant safety requirements for DI&C yielded several CVML-specific considerations due to the uniqueness of its characteristics in comparison with typical DI&C systems. For example, CVML models often employ commonly used (open-source) datasets, and it is not always possible to determine the level of overlap among open-source datasets. Therefore, the independence of the developed CVML models when demonstrating diversity is questionable, therefore creating vulnerability to common cause failure (CCF). The design verification process is also impacted since the data overlap could result in overestimation of the software validation and verification (V&V) performance results. Section 2 of this report evaluates a list of the identified CVML-specific characteristics and discusses the resulting considerations and potential solutions in the context of each referenced requirement. A summation is provided in Section 3. This report is not to be used as a guideline. It was developed to identify and consider issues in the implementation of ML technologies used to augment activities that may have a bearing on plant operation. The report draws parallels to the use of DI&C technologies, for which many standards are available to guide their use in nuclear plant operation. It considers the technologies and some of the potential implications of their use in safety-related applications but is not intended to address regulatory or licensing related issues.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Evaluation of the Reconstruction Accuracy of the Ultrasound Model–Based Image Reconstruction (U-MBIR) Method for Concrete to Optimize Damage Detection

Reinforced concrete is a critical structural material used to construct nuclear power plants (NPPs). As such, its safety and performance must be thoroughly examined throughout the life cycle of the NPP infrastructure system. Ultrasonic measurements have been an industry standard for both surface and subsurface inspections. To support the development of these techniques, Oak Ridge National Laboratory (ORNL) has researched and developed advanced image reconstruction algorithms to capture internal damage. The results and discussion presented herein summarize the current state of the ultrasonic model–based iterative reconstruction (U-MBIR) algorithm developed at ORNL. In the work documented in this report, the U-MBIR methodology was applied to four sets of ultrasonic data collected from concrete specimens. The results demonstrate that the U-MBIR algorithm can successfully detect defects within the four concrete samples. The reconstruction images help identify the specimen thickness, regions of delamination, and location of rebar embedded within the concrete. The reconstruction images allow engineers and technicians to characterize the internal defects within concrete specimens and structural members. Ultimately, this knowledge can guide engineers in making informed decisions regarding the performance, safety, and reliability of structural materials (i.e., reinforced concrete) throughout the life cycle of NPPs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Reassessing the Origins and Contemporary Relevance of ck Acceptability Parameters: Evolving Perspectives on Similarity

“Sensitivity and Uncertainty Analyses Applied to Criticality Safety Validation,” introduces sensitivity and uncertainty methods to address challenges in defining and extending areas of applicability for criticality safety validation. These areas are traditionally defined by the bounds or limits on key parameters, but establishing valid ranges and managing complex parameter variations remain challenging. NUREG/CR-6655 introduces ck and other integral indices, as well as concepts such as the completeness of benchmark coverage, to better quantify system similarities. The work proposed herein seeks to evaluate these foundational concepts to ensure that the bounds remain effective in guiding the assessment of similarity and applicability in modern applications. The concept of completeness, along with other parameters envisioned within the framework, serves as an example of the foundational ideas that have been established, though their effectiveness in practice may not be fully understood. Advancements in scripting tools, coupled with the speed and efficiency of modern computing and statistical models, now allow for faster and more thorough assessments than previously possible. These advancements also enable the identification of trends within the data, which could provide additional insight into system behavior and further broaden the scope of previously performed benchmarks. By leveraging these capabilities, we will revisit and expand the scope of these foundational methods to determine whether the necessary elements for robust similarity evaluation are already embedded, partially realized, or remain untapped.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗