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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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More rational approach offers potential for optimization of design. Improvement in deterministic method of selection of structural-load safety factors makes possible to design structures more nearly optimum with respect to competing demands for both reliability and attributes detracting from reliability (principally lighter weight, smaller size, and lower cost).
Sunlight-driven water splitting allows renewable hydrogen to be produced from abundant and environmentally benign water. Large-scale societal implementation of this green fuel production technology within energy generation systems is essential for the establishment of sustainable future societies. Among various technologies, photocatalytic water splitting using particulate semiconductors has attracted increasing attention as a method to produce large amounts of green fuels at low cost. The key to making this technology practical is the development of photocatalysts capable of splitting water with high solar-to-fuel energy conversion efficiency. Furthermore, advances that enable the deployment of water-splitting photocatalysts over large areas are necessary, as is the ability to recover hydrogen safely and efficiently from the produced oxyhydrogen gas. This lead article describes the key discoveries and recent research trends in photosynthesis using particulate semiconductors and photocatalyst sheets for overall water splitting, via one-step excitation and two-step excitation (Z-scheme reactions), as well as for direct conversion of carbon dioxide into renewable fuels using water as an electron donor. We describe the latest advances in solar water-splitting and carbon dioxide reduction systems and pathways to improve their future performance, together with challenges and solutions in their practical application and scalability, including the fixation of particulate photocatalysts, hydrogen recovery, safety design of reactor systems, and approaches to separately generate hydrogen and oxygen from water.
Although extensive ground testing, utilizing both the Captive Trajectory system (CTS) and grid method, generally precedes flight testing of new aircraft/weapon combinations, the flight test results often do not match the wind tunnel predictions. These discrepancies are generally attributed to model scale, wind tunnel test errors and Reynolds Number effects, and may have been the cause of several previous aircraft/weapon incidents. The paper describes the procedure used at the Naval Air Warfare Center, Aircraft Division, Warminster (NAWCADWAR) during the early phases of wind tunnel testing and analysis, as well as subsequent flight testing to validate the predicted trajectories. This approach is designed to improve the safety of the flight tests for the critical portions of the aircraft envelope.
The NASA Langley Research Center (LaRC), Cockpit Motion Facility (CMF) motion base design has taken advantage of inherent hydraulic characteristics to implement safety features using hardware solutions only. Motion system safety has always been a concern and its implementation is addressed differently by each organization. Some approaches rely heavily on software safety features. Software which performs safety functions is subject to more scrutiny making its approval, modification, and development time consuming and expensive. The NASA LaRC's CMF motion system is used for research and, as such, requires that the software be updated or modified frequently. The CMF's customers need the ability to update the simulation software frequently without the associated cost incurred with safety critical software. This paper describes the CMF engineering team's approach to achieving motion base safety by designing and implementing all safety features in hardware, resulting in applications software (including motion cueing and actuator dynamic control) being completely independent of the safety devices. This allows the CMF safety systems to remain intact and unaffected by frequent research system modifications.
The National Aviation Operational Monitoring Service (NAOMS) was a research project under NASA s Aviation Safety Program during the years from 2000 to 2005. The purpose of this project was to develop a methodology for gaining reliable information on changes over time in the rates-of-occurrence of safety-related events as a means of assessing the safety of the national airspace. The approach was a scientifically designed survey of the operators of the aviation system concerning their safety-related experiences. This report presents the results of the methodology developed and a demonstration of the NAOMS concept through a survey of nearly 20,000 randomly selected air-carrier pilots. Results give evidence that the NAOMS methodology can provide a statistically sound basis for evaluating trends of incidents that could compromise safety. The approach and results are summarized in the report and supporting documentation and complete analyses of results are presented in 14 appendices.
Presently, there are three avenues by which Unmanned Aircraft System (UAS) operations are authorized in the U.S. National Airspace System (NAS): obtaining either (i) a certificate of authorization (COA), or (ii) a special airworthiness certificate (SAC) in either the experimental, or the restricted category, or (iii) an exemption from an airworthiness certificate together with a civil COA. The first is meant primarily for public entities, such as NASA; the remaining two are the only available means for civil UAS operations. Recently, the Federal Aviation Administration (FAA) has also proposed a regulatory framework targeted for certain small UAS, specifically those weighing 55 pounds or less, although final rulemaking remains pending. We have previously shown how an assurance case can aggregate heterogeneous reasoning and safety evidence, with application to UAS safety. In this paper, we describe how assurance cases can serve as a common framework to justify overall system safety, unifying both operational aspects and airworthiness, in particular system design assurance. We also show how this approach can coexist with, and augment, existing safety analysis processes and best-practices, by transforming the artifacts they produce into structured assurance arguments. To illustrate the applicability and utility of our approach, we have been applying it for the design assurance of an unmanned rotorcraft system, intended for precision agriculture operations, as part of the NASA Unmanned Aircraft System (UAS) Integration in the National Airspace System (NAS) project.
The National Reactor Innovation Center (NRIC) is leading a transformative initiative to accelerate advanced reactor deployment by fundamentally reimagining how nuclear safety basis documentation is developed, reviewed, and maintained. Traditional Documented Safety Analysis (DSA) processes for DOE-authorized facilities rely on static, document-centric workflows that consume significant time and resources, exemplified by recent major licensing efforts requiring hundreds of thousands of staff hours and millions of pages of documentation review. These conventional approaches create barriers to the rapid, cost-effective deployment of advanced reactors that America's future energy needs demand. NRIC's DOE Authorization Digital Transformation Project addresses these challenges through an innovative framework that integrates artificial intelligence (AI), digital engineering, and systems-based data management into a cohesive digital ecosystem. This white paper presents NRIC's methodology for evaluating AI-enabled document generation capabilities within this broader digital infrastructure, using the Demonstration of Microreactor Experiments (DOME) facility as a pilot case study. The evaluation will assess an AI tool's ability to generate a Preliminary Documented Safety Analysis (PDSA) through progressive integration stages—from standalone document processing to full digital thread connectivity—while maintaining rigorous verification, validation, and regulatory acceptance standards. By establishing dynamic, traceable connections between design data and safety documentation, NRIC's approach has the potential to reduce both document development time and regulatory review cycles by as much as 50%, while simultaneously improving accuracy, consistency, and traceability. This initiative represents a critical step toward establishing reusable digital infrastructure that reactor developers can leverage to accelerate their path from concept to commercial operation, directly supporting NRIC's mission to demonstrate and deploy advanced nuclear energy technologies.
One lesson learned from Orbiting Maneuvering Vehicle (OMV) program experience is that Design Reference Missions must include an appropriate balance of operations and performance inputs to effectively drive vehicle systems design and configuration. Rendezvous trajectory design is based on vehicle characteristics (e.g., mass, propellant tank size, and mission duration capability) and operational requirements, which have evolved through the Gemini, Apollo, and STS programs. Operational constraints affecting the rendezvous final approach are summarized. The two major objectives of operational rendezvous design are vehicle/crew safety and mission success. Operational requirements on the final approach which support these objectives include: tracking/targeting/communications; trajectory dispersion and navigation uncertainty handling; contingency protection; favorable sunlight conditions; acceptable relative state for proximity operations handover; and compliance with target vehicle constraints. A discussion of the ways each of these requirements may constrain the rendezvous trajectory follows. Although the constraints discussed apply to all rendezvous, the trajectory presented in 'Cargo Transfer Vehicle Preliminary Reference Definition' (MSFC, May 1991) was used as the basis for the comments below.
The world-wide aviation system is one of the most complex dynamical systems ever developed and is generating data at an extremely rapid rate. Most modern commercial aircraft record several hundred flight parameters including information from the guidance, navigation, and control systems, the avionics and propulsion systems, and the pilot inputs into the aircraft. These parameters may be continuous measurements or binary or categorical measurements recorded in one second intervals for the duration of the flight. Currently, most approaches to aviation safety are reactive, meaning that they are designed to react to an aviation safety incident or accident. In this paper, we discuss a novel approach based on the theory of multiple kernel learning to detect potential safety anomalies in very large data bases of discrete and continuous data from world-wide operations of commercial fleets. We pose a general anomaly detection problem which includes both discrete and continuous data streams, where we assume that the discrete streams have a causal influence on the continuous streams. We also assume that atypical sequence of events in the discrete streams can lead to off-nominal system performance. We discuss the application domain, novel algorithms, and also discuss results on real-world data sets. Our algorithm uncovers operationally significant events in high dimensional data streams in the aviation industry which are not detectable using state of the art methods
Abstract Background Desirability of outcome ranking (DOOR) is a novel approach to clinical trial design that incorporates safety and efficacy assessments into an ordinal ranking system to evaluate overall outcomes of clinical trial participants. Here, we derived and applied a disease-specific DOOR endpoint to registrational trials for complicated intra-abdominal infection (cIAI). Methods Initially, we applied an a priori DOOR prototype to electronic patient-level data from 9 phase 3 noninferiority trials for cIAI submitted to the US Food and Drug Administration between 2005 and 2019. We derived a cIAI-specific DOOR endpoint based on clinically meaningful events that trial participants experienced. Next, we applied the cIAI-specific DOOR endpoint to the same datasets and, for each trial, estimated the probability that a participant assigned to the study treatment would have a more desirable DOOR or component outcome than if assigned to the comparator. Results Three key findings informed the cIAI-specific DOOR endpoint: (1) a significant proportion of participants underwent additional surgical procedures related to their baseline infection; (2) infectious complications of cIAI were diverse; and (3) participants with worse outcomes experienced more infectious complications, more serious adverse events, and underwent more procedures. DOOR distributions between treatment arms were similar in all trials. DOOR probability estimates ranged from 47.4% to 50.3% and were not significantly different. Component analyses depicted risk-benefit assessments of study treatment versus comparator. Conclusions We designed and evaluated a potential DOOR endpoint for cIAI trials to further characterize overall clinical experiences of participants. Similar data-driven approaches can be utilized to create other infectious disease–specific DOOR endpoints.
Space flight safety, discussing escape, rescue and survival design approaches for astronauts
The loads and low frequency dynamics data base, part of Environet, is described with particular attention given to its development and contents. The objective of the data base is to provide the payload designer with design approaches and design data to meet STS safety requirements. Currently the data base consists of the following sections: abstract, scope, glossary, requirements, interaction with other environments, summary of the loads analysis process, design considerations, guidelines for payload design loads, information data base, and references.
The current ESFR (European Sodium Fast Reactor) design was proposed and in-depth evaluated in the frame of the past ESFR-SMART project. As a follow-up project, the ESFR-SIMPLE has been launched with the aim of challenging the current commercial-size ESFR design in terms of safety features and economic performance. Among the new safety measures to be developed and assessed in ESFR-SIMPLE, the current oxide fuel ESFR design will be challenged by a modified version of the core with metallic fuel. This intends to conclude on what types of benefits can be obtained with high-density fuel, under similar safety and design constraints. In this paper, the designing approach for enabling the use of metallic fuel in the current ESFR core is described and a preliminary neutronic evaluation is carried out. The optimal configuration is established through the optimization of key neutronic parameters aiming at the potential reduction of the plutonium inventory. The resulting core configuration serves as a basis for further safety assessment analyses, which will provide insight into the advantages and drawbacks of the two types of fuels.
The objective of this study was to establish the initial quantitative reliability bounds for nuclear electric propulsion systems in a manned Mars mission required to ensure crew safety and mission success. Finding the reliability bounds involves balancing top-down (mission driven) requirements and bottom-up (technology driven) capabilities. In seeking this balance we hope to accomplish the following: (1) provide design insights into the achievability of the baseline design in terms of reliability requirements, given the existing technology base; (2) suggest alternative design approaches which might enhance reliability and crew safety; and (3) indicate what technology areas require significant research and development to achieve the reliability objectives.
The Galileo spacecraft, which will release probes to explore the Jupiter system, was launched in October, 1989 as the payload on STS-34, and the Ulysses spacecraft, which will fly by Jupiter en route to a polar orbit of the sun, is presently entering system-test activity in preparation for an October, 1990 launch. This paper reviews the Galileo and Ulysses mission objectives and design approaches and presents details of the missions' safety analysis. The processes used to develop the safety analysis are described and the results of safety tests are presented.
The Space Station Safety Plan has been prepared as an adjunct to the subject contract final report, suggesting the tasks and implementation procedures to ensure that threats are addressed and resolution strategy options identified and incorporated into the space station program. The safety program's approach is to realize minimum risk exposure without levying undue design and operational constraints. Safety objectives and risk acceptances are discussed.
The aviation literature gives relatively little guidance to practitioners about the specifics of architecting systems for safety, particularly the impact of architecture on allocating safety requirements, or the relative ease of system assurance resulting from system or subsystem level architectural choices. As an exemplar, this paper considers common architectural patterns used within traditional aviation systems and explores their safety and safety assurance implications when applied in the context of integrating artificial intelligence (AI) and machine learning (ML) based functionality. Considering safety as an architectural property, we discuss both the allocation of safety requirements and the architectural trade-offs involved early in the design lifecycle. This approach could be extended to other assured properties, similar to safety, such as security. We conclude with a discussion of the safety considerations that emerge in the context of candidate architectural patterns that have been proposed in the recent literature for enabling autonomy capabilities by integrating AI and ML. A recommendation is made for the generation of a property-driven architectural pattern catalogue.
The aviation literature gives relatively little guidance to practitioners about the specifics of architecting systems for safety, particularly the impact of architecture on allocating safety requirements, or the relative ease of system assurance resulting from system or subsystem level architectural choices. As an exemplar, this paper considers common architectural patterns used within traditional aviation systems and explores their safety and safety assurance implications when applied in the context of integrating artificial intelligence (AI) and machine learning (ML) based functionality. Considering safety as an architectural property, we discuss both the allocation of safety requirements and the architectural trade-offs involved early in the design lifecycle. This approach could be extended to other assured properties, similar to safety, such as security. We conclude with a discussion of the safety considerations that emerge in the context of candidate architectural patterns that have been proposed in the recent literature for enabling autonomy capabilities by integrating AI and ML. A recommendation is made for the generation of a property-driven architectural pattern catalogue.