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This document provides guidelines for the accomplishment of Failure Mode, Effects, and Criticality Analysis (FMECA) on the Apollo program. It is a procedure for analysis of hardware items to determine those items contributing most to system unreliability and crew safety problems.
The complexities of modern biomedicine are rapidly increasing. Thus, modeling and simulation have become increasingly important as a strategy to understand and predict the trajectory of pathophysiology, disease genesis, and disease spread in support of clinical and policy decisions. In such cases, inappropriate or ill-placed trust in the model and simulation outcomes may result in negative outcomes, and hence illustrate the need to formalize the execution and communication of modeling and simulation practices. Although verification and validation have been generally accepted as significant components of a model’s credibility, they cannot be assumed to equate to a holistic credible practice, which includes activities that can impact comprehension and in-depth examination inherent in the devel-opment and reuse of the models. For the past several years, the Committee on Credible Practice of Modeling and Simulation in Healthcare, an interdisciplinary group seeded from a U.S. interagency initiative, has worked to codify best practices. Here, we provide Ten Rules for credible practice of modeling and simulation in healthcare developed from a comparative analysis by the Committee’s multidisciplinary membership, followed by a large stakeholder com-munity survey. These rules establish a unified conceptual framework for modeling and simulation design, implementation, evaluation, dissemination and usage across the modeling and simulation life-cycle. While biomedical science and clinical care domains have somewhat different requirements and expectations for credible practice, our study converged on rules that would be useful across a broad swath of model types. In brief, the rules are: (1) Define context clearly. (2) Use contextually appropriate data. (3) Evaluate within context. (4) List limitations explicitly. (5) Use version control. (6) Document appropriately. (7) Disseminate broadly. (8) Get independent reviews. (9) Test competing imple-mentations. (10) Conform to standards. Although some of these are common sense guidelines, we have found that many are often missed or misconstrued, even by seasoned practitioners. Computational models are already widely used in basic science to generate new biomedical knowledge. As they penetrate clinical care and healthcare policy, contributing to personalized and precision medicine, clinical safety will require established guidelines for the credible practice of modeling and simulation in healthcare.
As deep neural networks (DNNs) are increasingly used in safety critical applications, there is a growing concern for their trustworthiness. Even highly trained, high-performant networks are not 100% accurate. However, it is very difficult to predict their behaviour during deployment without ground truth. In this paper, we provide a comparative and replicability study on recent approaches that have been proposed to evaluate the trustworthiness of DNNs. We find that it is very difficult to run and reproduce the results for these approaches on their replication packages, and it is even more difficult to run the tools on artifacts other than their own. Further, it is difficult to compare the effectiveness of the tools, due to lack of clearly defined evaluation metrics. Our results indicate that more effort is needed in our research community to obtain sound techniques for evaluating the trustworthiness of neural networks in safety-critical domains. To this end, we contribute an evaluation framework that incorporates the considered approaches and enables evaluation on common benchmarks, using common metrics. Using this framework, we run a comparative study of the three approaches.
Human-rated missions like NASA's Exploration Mission - 1 (EM-1) and the Orion Multi-Purpose Crew Vehicle are becoming exceedingly complex in terms of software's contribution to achieving mission objectives. The increasing complexity and inherent safety critical nature of the embedded flight software imposes a unique resource challenge to assurance providers responsible for affirming that the mission is going to fly safely. Another challenge NASA and other Government agencies are facing is that more and more software is being developed using an agile development methodology, which is divergent from the typical waterfall, iterative, and incremental development methodologies assurance providers generally observe in the development of safety-critical embedded software. Orion Independent Verification and Validation (IV&V) has addressed these challenges by providing focused assurance results of critical mission capabilities prioritized by a dynamic assessment of risk level. Prior to this approach, Orion IV&V evaluated areas of risk in much broader, and more static, terms. Due to the agile software development life cycle that Orion follows, IV&V findings were often reported months out of phase with the developer thereby imposing increased rework costs. As a result of evolving the approach to adding assurance on Orion, IV&V is able to incrementally deliver high-priority assurance conclusions and more impactful issues more in phase with the developer activities, thereby increasing the value of the findings to the project. The agile IV&V approach employed by the Orion IV&V team strives to achieve a cadence of delivery that matches the pace of development. This agile approach provides increased flexibility for the assurance provider to become more efficient in reporting assurance conclusions and issues. This paper and presentation will discuss the principles which drive the design of our approach, results to date, and stimulate thinking for groups looking to add assurance to software being developed using an agile methodology.
The goal of the NASA Aviation Safety Program (AvSP) is to develop and demonstrate technologies that contribute to a reduction in the aviation fatal accident rate by a factor of 5 by the year 2007 and by a factor of 10 by the year 2022. Integrated safety analysis of day-to-day operations and risks within those operations will provide an understanding of the Aviation Safety Program portfolio. Safety benefits analyses are currently being conducted. Preliminary results for the Synthetic Vision Systems (SVS) and Weather Accident Prevention (WxAP) projects of the AvSP have been completed by the Logistics Management Institute under a contract with the NASA Glenn Research Center. These analyses include both a reliability analysis and a computer simulation model. The integrated safety analysis method comprises two principal components: a reliability model and a simulation model. In the reliability model, the results indicate how different technologies and systems will perform in normal, degraded, and failed modes of operation. In the simulation, an operational scenario is modeled. The primary purpose of the SVS project is to improve safety by providing visual-flightlike situation awareness during instrument conditions. The current analyses are an estimate of the benefits of SVS in avoiding controlled flight into terrain. The scenario modeled has an aircraft flying directly toward a terrain feature. When the flight crew determines that the aircraft is headed toward an obstruction, the aircraft executes a level turn at speed. The simulation is ended when the aircraft completes the turn.
"Raising the bar" in safety performance is a critical challenge for many organizations, including Kennedy Space Center. Contributing-factor taxonomies organize information about the reasons accidents occur and therefore are essential elements of accident investigations and safety reporting systems. Organizations must balance efforts to identify causes of specific accidents with efforts to evaluate systemic safety issues in order to become more proactive about improving safety. This project successfully addressed the following two problems: (1) methods and metrics to support the design of effective taxonomies are limited and (2) influence relationships among contributing factors are not explicitly modeled within a taxonomy.
This review paper provides an in-depth analysis of the role of Direct Current (DC) power systems in residential settings, focusing on their safety, efficiency, and environmental advantages. It recognizes the significant contribution of the residential sector to global carbon dioxide emissions and explores how DC power systems can help mitigate these effects. The paper traces the historical evolution of DC power, its resurgence with renewable energy technologies, and the advancements in power electronics that facilitate its integration. Emphasizing the efficiency and safety benefits, especially in low-voltage applications, the paper highlights the seamless integration of DC systems with inherently DC-generating renewable sources like solar PV and wind. The review discusses the critical role of converter technologies in the transition to DC power and examines the compatibility of DC systems with energy storage solutions, underscoring their potential for enhanced energy management. It also addresses the environmental impacts of adopting DC power, aligning with global carbon reduction efforts. The paper analyzes regional case studies, exploring practical applications and outcomes, and addresses challenges such as the need for standardization. It concludes with recommendations for stakeholders and future research directions, emphasizing the economic, technological, and environmental aspects of DC power systems. Overall, the paper presents DC power as a viable and sustainable option for residential energy conservation, contingent upon ongoing technological progress, supportive policies, and standardization.
We propose a framework using system dynamics to model the dynamic behavior of organizations in accident analysis. Most current accident analysis techniques are event-based and do not adequately capture the dynamic complexity and non-linear interactions that characterize accidents in complex systems. In this paper we propose a set of system safety archetypes that model common safety culture flaws in organizations, i.e., the dynamic behaviour of organizations that often leads to accidents. As accident analysis and investigation tools, the archetypes can be used to develop dynamic models that describe the systemic and organizational factors contributing to the accident. The archetypes help clarify why safety-related decisions do not always result in the desired behavior, and how independent decisions in different parts of the organization can combine to impact safety.
This research investigated the shape and rise velocities of gas bubbles (helium, nitrogen, argon, and krypton) in molten LiCl-KCl at 500 °C using a specialized optical visualization apparatus. The apparatus features a custom quartz rectangular prism cell housed in a furnace, enabling the application of the shadowgraph measurement technique. Bubbles with diameters between 0.45 and 3.2 mm were produced via a capillary, and their equivalent diameters and rise velocities were analyzed using high-resolution imaging and centroid tracking algorithms. Important non-dimensional parameters were calculated to characterize behavior. Bubbles with 0.03 < Eo < 1.32, 17 < Re < 718, and Mo order of 10 -11 were generated in the molten LiCl-KCl, revealing that bubbles with diameters less than 1.46 mm remain spherical, whereas those with larger diameters are ellipsoidal. The transition and oscillation onset for bubble shape occurred at larger diameters than those previously observed in air–water systems. Comparative analysis of the gas-molten salt data against existing air–water bubble rise velocity correlations highlighted inaccuracies in predictions, particularly across the different bubble regimes. An existing correlation was calibrated to the molten salt data to improve the bubble velocity predictions. In conclusion, this study contributes essential experimental data for the design and safety evaluation of molten salt reactors and offers insights for the optimization of sparge systems for fission product removal.
The abatement of safety and environmental burden associated with low and ultra-low Global Warming Potential (GWP) refrigerants is a critical undertaking. As the industry shifts towards more environmentally friendly alternatives, mitigating the potential risks and ensuring safety standards becomes paramount. The adoption of mildly and highly flammable refrigerants contributes significantly to minimizing the greenhouse gas impact on the environment, aligning with global climate and sustainability goals. However, it is essential to address safety concerns and potential environmental implications associated with the end use of these refrigerants. A method to mitigate the safety risk in a flammable refrigerant based heating, ventilation, air-conditioning, and refrigeration (HVACR) system is the primary focus of this paper. Advent of A2L and A3 refrigerants as replacements to high GWP refrigerants requires careful handling of leak episodes to lower or eliminate the risk associated with creating flammable mixtures capable of fire/explosion hazard. Solid materials tailored to target the molecule of interest (i.e., refrigerant.) by engineering the microporous structure as well as chemically functionalizing the surface to attract and hold on to the chemical compound being removed from the gas stream was realized. Quantitative analysis reveals the adsorbent's effectiveness in reducing leak potential in the range of 40 %–100 % for various refrigerants. Strategic placement and active leak management with negative pressure offer promising avenues for capturing leaked refrigerants, enhancing overall safety.
Abstract This paper examines both mathematical formulation and practical implementation of an ecological adaptive cruise controller (ECO-ACC) with connected infrastructure. Human errors are typical sources of accidents in urban driving, which can be remedied by rigorous control theories. Designing an ECO-ACC is, therefore, a classical research problem to improve safety and energy efficiency. We add two main contributions to the literature. First, we propose a mathematical framework of an online ECO-ACC for plug-in hybrid electric vehicle (PHEV). Second, we demonstrate ECO-ACC in a real world, which includes other human drivers and uncertain traffic signals on a 2.6 (km) length of the corridor with eight signalized intersections in Southern California. The demonstration results show, on average, 30.98% of energy efficiency improvement and 8.51% additional travel time.
This paper will present technologies and concepts for novel aeropropulsion systems. These technologies will enhance the safety of operations, reduce life cycle costs, and contribute to reduced costs of air travel and access to space. One of the goals of the NASA program is to reduce the carbon-dioxide emissions of aircraft engines. Engine concepts that use highly efficient fuel cell/electric drive technologies in hydrogen-fueled engines will be presented in the proposed paper. Carbon-dioxide emissions will be eliminated by replacing hydrocarbon fuel with hydrogen, and reduce NOx emissions through better combustion process control. A revolutionary exoskeletal engine concept, in which the engine drum is rotated, will be shown. This concept has the potential to allow a propulsion system that can be used for subsonic through hypersonic flight. Dual fan concepts that have ultra-high bypass ratios, low noise, and low drag will be presented. Flow-controlled turbofans and control-configured turbofans also will be discussed. To increase efficiency, a system of microengines distributed along lifting surfaces and on the fuselage is being investigated. This concept will be presented in the paper. Small propulsion systems for affordable, safe personal transportation vehicles will be discussed. These low-oil/oilless systems use technologies that enable significant cost and weight reductions. Pulse detonation engine-based hybrid-cycle and combined-cycle propulsion systems for aviation and space access will be presented.
Once or twice in an age, a year comes along that the historians proclaim as an Annus Mirabilis - a year of wonders. For the Jet Propulsion Laboratory, 2004 was just that sort of time. From beginning to end, it was a nonstop experience of wondrous events in space. Imagine that two robot rovers embark on cross-country rambles across Mars, scrutinizing rocks for signs of past water on the now-arid world. A flagship spacecraft brakes into orbit at Saturn to begin longterm surveillance of the ringed world, preparing to drop a sophisticated probe to the surface of its haze-shrouded largest moon. Another craft makes the closest-ever pass by the nucleus of a comet, collecting sample particles as it goes. Two new space telescopes peer into the depths of the universe far beyond our solar system, viewing stars, nebulas and galaxies in invisible light beyond the spectrum our eyes can see. A pair of instruments is lofted on a NASA Earth-orbiting satellite to monitor air quality and the protective layer of ozone blanketing our home planet. A small probe brings samples of the solar wind to Earth for in-depth study. While JPL was absorbed with all of these ventures on other worlds, NASA and the White House unveiled an ambitious new plan of space exploration. The Vision for Space Exploration announced in January foresees a program of robotic and astronaut missions leading to a human return to the Moon by 2020, and eventual crewed expeditions to Mars. The vision also calls for more robotic missions to the moons of the outer planets; spaceborne observatories that will search for Earth-like planets around other stars and explore the formation and evolution of the universe; and continued study of our home planet. In order to accomplish all of this, NASA must perfect many as-yet-uninvented technologies and space transportation capabilities. JPL has a great deal to bring to this vision. Robotic exploration of Mars will lead the way for missions that will carry women and men to the red planet. Our engineers and scientists are formulating spacecraft that could use nuclear power to enable exploration missions of the future. And even now we are designing formations of space telescopes that will capture family portraits of the planets around neighboring stars. Those are only some of the ways that the Laboratory is contributing to NASA's broader goals. During 2004, JPL made a distinctive contribution to agencywide initiatives in areas such as safety, NASA transformation, the agency's Internet portal and NASA's Explorer Schools programs. Years like 2004 pose a special challenge for us. It would be easy to say that this was a once-in-a-decade high point of mission activities, but I believe that this would miss an opportunity. We are fortunate to have many space projects in the works that have the promise of being just as exhilarating as the great mission successes that we celebrated this year. The challenge and opportunity for us now is to make every year like this one.
Automation has contributed substantially to the sustained improvement of aviation safety by minimizing the physical workload of the pilot and increasing operational efficiency. Nevertheless, in complex and highly automated aircraft, automation also has unintended consequences. As systems become more complex and the authority and autonomy (A&A) of the automation increases, human operators become relegated to the role of a system supervisor or administrator, a passive role not conducive to maintaining engagement and airplane state awareness (ASA). The consequence is that flight crews can often come to over rely on the automation, become less engaged in the human-machine interaction, and lose awareness of the automation mode under which the aircraft is operating. Likewise, the complexity of the system and automation modes may lead to poor understanding of the interaction between a mode of automation and a particular system configuration or phase of flight. These and other examples of mode confusion often lead to mismanaging the aircraftâ€"TM"s energy state or the aircraft deviating from the intended flight path. This report examines methods for assessing whether, and how, operational constructs properly assign authority and autonomy in a safe and coordinated manner, with particular emphasis on assuring adequate airplane state awareness by the flight crew and air traffic controllers in off-nominal and/or complex situations.
A large variety of Remotely Piloted Aircraft (RPA) designs are currently in production or in development. These aircraft range from small electric quadcopters that are flown close to the ground within visual range of the operator, to larger systems capable of extended flight in airspace shared with conventional aircraft. Before RPA can operate routinely and safely in civilian airspace, we need to understand the unique human factors associated with these aircraft. The task of flying an RPA in civilian airspace involves challenges common to the operation of other highly-automated systems, but also introduces new considerations for pilot perception, decision-making, and action execution. RPA pilots participated in focus groups where they were asked to recall critical incidents that either presented a threat to safety, or highlighted a case where the pilot contributed to system resilience or mission success. Ninety incidents were gathered from focus-groups. Human factor issues included the impact of reduced sensory cues, traffic separation in the absence of an out-the-window view, control latencies, vigilance during monotonous and ultra-long endurance flights, control station design considerations, transfer of control between control stations, the management of lost link procedures, and decision-making during emergencies. Some of these concerns have received significant attention in the literature, or are analogous to human factors of manned aircraft. The presentation will focus on issues that are poorly understood, and have not yet been the subject of extensive human factors study. Although many of the reported incidents were related to pilot error, the participants also provided examples of the positive contribution that humans make to the operation of highly-automated systems.
Remotely Piloted Aircraft (RPA) range from small electric quadcopters that are flown close to the ground within visual range of the operator, to larger systems capable of extended flight in airspace shared with conventional aircraft. Before RPA can operate routinely and safely in civilian airspace, we need to understand the unique human factors associated with these aircraft. RPA pilots participated in focus groups where they were asked to recall critical incidents that either presented a threat to safety, or highlighted a case where the pilot contributed to system resilience or mission success. Ninety incidents were gathered from focus-groups. Human factor issues included the impact of reduced sensory cues, traffic separation in the absence of an out-the-window view, control latencies, vigilance during monotonous and ultra-long endurance flights, control station design considerations, transfer of control between control stations, the management of lost link procedures, and decision-making during emergencies. Some of these concerns have received significant attention in the literature, or are analogous to human factors of manned aircraft. Although many of the reported incidents were related to pilot error, the participants also provided examples of the positive contribution that humans make to the operation of highly-automated systems.
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.
This study investigates the behavior of fission gas bubbles and five metal precipitates (5MPs) (Mo, Ru, Rh, Tc, Pd) in spent uranium dioxide (UO 2 ) fuel under various ion irradiation doses, temperatures, and flux conditions. Utilizing in-situ ion irradiation and advanced transmission electron microscopy, we analyzed the evolution of fission gas bubbles and 5MPs in UO 2 samples from the Belgium Reactor 3 (BR-3). Our findings reveal significant shrinkage of fission gas bubbles and 5MPs with increasing irradiation dose, accompanied by a decrease in pair density. We demonstrate that ion irradiation induces a homogeneous re-solution process where individual atoms are ejected from bubbles and precipitates, leading to their dissolution and subsequent re-precipitation in the matrix. In conclusion, this study provides critical insights into the dynamic behavior of fission products under irradiation, facilitating the development of predictive models and contributing to the optimization of nuclear fuel performance and safety.