Results for “Behavior Based Safety” — Page 24

DOE OSTI2025

Manganese‐Based Spinel Cathodes: A Promising Frontier for Solid‐State Lithium‐Ion Batteries

Recently, all-solid-state lithium-ion batteries (ASSLIBs), which exhibit improved safety and enhanced energy density compared to conventional commercialized lithium-ion batteries (LIBs), thereby have garnered extensive research interest. Among the promising cathode candidates, Mn-based spinel cathodes LiMn 2 O 4 (LMO) and LiNi 0.5 Mn 1.5 O 4 (LNMO), with the unique characteristics of low cost, structural stability, and 3D Li-ion diffusion channels, have demonstrated excellent performance in LIBs and presented great potential in ASSLIBs applications. However, several challenges, including structural degradations, poor interfacial contact, large interfacial resistance, and Mn-dissolution/diffusion during the electrochemical cycling, hinder their practical applications and commercialization in the ASSLIBs. Particularly, the high-voltage LNMO cathodes suffer from the challenge of electrochemical incompatibility with most of the solid-state electrolytes (SSEs). Herein, the spinel structure, the electrochemical behavior, and the structural degradation of the LMO/LNMO are explored. The characteristics and recent progress of the mitigating strategies to the challenges of various SSEs, including polymer-, oxide-, composite-, sulfide-, halide-, and LiPON-based SSEs, are introduced when paired with LMO/LNMO. Finally, the directions for future research to advance Mn-based spinel cathodes and fulfill the requirements of the next-generation ASSLIBs are also discussed.

Dou, Yu [Concordia University, Montreal, QC (Canad↗

DOE OSTI2025

Step-loaded creep testing of Zircaloy-4 cladding at higher temperatures in the α-phase

A refined understanding of zirconium-based cladding thermomechanical performance during rapid transients is essential for enhancing the safety and operation of light-water reactors. Traditional models for zirconium alloys under accident conditions generally assume that creep dominates fuel cladding performance. Here, these historic models have largely remained unchanged and serve as the basis for safety criteria development. As the U.S. nuclear industry pursues higher burnup levels, the increased release of fission gases during transients raises the risk of cladding failure in the low-temperature hcp α-phase, making the fidelity of these models of greater importance. Creep testing was conducted from 550–700°C with 25–120 MPa applied hoop stresses to investigate Zircaloy-4 deformation at accident-relevant temperatures in the α-phase. Step-loading was employed to capture creep behavior across a wide stress range from a single sample. The stress-strain rate data at higher temperatures (650 and 700°C) were well-described by isotropic versions of the Erbacher and Kaddour models, while the lower temperature data (550 and 600°C) were underpredicted by both anisotropic and isotropic model variants. Greater strain rates during the initial loading step at 650 and 700°C were attributed to recrystallization and grain growth of sub-micron crystallites. Yet, texture analysis revealed the basal split texture remained after testing. These observations produced results suggesting Zircaloy-4 claddings experience higher creep rates across the α-phase than previously thought, possibly related to dynamic anisotropy due to temperature dependent activation of deformation mechanisms, effects of biaxial loading, and variation in material condition between the current testing used in previous model development.

36 MATERIALS SCIENCE↗

NASA NTRS2004

Explanation Constraint Programming for Model-based Diagnosis of Engineered Systems

We can expect to see an increase in the deployment of unmanned air and land vehicles for autonomous exploration of space. In order to maintain autonomous control of such systems, it is essential to track the current state of the system. When the system includes safety-critical components, failures or faults in the system must be diagnosed as quickly as possible, and their effects compensated for so that control and safety are maintained under a variety of fault conditions. The Livingstone fault diagnosis and recovery kernel and its temporal extension L2 are examples of model-based reasoning engines for health management. Livingstone has been shown to be effective, it is in demand, and it is being further developed. It was part of the successful Remote Agent demonstration on Deep Space One in 1999. It has been and is being utilized by several projects involving groups from various NASA centers, including the In Situ Propellant Production (ISPP) simulation at Kennedy Space Center, the X-34 and X-37 experimental reusable launch vehicle missions, Techsat-21, and advanced life support projects. Model-based and consistency-based diagnostic systems like Livingstone work only with discrete and finite domain models. When quantitative and continuous behaviors are involved, these are abstracted to discrete form using some mapping. This mapping from the quantitative domain to the qualitative domain is sometimes very involved and requires the design of highly sophisticated and complex monitors. We propose a diagnostic methodology that deals directly with quantitative models and behaviors, thereby mitigating the need for these sophisticated mappings. Our work brings together ideas from model-based diagnosis systems like Livingstone and concurrent constraint programming concepts. The system uses explanations derived from the propagation of quantitative constraints to generate conflicts. Fast conflict generation algorithms are used to generate and maintain multiple candidates whose consistency can be tracked across multiple time steps.

Narasimhan, Sriram↗

NASA NTRS2013

Autonomous Control of Space Nuclear Reactors

Nuclear reactors to support future robotic and manned missions impose new and innovative technological requirements for their control and protection instrumentation. Long-duration surface missions necessitate reliable autonomous operation, and manned missions impose added requirements for failsafe reactor protection. There is a need for an advanced instrumentation and control system for space-nuclear reactors that addresses both aspects of autonomous operation and safety. The Reactor Instrumentation and Control System (RICS) consists of two functionally independent systems: the Reactor Protection System (RPS) and the Supervision and Control System (SCS). Through these two systems, the RICS both supervises and controls a nuclear reactor during normal operational states, as well as monitors the operation of the reactor and, upon sensing a system anomaly, automatically takes the appropriate actions to prevent an unsafe or potentially unsafe condition from occurring. The RPS encompasses all electrical and mechanical devices and circuitry, from sensors to actuation device output terminals. The SCS contains a comprehensive data acquisition system to measure continuously different groups of variables consisting of primary measurement elements, transmitters, or conditioning modules. These reactor control variables can be categorized into two groups: those directly related to the behavior of the core (known as nuclear variables) and those related to secondary systems (known as process variables). Reliable closed-loop reactor control is achieved by processing the acquired variables and actuating the appropriate device drivers to maintain the reactor in a safe operating state. The SCS must prevent a deviation from the reactor nominal conditions by managing limitation functions in order to avoid RPS actions. The RICS has four identical redundancies that comply with physical separation, electrical isolation, and functional independence. This architecture complies with the safety requirements of a nuclear reactor and provides high availability to the host system. The RICS is intended to interface with a host computer (the computer of the spacecraft where the reactor is mounted). The RICS leverages the safety features inherent in Earth-based reactors and also integrates the wide range neutron detector (WRND). A neutron detector provides the input that allows the RICS to do its job. The RICS is based on proven technology currently in use at a nuclear research facility. In its most basic form, the RICS is a ruggedized, compact data-acquisition and control system that could be adapted to support a wide variety of harsh environments. As such, the RICS could be a useful instrument outside the scope of a nuclear reactor, including military applications where failsafe data acquisition and control is required with stringent size, weight, and power constraints.

Merk, John↗

DOE OSTI2016

Nuclide Release Pathways in and Around a Trench Repository for Radioactive Waste - 16014

An effective model for a safety assessment of a conceptual trench repository system, in which low-and intermediate level radioactive waste (LILW) is disposed of has been developed. The repository system is assumed to be located in the surface area of a mountain hill near the seashore. An easy-to-use computer program based on this model, developed as a GoldSim template, has been extended based on the previous one in consideration of the rather possible complex pathways in and around the trench for its performance assessment, which is able to evaluate a nuclide release from the repository and farther transport into the geosphere and biosphere under various normal, disruptive natural, and manmade events, and scenarios that can occur after a failure of waste drums with associated uncertainty. To demonstrate the nuclide release and transport behavior through these various possible pathways in the near- and far-fields of the repository system under certain scenarios, some illustrative evaluations and a simple sensitivity investigation with C-14 for the concrete barriers of the trench were made. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

The promise of metal-halide-perovskite solar photovoltaics: A brief review

Solar photovoltaics (PVs) based on metal-halide perovskites (MHPs) have taken the renewable-energy world by storm. The excitement stems from the promise of a high-efficiency, low-cost, and low “carbon-footprint” new PV technology. Here, a brief overview of the important topics pertaining to MHPs, perovskite solar cells (PSCs) and perovskite solar modules (PSMs) is presented. The topics include: (1) PSC architectures, (2) MHPs, (3) synthesis and processing of MHP thin films, (4) MHP thin-film microstructures, (5) PSC functional layers, (6) interfacial engineering in PSCs, (7) PSC performance, (8) PSC stability, (9) PSMs, (10) lead toxicity, and (11) mechanical behavior and reliability. The significant challenges in the path toward commercialization of this burgeoning PV technology are also highlighted. Chief among them are scalability, stability, reliability, and safety, while achieving high efficiency, low cost, and low “carbon-footprint.” Furthermore, the promise of this new PV technology and the fascinating underlying science make it a worthwhile endeavor to address these challenges.

14 SOLAR ENERGY↗

DOE OSTI2017

The Trip Itinerary Optimization Platform: A Framework for Personalized Travel Information

The New Concepts Incubator team at the National Renewable Energy Laboratory (NREL) developed a three-stage online platform for travel diary collection, personal travel plan optimization and travel itinerary visualization. In the first stage, users provide a travel diary for the previous day through an interactive map and calendar interface and survey for travel attitudes and behaviors. One or more days later, users are invited via email to engage in a second stage where they view a personal mobility dashboard displaying recommended travel itineraries generated from a novel framework that optimizes travel outcomes over a sequence of interrelated trips. A week or more after viewing these recommended travel itineraries on the dashboard, users are emailed again to engage in a third stage where they complete a final survey about travel attitudes and behaviors. A usability study of the platform conducted online showed that, in general, users found the system valuable for informing their travel decisions. A total of 274 individuals were recruited through Amazon Mechanical Turk, an online survey platform, to participate in a transportation study using this platform. On average, the platform distilled 65 feasible travel plans per individual into two recommended itineraries, each optimal according to one or more outcomes and dependent on the fixed times and locations from the travel diary. For 45 percent of users, the trip recommendation algorithm returned only a single, typically automobile-centric, itinerary because there were no other viable alternative transportation modes available. Platform users generally agreed that the dashboard was enjoyable and easy to use, and that it would be a helpful tool in adopting new travel behaviors. Users generally agreed most that the time, cost and user preferred recommendations 'made sense' to them, and were most willing to implement these itineraries. Platform users typically expressed low willingness to try the carbon and calories optimized itineraries. Of the platform users who viewed the dashboard, 13 percent reported changing their travel behavior, most adopting the time, calories or carbon optimized itineraries. While the algorithm incorporates a wealth of travel data obtained from online APIs pertaining to a travelers route such as historic traffic condition data, public transit time-tables, and bike path routes, open-ended responses from users expressed an interest in the integration of even more fine-grained traffic data and the ability to dynamically model the effect of changes in travel times. Users also commonly expressed concerns over the safety of walking and biking recommendations. Responses indicate that more information about the amenities available to cyclists and pedestrians (sidewalks, shade from trees, access to food) and routes that avoid areas of perceived elevated danger would reduce barriers to implementing these recommendations. More accurate representations of personal vehicle trips (based on vehicle make and model, implications of parking) and the identification of routes that optimize caloric intensity (seeking out elevation changes or longer walks to public transit) are promising avenues for future research.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2018

In Situ Monitoring of Groundwater Contamination for Sustainable Remediation Using the Kalman Filter - 18423

Groundwater monitoring is critical for nuclear-related facilities as well as radioactively contaminated sites. Recent advances in sensing, data analytics and simulation capabilities provide substantial opportunities to improve and change current monitoring procedures. In particular, we need a paradigm shift from contaminant-only or compliance-only monitoring programs to comprehensive monitoring, i.e., including other ancillary environmental variables for a holistic understanding of the groundwater systems and plume behaviors. Such new approaches are needed for the effective implementation of sustainable remediation (enhanced and natural attenuation), and they have great potential for cost reduction in site monitoring. This paper reviews recent developments for improving long-term monitoring, with focus on the effective use of in situ sensors, data analytics and simulation capabilities. In particular, we highlight a recent application of the Kalman filter algorithm to estimate contaminant concentrations continuously in real time, based on in-situ measured water quality parameters (e.g. electrical conductance and pH) and sparse groundwater sampling. The results show that we can reduce the groundwater sampling frequency significantly, while capturing the dynamics of short- and long-term contaminant concentration changes. Such advanced and integrated monitoring systems will be beneficial for local residents (e.g., to ensure the safety by detecting adverse events early, enabling a swift response) as well as for site operators (e.g., to gain/improve public acceptance, to be better prepared for litigations and false claims, and to reduce overall monitoring cost). (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2017

Determining appropriate data analytics for transformer health monitoring - 107

Transformers are vital assets for the safe, reliable and cost-effective operation of nuclear power plants. The unexpected failure of a transformer can lead to different consequences ranging from a lack of export capability, with the corresponding economic penalties, to catastrophic failure, with the associated health, safety and economic effects. Condition monitoring techniques examine the health of the transformer periodically, with the aim to identify early indicators of anomalies. However, many transformer failures occur because diagnostic and monitoring models do not identify degraded conditions in time. Therefore, health monitoring is an essential component to transformer life cycle management. Existing tools for transformer health monitoring use traditional dissolved gas analysis based diagnostics techniques. With the advance of prognostics and health management (PHM) applications, we can enhance traditional transformer health monitoring techniques using PHM analytics. The design of an appropriate data analytics system requires a multi-stage design process including: (i) specification of engineering requirements; (ii) characterization of existing data sources and analytics to identify complementary techniques; (iii) development of the functional specification of the analytics suite to formalize its behavior, and finally (iv) deployment, validation, and verification of the functional requirements in the final platform. Accordingly, in this paper we propose a transformer analytics suite which incorporates anomaly detection, diagnostics, and prognostics modules in order to complement existing tools for transformer health monitoring. (authors)

42 ENGINEERING↗

DOE OSTI2026

Bayesian Optimization of Non-Invariant Systems with Constraints Developed for Application to the ECR Ion Source VENUS

In this work, we consider the optimization of non-invariant systems with both safety and control constraints. We present a new approach based on Bayesian optimization for the dynamic, safe and controlled optimization of such systems. Although there are other possible use cases, we focus on the application to the electron cyclotron resonance ion source VENUS. From experimental data, we have observed that VENUS behaves to first order as a non-invariant dynamic system with moving areas of instability. Our novel approach aims at providing a tool that can maintain system optimization in a safe way. This is accomplished by making sure the objective function, the beam current in the case of VENUS, does not fall under an operational minimum, while simultaneously requiring the optimization to avoid areas where VENUS is unstable. We compare the result of our approach on synthetic data modeled to mimic the behavior of VENUS with two methods from the literature, a standard Bayesian optimizer and a safe Bayesian optimizer, both adapted to deal with dynamic systems. A cross Student T-test is conducted to show the significance of the improvement given by the new method we introduce here, regarding the two preexisting methods we compared to. The results of the tests conducted on synthetic data show that the proposed method succeeds at maintaining the system optimized and obeys the predefined constraints better than the literature methods explored.

Bayesian optimization↗

NASA NTRS2010

Contingency Operations of Americas Next Moon Rocket, Ares V

America has begun the development of a new space vehicle system which will enable humans to return to the moon and reach even farther destinations. The system is called Constellation: it has 2 earth-launch vehicles, Ares I and Ares V; a crew module, Orion; and a lander, Altair with descent and ascent stages. Ares V will launch an Earth Departure Stage (EDS) and Altair into low earth orbit. Ares I will launch the Orion crew module into low earth orbit where it will rendezvous and dock with the Altair and EDS "stack". After rendezvous, the stack will contain four complete rocket systems, each capable of independent operations. Of course this multiplicity of vehicles provides a multiplicity of opportunities for off-nominal behavior and multiple mitigation options for each. Contingency operations are complicated by the issues of crew safety and the possibility of debris from the very large components impacting the ground. This paper examines contingency operations of the EDS in low earth orbit, during the boost to translunar orbit, and after the translunar boost. Contingency operations under these conditions have not been a consideration since the Apollo era and analysis of the possible contingencies and mitigations will take some time to evolve. Since the vehicle has not been designed, much less built, it is not possible to evaluate contingencies from a root-cause basis or from a probability basis; rather they are discussed at an effects level (such as the reaction control system is consuming propellant at a high rate). Mitigations for the contingencies are based on the severity of the off-nominal condition, the time of occurrence, recovery options, options for alternate missions, crew safety, evaluation of the condition (forensics) and future prevention. Some proposed mitigations reflect innovation in thinking and make use of the multiplicity of on-orbit resources including the crew; example: Orion could do a "fly around" to allow the crew to determine the condition and cause of a partially separated payload shroud. Other mitigations are really alternate missions; example, an engine out on during ascent resulted in insufficient propellant for the lunar mission, but the on-orbit vehicle stack is otherwise perfect and can pursue an alternate mission, such as a high ballistic trajectory to test the high-speed atmospheric reentry of Orion. Evaluation and presentation of contingency operations at this early stage of the development of the Ares V rocket will improve the design of the vehicle and lay the groundwork for the exhaustive contingency planning which must be done after the vehicle is built as preparations for operations.

Jaap, John↗

NASA NTRS1990

Assessing information transfer in full mission flight simulations

Considerable attention must be given to the important topic of aircrew situation awareness in any discussion of aviation safety and flight deck design. Reliable means of assessing this important aspect of crew behavior without simultaneously interfering with the behavior are difficult to develop. Unobtrusive measurement of crew situation awareness is particularly important in the conduct of full mission simulations where considerable effort and cost is expended to achieve a high degree of operational fidelity. An unobtrusive method of assessing situational awareness is described here which employs a topical analysis of intra-crew communications. The communications were taken from videotapes of crew behavior prior to, during, and following an encounter with a microburst/windshear event. The simulation scenario re-created an actual encounter with an event during an approach into Denver Stapleton Airport. The analyses were conducted on twelve experienced airline crews with the objective of determining the effect on situation awareness of uplinking ground-based information of the crew during the approach. The topical analysis of crew communication was conducted on all references to weather or weather-related topics. The general weather topic was further divided into weather subtopical references such as surface winds, windshear, precipitation, etc., thereby allowing for an assessment of the relative frequency of subtopic reference during the scenario. Reliable differences were found between the relative frequency of subtopic references when comparing the communications of crews receiving a cockpit display of ground-based information to the communications of a control group. The findings support the utility of this method of assessing situation awareness and information value in full mission simulations. A limiting factor in the use of this measure is that crews vary in the amount of intra-crew communications that may take place due to individual differences and other factors associated with crew coordination. This factor must be taken into consideration when employing this measure. Viewgraphs are given.

Lee, Alfred T.↗

DOE OSTI2020

On the Formalization of Development and Assessment Process for Digital Twins in the Nearly Autonomous Management and Control System

In recent years, the autonomous control system has been encouraged in advanced reactors for restoring economic viability, simplifying the operation and maintenance, and enabling remote-site power generations [1]. Since the reactor is expected to be operated for a long period of time with a limited number of individuals onsite, it is recommended that the autonomous control system should have access to very realistic models of the state of processes in the whole lifecycle, together with these process behaviors in interaction with their environment in the real world. As a result, digital twin (DT) technology is suggested in autonomous control systems. DT is defined as a digital representation of a physical object or system, which contains a record for the histories of loads, operation and maintenance status, predictions for the near-term transient of important state variables, and decision-making process [2]. Since machine learning (ML) can recognize patterns within a complex system in real-time applications, it has been used to build DTs in the autonomous control systems for advanced reactors. Meanwhile, due to the rareness of operation data in accident scenarios, the development and assessment of DTs is expected to be mainly driven by simulations. Although the capability and feasibility of ML-based DTs are recognized in improving the safety and efficiency of reactor control, a major concern from the regulatory commission and the nuclear industry is whether the information from a DT is developed and assessed in accordance with expectation and requirements by the target decision. Such concerns not only affect the acceptance criteria for DTs, but also values that can be extracted from DTs and autonomous control system during operations. Inspired by the success of formal methods in improving the reliability and robustness of computer programming and software development, it is suggested that the development and assessment process (DAP) for both separate DTs and integral control system should be formalized in a transparent, consistent, and improvable manner. In this study, a digital-twin development and assessment process (DT-DAP) is proposed by adapting the evaluation model development and assessment process (EMDAP) [3] to requirements by the autonomous control system, ML algorithms, and DT technology. To demonstrate the framework, a baseline nearly autonomous management and control (NAMAC) system with ML-based DTs for diagnosis and prognosis is developed and assessed based on the framework. It is found that with selected testing methods and techniques, the DT-DAP can help identify errors in DTs and NAMAC which would otherwise be left unverified. Meanwhile, it is found that the DT-DAP can improve the DTs and NAMAC by continuously learning and iterating through different elements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRSDate not supplied

The effect of reduced pressure on the characteristics of spreading flames

Flame spread over solid fuels is a canonical problem in fire science, due to its direct implications on material flammability and importance in fire development. In a microgravity environment, such as onboard a spacecraft, flames can behave very differently than on Earth. This is concerning for spaceflight life safety, especially in higher-oxygen environments. Due to the difficulties associated with microgravity testing, low-pressure environments have been proposed as an alternative to approximately replicate the burning behavior of solid fuels observed in reduced gravity conditions because of similar diffusion and heat transfer mechanisms. However, the roles played by gravity and pressure on flame length, standoff distance, and flame spread rate vary with the burning configuration. In concurrent flame spread, the buoyant flow enhances the spread rate by bringing the flame closer to the fuel surface and increasing the heating of the solid fuel. In opposed flame spread, the sample is preheated by the flame ahead of the flame leading edge, which is strongly affected by the surrounding flow field. In this work, we consider flames spreading over thin cotton samples in both downward (opposed) and upward (concurrent) configurations to investigate the effect of pressure (30-100 kPa) on flame characteristics, such as spread rate and standoff distance. A small forced flow is induced upward so that the flames are exposed to a mixed (forced and free) flow. By reducing pressure, flames become less bright, their standoff distance increases, and their spread rates decrease similar to what is observed in low-gravity environments. These results could in help understanding the differences between flames spreading at low pressure and low gravity environments for these similar, yet very different, spreading configurations. They could also provide more information about potential Earth-based flammability testing of materials for spacecraft applications.

fire safety↗

NASA NTRSDate not supplied

The Effect of Reduced Pressure on the Characteristics of Spreading Flames

Flame spread over solid fuels is a canonical problem in fire science, due to its direct implications on material flammability and importance in fire development. In a microgravity environment, such as onboard a spacecraft, flames can behave very differently than on Earth. This is concerning for spaceflight life safety, especially in higher-oxygen environments. Due to the difficulties associated with microgravity testing, low-pressure environments have been proposed as an alternative to approximately replicate the burning behavior of solid fuels observed in reduced gravity conditions because of similar diffusion and heat transfer mechanisms. However, the roles played by gravity and pressure on flame length, standoff distance, and flame spread rate vary with the burning configuration. In concurrent flame spread, the buoyant flow enhances the spread rate by bringing the flame closer to the fuel surface and increasing the heating of the solid fuel. In opposed flame spread, the sample is preheated by the flame ahead of the flame leading edge, which is strongly affected by the surrounding flow field. In this work, we consider flames spreading over thin cotton samples in both downward (opposed) and upward (concurrent) configurations to investigate the effect of pressure (30-100 kPa) on flame characteristics, such as spread rate and standoff distance. A small forced flow is induced upward so that the flames are exposed to a mixed (forced and free) flow. By reducing pressure, flames become less bright, their standoff distance increases, and their spread rates decrease similar to what is observed in low-gravity environments. These results could in help understanding the differences between flames spreading at low pressure and low gravity environments for these similar, yet very different, spreading configurations. They could also provide more information about potential Earth-based flammability testing of materials for spacecraft applications.

fire safety↗

NASA NTRSDate not supplied

Systems Health Management and Prognostics Approaches for Electric Aircrafts

As more and more electric vehicles emerge in our daily operation progressively, a very critical challenge lies in the prediction of remaining driving flying time/distance for the flying vehicles. This information is important, particularly in the case of auto vehicles, because such vehicles can become self-aware, autonomously compute its own capabilities, and identify how to best plan and successfully complete vehicular missions safely. In case of electric aircrafts, computing the remaining flying time is also safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision-making. A systematic prediction framework is implemented to identify all possible sources of uncertainty, quantify each of them individually, and mathematically estimate their combined effect on the system-level quantity of interest, in this case, the remaining flying time/distance of the unmanned aircraft. Note - This presentation contains all previously published information.

Systems Health Managent↗

NASA NTRSDate not supplied

Health Monitoring and Prognostics for Electric Aircrafts

As more and more electric vehicles emerge in our daily operation progressively, a very critical challenge lies in the prediction of remaining driving flying time/distance for the flying vehicles. This information is important, particularly in the case of auto vehicles, because such vehicles can become self-aware, autonomously compute its own capabilities, and identify how to best plan and successfully complete vehicular missions safely. In case of electric aircrafts, computing the remaining flying time is also safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision-making. A systematic prediction framework is implemented to identify all possible sources of uncertainty, quantify each of them individually, and mathematically estimate their combined effect on the system-level quantity of interest, in this case, the remaining flying time/distance of the unmanned aircraft. Note - This presentation contains all previously approved and published information.

Systems Health Managent↗

NASA NTRS2007

Gravity-Dependent Combustion and Fluids Research - From Drop Towers to Aircraft to the ISS

Driven by the need for knowledge related to the low-gravity environment behavior of fluids in liquid fuels management, thermal control systems and fire safety for spacecraft, NASA embarked on a decades long research program to understand, accommodate and utilize the relevant phenomena. Beginning in the 1950s, and continuing through to today, drop towers and aircraft were used to conduct an ever broadening and increasingly sophisticated suite of experiments designed to elucidate the underlying gravity-dependent physics that drive these processes. But the drop towers and aircraft afford only short time periods of continuous low gravity. Some of the earliest rocket test flights and manned space missions hosted longer duration experiments. The relatively longer duration low-g times available on the space shuttle during the 1980s and 1990s enabled many specialized experiments that provided unique data for a wide range of science and engineering disciplines. Indeed, a number of STS-based Spacelab missions were dedicated solely to basic and applied microgravity research in the biological, life and physical sciences. Between 1980 and 2000, NASA implemented a vigorous Microgravity Science Program wherein combustion science and fluid physics were major components. The current era of space stations from the MIR to the International Space Station have opened up a broad range of opportunities and facilities that are now available to support both applied research for technologies that will help to enable the future exploration missions and for a continuation of the non-exploration basic research that began over fifty years ago. The ISS-based facilities of particular value to the fluid physics and combustion/fire safety communities are the Fluids and Combustion Facility Combustion Integrated Rack and the Fluids Integrated Rack.

Urban, David L.↗