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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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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Remediation of Temporary Storage Sites in Support of the Port Hope Area Initiative - 20295

The Port Hope Area Initiative is a community-based solution for the long-term management of historic low level radioactive waste (LLRW) resulting from 60 years of uranium and radium processing operations in the Town of Port Hope which is located in Ontario, Canada. The Eldorado refinery, on the north shore of Lake Ontario, began refining radium-226 from pitchblende ore, later transitioning to the refining of uranium. Through the history of the operation, LLRW was deposited throughout the town of Port Hope as a result of fugitive emissions from the plant and/or through the re-use of process residues as building material and backfill. Historical clean-up activities conducted in the late 1970's involved the remediation of approximately 400 properties and the relocation of 100,000 cubic metres of contaminated soil to a disposal facility in Chalk River operated by Atomic Energy of Canada Limited (AECL). Owing to space limitations at that disposal facility, any LLRW identified through construction monitoring since that time has been stored in the community at three temporary storage sites located throughout the town. These include: the Centre Pier mound that contained approximately of 19,800 m{sup 3} of LLRW-impacted soil that originated from the construction of a new water treatment plant; two mounds located at a licensed storage facility containing LLRW obtained from residential clean-up activities (11,000 m{sup 3}); and a small pad adjacent to the municipal sewage treatment plant containing 2200 m{sup 3} of LLRW-containing sludge. With the construction of a new long-term waste management facility (LTWMF) that has been designed to house all of the LLRW identified within Port Hope, the three sites were early candidates for remediation. The clean-up of the three temporary storage sites was a significant milestone for the Port Hope Area Initiative. After a decade of planning and consultation, this work represents the first sites in the municipality to be remediated with the waste being safety removed and transferred to the newly constructed LTWMF. This paper discusses the challenges associated with the clean-up activities for these three sites and the strategies employed to address those challenges. These included weather-related challenges, owing to the seasons over which the work was conducted as well as those associated with working within a closely-knit community. Canadian Nuclear Laboratories (CNL), working on behalf of the federal government, has worked diligently to develop a positive and trusting relationship with the community. Consequently, the successful execution of this project needed to be sensitive to, and respectful of the needs of the community. In addition to the usual Health, Safety and Environment training, project staff received community awareness training that spoke to the history of this community-based initiative and the expected behavior when working within the community. Transportation routes were defined based on safety and the need to minimize disruption to local traffic while haul-times where scheduled around school bus hours to enhance public safety. The successful completion of this first of many remediation projects to be completed under the Port Hope Area Initiative reflected years of careful planning. Nevertheless, there were a number of 'lessons learned' that have been applied on other ongoing projects be completed under the Port Hope Area Initiative. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

I Asked 30,000 People in the Nuclear Industry About Safety Culture; This is What I Learned - 19204

Organizations in the nuclear industry place a high value on maintaining the safety of the workforce and community. Some of these organizations do a better job than others when it comes to developing and sustaining a healthy safety culture. We spent six years studying nuclear organizations to better understand the factors that influence safety culture. We used mixed methods to evaluate perceptions of safety culture in these organizations including administering a valid and reliable safety culture survey, conducting one-on-one interviews with managers, and facilitating focus groups with members of the workforce. We analyzed the quantitative and qualitative data collected from more than 30,000 workers in U.S. based organizations. All of the organizations had a nuclear component to their operations. They operated nuclear reactors, processed nuclear materials, decontaminated and decommissioned buildings with radiological contamination, cleaned-up hazardous/mixed waste, and conducted basic science research and development. We talked to craft workers, technicians, engineers, scientific professionals, support personnel, production workers, supervisors and managers. We conducted extensive statistical analysis and learned that, with rare exception, there is a gap between the perceptions of managers and the workforce that they manage. Managers almost always have a more positive perception of safety culture than the people that are actually performing the work. It is not a question of whether there will be a gap; it is simply a matter of the magnitude of the gap. We also learned through exploratory factor analysis that there is one dominant factor that accounted for almost all (75%) of the variance in the perceptions of safety culture. It was the behavior of the leaders, the decisions they made, and the systems they implemented that most influenced the workforce's perception of safety culture. Personal accountability for safety accounted for 14% of the variance, communication and reporting accounted for another 6%. Everything else accounted for the remaining 5%. Management systems, decision making and behavior is the dominant factor and managers almost always have a more positive perception than the people that work for them. People that work in organizations where management exhibits positive decision-making and safety-related behaviors tend to have more positive perceptions of safety culture. Based upon these results, we developed a theory that there were a few important factors on which management could focus on if they sought to influence the safety culture in their organization. Our experience and research suggests that management often fails to recognize five root causes of employee discontent. Employees seek: - To be recognized as an individual; - To be respected; - A sense of stability; - Fairness; - To make a difference. Understanding the perceptions of the workforce is critical because perceptions influence attitudes, which contribute to behaviors that determine individual performance. An organisation's performance is simply the sum of the performance of all of the members of that organization. To change an organisation's safety culture, interventions should target management behavior and decision making for the greatest return on investment. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Motion Planning Algorithms for Safety and Quantum Computing Efficiency

Motion planning remains a fundamental problem in robotics. Sampling-based algorithms use randomization to allow efficient solutions to this complex problem. As mobile robots and autonomous vehicles become more prevalent in everyday life, motion planning must be applied to increasingly challenging scenarios. Safety has become a paramount concern in motion planning for ensuring robotic applications enrich human lives. To date, many motion planning techniques to increase safety in the face of uncertain and dynamic environments have been developed. This dissertation first addresses distributional safety of Rapidly-Exploring Random Trees (RRT) through our algorithm W-Safe RRT. To acknowledge distributional uncertainty and poor modeling, W-Safe RRT uses the Wasserstein metric to provide a probabilistic bound on the distributional distance between a robot and obstacles. Human-interpretable environmental agent classification allows online safety margin adaptation. We propose and analyze an integrating region method for online classification that increases actor labeling accuracy based on behavioral feature values when compared to state of the art methods. The method performs class assignments based on local maximum likelihood in a created behavioral feature-space, allowing a notion of classification uncertainty. Model-based methods with safety guarantees can quickly become computationally in tractable, especially with multiple agents, higher dimensions, and plentiful unknowns. Sampling based algorithms have been parallelized for computation with multi-core computers and GPUs. We consider the use of quantum algorithms and computers for sampling-based motion planning for the first time. Quantum computing performs operations on superpositions of states and can solve certain problems much more efficiently than classical computers, but introduces previously unseen challenges. With Quantum-RRT, we recast the motion planning problem into a database-search structure and use Quantum Amplitude Amplification to find reachable states in the database with a quadratic performance increase over classical methods. We address two error sources with this method: quantum measurement and quantum oracle errors. We then extend this method to Parallel Quantum-RRT, which uses a manager-worker architecture with multiple parallel quantum workers to increase database search efficiency. We compare algorithm architectures and characterize probabilities of multiple workers finding solutions. Lastly, we test in simulation the quantum algorithms against classical versions in a wide variety of scenarios, concluding that a similar parallelization improvement is to be found in the quantum case as was found in the parallelization of classical RRT.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Effect of cathode on crosstalk in Si-based lithium-ion cells

Crosstalk between the cathode and the anode in Li-ion batteries has a great impact on performance, safety and cycle lifetime. However, a systematic investigation of crosstalk behavior in silicon (Si)-based cells with various cathode materials has not been reported. We investigated the crosstalk behavior of a Si anode coupled with one of the following cathodes—LiCoO 2 (LCO), LiNi 0.5 Mn 0.3 Co 0.2 (NMC532), and LiFePO 4 (LFP)—in a full cell. For each electrochemical couple, we compared electrolyte decomposition products, solid electrolyte interphase (SEI) chemistry, and degradation mechanisms during cycling. From a very early stage of cycling, each couple showed different crosstalk behavior; different electrolyte decomposition products and SEI chemistry on the Si anodes were seen. Specifically, the formation and growth mechanism of Si SEI differ depending on cathode materials. For the LFP system, the Si SEI rich in LiF and inorganic species, which is stable and robust. It forms at an early stage of cycle. As a result, the SEI of Si from the LFP system well tolerates SEI breakage due to mechanical changes of Si and suppresses Li loss, resulting in stable cycle life.

25 ENERGY STORAGE↗
NASA NTRS2009

A Belief-Based Model of Air Traffic Controllers Performing Separation Assurance

A model of an air traffic controller performing a separation assurance task was produced. The model was designed to be simple to use and deploy in a simulator, but still provide realistic behavior. The model is based upon an evaluation of the safety function of the controller for separation assurance, and utilizes fast and frugal heuristics and belief networks to establish a knowledge set for the controller model. Based on this knowledge set, the controller acts to keep aircraft separated. Validation results are provided to demonstrate the model s performance.

Landry, S.J.↗
NASA NTRSDate not supplied

A Framework for the Analysis of Deep Neural Networks in Autonomous Aerospace Applications using Bayesian Statistics

Deep Neural Networks (DNNs) are considered to be key components in many autonomous systems. Applications range from vision-based obstacle avoidance to intelligent/learning control and planning. Safety-critical applications as found in the aerospace domain require that the behavior of the DNN is validated and tested rigorously for safety of the autonomous system (AUS). In this paper, we present a framework to support testing of DNNs and the analysis of the network structure. Our framework employs techniques from statistical modeling and active learning to effectively generate test cases for DNN safety testing and performance analysis. We will present results of a case study on a physics-based Deep recurrent residual neural network (DR-RNN), which has been trained to emulate the aerodynamics behavior of a fixed-wing aircraft.

Deep Neural networks↗
NASA NTRSDate not supplied

Scenario-Based Task Design for Airline Pilot Anticipatory Behaviors: Asynchronous Assessment of Complex Cognitive Skills

Airline pilots must anticipate potential threats to passenger safety and efficient flight. Such anticipation needs to occur at both the system and individual levels, yet no formal training for these anticipatory behaviors currently exists. The emerging field of resilience engineering provides a framework to explore this problem. Given the complex nature of this problem, the assessment portion of the project constituted a challenge. Simulator time is expensive as simulators are costly to run, and they are extremely limited in number. Also, by the nature of their work, pilots as a group are hard to connect with in person; thus, asynchronous methods were adopted. Further, to ensure that authentic pilot behaviors were observed, task-based scenarios were used rather than focus group or interview protocols. This session explores the design of asynchronous learning and a measure for assessing pilot anticipatory behaviors outside of a simulator to help design learning opportunities for pilots. The scenario-based and active assessment items will be discussed in detail, and demonstrations of these items will be shared. These items constitute the bulk of the challenge for this work. At the time of this writing, data is being collected to assess the effectiveness of the interactive training module and validate the measures. This data will be analyzed and presented as part of the session. This will include any linkages between the scenario-based and traditional assessment items.

task design↗
DOE OSTI2025

E-scooter safety: How attitudinal factors influence risky behavior among shared e-scooter riders

In recent years, e-scooter usage for short-distance trips has grown rapidly. This surge in e-scooter use, combined with the high exposure of e-scooter riders to accident risk, has sparked concerns regarding e-scooter safety. Despite some studies focusing on e-scooter safety, little is known about how attitudinal factors lead e-scooter riders to engage in risky riding behaviors. In this paper, we developed a survey-based empirical model to identify the attitudinal factors influencing engagement in risky behaviors among e-scooter users. We used survey data collected from 420 shared e-scooter users in Chicago in 2022. The survey showed that 47.7% of respondents had experienced at least one collision or fall-off while riding e-scooters. We employed the Partial Least Squares Structural Equation Model (PLS-SEM) to examine the relationships between latent attitudinal factors and risky behavior engagement. Moreover, we conducted Permutation Multi-group Analysis (PMGA) to assess the moderating effect of socio-demographic factors within the estimated model. The findings suggest that riders’ unsafe riding attitude and riding confidence are the most influential factors shaping their risky behavior engagement. In addition, accident experience, infrastructure suitability, perceived enjoyment, traffic risk perception, and operational risk perception are among the other significant predictors. Among socio-demographic factors, gender, age, education, and car use frequency significantly influence riders’ engagement in risky behaviors. The results highlight the importance of infrastructure suitability and accident experience in analyzing e-scooter users’ riding behavior. The developed model advances our understanding of factors contributing to e-scooter riders’ risky behavior engagement. The findings offer valuable insights for policymakers and e-scooter vendors aiming to mitigate e-scooter users’ accident risk. Specifically, we recommend three safety countermeasures: (1) safety training programs to encourage a safer attitude, (2) practice-based initiatives to enhance riding confidence, and (3) infrastructure improvements, especially the expansion of bike lanes.

E-scooter↗
NASA NTRS2003

Archetypes for Organisational Safety

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.

Marais, Karen↗
DOE OSTI2021

Reachability Analysis for FollowerStopper: Safety Analysis and Experimental Results

Motivated by earlier work and the developer of a new algorithm, the FollowerStopper, this article uses reachability analysis to verify the safety of the FollowerStopper algorithm, which is a controller designed for dampening stop-and-go traffic waves. With more than 1100 miles of driving data collected by our physical platform, we validate our analysis results by comparing it to human driving behaviors. The FollowerStopper controller has been demonstrated to dampen stop-and-go traffic waves at low speed, but previous analysis on its relative safety has been limited to upper and lower bounds of acceleration. To expand upon previous analysis, reachability analysis is used to investigate the safety at the speeds it was originally tested and also at higher speeds. Two formulations of safety analysis with different criteria are shown: distance-based and time headway-based. The FollowerStopper is considered safe with distance-based criterion. However, simulation results demonstrate that the FollowerStopper is not representative of human drivers - it follows too closely behind vehicles, specifically at a distance human would deem as unsafe. On the other hand, under the time headway-based safety analysis, the FollowerStopper is not considered safe anymore. A modified FollowerStopper is proposed to satisfy time-based safety criterion. Simulation results of the proposed FollowerStopper shows that its response represents human driver behavior better.

Chou, Fang-Chieh↗
NASA NTRS2019

Human Performance Contributions to Safety in Commercial Aviation

Every day in aviation, pilots, air traffic controllers, and other front-line personnel perform countless correct judgments and actions in a variety of operational environments. These judgments and actions are often the difference between an accident and a non-event. Ironically, data on these behaviors are rarely collected or analyzed. Data-driven decisions about safety management and design of safety-critical systems are limited by the available data, which influence how decision makers characterize problems and identify solutions. Large volumes of data are collected on the failures and errors that result in infrequent incidents and accidents, but in the absence of data on behaviors that result in routine successful outcomes, safety management and system design decisions are based on a small sample of nonrepresentative safety data. This assessment aimed to find and document “safety successes” made possible by human operators. With many Aeronautics Research Mission Directorate (ARMD) Programs and Projects focusing on increased automation and autonomy and decreased human involvement, failure to fully consider the human contributions to successful system performance in civil aviation represents a significant risk — a risk that has not been recognized to date. Without understanding how humans contribute to safety, any estimate of predicted safety of autonomous capabilities is incomplete and inherently suspect. Furthermore, understanding the ways in which humans contribute to safety can promote strategic interactions among safety technologies, functions, procedures and the people using them. Without this understanding, the full benefits of an integrated, optimized human/technology or autonomous system will not be realized. Historically, safety has been consistently defined in terms of the occurrence of accidents or recognized risks (i.e., in terms of things that go wrong). These adverse outcomes are explained by identifying their causes, and safety is restored by eliminating or mitigating these causes. An alternative to this approach is to focus on what goes right and identify how to replicate that process. Focusing on the rare cases of failures attributed to “human error” provides little information about why human performance routinely prevents adverse events. Hollnagel has proposed that things go right because people continuously adjust their work to match their operating conditions. These adjustments become increasingly important as systems continue to grow in complexity. Thus, the definition of safety should reflect not only “avoiding things that go wrong” but “ensuring that things go right.” The basis for safety management requires developing an understanding of everyday activities. However, few mechanisms to monitor everyday work exist in the aviation domain, which limits opportunities to learn how designs function in reality. This concept of safety thinking and safety management is reflected in the emerging field of resilience engineering. According to Hollnagel, a system is resilient if it can sustain required operations under expected and unexpected conditions by adjusting its functioning prior to, during, or following changes, disturbances, and opportunities. To explore “positive” behaviors that contribute to resilient performance in commercial aviation, the assessment team examined a range of existing sources of data about pilot and air traffic control (ATC) tower controller performance, including subjective interviews with domain experts and objective aircraft flight data records. These data were used to identify strategies that support resilient performance, methods for exploring and refining those strategies in existing data, and proposed methods for capturing and analyzing new data.

Null, Cynthia H.↗
DOE OSTI2017

Constitutive behavior and progressive mechanical failure of electrodes in lithium-ion batteries

The electrodes of lithium-ion batteries (LIB) are known to be brittle and to fail earlier than the separators during an external crush event. Thus, the understanding of mechanical failure mechanism for LIB electrodes (anode and cathode) is critical for the safety design of LIB cells. In this paper, we present experimental and numerical studies on the constitutive behavior and progression of failure in LIB electrodes. Mechanical tests were designed and conducted to evaluate the constitutive properties of porous electrodes. Constitutive models were developed to describe the stress-strain response of electrodes under uniaxial tensile and compressive loads. The failure criterion and a damage model were introduced to model their unique tensile and compressive failure behavior. The failure mechanism of LIB electrodes was studied using the blunt rod test on dry electrodes, and numerical models were built to simulate progressive failure. The different failure processes were examined and analyzed in detail numerically, and correlated with experimentally observed failure phenomena. Finally, the test results and models improve our understanding of failure behavior in LIB electrodes, and provide constructive insights on future development of physics-based safety design tools for battery structures under mechanical abuse.

25 ENERGY STORAGE↗
DOE OSTI2023

Transition from Vogel-Fulcher-Tammann to Arrhenius Ion-Conducting Behavior in Poly(Ethyl Acrylate)-Based Solid Polymer Electrolytes via Succinonitrile Plasticizer Addition

Solid polymer electrolytes (SPEs) offer potential advantages over liquid electrolytes, including flexibility, safety, and processability. However, they suffer from low room-temperature ionic conductivity. Recently, it has been reported a poly(ethyl acrylate) based (polyEA) SPE, by incorporating 50 wt% of succinonitrile (SN) solid plasticizer, 30 wt% of lithium salt and 5 wt% of fluoroethylene carbonate additive, which achieves a high room-temperature ionic conductivity of 1.01 × 10 −3 S cm −1 (Nat. Nanotechnol, 2022, 17, 768-776). This novel SPE exhibits stability against Li 0 and anodic stability up to 4.9 V vs Li + /Li. However, the specific mechanism responsible for its high ionic conductivity remains elusive. In this work, by adjusting the weight ratio of SN in the SPE, a transition from Vogel-Fulcher-Tammann to Arrhenius ion-conducting behavior is observed. It is demonstrated that the addition of SN leads to the gradual decoupling of Li-ion from the polymer backbone and its coordination with SN, as revealed by 6 Li solid-state nuclear magnetic resonance spectroscopy. As a result, Li-ion migration primarily occurs through SN rather than the segmental motion of the polymer backbone. Performances of the SPE in Cu||Li, Li||Li and a LiFePO 4 ||Li pouch cells are shown to demonstrate the commercial viability of this SPE in Li 0 -anode solid-state batteries.

Electrochemistry↗
NASA NTRS2019

Human Performance Contributions to Safety in Commercial Aviation

In the commercial aviation domain, large volumes of data are collected and analyzed on the failures and errors that result in infrequent incidents and accidents, but in the absence of data on behaviors that contribute to routine successful outcomes, safety management and system design decisions are based on a small sample of non- representative safety data. Analysis of aviation accident data suggests that human error is implicated in up to 80% of accidents, which has been used to justify future visions for aviation in which the roles of human operators are greatly diminished or eliminated in the interest of creating a safer aviation system. However, failure to fully consider the human contributions to successful system performance in civil aviation represents a significant and largely unrecognized risk when making policy decisions about human roles and responsibilities. Opportunities exist to leverage the vast amount of data that has already been collected, or could be easily obtained, to increase our understanding of human contributions to “things going right” in commercial aviation. The principal focus of this assessment was to identify current gaps and explore methods for identifying human “success” data generated by the aviation system, from personnel and within the supporting infrastructure.

Holbrook, Jon B.↗
DOE OSTI2018

Modeling the Long-Term Behavior of Cementitious Barriers - 18188

Cementitious materials are commonly included as backfill/barrier materials in geological repositories for radioactive waste. An understanding of the long-term behavior of cement-based barriers is therefore required to provide confidence in their safety functions within an environmental safety case. Geochemical modelling has been undertaken on several different radioactive waste repository concepts (and their natural/industrial analogues), to explore the nature of cement degradation over timescales relevant to postclosure safety (many tens of thousands of years to c. 1 Ma). In radionuclide transport calculations undertaken as part of performance assessments, it is typically considered that the properties of cementitious engineered barrier materials change as they degrade, potentially resulting in an increase in porosity hydraulic conductivity, and effective diffusion coefficients. However, reactive transport modelling (supported by some analogue data) suggests that, in some repository systems, a degree of clogging of the cement pore space could occur and that some advective flow paths (cracks in the barriers, fractures in the host rock) could become (to some extent) infilled by cement and rock alteration products. This could result in a reduction in water flow and contaminant transport in the vicinity of the cement-rock interface, but some uncertainties remain (especially process couplings and the nature of water flow in complex fracture networks that are becoming clogged). In addition, the armoring of fracture surfaces could result in decreased potential for diffusion of solutes into the rock matrix. It is envisaged that ongoing work will continue to improve reactive-transport model capabilities, such that the implications cement degradation has for contaminant transport can be predicted with greater confidence. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRSDate not supplied

Systems Health Management and Decision Making

In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to accurately predict the future state of any system, it is required to possess knowledge of its current and future operations. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prior stated prediction problem. In case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operations of the vehicle. Discuss research approach to develop a system level health monitoring safety indicator which runs estimation and prediction algorithms to estimate remaining useful life predictions at system as well as subsystem levels. Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making. In addition a digital twin concept is being implemented in the framework to demonstrate verification and validation of developed algorithms. Note - This presentation is for the short workshop conducted at the same conference and contains all previously approved and published information.

Systems Health Managent↗
NASA NTRS2018

Systems Health Monitoring and Prognostics Using Model Based Approach

In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to accurately predict the future state of any system, it is required to possess knowledge of its current and future operations. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prior stated prediction problem. In case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operations of the vehicle. Our research approach is to develop a system level health monitoring safety indicator which runs estimation and prediction algorithms to estimate remaining useful life predictions at system as well as subsystem levels. Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making. In addition a digital twin concept is being implemented in the framework to demonstrate verification and validation of developed algorithms.

Electronics Prognostics↗
NASA NTRS2013

Modeling Complex Cross-Systems Software Interfaces Using SysML

The complex flight and ground systems for NASA human space exploration are designed, built, operated and managed as separate programs and projects. However, each system relies on one or more of the other systems in order to accomplish specific mission objectives, creating a complex, tightly coupled architecture. Thus, there is a fundamental need to understand how each system interacts with the other. To determine if a model-based system engineering approach could be utilized to assist with understanding the complex system interactions, the NASA Engineering and Safety Center (NESC) sponsored a task to develop an approach for performing cross-system behavior modeling. This paper presents the results of applying Model Based Systems Engineering (MBSE) principles using the System Modeling Language (SysML) to define cross-system behaviors and how they map to crosssystem software interfaces documented in system-level Interface Control Documents (ICDs).

Earth orbit↗