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At least 37 records · Page 2

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↗

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↗

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↗

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↗

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↗

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.↗

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↗

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.↗

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↗

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↗

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↗

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↗

Model-Based Safety Analysis

System safety analysis techniques are well established and are used extensively during the design of safety-critical systems. Despite this, most of the techniques are highly subjective and dependent on the skill of the practitioner. Since these analyses are usually based on an informal system model, it is unlikely that they will be complete, consistent, and error free. In fact, the lack of precise models of the system architecture and its failure modes often forces the safety analysts to devote much of their effort to gathering architectural details about the system behavior from several sources and embedding this information in the safety artifacts such as the fault trees. This report describes Model-Based Safety Analysis, an approach in which the system and safety engineers share a common system model created using a model-based development process. By extending the system model with a fault model as well as relevant portions of the physical system to be controlled, automated support can be provided for much of the safety analysis. We believe that by using a common model for both system and safety engineering and automating parts of the safety analysis, we can both reduce the cost and improve the quality of the safety analysis. Here we present our vision of model-based safety analysis and discuss the advantages and challenges in making this approach practical.

Joshi, Anjali↗

Structure evolution and tin redistribution during oxidation of Zircaloy-4 at 500°C

Zirconium (Zr) alloys are widely used as fuel cladding in nuclear power reactors due to their thermal stability, mechanical durability, corrosion resistance, and low neutron absorption cross-section. However, their performance is challenged by oxidation in reactor environments, making the study of Zr alloy corrosion behavior crucial for ensuring the safety, longevity, and economic viability of nuclear power systems. While the oxidation behavior of Zr-based cladding materials has been extensively studied since the 1950s, a mechanistic understanding into the relationship between structure evolution, solute element redistribution, and properties remains elusive. Valuable insights may be obtained through advanced experimental methods, such as in-situ and high resolution microscopy techniques. Here, in this study, the oxidation behavior of Zircaloy-4 at 500 °C in O 2 is characterized using a multimodal advanced characterization approach. Using in-situ X-ray diffraction, the phase evolution from metastable to stable oxides is tracked in real time. Complementary high-resolution techniques, including electron microscopy and atom probe tomography, reveal nanoscale insights into the microstructural changes and solute redistribution across the oxide/metal interface. Nanohardness mapping across the oxide/metal interface highlights localized mechanical property variations that may be linked to changes in microstructure and crystal structure within the oxide layer. These findings offer valuable insights into the microstructure and property evolution of Zircaloy-4 during oxidation, contributing to a better understanding of microstructural changes in Zr-based alloys under oxidative environments.

APT↗

Performability evaluation of the SIFT computer

The paper deals with the models, techniques, and evaluation methods that were successfully used to test the performance of the SIFT degradable computing system. The performance of the computer plus its air transport mission environment is modeled as a random variable, taking values in a set of 'accomplishment level'. The levels are defined in terms of four attributes of total system (computer plus environment) behavior, namely safety, no change in mission profile, no operational penalties, and no economic penalties. The base model of the total system is a stochastic process, whose states describe the internal structure of SIFT and the relevant conditions of its computational environment. Base model state trajectories are related to accomplishment levels via a special function, and solution methods are then used to determine the performability of the total system for various parameters of the computer and environment.

Meyer, J. F.↗

Magnetically Actuated Propellant Orientation Experiment, Controlling Fluid Motion With Magnetic Fields in a Low-Gravity Environment

This report details the results of a series of fluid motion experiments to investigate the use of magnets to orient fluids in a low-gravity environment. The fluid of interest for this project was liquid oxygen (LO2) since it exhibits a paramagnetic behavior (is attracted to magnetic fields). However, due to safety and handling concerns, a water-based ferromagnetic mixture (produced by Ferrofluidics Corporation) was selected to simplify procedures. Three ferromagnetic fluid mixture strengths and a nonmagnetic water baseline were tested using three different initial fluid positions with respect to the magnet. Experiment accelerometer data were used with a modified computational fluid dynamics code termed CFX-4 (by AEA Technologies) to predict fluid motion. These predictions compared favorably with experiment video data, verifying the code's ability to predict fluid motion with and without magnetic influences. Additional predictions were generated for LO2 with the same test conditions and geometries used in the testing. Test hardware consisted of a cylindrical Plexiglas tank (6-in. bore with 10-in. length), a 6,000-G rare Earth magnet (10-in. ring), three-axis accelerometer package, and a video recorder system. All tests were conducted aboard the NASA Reduced-Gravity Workshop, a KC-135A aircraft.

Martin, J. J.↗

Anomalous Thermal Decomposition Behavior of Polycrystalline LiNi 0.8 Mn 0.1 Co 0.1 O 2 in PEO-Based Solid Polymer Electrolyte

we report that replacing liquid electrolytes (LEs) with polymer electrolytes has been considered a promising approach to developing next-generation lithium-ion batteries (LIBs) with high energy density and superior safety. Nevertheless, compared with the extensive research on the electrochemical stability of the cathode/polymer electrolyte interfaces, reports on their thermal behaviors are rare to date. Herein, this work systematically investigates the thermal stability of two typical layered oxide cathodes, LiCoO 2 (LCO) and LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811), with poly(ethylene oxide) (PEO) electrolyte and with carbonate LEs, respectively. It is found that the oxygen release from the cathodes plays a central role in thermal runaway. Replacing the LE with PEO electrolyte can considerably improve the thermal stability of LCO, but surprisingly, deteriorate that of NMC811. The reason is that the surface of single-crystalline LCO particles can be effectively passivated by the PEO electrolyte during heating, but PEO cannot sufficiently passivate all the primary particles of NMC811 owing to insufficient interface wettability of PEO electrolyte within the polycrystalline secondary NMC811 particles. The findings in this work collectively formulate valuable guidance for improving the safety of polymer-electrolyte-based as well as other types of all-solid-state lithium-ion batteries.

25 ENERGY STORAGE↗

Hydrogen Quantitative Risk Assessment

DOE has identified consistent safety, codes, and standards as a critical need for the deployment of hydrogen technologies, with key barriers related to the availability and implementation of technical information in the development of regulations, codes, and standards. Advances in codes and standards have been enabled by risk-informed approaches to create and implement revisions to codes, such as National Fire Protection Association (NFPA) 2, NFPA 55, and International Organization for Standardization (ISO) Technical Specification (TS)-19880-1. This project provides the technical basis for these revisions, enabling the assessment of the safety of hydrogen fuel cell systems and infrastructure using QRA and physics-based models of hydrogen behavior. The risk and behavior tools that are developed in this project are motivated by, shared directly with, and used by the committees revising relevant codes and standards, thus forming the scientific basis to ensure that code requirements are consistent, logical, and defensible.

08 HYDROGEN↗