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We report large-format lithium-ion (Li-ion) batteries with high energy density for electric vehicles are prone to thermal runaway (or even explosion) under abusive conditions. In this study, overcharge induced explosion behaviors of large-format Li-ion pouch cells with Li[Ni 0.8 Co 0.1 Mn 0.1 ]O 2 cathode at different current rates (C-rates) (0.5C, 1C, 2C) were investigated. The explosion characteristics of the cells were elucidated by discussing the evolution of the cell voltage, the surface temperature and the shock wave pressure. Generally, the whole overcharge process could be divided into four stages according to the evolution of several key parameters and the overcharge behaviors; the overcharge C-rate has a great influence on cells’ thermal behaviors. The experimental results showed that the thermal runaway process of Li-ion cells caused by overcharging consisted of two kinds of explosions, physical explosion and chemical explosion. The existence of observable negative pressure zone in the pressure curves indicated that the Li-ion cells are not a self-supplying oxygen system during the explosion. Further, the explosion dynamics parameters were matched. An explosion TNT-equivalent conversion strategy that depended on the pressure of the shock wave was utilized to evaluate the released energy and its hazards. In addition, with respect to the overcharge of Li-ion pouch cells, a safety assessment method and a safety management method were proposed based on the explosion behaviors. From the perspective of battery safety, this study is of great significance for the safety design of Li-ion cells and can provide guidance for engineers to optimize the safety function of battery packs.
Abstract Inevitable safety issues have pushed battery engineers to become more conservative in battery system design; however, battery‐involved accidents still frequently are reported in headlines. Identifying, understanding, and predicting safety risks have become priorities to further accelerate technology and industry development. However, diverse loading scenarios, significantly varied stress‐induced short circuit mechanisms, and highly coupled mechanical–electrochemical safety behaviors have remained grand challenges. Herein, the safety risk is termed as the probability of the mechanical triggering of an internal short circuit, to reflect the safety related behaviors of lithium‐ion batteries. Based on a mechanical model and experimental results, a sufficient dataset is generated consisting of strain states and their corresponding safety risks, covering both cylindrical and pouch cells, various states of charges, and loading conditions. Machine‐learning tools combined with the established finite element mechanical model are applied to predict the safety risks of the cells. The results achieve a high level of accuracy on the test data (the relative error of the average short circuit prediction deviation is less than 6.2%.). This work underpins the safety risk concept and highlights the promise of physics combined with data‐driven modeling methodology to predict the safety behaviors of energy storage systems.
A Dynamic Flowgraph Methodology (DFM) based on an integrated approach to modeling and analyzing the behavior of software-driven embedded systems for assessing and verifying reliability and safety is discussed. DFM is based on an extension of the Logic Flowgraph Methodology to incorporate state transition models. System models which express the logic of the system in terms of causal relationships between physical variables and temporal characteristics of software modules are analyzed to determine how a certain state can be reached. This is done by developing timed fault trees which take the form of logical combinations of static trees relating the system parameters at different point in time. The resulting information concerning the hardware and software states can be used to eliminate unsafe execution paths and identify testing criteria for safety critical software functions.
Model-based development tools are increasingly being used for system-level development of safety-critical systems. Architectural and behavioral models provide important information that can be leveraged to improve the system safety analysis process. Model-based design artifacts produced in early stage development activities can be used to perform system safety analysis, reducing costs and providing accurate results throughout the system life-cycle. In this report we describe an extension to the Architecture Analysis and Design Language (AADL) that supports modeling of system behavior under failure conditions. This Safety Annex enables the independent modeling of component failures and allows safety engineers to weave various types of fault behavior into the nominal system model. The accompanying tool support uses model checking to propagate errors from their source to their effect on safety properties without the need to add separate propagation specifications. The tool also captures all minimal set of fault combinations that can cause violation of the safety properties, that can be compared to qualitative and quantitative objectives as part of the safety assessment process. We describe the Safety Annex, illustrate its use with a representative example, and discuss and demonstrate the tool support enabling an analyst to investigate the system behavior under failure conditions.
The source term used in reactor performance and safety analysis requires understanding the chemical speciation and transport behavior of fission and activation products in the primary heat transport system (PHTS) and containment. As a starting condition, the transport models will use the isotopic compositions determined through ORIGEN (Bell 1973) calculations and thermochemistry that describes the speciation of the fuel, the salt, activation products and fission products. However, as changes in phase will be under non-equilibrium conditions, the source terms will also need models for the transport behavior of key compounds in the PHTS under various scenarios: normal operation with and without an off-gas system, maintenance, off-normal events, and severe reactor accidents. This document highlights those mechanistic behaviors for which models are needed. Simulations of reactor behavior require these models to be developed for molten salt reactors (MSRs), especially if not part of the suite used in describing LWR behavior. The document concludes with recommendations how to develop these models based on what is already known about reactor safety and fission product behavior.
Data-driven decisions about safety management and design of safety-critical systems are limited by the available data, which influence, and are influenced by, how decision makers characterize problems and identify solutions. 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 safety-producing behaviors, 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 aviation safety represents a significant and largely unrecognized risk when making policy decisions about safety management and system design. Opportunities exist to leverage the vast amount of data that have already been collected, or could be easily obtained, to increase our understanding of human contributions to safety in commercial aviation. This presentation will focus on those opportunities as well as the challenges associated with collecting and analyzing data on operators’ safety-producing behaviors.
Traditional approaches for aircraft certification require the assumption of an initial flaw condition, either represented as barely visible impact damage (BVID) or through inclusion of a Teflon insert to serve as surrogate damage. Based on the initial composite damage state, the structure must be shown to demonstrate structural durability and damage tolerance (DaDT) according to the following criteria: a. Damage displays no detrimental growth under cyclic loading b. The structure is able to sustain design limit load (DLL) Currently, the only available manner for validating structural performance is through test. Since damage can occur over a wide variety of areas within a structure, this approach has proven to be increasingly expensive and time consuming for composite airframes and acreage structure within the design-test-certification building block. A further complicating factor is the requirement to accurately capture the most critical damage morphologies as a starting condition. To understand the severity of the damage, it is either required to experimentally determine the most critical areas at tremendous expense or rely on legacy data of similar structural testing, which limits design space expansion. A preferred solution is to use advanced analysis to provide improved understanding of load margins for critical locations based on a wide variety of potential starting damage conditions. The standard industry approach for DaDT certification adheres to the use of the traditional virtual crack closure technique (VCCT) method. VCCT is generally a preferred method because it conforms to the current certification principles of damage from a known flaw, and when used correctly, can be effective at predicting delamination propagation under static and cyclic loading. The VCCT method requires the inclusion of an initial flaw in the finite element (FE) model requiring a-priori knowledge of the flaw location. This in turn requires a plethora of analysis cases to be examined to cover a reasonable span of potential damage states. Additionally, the VCCT approach requires node-to-node connectivity rendering it incompatible with the best practices and approaches for using continuum damage mechanics (CDM) based progressive damage and failure analysis (PDFA) tools within a typical FE solver. Alternatives to VCCT have emerged in the form of cohesive elements which utilize the cohesive zone model (CZM). Unlike VCCT which models linear elastic fracture mechanics, cohesive elements couples continuum and fracture based responses through the use of bilinear traction separation laws. These laws are defined based on a penalty stiffness, a cohesive strength, and a strain energy release rate. The approach can be mesh regularized with native cohesive elements within many FE solvers such as Abaqus and LS-DYNA. In Phase I of the NASA Advanced Composites Consortium (ACC) post-buckled stiffened panel with BVID, Strength and Life [1], the performance of cohesive elements were benchmarked in comparison to VCCT and LEFM solutions and showed good agreement using Abaqus explicit [2]. To realize savings on current and future programs, it is still necessary to close technical gaps related to the use of cohesive elements with Abaqus Standard. Within a program environment, standard finite element analysis is the preferred analytical capability for quasi-static loading as it eliminates uncertainty due to oscillatory behavior commonly seen with explicit analysis. This oscillatory behavior creates difficulties in writing margins of safety based on the analysis. The use of negative tangent stiffness material models complicates convergence which typically requires the use of numerical controls such as viscous damping to overcome. To date, there has not been a comprehensive study on how to establish best practices for cohesive element convergence for predictive capability within the Abaqus implicit solver. In pursuit of these goals, under the NASA ACC program, several numerical benchmark problems were proposed including pure mode I (double cantilevered beam – DCB), pure mode II (end notch flexure – ENF), and symmetric/unsymmetric evolving mixed mode (single leg bend – SLB). This paper focuses on the use of cohesive elements to model the delamination through the use of CZM. Specifically, finite element models for the DCB, ENF, symmetric SLB, and unsymmetric SLB, are developed and various solution controls for convergence are studied to develop a best practice. Once the best practice has been developed, the predictive capability of the objective CZM model is used to analyze the hat pull-off strength of a standard hat stiffened configuration under various loading conditions.
Throughout the 2023 DIII-D negative triangularity (NT) campaign, unexpected magnetic fluctuations indicative of an edge localized instability were observed in the majority of strongly shaped (–0.55 ≤ δ ≤ –0.45) discharges. Moreover, these same fluctuations were found to be absent in weaker NT plasma shapes. Based on a database study, three separate mode behaviors are observed based primarily on the edge safety factor and normalized plasma beta β N . The main regime is the bursty state, in which short (~5 ms) magnetic bursts occur every 5–10 ms. Each burst drives a small reduction in the edge electron temperature (T e ) as measured by electron cyclotron emissions (ECE), which then rapidly recovers between the bursts. The quiescent regime appears to have governing mechanics similar to the bursty regime, but with multiple unique mode signatures observed in the magnetics. These additional modes greatly reduce the bursty nature of the plasma. Finally, a saturated state is observed in a number of discharges, particularly at early time slices. The saturated regime is often short-lived (maximum 500 ms), but can have a large impact on the dynamics of the plasma edge region, causing significant drops in electron temperature as observed in the ECE diagnostic. 2D ECE imaging (ECE-I) is utilized, showing large kink-like perturbations localized near the last closed flux surface that extend into the SOL indicative of an external kink/peeling behavior. Additionally, evidence of phase mixing and observed tearing-parity perturbations localized near the edge rational surfaces is observed in the quiescent regime plasmas. As a result, the various modes do not appear to have a large impact on global confinement but may play a role in regulating the transport of the NT edge and the observed edge gradients.
This Conference Proceedings is a collection of 6 abstracts and 3 papers presented April 19-20, 2001 in Denver, CO. The conference focus was "Best Practices and Benchmarking in Collegiate and Industry Programs". Topics covered include: satellite-based aviation navigation; weather safety training; human-behavior and aircraft maintenance issues; disaster preparedness; the collegiate aviation emergency response checklist; aviation safety research; and regulatory status of maintenance resource management.
We investigate and model the cook-off behavior of LX-17 to understand the response of explosive systems in abnormal thermal environments. Decomposition has been explored via conventional ODTX (One-Dimensional Time-to-eXplosion), PODTX (ODTX with pressure-measurement), TGA (Thermo-Gravimetric Analysis), and DSC (Differential Scanning Calorimetry) experiments under isothermal and ramped temperature profiles. The data were used to fit reaction rate parameters for proposed schemes in an ALE3D computational model. This model includes chemical reactions, thermo- and hydro-dynamics, and material properties, including thermal expansion, compressibility, and strength. These parameterizations were carried out utilizing a Python evolutionary optimization method on LLNL’s high-performance computing clusters. Additional experiments are being developed to further characterize and monitor decomposition intermediates to improve the model. Once experimentally validated, this model will be scalable to several applications involving LX-17. Furthermore, the optimization methodology developed herein should be applicable to other high explosive materials.
Our understanding of the fire safety risk in manned spacecraft has been limited by the small scale of the testing we have been able to conduct in low-gravity. Fire growth and spread cannot be expected to scale linearly with sample size so we cannot make accurate predictions of the behavior of realistic scale fires in spacecraft based on the limited low-g testing to date. As a result, spacecraft fire safety protocols are necessarily very conservative and costly. Future crewed missions are expected to be longer in duration than previous exploration missions outside of low-earth orbit and accordingly, more complex in terms of operations, logistics, and safety. This will increase the challenge of ensuring a fire-safe environment for the crew throughout the mission. Based on our fundamental uncertainty of the behavior of fires in low-gravity, the need for realistic scale testing at reduced gravity has been demonstrated. To address this concern, a spacecraft fire safety research project is underway to reduce the uncertainty and risk in the design of spacecraft fire safety systems by testing at nearly full scale in low-gravity. This project is supported by the NASA Advanced Exploration Systems Program Office in the Human Exploration and Operations Mission Directorate. The activity of this project is supported by an international topical team of fire experts from other space agencies to maximize the utility of the data and to ensure the widest possible scrutiny of the concept. The large-scale space flight experiment will be conducted on three missions; each in an Orbital Sciences Corporation Cygnus vehicle after it has deberthed from the ISS. Although the experiment will need to meet rigorous safety requirements to ensure the carrier vehicle does not sustain damage, the absence of a crew allows the fire products to be released into the cabin. The tests will be fully automated with the data downlinked at the conclusion of the test before the Cygnus vehicle reenters the atmosphere. The international topical team is collaborating with the NASA team in the definition of the experiment requirements and performing supporting analysis, experimentation and technology development.
Stress and anxiety-related problems are among the most common and costly behavioral health problems in society, and for those working in operational environments (i.e. astronauts, flight controllers, military) this can seriously impact crew performance, safety, and wellbeing. Technology-based interventions are effective for treating behavioral health problems, and can significantly improve the delivery of evidence-based health care. This study is evaluating the effectiveness, usefulness, and usability of a self-guided multimedia stress management and resilience training program in a randomized controlled trial (RCT) with a sample of flight controllers at Johnson Space Center. The intervention, SMART-OP (Stress Management and Resilience Training for Optimal Performance), is a six-session, cognitive behavioral-based computer program that uses self-guided, interactive activities to teach skills that can help individuals build resilience and manage stress. In a prior RCT with a sample of stressed but otherwise healthy individuals, SMART-OP reduced perceived stress and increased perceived control over stress in comparison to an Attention Control (AC) group. SMART-OP was rated as "highly useful" and "excellent" in usability and acceptability. Based on α-amylase data, individuals in SMART-OP recovered quicker and more completely from a social stress test as compared to the AC group [1]. In the current study, flight controllers are randomized either to receive SMART-OP training, or to a 6-week waitlist control period (WLC) before beginning SMART-OP. Eligible participants include JSC flight controllers and instructors without any medical or psychiatric disorder, but who are stressed based on self-report. Flight controllers provide a valid analog sample to astronauts in that they work in an operational setting, use similar terminology to astronauts, are mission-focused, and work under the same broader work culture. The study began in December 2014, and to date 79 flight controllers and instructors have expressed interest in the study, 49 of those were cleared for participation, we have screened 44 for eligibility, and 23 have met inclusion criteria. Recruitment is ongoing and the study will continue until December 2016. Outcome measures include perceived stress, perceived control over stress, resilience, mood, personality, emotion regulation, sleep, health behaviors, and psychophysiological data such as 24-hour heart rate, alpha amylase, and urinary and salivary cortisol. We are also collecting user feedback such as usability, working alliance, usefulness, and treatment credibility.
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)
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)
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.
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.
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.