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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 1,459 records · Page 81

Life prediction technologies for aeronautical propulsion systems

Fatigue and fracture problems continue to occur in aeronautical gas turbine engines. Components whose useful life is limited by these failure modes include turbine hot-section blades, vanes, and disks. Safety considerations dictate that catastrophic failures be avoided, while economic considerations dictate that catastrophic failures be avoided, while economic considerations dictate that noncatastrophic failures occur as infrequently as possible. Therefore, the decision in design is making the tradeoff between engine performance and durability. LeRC has contributed to the aeropropulsion industry in the area of life prediction technology for over 30 years, developing creep and fatigue life prediction methodologies for hot-section materials. At the present time, emphasis is being placed on the development of methods capable of handling both thermal and mechanical fatigue under severe environments. Recent accomplishments include the development of more accurate creep-fatigue life prediction methods such as the total strain version of LeRC's strain-range partitioning (SRP) and the HOST-developed cyclic damage accumulation (CDA) model. Other examples include the development of a more accurate cumulative fatigue damage rule - the double damage curve approach (DDCA), which provides greatly improved accuracy in comparison with usual cumulative fatigue design rules. Other accomplishments in the area of high-temperature fatigue crack growth may also be mentioned. Finally, we are looking to the future and are beginning to do research on the advanced methods which will be required for development of advanced materials and propulsion systems over the next 10-20 years.

Mcgaw, Michael A.↗

Advanced Guidance and Control for Hypersonics and Space Access

Advanced guidance and control (AG&C) technologies are critical for meeting safety, reliability, and cost requirements for the next generation of reusable launch vehicle (RLV), whether it is fully rocket-powered or has air- breathing components. This becomes clear upon examining the number of expendable launch vehicle failures in the recent past where AG&C technologies could have saved a RLV with the same failure mode, the additional vehicle problems where t h i s technology applies, and the costs and time associated with mission design with or without all these failure issues. The state-of-the-art in guidance and control technology, as well as in computing technology, is the point where we can look to the possibility of being able to safely return a RLV in any situation where it can physically be recovered. This paper outlines reasons for AWC, current technology efforts, and the additional work needed for making this goal a reality. There are a number of approaches to AG&C that have the potential for achieving the desired goals. For some of these methods, we compare the results of tests designed to demonstrate the achievement of the goals. Tests up to now have been focused on rocket-powered vehicles; application to hypersonic air-breathers is planned. We list the test cases used to demonstrate that the desired results are achieved, briefly describe an automated test scoring method, and display results of the tests. Some of the technology components have reached the maturity level where they are ready for application to a new vehicle concept, while others are not far along in development.

Hanson, John M.↗

Failure Assessments for MQXF Magnet Support Structure with a Graded Approach

The High-Luminosity Large Hadron Collider (HLLHC) upgrade requires new quadrupoles, MQXF, to replace the present LHC inner triplets. The MQXFA magnet is the first prototype that has a 150 mm aperture and uses Nb 3 Sn superconducting technology in a 4.2 m magnetic length structure. The support structure design of the MQXFA magnet is based on the bladder-and-key technology, where a relatively low pre-stress at room temperature is increased to the final preload targets during the cool-down by the differential thermal contraction of the various components. The magnet support structure components experience different load levels from pre-load to cool-down and excitation. Consequently, a few parts experience high stresses that may cause localized plastic deformations or internal fracture development. The concept presented in this paper for the failure assessment of support structures integrates nonlinear finite element analysis with detailed sub-models and fracture mechanics into an advanced engineering tool. The nonlinear FE solutions enable estimations of the structural response to the given loads, and the advanced fracture analysis with failure assessment diagram (FAD) assesses the structure safety index of results obtained from the FE model. The study describes how the MQXFA shell end segments are being optimized based on the failure analyses.

43 PARTICLE ACCELERATORS↗

Hazard Detection Methods for Lunar Landing

The methods and experiences from the Apollo Program are fundamental building blocks for the development of lunar landing strategies for the Constellation Program. Each of the six lunar landing Apollo missions landed under near ideal lighting conditions. The astronauts visually performed terrain relative navigation while looking out of windows, and were greatly aided by external communication and well lit scenes. As the LM approached the landing site, the astronauts performed visual hazard detection and avoidance, also under near-ideal lighting conditions. The astronauts were looking out of the windows trying to the best of their ability to avoid rocks, slopes, and craters and find a safe landing location. NASA has expressed a desire for global lunar access for both crewed and robotic sortie lunar exploration missions (Cook, 2007) (Dale, 2006). Early NASA architecture studies have identified the lunar poles as desirable locations for early lunar missions. These polar missions have less than ideal lighting conditions and will significantly affect the way a crewed vehicle plans to land at such locales. Consequently, a variety of hazard identification methods should be considered for use by the crew to ensure a high degree of safety. This paper discusses such identification methods applicable to the poorly lit polar lunar environment, better ensuring global access for the soon to be designed Lunar Lander Vehicle (LLV).

Brady, Tye↗

Managing Large Scale Project Analysis Teams through a Web Accessible Database

Large scale space programs analyze thousands of requirements while mitigating safety, performance, schedule, and cost risks. These efforts involve a variety of roles with interdependent use cases and goals. For example, study managers and facilitators identify ground-rules and assumptions for a collection of studies required for a program or project milestone. Task leaders derive product requirements from the ground rules and assumptions and describe activities to produce needed analytical products. Disciplined specialists produce the specified products and load results into a file management system. Organizational and project managers provide the personnel and funds to conduct the tasks. Each role has responsibilities to establish information linkages and provide status reports to management. Projects conduct design and analysis cycles to refine designs to meet the requirements and implement risk mitigation plans. At the program level, integrated design and analysis cycles studies are conducted to eliminate every 'to-be-determined' and develop plans to mitigate every risk. At the agency level, strategic studies analyze different approaches to exploration architectures and campaigns. This paper describes a web-accessible database developed by NASA to coordinate and manage tasks at three organizational levels. Other topics in this paper cover integration technologies and techniques for process modeling and enterprise architectures.

O'Neil, Daniel A.↗

Using Game Theoretic Models to Predict Pilot Behavior in NextGen Merging and Landing Scenario

In this paper, we present an implementation of the Semi Network-Form Game framework to predict pilot behavior in a merging and landing scenario. In this scenario, two aircraft are approaching to a freeze horizon with approximately equal distance when they become aware of each other via an ADS-B communication link that will be available in NextGen airspace. Both pilots want to gain advantage over the other by entering the freeze horizon earlier and obtain the first place in landing. They re-adjust their speed accordingly. However, they cannot simply increase their speed to the maximum allowable values since they are concerned with safety, separation distance, effort, possibility of being vectored-off from landing and possibility of violating speed constraints. We present how to model these concerns and the rest of the system using semi network-from game framework. Using this framework, based on certain assumptions on pilot utility functions and on system configuration, we provide estimates of pilot behavior and overall system evolution in time. We also discuss the possible employment of this modeling tool for airspace design optimization. To support this discussion, we provide a case where we investigate the effect of increasing the merging point speed limit on the commanded speed distribution and on the percentage of vectored aircraft.

Yildiz, Yildiray↗

Knowledge Discovery for Early Failure Assessment of Complex Engineered Systems Using Natural Language Processing

Emerging complex engineered systems may have unexpected safety issues due to novel operational environments, increasing autonomy, human-machine interaction, and other factors. To prevent failures in operation or testing that necessitate costly redesign, it is desirable to predict likely failure modes early in the design process. Information about past engineering failures in natural language format presents one possible solution by enabling the retrieval of information that can inform new designs. However, identifying documents containing usable information and extracting the required information can be prohibitively time-consuming when implemented at scale. In this research, an automated natural language processing (NLP) framework is proposed to discover relevant knowledge from documents containing failure-related design information. The framework is applied to NASA’s Lessons Learned Information System (LLIS),which is publicly available. Documents containing usable information are filtered using two different NLP-based models. Next, from the identified usable documents, a failure taxonomy is extracted using a partitioned hierarchical topic modeling approach. Partitions of the document describe different sections of the failure taxonomy – i.e., failure, cause of failure, and recommendations – as indicated by the structure of the original document. The extracted failure taxonomy can be leveraged in early design failure assessment methods. Moreover, the framework can be used to identify documents containing usable failure-related design information from other databases and extract relevant information from these documents.

Documentation and Information Science↗

Knowledge Discovery for Early Failure Assessment of Complex Engineered Systems Using Natural Language Processing

Emerging complex engineered systems may have unexpected safety issues due to novel operational environments, increasing autonomy, human-machine interaction, and other factors. To prevent failures in operation or testing that necessitate costly redesign, it is desirable to predict likely failure modes early in the design process. Information about past engineering failures in natural language format presents one possible solution by enabling the retrieval of information that can inform new designs. However, identifying documents containing usable information and extracting the required information can be prohibitively time-consuming when implemented at scale. In this research, an automated natural language processing (NLP) framework is proposed to discover relevant knowledge from documents containing failure-related design information. The framework is applied to NASA’s Lessons Learned Information System (LLIS),which is publicly available. Documents containing usable information are filtered using two different NLP-based models. Next, from the identified usable documents, a failure taxonomy is extracted using a partitioned hierarchical topic modeling approach. Partitions of the document describe different sections of the failure taxonomy – i.e., failure, cause of failure, and recommendations – as indicated by the structure of the original document. The extracted failure taxonomy can be leveraged in early design failure assessment methods. Moreover, the framework can be used to identify documents containing usable failure-related design information from other databases and extract relevant information from these documents.

Documentation and Information Science↗

Scoping, Tailoring, and Abstraction Refinement in the Hazard Assessment Process

Hazard assessment is an engineering activity that produces insight into which states of thing being engineered might be hazardous. In aviation contexts, it is often performed for certification credit at both the aircraft and system levels during the early design phase of the system’s lifecycle. However, novel aircraft paradigms such as urban air mobility (UAM) operations might either violate assumptions on which traditional aviation hazard assessment is based or simply possess attributes that would make other approaches more effective. In this paper, we define the key concepts underpinning hazard assessment and identify the limitations and assumptions inherent in hazard analysis. We analyze popular techniques to show how they embody these key concepts. We identify ways in which hazard assessment may be scoped and tailored to an application. And, using worked examples, we discuss how, where, and why such tailoring might be needed, especially in novel contexts.

Aviation Safety↗

Urban Air Mobility Traffic Analysis Tool for Airspace Involving Vertiport Hub Operations to Examine Simulated Conflicts

Presented herein are details of the development of an Urban Air Mobility Traffic Analysis Tool (UAM TAT), designed to analyze the traffic of Vertical Take-off and Landing (VTOL) air-craft in urban agglomerations to enable the Urban Air Mobility(UAM) operations. The tool aims to address challenges of UAM operations in a simulated airspace by testing different scenarios and methods for air traffic management. It emphasizes the need for effective risk management practices and methodologies to ensure the safety of operations, given the increasing use of highly automated aircraft (i.e., Advanced Air Mobility (AAM))in urban environments. The tool is modular and allows for the simulation of various families of VTOLs and different air traffic rules, making it suitable for defining and estimating airspace and vertiports capacity, determining VTOL requirements, and testing and comparing air traffic management methods. The results of five different simulations are presented that show the capabilities and functionalities of the tool. The simulations present the impact of vertiport hub operations and various ATM approach on the VTOLs’ conflicts.

Urban Air Mobility↗

Transforming the NAS: The Next Generation Air Traffic Control System

The next-generation air traffic control system must be designed to safely and efficiently accommodate the large growth of traffic expected in the near future. It should be sufficiently scalable to contend with the factor of 2 or more increase in demand expected by the year 2020. Analysis has shown that the current method of controlling air traffic cannot be scaled up to provide such levels of capacity. Therefore, to achieve a large increase in capacity while also giving pilots increased freedom to optimize their flight trajectories requires a fundamental change in the way air traffic is controlled. The key to achieving a factor of 2 or more increase in airspace capacity is to automate separation monitoring and control and to use an air-ground data link to send trajectories and clearances directly between ground-based and airborne systems. In addition to increasing capacity and offering greater flexibility in the selection of trajectories, this approach also has the potential to increase safety by reducing controller and pilot errors that occur in routine monitoring and voice communication tasks.

Erzberger, Heinz↗

A materials-informatics based study of solid electrolytes and protective coatings for Li batteries

All-solid-state batteries with Li metal anode can address the safety issues surrounding traditional Li-ion batteries as well as the demand for higher energy densities. However, the development of solid electrolytes and protective coatings simultaneously possessing high ionic conductivity and wide electrochemical stability has proven to be a challenge. Here, we present a data-driven approach to explore the Li compound space for promising solid electrolytes and coatings. This is accomplished through the generation of a large database of battery-related materials properties of Li compounds by computing Li+ migration barriers using bond-valence-based pair potentials, and stability windows using density functional theory energies. Using this database, we implement machine learning models that can accurately predict migration barriers and electrochemical stability windows for any new Li compound. Through feature engineering, we ensure that our models are both accurate and interpretable. We perform feature importance analysis on our models to highlight materials properties that can be tuned for future design of coatings/electrolytes. Our database and informatics approach provide a valuable tool for the rapid discovery of new solid-state battery chemistries.

Solid state batteries↗

Results of Partially-Reflected Critical Experiments in Square-Pitched Arrays of Water-Moderated 6.9 Percent Enriched Fuel Rods

The Seven Percent Critical Experiment (7uPCX) was designed to provide benchmark criticality and reactor physics data for water-moderated pin-fueled nuclear reactor cores. The enrichment of the fuel was chosen to explore the enrichment range above the current 5% ceiling for US commercial pressurized water reactors. The experiment was part of the US Department of Energy (DOE) Nuclear Energy Research Initiative (NERI) Project 01-124 titled “Reactor Physics and Criticality Benchmark Evaluations for Advanced Nuclear Fuel”. The NERI project was a collaboration between AREVA Federal Services, LLC; the University of Florida; Oak Ridge National Laboratory; and Sandia National Laboratories (SNL). The experiments at Sandia are currently supported by the DOE National Nuclear Security Administration Nuclear Criticality Safety Program. Two sets of benchmark experiments have been completed and documented as LEU-COMP-THERM-080 and LEU-COMP-THERM-078. Those experiments were done with the number of fuel rods in the fully-reflected array as the approach parameter. The experiments reported here are similar to those in LEU-COMP-THERM-080 except that the arrays are partially-reflected – the arrays were larger than would be possible with full reflection and the approach-to-critical experiments were done with the depth of the water in the critical assembly as the approach parameter. These experiments are reported as LEU-COMP-THERM-096.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Fast, Controllable, and Modular Solid-State Circuit Breaker Design for Battery Management Systems

Electric power grid is experiencing a growing number of distributed and inertia-free generation resources. To facilitate the growing generation and load demands, and ensure stable operation, energy storage systems, especially behind-themeter-storage (BTMS), have emerged as a potential candidate. BTMS plays a vital role in the grid storage sector and supports high power charging for EVs. However, the potential of thermal runaway and associated safety concerns in the batteries can hamper their widespread adoption. In this work, we provide a solution for a fast and controllable discharge of a cell that was identified as a stressful/faulty, in the battery pack, and fast circuit breaking leveraging the Solid-State Circuit Breaker (SSCB) technology which provides active control over the cell connection as opposed to conventional passive solutions. Testing on the simulation platform successfully validated the concept, demonstrating its efficacy. Controlled discharge testing with 20Ah LiFePO4 Lithium Iron Phosphate (LFP) cells from 1C-10C current rate on the hardware prototype corroborated simulation results, demonstrating design feasibility and providing essential data for its performance and thermal characteristics, while also revealing limitations that inform areas for further optimization.

33 ADVANCED PROPULSION SYSTEMS↗

Scoping, Tailoring, and Abstraction Refinement in Hazard Assessment Processes

Hazard assessment is an engineering activity that produces insight into which states of thing being engineered might be hazardous. In aviation contexts, it is often performed for certification credit at both the aircraft and system levels during the early design phase of the system’s lifecycle. However, novel aircraft paradigms such as urban air mobility (UAM)operations might either violate assumptions on which traditional aviation hazard assessment is based or simply possess attributes that would make other approaches more effective. In this paper, we define the key concepts under pinning hazard assessment and identify the limitations and assumptions inherent in hazard analysis. We analyze popular techniques to show how they embody these key concepts. We identify ways in which hazard assessment may be scoped and tailored to an application. And, using worked examples, we discuss how, where, and why such tailoring might be needed, especially in novel contexts.

aviation safety↗

Fast-charging lithium-ion batteries: Synergy of carbon nanotubes and laser ablation

Advancing lithium-ion battery (LiB) technology to achieve 10–15-min extreme fast charging (XFC) while maintaining high energy density and longevity poses a significant challenge. Addressing Li-plating is crucial, as it depletes useable Li, causing deterioration and safety issues. Here, this study explores a holistic approach incorporating Single-Wall Carbon Nanotubes (SWCNTs) and Laser Ablation (LA) to mitigate Li-plating while maintaining high charge acceptance under 10–15-min XFC. SWCNTs enhance the electrical conductivity and mechanical integrity of the positive electrode (PE), reducing overall cell overpotential at high charging rates. Concurrently, LA is applied to negative electrodes (NE) to reduce tortuosity of ion-diffusion pathways and increase surface wettability, improving Li-ion transport. Combining SWCNTs in the PE and LA on the NE, our experimental findings demonstrate a significant reduction in Li-plating and maintained high charge acceptance of ~84.33 % after 800 5C (12 min) charge cycles for cells having PE with ~3.3 mAh cm –2 and NE with 3.9 mAh cm –2 loadings. This study highlights the potential of combining SWCNTs and LA to address Li-plating in LiBs and opens new avenues for designing battery systems capable of achieving 10–15-min XFC.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Quantification of electrochemical-mechanical coupling in lithium-ion batteries

Lithium-ion battery safety and durability by nature are dependent on electrochemical and mechanical coupling. Interdisciplinary efforts are required to understand and quantify coupling behaviors. Here we design and conduct mechanically constrained charge and discharge characterizations with efforts supported by multiphysics modeling to unravel the coupling mechanisms of solid-liquid electrode-electrolyte and solid-solid active materials in lithium-ion batteries. We demonstrate that a lithium-ion battery cell under mechanical constraint exhibits a higher voltage during charging and a shorter charging time because of increased electrolyte resistance and decreased diffusivity caused by decreased electrode porosity. The reaction force response of the cell is a combined result of the cell structural response mechanically and lithium-ion intercalation/de-intercalation-induced volume variation electrochemically. Under mechanical constraint, cell capacity is significantly reduced in fast-charge scenarios; however, it can be recovered by a constant-voltage charge protocol. The results highlight the promise of multiphysics approaches to unravel the electrochemical-mechanical coupling mechanisms to direct battery system design and management.

25 ENERGY STORAGE↗

Nuclear safety Enhanced: A Deep dive into current and future RAVEN applications

As the horizon of nuclear energy expands with the advent of small modular reactors, IV generation reactors, and fusion reactors, there is a growing perspective that the licensing process could benefit from a more comprehensive approach. Moving beyond traditional deterministic and PRA analysis might pave the way for a novel safety analysis paradigm propelled by the increasing computational power at our disposal. This paper explores different methodologies that can improve the outcomes of nuclear safety analysis. These range from uncertainty quantification techniques, aimed at enhancing the precision of safety margins, to deploying dynamic event trees by driving system code simulations, capturing the potential evolutions of severe accidents. These methodologies introduce innovative dimensions to safety analysis, considering the consequences of postulated events and the dynamics of accident sequences. However, they also bring forth challenges, especially in managing the complexity and sheer volume of potential scenarios. The paper touches upon some strategies to counter these challenges, emphasizing the importance of adaptability and continuous evolution in the face of emerging nuclear safety concerns. Additionally, the paper sheds light on the need for advanced tools to apply these methodologies. Among these tools is RAVEN, an open-source software designed for parametric and probabilistic analyses. Its core components, including distribution, sampler, and reduced order model, enable various applications, from risk assessment and mitigation to dynamic learning and plant control logic simulations.

97 - MATHEMATICS AND COMPUTING↗