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At least 1,567 records · Page 87

The Zero Boil-Off Tank Experiment Ground Testing and Verification of Fluid and Thermal Performance

The Zero Boil-Off Technology (ZBOT) Experiment involves performing a small scale International Space Station (ISS) experiment to study tank pressurization and pressure control in microgravity. The ZBOT experiment consists of a vacuum jacketed test tank filled with an inert fluorocarbon simulant liquid. Heaters and thermo-electric coolers are used in conjunction with an axial jet mixer flow loop to study a range of thermal conditions within the tank. The objective is to provide a high quality database of low gravity fluid motions and thermal transients which will be used to validate Computational Fluid Dynamic (CFD) modeling. This CFD can then be used in turn to predict behavior in larger systems with cryogens. This paper will discuss the work that has been done to demonstrate that the ZBOT experiment is capable of performing the functions required to produce a meaningful and accurate results, prior to its launch to the International Space Station. Main systems discussed are expected to include the thermal control system, the optical imaging system, and the tank filling system.This work is sponsored by NASAs Human Exploration Mission Directorates Physical Sciences Research program.

Fluid management↗

Using Degradation Modeling to Identify Fragile Operational Conditions in Human- and Component-driven Resilience Assessment

Studying failure events shows that many high-impact events result from the complex interactions between precipitating failure events and degraded operational conditions. Often, when a system is put in operations, unforeseen practical realities (e.g., maintenance and/or workforce availability) lead the system to be operated in configurations outside its envisioned nominal range. However, design-time failure models often assume that the failure events are initiated in an idealized, nominal state of system operation, resulting in an incomplete assessment of future risk. To solve this, this paper develops a framework to consider degraded operational performance in scenario-based resilience models which uses a corresponding model of performance degradation to determine the values of deteriorated model parameters in the resilience model. This framework is demonstrated on a remotely-piloted rover to determine the (individual and combined) effect of drive-train wear and operator fatigue on the resilience of the rover to drive-train faults. This demonstration showed the substantial impact that degradation has on resilience, highlighting the need to account for degradation in resilience models–specifically, unconsidered degradation can lead to overestimates of resilience (and thus underestimates of safety margin) and because resilience can degrade prior to visible unreliability, which can lead to an operational environment with a high propensity for high-impact unforeseen failure events.

resilience↗

Using Degradation Modeling to Identify Fragile Operational Conditions in Human- and Component-driven Resilience Assessment

Studying failure events shows that many high-impact events result from the complex interactions between precipitating failure events and degraded operational conditions. Often, when a system is put in operations, unforeseen practical realities (e.g., maintenance and/or workforce availability) lead the system to be operated in configurations outside its envisioned nominal range. However, design-time failure models often assume that the failure events are initiated in an idealized, nominal state of system operation, resulting in an incomplete assessment of future risk. To solve this, this paper develops a framework to consider degraded operational performance in scenario-based resilience models which uses a corresponding model of performance degradation to determine the values of deteriorated model parameters in the resilience model. This framework is demonstrated on a remotely-piloted rover to determine the (individual and combined) effect of drive-train wear and operator fatigue on the resilience of the rover to drive-train faults. This demonstration showed the substantial impact that degradation has on resilience, highlighting the need to account for degradation in resilience models--specifically, unconsidered degradation can lead to overestimates of resilience (and thus underestimates of safety margin) and because resilience can degrade prior to visible unreliability, which can lead to an operational environment with a high propensity for high-impact unforeseen failure events.

Daniel Hulse↗

Safety Impacts of Automated Vehicles in Mixed Traffic

Previous research have shown that Automated Vehicles (AV) have the potential to improve transportation thanks to the possibility to perform some control functions without driver input (1). A question that remains is what are the safety impacts of the interaction between human-driven vehicles with different levels of automation at a particular intersection?The main objective of this paper is to build the behavioral framework to simulate different levels of automation and to study the safety impact of these levels under different penetration scenarios. Real-life connected vehicle data were incorporated to revise the Wiedemann car-following model and simulate the behavior of human-driven vehicles, level 3 and level 5 AVs.

Ramin, Arvin↗

An Innovative Approach to Modeling VIPER Rover Software Life Cycle Cost

NASA’s “Volatiles Investigating Polar Exploration Rover” (VIPER) will be the first robotic mission to prospect for water ice near the south pole of the Moon in late 2023 on a 100-Earth-day mission. The information that the VIPER rover provides will help improve understanding of the composition, distribution, and accessibility of Lunar polar volatiles and will help determine how the Moon’s resources can support future human space exploration. VIPER, however, represents a radical departure from the way that NASA has traditionally developed planetary robotic missions. A key consequence of these differences is that estimating the cost of VIPER’s rover software is challenging and complex.For example, VIPER is being developed using management procedures typically applied to NASA research and technology projects, rather than space flight programs. In addition, key portions of the rover’s software are being designed as ground software to run on mission control computers (rather than on-board the rover as flight software as with prior planetary missions) taking advantage of continuous, interactive data communications between the Moon and Earth and higher performance computing available on the ground. Moreover, the rover’s software is being engineered using Agile software development practices and incorporates a significant amount of open-source, rather than following traditional (spiral, waterfall, etc.) development methods and in-house code. In this paper, we present an innovative process to estimate the life cycle cost of VIPER’s rover software. We first describe how we modeled the architecture and code counts for three software elements: Rover Flight Software (RFSW), Rover Ground Software (RGSW), and Rover Simulation Software (RSIM). We then discuss key challenges and unique aspects of our approach, such as the lack of Lunar rover analogies, the need to integrate and test large open source software, and the strategies developed to account for use of non-space flight management practices and the impact of the COVID-19 pandemic. We conclude with a summary of our results, including cumulative distribution, nearest neighbors and cluster analysis, as well as heuristics used to confirm the reasonableness of the cost estimate.

Utz, Hans↗

Drosophila models to study causative genes for human rare intractable neurological diseases

Highlights: • Drosophila models targeting some ALS-causing genes are described. • Drosophila models targeting some CMT-causing genes are described. • Drosophila models targeting some Sotos syndrome-causing genes are described. • Genes and pathways that commonly interact with ALS- and/or CMT-causing genes are described. Drosophila is emerging as a convenient model for investigating human diseases. Functional homologues of almost 75% of human disease-related genes are found in Drosophila. Amyotrophic lateral sclerosis (ALS) is a severe neurodegenerative disease that causes defects in motoneurons. Charcot-Marie-Tooth disease (CMT) is one of the most commonly found inherited neuropathies affecting both motor and sensory neurons. No effective therapy has been established for either of these diseases. In this review, after overviewing ALS, Drosophila models targeting several ALS-causing genes, including TDP-43, FUS and Ubiquilin2, are described with their genetic interactants. Then, after overviewing CMT, examples of Drosophila models targeting several CMT-causing genes, including mitochondria-related genes and FIG 4, are also described with their genetic interactants. In addition, we introduce Sotos syndrome caused by mutations in the epigenetic regulator gene NSD1. Lastly, several genes and pathways that commonly interact with ALS- and/or CMT-causing genes are described. In the case of ALS and CMT that have many causative genes, it may be not practical to perform gene therapy for each of the many disease-causing genes. The possible uses of the common genes and pathways as novel diagnosis markers and effective therapeutic targets are discussed.

60 APPLIED LIFE SCIENCES↗

Automatic identification and quantification of dense microcracks in high-performance fiber-reinforced cementitious composites through deep learning-based computer vision

Highlights: • A method is presented to detect, locate, quantify, and visualize dense microcracks in HPFRCC. • Quantification of dense microcracks is realized using deep learning method for the first time. • The presented method uses deep learning models that are trained using a realistic dataset size. • The presented method has a high computation efficiency for identifying and quantifying cracks. • The presented method provides crack width with errors up to 50 μm and a R{sup 2} value of 0.984. High-performance fiber-reinforced cementitious composites (HPFRCCs) feature high mechanical strengths, crack resistance, and durability. Under excessive loading, HPFRCCs demonstrate dense microcracks that are difficult to identify using existing methods. This study presents a computer vision method for identification, quantification, and visualization of microcracks in HPFRCCs based on deep learning. The presented method integrates multiple deep learning models and computer vision techniques in a hierarchical architecture. The crack pattern (e.g., number, width, and spacing of cracks) are automatically determined from pictures without human intervention. This study shows that the presented method achieves an accuracy of 0.992 for crack detection and an accuracy finer than 50 μm (R{sup 2} > 0.984) for quantification of crack width when deep learning models are trained using only 200 pictures of HPFRCCs and 200 pictures of conventional concrete with incorporation of data augmentation. The presented method is expected to be also applicable to other materials featuring complex cracks.

36 MATERIALS SCIENCE↗

Small Molecule IL-36γ Antagonist as a Novel Therapeutic Approach for Plaque Psoriasis

IL-36 cytokines are pro-inflammatory members of the IL-1 family that are upregulated in inflammatory disorders. Specifically, IL-36γ is highly expressed in active psoriatic lesions and can drive pro-inflammatory processes in 3D human skin equivalents supporting a role for this target in skin inflammation. Small molecule antagonists of interleukins have been historically challenging to generate. Nevertheless, we performed a small molecule high-throughput screen to identify IL-36 antagonists using a novel TR-FRET binding assay. Several compounds, including 2-oxypyrimidine containing structural analogs of the marketed endothelin receptor A antagonist Ambrisentan, were identified as hits from the screen. A-552 was identified as a the most potent antagonist of human IL-36γ, but not the closely related family member IL-36α, was capable of attenuating IL-36γ induced responses in mouse and human disease models. Additionally, x-ray crystallography studies identified key amino acid residues in the binding pocket present in human IL-36γ that are absent in human IL-36α. A-552 represents a first-in-class small molecule antagonist of IL-36 signaling that could be used as a chemical tool to further investigate the role of this pathway in inflammatory skin diseases such as psoriasis.

60 APPLIED LIFE SCIENCES↗

Fault diagnosis

The objective of the research in this area of fault management is to develop and implement a decision aiding concept for diagnosing faults, especially faults which are difficult for pilots to identify, and to develop methods for presenting the diagnosis information to the flight crew in a timely and comprehensible manner. The requirements for the diagnosis concept were identified by interviewing pilots, analyzing actual incident and accident cases, and examining psychology literature on how humans perform diagnosis. The diagnosis decision aiding concept developed based on those requirements takes abnormal sensor readings as input, as identified by a fault monitor. Based on these abnormal sensor readings, the diagnosis concept identifies the cause or source of the fault and all components affected by the fault. This concept was implemented for diagnosis of aircraft propulsion and hydraulic subsystems in a computer program called Draphys (Diagnostic Reasoning About Physical Systems). Draphys is unique in two important ways. First, it uses models of both functional and physical relationships in the subsystems. Using both models enables the diagnostic reasoning to identify the fault propagation as the faulted system continues to operate, and to diagnose physical damage. Draphys also reasons about behavior of the faulted system over time, to eliminate possibilities as more information becomes available, and to update the system status as more components are affected by the fault. The crew interface research is examining display issues associated with presenting diagnosis information to the flight crew. One study examined issues for presenting system status information. One lesson learned from that study was that pilots found fault situations to be more complex if they involved multiple subsystems. Another was pilots could identify the faulted systems more quickly if the system status was presented in pictorial or text format. Another study is currently under way to examine pilot mental models of the aircraft subsystems and their use in diagnosis tasks. Future research plans include piloted simulation evaluation of the diagnosis decision aiding concepts and crew interface issues. Information is given in viewgraph form.

Abbott, Kathy↗

Human factors requirements for telerobotic command and control: The European Space Agency experimental programme

Space Telerobotics research, performed under contract to the European Space Agency (ESA), concerning the execution of human factors experiments, and ultimately leading to the development of a telerobotics test bed, has been carried out since 1985 by a British Consortium consisting of British Aerospace, the United Kingdom Atomic Energy Authority and, more recently, the UK National Advanced Robotics Research Centre. The principal aim of the first study of the series was to derive preliminary requirements for a teleoperation servicing system, with reference to two mission model scenarios. The first scenario introduced the problem of communications time delays, and their likely effect on the ground-based operator in control of a manipulator system on board an unmanned servicing vehicle in Low Earth Orbit. In the second scenario, the operator was located on the NASA Orbiter aft flight deck, supervising the control of a prototype manipulator in the 'servicing' of an experimental payload in the cargo bay area. Human factors analyses centered on defining the requirements for the teleoperator workstation, such as identifying basic ergonomic requirements for workstation and panel layouts, defining teleoperation strategies, developing alphanumeric and graphic screen formats for the supervision or direct control of the manipulator, and the potential applications of expert system technology. The second study for ESA involved an experimental appraisal of some of the important issues highlighted in the first study, for which relevant human factors data did not exist. Of central importance during the second study was the issue of communications time delays and their effect on the manual control of a teleoperated manipulator from a ground-based command and control station.

Stone, Robert J.↗

Mars Solar Power

NASA missions to Mars, both robotic and human, rely on solar arrays for the primary power system. Mars presents a number of challenges for solar power system operation, including a dusty atmosphere which modifies the spectrum and intensity of the incident solar illumination as a function of time of day, degradation of the array performance by dust deposition, and low temperature operation. The environmental challenges to Mars solar array operation will be discussed and test results of solar cell technology operating under Mars conditions will be presented, along with modeling of solar cell performance under Mars conditions. The design implications for advanced solar arrays for future Mars missions is discussed, and an example case, a Martian polar rover, are analyzed.

Landis, Geoffrey A.↗

Physics-Based Modeling of Meteor Entry and Breakup

A new research effort at NASA Ames Research Center has been initiated in Planetary Defense, which integrates the disciplines of planetary science, atmospheric entry physics, and physics-based risk assessment. This paper describes work within the new program and is focused on meteor entry and breakup.Over the last six decades significant effort was expended in the US and in Europe to understand meteor entry including ablation, fragmentation and airburst (if any) for various types of meteors ranging from stony to iron spectral types. These efforts have produced primarily empirical mathematical models based on observations. Weaknesses of these models, apart from their empiricism, are reliance on idealized shapes (spheres, cylinders, etc.) and simplified models for thermal response of meteoritic materials to aerodynamic and radiative heating. Furthermore, the fragmentation and energy release of meteors (airburst) is poorly understood.On the other hand, flight of human-made atmospheric entry capsules is well understood. The capsules and their requisite heatshields are designed and margined to survive entry. However, the highest speed Earth entry for capsules is 13 kms (Stardust). Furthermore, Earth entry capsules have never exceeded diameters of 5 m, nor have their peak aerothermal environments exceeded 0.3 atm and 1 kW/sq cm. The aims of the current work are: (i) to define the aerothermal environments for objects with entry velocities from 13 to 20 kms; (ii) to explore various hypotheses of fragmentation and airburst of stony meteors in the near term; (iii) to explore the possibility of performing relevant ground-based tests to verify candidate hypotheses; and (iv) to quantify the energy released in airbursts. The results of the new simulations will be used to anchor said risk assessment analyses. With these aims in mind, state-of-the-art entry capsule design tools are being extended for meteor entries. We describe: (i) applications of current simulation tools to spherical geometries of diameters ranging from 1 to 100 m for an entry velocity of 20 kms and stagnation pressures ranging from 1 to 100 atm; (ii) the influence of shape and departure of heating environment predictions from those for a simple spherical geometry; (iii) assessment of thermal response models for silica subject to intense radiation; and (iv) results for porosity-driven gross fragmentation of meteors, idealized as a collection of smaller objects. Lessons learned from these simulations will be used to help understand the Chelyabinsk meteor entry up to its first point of fragmentation.

Near-Earth Asteroids↗

Physics-Based Modeling of Meteor Entry and Breakup

A new research effort at NASA Ames Research Center has been initiated in Planetary Defense, which integrates the disciplines of planetary science, atmospheric entry physics, and physics-based risk assessment. This paper describes work within the new program and is focused on meteor entry and breakup. Over the last six decades significant effort was expended in the US and in Europe to understand meteor entry including ablation, fragmentation and airburst (if any) for various types of meteors ranging from stony to iron spectral types. These efforts have produced primarily empirical mathematical models based on observations. Weaknesses of these models, apart from their empiricism, are reliance on idealized shapes (spheres, cylinders, etc.) and simplified models for thermal response of meteoritic materials to aerodynamic and radiative heating. Furthermore, the fragmentation and energy release of meteors (airburst) is poorly understood. On the other hand, flight of human-made atmospheric entry capsules is well understood. The capsules and their requisite heat shields are designed and margined to survive entry. However, the highest speed Earth entry for capsules is 13 kms (Stardust). Furthermore, Earth entry capsules have never exceeded diameters of 5 m, nor have their peak aerothermal environments exceeded 0.3 atm and 1 kWcm2. The aims of the current work are: (i) to define the aerothermal environments for objects with entry velocities from 13 to 20 kms; (ii) to explore various hypotheses of fragmentation and airburst of stony meteors in the near term; (iii) to explore the possibility of performing relevant ground-based tests to verify candidate hypotheses; and (iv) to quantify the energy released in airbursts. The results of the new simulations will be used to anchor said risk assessment analyses.With these aims in mind, state-of-the-art entry capsule design tools are being extended for meteor entries. We describe: (i) applications of current simulation tools to spherical geometries of diameters ranging from 1 to 100 m for an entry velocity of 20 kms and stagnation pressures ranging from 1 to 100 atm; (ii) the influence of shape and departure of heating environment predictions from those for a simple spherical geometry; (iii) assessment of thermal response models for silica subject to intense radiation; and (iv) results for porosity-driven gross fragmentation of meteors, idealized as a collection of smaller objects. Lessons learned from these simulations will be used to help understand the Chelyabinsk meteor entry up to its first point of fragmentation.

Atmospheric Entry↗

Developing Probabilistic Safety Performance Margins for Unknown and Underappreciated Risks

Probabilistic safety requirements currently formulated or proposed for space systems, nuclear reactor systems, nuclear weapon systems, and other types of systems that have a low-probability potential for high-consequence accidents depend on showing that the probability of such accidents is below a specified safety threshold or goal. Verification of compliance depends heavily upon synthetic modeling techniques such as PRA. To determine whether or not a system meets its probabilistic requirements, it is necessary to consider whether there are significant risks that are not fully considered in the PRA either because they are not known at the time or because their importance is not fully understood. The ultimate objective is to establish a reasonable margin to account for the difference between known risks and actual risks in attempting to validate compliance with a probabilistic safety threshold or goal. In this paper, we examine data accumulated over the past 60 years from the space program, from nuclear reactor experience, from aircraft systems, and from human reliability experience to formulate guidelines for estimating probabilistic margins to account for risks that are initially unknown or underappreciated. The formulation includes a review of the safety literature to identify the principal causes of such risks.

Safety Performance Margin↗

Foreword Special issue on the Kilopower Project, Kilowatt Reactor Using Stirling TechnologY (KRUSTY) Test

This special issue of Nuclear Technology contains full-length, peer-reviewed papers describing the design work leading up to and the results of the Kilowatt Reactor Using Stirling TechnologY (KRUSTY) test. KRUSTY was the centerpiece of the National Aeronautics and Space Administration (NASA) Kilopower Project to design, build, and test a space nuclear reactor. This test was the first such test since the end of the Space Nuclear Auxiliary Power (SNAP) project at the end of the 1960s. In this issue, the introduction paper presents the goals of the Kilopower Project and the potential missions this reactor concept could serve in NASA. Kilopower was intended to serve both human exploration needs on planetary surfaces as well as science needs for deep-space exploration. The design work for the experiment by Poston and the power conversion development by Gibson present the pre-work required to perform the eventual KRUSTY test. A paper on regulatory analysis follows, to show the path used to gain approval of the proposed experiment. Then, the early zero-power critical experiments are presented by Sanchez and Grove. These experiments were essential data used to enhance model predictions prior to the high-temperature test. Next, Poston presents the three experiments (warm criticals) that increase the temperature in an incremental fashion prior to the final experiment. These experiments were used to achieve final regulatory approval of the final high-temperature experiment. The last paper by Poston presents the results of the steady-state and transient testing of the reactor at full power and at the design temperature. These results show that the reactor design and as-built experiment met all of the requirements that NASA had developed for the system. Any experiment of this magnitude was accomplished only because of the hard work and dedication of a large number of people at multiple institutions, including the NASA Glenn Research Center, NASA Marshall Space Flight Center, Y-12 National Security Site, Los Alamos National Laboratory, and the Nevada National Security Site prime contractor (formerly National Security Technologies and now the Mission Support and Test Services). The project was jointly funded by the Space Technology Mission Directorate at NASA and the Criticality Safety Program at the National Nuclear Security Administration (NNSA). A special thanks to Jerry McKamy and Angela Chambers at the NNSA and Lee Mason and Don Palac at NASA for their support and guidance. For the authors and multitude of staff that performed this work, the passion for space nuclear reactors was the key to making this experiment a reality.

99 GENERAL AND MISCELLANEOUS↗

Assessment of Electric Grid Transmission System Simulator for Human Factors Research

Over the past decades, various technologies have been developed for electric grid operations to support clean energy, meet rising electricity demands, and address infrastructure concerns. However, the human factors aspect is often overlooked during rapid integration. Questions persist about how these technologies impact human performance. Simulators play a critical role in supporting investigation of human factors design concepts and conducting comprehensive usability testing to evaluate human performance and assess human reliability. This paper aims to address human factors research simulator requirements and conduct a comparative study of six different simulators. A detailed evaluation reveals that the evaluated simulators lack the ability to customize user interfaces. Additionally, their user interface designs do not fulfill the basic human factors design principles, potentially leading to increased response variability and reduced statistical power when conducting controlled experimental research. In the future, it is essential to develop scripting tools to integrate customizable user interfaces and simulation models, ensuring meeting research requirements.

Li, Ruixuan↗

FEDERATED LEARNING ON STOCHASTIC NEURAL NETWORKS

Federated learning is a machine learning paradigm that leverages edge computing on client devices to optimize models while maintaining user privacy by ensuring that local data remain on the device. However, since all data are collected by clients, federated learning is susceptible to latent noise in local datasets. Factors such as limited measurement capabilities or human errors may introduce inaccuracies in client data. To address this challenge, we propose the use of a stochastic neural network as the local model within the federated learning framework. Stochastic neural networks not only facilitate the estimation of the true underlying states of the data but also enable the quantification of latent noise. We refer to our federated learning approach, which incorporates stochastic neural networks as local models, as federated stochastic neural networks. In this work we will present numerical experiments demonstrating the performance and effectiveness of our method, particularly in handling nonindependent and identically distributed data.

97 MATHEMATICS AND COMPUTING↗

A review of the analytical simulation of aircraft crash dynamics

A large number of full scale tests of general aviation aircraft, helicopters, and one unique air-to-ground controlled impact of a transport aircraft were performed. Additionally, research was also conducted on seat dynamic performance, load-limiting seats, load limiting subfloor designs, and emergency-locator-transmitters (ELTs). Computer programs were developed to provide designers with methods for predicting accelerations, velocities, and displacements of collapsing structure and for estimating the human response to crash loads. The results of full scale aircraft and component tests were used to verify and guide the development of analytical simulation tools and to demonstrate impact load attenuating concepts. Analytical simulation of metal and composite aircraft crash dynamics are addressed. Finite element models are examined to determine their degree of corroboration by experimental data and to reveal deficiencies requiring further development.

Fasanella, Edwin L.↗