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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 469 records · Page 26

Applied Time Domain Stability Margin Assessment for Nonlinear Time-Varying Systems

The baseline stability margins for NASA's Space Launch System (SLS) launch vehicle were generated via the classical approach of linearizing the system equations of motion and determining the gain and phase margins from the resulting frequency domain model. To improve the fidelity of the classical methods, the linear frequency domain approach can be extended by replacing static, memoryless nonlinearities with describing functions. This technique, however, does not address the time varying nature of the dynamics of a launch vehicle in flight. An alternative technique for the evaluation of the stability of the nonlinear launch vehicle dynamics along its trajectory is to incrementally adjust the gain and/or time delay in the time domain simulation until the system exhibits unstable behavior. This technique has the added benefit of providing a direct comparison between the time domain and frequency domain tools in support of simulation validation. This technique was implemented by using the Stability Aerospace Vehicle Analysis Tool (SAVANT) computer simulation to evaluate the stability of the SLS system with the Adaptive Augmenting Control (AAC) active and inactive along its ascent trajectory. The gains for which the vehicle maintains apparent time-domain stability defines the gain margins, and the time delay similarly defines the phase margin. This method of extracting the control stability margins from the time-domain simulation is relatively straightforward and the resultant margins can be compared to the linearized system results. The sections herein describe the techniques employed to extract the time-domain margins, compare the results between these nonlinear and the linear methods, and provide explanations for observed discrepancies. The SLS ascent trajectory was simulated with SAVANT and the classical linear stability margins were evaluated at one second intervals. The linear analysis was performed with the AAC algorithm disabled to attain baseline stability margins. At each time point, the system was linearized about the current operating point using Simulink's built-in solver. Each linearized system in time was evaluated for its rigid-body gain margin (high frequency gain margin), rigid-body phase margin, and aero gain margin (low frequency gain margin) for each control axis. Using the stability margins derived from the baseline linearization approach, the time domain derived stability margins were determined by executing time domain simulations in which axis-specific incremental gain and phase adjustments were made to the nominal system about the expected neutral stability point at specific flight times. The baseline stability margin time histories were used to shift the system gain to various values around the zero margin point such that a precise amount of expected gain margin was maintained throughout flight. When assessing the gain margins, the gain was applied starting at the time point under consideration, thereafter following the variation in the margin found in the linear analysis. When assessing the rigid-body phase margin, a constant time delay was applied to the system starting at the time point under consideration. If the baseline stability margins were correctly determined via the linear analysis, the time domain simulation results should contain unstable behavior at certain gain and phase values. Examples will be shown from repeated simulations with variable added gain and phase lag. Faithfulness of margins calculated from the linear analysis to the nonlinear system will be demonstrated.

Kiefer, J. M.↗

Deep Learning and Uncertainty Quantification for Climate Resilience

Modeling and monitoring of earth’s processes through physical models and satellite observations at high resolutions is crucial for ensuring society’s ability to adapt to climate change. Deep learning (DL) has been shown to be a valuable tool for generating high resolution data, emulating physical models, and detecting weather patterns which can then be used to inform stakeholders and decision makers. However, both the data and model parameters contain substantial uncertainties that may alter users’ decisions. In this work we present two DL applications on high-resolution climate and satellite datasets using Bayesian neural networks to generate well calibrated uncertainty estimates.

Vandal, Thomas↗

Results from NASA Agile Teams Study

In order to meet the demands of the current global economy, a study of agile teams at NASA was conducted by the NASA Engineering and Safety Center (NESC) to explore how the Agency can become more adaptable and flexible due to several influences, including the maturity and availability of digital tools and NASA’s increased reliance on commercial providers. NESC Technical Discipline Teams (TDTs) perform annual studies to understand the needs of their stakeholders, establish a state of the discipline, and inform strategic planning efforts. As part of the 2022 interview series, the Systems Engineering TDT utilized the dissertation work of Dr. Jackelynne Silva-Martinez that focused on NASA agile teams. The Systems Engineering TDT partnered with the Software and Human Factors TDTs on the formulation of interview questions and subsequent solicitation of customer inputs, which helped attract diverse agile teams across the Agency. 34 participants were interviewed, including civil servants and contractors, with open-ended questions related to their teams’ adoption and transition to agile. Participants were also questioned about their perceptions of the implementation of agile approaches across the Agency. Results showed a consistent framing of agile as incremental knowledge growth, a way of showing progress, and as the incorporation of frequent customer feedback. However, participants emphasized a lack of a common understanding of agile across the Agency, which sometimes caused managers and engineers to be reluctant to accept and support them. Results also showed the most successful agile teams had formal training with over five years of agile experience, used retrospectives, and tailored their agile processes for their specific situation and needs. This paper provides details of the interview responses gathered in the study and suggests actions for NASA to become more agile.

NASA↗

Automated Generation of Graph-based Cyber Threat Intel

With the advancement of AI technology and tools, specifically in the cybersecurity domain, both cyber defenders and threat actors are continuously adapting the use of these capabilities to expedite their operations. With this phenomenon, threat intelligence that is up to date, refreshable, and has relevant context to a specific threat becomes more and more important as it enables cybersecurity professionals to gain insight into relevant data and relationships to guide their operations. This project enables users to frequently aggregate threat intelligence from various sources, such as vendor vulnerability advisories affecting critical infrastructure, malware reports, and adversary writeups into a centralized, standardized database. The project utilizes the Structured Threat Intelligence eXpression (STIX) for a standardized, shareable threat intelligence data format and Neo4j as a graph database solution to store STIX nodes and relationships. Initial results of the project include datasets of over 8,000 nodes and 20,000 relationships extracted from over 500 data sources that have been released within the past month.

Threat Intelligence↗

Validation of Image-Based Neural Network Controllersthrough Adaptive Stress Testing

Neural networks have become state-of-the-art for computer vision problems because of their ability to efficiently model complex functions from large amounts of data. While neural networks can be shown to perform well empirically fora variety of tasks, their performance is difficult to guarantee.Neural network verification tools have been developed that can certify robustness with respect to a given input image; however,for neural network systems used in closed-loop controllers,robustness with respect to individual images does not address multi-step properties of the neural network controller and itsenvironment. Furthermore, neural network systems interacting in the physical world and using natural images are operating in a black-box environment, making formal verification in-tractable. This work combines the adaptive stress testing (AST)framework with neural network verification tools to search for the most likely sequence of image disturbances that cause the neural network controlled system to reach a failure. Anautonomous aircraft taxi application is presented, and results show that the AST method finds failures with more likely image disturbances than baseline methods. Further analysis of AST results revealed an explainable cause of the failure, giving insight into the problematic scenarios that should be addressed.

Adaptive Stress Testing, Marabou, Deep Neural Netw↗

Molecular aspects of stress-gene regulation during spaceflight

Spaceflight-associated stress has been the topic of investigation since the first terrestrial organisms were exposed to this unique environment. Organisms that evolved under the selection pressures of earth-normal environments can perceive spaceflight as a stress, either directly because gravity influences an intrinsic biological process, or indirectly because of secondary effects imparted by spaceflight upon environmental conditions. Different organisms and even different organs within an organism adapt to a spaceflight environment with a diversity of tactics. Plants are keenly sensitive to gravity for directed development, and are also sensitive to other stresses associated with closed-system spaceflight environments. Within the past decade, the tools of molecular biology have begun to provide a sophisticated evaluation of spaceflight-associated stress and the genetic responses that accompany metabolic adaptation to spaceflight.

manned↗

Biologically Inspired Technology Using Electroactive Polymers (EAP)

Evolution allowed nature to introduce highly effective biological mechanisms that are incredible inspiration for innovation. Humans have always made efforts to imitate nature's inventions and we are increasingly making advances that it becomes significantly easier to imitate, copy, and adapt biological methods, processes and systems. This brought us to the ability to create technology that is far beyond the simple mimicking of nature. Having better tools to understand and to implement nature's principles we are now equipped like never before to be inspired by nature and to employ our tools in far superior ways. Effectively, by bio-inspiration we can have a better view and value of nature capability while studying its models to learn what can be extracted, copied or adapted. Using electroactive polymers (EAP) as artificial muscles is adding an important element to the development of biologically inspired technologies.

robotics↗

Working at the Speed of Innovation: Impedance Mismatch in Rapid and Innovation Projects

In this paper we report on the results of an ethnographic study of a rapid design innovation (RDI) experiment in NASA Aeronautics. This work is based on the study of the Aeronautics Autonomy Testbed Capability (AATC) team in the Convergent Aeronautics Solutions (CAS) project. This paper focuses on and summarizes one of the key over-arching findings from the study: there is a significant mismatch in the organizational culture in the rest of the organization compared with that required for RDI. And, if this organizational cultural mismatch is not addressed, the likelihood of any organization being able to advance a new and different type of work (such as RDI) will be jeopardized. We delineate several aspects of the two different cultures identified in order to enable leaders and practitioners to better understand what contributes to the cultural dissonance and the implications of the differences in the cultures. As well, we identify ways in which those differences can be addressed. Research from organization and other social sciences are incorporated to highlight the differences. The implications of the research suggest that the significant cultural differences trigger a strong and resistive response from the dominant culture that may negate leadership’s strategy to build the new capacity for RDI. While the research results noted the pervasive nature of innovation throughout the workplace, the type of innovation envisioned in RDI is a rare type of innovation that requires significantly new methods, work processes, tools, and skills such that approaches used in the dominate culture cannot be adopted by expediting the existing approaches. Examples include: innovation teaming and leadership; the need for adaptive leadership that changes the relationship of a research leader to the other researchers; and, an interdisciplinary teaming approach which shapes team relationships and activities. Each of these aspects requires new teaming, tools, and skills in order to succeed. Thus, when introducing RDI activities where there is a different dominant culture, teams need to be: well trained; protected; recognized and rewarded. And, team leaders must also be trained in the unique types of teaming and innovation tools used in RDI. Both RDI teaming and team leadership must be sanctioned, supported, and rewarded by leadership. Because of the cultural mismatch, in some organizations looking to add RDI to their existing and established organizations, sep to avoid or mitigate the negative impact of the culture mismatch.

Crain, Cathleen↗

Employing Earned Value Management in Government Research and Design - Lessons Learned from the Trenches

To effectively manage a project, the project manager must have a plan, understand the current conditions, and be able to take action to correct the course when challenges arise. Research and design projects face technical, schedule, and budget challenges that make it difficult to utilize project management tools developed for projects based on previously demonstrated technologies. Projects developing new technologies by their inherent nature are trying something new and thus have little to no data to support estimates for schedule and cost, let alone the technical outcome. Projects with a vision for the outcome but little confidence in the exact tasks to accomplish in order to achieve the vision incur cost and schedule penalties when conceptual solutions require unexpected iterations or even a reinvention of the plan. This presentation will share the project management methodology and tools developed through trial and error for a NASA research and design project combining industry, academia, and NASA inhouse work in which Earned Value Management principles were employed but adapted for the reality of the government financial system and the reality of challenging technology development. The priorities of the presented methodology are flexibility, accountability, and simplicity to give the manager tools to help deliver to the customer while not using up valuable time and resources on extensive planning and analysis. This presentation will share the methodology, tools, and work through failed and successful examples from the three years of process evolution.

Simon, Tom↗

An affordable platform for automated synthesis and electrochemical characterization

In recent years, self-driving laboratories (SDLs) have emerged as a powerful tool to expedite various areas of chemical research. For optimal functionality, these laboratories must be adaptable, readily modifying configurations to meet researchers' specific needs. Despite these advances, much of chemistry still depends on proprietary equipment from specialized vendors, which can be restrictive and difficult to customize for diverse lab setups. Moreover, ensuring reproducibility requires full disclosure of equipment details. In this work, we introduce an automated system featuring a cost-effective, self-designed potentiostat and a straightforward synthesis platform. We provide complete transparency by disclosing the electronic schematics of the potentiostat and the software used in the system. Our aim is to reduce the barriers to entry for SDLs and promote the principles of open science.

Pablo-García, Sergio↗

The computation of mesh configurations for three-dimensional flow analysis

A geometry modeling method was developed to define three-dimensional mesh configurations, which were expressed by the set of surface intersections with a coordinate mesh. These configurations define bodies for transonic potential-flow computation in simple physical coordinates. Various configurations were prepared for 3-D potential flow analysis, including many bare inlet models in cylindrical coordinates. Trimmed surface models were used to prepare nacelle installation configurations. A variety of ducts and mixers were represented. Analytically defined mesh/surface intersections were compared with similar data obtained from the corresponding surface model. Parameters for an analytic surface definition from mesh-surface intersections obtained from a model of the surface were produced. In both studies the modeling accuracy was shown to be compatible with the flow analysis requirements. This technique fulfills the requirements of the associated three-dimensional potential-flow analysis. It preserves the flow analysis method's superior flexibility for adapting to unusual geometries. The geometry modeling technique is supported by a sufficient set of tools for effective use by general users, and sufficient accuracy was demonstrated.

Gibson, S. G.↗

Development and Flight Testing of an Adaptive Vehicle Health-Monitoring Architecture

On going development and testing of an adaptable vehicle health-monitoring architecture is presented. The architecture is being developed for a fleet of vehicles. It has three operational levels: one or more remote data acquisition units located throughout the vehicle; a command and control unit located within the vehicle, and, a terminal collection unit to collect analysis results from all vehicles. Each level is capable of performing autonomous analysis with a trained expert system. The expert system is parameterized, which makes it adaptable to be trained to both a user's subject reasoning and existing quantitative analytic tools. Communication between all levels is done with wireless radio frequency interfaces. The remote data acquisition unit has an eight channel programmable digital interface that allows the user discretion for choosing type of sensors; number of sensors, sensor sampling rate and sampling duration for each sensor. The architecture provides framework for a tributary analysis. All measurements at the lowest operational level are reduced to provide analysis results necessary to gauge changes from established baselines. These are then collected at the next level to identify any global trends or common features from the prior level. This process is repeated until the results are reduced at the highest operational level. In the framework, only analysis results are forwarded to the next level to reduce telemetry congestion. The system's remote data acquisition hardware and non-analysis software have been flight tested on the NASA Langley B757's main landing gear. The flight tests were performed to validate the following: the wireless radio frequency communication capabilities of the system, the hardware design, command and control; software operation and, data acquisition, storage and retrieval.

Woodard, Stanley E.↗

MAPGEN Planner: Mixed-Initiative Activity Planning for the Mars Exploration Rover Mission

This document describes the Mixed-initiative Activity Plan Generation system MAPGEN. The system is be- ing developed as one of the tools to be used during surface operations of NASA's Mars Exploration Rover mission (MER). However, the core technology is general and can be adapted to different missions and applications. The motivation for the system is to better support users that need to rapidly build activity plans that have to satisfy complex rules and fit within resource limits. The system therefore combines an existing tool for activity plan editing and resource modeling, with an advanced constraint-based reasoning and planning framework. The demonstration will show the key capabilities of the automated reasoning and planning component of the system, with emphasis on how these capabilities will be used during surface operations of the MER mission.

Ai-Chang, Mitch↗

An Approach to V&V of Embedded Adaptive Systems

Rigorous Verification and Validation (V&V) techniques are essential for high assurance systems. Lately, the performance of some of these systems is enhanced by embedded adaptive components in order to cope with environmental changes. Although the ability of adapting is appealing, it actually poses a problem in terms of V&V. Since uncertainties induced by environmental changes have a significant impact on system behavior, the applicability of conventional V&V techniques is limited. In safety-critical applications such as flight control system, the mechanisms of change must be observed, diagnosed, accommodated and well understood prior to deployment. In this paper, we propose a non-conventional V&V approach suitable for online adaptive systems. We apply our approach to an intelligent flight control system that employs a particular type of Neural Networks (NN) as the adaptive learning paradigm. Presented methodology consists of a novelty detection technique and online stability monitoring tools. The novelty detection technique is based on Support Vector Data Description that detects novel (abnormal) data patterns. The Online Stability Monitoring tools based on Lyapunov's Stability Theory detect unstable learning behavior in neural networks. Cases studies based on a high fidelity simulator of NASA's Intelligent Flight Control System demonstrate a successful application of the presented V&V methodology. ,

Liu, Yan↗

Ubiquitous Wireless Smart Sensing and Control

Need new technologies to reliably and safely have humans interact within sensored environments (integrated user interfaces, physical and cognitive augmentation, training, and human-systems integration tools). Areas of focus include: radio frequency identification (RFID), motion tracking, wireless communication, wearable computing, adaptive training and decision support systems, and tele-operations. The challenge is developing effective, low cost/mass/volume/power integrated monitoring systems to assess and control system, environmental, and operator health; and accurately determining and controlling the physical, chemical, and biological environments of the areas and associated environmental control systems.

Wagner, Raymond↗

Ubiquitous Wireless Smart Sensing and Control. Pumps and Pipes JSC: Uniquely Houston

Need new technologies to reliably and safely have humans interact within sensored environments (integrated user interfaces, physical and cognitive augmentation, training, and human-systems integration tools).Areas of focus include: radio frequency identification (RFID), motion tracking, wireless communication, wearable computing, adaptive training and decision support systems, and tele-operations. The challenge is developing effective, low cost/mass/volume/power integrated monitoring systems to assess and control system, environmental, and operator health; and accurately determining and controlling the physical, chemical, and biological environments of the areas and associated environmental control systems.

Wagner, Raymond↗

Development of nanolaminate thin shell mirrors

This paper will discuss the development of thin-shell, nano-laminate mirror substrates that are capable of being electro-actively figured. This technology has the potential to substantially reduce the cost of space based optics by allowing replication of ultra-lightweight primary mirrors from a master precision tool.

nanolaminate↗

Adapt: A Weather Radar Data Analysis and Nowcasting Platform for Informed Adaptive Scanning

SF-26-021 Adapt is a data processing platform for real-time data analysis, short term prediction of targets convective cells and tracking for archived data. It provides tools for downloading, processing, segmenting, projecting, analyzing, and visualizing storm cell data from weather radar. The pipeline includes cell detection, motion estimation using optical flow, cell property extraction, and persistence to NetCDF and SQLite/Parquet for guiding adaptive scanning.

Raut, Bhupendra Ashokrao [Argonne National Laborat↗