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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 307 records · Page 17

The role of AI in detecting and mitigating human errors in safety-critical industries: A review

For safety-critical industries, human error (HE) presents continual risks to system productivity, reliability and safety. Artificial intelligence (AI) and machine learning (ML) methods have emerged as promising approaches to understand, categorize and mitigate the risk of HE in safety-critical industries. Furthermore, this review offers an examination of the current landscape regarding the utilization of AI/ML with regards to HE in safety-critical industries, categorizing literature into descriptive modeling, predictive modeling, prescriptive modeling, and generative modeling techniques. Additionally, the review aims to provide insights regarding themes in literature, challenges, and future research directions. Findings of the review suggest that AI/ML methods can prove useful in addressing the HE problem across safety-critical industries.

42 ENGINEERING↗

Sensor fusion IV: Control paradigms and data structures; Proceedings of the Meeting, Boston, MA, Nov. 12-15, 1991

Various papers on control paradigms and data structures in sensor fusion are presented. The general topics addressed include: decision models and computational methods, sensor modeling and data representation, active sensing strategies, geometric planning and visualization, task-driven sensing, motion analysis, models motivated biology and psychology, decentralized detection and distributed decision, data fusion architectures, robust estimation of shapes and features, application and implementation. Some of the individual subjects considered are: the Firefly experiment on neural networks for distributed sensor data fusion, manifold traversing as a model for learning control of autonomous robots, choice of coordinate systems for multiple sensor fusion, continuous motion using task-directed stereo vision, interactive and cooperative sensing and control for advanced teleoperation, knowledge-based imaging for terrain analysis, physical and digital simulations for IVA robotics.

Schenker, Paul S.↗

Software Process Assessment (SPA)

NASA's environment mirrors the changes taking place in the nation at large, i.e. workers are being asked to do more work with fewer resources. For software developers at NASA's Goddard Space Flight Center (GSFC), the effects of this change are that we must continue to produce quality code that is maintainable and reusable, but we must learn to produce it more efficiently and less expensively. To accomplish this goal, the Data Systems Technology Division (DSTD) at GSFC is trying a variety of both proven and state-of-the-art techniques for software development (e.g., object-oriented design, prototyping, designing for reuse, etc.). In order to evaluate the effectiveness of these techniques, the Software Process Assessment (SPA) program was initiated. SPA was begun under the assumption that the effects of different software development processes, techniques, and tools, on the resulting product must be evaluated in an objective manner in order to assess any benefits that may have accrued. SPA involves the collection and analysis of software product and process data. These data include metrics such as effort, code changes, size, complexity, and code readability. This paper describes the SPA data collection and analysis methodology and presents examples of benefits realized thus far by DSTD's software developers and managers.

Rosenberg, Linda H.↗

Distance Learning With NASA Lewis Research Center's Learning Technologies Project

The NASA Lewis Research Center's Learning Technologies Project (LTP) has responded to requests from local school district technology coordinators to provide content for videoconferencing workshops. Over the past year we have offered three teacher professional development workshops that showcase NASA Lewis-developed educational products and NASA educational Internet sites. In order to determine the direction of our involvement with distance learning, the LTP staff conducted a survey of 500 U.S. schools. We received responses from 72 schools that either currently use distance learning or will be using distance learning in 98-99 school year. The results of the survey are summarized in the article. In addition, the article provides information on distance learners, distance learning technologies, and the NASA Lewis LTP videoconferencing workshops. The LTP staff will continue to offer teacher development workshops through videoconferencing during the 98-99 school year. We hope to add workshops on new educational products as they are developed at NASA Lewis.

Petersen, Ruth↗

Overview of Aqua MODIS 10-year On-orbit Calibration and Performance

Since launch in May 2002, Aqua MODIS has successfully operated for nearly 10 years, continuously collecting global datasets for scientific studies of key parameters of the earth's land, ocean, and atmospheric properties and their changes over time. The quality of these geophysical parameters relies on the input quality of sensor calibrated radiances. MODIS observations are made in 36 spectral bands with wavelengths ranging from visible (VIS) to longwave infrared (LWIR). Its reflective solar bands (RSB) are calibrated using data collected from its on-board solar diffuser and regularly scheduled lunar views. The thermal emissive bands (TEB) are calibrated using an on-board blackbody (BB). The changes in the sensor's spectral and spatial characteristics are monitored by an on-board spectroradiometric calibration assembly (SRCA). This paper presents an overview of Aqua MODIS 10-year on-orbit operation and calibration activities, from launch to present, and summarizes its on-orbit radiometric, spectral, and spatial calibration and characterization performance. In addition, it will illustrate and discuss on-orbit changes in sensor characteristics and corrections applied to continuously maintain the sensor level 1B (L1B) data quality, as well as lessons learned that could benefit future calibration efforts.

Xiong, X.↗

Spaceport Command and Control System - Support Software Development

The Information Architecture Support (IAS) Team, the component of the Spaceport Command and Control System (SCCS) that is in charge of all the pre-runtime data, was in need of some report features to be added to their internal web application, Information Architecture (IA). Development of these reports is crucial for the speed and productivity of the development team, as they are needed to quickly and efficiently make specific and complicated data requests against the massive IA database. These reports were being put on the back burner, as other development of IA was prioritized over them, but the need for them resulted in internships being created to fill this need. The creation of these reports required learning Ruby on Rails development, along with related web technologies, and they will continue to serve IAS and other support software teams and their IA data needs.

Information Architecture↗

In-Space Networking on NASA's SCAN Testbed

The NASA Space Communications and Navigation (SCaN) Testbed, an external payload onboard the International Space Station, is equipped with three software defined radios and a flight computer for supporting in-space communication research. New technologies being studied using the SCaN Testbed include advanced networking, coding, and modulation protocols designed to support the transition of NASAs mission systems from primarily point to point data links and preplanned routes towards adaptive, autonomous internetworked operations needed to meet future mission objectives. Networking protocols implemented on the SCaN Testbed include the Advanced Orbiting Systems (AOS) link-layer protocol, Consultative Committee for Space Data Systems (CCSDS) Encapsulation Packets, Internet Protocol (IP), Space Link Extension (SLE), CCSDS File Delivery Protocol (CFDP), and Delay-Tolerant Networking (DTN) protocols including the Bundle Protocol (BP) and Licklider Transmission Protocol (LTP). The SCaN Testbed end-to-end system provides three S-band data links and one Ka-band data link to exchange space and ground data through NASAs Tracking Data Relay Satellite System or a direct-to-ground link to ground stations. The multiple data links and nodes provide several upgradable elements on both the space and ground systems. This paper will provide a general description of the testbeds system design and capabilities, discuss in detail the design and lessons learned in the implementation of the network protocols, and describe future plans for continuing research to meet the communication needs for evolving global space systems.

space networks↗

Automated Software for Manned Spacecraft - Bridging the Gap from Sci Fi to Reality

With a voice command or a few taps on the console, the spacecraft pivots on a dime at high velocity and gently docks to an orbiting space platform. This is the image most people have of the complex software computations and integrated hardware performance necessary for a spacecraft to successfully perform an automated launch, rendezvous, and docking. Today’s reality is that while computer operations are advancing rapidly, science fiction over-simplifies and over-sells current capabilities. This paper discusses the integration of spacecraft computer automation into the operation of one of the United States’ new Commercial Crew vehicles - the Boeing CST-100 Starliner. Lessons learned by the Boeing Mission Operations team, a private-public partnership with NASA, from conceptual design through real-time operation of the first test flight will be discussed. Focus will center on how operations has learned to use the automated software to their advantage while also knowing how to adjust the automation in response to spacecraft or mission anomalies. One goal of advanced spacecraft automation is the ability to reduce both the crew workload and the ground control footprint while at the same time increasing spacecraft and mission flexibility. Historically, crewed spacecraft required a large number of operators on the ground to use a plethora of tools to compute nominal and contingency mission trajectories. Moving those sophisticated software tools to being onboard the vehicle can reduce the need for such complex ground support. Given that today’s spacecraft software is not yet as capable or as flexible in all circumstances as the computers depicted in movies, there is usually a trade-off between software automation cost and the flexibility of that software resulting in a trade-off between what is performed on the spacecraft and what is left to onboard crew or ground control. For missions that go beyond the Moon, software that autonomously controls nearly every aspect of a crewed mission will become a necessity given the long time delays between the spacecraft and Earth’s ground control teams. The lessons learned by Boeing and its Mission Operations team, through the design and implementation of Starliner’s hardware and software automation, will be able to inform future public and private spacecraft design. As the technologies and capabilities evolve, incorporating lessons learned in successful low Earth orbit commercial crew vehicle missions, spacecraft designs will continue to improve and be able to better enable safe execution of human missions to the Moon and beyond.

Robert C Dempsey↗

Automated Software for Manned Spacecraft - Bridging the Gap from Sci Fi to Reality

With a voice command or a few taps on the console, the spacecraft pivots on a dime at high velocity and gently docks to an orbiting space platform. This is the image most people have of the complex software computations and integrated hardware performance necessary for a spacecraft to successfully perform an automated launch, rendezvous, and docking. Today’s reality is that while computer operations are advancing rapidly, science fiction over-simplifies and over-sells current capabilities. This paper discusses the integration of spacecraft computer automation into the operation of one of the United States’ new Commercial Crew vehicles - the Boeing CST-100 Starliner. Lessons learned by the Boeing Mission Operations team, a private-public partnership with NASA, from conceptual design through real-time operation of the first test flight will be discussed. Focus will center on how operations has learned to use the automated software to their advantage while also knowing how to adjust the automation in response to spacecraft or mission anomalies. One goal of advanced spacecraft automation is the ability to reduce both the crew workload and the ground control footprint while at the same time increasing spacecraft and mission flexibility. Historically, crewed spacecraft required a large number of operators on the ground to use a plethora of tools to compute nominal and contingency mission trajectories. Moving those sophisticated software tools to being onboard the vehicle can reduce the need for such complex ground support. Given that today’s spacecraft software is not yet as capable or as flexible in all circumstances as the computers depicted in movies, there is usually a trade-off between software automation cost and the flexibility of that software resulting in a trade-off between what is performed on the spacecraft and what is left to onboard crew or ground control. For missions that go beyond the Moon, software that autonomously controls nearly every aspect of a crewed mission will become a necessity given the long time delays between the spacecraft and Earth’s ground control teams. The lessons learned by Boeing and its Mission Operations team, through the design and implementation of Starliner’s hardware and software automation, will be able to inform future public and private spacecraft design. As the technologies and capabilities evolve, incorporating lessons learned in successful low Earth orbit commercial crew vehicle missions, spacecraft designs will continue to improve and be able to better enable safe execution of human missions to the Moon and beyond.

Robert C. Dempsey↗

Automated Software for Crewed Spacecraft - Bridging the Gap from Sci Fi to Reality

With a voice command or a few taps on the console, the spacecraft pivots on a dime at high velocity and gently docks to an orbiting space platform. This is the image most people have of the complex software computations and integrated hardware performance necessary for a spacecraft to successfully perform an automated launch, rendezvous, and docking. Today’s reality is that while computer operations are advancing rapidly, science fiction over-simplifies and over-sells current capabilities. This paper discusses the integration of spacecraft computer automation into the operation of one of the United States’ new Commercial Crew vehicles - the Boeing CST-100 Starliner. Lessons learned by the Boeing Mission Operations team, a private-public partnership with NASA, from conceptual design through real-time operation of the first test flight will be discussed. Focus will center on how operations has learned to use the automated software to their advantage while also knowing how to adjust the automation in response to spacecraft or mission anomalies. One goal of advanced spacecraft automation is the ability to reduce both the crew workload and the ground control footprint while at the same time increasing spacecraft and mission flexibility. Historically, crewed spacecraft required a large number of operators on the ground to use a plethora of tools to compute nominal and contingency mission trajectories. Moving those sophisticated software tools to being onboard the vehicle can reduce the need for such complex ground support. Given that today’s spacecraft software is not yet as capable or as flexible in all circumstances as the computers depicted in movies, there is usually a trade-off between software automation cost and the flexibility of that software resulting in a trade-off between what is performed on the spacecraft and what is left to onboard crew or ground control. For missions that go beyond the Moon, software that autonomously controls nearly every aspect of a crewed mission will become a necessity given the long time delays between the spacecraft and Earth’s ground control teams. The lessons learned by Boeing and its Mission Operations team, through the design and implementation of Starliner’s hardware and software automation, will be able to inform future public and private spacecraft design. As the technologies and capabilities evolve, incorporating lessons learned in successful low Earth orbit commercial crew vehicle missions, spacecraft designs will continue to improve and be able to better enable safe execution of human missions to the Moon and beyond.

Robert C Dempsey↗

Trustworthiness and Trust: Identifying Factors that Drive Successful Human-AI Interaction in Nuclear Power Plant Applications

Emerging technologies such as artificial intelligence (AI) and machine learning (ML) are rapidly evolving and considered a promising tool for efficient and continued safe operations of the U.S. nuclear power plants (NPPs). Emerging AI techniques like large language models (LLMs) are one such technology that may support personnel at existing NPPs perform work more efficiently. For example, operators may query the current operational status of a power plant via a chat interface leveraging LLMs to access plant-related information in an interactive manner rather than manually collecting various sensor data for tasks such as surveillances or completing work orders. This is a fundamental shift in the way operators currently perform their tasks today. The literature of human-automation interaction indicates that trust is a crucial factor that drives successful interaction between a human operator and an automated system, like an AI-infused NPP application. This work presents the results of a literature review on key factors that relate to trust in AI/LLM technologies for NPP applications. The relevant literature of human factors and cognitive engineering has identified various factors related to trust including trustworthiness, performance characteristics, operator skill and perceived risk. This preliminary literature review will guide development and evaluation of models involving the identified factors influencing trust in AI and develop a framework for human-centered design for interface between humans and AI. By addressing trust, this work supports developing a technical basis for designing key characteristics of AI/LLM to support calibrated trust, which will ultimately support wide-scale adoption of AI/LLM technologies, as well as ensure safe, effective, and reliable use.

99 - GENERAL AND MISCELLANEOUS↗

Metric Learning for Hyperspectral Image Segmentation

We present a metric learning approach to improve the performance of unsupervised hyperspectral image segmentation. Unsupervised spatial segmentation can assist both user visualization and automatic recognition of surface features. Analysts can use spatially-continuous segments to decrease noise levels and/or localize feature boundaries. However, existing segmentation methods use tasks-agnostic measures of similarity. Here we learn task-specific similarity measures from training data, improving segment fidelity to classes of interest. Multiclass Linear Discriminate Analysis produces a linear transform that optimally separates a labeled set of training classes. The defines a distance metric that generalized to a new scenes, enabling graph-based segmentation that emphasizes key spectral features. We describe tests based on data from the Compact Reconnaissance Imaging Spectrometer (CRISM) in which learned metrics improve segment homogeneity with respect to mineralogical classes.

Compact Reconnaissance Imaging Spectrometer (CRISM↗

Intelligent machines in the twenty-first century: foundations of inference and inquiry

The last century saw the application of Boolean algebra to the construction of computing machines, which work by applying logical transformations to information contained in their memory. The development of information theory and the generalization of Boolean algebra to Bayesian inference have enabled these computing machines, in the last quarter of the twentieth century, to be endowed with the ability to learn by making inferences from data. This revolution is just beginning as new computational techniques continue to make difficult problems more accessible. Recent advances in our understanding of the foundations of probability theory have revealed implications for areas other than logic. Of relevance to intelligent machines, we recently identified the algebra of questions as the free distributive algebra, which will now allow us to work with questions in a way analogous to that which Boolean algebra enables us to work with logical statements. In this paper, we examine the foundations of inference and inquiry. We begin with a history of inferential reasoning, highlighting key concepts that have led to the automation of inference in modern machine-learning systems. We then discuss the foundations of inference in more detail using a modern viewpoint that relies on the mathematics of partially ordered sets and the scaffolding of lattice theory. This new viewpoint allows us to develop the logic of inquiry and introduce a measure describing the relevance of a proposed question to an unresolved issue. Last, we will demonstrate the automation of inference, and discuss how this new logic of inquiry will enable intelligent machines to ask questions. Automation of both inference and inquiry promises to allow robots to perform science in the far reaches of our solar system and in other star systems by enabling them not only to make inferences from data, but also to decide which question to ask, which experiment to perform, or which measurement to take given what they have learned and what they are designed to understand.

Review↗

Spacecraft COst REduction Team (SCORE): TQM/CI on a massive scale

The business of building satellites and space systems has matured. Few missions require, or can afford, excellent performance at any price. The new paradigm is doing more with less, providing quality systems at lower cost--in other words, doing our job 'Faster-Better-Cheaper.' The TRW Spacecraft COst REduction (SCORE) initiative was launched in 1990 by Daniel S. Goldin, then general manager of TRW's Space & Technology Group. The SCORE mission is to apply continuous improvement (CI) techniques to effect major reductions in the cost (our primary goal) and span time (as a corollary) required for the production of spacecraft. SCORE is a multi-year initiative that is having a profound effect on both the procedural and the cultural aspects of how we do business. The objectives of this initiative are being realized. The focus of this paper is not on the results of SCORE per se, but rather on the things we have leaned about how to do continuous improvement on a massive scale, with multilevel (hierarchical) CI teams. The following sections summarize the chronology of the SCORE initiative, from team formation to development of the year-end report for 1991. Lessons learned, the core of this presentation, are discussed--with particular focus on the unique aspects of SCORE. The SCORE initiative is continuing and, as a part of our evolving culture, will never end. It has resulted in profound insights into the way we do work and (the topic at hand) how to do CI for large and complex multidisciplinary development activities.

Bullard, Jerry D.↗

U.S. GPM Status

The joint U.S.-Japan Global Precipitation Measurement (GPM) mission, now in its tenth year of operations, continues to pursue research on scientific and operational shortcomings in algorithms for retrieving global precipitation from satellite observations. A summary of operations, including the orbit boost, processing, science, and applications is provided. This includes key improvements to the GPM products for which NASA has lead responsibility. This includes refinements to ensure continuity for each product across the boundary in 2014 between the predecessor Tropical Rainfall Measuring Mission (TRMM) and the GPM Core Observatory. Early evaluations of the U.S. Science Team’s Integrated Multi-satellitE Retrievals for GPM (IMERG) in V07 show interesting behavior across the TRMM orbit boost that is highly relevant to the planned orbit boost for the GPM Core observatory. We will present summary statistics that illustrate the tremendous demand that exists in the user community for GPM precipitation products, which on the U.S. side is primarily focused on IMERG, and end by considering major issues that might be addressed in up-coming versions. These include the use of machine learning algorithms, the operational challenge of swarms of “small”, perhaps short-lived satellites, and continuation of precessing calibration satellites after GPM.

GPM↗

Integrating NASA Dryden Research Endeavors into the Teaching-Learning of Mathematics in the K-12 Classroom via the WWW

The primary goal of this project was to continue populating the currently existing web site developed in 1998 in conjunction with the NASA Dryden Flight Research Center and California Polytechnic State University, with more mathematics lesson plans and activities that K-12 teachers, students, home-schoolers, and parents could access. All of the activities, while demonstrating some mathematical topic, also showcase the research endeavors of the NASA Dryden Flight Research Center. The website is located at: http://daniel.calpoly.edu/~dfrc/Robin. The secondary goal of this project was to share the web-based activities with educators at various conferences and workshops. To address the primary goal of this project, over the past year, several new activities were posted on the web site and some of the existing activities were enhanced to contain more video clips, photos, and materials for teachers. To address the project's secondary goal, the web-based activities were showcased at several conferences and workshops. Additionally, in order to measure and assess the outreach impact of the web site, a link to the web site hitbox.com was established in April 2001, which allowed for the collection of traffic statistics against the web site (such as the domains of visitors, the frequency of visitors to this web site, etc.) Provided is a description of some of the newly created activities posted on the web site during the project period of 2001-2002, followed by a description of the conferences and workshops at which some of the web-based activities were showcased. Next is a brief summary of the web site's traffic statistics demonstrating its worldwide educational impact, followed by a listing of some of the awards and accolades the web site has received.

Ward, Robin A.↗

Weighted Composition Operators for Learning Nonlinear Dynamics

Operator theoretic methods in dynamical system have been dominated by the use of Koopman operators and their continuous time counterparts, such as Koopman Generators and Liouville Operators. The advantage gained from their use primarily stems from the ability to extract subspaces and eigenfunctions within a space of observables that are invariant with respect to the Koopman operator over that space. When this occurs, a dynamic mode decomposition of the systems state provides a linear model for the dynamical system. Not all Koopman operators have eigenfunctions that may be exploited in this manner. However, the framework can still be leveraged for approximations using other operators. In this setting, we present a different operator for the study of dynamical systems, the weighted composition operator. These operators are compact for a wide range of dynamics and spaces, and through their interactions with occupation kernels and vector valued kernels, they admit an estimation of the underlying dynamics. Here, this manuscript presents a new algorithm for the data driven study of dynamical systems from data, and also provides two numerical experiments where convergence is achieved as a proof of concept.

97 MATHEMATICS AND COMPUTING↗