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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

SigmaCLIPSE = presentation management + NASA CLI PS + SQL

SigmaCLIPSE provides an expert systems and 'intelligent' data base development program for diverse systems integration environments that require support for automated reasoning and expert systems technology, presentation management, and access to 'intelligent' SQL data bases. The SigmaCLIPSE technology and and its integrated ability to access 4th generation application development and decision support tools through a portable SQL interface, comprises a sophisticated software development environment for solving knowledge engineering and expert systems development problems in information intensive commercial environments -- financial services, health care, and distributed process control -- where the expert system must be extendable -- a major architectural advantage of NASA CLIPS. SigmaCLIPSE is a research effort intended to test the viability of merging SQL data bases with expert systems technology.

Weiss, Bernard P., Jr.↗
NASA NTRS1996

Sequence-of-events-driven automation of the deep space network

In February 1995, sequence-of-events (SOE)-driven automation technology was demonstrated for a Voyager telemetry downlink track at DSS 13. This demonstration entailed automated generation of an operations procedure (in the form of a temporal dependency network) from project SOE information using artificial intelligence planning technology and automated execution of the temporal dependency network using the link monitor and control operator assistant system. This article describes the overall approach to SOE-driven automation that was demonstrated, identifies gaps in SOE definitions and project profiles that hamper automation, and provides detailed measurements of the knowledge engineering effort required for automation.

Hill, R., Jr.↗
NASA NTRS1996

Sequence-of-Events-Driven Automation of the Deep Space Network

In February 1995, sequence-of-events (SOE)-driven automation technology was demonstrated for a Voyager telemetry downlink track at DSS 13. This demonstration entailed automated generation of an operations procedure (in the form of a temporal dependency network) from project SOE information using artificial intelligence planning technology and automated execution of the temporal dependency network using the link monitor and control operator assistant system. This article describes the overall approach to SOE-driven automation that was demonstrated, identifies gaps in SOE definitions and project profiles that hamper automation, and provides detailed measurements of the knowledge engineering effort required for automation.

Hill, R., Jr.↗
NASA NTRS2000

A Program of Research and Education in Aerospace Structures at the Joint Institute for Advancement of Flight Sciences

The objectives of the cooperative effort with NASA was to conduct research related to aerospace structures and to increase the quality and quantity of highly trained engineers knowledgeable about aerospace structures. The program has successfully met the objectives and has been of significant benefit to NASA LARC, the GWU and the nation. The program was initiated with 3 students in 1994 under the direction of Dr. Robert Tolson as the Principal Investigator. Since initiation, 14 students have been involved in the program, resulting in 11 MS degrees with 2 more expected in 2000. The 11 MS theses and projects are listed. For technology transfer purposes some research is not reported in thesis form. Graduates from the program have been hired at aerospace and other companies across the nation, providing GWU and LARC with important industry and government contacts.

Tolson, Robert H.↗
NASA NTRS2000

Qualitative Discovery in Medical Databases

Implication rules have been used in uncertainty reasoning systems to confirm and draw hypotheses or conclusions. However a major bottleneck in developing such systems lies in the elicitation of these rules. This paper empirically examines the performance of evidential inferencing with implication networks generated using a rule induction tool called KAT. KAT utilizes an algorithm for the statistical analysis of empirical case data, and hence reduces the knowledge engineering efforts and biases in subjective implication certainty assignment. The paper describes several experiments in which real-world diagnostic problems were investigated; namely, medical diagnostics. In particular, it attempts to show that: (1) with a limited number of case samples, KAT is capable of inducing implication networks useful for making evidential inferences based on partial observations, and (2) observation driven by a network entropy optimization mechanism is effective in reducing the uncertainty of predicted events.

Maluf, David A.↗
NASA NTRS1995

Application of NASA's Advanced Life Support Technologies for Waste Treatment, Water Purification and Recycle, and Food Production in Polar Regions

NASA's advanced life support technologies are being combined with Arctic science and engineering knowledge to address the unique needs of the remote communities of Alaska through the Advanced Life Systems for Extreme Environments (ALSEE) project. ALSEE is a collaborative effort involving NASA, the State of Alaska, the University of Alaska, the North Slope Borough of Alaska, and the National Science Foundation (NSF). The focus is a major issue in the state of Alaska and other areas of the Circumpolar North, the health and welfare of its people, their lives and the subsistence lifestyle in remote communities, economic opportunity, and care for the environment. The project primarily provides treatment and reduction of waste, purification and recycling of water. and production of food. A testbed is being established to demonstrate the technologies which will enable safe, healthy, and autonomous function of remote communities and to establish the base for commercial development of the resulting technology into new industries. The challenge is to implement the technological capabilities in a manner compatible with the social and economic structures of the native communities, the state, and the commercial sector. Additional information is contained in the original extended abstract.

Bubenheim, David L.↗
NASA NTRS2008

DARPA/USAF/USN J-UCAS X-45A System Demonstration Program: A Review of Flight Test Site Processes and Personnel

The Joint Unmanned Combat Air Systems (J-UCAS) program is a collaborative effort between the Defense Advanced Research Project Agency (DARPA), the US Air Force (USAF) and the US Navy (USN). Together they have reviewed X-45A flight test site processes and personnel as part of a system demonstration program for the UCAV-ATD Flight Test Program. The goal was to provide a disciplined controlled process for system integration and testing and demonstration flight tests. NASA's Dryden Flight Research Center (DFRC) acted as the project manager during this effort and was tasked with the responsibilities of range and ground safety, the provision of flight test support and infrastructure and the monitoring of technical and engineering tasks. DFRC also contributed their engineering knowledge through their contributions in the areas of autonomous ground taxi control development, structural dynamics testing and analysis and the provision of other flight test support including telemetry data, tracking radars, and communications and control support equipment. The Air Force Flight Test Center acted at the Deputy Project Manager in this effort and was responsible for the provision of system safety support and airfield management and air traffic control services, among other supporting roles. The T-33 served as a J-UCAS surrogate aircraft and demonstrated flight characteristics similar to that of the the X-45A. The surrogate served as a significant risk reduction resource providing mission planning verification, range safety mission assessment and team training, among other contributions.

Cosentino, Gary B.↗
NASA NTRS2011

Software Certification - Coding, Code, and Coders

We describe a certification approach for software development that has been adopted at our organization. JPL develops robotic spacecraft for the exploration of the solar system. The flight software that controls these spacecraft is considered to be mission critical. We argue that the goal of a software certification process cannot be the development of "perfect" software, i.e., software that can be formally proven to be correct under all imaginable and unimaginable circumstances. More realistically, the goal is to guarantee a software development process that is conducted by knowledgeable engineers, who follow generally accepted procedures to control known risks, while meeting agreed upon standards of workmanship. We target three specific issues that must be addressed in such a certification procedure: the coding process, the code that is developed, and the skills of the coders. The coding process is driven by standards (e.g., a coding standard) and tools. The code is mechanically checked against the standard with the help of state-of-the-art static source code analyzers. The coders, finally, are certified in on-site training courses that include formal exams.

training↗
NASA NTRS2013

Evidence of Temporal Variation of Titan Atmospheric Density in 2005-2013

One major science objective of the Cassini mission is an investigation of Titan's atmosphere constituent abundances. Titan's atmospheric density is of interest not only to planetary scientists but also to mission design and mission control engineers. Knowledge of the dependency of Titan's atmospheric density with altitude is important because any unexpectedly high atmospheric density has the potential to tumble the spacecraft during a flyby. During low-altitude Titan flyby, thrusters are fired to counter the torque imparted on the spacecraft due to the Titan atmosphere. The denser the Titan's atmosphere is, the higher are the duty cycles of the thruster firings. Therefore thruster firing telemetry data could be used to estimate the atmospheric torque imparted on the spacecraft. Since the atmospheric torque imparted on the spacecraft is related to the Titan's atmospheric density, atmospheric densities are estimated accordingly. In 2005-2013, forty-three low-altitude Titan flybys were executed. The closest approach altitudes of these Titan flybys ranged from 878 to 1,074.8 km. Our density results are also compared with those reported by other investigation teams: Voyager-1 (in November 1980) and the Huygens Atmospheric Structure Instrument, HASI (in January 2005). From our results, we observe a temporal variation of the Titan atmospheric density in 2005-2013. The observed temporal variation is significant and it isn't due to the estimation uncertainty (5.8%, 1 sigma) of the density estimation methodology. Factors that contributed to this temporal variation have been conjectured but are largely unknown. The observed temporal variation will require synergetic analysis with measurements made by other Cassini science instruments and future years of laboratory and modeling efforts to solve. The estimated atmospheric density results are given in this paper help scientists to better understand and model the density structure of the Titan atmosphere.

Atmosphere↗
NASA NTRSDate not supplied

Dust Characterization Needs for Dust Mitigation

Unknowns remain regarding several lunar dust characteristics, and the lunar dust mitigation community, in collaboration with the science community, is compiling a list of lunar dust characterization needs. It is expected, through the course of currently planned or future lunar surface mission instrumentation, lab experiments, or analysis, that some of these unknowns will be characterized. This list is derived from several sources including findings from the 2020 publication “The Impact of Lunar Dust on Human Exploration”, NASA-STD-1008, SLS-SPEC-159 DSNE, and known gaps identified within NASA programs and projects. The goal of this information collection process is to create a list of dust characterization needs based on scientific and engineering knowledge gaps that will aid in the design and survival of designed and future systems, and address the challenges related to defining the lunar environment and mitigating lunar dust effects on systems and operations. Examples of dust properties and characterization needs include detailed examination of the finest fraction of lunar regolith as it varies by surface location, understanding dust transfer within natural and induced environments, determination of the effects of the lunar plasma environment with regards to materials and hardware, understand the triboelectric charging effects for activities and hardware in contact with the regolith, including grain to grain electrostatic interactions, and material adhesive properties.

dust mitigation↗
NASA NTRSDate not supplied

Analyzing Launch Operations using the Spaceport Throughput Analysis Resource (STAR)

NASA’s Kennedy Space Center (KSC) and Cape CanaveralSpace Force Station (CCSFS) are the world’s preeminent multi-user spaceport, providing facilities and launch capabilities to the agency, NASA’s commercial partners, and other government agencies. KSC works to ensure an environment in which NASA’s programs and other users can safely and effectively carry out their operations. Approximately 100 launches are expected to take place in 2024. KSC needs to meet the needs of customers who request launches based on their own schedules, but who may not be aware of KSC-wide resource limitations and external constraints on launch operations. KSC-wide resources include telecommunications, range tracking, commodities such as Helium and Nitrogen, and special equipment needed to support launches. External constraints include seasonal launch operations. Since space vehicles are complex and launch operations are uncertain, unexpected events can also cause delays in operations. The Spaceport Throughput AnalysisResource (STAR) assesses whether a specific set of pro-posed launches and associated activities can be performed given the resources KSC currently has available, and external constraints imposed on KSC operations. STAR integrates short-horizon scheduling and simulation of launches using a monte-carlo approach driven by configurable probabilities of different classes of event outcomes, including de-lays and worst-case use of resources. The resulting analyses inform stakeholders of key constraints preventing customers from being able to perform their missions as desired, and give insight into how to improve spaceport throughput. The rest of the paper is organized as follows. In 2 we de-scribe the problem STAR is intended to solve. In Section3 we formally describe the scheduling problem ingredients. In Section 4 we describe how manifests are simulated. InSection 5 we describe the constraints problem that is solved when rescheduling. In Section 6 we describe what information is recorded during manifest simulation in order to evaluate delays. In Section 7 we describe the specific problem solved for KSC. In Section 8 we describe the challenges of knowledge engineering for STAR.

Planning Scheduling Analysis↗
DOE OSTI2018

Experimental and Computational Investigations of Plenum-to-Plenum Heat Transfer and Gas Dynamics under Natural Circulation in a Prismatic Very High Temperature Reactor

All the goals and the objectives set for the project were successfully executed and achieved and all the milestones have been successfully completed. The results that have been obtained for the first time advance the scientific and engineering knowledge and understanding of the plenum-to plenum natural convection of prismatic block nuclear reactors that is encountered during accident or abnormal operation. These have been accomplished by developing and implementing for the first time unique and flexible scaled-down separate and integrated effects experimental plenumto- plenum facility (P2PF) with dual channels at this time that has been equipped with sophisticated measurement techniques integrated in a novel way on the heated and cooled channels. The unique facility is an asset now that can be extended to research multiple channels and to study the effects of hot plumes in the plena for future projects if funding will be available. It can also be modified to research natural convection of pebble bed reactors. Hence, it complement the HTTF at Oregon State University. However, in this study, heat transfer coefficients from the inner wall surface to the flowing gas (both helium and air were used) and the radial temperature and gas velocity profiles have been measured and investigated along the height of the heated and cooled channels using in house developed wall flush mounted heat transfer probes, thermocouple with in house developed adjuster for radial movement with 1 mm increment inside the channel and hot wire anemometry with also in house developed adjuster for 1 mm radial movement inside the channel, respectively. Also advanced tracer technique has been developed to quantify also for the first time the dispersion of the gas dynamics of the hot and cold channels. The research has provided new knowledge and new benchmarking data that can be used to validate computational fluid dynamics (CFD) codes with conjugate heat transfer. The work and its results that have been performed within the budget have demonstrated their superior technical effectiveness and high economic feasibility to perform needed studies for safety analysis and assessment at least cost for these types of gas cooled very high temperature 4th generation nuclear reactors. Accordingly, the results obtained in this project and the unique facility and techniques that have been developed will benefit greatly the public by advancing the technology of the prismatic block nuclear reactors toward commercialization and to ensure they will be designed and operated safely by utilizing the obtained knowledge and having well validated CFD simulations integrated with heat transfer computations

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2013

Public Resistance is Waste-Based and What to Do About That - 13412

'Nuclear Communicators' connect a highly advanced sci-tech world with the world of everyday living. One challenge is helping stakeholders fit together three Big Ideas: (1) the valuable nuclear energy resource, (2) nuclear energy's invisible mortal dangers and potential bad-guy threats, and (3) critical scientific and engineering knowledge that is far over the heads of average (grade 8) USA reading levels. This article provides an overview of what does - and does not - work in our public communications. What does not work: 1. Going off topic. Address what concerns people most: how to manage nuclear wastes. 2. Underestimating public intelligence. What works: 1. Doing your homework on community history regarding nuclear materials. 2. Having discussion forums and public meetings with special guests from industry, government, and local leaders. 3. Regular cycles of communication with community groups to build a long-term dialogue. Solutions to some communication challenges require handling four gaps and one jungle: 1. Facts gap - Honest information about waste disposition. 2. Time gap - The timelines associated with waste management include 300 years, 10,000 years, and 703.8 million years. How do we talk about this? 3. Money gap - Who pays for new waste management challenges and technologies? 4. Confidence gap - Link local options to regional, national, and global knowledge. 5. Decision jungle - How can we make waste management rules and infrastructure more logical and transparent? Public communication needs to be grounded in facts for people who want to be credible actors in the new nuclear world. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

From Machine Learning to Machine Reasoning: A Model-based Approach to Analyze Equipment Reliability Data

In current nuclear power plants (NPPs) a large amount of condition-based data which can be used to assess and monitor component health and performance. Assessing component health from such data can be performed with a large variety of methods. While the analysis of numeric data can be performed with several methods, the extraction of information from textual data remains a challenge. Currently employed natural language processing (NLP) methods do not really provide quantitative information that might be contained in IRs. In addition, the integration of numeric and textual data to identify possible causal relationships between data elements is still an unresolved challenge. This paper presents an approach to extract information from textual (e.g., incident or maintenance reports) and numeric data that relies on model based system engineer (MBSE) models. MBSE are diagrams designed to represent system and component dependencies (from both a form and functional point of view). In our approach, MBSE models emulate system engineer knowledge about component/system architecture. NLP methods are employed to perform syntactic and semantic analyses. Syntactic analysis analyzes the grammatical structure of a sentence while semantic analysis is designed to analyze the logic structure of a sentence. An innovative element of our approach is that semantic analysis uses MBSE models to identify links between textual elements. Similarly, numeric data is directly linked to elements of the MBSE models in order to map which functions are being monitored.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A Model Based Approach to Extract Health Information from Textual Data

In current nuclear power plants (NPPs) a large amount of condition-based data is being generated and stored to assess and monitor component health and performance. The format of this data can be either numeric (e.g., pump vibration data) or textual (e.g., condition report which assess component health). While assessing component health from numeric data can be performed with a large variety of methods, the extraction of information from textual data still remains a challenge. Natural language processing (NLP) methods are starting to be deployed in current NPPs mainly to filter out incident reports (IRs) that are not safety related by employing supervised machine learning methods. However, these methods do not really provide the quantitative information that might be contained in IRs. This paper presents an approach to extract information from textual data (e.g., from IRs, maintenance reports) that is based on NLP data analytics methods coupled with model-based system engineer (MBSE) models. NLP methods are employed to perform syntactic and semantic analyses. Syntactic analysis analyzes the grammatical structure of a sentence; such analysis includes: part of speech (POS) tagging (i.e., identification of grammatic elements of each string - e.g., nouns, verbs), named entity recognition (i.e., identification of text entities - e.g., names, dates, events), and relation extraction (e.g., coreference resolution). On the other hand, semantic analysis is designed to analyze the logic structure of a sentence. Through a specific set of rules, our methods can identify whether a sentence contains health information of a component (e.g., degraded performance, anomaly behavior) or the causal relationship between two events (i.e., a cause-effect pair). An innovative element of our approach is that semantic analysis relies on MBSE models to identify links between textual elements. MBSE are diagrams designed to represent system and component dependencies (from both a form and functional point of view). In our approach, MBSE models emulate system engineer knowledge about component/system architecture. This paper presents in detail how the integration of NLP methods and MBSE models is performed. Few analysis examples focusing on centrifugal pumps are presented.

97 - MATHEMATICS AND COMPUTING↗
NASA NTRS1991

Advances in knowledge-based software engineering

The underlying hypothesis of this work is that a rigorous and comprehensive software reuse methodology can bring about a more effective and efficient utilization of constrained resources in the development of large-scale software systems by both government and industry. It is also believed that correct use of this type of software engineering methodology can significantly contribute to the higher levels of reliability that will be required of future operational systems. An overview and discussion of current research in the development and application of two systems that support a rigorous reuse paradigm are presented: the Knowledge-Based Software Engineering Environment (KBSEE) and the Knowledge Acquisition fo the Preservation of Tradeoffs and Underlying Rationales (KAPTUR) systems. Emphasis is on a presentation of operational scenarios which highlight the major functional capabilities of the two systems.

Truszkowski, Walt↗
NASA NTRS1985

A knowledge based software engineering environment testbed

The Carnegie Group Incorporated and Boeing Computer Services Company are developing a testbed which will provide a framework for integrating conventional software engineering tools with Artifical Intelligence (AI) tools to promote automation and productivity. The emphasis is on the transfer of AI technology to the software development process. Experiments relate to AI issues such as scaling up, inference, and knowledge representation. In its first year, the project has created a model of software development by representing software activities; developed a module representation formalism to specify the behavior and structure of software objects; integrated the model with the formalism to identify shared representation and inheritance mechanisms; demonstrated object programming by writing procedures and applying them to software objects; used data-directed and goal-directed reasoning to, respectively, infer the cause of bugs and evaluate the appropriateness of a configuration; and demonstrated knowledge-based graphics. Future plans include introduction of knowledge-based systems for rapid prototyping or rescheduling; natural language interfaces; blackboard architecture; and distributed processing

Gill, C.↗