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At least 235 records · Page 13

Architectural Analysis of Complex Evolving Systems of Systems

The goal of this collaborative project between FC-MD, APL, and GSFC and supported by NASA IV&V Software Assurance Research Program (SARP), was to develop a tool, Dynamic SAVE, or Dyn-SAVE for short, for analyzing architectures of systems of systems. The project team was comprised of the principal investigator (PI) from FC-MD and four other FC-MD scientists (part time) and several FC-MD students (full time), as well as, two APL software architects (part time), and one NASA POC (part time). The PI and FC-MD scientists together with APL architects were responsible for requirements analysis, and for applying and evaluating the Dyn-SAVE tool and method. The PI and a group of FC-MD scientists were responsible for improving the method and conducting outreach activities, while another group of FC-MD scientists were responsible for development and improvement of the tool. Oversight and reporting was conducted by the PI and NASA POC. The project team produced many results including several prototypes of the Dyn-SAVE tool and method, several case studies documenting how the tool and method was applied to APL s software systems, and several published papers in highly respected conferences and journals. Dyn-SAVE as developed and enhanced throughout this research period, is a software tool intended for software developers and architects, software integration testers, and persons who need to analyze software systems from the point of view of how it communicates with other systems. Using the tool, the user specifies the planned communication behavior of the system modeled as a sequence diagram. The user then captures and imports the actual communication behavior of the system, which is then converted and visualized as a sequence diagram by Dyn-SAVE. After mapping the planned to the actual and specifying parameter and timing constraints, Dyn-SAVE detects and highlights deviations between the planned and the actual behavior. Requirements based on the need to analyze two inter-system communication protocols that are representative of protocols used in the Aerospace industry have been specified. The protocols are related: APL s Common Ground System (CGS) as used in the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) and the Radiation Belt Space Probes (RBSP) missions. The analyzed communications were implementations of the Telemetry protocol and the CCSDS File Delivery Protocol (CFDP) protocol. Based on these requirements, three prototypes of Dyn-SAVE were developed and applied to these protocols. The application of Dyn-SAVE to these protocols resulted in the detection of several issues. Dyn-SAVE was also applied to several Testbeds that have previously been used for experimentation earlier on this project, as well as, to other protocols and logs for testing its broader applicability. For example, Dyn-SAVE was used to analyze 1) the communication pattern between a web browser and a web server, 2) the system log of a computer in order to detect offnominal computer shut-down behavior, and 3) the actual test cases of NASA Goddard s Core Flight System (CFS) and automatically generated test cases in order to determine the overlap between the two sets of test cases. In all cases, Dyn-SAVE assisted in providing insightful conclusions about each of the cases identified above.

Lindvall, Mikael↗

The application of integrated knowledge-based systems for the Biomedical Risk Assessment Intelligent Network (BRAIN)

One of NASA's goals for long duration space flight is to maintain acceptable levels of crew health, safety, and performance. One way of meeting this goal is through BRAIN, an integrated network of both human and computer elements. BRAIN will function as an advisor to mission managers by assessing the risk of inflight biomedical problems and recommending appropriate countermeasures. Described here is a joint effort among various NASA elements to develop BRAIN and the Infectious Disease Risk Assessment (IDRA) prototype. The implementation of this effort addresses the technological aspects of knowledge acquisition, integration of IDRA components, the use of expert systems to automate the biomedical prediction process, development of a user friendly interface, and integration of IDRA and ExerCISys systems. Because C language, CLIPS and the X-Window System are portable and easily integrated, they were chosen ss the tools for the initial IDRA prototype.

Loftin, Karin C.↗

Dynamic Acquisition and Retrieval Tool (DART) for Comet Sample Return : Session: 2.06.Robotic Mobility and Sample Acquisition Systems

The 2011 Decadal Survey for planetary science released by the National Research Council of the National Academies identified Comet Surface Sample Return (CSSR) as one of five high priority potential New Frontiers-class missions in the next decade. The main objectives of the research described in this publication are: develop a concept for an end-to-end system for collecting and storing a comet sample to be returned to Earth; design, fabricate and test a prototype Dynamic Acquisition and Retrieval Tool (DART) capable of collecting 500 cc sample in a canister and eject the canister with a predetermined speed; identify a set of simulants with physical properties at room temperature that suitably match the physical properties of the comet surface as it would be sampled. We propose the use of a dart that would be launched from the spacecraft to impact and penetrate the comet surface. After collecting the sample, the sample canister would be ejected at a speed greater than the comet's escape velocity and captured by the spacecraft, packaged into a return capsule and returned to Earth. The dart would be composed of an inner tube or sample canister, an outer tube, a decelerator, a means of capturing and retaining the sample, and a mechanism to eject the canister with the sample for later rendezvous with the spacecraft. One of the significant unknowns is the physical properties of the comet surface. Based on new findings from the recent Deep Impact comet encounter mission, we have limited our search of solutions for sampling materials to materials with 10 to 100 kPa shear strength in loose or consolidated form. As the possible range of values for the comet surface temperature is also significantly different than room temperature and testing at conditions other than the room temperature can become resource intensive, we sought sample simulants with physical properties at room temperature similar to the expected physical properties of the comet surface material. The chosen DART configuration, the efforts to identify a test simulant and the properties of these simulants, and the results of the preliminary testing will be described in this paper.

Dynamic Acquisition and Retrieval Tool (DART)↗

Lessons for Future In-Space Telerobotic Servicing from Robotic Refueling Mission

The Robotic Refueling Mission (RRM) was a multi-phased technology development effort by the National Aeronautics & Space Administration (NASA) and the Canadian Space Agency (CSA). The program leveraged the existing robotic systems and expertise of the International Space Station (ISS) program and the tool design and satellite servicing expertise of NASA’s Exploration & In-space Services (NExIS) Projects Division at Goddard Space Flight Center (GSFC) to evaluate new hardware and techniques for on-orbit telerobotic servicing. Between 2011 and 2021, two external ISS payloads housed over a dozen robotic tools and adapters designed to service a variety of existing and novel satellite interfaces. Robot operators at NASA’s Johnson Space Center (JSC) and CSA used the Special Purpose Dexterous Manipulator (SPDM) to retrieve and operate these tools for tasks such as cutting wires or multi-layer insulation blanketing, removing valve caps, mating electrical connectors, transferring fluids, and performing visual inspections inside a vehicle. Each phase of RRM involved years of preparation. Tool and interface designs were prototyped and evaluated using both NASA and Canadian ground robotic systems. Procedures were developed by GSFC engineers and vetted in partnership with JSC and CSA robot operators. GSFC engineers were trained to provide real-time support during on-orbit operations. These preparatory efforts and the successful on-orbit evaluations yielded an array of lessons for future in-space telerobotic missions. Designing robotic tools for the space environment requires special consideration of materials, indicators, and differences between ground and flight use cases and environments. When there is a limited window for on-orbit operations, devoting time and high-fidelity hardware to ground testing can be critical. Needs during potential troubleshooting are more essential to camera view quality, frame rate, and position requirements more than nominal operations. Detailed hardware manuals, nominal and contingency procedures, along with clearly defined operations team roles and protocols are vital for efficiency. RRM also demonstrated how the ISS can be utilized to increase the technology readiness levels required for future missions and led to additional technology partnerships between NExIS and the ISS program. The lessons from RRM are currently being applied to designs, operations concepts, and ground test methodology for missions such as On-orbit Servicing, Assembly, and Manufacturing1(OSAM-1)and Mars Sample Return.

Zakiya Tomlinson↗

Low-Cost Preform and Molding Processes

The entry cost for prototyping a composite component for manufacture using automated, high rate processes is prohibitively expensive in many cases, especially for small business, where tooling costs may be several $100k. Discussions with industry also indicate that many small companies, tier 1 and 2 suppliers, have an interest to mold composite parts but do not want to deal with the capital cost, material handling issues, and labor associated with dry fiber preforming operations. While the molders may locate near the end user for logistics reasons, it may be more cost effective for the performer to remain regional and invest in capital equipment to support preform automation, thus keeping costs to a minimum. This project was designed to explore and demonstrate several options to meet these industry needs. Dry fiber preforming approaches were evaluated which allow for low pressure resin infusion, single sided tooling options such a vacuum assisted resin transfer molding (VARTM) or low pressure resin transfer molding (RTM-light). Unlike sheet molding compound, SMC compression molding where typical molding pressures of 1000 psi are required to push material into the desired location; positioning of a dry fiber preform into the desired location on the tool allows for low molding pressures of 10-50 psi. Lower molding pressures allow for use of low cost, additive fabrication of polymeric tooling. Polymeric tooling is suitable for rapid part prototyping and limited production. Dry fiber preforming approaches evaluated included use of commercial chopped strand mat, robotic chopper gun deposition, and continuous fiber preform augmentation using tailored fiber placement (TFP). Use of chopped strand mat does not require a robotic deposition method, however a cutting table is generally required and there is typically 20-30% scrap generation. While various fiber areal weights are available, the preform is not readily optimized for minimal fiber use or weight savings. In contrast, a robotic chopper gun approach allows for localized deposition where fiber is required to meet structural requirements. The robotic method is highly automated and minimizes fiber scrap, however the capital cost of the equipment and engineering labor for programming can result in higher preform cost compared to chopped strand mat in certain cases depending on preform complexity. Dry fiber preforming using the robotic chopper gun method allows for creation of three dimensional forms. This approach may be ideal for molding in-house, or if the preforms stack together densely to allow for efficient shipping. Applications evaluated for this program considered trade-off between fabrication of a fully 3D preform versus production of a flat preform which is designed to readily drape into the final desired shape. Such a preform design greatly simplifies robotic programming and requires no specialized tooling. The flat preforms are easily stacked and shipped to the final molding location. Flat preforms are much easier to augment with TFP continuous fiber to provide local reinforcement. The demonstration and evaluation of these preforming and tooling methods were completed on three component applications. The first application was a battery box cover for an electric vehicle which was highly three dimensional. The second demonstrator article was comprised of complex contours and was used to demonstrate the use of TFP and RTM-light molding process. The third demonstration article was the roof of an operator’s cab for large construction equipment. The roof is relatively flat however it is comprised of complex changes in thickness which clearly demonstrate the advantage of robotic chopper gun approach as compared to using numerous preform layers of chopped strand mat. The cost trades for the various preforming methods are summarized to help guide the reader as to preforming method considerations. Finally, these demonstrations all used glass fiber roving. A fourth, exploratory task was added to evaluate the ability to make preforms using Zoltek’s carbon fiber split tow roving. We were able to adapt the chopper gun to make flat preforms for laminate testing, but further development effort would be required to make suitable preforms.

36 MATERIALS SCIENCE↗

Multi-Rigor Agile Verification and Rapid Prototyping for Formally Verified Software

We propose a novel approach to developing formally verified systems through Multi-rigor Agile Verification. Multi-rigor Agile Verification is rooted in the hypothesis of Rigor Independence, that a system’s specification and verification architecture depend primarily on the system requirements to be verified, and they depend very little on the rigor level of the methods used to verify those requirements. Due to its iterative nature, Multi-rigor Agile Verification promises to mitigate many of the high upfront design costs experienced by formally verified systems and to deliver a better-architected, and thus better-trusted, system in the end. We then discuss the tooling needed to perform Multi-rigor Agile Verification and go in depth to build one of those tools, which directly generates executable prototype code from declarative formal specifications using the Maude rewrite-logic framework.

97 MATHEMATICS AND COMPUTING↗

The Integrated Airport Competition Model, 1998

This paper addresses recent model development by the Directorate General of Civil Aviation (DGCA) and Hague Consulting Group (HCG) concerning long-distance travel. Long-distance travel demand is growing very quickly and raising a great deal of economic and policy issues. There is increasing competition among the main Western European airports, and smaller, regional airports are fighting for market share. New modes of transport, such as high speed rail, are also coming into the picture and affect the mode split for medium distance transport within Europe. Developments such as these are demanding the attention of policy makers and a tool is required for their analysis. For DGCA, Hague Consulting Group has developed a model system to provide answers to the policy questions posed by these expected trends, and to identify areas where policy makers can influence the traveller choices. The development of this model system, the Integrated Airport Competition Model/integraal Luchthaven Competitie Model (ILCM), began in 1992. Since that time the sub-models, input data and user interface have been expanded, updated and improved. HCG and DGCA have transformed the ILCM from a prototype into an operational forecasting tool.

Veldhuis, J.↗

The Integrated Airport Competition Model, 1998

This paper addresses recent model development by the Directorate General of Civil Aviation (DGCA) and Hague Consulting Group (HCG) concerning long-distance travel, Long-distance travel demand is growing very quickly and raising a great deal of economic and policy issues. There is increasing competition among the main Western European airports, and smaller, regional airports are fighting for market share. New modes of transport, such as high speed rail, arc also coming into the picture and affect the mode split for medium distance transport within Europe. Developments such as these are demanding the attention of policy makers and a tool is required for their analysis. For DGCA, Hague Consulting Group has developed a model system to provide answers to the policy questions posed by these expected trends, and to identify areas where policy makers can influence the traveller choices. The development of this model system, the Integrated Airport Competition Model/Integral Luchthaven Competitive Model (ILCM), began in 1992. Since that time the sub-models, input data and user interface have been expanded, updated and improved. HCG and DGCA have transformed the ILCM from a prototype into an operational forecasting tool.

Veldhuis, J.↗

Taking the Risk Out of Risk Assessment

The ability to understand risks and have the right strategies in place when risky events occur is essential in the workplace. More and more organizations are being confronted with concerns over how to measure their risks or what kind of risks they can take when certain events transpire that could have a negative impact. NASA is one organization that faces these challenges on a daily basis, as effective risk management is critical to the success of its missions especially the Space Shuttle missions. On July 29, 1996, former NASA Administrator Daniel Goldin charged NASA s Office of Safety and Mission Assurance with developing a probabilistic risk assessment (PRA) tool to support decisions on the funding of Space Shuttle upgrades. When issuing the directive, Goldin said, "Since I came to NASA [in 1992], we've spent billions of dollars on Shuttle upgrades without knowing how much they improve safety. I want a tool to help base upgrade decisions on risk." Work on the PRA tool began immediately. The resulting prototype, the Quantitative Risk Assessment System (QRAS) Version 1.0, was jointly developed by NASA s Marshall Space Flight Center, its Office of Safety and Mission Assurance, and researchers at the University of Maryland. QRAS software automatically expands the reliability logic models of systems to evaluate the probability of highly detrimental outcomes occurring in complex systems that are subject to potential accident scenarios. Even in its earliest forms, QRAS was used to begin PRA modeling of the Space Shuttle. In parallel, the development of QRAS continued, with the goal of making it a world-class tool, one that was especially suited to NASA s unique needs. From the beginning, an important conceptual goal in the development of QRAS was for it to help bridge the gap between the professional risk analyst and the design engineer. In the past, only the professional risk analyst could perform, modify, use, and perhaps even adequately understand PRA. NASA wanted to change this by developing a PRA tool that would be friendlier, more understandable, and more useful to the broader engineering community. This concept ultimately led to the look, feel, and functionality that QRAS has today.

Source record↗

Use of data description languages in the interchange of data

The Consultative Committee for Space Data Systems (CCSDS) is developing Standards for the interchange of information between systems, including those operating under different environments. The objective is to perform the interchange automatically, i.e. in a computer interpretable manner. One aspect of the concept developed by CCSDS is the use of a separate data description to specify the data being transferred. Using the description, data can then be automatically parsed by the receiving computer. With a suitably expressive Data Description Language (DDL), data formats of arbitrary complexity can be handled. The advantages of this approach are: (1) that the description need only be written and distributed once to all users, and (2) new software does not need to be written for each new format, provided generic tools are available to support writing and interpretation of descriptions and the associated data instances. Consequently, the effort of 'hard coding' each new format is avoided and problems of integrating multiple implementations of a given format by different users are avoided. The approach is applicable in any context where computer parsable description of data could enhance efficiency (e.g. within a spacecraft control system, a data delivery system or an archive). The CCSDS have identified several candidate DDL's: EAST (Extended Ada Subset), TSDN (Transfer Syntax Data Notation) and MADEL (Modified ASN.1 as a Data Description Language -- a DDL based on the Abstract Syntax Notation One - ASN.1 - specified in the ISO/IEC 8824). This paper concentrates on ESA's development of MADEL. ESA have also developed a 'proof of concept' prototype of the required support tools, implemented on a PC under MS-DOS, which has successfully demonstrated the feasibility of the approach, including the capability within an application of retrieving and displaying particular data elements, given its MADEL description (i.e. a data description written in MADEL). This paper outlines the work done to date and assesses the applicability of this modified ASN.1 as a DDL. The feasibility of the approach is illustrated with several examples.

Pignede, M.↗

Methodology for Prototyping Increased Levels of Automation for Spacecraft Rendezvous Functions

The Crew Exploration Vehicle necessitates higher levels of automation than previous NASA vehicles, due to program requirements for automation, including Automated Rendezvous and Docking. Studies of spacecraft development often point to the locus of decision-making authority between humans and computers (i.e. automation) as a prime driver for cost, safety, and mission success. Therefore, a critical component in the Crew Exploration Vehicle development is the determination of the correct level of automation. To identify the appropriate levels of automation and autonomy to design into a human space flight vehicle, NASA has created the Function-specific Level of Autonomy and Automation Tool. This paper develops a methodology for prototyping increased levels of automation for spacecraft rendezvous functions. This methodology is used to evaluate the accuracy of the Function-specific Level of Autonomy and Automation Tool specified levels of automation, via prototyping. Spacecraft rendezvous planning tasks are selected and then prototyped in Matlab using Fuzzy Logic techniques and existing Space Shuttle rendezvous trajectory algorithms.

Hart, Jeremy J.↗

Resource Allocation Planning Helper (RALPH): Lessons learned

The current task of Resource Allocation Process includes the planning and apportionment of JPL's Ground Data System composed of the Deep Space Network and Mission Control and Computing Center facilities. The addition of the data driven, rule based planning system, RALPH, has expanded the planning horizon from 8 weeks to 10 years and has resulted in large labor savings. Use of the system has also resulted in important improvements in science return through enhanced resource utilization. In addition, RALPH has been instrumental in supporting rapid turn around for an increased volume of special what if studies. The status of RALPH is briefly reviewed and important lessons learned from the creation of an highly functional design team are focused on through an evolutionary design and implementation period in which an AI shell was selected, prototyped, and ultimately abandoned, and through the fundamental changes to the very process that spawned the tool kit. Principal topics include proper integration of software tools within the planning environment, transition from prototype to delivered to delivered software, changes in the planning methodology as a result of evolving software capabilities and creation of the ability to develop and process generic requirements to allow planning flexibility.

Durham, Ralph↗

Experimental Verification of Electric Drive Technologies Based on Artificial Intelligence Tools

In this report, a fully integrated prototype of a flight servo control system is successfully developed and implemented using brushless dc motors. The control system is developed by the fuzzy logic theory, and implemented with a multilayer neural network. First, a neural network-based architecture is introduced for fuzzy logic control. The characteristic rules and their membership functions of fuzzy systems are represented as the processing nodes in the neural network structure. The network structure and the parameter learning are performed simultaneously and online in the fuzzy-neural network system. The structure learning is based on the partition of input space. The parameter learning is based on the supervised gradient decent method, using a delta adaptation law. Using experimental setup, the performance of the proposed control system is evaluated under various operating conditions. Test results are presented and discussed in the report. The proposed learning control system has several advantages, namely, simple structure and learning capability, robustness and high tracking performance and few nodes at hidden layers. In comparison with the PI controller, the proposed fuzzy-neural network system can yield a better dynamic performance with shorter settling time, and without overshoot. Experimental results have shown that the proposed control system is adaptive and robust in responding to a wide range of operating conditions. In summary, the goal of this study is to design and implement-advanced servosystems to actuate control surfaces for flight vehicles, namely, aircraft and helicopters, missiles and interceptors, and mini- and micro-air vehicles.

Rubaai, Ahmed↗

Securing Sensitive Flight and Engine Simulation Data Using Smart Card Technology

NASA Glenn Research Center has developed a smart card prototype capable of encrypting and decrypting disk files required to run a distributed aerospace propulsion simulation. Triple Data Encryption Standard (3DES) encryption is used to secure the sensitive intellectual property on disk pre, during, and post simulation execution. The prototype operates as a secure system and maintains its authorized state by safely storing and permanently retaining the encryption keys only on the smart card. The prototype is capable of authenticating a single smart card user and includes pre simulation and post simulation tools for analysis and training purposes. The prototype's design is highly generic and can be used to protect any sensitive disk files with growth capability to urn multiple simulations. The NASA computer engineer developed the prototype on an interoperable programming environment to enable porting to other Numerical Propulsion System Simulation (NPSS) capable operating system environments.

Blaser, Tammy M.↗

Building Toward the Future in Chemical and Materials Simulation with Accessible and Intelligently Designed Web Applications

Over the last few decades, significant progress has been made in the development and use of electronic structure and other molecular simulation methods. As these methods become more mature and are able to simulate larger and more complex chemical simulations, the need for improvement in scientific visualization, molecular builders, simplified input to simulation methods, and the development of new approaches and languages to describe simulations, along with workflows to carry them out, becomes more apparent. In this chapter, we describe our recent efforts in developing a prototype open-source computational tool called Arrows that combines NWChem, SQL and NoSQL databases, email, web APIs, and web applications in a way that make molecular and materials modeling accessible to all scientists and engineers. At the same time, because of its simplified input, it provides a framework for expert users to carry out large numbers of calculations and run complex workflows.

The effect of secondary phases on microstructure and irradiation damage in an as-built additively manufactured 316 L stainless steel with a hafnium compositional gradient

Additive manufacturing (AM) or rapid prototyping has become a crucial tool for reducing both cost and time while increasing efficiency in qualifying structural materials for reactor use. In this study, directed energy deposition (DED) was used to develop an as-built 316 L stainless steel sample with three regions of increasing Hf-dopant to study the effects of Hf on the irradiation response of the material. Morphological and microstructural changes were analyzed before and after 2 MeV proton irradiation at 360 °C to a damage of 2.5 dpa at ~ 10 µm below the surface. The addition of Hf effectively suppressed radiation-induced damage (dislocation loops, radiation-induced segregation) due to enhanced point defect recombination. The radiation damage seen in the as-built sample was further compared to a thermo-mechanically treated counterpart of the same fabrication and irradiation parameters which was found to behave superiorly. In conclusion, the increased radiation resistance of this material may be attributed to the as-built microstructure, which includes undissolved Hf particles, delta ferrite grains and cellular sub-grain boundaries that can hinder defect motion.

316L Stainless Steel↗

32 examples of LLM applications in materials science and chemistry: towards automation, assistants, agents, and accelerated scientific discovery

Abstract Large language models (LLMs) are reshaping many aspects of materials science and chemistry research, enabling advances in molecular property prediction, materials design, scientific automation, knowledge extraction, and more. Recent developments demonstrate that the latest class of models are able to integrate structured and unstructured data, assist in hypothesis generation, and streamline research workflows. To explore the frontier of LLM capabilities across the research lifecycle, we review applications of LLMs through 32 total projects developed during the second annual LLM hackathon for applications in materials science and chemistry, a global hybrid event. These projects spanned seven key research areas: (1) molecular and material property prediction, (2) molecular and material design, (3) automation and novel interfaces, (4) scientific communication and education, (5) research data management and automation, (6) hypothesis generation and evaluation, and (7) knowledge extraction and reasoning from the scientific literature. Collectively, these applications illustrate how LLMs serve as versatile predictive models, platforms for rapid prototyping of domain-specific tools, and much more. In particular, improvements in both open source and proprietary LLM performance through the addition of reasoning, additional training data, and new techniques have expanded effectiveness, particularly in low-data environments and interdisciplinary research. As LLMs continue to improve, their integration into scientific workflows presents both new opportunities and new challenges, requiring ongoing exploration, continued refinement, and further research to address reliability, interpretability, and reproducibility.

Computer Science↗

Precision signal power measurement

Accurate estimation of signal power is an important Deep Space Network (DSN) consideration. Ultimately, spacecraft power and weight is saved if no reserve transmitter power is needed to compensate for inaccurate measurements. Spectral measurement of the received signal has proved to be an effective method of estimating signal power over a wide dynamic range. Furthermore, on-line spectral measurements provide an important diagnostic tool for examining spacecraft anomalies. Prototype equipment installed at a 64-m-diameter antenna site has been successfully used to make measurements of carrier power and sideband symmetry of telemetry signals received from the Mariner Mars 1971 spacecraft.

Winkelstein, R.↗