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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Electrical meter probe contact verification system

A system and method verifies continuity with and measures voltage across a circuit under test (in some instances simultaneously) using two or more test probes. Two or more probe continuity circuits measure continuity through the test probes by injecting a test current through and measuring a processed test current received at each of the plurality of test probes. The probe continuity circuits measure the respective processed test current rendered by the test current flowing through the test circuit at each test probe. A voltmeter measures the potential difference across the test probes.

42 ENGINEERING↗
DOE OSTI2023

On-the-fly computation of analog mixed-signal (AMS) measurements

The present disclosure generally relates to an analog mixed-signal (AMS) design verification system. In particular, the present disclosure relates to a system and method for system verification. One example method includes: obtaining an electronic representation of the circuit design; generating at least a portion of a waveform using the electronic representation of the circuit to obtain a first segment of the waveform associated with the circuit; converting, via the one or more processors, one or more measurement functions to code for performing the one or more computations on the first segment of the waveform; performing one or more computations on the first segment of the waveform using the code; and identifying when a behavior of the circuit violates a design specification based on whether a result of the one or more computations meets a threshold.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1987

Verification issues for rule-based expert systems

Verification and validation of expert systems is very important for the future success of this technology. Software will never be used in non-trivial applications unless the program developers can assure both users and managers that the software is reliable and generally free from error. Therefore, verification and validation of expert systems must be done. The primary hindrance to effective verification and validation is the use of methodologies which do not produce testable requirements. An extension of the flight technique panels used in previous NASA programs should provide both documented requirements and very high levels of verification for expert systems.

Culbert, Chris↗
NASA NTRS2011

Systems, methods and apparatus for pattern matching in procedure development and verification

Systems, methods and apparatus are provided through which, in some embodiments, a formal specification is pattern-matched from scenarios, the formal specification is analyzed, and flaws in the formal specification are corrected. The systems, methods and apparatus may include pattern-matching an equivalent formal model from an informal specification. Such a model can be analyzed for contradictions, conflicts, use of resources before the resources are available, competition for resources, and so forth. From such a formal model, an implementation can be automatically generated in a variety of notations. The approach can improve the resulting implementation, which, in some embodiments, is provably equivalent to the procedures described at the outset, which in turn can improve confidence that the system reflects the requirements, and in turn reduces system development time and reduces the amount of testing required of a new system. Moreover, in some embodiments, two or more implementations can be "reversed" to appropriate formal models, the models can be combined, and the resulting combination checked for conflicts. Then, the combined, error-free model can be used to generate a new (single) implementation that combines the functionality of the original separate implementations, and may be more likely to be correct.

Hinchey, Michael G.↗
NASA NTRS2005

A Tool for Requirements-Based Programming

Absent a general method for mathematically sound, automated transformation of customer requirements into a formal model of the desired system, developers must resort to either manual application of formal methods or to system testing (either manual or automated). While formal methods have afforded numerous successes, they present serious issues, e.g., costs to gear up to apply them (time, expensive staff), and scalability and reproducibility when standards in the field are not settled. The testing path cannot be walked to the ultimate goal, because exhaustive testing is infeasible for all but trivial systems. So system verification remains problematic. System or requirements validation is similarly problematic. The alternatives available today depend on either having a formal model or pursuing enough testing to enable the customer to be certain that system behavior meets requirements. The testing alternative for non-trivial systems always have some system behaviors unconfirmed and therefore is not the answer. To ensure that a formal model is equivalent to the customer s requirements necessitates that the customer somehow fully understands the formal model, which is not realistic. The predominant view that provably correct system development depends on having a formal model of the system leads to a desire for a mathematically sound method to automate the transformation of customer requirements into a formal model. Such a method, an augmentation of requirements-based programming, will be briefly described in this paper, and a prototype tool to support it will be described. The method and tool enable both requirements validation and system verification for the class of systems whose behavior can be described as scenarios. An application of the tool to a prototype automated ground control system for NASA mission is presented.

Rash, James L.↗
NASA NTRS1982

An integrated user-oriented laboratory for verification of digital flight control systems: Features and capabilities

A Digital Flight Control Systems Verification Laboratory (DFCSVL) has been established at NASA Ames Research Center. This report describes the major elements of the laboratory, the research activities that can be supported in the area of verification and validation of digital flight control systems (DFCS), and the operating scenarios within which these activities can be carried out. The DFCSVL consists of a palletized dual-dual flight-control system linked to a dedicated PDP-11/60 processor. Major software support programs are hosted in a remotely located UNIVAC 1100 accessible from the PDP-11/60 through a modem link. Important features of the DFCSVL include extensive hardware and software fault insertion capabilities, a real-time closed loop environment to exercise the DFCS, an integrated set of software verification tools, and a user-oriented interface to all the resources and capabilities.

Defeo, P.↗
NASA NTRS2017

Cleared for Launch - Lessons Learned from the OSIRIS-REx System Requirements Verification Program

Requirements verification of a large flight system is a challenge. It is especially challenging for engineers taking on their first role in space systems engineering. This paper describes our approach to verification of the Origins, Spectral Interpretation, Resource Identification, Security-Regolith Explorer (OSIRIS-REx) system requirements. It also captures lessons learned along the way from developing systems engineers embroiled in this process. We begin with an overview of the mission and science objectives as well as the project requirements verification program strategy. A description of the requirements flow down is presented including our implementation for managing the thousands of program and element level requirements and associated verification data. We discuss both successes and methods to improve the managing of this data across multiple organizational interfaces. Our approach to verifying system requirements at multiple levels of assembly is presented using examples from our work at instrument, spacecraft, and ground segment levels. We include a discussion of system end-to-end testing limitations and their impacts to the verification program. Finally, we describe lessons learned that are applicable to all emerging space systems engineers using our unique perspectives across multiple organizations of a large NASA program.

Requirements Verification↗
DOE OSTI2023

The RF Protection Interlock System Prototype Verification

The Radio Frequency Protection Interlock system plays vital role in the LLRF related/dependent accelerator sections Protection. It’s main role is to collect information from number different sensors and indicators around nearest cavities and cryomodule and provide instant RF signal termination in case of safety thresholds violation. This submission describes newly designed RFPI system tailored to the Proton Improvement Plan II (PIP-II) requirements. The proof of concept prototype of this system has been build. The paper includes also the CMTF environment evaluation tests results and findings as an input to the next full-scope prototype design.

43 PARTICLE ACCELERATORS↗
NASA NTRS1998

Feasibility of Using Neural Network Models to Accelerate the Testing of Mechanical Systems

Verification testing is an important aspect of the design process for mechanical mechanisms, and full-scale, full-length life testing is typically used to qualify any new component for use in space. However, as the required life specification is increased, full-length life tests become more costly and lengthen the development time. At the NASA Lewis Research Center, we theorized that neural network systems may be able to model the operation of a mechanical device. If so, the resulting neural network models could simulate long-term mechanical testing with data from a short-term test. This combination of computer modeling and short-term mechanical testing could then be used to verify the reliability of mechanical systems, thereby eliminating the costs associated with long-term testing. Neural network models could also enable designers to predict the performance of mechanisms at the conceptual design stage by entering the critical parameters as input and running the model to predict performance. The purpose of this study was to assess the potential of using neural networks to predict the performance and life of mechanical systems. To do this, we generated a neural network system to model wear obtained from three accelerated testing devices: 1) A pin-on-disk tribometer; 2) A line-contact rub-shoe tribometer; 3) A four-ball tribometer.

Fusaro, Robert L.↗
NASA NTRS1991

Validation and verification of expert systems

Validation and verification (V&V) are procedures used to evaluate system structure or behavior with respect to a set of requirements. Although expert systems are often developed as a series of prototypes without requirements, it is not possible to perform V&V on any system for which requirements have not been prepared. In addition, there are special problems associated with the evaluation of expert systems that do not arise in the evaluation of conventional systems, such as verification of the completeness and accuracy of the knowledge base. The criticality of most NASA missions make it important to be able to certify the performance of the expert systems used to support these mission. Recommendations for the most appropriate method for integrating V&V into the Expert System Development Methodology (ESDM) and suggestions for the most suitable approaches for each stage of ESDM development are presented.

Gilstrap, Lewey↗