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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Mars Exploration Rover Mission: Entry, Descent, and Landing System Validation

System validation for a Mars entry, descent, and landing system is not simply a demonstration that the electrical system functions in the associated environments. The function of this system is its interaction with the atmospheric and surface environment. Thus, in addition to traditional test-bed, hardware-in-the-loop, testing, a validation program that confirms the environmental interaction is required. Unfortunately, it is not possible to conduct a meaningful end-to-end test of a Mars landing system on Earth. The validation plan must be constructed from an interconnected combination of simulation, analysis and test. For the Mars Exploration Rover mission, this combination of activities and the logic of how they combined to the system's validation was explicitly stated, reviewed, and tracked as part of the development plan.

system validation↗
NASA NTRS1995

Formal methods and their role in digital systems validation for airborne systems

This report is based on one prepared as a chapter for the FAA Digital Systems Validation Handbook (a guide to assist FAA certification specialists with advanced technology issues). Its purpose is to explain the use of formal methods in the specification and verification of software and hardware requirements, designs, and implementations; to identify the benefits, weaknesses, and difficulties in applying these methods to digital systems used in critical applications; and to suggest factors for consideration when formal methods are offered in support of certification. The presentation concentrates on the rationale for formal methods and on their contribution to assurance for critical applications within a context such as that provided by DO-178B (the guidelines for software used on board civil aircraft); it is intended as an introduction for those to whom these topics are new.

Rushby, John↗
NASA NTRS1993

Formal methods and digital systems validation for airborne systems

This report has been prepared to supplement a forthcoming chapter on formal methods in the FAA Digital Systems Validation Handbook. Its purpose is as follows: to outline the technical basis for formal methods in computer science; to explain the use of formal methods in the specification and verification of software and hardware requirements, designs, and implementations; to identify the benefits, weaknesses, and difficulties in applying these methods to digital systems used on board aircraft; and to suggest factors for consideration when formal methods are offered in support of certification. These latter factors assume the context for software development and assurance described in RTCA document DO-178B, 'Software Considerations in Airborne Systems and Equipment Certification,' Dec. 1992.

Rushby, John↗
DOE OSTI2026

Post-Event Fault Identification with Machine Learning for Protection System Validation

Power system protection devices have transitioned over the past few decades from mechanical to analog devices, then to solid state and finally digital. Relays and their associated critical network of equipment have significantly increased in complexity. Even internally, relays have gained significant intricacy, with relatively simple overcurrent or differential functions now being assisted by a myriad of other functions. This is necessary as the grid becomes more complex, but it brings increased difficulty in monitoring and upkeep. Misoperation caused by accidental improper relay settings or deliberate malicious actions is a constant challenge faced by all utilities. These improper settings can be difficult to identify and may require exhaustive post-mortem analysis, typically after a major outage event has already occurred. A mechanism is needed for monitoring the behavior of protection systems to validate that their performance falls within expectations. Relays that fail to isolate a fault or trip when there is no system disturbance can be flagged for settings review in situations where this behavior may not have been noticed due to manual restoration or backup protection operations. This work presents a concept for a machine learning (ML) system capable of validating the performance of protection systems by identifying fault events and characterizing protection system responses based solely on available current and voltage measurements. As a first step in its development, an experimental dataset is generated, and a random forest model is implemented with high accuracy in distinguishing four power system scenarios.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1989

Design for validation: An approach to systems validation

Every complex system built is validated in some manner. Computer validation begins with review of the system design. As systems became too complicated for one person to review, validation began to rely on the application of adhoc methods by many individuals. As the cost of the changes mounted and the expense of failure increased, more organized procedures became essential. Attempts at devising and carrying out those procedures showed that validation is indeed a difficult technical problem. The successful transformation of the validation process into a systematic series of formally sound, integrated steps is necessary if the liability inherent in the future digita-system-based avionic and space systems is to be minimized. A suggested framework and timetable for the transformtion are presented. Basic working definitions of two pivotal ideas (validation and system life-cyle) are provided and show how the two concepts interact. Many examples are given of past and present validation activities by NASA and others. A conceptual framework is presented for the validation process. Finally, important areas are listed for ongoing development of the validation process at NASA Langley Research Center.

Carter, William C.↗
NASA NTRS2005

Performance Evaluation of a Data Validation System

Online data validation is a performance-enhancing component of modern control and health management systems. It is essential that performance of the data validation system be verified prior to its use in a control and health management system. A new Data Qualification and Validation (DQV) Test-bed application was developed to provide a systematic test environment for this performance verification. The DQV Test-bed was used to evaluate a model-based data validation package known as the Data Quality Validation Studio (DQVS). DQVS was employed as the primary data validation component of a rocket engine health management (EHM) system developed under NASA's NGLT (Next Generation Launch Technology) program. In this paper, the DQVS and DQV Test-bed software applications are described, and the DQV Test-bed verification procedure for this EHM system application is presented. Test-bed results are summarized and implications for EHM system performance improvements are discussed.

Wong, Edmond↗
NASA NTRS1997

Real-Time Sensor Validation System Developed for Reusable Launch Vehicle Testbed

A real-time system for validating sensor health has been developed for the reusable launch vehicle (RLV) program. This system, which is part of the propulsion checkout and control system (PCCS), was designed for use in an integrated propulsion technology demonstrator testbed built by Rockwell International and located at the NASA Marshall Space Flight Center. Work on the sensor health validation system, a result of an industry-NASA partnership, was completed at the NASA Lewis Research Center, then delivered to Marshall for integration and testing. The sensor validation software performs three basic functions: it identifies failed sensors, it provides reconstructed signals for failed sensors, and it identifies off-nominal system transient behavior that cannot be attributed to a failed sensor. The code is initiated by host software before the start of a propulsion system test, and it is called by the host program every control cycle. The output is posted to global memory for use by other PCCS modules. Output includes a list indicating the status of each sensor (i.e., failed, healthy, or reconstructed) and a list of features that are not due to a sensor failure. If a sensor failure is found, the system modifies that sensor's data array by substituting a reconstructed signal, when possible, for use by other PCCS modules.

Jankovsky, Amy L.↗
NASA NTRS2001

Commercial Systems Validation Overview

The Commercial Systems Validation Laboratory (CSVL) is composed of the 1) Virtual Product Laboratory (VPL), 2) Commercial Instrument Validation Laboratory (CIVL), and 3) In-Flight Verification & Validation Network (IVVN). All three laboratories are described in this viewgraph presentation, which covers the characterization of CCD cameras, hyperspectral sensors, ground reference equipment, and the Multispectral Thermal Imager (MTI). The presentation also includes sections on thermal modeling, measurements taken from a float, and the Scientific Data Purchase (SDP) Program. The section of the SDP profiles four data providers: 1) EarthSat; 2) Intermap; 3) Positive Systems; 4) Space Imaging.

Ryan, Robert↗
NASA NTRS1988

Expert system validation in prolog

An overview of the Expert System Validation Assistant (EVA) is being implemented in Prolog at the Lockheed AI Center. Prolog was chosen to facilitate rapid prototyping of the structure and logic checkers and since February 1987, we have implemented code to check for irrelevance, subsumption, duplication, deadends, unreachability, and cycles. The architecture chosen is extremely flexible and expansible, yet concise and complementary with the normal interactive style of Prolog. The foundation of the system is in the connection graph representation. Rules and facts are modeled as nodes in the graph and arcs indicate common patterns between rules. The basic activity of the validation system is then a traversal of the connection graph, searching for various patterns the system recognizes as erroneous. To aid in specifying these patterns, a metalanguage is developed, providing the user with the basic facilities required to reason about the expert system. Using the metalanguage, the user can, for example, give the Prolog inference engine the goal of finding inconsistent conclusions among the rules, and Prolog will search the graph intantiations which can match the definition of inconsistency. Examples of code for some of the checkers are provided and the algorithms explained. Technical highlights include automatic construction of a connection graph, demonstration of the use of metalanguage, the A* algorithm modified to detect all unique cycles, general-purpose stacks in Prolog, and a general-purpose database browser with pattern completion.

Stock, Todd↗
NASA NTRS2012

Bioculture System Validation

The Bioculture System first flight will be to validate the performance of the hardware and its automated and manual operational capabilities in the space flight environment of the International Space Station. Biology, Engineering, and Operations tests will be conducted in the Bioculture System fully characterize its automated and manual functions to support cell culturing for short and long durations. No hypothesis-driven research will be conducted with biological sample, and the science leads have all provided their concurrence that none of the data they collect will be considered as proprietary and can be free distributed to the science community. The outcome of the validation flight will be to commission the hardware for use by the science community. This presentation will provide non-proprietary details about the Bioculture System and information about the activities for the first flight.

Bioculture↗
NASA NTRS2007

Prototype of NASA's Global Precipitation Measurement Mission Ground Validation System

NASA is developing a Ground Validation System (GVS) as one of its contributions to the Global Precipitation Mission (GPM). The GPM GVS provides an independent means for evaluation, diagnosis, and ultimately improvement of GPM spaceborne measurements and precipitation products. NASA's GPM GVS consists of three elements: field campaigns/physical validation, direct network validation, and modeling and simulation. The GVS prototype of direct network validation compares Tropical Rainfall Measuring Mission (TRMM) satellite-borne radar data to similar measurements from the U.S. national network of operational weather radars. A prototype field campaign has also been conducted; modeling and simulation prototypes are under consideration.

Schwaller, M. R.↗
NASA NTRS1998

Real-Time Sensor Validation System Developed

Real-time sensor validation improves process monitoring and control system dependability by ensuring data integrity through automated detection of sensor data failures. The NASA Lewis Research Center, Expert Microsystems, and Intelligent Software Associates have developed an innovative sensor validation system that can automatically detect automated sensor failures in real-time for all types of mission-critical systems. This system consists of a sensor validation network development system and a real-time kernel. The network development system provides tools that enable systems engineers to automatically generate software that can be embedded within an application. The sensor validation methodology captured by these tools can be scaled to validate any number of sensors, and permits users to specify system sensitivity. The resulting software reliably detects all types of sensor data failures.

Zakrajsek, June F.↗
NASA NTRS2021

System Validation on the Europa Clipper mission in Early Implementation Phase

NASA’s next flag-ship mission - Europa Clipper, will embark on a journey to Jupiter’s icy moon Europa in 2024 to assess its environment and habitability with a highly capable spacecraft. Post Jupiter-Orbit-Insertion, the spacecraft will be commanded to perform intricate, yet meticulously planned Europa flybys to perform science investigations using a suite of instruments, while withstanding Jupiter’s harsh radiation environment. The success of this mission is dependent on a well-coordinated project and its elements such as the flight hardware and software, the ground support and mission operations teams, procedures and other cross-cutting elements. The Europa Clipper project needs to ensure that these elements are realized at a reasonable confidence level prior to launch and other mission critical events. System Validation test and analysis activities exercise and confirm the integrity of the system of all project elements in the expected flight environment with reasonable stressing conditions. These activities go beyond system design requirements verification and are driven by validation objectives that describe the end-to-end functional and operational capabilities required during nominal and off-nominal flight-like scenarios and critical events. The challenges associated with validating that the Europa Clipper project as a whole can function and perform correctly to meet the intended mission objectives with the as-delivered capabilities of all of its elements are daunting. This paper discusses the systematic methodology established in the early implementation phase of the Europa Clipper project for developing System Validation activities and their validation objectives, and addressing any validation-related challenges on the project. Approaches include decomposition of mission objectives using activity timelines in the Mission Design plan for developing nominal scenarios, use of fault trees for exploring off-nominal cases and system boundaries, and use of Model-based Systems Engineering (MBSE) tools for planning and prioritizing these activities.

Wang, Xu↗
NASA NTRS2007

Engineering Software Suite Validates System Design

EDAptive Computing Inc.'s (ECI) EDAstar engineering software tool suite, created to capture and validate system design requirements, was significantly funded by NASA's Ames Research Center through five Small Business Innovation Research (SBIR) contracts. These programs specifically developed Syscape, used to capture executable specifications of multi-disciplinary systems, and VectorGen, used to automatically generate tests to ensure system implementations meet specifications. According to the company, the VectorGen tests considerably reduce the time and effort required to validate implementation of components, thereby ensuring their safe and reliable operation. EDASHIELD, an additional product offering from ECI, can be used to diagnose, predict, and correct errors after a system has been deployed using EDASTAR -created models. Initial commercialization for EDASTAR included application by a large prime contractor in a military setting, and customers include various branches within the U.S. Department of Defense, industry giants like the Lockheed Martin Corporation, Science Applications International Corporation, and Ball Aerospace and Technologies Corporation, as well as NASA's Langley and Glenn Research Centers

Source record↗
DOE OSTI2026

Protection System Validation Using Post-Event Anomaly Classification with Machine Learning

Power system protection devices have transitioned over the past few decades from mechanical to analog devices, then to solid state and finally digital. Relays and their associated critical network of equipment have significantly increased in complexity. Even internally, relays have gained significant intricacy, with relatively simple overcurrent or differential functions now being assisted by a myriad of other functions. This is necessary as the grid becomes more complex, but it brings increased difficulty in monitoring and upkeep. Misoperation caused by improper relay settings or malicious actions is a constant challenge faced by all utilities. These improper settings can be difficult to identify and may require exhaustive post-mortem analysis, typically after a major outage event has already occurred. A mechanism is needed for monitoring the behavior of protection systems to validate that they act and perform as expected. This work presents a concept for a machine learning (ML) system capable of validating the performance of protection systems by classifying anomalous events and characterizing protection system responses based solely on available current and voltage measurements. As a first step in its development, an experimental dataset is generated, and a random forest model is implemented with high accuracy in distinguishing four power system scenarios.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Protection System Validation with Machine Learning Anomaly Classification

A poster for the Early Career Poster Session. Power system protection devices have transitioned over the past few decades from mechanical to analog devices, then to solid state and finally digital. Relays and their associated critical network of equipment have significantly increased in complexity. Even internally, relays have gained significant intricacy, with relatively simple overcurrent or differential functions now being assisted by a myriad of other functions. This is necessary as the grid becomes more complex, but it brings increased difficulty in monitoring and upkeep. Misoperation caused by improper relay settings or malicious actions is a constant challenge faced by all utilities. These improper settings can be difficult to identify and may require exhaustive post-mortem analysis, typically after a major outage event has already occurred. A mechanism is needed for monitoring the behavior of protection systems to validate that they act and perform as expected. This work presents a concept for a machine learning (ML) system capable of validating the performance of protection systems by classifying anomalous events and characterizing protection system responses based solely on available current and voltage measurements. As a first step in its development, an experimental dataset is generated, and a random forest model is implemented with high accuracy in distinguishing four power system scenarios.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1985

Integrated Application of Active Controls (IAAC) technology to an advanced subsonic transport project: Test act system validation

The primary objective of the Test Active Control Technology (ACT) System laboratory tests was to verify and validate the system concept, hardware, and software. The initial lab tests were open loop hardware tests of the Test ACT System as designed and built. During the course of the testing, minor problems were uncovered and corrected. Major software tests were run. The initial software testing was also open loop. These tests examined pitch control laws, wing load alleviation, signal selection/fault detection (SSFD), and output management. The Test ACT System was modified to interface with the direct drive valve (DDV) modules. The initial testing identified problem areas with DDV nonlinearities, valve friction induced limit cycling, DDV control loop instability, and channel command mismatch. The other DDV issue investigated was the ability to detect and isolate failures. Some simple schemes for failure detection were tested but were not completely satisfactory. The Test ACT System architecture continues to appear promising for ACT/FBW applications in systems that must be immune to worst case generic digital faults, and be able to tolerate two sequential nongeneric faults with no reduction in performance. The challenge in such an implementation would be to keep the analog element sufficiently simple to achieve the necessary reliability.

Source record↗