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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

A Framework for Integration of IVHM Technologies for Intelligent Integration for Vehicle Management

As a part of the overall goal of developing Integrated Vehicle Health Management (IVHM) systems for aerospace vehicles, the NASA Faculty Fellowship Program (NFFP) at Marshall Space Flight Center has performed a pilot study on IVHM principals which integrates researched IVHM technologies in support of Integrated Intelligent Vehicle Management (IIVM). IVHM is the process of assessing, preserving, and restoring system functionality across flight and ground systems (NASA NGLT 2004). The framework presented in this paper integrates advanced computational techniques with sensor and communication technologies for spacecraft that can generate responses through detection, diagnosis, reasoning, and adapt to system faults in support of IIVM. These real-time responses allow the IIVM to modify the effected vehicle subsystem(s) prior to a catastrophic event. Furthermore, the objective of this pilot program is to develop and integrate technologies which can provide a continuous, intelligent, and adaptive health state of a vehicle and use this information to improve safety and reduce costs of operations. Recent investments in avionics, health management, and controls have been directed towards IIVM. As this concept has matured, it has become clear the IIVM requires the same sensors and processing capabilities as the real-time avionics functions to support diagnosis of subsystem problems. New sensors have been proposed, in addition, to augment the avionics sensors to support better system monitoring and diagnostics. As the designs have been considered, a synergy has been realized where the real-time avionics can utilize sensors proposed for diagnostics and prognostics to make better real-time decisions in response to detected failures. IIVM provides for a single system allowing modularity of functions and hardware across the vehicle. The framework that supports IIVM consists of 11 major on-board functions necessary to fully manage a space vehicle maintaining crew safety and mission objectives: Guidance and Navigation; Communications and Tracking; Vehicle Monitoring; Information Transport and Integration; Vehicle Diagnostics; Vehicle Prognostics; Vehicle mission Planning; Automated Repair and Replacement; Vehicle Control; Human Computer Interface; and Onboard Verification and Validation. Furthermore, the presented framework provides complete vehicle management which not only allows for increased crew safety and mission success through new intelligence capabilities, but also yields a mechanism for more efficient vehicle operations. The representative IVHM technologies for IIVH includes: 1) robust controllers for use in re-usable launch vehicles, 2) scaleable/flexible computer platform using heterogeneous communication, 3) coupled electromagnetic oscillators for enhanced communications, 4) Linux-based real-time systems, 5) genetic algorithms, 6) Bayesian Networks, 7) evolutionary algorithms, 8) dynamic systems control modeling, and 9) advanced sensing capabilities. This paper presents IVHM technologies developed under NASA's NFFP pilot project. The integration of these IVHM technologies forms the framework for IIVM.

Paris, Deidre E.↗
NASA NTRS2005

Intelligent Vehicle Health Management

As a part of the overall goal of developing Integrated Vehicle Health Management systems for aerospace vehicles, the NASA Faculty Fellowship Program (NFFP) at Marshall Space Flight Center has performed a pilot study on IVHM principals which integrates researched IVHM technologies in support of Integrated Intelligent Vehicle Management (IIVM). IVHM is the process of assessing, preserving, and restoring system functionality across flight and ground systems (NASA NGLT 2004). The framework presented in this paper integrates advanced computational techniques with sensor and communication technologies for spacecraft that can generate responses through detection, diagnosis, reasoning, and adapt to system faults in support of INM. These real-time responses allow the IIVM to modify the affected vehicle subsystem(s) prior to a catastrophic event. Furthermore, the objective of this pilot program is to develop and integrate technologies which can provide a continuous, intelligent, and adaptive health state of a vehicle and use this information to improve safety and reduce costs of operations. Recent investments in avionics, health management, and controls have been directed towards IIVM. As this concept has matured, it has become clear the INM requires the same sensors and processing capabilities as the real-time avionics functions to support diagnosis of subsystem problems. New sensors have been proposed, in addition, to augment the avionics sensors to support better system monitoring and diagnostics. As the designs have been considered, a synergy has been realized where the real-time avionics can utilize sensors proposed for diagnostics and prognostics to make better real-time decisions in response to detected failures. IIVM provides for a single system allowing modularity of functions and hardware across the vehicle. The framework that supports IIVM consists of 11 major on-board functions necessary to fully manage a space vehicle maintaining crew safety and mission objectives: Guidance and Navigation; Communications and Tracking; Vehicle Monitoring; Information Transport and Integration; Vehicle Diagnostics; Vehicle Prognostics; Vehicle mission Planning; Automated Repair and Replacement; Vehicle Control; Human Computer Interface; and Onboard Verification and Validation. Furthermore, the presented framework provides complete vehicle management which not only allows for increased crew safety and mission success through new intelligence capabilities, but also yields a mechanism for more efficient vehicle operations. The representative IVHM technologies for computer platform using heterogeneous communication, 3) coupled electromagnetic oscillators for enhanced communications, 4) Linux-based real-time systems, 5) genetic algorithms, 6) Bayesian Networks, 7) evolutionary algorithms, 8) dynamic systems control modeling, and 9) advanced sensing capabilities. This paper presents IVHM technologies developed under NASA's NFFP pilot project and the integration of these technologies forms the framework for IIVM.

Paris, Deidre E.↗
NASA NTRS2007

Development of a Radio Frequency Space Environment Path Emulator for Evaluating Spacecraft Ranging Hardware

The Formation Flying Testbed (FFTB) at the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) provides a hardware-in-the-loop test environment for formation navigation and control. The facility is evolving as a modular, hybrid, dynamic simulation facility for end-to-end guidance, navigation and. control (GN&C) design and analysis of formation flying spacecraft. The core capabilities of the FFTB, as a platform for testing critical hardware and software algorithms in-the-loop, have expanded to include S-band Radio Frequency (RF) modems for inter-spacecraft communication and ranging. To enable realistic simulations that require RF ranging sensors for relative navigation, a mechanism is needed to buffer the RF signals exchanged between spacecraft that accurately emulates the dynamic environment through which the RF signals travel, including the effects of medium, moving platforms, and radiated power. The Path Emulator for RF Signals (PERFS), currently under development at NASA GSFC, provides this capability. The function and performance of a prototype device are presented.

Mitchell, Jason W.↗
NASA NTRS2015

Post-Flight Analysis of the Guidance, Navigation, and Control Performance During Orion Exploration Flight Test 1

The first test flight of the Orion Multi-Purpose Crew Vehicle presented additional challenges for guidance, navigation and control as compared to a typical re-entry from the International Space Station or other Low Earth Orbit. An elevated re-entry velocity and steeper flight path angle were chosen to achieve aero-thermal flight test objectives. New IMU's, a GPS receiver, and baro altimeters were flight qualified to provide the redundant navigation needed for human space flight. The guidance and control systems must manage the vehicle lift vector in order to deliver the vehicle to a precision, coastal, water landing, while operating within aerodynamic load, reaction control system, and propellant constraints. Extensive pre-flight six degree-of-freedom analysis was performed that showed mission success for the nominal mission as well as in the presence of sensor and effector failures. Post-flight reconstruction analysis of the test flight is presented in this paper to show whether that all performance metrics were met and establish how well the pre-flight analysis predicted the in-flight performance.

Barth, Andrew↗
NASA NTRS2016

Seismic Exploration of Small Bodies

As a result of the Phase I study, we have demonstrated that a mission to a smallbody (asteroid, comet) whose objective is to conduct a seismic experiment to understandthe interior structure, can be accomplished with small (<200 kg) spacecraft launched on asmall launch vehicle (Athena IIc).We modeled the seismic response of a small body and calculated that the energynecessary to propagate through the body and be detected by a seismometer. Thesecalculations provide guidance as to the type of energy source that is required. A simpleenergy source similar to a NASA standard initiator (NSI) can be used, although a singleNSI is insufficient. An NSI is an explosive pyrotechnic that is used to sever connectionson spacecraft. Use of such an energy source has illustrated two additional areas of study -anchoring of the source and sensor to the surface and understanding the efficiency ofenergy propagation from the source into the surface.The spacecraft has the ability to carry and deploy a series of source/sensors toconduct the experiment by placing them on the surface. We identified a suite of candidatenear-Earth asteroids as targets and used one 1991VG as the target to calculate the missiontrajectory and ∆V requirements. Spacecraft and launch vehicle performance are launchthat any of the candidates could be reached with appropriate mass and launch margins.Sources and sensors are deployed from arm attached to the spacecraft. Thespacecraft maneuvers next to the target body and presses the sensor against the surfaceand releases it. After emplacing all of the surface packages, the sensors are monitored fora period of time to measure the seismic noise. Finally, the active seismic experiment isconducted.The work conducted during Phase I demonstrates that a small mission can be designed to conduct an active seismic experiment on a small near-Earth body. Whileother targets may require more performance, the basic architecture is viable for anytarget.We have identified a number of specific technical areas that require more detailed study. Those areas are largely focused on the detailed analysis and design of the source mechanism and anchoring it to the surface. Such topics will be part of a Phase IIproposal.

Spacecraft↗
NASA NTRS1990

Knowledge/geometry-based Mobile Autonomous Robot Simulator (KMARS)

Ongoing applied research is focused on developing guidance system for robot vehicles. Problems facing the basic research needed to support this development (e.g., scene understanding, real-time vision processing, etc.) are major impediments to progress. Due to the complexity and the unpredictable nature of a vehicle's area of operation, more advanced vehicle control systems must be able to learn about obstacles within the range of its sensor(s). A better understanding of the basic exploration process is needed to provide critical support to developers of both sensor systems and intelligent control systems which can be used in a wide spectrum of autonomous vehicles. Elcee Computek, Inc. has been working under contract to the Flight Dynamics Laboratory, Wright Research and Development Center, Wright-Patterson AFB, Ohio to develop a Knowledge/Geometry-based Mobile Autonomous Robot Simulator (KMARS). KMARS has two parts: a geometry base and a knowledge base. The knowledge base part of the system employs the expert-system shell CLIPS ('C' Language Integrated Production System) and necessary rules that control both the vehicle's use of an obstacle detecting sensor and the overall exploration process. The initial phase project has focused on the simulation of a point robot vehicle operating in a 2D environment.

Cheng, Linfu↗
NASA NTRS2019

A Survey of the Spacecraft Line-Of-Sight Jitter Problem

Predicting, managing, controlling, and testing spacecraft Line-of-Sight (LoS) jit- ter due to on-board internal disturbance sources is a challenging multi- disciplinary systems engineering problem, especially for those observatories hosting extremely sensitive optical sensor payloads with stringent requirements on allowable LoS jitter. Some specific spacecraft jitter engineering challenges will be introduced and described in this survey paper. Illustrative examples of missions where dynamic interactions have to be addressed to satisfy demanding payload instrument LoS jitter requirements will be provided. Some lessons learned and a set of recommended rules of thumb are also presented to provide guidance for analysts on where to initiate and how to approach a new spacecraft jitter design problem. These experience-based spacecraft jitter lessons learned and rules of thumb are provided in the hope they can be leveraged on new space system development projects to help overcome unfamiliarity with previously identified jitter technical pitfalls and challenges.

Dennehy, Cornelius J.↗
NASA NTRS1993

Computationally efficient algorithms for real-time attitude estimation

For many practical spacecraft applications, algorithms for determining spacecraft attitude must combine inputs from diverse sensors and provide redundancy in the event of sensor failure. A Kalman filter is suitable for this task, however, it may impose a computational burden which may be avoided by sub optimal methods. A suboptimal estimator is presented which was implemented successfully on the Delta Star spacecraft which performed a 9 month SDI flight experiment in 1989. This design sought to minimize algorithm complexity to accommodate the limitations of an 8K guidance computer. The algorithm used is interpreted in the framework of Kalman filtering and a derivation is given for the computation.

Pringle, Steven R.↗
NASA NTRS1999

Experimental and Numerical Analysis of Structural Acousticcontrol Interior Noise Reduction

The research results contained in this technical report were performed under the NASA grant entitled "Experimental and Numerical Structural Acoustic Control for Interior Noise Reduction". The report is based essentially on partial progress of the Ph.D. dissertation prepared by Jeffrey S. Bevan under direct guidance of Dr. Chuh Mei. The document presents a finite element formulation and control of sound radiated from cylindrical panels embedded with piezoceramic actuators. The extended MIN6 shallow shell element is fully electrical-structural coupled. A piezoelectric modal actuator participation (PMAP) is defined which indicates the actuator performance to each of the offending modes. Genetic algorithm is also employed to validate the sensor and actuator locations determined by the PMAP criteria. The work was conducted at the Department of Aerospace Engineering, Old Dominion University. Mr. Travis L. Turner, Structural Acoustics Branch, NASA Langley Research Center is the technical monitor.

Mei, Chuh↗
NASA NTRS2000

Development of Wireless Subsurface Microsensors for Health Monitoring of Thermal Protection Systems

Low cost access to space is a primary goal for both NASA and the U.S. aerospace industry. Integrated subsystem health diagnostics is an area where major improvements have been identified for potential implementation into the design of new reusable launch vehicles (RLVS) in order to reduce life cycle costs, increase safety margins and improve mission reliability. A number of efforts are underway to use existing and emerging technologies to establish new methods for vehicle health monitoring on operational vehicles as well as X-vehicles. This paper summarizes a joint effort between several NASA centers and industry partners to develop rapid wireless diagnostic tools for failure management and long-term TPS performance monitoring of thermal protection systems (TPS) on future RLVS. An embedded wireless microsensor suite is being designed to allow rapid subsurface TPS health monitoring and damage assessment. This sensor suite will consist of both passive overlimit sensors and sensors for continuous parameter monitoring in flight. The on-board diagnostic system can be used to radio in maintenance requirements before landing and the data could also be used to assist in design validation for X-vehicles. For a 3rd generation vehicle, wireless diagnostics should be at a stage of technical development that will allow use for intelligent feedback systems for guidance and navigation control applications and can also serve as feedback for TPS that can intelligently adapt to its environment.

Pallix, Joan↗
NASA NTRS2011

The Space Operations Simulation Center (SOSC) and Closed-loop Hardware Testing for Orion Rendezvous System Design

The Space Operations Simulation Center (SOSC) at the Lockheed Martin (LM) Waterton Campus in Littleton, Colorado is a dynamic test environment focused on Autonomous Rendezvous and Docking (AR&D) development testing and risk reduction activities. The SOSC supports multiple program pursuits and accommodates testing Guidance, Navigation, and Control (GN&C) algorithms for relative navigation, hardware testing and characterization, as well as software and test process development. The SOSC consists of a high bay (60 meters long by 15.2 meters wide by 15.2 meters tall) with dual six degree-of-freedom (6DOF) motion simulators and a single fixed base 6DOF robot. The large testing area (maximum sensor-to-target effective range of 60 meters) allows for large-scale, flight-like simulations of proximity maneuvers and docking events. The facility also has two apertures for access to external extended-range outdoor target test operations. In addition, the facility contains four Mission Operations Centers (MOCs) with connectivity to dual high bay control rooms and a data/video interface room. The high bay is rated at Class 300,000 (. 0.5 m maximum particles/m3) cleanliness and includes orbital lighting simulation capabilities.

D'Souza, Christopher↗
NASA NTRS2016

GN and C Subsystem Concept for Safe Precision Landing of the Proposed Lunar MARE Robotic Science Mission

The Lunar MARE (Moon Age and Regolith Explorer) Discovery Mission concept targets delivery of a science payload to the lunar surface for sample collection and dating. The mission science is within a 100-meter radius region of smooth lunar maria terrain near Aristarchus crater. The location has several small, sharp craters and rocks that present landing hazards to the spacecraft. For successful delivery of the science payload to the surface, the vehicle Guidance, Navigation and Control (GN&C) subsystem requires safe and precise landing capability, so design infuses the NASA Autonomous precision Landing and Hazard Avoidance Technology (ALHAT) and a gimbaled, throttleable LOX/LCH4 main engine. The ALHAT system implemented for Lunar MARE is a specialization of prototype technologies in work within NASA for the past two decades, including a passive optical Terrain Relative Navigation (TRN) sensor, a Navigation Doppler Lidar (NDL) velocity and range sensor, and a Lidar-based Hazard Detection (HD) sensor. The landing descent profile is from a retrograde orbit over lighted terrain with landing near lunar dawn. The GN&C subsystem with ALHAT capabilities will deliver the science payload to the lunar surface within a 20-meter landing ellipse of the target location and at a site having greater than 99% safety probability, which minimizes risk to safe landing and delivery of the MARE science payload to the intended terrain region.

MARE (Moon Age and Regolith Explorer)↗
DOE OSTI2012

Appendix I3-1 to Wind HUI Initiative 1: AWST-WindNET-Phase 1 Final Report

This report is an appendix to the Hawaii WindHUI efforts to develop and operationalize short-term wind forecasting and wind ramp event forecasting capabilities. The report summarizes the WindNET Phase 1 efforts on the Big Island of Hawaii and includes descriptions of modeling methodologies, use of field validation data, results and recommendations. The objective of the WindNET project was to investigate the improvement that could be obtained in short-term wind power forecasting for wind generation facilities operating on the island grids operated by Hawaiian Electric Companies through the use of atmospheric sensors deployed at targeted locations. WindNET is envisioned as a multiphase project that will address the short-term wind forecasting issues of all of the wind generation facilities on the all of the Hawaiian Electric Companies' island grid systems. The first phase of the WindNET effort (referred to as WindNET-1) was focused on the wind generation facilities on the Big Island of Hawaii. With complex terrain and marine environment, emphasis was on improving the 0 to 6 hour forecasts of wind power ramps and periods of wind variability, with a particular interest in the intra-hour (0-1 hour) look-ahead period. The WindNET project was built upon a foundation that was constructed with the results from a previously completed observation targeting study for the Big Island that was conducted as part of a project supported by the National Renewable Energy Laboratory (NREL) and interactions with the western utilities. The observational targeting study provided guidance on which variables to measure and at what locations to get the most improvement in forecast performance at a target forecast site. The recommendations of the observation targeting study were based on the application two techniques: (1) an objective method called ensemble sensitivity analysis (ESA) (Ancell and Hakim, 2007; Torn and Hakim, 2008; Zack et al, 2010); and (2) a subjective method based on a diagnostic analysis of large ramp events. The analysis was completed for both the wind farm on the southern tip of the Big Island and on the northern tip of the island. The WindNET project was designed to also deploy sensors to validate the Big Island observational targeting study and enhance operator's understanding of predominate causes of wind variability conditions at the wind facilities. Compromises had to be made with the results from the observation targeting study to accommodate project resource limitations, availability of suitable sites, and other factors. To focus efforts, field sensor deployment activities focused on the wind facility on the southern point of Big Island.

14 SOLAR ENERGY↗
NASA NTRS1988

Feasibility of using GPS measurements for OMV attitude update

This paper presents the results of a feasibility study to determine whether the measurements from GPS satellites can be used to estimate the OMV attitude to an accuracy comparable to the onboard sun sensors, i.e., better than 0.5 degree in each axis. The results documented in this paper demonstrate that OMV attitude can be estimated to an accuracy of 0.1 - 0.5 degree in each axis by processing GPS measurements in an onboard integrated, 17-state GPS/inertial navigation filter. The result is particularly significant for missions of short duration burns where accurate attitude information is needed to minimize guidance and control errors. It is shown that the GPS attitude technique described in this paper can be easily implemented in the current OMV navigation system design. Results reported in this paper are expected to support the goal of developing a fault-tolerant guidance, navigation, and control system offering an improved total navigation performance for the OMV.

Upadhyay, Triveni N.↗
NASA NTRS2005

IVHM Framework for Intelligent Integration for Vehicle Health Management

Integrated Vehicle Health Management (IVHM) systems for aerospace vehicles, is the process of assessing, preserving, and restoring system functionality across flight and techniques with sensor and communication technologies for spacecraft that can generate responses through detection, diagnosis, reasoning, and adapt to system faults in support of Integrated Intelligent Vehicle Management (IIVM). These real-time responses allow the IIVM to modify the affected vehicle subsystem(s) prior to a catastrophic event. Furthermore, this framework integrates technologies which can provide a continuous, intelligent, and adaptive health state of a vehicle and use this information to improve safety and reduce costs of operations. Recent investments in avionics, health management, and controls have been directed towards IIVM. As this concept has matured, it has become clear that IIVM requires the same sensors and processing capabilities as the real-time avionics functions to support diagnosis of subsystem problems. New sensors have been proposed, in addition to augment the avionics sensors to support better system monitoring and diagnostics. As the designs have been considered, a synergy has been realized where the real-time avionics can utilize sensors proposed for diagnostics and prognostics to make better real-time decisions in response to detected failures. IIVM provides for a single system allowing modularity of functions and hardware across the vehicle. The framework that supports IIVM consists of 11 major on-board functions necessary to fully manage a space vehicle maintaining crew safety and mission objectives. These systems include the following: Guidance and Navigation; Communications and Tracking; Vehicle Monitoring; Information Transport and Integration; Vehicle Diagnostics; Vehicle Prognostics; Vehicle Mission Planning, Automated Repair and Replacement; Vehicle Control; Human Computer Interface; and Onboard Verification and Validation. Furthermore, the presented framework provides complete vehicle management which not only allows for increased crew safety and mission success through new intelligence capabilities, but also yields a mechanism for more efficient vehicle operations.

Paris, Deidre↗
NASA NTRS2019

Defining Navigation Requirements for Future Precision Lander Missions

Human mission concepts for both the Moon and Mars require landing precision capabilities beyond the current state of art. The Safe and Precise Landing Integrated Capabilities Evolution (SPLICE) project leverages previous work at NASA to develop multimission precision landing and hazard avoidance (PL&HA) technologies to meet the advanced landing requirements. SPLICE aims to develop guidance, navigation and control (GN&C) capabilities for both Moon and Mars lander missions. The approach the project is using to identify a standard suite begins with developing a PL&HA requirements matrix to inform technology investments. The approach to develop a multi-mission navigation requirements matrix includes identifying representative concepts of operations for both robotic and human missions. It also identifies navigation sensor options with estimated performance parameters. This paper summarizes the concepts of operations and sensors considered to develop the SPLICE PL&HA requirements matrix. A description of the analysis used to determine candidate optimal sensor suites and initial results are provided.

Dwyer Cianciolo, Alicia↗
DOE OSTI2016

A SPATIOTEMPORAL APPROACH FOR HIGH RESOLUTION TRAFFIC FLOW IMPUTATION

Along with the rapid development of Intelligent Transportation Systems (ITS), traffic data collection technologies have been evolving dramatically. The emergence of innovative data collection technologies such as Remote Traffic Microwave Sensor (RTMS), Bluetooth sensor, GPS-based Floating Car method, automated license plate recognition (ALPR) (1), etc., creates an explosion of traffic data, which brings transportation engineering into the new era of Big Data. However, despite the advance of technologies, the missing data issue is still inevitable and has posed great challenges for research such as traffic forecasting, real-time incident detection and management, dynamic route guidance, and massive evacuation optimization, because the degree of success of these endeavors depends on the timely availability of relatively complete and reasonably accurate traffic data. A thorough literature review suggests most current imputation models, if not all, focus largely on the temporal nature of the traffic data and fail to consider the fact that traffic stream characteristics at a certain location are closely related to those at neighboring locations and utilize these correlations for data imputation. To this end, this paper presents a Kriging based spatiotemporal data imputation approach that is able to fully utilize the spatiotemporal information underlying in traffic data. Imputation performance of the proposed approach was tested using simulated scenarios and achieved stable imputation accuracy. Moreover, the proposed Kriging imputation model is more flexible compared to current models.

Han, Lee↗