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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

An Advanced Fly-By-Wire Flight Control System for the RASCAL Research Rotorcraft: Concept to Reality

Design features of a new fly-by-wire flight control system for the Rotorcraft-Aircrew Systems Concepts Airborne Laboratory (RASCAL) are described. Using a UH-60A Black Hawk helicopter as a baseline vehicle, the RASCAL will be a flying laboratory capable of supporting the research requirements of major NASA and Army guidance, control, and display research programs. The paper describes the research facility requirements of these pro-rams and the design implementation of the research flight control system (RFCS), with emphasis on safety-of-flight, adaptability to multiple requirements and performance considerations.

Rediess, Nicholas A.↗
NASA NTRS2005

Postural Control Disturbances Produced By Exposure to HMD and Dome Vr Systems

Two critical and unresolved human factors issues in VR systems are: 1) potential "cybersickness", a form of motion sickness which is experienced in virtual worlds, and 2) maladaptive sensorimotor performance following exposure to VR systems. Interestingly, these aftereffects are often quite similar to adaptive sensorimotor responses observed in astronauts during and/or following space flight. Most astronauts and cosmonauts experience perceptual and sensorimotor disturbances during and following space flight. All astronauts exhibit decrements in postural control following space flight. It has been suggested that training in virtual reality (VR) may be an effective countermeasure for minimizing perceptual and/or sensorimotor disturbances. People adapt to consistent, sustained alterations of sensory input such as those produced by microgravity, and experimentally-produced stimulus rearrangements (e.g., reversing prisms, magnifying lenses, flight simulators, and VR systems). Adaptation is revealed by aftereffects including perceptual disturbances and sensorimotor control disturbances. The purpose of the current study was to compare disturbances in postural control produced by dome and head-mounted virtual environment displays. Individuals recovered from motion sickness and the detrimental effects of exposure to virtual reality on postural control within one hour. Sickness severity and initial decrements in postural equilibrium decreases over days, which suggests that subjects become dual-adapted over time. These findings provide some direction for developing training schedules for VR users that facilitate adaptation, and address safety concerns about aftereffects.

Harm, D. L.↗
NASA NTRS2009

A Method for Determining the Nominal Occular Hazard Zone for Gaussian Beam Laser Rangers with a Firmware Controlled Variable Focal Length

LIDAR systems that maintain a constant beam spot size on a retroreflector in order to increase the accuracy of bearing and ranging data must use a software controlled variable position lens. These systems periodically update the estimated range and set the position of the focusing lens accordingly. In order to precisely calculate the r NOHD for such a system, the software method for setting the variable position lens and gaussian laser propagation can be used to calculate the irradiance at any point given the range estimation. NASA s Space Shuttle LIDAR, called the Trajectory Control Sensor (TCS), uses this configuration. Analytical tools were developed using Excel and VBA to determine the radiant energy to the International Space Station (ISS) crewmembers eyes while viewing the shuttle on approach and departure. Various viewing scenarios are considered including the use of through-the-lens imaging optics and the window transmissivity at the TCS wavelength. The methodology incorporates the TCS system control logic, gaussian laser propagation, potential failure mode end states, and guidance from American National Standard for the Safe Use of Lasers (ANSI Z136.1-2007). This approach can be adapted for laser safety analyses of similar LIDAR systems.

Picco, C. E.↗
NASA NTRS2010

Modified Universal Design Survey: Enhancing Operability of Launch Vehicle Ground Crew Worksites

Operability is a driving requirement for next generation space launch vehicles. Launch site ground operations include numerous operator tasks to prepare the vehicle for launch or to perform preflight maintenance. Ensuring that components requiring operator interaction at the launch site are designed for optimal human use is a high priority for operability. To promote operability, a Design Quality Evaluation Survey based on Universal Design framework was developed to support Human Factors Engineering (HFE) evaluation for NASA s launch vehicles. Universal Design per se is not a priority for launch vehicle processing however; applying principles of Universal Design will increase the probability of an error free and efficient design which promotes operability. The Design Quality Evaluation Survey incorporates and tailors the seven Universal Design Principles and adds new measures for Safety and Efficiency. Adapting an approach proven to measure Universal Design Performance in Product, each principle is associated with multiple performance measures which are rated with the degree to which the statement is true. The Design Quality Evaluation Survey was employed for several launch vehicle ground processing worksite analyses. The tool was found to be most useful for comparative judgments as opposed to an assessment of a single design option. It provided a useful piece of additional data when assessing possible operator interfaces or worksites for operability.

Blume, Jennifer L.↗
NASA NTRS2014

Strain Gage Load Calibration of the Wing Interface Fittings for the Adaptive Compliant Trailing Edge Flap Flight Test

The safety-of-flight parameters for the Adaptive Compliant Trailing Edge (ACTE) flap experiment require that flap-to-wing interface loads be sensed and monitored in real time to ensure that the structural load limits of the wing are not exceeded. This paper discusses the strain gage load calibration testing and load equation derivation methodology for the ACTE interface fittings. Both the left and right wing flap interfaces were monitored; each contained four uniquely designed and instrumented flap interface fittings. The interface hardware design and instrumentation layout are discussed. Twenty-one applied test load cases were developed using the predicted in-flight loads. Pre-test predictions of strain gage responses were produced using finite element method models of the interface fittings. Predicted and measured test strains are presented. A load testing rig and three hydraulic jacks were used to apply combinations of shear, bending, and axial loads to the interface fittings. Hardware deflections under load were measured using photogrammetry and transducers. Due to deflections in the interface fitting hardware and test rig, finite element model techniques were used to calculate the reaction loads throughout the applied load range, taking into account the elastically-deformed geometry. The primary load equations were selected based on multiple calibration metrics. An independent set of validation cases was used to validate each derived equation. The 2-sigma residual errors for the shear loads were less than eight percent of the full-scale calibration load; the 2-sigma residual errors for the bending moment loads were less than three percent of the full-scale calibration load. The derived load equations for shear, bending, and axial loads are presented, with the calculated errors for both the calibration cases and the independent validation load cases.

Miller, Eric J.↗
NASA NTRS2004

Verification and Validation Methodology of Real-Time Adaptive Neural Networks for Aerospace Applications

Recent research has shown that adaptive neural based control systems are very effective in restoring stability and control of an aircraft in the presence of damage or failures. The application of an adaptive neural network with a flight critical control system requires a thorough and proven process to ensure safe and proper flight operation. Unique testing tools have been developed as part of a process to perform verification and validation (V&V) of real time adaptive neural networks used in recent adaptive flight control system, to evaluate the performance of the on line trained neural networks. The tools will help in certification from FAA and will help in the successful deployment of neural network based adaptive controllers in safety-critical applications. The process to perform verification and validation is evaluated against a typical neural adaptive controller and the results are discussed.

Gupta, Pramod↗
NASA NTRSDate not supplied

Adaptive Stress Testing: Using Reinforcement Learning to Find Failures in Safety-Critical Systems

Emerging applications in artificial intelligence, such as driverless cars and autonomous aircraft promise to be more efficient, cheaper to operate, and always available. However, ensuring the safety of these systems remains a major challenge to their certification and adoption. These autonomous systems are expected to routinely make safety-critical decisions where failures can have serious consequences including loss of life and property. Testing and validation techniques aim to identify and diagnose potential failures before the system is deployed. However, finding failure scenarios in autonomous systems can be very challenging due to high-dimensional and continuous state spaces, interaction with large environments over many time steps, and the rarity of failures. This talk presents Adaptive Stress Testing (AST), a simulation-based testing framework for finding the most likely path to a failure event of a safety-critical system. The key idea of AST is that stress testing can be formulated as a Partially Observable Markov Decision Process (POMDP), which enables reinforcement learning techniques to be used for finding failure events. Reinforcement learning algorithms can efficiently explore the search space and have been shown to scale to very large systems. We present applications of AST to find failures in various safety-critical systems including the aircraft collision avoidance systems, autonomous cars, and small unmanned aerial vehicles.

autonomous vehicles↗
NASA NTRS1971

Unified hatch system

Special hatch sealing mechanism design increases safety, reliability, and convenience. Adaptations are possible for oceanographic and high-speed aircraft design, or for any system where quick-opening pressure hatch is required. In normal mode, hatching mechanism is manually operated from either side.

Hart, R. J.↗
NASA NTRS2006

Power System Concepts for the Lunar Outpost: A Review of the Power Generation, Energy Storage, Power Management and Distribution (PMAD) System Requirements and Potential Technologies for Development of the Lunar Outpost

This paper will review potential power system concepts for the development of the lunar outpost including power generation, energy storage, and power management and distribution (PMAD). In particular, the requirements of the initial robotic missions will be discussed and the technologies considered will include cryogenics and regenerative fuel cells (RFC), AC and DC transmission line technology, high voltage and low voltage power transmission, conductor materials of construction and power beaming concepts for transmitting power to difficult to access locations such as at the bottom of craters. Operating conditions, component characteristics, reliability, maintainability, constructability, system safety, technology gaps/risk and adaptability for future lunar missions will be discussed for the technologies considered.

Khan, Z.↗
NASA NTRS2016

Landing Hazard Avoidance Display

Landing hazard avoidance displays can provide rapidly understood visual indications of where it is safe to land a vehicle and where it is unsafe to land a vehicle. Color coded maps can indicate zones in two dimensions relative to the vehicles position where it is safe to land. The map can be simply green (safe) and red (unsafe) areas with an indication of scale or can be a color coding of another map such as a surface map. The color coding can be determined in real time based on topological measurements and safety criteria to thereby adapt to dynamic, unknown, or partially known environments.

Abernathy, Michael Franklin↗
NASA NTRSDate not supplied

Guidance for Designing Safety into Urban Air Mobility: Hazard Analysis Techniques

The national airspace system is exceptionally safe, specifically in terms of commercial air traffic operations. The introduction of innovative aircraft (such as electric vertical takeoff and landing vehicles) undergoing novel operations (such as for an urban air passenger carrying mission) is a potential disruptor to the current means of regulating and ensuring the safety of air travel. The aviation industry and associated regulatory bodies are adapting their approaches to assuring system safety to enable these new paradigms. However, any system safety analysis requires that a hazard assessment be performed. In this work, we consider the Functional Hazard Assessment (FHA) and Systems Theoretic Process Analysis (STPA) techniques for hazard assessment and evaluate whether they can be used in a complementary fashion for regulatory approval purposes. We perform an FHA and an STPA on an electric vertical takeoff and landing (eVTOL) vehicle undergoing an urban air mobility (UAM) passenger carrying reference scenario and present excerpts of this analysis. We then draw parallels between the techniques and highlight elements where they naturally reinforce to each other’s results, specifically in the consideration of hazard severity with respect to flight phases, the design of hazard mitigations, and the applicability of the results to all types of regulatory approvals (e.g., type certification, operational approval, and crew training).

Mallory S Graydon↗
NASA NTRS2006

Case Study: Test Results of a Tool and Method for In-Flight, Adaptive Control System Verification on a NASA F-15 Flight Research Aircraft

Adaptive control technologies that incorporate learning algorithms have been proposed to enable autonomous flight control and to maintain vehicle performance in the face of unknown, changing, or poorly defined operating environments [1-2]. At the present time, however, it is unknown how adaptive algorithms can be routinely verified, validated, and certified for use in safety-critical applications. Rigorous methods for adaptive software verification end validation must be developed to ensure that. the control software functions as required and is highly safe and reliable. A large gap appears to exist between the point at which control system designers feel the verification process is complete, and when FAA certification officials agree it is complete. Certification of adaptive flight control software verification is complicated by the use of learning algorithms (e.g., neural networks) and degrees of system non-determinism. Of course, analytical efforts must be made in the verification process to place guarantees on learning algorithm stability, rate of convergence, and convergence accuracy. However, to satisfy FAA certification requirements, it must be demonstrated that the adaptive flight control system is also able to fail and still allow the aircraft to be flown safely or to land, while at the same time providing a means of crew notification of the (impending) failure. It was for this purpose that the NASA Ames Confidence Tool was developed [3]. This paper presents the Confidence Tool as a means of providing in-flight software assurance monitoring of an adaptive flight control system. The paper will present the data obtained from flight testing the tool on a specially modified F-15 aircraft designed to simulate loss of flight control faces.

Jacklin, Stephen A.↗
NASA NTRS1991

Adaptive control with an expert system based supervisory level

Adaptive control is presently one of the methods available which may be used to control plants with poorly modelled dynamics or time varying dynamics. Although many variations of adaptive controllers exist, a common characteristic of all adaptive control schemes, is that input/output measurements from the plant are used to adjust a control law in an on-line fashion. Ideally the adjustment mechanism of the adaptive controller is able to learn enough about the dynamics of the plant from input/output measurements to effectively control the plant. In practice, problems such as measurement noise, controller saturation, and incorrect model order, to name a few, may prevent proper adjustment of the controller and poor performance or instability result. In this work we set out to avoid the inadequacies of procedurally implemented safety nets, by introducing a two level control scheme in which an expert system based 'supervisor' at the upper level provides all the safety net functions for an adaptive controller at the lower level. The expert system is based on a shell called IPEX, (Interactive Process EXpert), that we developed specifically for the diagnosis and treatment of dynamic systems. Some of the more important functions that the IPEX system provides are: (1) temporal reasoning; (2) planning of diagnostic activities; and (3) interactive diagnosis. Also, because knowledge and control logic are separate, the incorporation of new diagnostic and treatment knowledge is relatively simple. We note that the flexibility available in the system to express diagnostic and treatment knowledge, allows much greater functionality than could ever be reasonably expected from procedural implementations of safety nets. The remainder of this chapter is divided into three sections. In section 1.1 we give a detailed review of the literature in the area of supervisory systems for adaptive controllers. In particular, we describe the evolution of safety nets from simple ad hoc techniques, up to the use of expert systems for more advanced supervision capabilities.

Sullivan, Gerald A.↗
NASA NTRS2023

Adaptive Independent Verification and Validation (IV&V) Reduces Risk of Software Impacting Safety in Artemis Missions

The National Aeronautics and Space Administration (NASA) is asking more of its human spaceflight programs than ever before through the collective Artemis Missions. The NASA Independent Verification and Validation (IV&V) Program contributes to NASA’s human spaceflight goals by providing IV&V services for NASA’s critical spacecraft and ground software. The IV&V Program is tasked with providing assurance from both individual and integrated mission software perspectives. The Artemis IV&V organization is actively supporting six distinct development efforts: Orion, the Space Launch System (SLS), Exploration Ground Systems (EGS), Mission Control Center (MCC), the Lunar Gateway, and the Human Landing System (HLS), representing a wide diversity of developer organizations, management structures, and development approaches. With much of this extremely complex flight and ground software being essential to human safety both on the ground and in space, Artemis IV&V is likewise challenged to provide more value-added assurance to future Artemis missions within a constrained budget. To meet this challenge, Artemis IV&V employs a variety of novel and evolving “Adaptive IV&V” approaches for planning and executing IV&V analysis to increase both the efficiency and effectiveness of the IV&V Program’s assurance activities, and to address the difficulties imposed by assuring software for a large, highly integrated, multi-mission enterprise managed and executed by physically and organizationally distinct programs. Instilling agile principles like iterative planning cycles, self-organizing teams, and regular retrospectives, into IV&V planning and execution has led to a more rapid turnaround of a minimum viable assurance product and allowed for increased alignment of assurance activities with development progress. Adopting an assurance case methodology has led to greater consistency and clearer communication of assurance design and provided a foundation for long-term maintenance of assurance plans, products, and results across missions. The IV&V-developed Assurance / Safety Case Analytical Network (A-SCAN) framework and tool has enabled the quantification and tracking of system/software risk and confidence. These confidence measures provide a means to repeatedly express the impact of planned and completed assurance work and the remaining residual risk. Applied as part of a “Follow-the-Risk” organizational ethos, this allows consistent rightsizing of analysis rigor and intensity commensurate with the perceived risk of defects, as well as appropriate targeting of the highest risk areas of the software to find safety issues before they can manifest. Finally, the development of the IV&V Advanced Risk Reduction Integrated Software Test and Operations Tri-program Lightweight Environment (ARRISTOTLE), an integrated software-only simulation of Orion, SLS, and EGS systems, has made it possible to independently test integrated pad and flight scenarios and inject faults to observe how the Artemis multi-program, mission software behaves in degraded modes and in response to hazards. These adaptive IV&V investments have enabled Artemis IV&V to become more efficient and effective in IV&V planning and execution and respond more readily to changes in the risk landscape, increasing the breadth and depth of risk reduction possible within the available resources. Residual risk tracking allows IV&V to communicate more effectively with stakeholders, both internal and external at all levels, and inform key decision-making personnel. This evolving assurance design approach provides IV&V surety that work is performed in the highest risk, most value-added areas of the software, to keep our astronauts and ground crews safe and ensure mission success.

Gerek A Whitman↗
NASA NTRS2023

Adaptive Independent Verification and Validation (IV&V) Reduces Risk of Software Impacting Safety in Artemis Missions

The National Aeronautics and Space Administration (NASA) is asking more of its human spaceflight programs than ever before through the collective Artemis Missions. The NASA Independent Verification and Validation (IV&V) Program contributes to NASA’s human spaceflight goals by providing IV&V services for NASA’s critical spacecraft and ground software. The IV&V Program is tasked with providing assurance from both individual and integrated mission software perspectives. The Artemis IV&V organization is actively supporting six distinct development efforts: Orion, the Space Launch System (SLS), Exploration Ground Systems (EGS), Mission Control Center (MCC), the Lunar Gateway, and the Human Landing System (HLS), representing a wide diversity of developer organizations, management structures, and development approaches. With much of this extremely complex flight and ground software being essential to human safety both on the ground and in space, Artemis IV&V is likewise challenged to provide more value-added assurance to future Artemis missions within a constrained budget. To meet this challenge, Artemis IV&V employs a variety of novel and evolving “Adaptive IV&V” approaches for planning and executing IV&V analysis to increase both the efficiency and effectiveness of the IV&V Program’s assurance activities, and to address the difficulties imposed by assuring software for a large, highly integrated, multi-mission enterprise managed and executed by physically and organizationally distinct programs. Instilling agile principles like iterative planning cycles, self-organizing teams, and regular retrospectives, into IV&V planning and execution has led to a more rapid turnaround of a minimum viable assurance product and allowed for increased alignment of assurance activities with development progress. Adopting an assurance case methodology has led to greater consistency and clearer communication of assurance design and provided a foundation for long-term maintenance of assurance plans, products, and results across missions. The IV&V-developed Assurance / Safety Case Analytical Network (A-SCAN) framework and tool has enabled the quantification and tracking of system/software risk and confidence. These confidence measures provide a means to repeatedly express the impact of planned and completed assurance work and the remaining residual risk. Applied as part of a “Follow-the-Risk” organizational ethos, this allows consistent rightsizing of analysis rigor and intensity commensurate with the perceived risk of defects, as well as appropriate targeting of the highest risk areas of the software to find safety issues before they can manifest. Finally, the development of the IV&V Advanced Risk Reduction Integrated Software Test and Operations Tri-program Lightweight Environment (ARRISTOTLE), an integrated software-only simulation of Orion, SLS, and EGS systems, has made it possible to independently test integrated pad and flight scenarios and inject faults to observe how the Artemis multi-program, mission software behaves in degraded modes and in response to hazards. These adaptive IV&V investments have enabled Artemis IV&V to become more efficient and effective in IV&V planning and execution and respond more readily to changes in the risk landscape, increasing the breadth and depth of risk reduction possible within the available resources. Residual risk tracking allows IV&V to communicate more effectively with stakeholders, both internal and external at all levels, and inform key decision-making personnel. This evolving assurance design approach provides IV&V surety that work is performed in the highest risk, most value-added areas of the software, to keep our astronauts and ground crews safe and ensure mission success.

Gerek Whitman↗
NASA NTRS1975

Fire safety: A case study of technology transfer

Two basic ways in which NASA-generated technology is being used by the fire safety community are described. First, improved products and systems that embody NASA technical advances are entering the marketplace. Second, NASA test data and technical information related to fire safety are being used by persons concerned with reducing the hazards of fire through improved design information and standards. The development of commercial fire safety products and systems typically requires adaptation and integration of aerospace technologies that may not have been originated for NASA fire safety applications.

Heins, C. F.↗
NASA NTRS2014

MARGInS: Model-Based Analysis of Realizable Goals in Systems

Under NASAs Constellation effort, the Exploration Technology Development Program funded research toward a system validation capability that applied machine learning and test-case generation techniques to the analysis of black-box system behavior. The behavior analysis capability scaled to spaces of hundreds of input parameters and tens of thousands of test cases. Aerospace systems at the vehicle level, especially those systems which contain some level of autonomy, are best described by hybrid and non-linear mathematics. Even simplified models of such systems need parameter dimensionalities in the hundreds or thousands of parameters in order to capture sufficient fidelity. The System Safety Assessments (such as those described in the SAE ARP 4761A Safety Assessment Process guidelines) for these systems are prone to errorinteractions between the vehicles subsystems are complex, and can display emergent behaviors. NASA captured this new analysis in the Model-based Analysis of Realizable Goals in Systems (MARGInS) tool and applied it to the Pad Abort 1 (PA-1) simulation as part of the independent validation and verification cycle before the PA-1 flight test in May of 2010. MARGInS evaluated the adherence of the high-fidelity simulation to its requirements, and deter- mined the margins to failure from the expected nominal input conditions. Following the PA-1 test, the capabilities within the MARGInS framework have been extended with sophisticated statistical and white-box test case generation techniques and applied to other NASA missions. The frame- work now includes a critical factors analysis that was applied to NASAs Orion simulation and design. NASAs Aeronautics Research Mission Directorate (ARMD) leveraged the existing MARGInS framework for work on aviation safety for civil transport vehicles and for research on autonomy issues. The NASA ARMD effort created a time series output prediction capability that has been used to characterize trajectories for a plane with an adaptive control system, and a safety boundary detection capability that has been applied to an air traffic control concept of operation for the Federal Aviation Administration. The statistical and machine- learning based techniques within MARGInS have been successfully combined with concolic execution to improve the coverage of a critical unit by driving system-level inputs. The use case driving the concolic execution and MARGInS integration was inspired by the Air France 447 disaster in which the loss of a critical functionality (the airspeed calculation from the pitot tubes) led to loss of the entire plane with the people aboard. To illustrate capabilities and limitations, we will highlight the analyses for the applications listed above. We will then discuss the future plans for MARGInS and its interfaces with other tools.

Validation↗