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At least 289 records · Page 16

Human versus automation in responding to failures: an expected-value analysis

A simple analytical criterion is provided for deciding whether a human or automation is best for a failure detection task. The method is based on expected-value decision theory in much the same way as is signal detection. It requires specification of the probabilities of misses (false negatives) and false alarms (false positives) for both human and automation being considered, as well as factors independent of the choice--namely, costs and benefits of incorrect and correct decisions as well as the prior probability of failure. The method can also serve as a basis for comparing different modes of automation. Some limiting cases of application are discussed, as are some decision criteria other than expected value. Actual or potential applications include the design and evaluation of any system in which either humans or automation are being considered.

NASA Discipline Space Human Factors↗

Coupled Solid Rocket Motor Ballistics and Trajectory Modeling for Higher Fidelity Launch Vehicle Design

Multi-stage launch vehicles with solid rocket motors (SRMs) face design optimization challenges, especially when the mission scope changes frequently. Significant performance benefits can be realized if the solid rocket motors are optimized to the changing requirements. While SRMs represent a fixed performance at launch, rapid design iterations enable flexibility at design time, yielding significant performance gains. The streamlining and integration of SRM design and analysis can be achieved with improved analysis tools. While powerful and versatile, the Solid Performance Program (SPP) is not conducive to rapid design iteration. Performing a design iteration with SPP and a trajectory solver is a labor intensive process. To enable a better workflow, SPP, the Program to Optimize Simulated Trajectories (POST), and the interfaces between them have been improved and automated, and a graphical user interface (GUI) has been developed. The GUI enables real-time visual feedback of grain and nozzle design inputs, enforces parameter dependencies, removes redundancies, and simplifies manipulation of SPP and POST's numerous options. Automating the analysis also simplifies batch analyses and trade studies. Finally, the GUI provides post-processing, visualization, and comparison of results. Wrapping legacy high-fidelity analysis codes with modern software provides the improved interface necessary to enable rapid coupled SRM ballistics and vehicle trajectory analysis. Low cost trade studies demonstrate the sensitivities of flight performance metrics to propulsion characteristics. Incorporating high fidelity analysis from SPP into vehicle design reduces performance margins and improves reliability. By flying an SRM designed with the same assumptions as the rest of the vehicle, accurate comparisons can be made between competing architectures. In summary, this flexible workflow is a critical component to designing a versatile launch vehicle model that can accommodate a volatile mission scope.

Ables, Brett↗

Enabling Rapid and Robust Structural Analysis During Conceptual Design

This paper describes a multi-year effort to add a structural analysis subprocess to a supersonic aircraft conceptual design process. The desired capabilities include parametric geometry, automatic finite element mesh generation, static and aeroelastic analysis, and structural sizing. The paper discusses implementation details of the new subprocess, captures lessons learned, and suggests future improvements. The subprocess quickly compares concepts and robustly handles large changes in wing or fuselage geometry. The subprocess can rank concepts with regard to their structural feasibility and can identify promising regions of the design space. The automated structural analysis subprocess is deemed robust and rapid enough to be included in multidisciplinary conceptual design and optimization studies.

Eldred, Lloyd B.↗

Pattern Recognition for a Flight Dynamics Monte Carlo Simulation

The design, analysis, and verification and validation of a spacecraft relies heavily on Monte Carlo simulations. Modern computational techniques are able to generate large amounts of Monte Carlo data but flight dynamics engineers lack the time and resources to analyze it all. The growing amounts of data combined with the diminished available time of engineers motivates the need to automate the analysis process. Pattern recognition algorithms are an innovative way of analyzing flight dynamics data efficiently. They can search large data sets for specific patterns and highlight critical variables so analysts can focus their analysis efforts. This work combines a few tractable pattern recognition algorithms with basic flight dynamics concepts to build a practical analysis tool for Monte Carlo simulations. Current results show that this tool can quickly and automatically identify individual design parameters, and most importantly, specific combinations of parameters that should be avoided in order to prevent specific system failures. The current version uses a kernel density estimation algorithm and a sequential feature selection algorithm combined with a k-nearest neighbor classifier to find and rank important design parameters. This provides an increased level of confidence in the analysis and saves a significant amount of time.

Restrepo, Carolina↗

A System for Fault Management for NASA's Deep Space Habitat

NASA's exploration program envisions the utilization of a Deep Space Habitat (DSH) for human exploration of the space environment in the vicinity of Mars and/or asteroids. Communication latencies with ground control of as long as 20+ minutes make it imperative that DSH operations be highly autonomous, as any telemetry-based detection of a systems problem on Earth could well occur too late to assist the crew with the problem. A DSH-based development program has been initiated to develop and test the automation technologies necessary to support highly autonomous DSH operations. One such technology is a fault management tool to support performance monitoring of vehicle systems operations and to assist with real-time decision making in connection with operational anomalies and failures. Toward that end, we are developing Advanced Caution and Warning System (ACAWS), a tool that combines dynamic and interactive graphical representations of spacecraft systems, systems modeling, automated diagnostic analysis and root cause identification, system and mission impact assessment, and mitigation procedure identification to help spacecraft operators (both flight controllers and crew) understand and respond to anomalies more effectively. In this paper, we describe four major architecture elements of ACAWS: Anomaly Detection, Fault Isolation, System Effects Analysis, and Graphic User Interface (GUI), and how these elements work in concert with each other and with other tools to provide fault management support to both the controllers and crew. We then describe recent evaluations and tests of ACAWS on the DSH testbed. The results of these tests support the feasibility and strength of our approach to failure management automation and enhanced operational autonomy.

Fault management↗

An architecture and model for cognitive engineering simulation analysis - Application to advanced aviation automation

The process of designing crew stations for large-scale, complex automated systems is made difficult because of the flexibility of roles that the crew can assume, and by the rapid rate at which system designs become fixed. Modern cockpit automation frequently involves multiple layers of control and display technology in which human operators must exercise equipment in augmented, supervisory, and fully automated control modes. In this context, we maintain that effective human-centered design is dependent on adequate models of human/system performance in which representations of the equipment, the human operator(s), and the mission tasks are available to designers for manipulation and modification. The joint Army-NASA Aircrew/Aircraft Integration (A3I) Program, with its attendant Man-machine Integration Design and Analysis System (MIDAS), was initiated to meet this challenge. MIDAS provides designers with a test bed for analyzing human-system integration in an environment in which both cognitive human function and 'intelligent' machine function are described in similar terms. This distributed object-oriented simulation system, its architecture and assumptions, and our experiences from its application in advanced aviation crew stations are described.

Corker, Kevin M.↗

Lunar and Planetary Science XXXV: The Future of Mars Surface Exploration

The session The Future of Mars Surface Exploration includes the following topics: 1) High Resolution Laser Scanning Techniques for Rock Abrasion and Texture Analyses on Mars and Earth; 2) Definitive Mineralogical Analysis of Mars Analog Rocks Using the CheMin XRD/XRF Instrument; 3) Quantitative Mineralogical Analysis of Mars Analogues Using CHEMIN Data and Rietveld Refinement; 4) In Situ Analytical Strategy for Mars Combining X-Ray and Optical Techniques; 5) In-Situ Dating on Mars: The Potential of OSL Dating; 6) Experiment of Dynamic Albedo of Neutrons (DAN): Searching for Water-rich Spots from the Rover on the Surface of Mars; and 7) Developing an Automated Science Analysis System for Mars Surface Exploration for MSL and Beyond.

Source record↗

Development and Demonstration of a Digital NDE Pipeline for Streamlined Analysis of Ultrasonic Data

Currently when nondestructive evaluation (NDE) is performed on composite structures, the results, although recorded digitally are often manually interpreted and indicated (drawn) on the part being inspected by hand. Following this, a determination must be made on how to disposition that part. This decision could be based on engineering guidelines and best practices, rule-of-thumb, expert opinion or finite-element analysis of the part with some approximate representation of the damage. In order to streamline this process for ultrasonic inspection an effort was undertaken as part of NASA Advanced Composites Project to develop the Digital NDE Pipeline. The Digital NDE Pipeline is an integrated tool suite and associated framework that streamlines the inspection and defect disposition process through model-assisted inspection optimization, automated defect analysis of NDE data, and mapping of NDE data into finite element analysis software. This paper will provide an overview of the Digital NDE Pipeline and provide details of the individual tools developed along with the results of applying these tools to a demonstration test case.

Composites↗

Analytical Approach for Estimating Preliminary Mass of ARES I Crew Launch Vehicle Upper Stage Structural Components

In January 2004, President Bush gave the National Aeronautics and Space Administration (NASA) a vision for Space Exploration by setting our sight on a bold new path to go back to the Moon, then to Mars and beyond. In response to this vision, NASA started the Constellation Program, which is a new exploration launch vehicle program. The primary mission for the Constellation Program is to carry out a series of human expeditions ranging from Low Earth Orbit to the surface of Mars and beyond for the purposes of conducting human exploration of space, as specified by the Vision for Space Exploration (VSE). The intent is that the information and technology developed by this program will provide the foundation for broader exploration activities as our operational experience grows. The ARES I Crew Launch Vehicle (CLV) has been designated as the launch vehicle that will be developed as a "first step" to facilitate the aforementioned human expeditions. The CLV Project is broken into four major elements: First Stage, Upper Stage Engine, Upper Stage (US), and the Crew Exploration Vehicle (CEV). NASA's Marshall Space Flight Center (MSFC) is responsible for the design of the CLV and has the prime responsibility to design the upper stage of the vehicle. The US is the second propulsive stage of the CLV and provides CEV insertion into low Earth orbit (LEO) after separation from the First Stage of the Crew Launch Vehicle. The fully integrated Upper Stage is a mix of modified existing heritage hardware (J-2X Engine) and new development (primary structure, subsystems, and avionics). The Upper Stage assembly is a structurally stabilized cylindrical structure, which is powered by a single J-2X engine which is developed as a separate Element of the CLV. The primary structure includes the load bearing liquid hydrogen (LH2) and liquid oxygen (LOX) propellant tanks, a Forward Skirt, the Intertank structure, the Aft Skirt and the Thrust Structure. A Systems Tunnel, which carries fluid and electrical power functions to other Elements of the CLV, is included as secondary structure. The MSFC has an overall responsibility for the integrated US element as well as structural design an thermal control of the fuel tanks, intertank, interstage, avionics, main propulsion system, Reaction Control System (RCS) for both the Upper Stage and the First Stage. MSFC's Spacecraft and Vehicle Department, Structural and Analysis Design Division is developing a set of predicted mass of these elements. This paper details the methodology, criterion and tools used for the preliminary mass predictions of the upper stage structural assembly components. In general, weight of the cylindrical barrel sections are estimated using the commercial code Hypersizer, whereas, weight of the domes are developed using classical solutions. HyperSizer is software that performs automated structural analysis and sizing optimization based on aerospace methods for strength, stability, and stiffness. Analysis methods range from closed form, traditional hand calculations repeated every day in industry to more advanced panel buckling algorithms. Margin-of-safety reporting for every potential failure provides the engineer with a powerful insight into the structural problem. Optimization capabilities include finding minimum weight panel or beam concepts, material selections, cross sectional dimensions, thicknesses, and lay-ups from a library of 40 different stiffened and sandwich designs and a database of composite, metallic, honeycomb, and foam materials. Multiple different concepts (orthogrid, isogrid, and skin stiffener) were run for multiple loading combinations of ascent design load with and with out tank pressure as well as proof pressure condition. Subsequently, selected optimized concept obtained from Hypersizer runs was translated into a computer aid design (CAD) model to account for the wall thickness tolerance, weld land etc for developing the most probable weight of the components. The flow diram summarizes the analysis steps used in developing these predicted mass.

Aggarwal, Pravin↗

Global auroral imaging: Dynamics of Explorer Miss ion

An automated contour analysis of auroral images from the DESAI database is being developed. The goal is to be able to feed DESAI images to the software and let it automatically determine the inner and outer boundaries of the auroral oval of a given set of DESAI images. With these contours established, the software will determine the enclosed polar cap area and (model based) integrated magnetic flux through that area. Through the use of this automated system, it will be possible to analyze a large fraction of the DESAI database and correlate it with various other solar-terrestrial space plasma physics parameters and indices.

Frank, L. A.↗

A Formal Methods Approach to the Analysis of Mode Confusion

The goal of the new NASA Aviation Safety Program (AvSP) is to reduce the civil aviation fatal accident rate by 80% in ten years and 90% in twenty years. This program is being driven by the accident data with a focus on the most recent history. Pilot error is the most commonly cited cause for fatal accidents (up to 70%) and obviously must be given major consideration in this program. While the greatest source of pilot error is the loss of situation awareness , mode confusion is increasingly becoming a major contributor as well. The January 30, 1995 issue of Aviation Week lists 184 incidents and accidents involving mode awareness including the Bangalore A320 crash 2/14/90, the Strasbourg A320 crash 1/20/92, the Mulhouse-Habsheim A320 crash 6/26/88, and the Toulouse A330 crash 6/30/94. These incidents and accidents reveal that pilots sometimes become confused about what the cockpit automation is doing. Consequently, human factors research is an obvious investment area. However, even a cursory look at the accident data reveals that the mode confusion problem is much deeper than just training deficiencies and a lack of human-oriented design. This is readily acknowledged by human factors experts. It seems that further progress in human factors must come through a deeper scrutiny of the internals of the automation. It is in this arena that formal methods can contribute. Formal methods refers to the use of techniques from logic and discrete mathematics in the specification, design, and verification of computer systems, both hardware and software. The fundamental goal of formal methods is to capture requirements, designs and implementations in a mathematically based model that can be analyzed in a rigorous manner. Research in formal methods is aimed at automating this analysis as much as possible. By capturing the internal behavior of a flight deck in a rigorous and detailed formal model, the dark corners of a design can be analyzed. This paper will explore how formal models and analyses can be used to help eliminate mode confusion from flight deck designs and at the same time increase our confidence in the safety of the implementation. The paper is based upon interim results from a new project involving NASA Langley and Rockwell Collins in applying formal methods to a realistic business jet Flight Guidance System (FGS).

Butler, Ricky W.↗

CFD Integrated Transition Modeling for High-Speed Flows via Coupled OVERFLOW-LASTRAC Analysis

This work details ongoing efforts at the NASA Langley Research Center to develop and validate a general-use CFD tool that includes built-in predictions of boundary-layer transition in high-speed flows. Existing tools for the coupling of the NASA OVERFLOW structured overset RANS solver and LASTRAC stability analysis code have been extended to capture boundary-layer transition in high-speed flows driven by either Mack’s first-mode or secondmode instabilities and/or crossflow instabilities. The efficacy of this coupled approach has been demonstrated by examining a variety of supersonic and hypersonic test cases for which experimental validation data is available. The intermittency prescription parameters inherited from prior low-speed applications are found to be suitable for some, but not all high-speed flow scenarios. The method is found to be robust for straight cone configurations and improvements necessary to accurately capture transition on geometries with spatially complex amplification factor envelopes with intermediate regions of slow N-factor variation are examined. The automated, coupled analysis is demonstrated for a 3d supersonic test case and found to perform well within the limits of the linear stability analysis on which it relies. Finally, a preliminary investigation of the method’s robustness to non-ideal CFD meshes is conducted.

High-speed flow↗

The Development and Hover Test Application of a Projection Moire Interferometry Blade Displacement Measurement System

Projection moir interferometry (PMI) was employed to measure blade deflections during a hover test of a generic model-scale rotor in the NASA Langley 14x22 subsonic wind tunnel s hover facility. PMI was one of several optical measurement techniques tasked to acquire deflection and flow visualization data for a rotor at several distinct heights above a ground plane. Two of the main objectives of this test were to demonstrate that multiple optical measurement techniques can be used simultaneously to acquire data and to identify and address deficiencies in the techniques. Several PMI-specific technical challenges needed to be addressed during the test and in post-processing of the data. These challenges included developing an efficient and accurate calibration method for an extremely large (65 inch) height range; automating the analysis of the large amount of data acquired during the test; and developing a method to determinate the absolute displacement of rotor blades without a required anchor point measurement. The results indicate that the use of a single-camera/single-projector approach for the large height range reduced the accuracy of the PMI system compared to PMI systems designed for smaller height ranges. The lack of the anchor point measurement (due to a technical issue with one of the other measurement techniques) limited the ability of the PMI system to correctly measure blade displacements to only one of the three rotor heights tested. The new calibration technique reduced the data required by 80 percent while new post-processing algorithms successfully automated the process of locating rotor blades in images, determining the blade quarter chord location, and calculating the blade root and blade tip heights above the ground plane.

Sekula, Martin K.↗

Design and Analysis of a Tool for Automated Fiber Placement of Composite Wind Tunnel Blades

For decades, composite wind tunnel blades have been constructed using labor-intensive hand layup processes. Automated Fiber Placement (AFP) is a relatively new technology that has not seen widespread use in manufacturing composite wind tunnel blades. AFP offers the potential for reduced manufacturing time, reduced cost, and improved consistency compared to traditional hand layup procedures. These manufacturing qualities are becoming increasingly important as existing wind tunnel blades are replaced due to impact damage or wear and tear from decades of use. Researchers at the NASA Langley Research Center are currently using the Integrated Structural Assembly of Advanced Composites (ISAAC) facility to investigate the feasibility of AFP for manufacturing composite wind tunnel blades. ISAAC uses manufacturing tools as surfaces on which to place fiber tows. A manufacturing tool was developed for using AFP to build a wind tunnel blade shape. This paper presents the structural design and analysis of this tool, for use with AFP, constructed from high temperature thermoplastics. The tool fabricated by this design process was successfully used for AFP and oven cure of two representative airfoil shaped composite structures.

Brian Mason↗

3D Localization of Defects in Facility Inspection

Wind tunnels are crucial facilities that support the aerospace industry. However, these facilities are large, complex, and pose unique maintenance and inspection requirements. Manual inspections to identify defects such as cracks, missing fasteners, leaks, and foreign objects are important but labor and schedule intensive. Our goal is to utilize small Unmanned Aircraft Systems (sUAS) and computer vision-based analysis to automate the inspection of the interior and exterior of NASA’s critical wind tunnel facilities. We detect missing fasteners as our defect class, and detect existing fasteners to provide potential future missing fastener sites for preventative maintenance. These detections are done on both 2D raw images and in 3D space to provide a visual reference and real world location to facilitate repairs. A dataset was created consisting of images taken along a grid-like pattern of an interior tunnel section in the AEDC National Full-Scale Aerodynamics Complex (NFAC) at NASA Ames Research Center. Our method uses object detection to create image level bounding boxes of the fasteners and missing fasteners, then uses photogrammetry to create a mapping from 2D image locations to 3D real world locations. The image level bounding boxes and the 2D to 3D mapping are then combined to determine the 3D location of the defects. We describe the data collection, photogrammetry, and computer vision techniques used for object detection as well as a quantitative analysis of the method.

Small Unmanned Aircraft Systems (sUAS)↗

Software Development and Testing Support for the Avionics Systems Telemetry Tool Suite

The Customer Avionics Interface Development and Analysis (CAIDA) team provides modeling and simulation software for the verification of the Launch Control System (LCS). In late 2015, CAIDA began development of the Data Exchange Message (DEM) Generator (DEMGen) and development of the DEM Modifier (DEMMod) in early 2017. DEMGen is able to mimic the telemetry streams normally sent by different simulators allowing increased user control and more telemetry instances. DEMMod takes in a telemetry stream and allows the modification of entire packets or simple measurement values. Together, these tools provide the capabilities to simulate and test complex launch scenarios to ensure LCS is fully prepared for any anomalous behavior during an actual launch. In early 2018, CAIDA began a new project called the CAIDA Advanced Telemetry Tool (CATT), which combined the code and documentation of DEMGen and DEMMod. CATT now allows the integration of new tools into a singular program providing compact and easy access. In the fall of 2018, the author worked with another intern, Antonio Negron, to develop several new CATT features along with proper documentation and unit testing. In the following spring, the author continued that work by integrating the features into CATT, solidifying the documentation, and expanding the testing to cover more cases. The outcome of both semesters includes an inspection engine for automated packet analysis, a packet-masking feature, and a multi-measurement sequencing feature.

Thomas, Taylor Walter↗