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NASA NTRS2007

Assessing Hurricane Katrina Vegetation Damage at Stennis Space Center using IKONOS Image Classification Techniques

Hurricane Katrina hit southwestern Mississippi on August 29, 2005, at 9:45 a.m. CDT as a category 3 storm with surges up to approx. 9 m and sustained winds of approx. 120 mph. The hurricane's wind, rain, and flooding devastated several coastal towns, from New Orleans through Mobile. The storm also caused significant damage to infrastructure and vegetation of NASA's SSC (Stennis Space Center). Storm recovery at SSC involved not only repairs of critical infrastructure but also forest damage mitigation (via timber harvests and control burns to reduce fire risk). This presentation discusses an effort to use commercially available high spatial resolution multispectral IKONOS data for vegetation damage assessment, based on data collected over SSC on September 2, 2005.

Spruce, Joseph P.↗
NASA NTRS2007

Neural Net Safety Monitor Design

The National Aeronautics and Space Administration (NASA) at the Dryden Flight Research Center (DFRC) has been conducting flight-test research using an F-15 aircraft (figure 1). This aircraft has been specially modified to interface a neural net (NN) controller as part of a single-string Airborne Research Test System (ARTS) computer with the existing quad-redundant flight control system (FCC) shown in figure 2. The NN commands are passed to FCC channels 2 and 4 and are cross channel data linked (CCDL) to the other computers as shown. Numerous types of fault-detection monitors exist in the FCC when the NN mode is engaged; these monitors would cause an automatic disengagement of the NN in the event of a triggering fault. Unfortunately, these monitors still may not prevent a possible NN hard-over command from coming through to the control laws. Therefore, an additional and unique safety monitor was designed for a single-string source that allows authority at maximum actuator rates but protects the pilot and structural loads against excessive g-limits in the case of a NN hard-over command input. This additional monitor resides in the FCCs and is executed before the control laws are computed. This presentation describes a floating limiter (FL) concept1 that was developed and successfully test-flown for this program (figure 3). The FL computes the rate of change of the NN commands that are input to the FCC from the ARTS. A window is created with upper and lower boundaries, which is constantly floating and trying to stay centered as the NN command rates are changing. The limiter works by only allowing the window to move at a much slower rate than those of the NN commands. Anywhere within the window, however, full rates are allowed. If a rate persists in one direction, it will eventually hit the boundary and be rate-limited to the floating limiter rate. When this happens, a persistent counter begins and after a limit is reached, a NN disengage command is generated. The tunable metrics for the FL are (1) window size, (2) drift rate, and (3) persistence counter. Ultimate range limits are also included in case the NN command should drift slowly to a limit value that would cause the FL to be defeated. The FL has proven to work as intended. Both high-g transients and excessive structural loads are controlled with NN hard-over commands. This presentation discusses the FL design features and presents test cases. Simulation runs are included to illustrate the dramatic improvement made to the control of NN hard-over effects. A mission control room display from a flight playback is presented to illustrate the neural net fault display representation. The FL is very adaptable to various requirements and is independent of flight condition. It should be considered as a cost-effective safety monitor to control single-string inputs in general.

Larson, Richard R.↗
NASA NTRS2007

Assessing Hurricane Katrina Damage to the Mississippi Gulf Coast Using IKONOS Imagery

Hurricane Katrina hit southwestern Mississippi on August 29, 2005, at 10 a.m. CDT as a category 3 event with storm surges up to approximately 9 m and sustained winds of approximately 120 mph. The hurricane ravaged several coastal towns, destroying or severely damaging hundreds of homes. Hurricand Katrina deposited millions of tons of debris and caused severe damage to coastal forests. In response, several Federal agencies have been using a broad range of remotely sensed data (e.g., IKONOS) to aid damage assessment and disaster recovery efforts. This presentation discusses an effort to use IKONOS data for damage assessment, based on data collected over southwestern coastal Mississippi on September 2, 2005.

Spruce, Joseph P.↗
NASA NTRS2007

Investigation of MMOD Impact on STS-115 Shuttle Payload Bay Door Radiator

The Orbiter radiator system consists of eight individual 4.6 m x 3.2 m panels located with four on each payload bay door. Forward panels #1 and #2 are 2.3 cm thick while the aft panels #3 and #4 have a smaller overall thickness of 1.3 cm. The honeycomb radiator panels consist of 0.028 cm thick Aluminum 2024-T81 facesheets and Al5056-H39 cores. The face-sheets are topped with 0.005 in. (0.127 mm) silver-Teflon tape. The radiators are located on the inside of the shuttle payload bay doors, which are closed during ascent and reentry, limiting damage to the on-orbit portion of the mission. Post-flight inspections at the Kennedy Space Center (KSC) following the STS-115 mission revealed a large micrometeoroid/orbital debris (MMOD) impact near the hinge line on the #4 starboard payload bay door radiator panel. The features of this impact make it the largest ever recorded on an orbiter payload bay door radiator. The general location of the damage site and the adjacent radiator panels can be seen in Figure 2. Initial measurements of the defect indicated that the hole in the facesheet was 0.108 in. (2.74 mm) in diameter. Figure 3 shows an image of the front side damage. Subsequent observations revealed exit damage on the rear facesheet. Impact damage features on the rear facesheet included a 0.03 in. diameter hole (0.76 mm), a approx.0.05 in. tall bulge (approx.1.3 mm), and a larger approx.0.2 in. tall bulge (approx.5.1 mm) that exhibited a crack over 0.27 in. (6.8 mm) long. A large approx.1 in. (25 mm) diameter region of the honeycomb core was also damaged. Refer to Figure 4 for an image of the backside damage to the panel. No damage was found on thermal blankets or payload bay door structure under the radiator panel. Figure 5 shows the front facesheet with the thermal tape removed. Ultrasound examination indicated a maximum facesheet debond extent of approximately 1 in. (25 mm) from the entry hole. X-ray examinations revealed damage to an estimated 31 honeycomb cells with an extent of 0.85 in. x 1.1 in. (21.6 x 27.9 mm). Pieces of the radiator at and surrounding the impact site were recovered during the repair procedures at KSC. They included the thermal tape, front facesheet, honeycomb core, and rear facesheet. These articles were examined at JSC using a scanning electron microscope (SEM) with an energy dispersive x-ray spectrometer (EDS). Figure 6 shows SEM images of the entry hole in the facesheet. The asymmetric height of the lip may be attributed to projectile shape and impact angle. Numerous instances of a glass-fiber organic matrix composite were observed in the facesheet tape sample. The fibers were approximately 10 micrometers in diameter and variable lengths. EDS analysis indicated a composition of Mg, Ca, Al, Si, and O. Figures 7 and 8 present images of the fiber bundles, which were believed to be circuit board material based on similarity in fiber diameter, orientation, consistency, and composition. A test program was initiated in an attempt to simulate the observed damage to the radiator facesheet and honeycomb. Twelve test shots were performed using projectiles cut from a 1.6 mm thick fiberglass circuit board substrate panel. Results from test HITF07017, shown in figures 9 and 10, correlates with the observed impact features reasonably well. The test was performed at 4.14 km/sec with an impact angle of 45 degrees using a cylindrical projectile with a diameter and length of 1.25 mm. The fiberglass circuit board material had a density of 1.65 g/cu cm, giving a projectile mass of 2.53 mg. An analysis was performed using the Bumper code to estimate the probability of impact to the shuttle from a 1.25 mm diameter particle. Table 1 shows a 1.6% chance (impact odds = 1 in 62) of a 1.25 mm or larger MMOD impact on the radiators of the vehicle during a typical ISS mission. There is a 0.4% chance (impact odds = 1 in 260) that a 1.25 mm or larger MMOD particle would impact the RCC wing leading edge and nose cap during a typical miion. Figure 11 illustrates the vulnerable areas of the wing leading edge reinforced carbon-carbon (RCC), an area of the vehicle that is very sensitive to impact damage. The highlighted red, orange, yellow, and light green areas would be expected to experience critical damage if impacted by an OD particle such as the one that hit the RH4 radiator panel on STS-115.

Hyde, J.↗
NASA NTRS2007

Directed Design of Experiments (DOE) for Determining Probability of Detection (POD) Capability of NDE Systems (DOEPOD)

This viewgraph presentation reviews some of the issues that people who specialize in Non destructive evaluation (NDE) have with determining the statistics of the probability of detection. There is discussion of the use of the binominal distribution, and the probability of hit. The presentation then reviews the concepts of Directed Design of Experiments for Validating Probability of Detection of Inspection Systems (DOEPOD). Several cases are reviewed, and discussed. The concept of false calls is also reviewed.

Generazio, Ed↗
NASA NTRS2008

The Chesapeake Bay Impact Crater: An Educational Investigation for Students into the Planetary Impact Process and its Environmental Consequences

Planetary impact craters are a common surface feature of many planetary bodies, including the Earth, the Moon, Mars, Mercury, Venus, and Jupiter s moons, Ganymede and Callisto. The NASA Langley Research Center in Hampton, VA, is located about 5 km inside the outer rim of the Chesapeake Bay Impact Crater. The Chesapeake Bay Impact Crater, with a diameter of 85 km is the sixth largest impact crater on our planet. The U.S. Geological Survey (USGS), in collaboration with the NASA Langley Research Center, the Virginia Department of Environmental Quality (VDEQ), the Hampton Roads Planning District Commission (HRPDC), and the Department of Geology of the College of William and Mary (WM) drilled into and through the crater at the NASA Langley Research Center and obtained a continuous core to a depth of 2075.9 ft (632.73 meters) from the Chesapeake Bay Impact Crater. At the NASA Langley location, the granite basement depth was at 2046 ft (623.87 meters). This collaborative drilling activity provided a unique educational opportunity and ongoing educational partnership between USGS, NASA Langley and the other collaborators. NASA Langley has a decade-long, ongoing educational partnership with the Colonial Coast Council of the Girl Scouts. The core drilling and on site analysis and cataloguing of the core segments provided a unique opportunity for the Girl Scouts to learn how geologists work in the field, their tools for scientific investigation and evaluation, how they perform geological analyses of the cores in an on-site tent and learn about the formation of impact craters and the impact of impacting bodies on the sub-surface, the surface, the oceans and atmosphere of the target body. This was accomplished with a two-part activity. Girl Scout day camps and local Girl Scout troops were invited to Langley Research Center Conference Center, where more than 300 Girl Scouts, their leaders and adult personnel were given briefings by scientists and educators from the USGS, NASA, VDEQ, HRPDC and WM on the principles of geology, the formation of impact craters, the consequences of the impacting body on the atmosphere, ocean, surface and sub-surface, the geological, chemical and biological analyses of the core and the cataloguing and storage of the core segments, etc. After the briefings, the Girl Scouts visited the drilling site where they inspected the core drilling rig, examined the core samples and discussed the drilling procedures, cores and interpretation of the cores with scientists and educators from the organizations conducting the core drilling. Demonstrations at the drilling site included demonstrations of impacting objects hitting multi-colored layered mud targets at different angles of entry. The multi-colored layers of mud were instructive in mapping out the distribution of impact-ejected material around the impact crater. The presentation will include a series of photographs of the Girl Scout participating in activities at the Chesapeake Bay Impact Crater drill site, including retrieving cores from the drilling rig, inspecting the core samples and participating in the impact-crater formation demonstrations.

Levine, Arlene S.↗
NASA NTRS2006

Adaptive Changes In Postural Equilibrium And Motion Sickness Following Repeated Exposures To Virtual Environments

Virtual environments offer unique training opportunities, particularly for training astronauts and preadapting them to the novel sensory conditions of microgravity. Two unresolved human factors issues in virtual reality (VR) systems are: 1) potential "cybersickness", 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. Changes in the environmental sensory stimulus conditions and the way we interact with the new stimuli may result in motion sickness, and perceptual, spatial orientation and sensorimotor disturbances. Initial interpretation of novel sensory information may be inappropriate and result in perceptual errors. Active exploratory behavior in a new environment, with resulting feedback and the formation of new associations between sensory inputs and response outputs, promotes appropriate perception and motor control in the new environment. Thus, people adapt to consistent, sustained alterations of sensory input such as those produced by microgravity, unilateral labyrinthectomy and experimentally produced stimulus rearrangements. 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, and to examine the effects of exposure duration, and repeated exposures to VR systems. Forty-one subjects (21 men, 20 women) participated in the study with an age range of 21-49 years old. One training session was completed in order to achieve stable performance on the posture and VR tasks before participating in the experimental sessions. Three experimental sessions were performed each separated by one day. The subjects performed a navigation and pick and place task in either a dome or head-mounted display (HMD) VR system for either 30 or 60 min. The environment was a square room with 15 pedestals on two opposite walls. The objects appeared on one set of pedestals and the subject s objective was to move the objects to the other set of pedestals. After the subject picked up an object, a pathway appeared and they were required to follow the pathway to the other side of the room. The subject was instructed to perform the task as quickly and accurately as possible, avoiding hitting walls and other any obstacles and placing the object on the center of the pedestal. Postural equilibrium was measured (using the Equitest CDP balance system, Neurocom, International) before, immediately after, and at 1 hr, 2 hr, 4 hr and 6 hr following exposure to VR. Postural equilibrium was measured during quiet stance with eyes open, eyes closed and vision and/or ankle proprioceptive inputs selectively altered by servo-controlling the visual surround and/or support surface to the subject s center of mass sway. Posture data was normalized using a log transformation and motion sickness data were normalized using the square root. In general, we found that exposure to VR resulted in decrements in postural stability. The largest decrements were observed in the tests performed immediately following exposure to VR and showed a fairly rapid recovery across the remaining test sessions. In addition, subjects generally showed improvement across days. We found significant main effects for day and time for the composite equilibrium score and for sensory organization tests (SOT) 1, 2 and 6. Significant main effects were observed for day for SOT 3 and 5. Although we found no significant main effects for gender (when center of gravity was used as a covariate), we did observe significant gender X time interaction effects for composite equilibrium and for SOT 1, 3, 4 and 5. Women appeared to show larger decrements in postural stability immediately after exposure to VR than men, but recover more quickly than n. Finally, we found no significant main effects for type of VR device or for exposure duration, however, these factors did interact with other factors during some of the SOTs. Subjects exhibited rapid recovery of motion sickness symptoms across time following exposure to VR and significantly less severe symptoms across days. We did not observe main effects for gender, type of device or duration of exposure. Individuals recovered from the detrimental effects of exposure to virtual reality on postural control and motion sickness 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 support the idea that preflight training of astronauts may serve as useful countermeasure for the sensorimotor effects of space flight.

Harm, D. L.↗
NASA NTRS2006

Small Body GN&C Research Report: A G-Guidance Enhancement to Increase Mission Functionality

G-Guidance is a robust G&C (guidance and control) algorithm developed under the small-body GN&C task. The G-Guidance scheme utilizes a model predictive control approach, along with a convexification of the governing dynamics, control constraints, and trajectory/state constraints. This report details an enhancement to the FY2005 G-Guidance algorithm; the addition of a fire-second approach helps to nullify velocity errors and hit desired final velocities much more precisely than the original Fire-first scheme developed in FY2005. The enhancement preserves the primary benefit of the algorithm, which is to ensure required thruster silent times during trajectory maneuvers. The fire-second scheme increases the versatility of the algorithm for missions employing G-Guidance. For instance, a landing sequence could employ the fire-second scheme to ensure a null final velocity at landing, whereas an ascent sequence could utilize a fire-first scheme to ensure there is no drift of the spacecraft toward the ground at the beginning of the maneuver. Examples are provided within to demonstrate a fire-first versus fire-second guidance scheme. As in the existing G-Guidance algorithm, the examples and schemes incorporate gravity models and thruster firing times into discrete dynamics that are solved as a optimal control problem to minimize fuel consumption or thruster energy expenditure.

velocity errors↗
NASA NTRS2008

Statistical Issues for Uncontrolled Reentry Hazards

A number of statistical tools have been developed over the years for assessing the risk of reentering objects to human populations. These tools make use of the characteristics (e.g., mass, shape, size) of debris that are predicted by aerothermal models to survive reentry. The statistical tools use this information to compute the probability that one or more of the surviving debris might hit a person on the ground and cause one or more casualties. The statistical portion of the analysis relies on a number of assumptions about how the debris footprint and the human population are distributed in latitude and longitude, and how to use that information to arrive at realistic risk numbers. This inevitably involves assumptions that simplify the problem and make it tractable, but it is often difficult to test the accuracy and applicability of these assumptions. This paper looks at a number of these theoretical assumptions, examining the mathematical basis for the hazard calculations, and outlining the conditions under which the simplifying assumptions hold. In addition, this paper will also outline some new tools for assessing ground hazard risk in useful ways. Also, this study is able to make use of a database of known uncontrolled reentry locations measured by the United States Department of Defense. By using data from objects that were in orbit more than 30 days before reentry, sufficient time is allowed for the orbital parameters to be randomized in the way the models are designed to compute. The predicted ground footprint distributions of these objects are based on the theory that their orbits behave basically like simple Kepler orbits. However, there are a number of factors - including the effects of gravitational harmonics, the effects of the Earth's equatorial bulge on the atmosphere, and the rotation of the Earth and atmosphere - that could cause them to diverge from simple Kepler orbit behavior and change the ground footprints. The measured latitude and longitude distributions of these objects provide data that can be directly compared with the predicted distributions, providing a fundamental empirical test of the model assumptions.

Matney, Mark↗
NASA NTRS2008

Photorefraction Screens Millions for Vision Disorders

Who would have thought that stargazing in the 1980s would lead to hundreds of thousands of schoolchildren seeing more clearly today? Collaborating with research ophthalmologists and optometrists, Marshall Space Flight Center scientists Joe Kerr and the late John Richardson adapted optics technology for eye screening methods using a process called photorefraction. Photorefraction consists of delivering a light beam into the eyes where it bends in the ocular media, hits the retina, and then reflects as an image back to a camera. A series of refinements and formal clinical studies followed their highly successful initial tests in the 1980s. Evaluating over 5,000 subjects in field tests, Kerr and Richardson used a camera system prototype with a specifically angled telephoto lens and flash to photograph a subject s eye. They then analyzed the image, the cornea and pupil in particular, for irregular reflective patterns. Early tests of the system with 1,657 Alabama children revealed that, while only 111 failed the traditional chart test, Kerr and Richardson s screening system found 507 abnormalities.

Source record↗
NASA NTRS2009

High-Performance Algorithm for Solving the Diagnosis Problem

An improved method of model-based diagnosis of a complex engineering system is embodied in an algorithm that involves considerably less computation than do prior such algorithms. This method and algorithm are based largely on developments reported in several NASA Tech Briefs articles: The Complexity of the Diagnosis Problem (NPO-30315), Vol. 26, No. 4 (April 2002), page 20; Fast Algorithms for Model-Based Diagnosis (NPO-30582), Vol. 29, No. 3 (March 2005), page 69; Two Methods of Efficient Solution of the Hitting-Set Problem (NPO-30584), Vol. 29, No. 3 (March 2005), page 73; and Efficient Model-Based Diagnosis Engine (NPO-40544), on the following page. Some background information from the cited articles is prerequisite to a meaningful summary of the innovative aspects of the present method and algorithm. In model-based diagnosis, the function of each component and the relationships among all the components of the engineering system to be diagnosed are represented as a logical system denoted the system description (SD). Hence, the expected normal behavior of the engineering system is the set of logical consequences of the SD. Faulty components lead to inconsistencies between the observed behaviors of the system and the SD. Diagnosis the task of finding faulty components is reduced to finding those components, the abnormalities of which could explain all the inconsistencies. The solution of the diagnosis problem should be a minimal diagnosis, which is a minimal set of faulty components. The calculation of a minimal diagnosis is inherently a hard problem, the solution of which requires amounts of computation time and memory that increase exponentially with the number of components of the engineering system. Among the developments to reduce the computational burden, as reported in the cited articles, is the mapping of the diagnosis problem onto the integer-programming (IP) problem. This mapping makes it possible to utilize a variety of algorithms developed previously for IP to solve the diagnosis problem. In the IP approach, the diagnosis problem can be formulated as a linear integer optimization problem, which can be solved by use of well-developed integer-programming algorithms. This concludes the background information.

Fijany, Amir↗
NASA NTRS2009

Processing and Probability Analysis of Pulsed Terahertz NDE of Corrosion under Shuttle Tile Data

This paper examines data processing and probability analysis of pulsed terahertz NDE scans of corrosion defects under a Shuttle tile. Pulsed terahertz data collected from an aluminum plate with fabricated corrosion defects and covered with a Shuttle tile is presented. The corrosion defects imaged were fabricated by electrochemically etching areas of various diameter and depth in the plate. In this work, the aluminum plate echo signal is located in the terahertz time-of-flight data and a threshold is applied to produce a binary image of sample features. Feature location and area are examined and identified as corrosion through comparison with the known defect layout. The results are tabulated with hit, miss, or false call information for a probability of detection analysis that is used to identify an optimal processing threshold.

Anastasi, Robert F.↗
NASA NTRS2008

Contamination Sources Effects Analysis (CSEA) - A Tool to Balance Cost/Schedule While Managing Facility Availability

A CSEA is similar to a Failure Modes Effects Analysis (FMEA). A CSEA tracks risk, deterrence, and occurrence of sources of contamination and their mitigation plans. Documentation is provided spanning mechanical and electrical assembly, precision cleaning, thermal vacuum bake-out, and thermal vacuum testing. These facilities all may play a role in contamination budgeting and reduction ultimately affecting test and flight. With a CSEA, visibility can be given to availability of these facilities, test sequencing and trade-offs. A cross-functional team including specialty engineering, contamination control, electrostatic dissipation, manufacturing, testing, and material engineering participate in an exercise that identifies contaminants and minimizes the complexity of scheduling these facilities considering their volatile schedules. Care can be taken in an efficient manner to insure correct cleaning processes are employed. The result is reduction in cycle time ("schedule hits"), reduced cost due to rework, reduced risk and improved communication and quality while achieving adherence to the Contamination Control Plan.

Wilcox, Margaret↗
NASA NTRS2008

Novel Ice Mitigation Methods

After the loss of Columbia, there was great concern in the Space Shuttle program for the impact of debris against the leading edges of the Orbiter wings. It was quickly recognized that, in addition to impacts by foam, ice that formed on the liquid-oxygen bellows running down the outside of the External Tank could break free during launch and hit this sensitive area. A Center Director s Discretionary Fund (CDDF) project would concentrate on novel ideas that were potentially applicable. The most successful of the new concepts for ice mitigation involved shape memory alloy materials. These materials can be bent into a given shape and, when heated, will return to their original shape.

Source record↗
NASA NTRS2009

Implementation of an Adaptive Controller System from Concept to Flight Test

The National Aeronautics and Space Administration (NASA) at the Dryden Flight Research Center (DFRC) has been conducting flight-test research using an F-15 aircraft (figure 1). This aircraft has been specially modified to interface a neural net (NN) controller as part of a single-string Airborne Research Test System (ARTS) computer with the existing quad-redundant flight control system (FCC) shown in figure 2. The NN commands are passed to FCC channels 2 and 4 and are cross channel data linked (CCDL) to the other computers as shown. Numerous types of fault-detection monitors exist in the FCC when the NN mode is engaged; these monitors would cause an automatic disengagement of the NN in the event of a triggering fault. Unfortunately, these monitors still may not prevent a possible NN hard-over command from coming through to the control laws. Therefore, an additional and unique safety monitor was designed for a single-string source that allows authority at maximum actuator rates but protects the pilot and structural loads against excessive g-limits in the case of a NN hard-over command input. This additional monitor resides in the FCCs and is executed before the control laws are computed. This presentation describes a "floating limiter" (FL) concept that was developed and successfully test-flown for this program (figure 3). The FL computes the rate of change of the NN commands that are input to the FCC from the ARTS. A window is created with upper and lower boundaries, which is constantly "floating" and trying to stay centered as the NN command rates are changing. The limiter works by only allowing the window to move at a much slower rate than those of the NN commands. Anywhere within the window, however, full rates are allowed. If a rate persists in one direction, it will eventually "hit" the boundary and be rate-limited to the floating limiter rate. When this happens, a persistent counter begins and after a limit is reached, a NN disengage command is generated. The tunable metrics for the FL are (1) window size, (2) drift rate, and (3) persistence counter. Ultimate range limits are also included in case the NN command should drift slowly to a limit value that would cause the FL to be defeated. The FL has proven to work as intended. Both high-g transients and excessive structural loads are controlled with NN hard-over commands. This presentation discusses the FL design features and presents test cases. Simulation runs are included to illustrate the dramatic improvement made to the control of NN hard-over effects. A mission control room display from a flight playback is presented to illustrate the neural net fault display representation. The FL is very adaptable to various requirements and is independent of flight condition. It should be considered as a cost-effective safety monitor to control single-string inputs in general.

Larson, Richard R.↗
NASA NTRS2008

Directed Design of Experiments for Validating Probability of Detection Capability of NDE Systems (DOEPOD)

The capability of an inspection system is established by applications of various methodologies to determine the probability of detection (POD). One accepted metric of an adequate inspection system is that there is 95% confidence that the POD is greater than 90% (90/95 POD). Directed design of experiments for probability of detection (DOEPOD) has been developed to provide an efficient and accurate methodology that yields observed POD and confidence bounds for both Hit- Miss or signal amplitude testing. Specifically, DOEPOD demands utilization of observance of occurrences. Directed DOEPOD does not assume prescribed POD logarithmic or similar functions with assumed adequacy over a wide range of flaw sizes and inspection system technologies, so that multi-parameter curve fitting or model optimization approaches to generate a POD curve are not required.

Generazio, Edward R.↗
NASA NTRS2009

Self-Supervised Learning of Terrain Traversability from Proprioceptive Sensors

Robust and reliable autonomous navigation in unstructured, off-road terrain is a critical element in making unmanned ground vehicles a reality. Existing approaches tend to rely on evaluating the traversability of terrain based on fixed parameters obtained via testing in specific environments. This results in a system that handles the terrain well that it trained in, but is unable to process terrain outside its test parameters. An adaptive system does not take the place of training, but supplements it. Whereas training imprints certain environments, an adaptive system would imprint terrain elements and the interactions amongst them, and allow the vehicle to build a map of local elements using proprioceptive sensors. Such sensors can include velocity, wheel slippage, bumper hits, and accelerometers. Data obtained by the sensors can be compared to observations from ranging sensors such as cameras and LADAR (laser detection and ranging) in order to adapt to any kind of terrain. In this way, it could sample its surroundings not only to create a map of clear space, but also of what kind of space it is and its composition. By having a set of building blocks consisting of terrain features, a vehicle can adapt to terrain that it has never seen before, and thus be robust to a changing environment. New observations could be added to its library, enabling it to infer terrain types that it wasn't trained on. This would be very useful in alien environments, where many of the physical features are known, but some are not. For example, a seemingly flat, hard plain could actually be soft sand, and the vehicle would sense the sand and avoid it automatically.

Bajracharya, Max↗
NASA NTRS2009

Predicting Pilot Performance in Off-Nominal Conditions: A Meta-Analysis and Model Validation

Pilot response to off-nominal (very rare) events represents a critical component to understanding the safety of next generation airspace technology and procedures. We describe a meta-analysis designed to integrate the existing data regarding pilot accuracy of detecting rare, unexpected events such as runway incursions in realistic flight simulations. Thirty-five studies were identified and pilot responses were categorized by expectancy, event location, and whether the pilot was flying with a highway-in-the-sky display. All three dichotomies produced large, significant effects on event miss rate. A model of human attention and noticing, N-SEEV, was then used to predict event noticing performance as a function of event salience and expectancy, and retinal eccentricity. Eccentricity is predicted from steady state scanning by the SEEV model of attention allocation. The model was used to predict miss rates for the expectancy, location and highway-in-the-sky (HITS) effects identified in the meta-analysis. The correlation between model-predicted results and data from the meta-analysis was 0.72.

Wickens, C.D.↗