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NASA NTRS1997

System identification of closed-loop cardiovascular control: effects of posture and autonomic blockade

We applied system identification to the analysis of fluctuations in heart rate (HR), arterial blood pressure (ABP), and instantaneous lung volume (ILV) to characterize quantitatively the physiological mechanisms responsible for the couplings between these variables. We characterized two autonomically mediated coupling mechanisms [the heart rate baroreflex (HR baroreflex) and respiratory sinus arrhythmia (ILV-HR)] and two mechanically mediated coupling mechanisms [the blood pressure wavelet generated with each cardiac contraction (circulatory mechanics) and the direct mechanical effects of respiration on blood pressure (ILV-->ABP)]. We evaluated the method in humans studied in the supine and standing postures under control conditions and under conditions of beta-sympathetic and parasympathetic pharmacological blockades. Combined beta-sympathetic and parasympathetic blockade abolished the autonomically mediated couplings while preserving the mechanically mediated coupling. Selective autonomic blockade and postural changes also altered the couplings in a manner consistent with known physiological mechanisms. System identification is an "inverse-modeling" technique that provides a means for creating a closed-loop model of cardiovascular regulation for an individual subject without altering the underlying physiological control mechanisms.

NASA Discipline Number 18-10↗

NASA NTRS1996

Evaluation of the Biolog MicroStation system for yeast identification

One hundred and fifty-nine isolates representing 16 genera and 53 species of yeasts were processed with the Biolog MicroStation System for yeast identification. Thirteen genera and 38 species were included in the Biolog database. For these 129 isolates, correct identifications to the species level were 13.2, 39.5 and 48.8% after 24, 48 and 72 hours incubation at 30 degrees C, respectively. Three genera and 15 species which were not included in the Biolog database were also tested. Of the 30 isolates studied, 16.7, 53.3 and 56.7% of the isolates were given incorrect names from the system's database after 24,48 and 72 h incubation at 30 degrees C, respectively. The remaining isolates of this group were not identified.

NASA Program Environmental Health↗

NASA NTRS2005

Model Structures and Algorithms for Identification of Aerodynamic Models for Flight Dynamics Applications

This paper describes model structures and parameter estimation algorithms suitable for the identification of unsteady aerodynamic models from input-output data. The model structures presented are state space models and include linear time-invariant (LTI) models and linear parameter-varying (LPV) models. They cover a wide range of local and parameter dependent identification problems arising in unsteady aerodynamics and nonlinear flight dynamics. We present a residue algorithm for estimating model parameters from data. The algorithm can incorporate apriori information and is described in detail. The algorithms are evaluated on the F-16XL wind-tunnel test data from NAS Langley Research Center. Results of numerical evaluation are presented. The paper concludes with a discussion major issues and directions for future work.

Prasanth, Ravi K.↗

NASA NTRS2006

NASA Technologies for Product Identification

Since 1975 bar codes on products at the retail counter have been accepted as the standard for entering product identity for price determination. Since the beginning of the 21st century, the Data Matrix symbol has become accepted as the bar code format that is marked directly on a part, assembly or product that is durable enough to identify that item for its lifetime. NASA began the studies for direct part marking Data Matrix symbols on parts during the Return to Flight activities after the Challenger Accident. Over the 20 year period that has elapsed since Challenger, a mountain of studies, analyses and focused problem solutions developed by and for NASA have brought about world changing results. NASA Technical Standard 6002 and NASA Handbook 6003 for Direct Part Marking Data Matrix Symbols on Aerospace Parts have formed the basis for most other standards on part marking internationally. NASA and its commercial partners have developed numerous products and methods that addressed the difficulties of collecting part identification in aerospace operations. These products enabled the marking of Data Matrix symbols in virtually every situation and the reading of symbols at great distances, severe angles, under paint and in the dark without a light. Even unmarkable delicate parts now have a process to apply a chemical mixture called NanocodesTM that can be converted to a Data Matrix. The accompanying intellectual property is protected by 10 patents, several of which are licensed. Direct marking Data Matrix on NASA parts virtually eliminates data entry errors and the number of parts that go through their life cycle unmarked, two major threats to sound configuration management and flight safety. NASA is said to only have people and stuff with information connecting them. Data Matrix is one of the most significant improvements since Challenger to the safety and reliability of that connection. This presentation highlights the accomplishments of NASA in its efforts to develop technologies for automatic identification, its efforts to implement them and its vision on their role in space.

Schramm, Fred, Jr.↗

NASA NTRS2008

Part Marking and Identification Materials on MISSE

Many different spacecraft materials were flown as part of the Materials on International Space Station Experiment (MISSE), including several materials used in part marking and identification. The experiment contained Data Matrix symbols applied using laser bonding, vacuum arc vapor deposition, gas assisted laser etch, chemical etch, mechanical dot peening, laser shot peening, and laser induced surface improvement. The effects of ultraviolet radiation on nickel acetate seal versus hot water seal on sulfuric acid anodized aluminum are discussed. These samples were exposed on the International Space Station to the low Earth orbital environment of atomic oxygen, ultraviolet radiation, thermal cycling, and hard vacuum, though atomic oxygen exposure was very limited for some samples. Results from the one-year exposure on MISSE-3 and MISSE-4 are compared to those from MISSE-1 and MISSE-2, which were exposed for four years. Part marking and identification materials on the current MISSE -6 experiment are also discussed.

Finckenor, Miria M.↗

NASA NTRS2009

Detection, Identification, Location, and Remote Sensing using SAW RFID Sensor Tags

In this presentation, we will consider the problem of simultaneous detection, identification, location estimation, and remote sensing for multiple objects. In particular, we will describe the design and testing of a wireless system capable of simultaneously detecting the presence of multiple objects, identifying each object, and acquiring both a low-resolution estimate of location and a high-resolution estimate of temperature for each object based on wireless interrogation of passive surface acoustic wave (SAW) radiofrequency identification (RFID) sensor tags affixed to each object. The system is being studied for application on the lunar surface as well as for terrestrial remote sensing applications such as pre-launch monitoring and testing of spacecraft on the launch pad and monitoring of test facilities. The system utilizes a digitally beam-formed planar receiving antenna array to extend range and provide direction-of-arrival information coupled with an approximate maximum-likelihood signal processing algorithm to provide near-optimal estimation of both range and temperature. The system is capable of forming a large number of beams within the field of view and resolving the information from several tags within each beam. The combination of both spatial and waveform discrimination provides the capability to track and monitor telemetry from a large number of objects appearing simultaneously within the field of view of the receiving array. In the presentation, we will summarize the system design and illustrate several aspects of the operational characteristics and signal structure. We will examine the theoretical performance characteristics of the system and compare the theoretical results with results obtained from experiments in both controlled laboratory environments and in the field.

Barton, Richard J.↗

NASA NTRS2009

Dynamic Structural Fault Detection and Identification

Aircraft structures are designed to guarantee safety of flight in some required operational envelope. When the aircraft becomes structurally impaired, safety of flight may not be guaranteed within that previously safe operational envelope. In this case the safe operational envelope must be redefined in-flight and a means to prevent excursion from this new envelope must be implemented. A specific structural failure mode that may result in a reduced safe operating envelope, the exceedance of which could lead to catastrophic structural failure of the aircraft, will be addressed. The goal of the DFEAP program is the detection of this failure mode coupled with flight controls adaptation to limit critical loads in the damaged aircraft structure. The DFEAP program is working with an F/A-18 aircraft model. The composite wing skins are bonded to metallic spars in the wing substructure. Over time, it is possible that this bonding can deteriorate due to fatigue. In this case, the ability of the wing spar to transfer loading between the wing skins is reduced. This failure mode can translate to a reduced allowable compressive strain on the wing skin and could lead to catastrophic wing buckling if load limiting of the wing structure is not applied. The DFEAP program will make use of a simplified wing strain model for the healthy aircraft. The outputs of this model will be compared in real-time to onboard strain measurements at several locations on the aircraft wing. A damage condition is declared at a given location when the strain measurements differ sufficiently from the strain model. Parameter identification of the damaged structure wing strain parameters will be employed to provide load limiting control adaptation for the aircraft. This paper will discuss the simplified strain models used in the implementation and their interaction with the strain sensor measurements. Also discussed will be the damage detection and identification schemes employed and the means by which the damaged aircraft parameters will be used to provide load limiting that keeps the aircraft within the safe operational envelope.

Smith, Timothy↗

NASA NTRS2010

Crater Identification Algorithm for the Lost in Low Lunar Orbit Scenario

Recent emphasis by NASA on returning astronauts to the Moon has placed attention on the subject of lunar surface feature tracking. Although many algorithms have been proposed for lunar surface feature tracking navigation, much less attention has been paid to the issue of navigational state initialization from lunar craters in a lost in low lunar orbit (LLO) scenario. That is, a scenario in which lunar surface feature tracking must begin, but current navigation state knowledge is either unavailable or too poor to initiate a tracking algorithm. The situation is analogous to the lost in space scenario for star trackers. A new crater identification algorithm is developed herein that allows for navigation state initialization from as few as one image of the lunar surface with no a priori state knowledge. The algorithm takes as inputs the locations and diameters of craters that have been detected in an image, and uses the information to match the craters to entries in the USGS lunar crater catalog via non-dimensional crater triangle parameters. Due to the large number of uncataloged craters that exist on the lunar surface, a probability-based check was developed to reject false identifications. The algorithm was tested on craters detected in four revolutions of Apollo 16 LLO images, and shown to perform well.

Hanak, Chad↗

NASA NTRS2011

Identification of Impact Craters in Foils from the Stardust Interstellar Dust Collector

The Stardust Interstellar Dust Collection tray provides the first opportunity for the direct laboratory-based measurement of contemporary interstellar dust. The total exposed surface of the tray was approximately 0.1 square meters, including 153 square centimeters of Al foil in addition to the silica aerogel tiles that are the primary collection medium. Preliminary examination of aerogel tiles has already revealed 16 tracks from particle impacts with an orientation consistent with an interstellar origin, and to date four of the particles associated with these tracks have a composition consistent with an extraterrestrial origin. Tentative identification of impact craters on three foil samples was also reported previously. Here we present the definitive identification of 20 impact craters on five foils.

Stroud, R. M.↗

NASA NTRS2011

DCS: A Case Study of Identification of Knowledge and Disposition Gaps Using Principles of Continuous Risk Management

The Human Research Program (HRP) is formulated around the program architecture of Evidence-Risk-Gap-Task-Deliverable. Review of accumulated evidence forms the basis for identification of high priority risks to human health and performance in space exploration. Gaps in knowledge or disposition are identified for each risk, and a portfolio of research tasks is developed to fill them. Deliverables from the tasks inform the evidence base with the ultimate goal of defining the level of risk and reducing it to an acceptable level. A comprehensive framework for gap identification, focus, and metrics has been developed based on principles of continuous risk management and clinical care. Research towards knowledge gaps improves understanding of the likelihood, consequence or timeframe of the risk. Disposition gaps include development of standards or requirements for risk acceptance, development of countermeasures or technology to mitigate the risk, and yearly technology assessment related to watching developments related to the risk. Standard concepts from clinical care: prevention, diagnosis, treatment, monitoring, rehabilitation, and surveillance, can be used to focus gaps dealing with risk mitigation. The research plan for the new HRP Risk of Decompression Sickness (DCS) used the framework to identify one disposition gap related to establishment of a DCS standard for acceptable risk, two knowledge gaps related to DCS phenomenon and mission attributes, and three mitigation gaps focused on prediction, prevention, and new technology watch. These gaps were organized in this manner primarily based on target for closure and ease of organizing interim metrics so that gap status could be quantified. Additional considerations for the knowledge gaps were that one was highly design reference mission specific and the other gap was focused on DCS phenomenon.

Norcross, Jason↗

NASA NTRS2011

Performance Evaluation and Parameter Identification on DROID III

The DROID III project consisted of two main parts. The former, performance evaluation, focused on the performance characteristics of the aircraft such as lift to drag ratio, thrust required for level flight, and rate of climb. The latter, parameter identification, focused on finding the aerodynamic coefficients for the aircraft using a system that creates a mathematical model to match the flight data of doublet maneuvers and the aircraft s response. Both portions of the project called for flight testing and that data is now available on account of this project. The conclusion of the project is that the performance evaluation data is well-within desired standards but could be improved with a thrust model, and that parameter identification is still in need of more data processing but seems to produce reasonable results thus far.

Plumb, Julianna J.↗

NASA NTRS2012

Intelligent Systems Approach for Automated Identification of Individual Control Behavior of a Human Operator

Results have been obtained using conventional techniques to model the generic human operator?s control behavior, however little research has been done to identify an individual based on control behavior. The hypothesis investigated is that different operators exhibit different control behavior when performing a given control task. Two enhancements to existing human operator models, which allow personalization of the modeled control behavior, are presented. One enhancement accounts for the testing control signals, which are introduced by an operator for more accurate control of the system and/or to adjust the control strategy. This uses the Artificial Neural Network which can be fine-tuned to model the testing control. Another enhancement takes the form of an equiripple filter which conditions the control system power spectrum. A novel automated parameter identification technique was developed to facilitate the identification process of the parameters of the selected models. This utilizes a Genetic Algorithm based optimization engine called the Bit-Climbing Algorithm. Enhancements were validated using experimental data obtained from three different sources: the Manual Control Laboratory software experiments, Unmanned Aerial Vehicle simulation, and NASA Langley Research Center Visual Motion Simulator studies. This manuscript also addresses applying human operator models to evaluate the effectiveness of motion feedback when simulating actual pilot control behavior in a flight simulator.

Zaychik, Kirill B.↗

NASA NTRS2012

Systems and methods for remote long standoff biometric identification using microwave cardiac signals

Systems and methods for remote, long standoff biometric identification using microwave cardiac signals are provided. In one embodiment, the invention relates to a method for remote biometric identification using microwave cardiac signals, the method including generating and directing first microwave energy in a direction of a person, receiving microwave energy reflected from the person, the reflected microwave energy indicative of cardiac characteristics of the person, segmenting a signal indicative of the reflected microwave energy into a waveform including a plurality of heart beats, identifying patterns in the microwave heart beats waveform, and identifying the person based on the identified patterns and a stored microwave heart beats waveform.

McGrath, William R.↗

NASA NTRS2012

Sensor-Only System Identification for Structural Health Monitoring of Advanced Aircraft

Environmental conditions, cyclic loading, and aging contribute to structural wear and degradation, and thus potentially catastrophic events. The challenge of health monitoring technology is to determine incipient changes accurately and efficiently. This project addresses this challenge by developing health monitoring techniques that depend only on sensor measurements. Since actively controlled excitation is not needed, sensor-to-sensor identification (S2SID) provides an in-flight diagnostic tool that exploits ambient excitation to provide advance warning of significant changes. S2SID can subsequently be followed up by ground testing to localize and quantify structural changes. The conceptual foundation of S2SID is the notion of a pseudo-transfer function, where one sensor is viewed as the pseudo-input and another is viewed as the pseudo-output, is approach is less restrictive than transmissibility identification and operational modal analysis since no assumption is made about the locations of the sensors relative to the excitation.

Kukreja, Sunil L.↗

NASA NTRS2015

Development of a Near-Real Time Hail Damage Swath Identification Algorithm for Vegetation

The Midwest is home to one of the world's largest agricultural growing regions. Between the time period of late May through early September, and with irrigation and seasonal rainfall these crops are able to reach their full maturity. Using moderate to high resolution remote sensors, the monitoring of the vegetation can be achieved using the red and near-infrared wavelengths. These wavelengths allow for the calculation of vegetation indices, such as Normalized Difference Vegetation Index (NDVI). The vegetation growth and greenness, in this region, grows and evolves uniformly as the growing season progresses. However one of the biggest threats to Midwest vegetation during the time period is thunderstorms that bring large hail and damaging winds. Hail and wind damage to crops can be very expensive to crop growers and, damage can be spread over long swaths associated with the tracks of the damaging storms. Damage to the vegetation can be apparent in remotely sensed imagery and is visible from space after storms slightly damage the crops, allowing for changes to occur slowly over time as the crops wilt or more readily apparent if the storms strip material from the crops or destroy them completely. Previous work on identifying these hail damage swaths used manual interpretation by the way of moderate and higher resolution satellite imagery. With the development of an automated and near-real time hail swath damage identification algorithm, detection can be improved, and more damage indicators be created in a faster and more efficient way. The automated detection of hail damage swaths will examine short-term, large changes in the vegetation by differencing near-real time eight day NDVI composites and comparing them to post storm imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua and Visible Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi NPP. In addition land surface temperatures from these instruments will be examined as for hail damage swath identification. Initial validation of the automated algorithm is based upon Storm Prediction Center storm reports but also the National Severe Storm Laboratory (NSSL) Maximum Estimated Size Hail (MESH) product. Opportunities for future work are also shown, with focus on expansion of this algorithm with pixel-based image classification techniques for tracking surface changes as a result of severe weather.

Bell, Jordan R.↗

NASA NTRS2016

Early Engagement of Safety and Mission Assurance Expertise Using Systems Engineering Tools: A Risk-Based Approach to Early Identification of Safety and Assurance Requirements

Decades of systems engineering practice have demonstrated that the earlier the identification of requirements occurs, the lower the chance that costly redesigns will needed later in the project life cycle. A better understanding of all requirements can also improve the likelihood of a design's success. Significant effort has been put into developing tools and practices that facilitate requirements determination, including those that are part of the model-based systems engineering (MBSE) paradigm. These efforts have yielded improvements in requirements definition, but have thus far focused on a design's performance needs. The identification of safety & mission assurance (S&MA) related requirements, in comparison, can occur after preliminary designs are already established, yielding forced redesigns. Engaging S&MA expertise at an earlier stage, facilitated by the use of MBSE tools, and focused on actual project risk, can yield the same type of design life cycle improvements that have been realized in technical and performance requirements.

Requirement↗

NASA NTRS2018

Time-Varying Manual Control Identification in a Stall Recovery Task under Different Simulator Motion Conditions

This paper adds data to help develop simulator motion guidelines for stall recovery training by identifying time-varying manual control behavior in a stall recovery task under different simulator motion conditions. A study was conducted in the NASA Ames Vertical Motion Simulator, where seventeen general aviation pilots performed a stall recovery task. Pilots had to follow a flight director through four stages of the stall recovery task. A time-varying identification method was used to quantify how pilots weigh position and velocity information throughout different stages of the task, in both roll and pitch. Four motion configurations were used: no motion, generic hexapod motion, enhanced hexapod motion and full motion. Pilot performance was highest for the enhanced hexapod and full motion conditions in both roll and pitch, and the lowest for the condition with no motion. The time-varying identification method revealed that, in the roll axis, pilot position gain did not significantly change between time segments, but was the lowest for the condition with no motion. The pilot velocity gain was significantly different between motion conditions, the largest difference being found at the beginning of the stall. The enhanced hexapod motion condition had the highest pilot velocity gain. In the pitch axis, the pilot position gain was significantly different between time segments but not between motion conditions. The pitch pilot velocity gain was highest for the full motion condition and increased at the beginning of the stall, but did not change significantly for the other motion conditions. Overall, pilot control behavior under enhanced hexapod motion was more similar to that under full aircraft motion compared to standard hexapod motion. This indicates that motion cueing on hexapod simulators might be improved for stall recovery training by using the enhanced hexapod motion developed in previous experiments.

stall recovery↗

NASA NTRS2019

Cleanroom Contamination Identification Method Development

During fabrication, assembly, and testing of spacecraft and flight hardware it is vital to avoid contaminants that can cause degradation and could result in significant failure. Yet, there is no existing contamination monitoring method that provides the identity of airborne particles in a cleanroom facility. Knowing the particle identities, would allow scientists and engineers to determine the source of the contaminants and prevent setbacks before they occur or cause damage. Current cleanliness monitoring methods include airborne particle counters (APCs), fallout filters, and visual inspections. Particle counts from APCs are the primary metric used to define a cleanroom class and hence its level of cleanliness, but do not provide identification nor can they differentiate between large and small sizes of particles. In addition, using fallout filters is not a proactive, timely, or representative approach to cleanroom contamination monitoring because these samples are only retrieved after 30 days and are placed away from spacecraft processing to avoid interference with operations. In contrast, the forced air sampling method can collect a sample within an hour at any location required and provide results in less than a day. This system uses a cassette and filter sample medium to capture airborne particles which are then taken to a scanning electron microscope with energy dispersive spectroscopy (SEM/EDS) to identify and size the captured particles. Development of forced air sampling into an established laboratory capability will allow for fast sampling and routine identification of unknown contamination sources within the cleanroom. The test method development required market research for an air sampling cassette that increases sample collection efficiency and a filter with low enough background contamination to allow differentiation between a blank (control) and the collected sample. It was determined that a conductive black cassette and a polycarbonate filter were the best options. Conductive black cassettes, in comparison to the standard styrene, are manufactured using polypropylene filled with carbon. This makes the cassette conductive and minimizes the tendency of particles to stick to the wall of the cassette due to electrostatic force. In previous trials a mixed cellulose ester (MCE) filter was used to capture the contaminants, however the rougher surface of the filter contributed to entrapment of the particles within the filter structure and made it harder to identify the particles. In comparison, track etched polycarbonate filters have random cylindrical pores and a smooth surface which contributes to uniform sample distribution on the surface of the filter. Future work includes: testing the system using control samples to determine the efficiency and suitability of the medium, performing sample collection in various environments to establish ideal operating parameters and analyzing contaminant particles using SEM/EDS and assistant characterization techniques. Once fully developed, employing the forced air sampling method will help to prevent damage to spacecraft, avoid schedule delays, and allow for mission success.

Hernandez Melendez, Jailyn M.↗