Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Training Analysis”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,153 records · Page 64

Microprocessor-based cardiopulmonary monitoring system

The system uses a dedicated microprocessor for transducer control and data acquisition and analysis. No data will be stored in this system, but the data will be transmitted to the onboard data system. The data system will require approximately 12 inches of rack space and will consume only 100 watts of power. An experiment specific control panel, through a series of lighted buttons, will guide the operator through the test series providing a smaller margin of error. The experimental validity of the system was verified, and the reproducibility of data and reliability of the system checked. In addition, ease of training, ease of operator interaction, and crew acceptance were evaluated in actual flight conditions.

Source record↗

Evaluation of several schemes for classification of remotely sensed data

Various numerical analysis schemes for the classification of remotely sensed data are evaluated with respect to their capabilities for crop identification. A per point Gaussian maximum likelihood classifier, per point sum-of-normal-densities classifier, per point linear classifier, per point Gaussian maximum likelihood decision tree classifier and a texture-sensitive per field Gaussian maximum likelihood classifier were applied to seven sets of Landsat MSS data on several crop types and regions. The results of the implementation of the classifiers indicate that, given a representative set of training statistics, the choice of classification algorithm of the differentiation of corn and soybeans from one another and from other crop types made relatively little difference in accuracy, whereas the use of a different training method affected the accuracy significantly. In addition, the linear classifier is found to be the easiest for the analyst to use and to cost least in computer time per classification.

Hixson, M.↗

Measures and Interpretations of Vigilance Performance: Evidence Against the Detection Criterion

Operators' performance in a vigilance task is often assumed to depend on their choice of a detection criterion. When the signal rate is low this criterion is set high, causing the hit and false alarm rates to be low. With increasing time on task the criterion presumably tends to increase even further, thereby further decreasing the hit and false alarm rates. Virtually all of the empirical evidence for this simple interpretation is based on estimates of the bias measure Beta from signal detection theory. In this article, I describe a new approach to studying decision making that does not require the technical assumptions of signal detection theory. The results of this new analysis suggest that the detection criterion is never biased toward either response, even when the signal rate is low and the time on task is long. Two modifications of the signal detection theory framework are considered to account for this seemingly paradoxical result. The first assumes that the signal rate affects the relative sizes of the variances of the information distributions; the second assumes that the signal rate affects the logic of the operator's stopping rule. Actual or potential applications of this research include the improved training and performance assessment of operators in areas such as product quality control, air traffic control, and medical and clinical diagnosis.

Balakrishnan, J. D.↗

Polymer-carbon black composite sensors in an electronic nose for air-quality monitoring

An electronic nose that uses an array of 32 polymer-carbon black composite sensors has been developed, trained, and tested. By selecting a variety of chemical functionalities in the polymers used to make sensors, it is possible to construct an array capable of identifying and quantifying a broad range of target compounds, such as alcohols and aromatics, and distinguishing isomers and enantiomers (mirror-image isomers). A model of the interaction between target molecules and the polymer-carbon black composite sensors is under development to aid in selecting the array members and to enable identification of compounds with responses not stored in the analysis library.

NASA Discipline Life Sciences Technologies↗

Impact Ice Microstructure Segmentation Using Transfer Learned Model

A process of using machine learning to segment impact ice microstructure is presented and analyzed. The segmentation was conducted with the goal of obtaining average grain size estimations. The model was trained on a set of micrographs of impact ice grown at NASA Glenn’s Icing Research Tunnel. The model leveraged a model pre-trained on a large set of micrographs of various materials as a starting point. Post-processing of the segmented images was done to connect broken boundaries. An automatic method of determining grain size following an ASTM standard was implemented. Segmentation results using different training sets as well as different encoder and decoder pairs are presented. Calculated sizes are compared to manual grain size measurement methods. Results show promise in accuracy as well as a possible improvement in repeatability and consistency. Next steps for improving the model are suggested.

Machine learning↗

Studies of Vestibular Neurons in Normal, Hyper- and Hypogravity

During the past year, pre-, in- and postflight studies were conducted in association with the Axon project for Bion 10 (Cosmos 2229). Recordings were made during pre- and postflight studies, from 118 horizontal semicircular canal afferents and 27 vestibular nucleus neurons in 7 rhesus monkeys; 137 pulse rotation protocols alone were executed (548 acceleration and deceleration responses were curve fit). Usable data was obtained from 127 horizontal afferents concerning their spontaneous discharge. Curve fits and analysis was made of sinusoidal and sum of sinusoidal responses from 42 and 35 horizontal afferents, respectively. Also recordings were made from neurons inflight from the two flight animals. The mean spontaneous rate varied from 128 spikes/sec. during preflight to 92 spikes/sec during postflight (day 5) - a change of 28%. In direct contrast to the results of Cosmos 2044, the best fitted neural adaptation operator (k) and the gain of the pulse response were decreased during post flight when compared to preflight. Surprisingly, the best fitted gain and k values for the sum of sines were slightly elevated during post flight tests. The gain and phase of single sine responses were compared for pre- and post flight tests and compared to a larger population of afferents. In contrast to Cosmos 2044 results where on the first day of post flight testing the gains of the best fitted sine response were skewed toward the higher values of the Miles and Braitman distribution, the gain of the best fitted sine responses during the first day of post flight testing (day 2) during Cosmos 2229 were exactly on the mode of the Miles and Braitman distribution. Thus, at least for the periodic stimuli, (pulses and sine waves) we found no change in gain and neural adaptation during post flight testing following Cosmos 2229. This conclusion is different from the one derived following the Cosmos 2044 flight. Cosmos flight 2229 differed from Cosmos flight 2044 in several significant ways: For example, during preflight, (1) The animals preflight training was different (less well trained on the gaze task) and (2) the animals were exposed to more experimental manipulations (surgical and rotational). Inflight, (1) the animals were required to make a pointing gesture (motor response) in association with eye movements to obtain reward, (2) the inflight diet was different (more balanced), (3) the feeder for one of the animals clogged following 9 days of flight resulting in evident dehydration and probably less head motion exposure in that monkey and (4) there was limited video taping of the monkeys in space. During postflight, (1) we were unable to test the flight animals until 26 hours postflight as compared to 14.5 hours during Cosmos 2044, (2) the animals received significantly more exposure to motion stimuli during postflight testing than during Cosmos 2044. These differences in the vestibular environment will require analysis of several parameters other than just neural and eye movement responses. For example, computer programs will have to be written and used to recover and quantify the number of head movements made by each animal during flight. This activity is critical to the production of neural adaptation and increased gain.

Correia, Manning J.↗

Application of ERTS-1 data to analysis of agricultural crops and forests in Michigan

The results reported are based on analysis of ERTS Frame 1033-15580 collected over southwestern Lower Michigan on August 25, 1972. Major agricultural crops such as corn and soybeans were approaching maturity at this data and forest canopies were dense. Extensive ground truth information was gathered by detailed field study of test strips. This detailed information was supplemented over larger areas by interpretation of RB-57 and C-47 photography and MSS imagery. Recognition processing of ERTS-1 MSS data was carried out on a digital computer. Fields and forest stands were selected as training sets and test areas. Aerial imagery was essential for locating the positions of these selected areas on ERTS digital tapes. The recognition process was successful for each type of vegetation which had a dense green canopy such as forests, corn, and soybeans. Bare soil was also recognizable as a category.

Safir, G. R.↗

Strategic Plan

The purpose of this document is to present the strategic plan and associated organizational structure that the National Space Biomedical Research Institute (NSBRI) will utilize to achieve the defined mission and objectives provided by NASA. Much of the information regarding the background and establishment of the NSBRI by NASA has been provided in other documentation and will not be repeated in this Strategic Plan. This Strategic Plan is presented in two volumes. Volume I (this volume) begins with an Introduction (Section 2) that provides the Institute's NASA-defined mission and objectives, and the organizational structure adopted to implement these through three Strategic Programs: Countermeasure Research; Education, Training and Outreach; and Cooperative Research and Development. These programs are described in Sections 3 to 5. Each program is presented in a similar way, using four subsections: Goals and Objectives; Current Strategies; Gaps and Modifications; and Resource Requirements. Section 6 provides the administrative infrastructure and total budget required to implement the Strategic Programs and assures that they form a single cohesive plan. This plan will ensure continued success of the Institute for the next five years. Volume II of the Strategic Plan provides an in-depth analysis of the current and future strategic programs of the 12 current NSBRI teams, including their goals, objectives, mutual interactions and schedules.

Source record↗

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

The Customer Avionics Interface Development and Analysis (CAIDA) team helps to provide modeling and simulation software for the verification of the Launch Control System (LCS). With a new iteration of telemetry tools being developed, extensive work must be done to ensure features are implemented in an efficient manner. The authors worked to develop new functionalities in the telemetry tools, update documentation, and perform various tests on the CAIDA Advanced Telemetry Tool (CATT). This was accomplished with Python through built-in library frameworks. In addition, work needed to be performed to set up a training document for new engineers and interns joining the team in the future. The outcome of this internship was the completion of several new features, unit and functional tests on CATT, thorough documentation, and a developer’s guide to programming under CAIDA.

Negron-Martinez, Antonio Jose↗

Analysis of the Westland Data Set

The "Westland" set of empirical accelerometer helicopter data with seeded and labeled faults is analyzed with the aim of condition monitoring. The autoregressive (AR) coefficients from a simple linear model encapsulate a great deal of information in a relatively few measurements; and it has also been found that augmentation of these by harmonic and other parameters call improve classification significantly. Several techniques have been explored, among these restricted Coulomb energy (RCE) networks, learning vector quantization (LVQ), Gaussian mixture classifiers and decision trees. A problem with these approaches, and in common with many classification paradigms, is that augmentation of the feature dimension can degrade classification ability. Thus, we also introduce the Bayesian data reduction algorithm (BDRA), which imposes a Dirichlet prior oil training data and is thus able to quantify probability of error in all exact manner, such that features may be discarded or coarsened appropriately.

Wen, Fang↗

Operations analysis of gravity assisted rapid transit

Gravity assisted rapid transit (GART) with 6 percent grades before and after each station are compared with conventional systems in terms of energy consumption, run time, line capacity and schedule stability under abnormal circumstances. Parametric analyses of run times and energy consumption include the impact of alternate accelerating and braking levels. The capcity analysis uses a network simulation program to determine the location and severity of all signal delays. Based on results of initial simulations, the block design was revised to eliminate bottlenecks in normal operations. The systems are then compared at headways of 80 to 180 seconds. One month of incidence reports of a modern operating transit system are reviewed to determine the failures to be simulated. The impact of failures resulting in station delays (30 to 360 seconds), speed limit reduction (20 mph and 30 mph to one or more trains), vehicle performance (75 percent acceleration) are compared at scheduled headway of 90 to 180 seconds.

Source record↗

Tracking Community Building in Open Science

Open Science is enabled by a vibrant community of researchers who regularly engage with the data, from its production to its organization, curation, archiving, dissemination, analysis, and publication. This presentation will examine community building in open science. The NASA Open Science Data Repository (OSDR) makes data available to the public following the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles. OSDR takes open science further with the OS Analysis Working Groups (AWGs) that facilitate community development and promotion. The primary activity of each AWG is to establish and validate analytical processes to generate higher-order data from data housed in OSDR. There are a number of these groups on various topics, including the Animal AWG, Plant AWG, Microbial AWG, Multi-Omics AWG, AI/ML AWG, and the Ames Life Sciences Data Archive (ALSDA) AWG. The international volunteers participating in these AWGs come from academia, citizen science initiatives, industry, and government. They include researchers, principal investigators, professors, trained hobbyists, and students from various domains and disciplines. Anyone may request to join the AWGs, and membership requests are vetted monthly by the group organizers before granting admission. Core to membership is demonstrated expertise through records of training, integrity, work in the professed domain(s), and good community standing. Regular virtual meetings are held for each AWG, with a varying cadence depending on the group's needs and goals. AWG communities share their expertise in research including cutting edge tools, software, frameworks, data formats, and libraries accelerating research collectively. This collaborative approach helps community members cross technology gaps and identify emerging challenges. These diverse communities encompass a wide range of individuals hailing from various sectors within the Science Mission Directorate and beyond. They serve as a means to promote and enhance transparency, accessibility, and inclusion. An annual AWG Symposium brings contributors together in person. Participation in AWGs can be synchronous or asynchronous, with some groups performing most of their work in off hours. Participants gain valuable skills and connections that allow them to add value to their communities and new organizations that they join, resulting in an expanded return on investment for the space life science community. Open science is increasingly a federal mandate and initiatives like NASA's Transform to Open Science and instruments like the Decadal Survey of Biological and Physical Sciences in Space demonstrate the need to carefully consider best practices in this domain. Here, we present greater detail about the makeup and participation metrics of the various AWGs affiliated with OSDR and details of successful peer-reviewed publication campaigns.

Christina M Johnson↗

Tracking Community Building in Open Science

Open Science is enabled by a vibrant community of researchers who regularly engage with the data, from its production to its organization, curation, archiving, dissemination, analysis, and publication. This presentation will examine community building in open science. The NASA Open Science Data Repository (OSDR) makes data available to the public following the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles. OSDR takes open science further with the OS Analysis Working Groups (AWGs) that facilitate community development and promotion. The primary activity of each AWG is to establish and validate analytical processes to generate higher-order data from data housed in OSDR. There are a number of these groups on various topics, including the Animal AWG, Plant AWG, Microbial AWG, Multi-Omics AWG, AI/ML AWG, and the Ames Life Sciences Data Archive (ALSDA) AWG. The international volunteers participating in these AWGs come from academia, citizen science initiatives, industry, and government. They include researchers, principal investigators, professors, trained hobbyists, and students from various domains and disciplines. Anyone may request to join the AWGs, and membership requests are vetted monthly by the group organizers before granting admission. Core to membership is demonstrated expertise through records of training, integrity, work in the professed domain(s), and good community standing. Regular virtual meetings are held for each AWG, with a varying cadence depending on the group's needs and goals. AWG communities share their expertise in research including cutting edge tools, software, frameworks, data formats, and libraries accelerating research collectively. This collaborative approach helps community members cross technology gaps and identify emerging challenges. These diverse communities encompass a wide range of individuals hailing from various sectors within the Science Mission Directorate and beyond. They serve as a means to promote and enhance transparency, accessibility, and inclusion. An annual AWG Symposium brings contributors together in person. Participation in AWGs can be synchronous or asynchronous, with some groups performing most of their work in off hours. Participants gain valuable skills and connections that allow them to add value to their communities and new organizations that they join, resulting in an expanded return on investment for the space life science community. Open science is increasingly a federal mandate and initiatives like NASA's Transform to Open Science and instruments like the Decadal Survey of Biological and Physical Sciences in Space demonstrate the need to carefully consider best practices in this domain. Here, we present greater detail about the makeup and participation metrics of the various AWGs affiliated with OSDR and details of successful peer-reviewed publication campaigns.

Christina M Johnson↗

Model Specification for Rework of Aircraft Engine, Power Transmission, and Accessory/Auxiliary Ball and Roller Bearings

This document provides a model specification for the rework and/or repair of bearings used in aircraft engines, helicopter main power train transmissions, and auxiliary bearings determined to be critical by virtue of performance, function, or availability. The rolling-element bearings to be processed under the provisions of this model specification may be used bearings removed after service, unused bearings returned from the field, or certain rejected bearings returned for reinspection and salvage. In commercial and military aircraft application, it has been a practice that rolling-element bearings removed at maintenance or overhaul be reworked and returned to service. Depending on the extent of rework and based upon theoretical analysis, representative life factors (LF) for bearings subject to rework ranged from 0.87 to 0.99 the lives of new bearings. Based on bearing endurance data, 92 percent of the bearing sets that would be subject to rework would result in L(sub 10) lives equaling and/or exceeding that predicted for new bearings. The remaining 8 percent of the bearings have the potential to achieve the analytically predicted life of new bearings when one of the rings is replaced at rework. The potential savings from bearing rework varies from 53 to 82 percent of that of new bearings depending on the cost, size, and complexity of the bearing

Zaretsky, Erwin V.↗

Acute Hemodynamic Effects of the Braslet-M Device on the International Space Station

The Braslet-M occlusion device is prescribed for cosmonauts as a countermeasure for early phases of spaceflight to temporarily alleviate symptoms associated with the cephalad fluid shift. Using a multipurpose ultrasound (US) device onboard, we assessed the acute hemodynamic effects of the Bracelet-M device on a long duration International Space Station (ISS) crewmember. Methods A combination of just-in-time training and real-time remote expert assistance was used to conduct the imaging procedures. An HDI-5000 imager (Philips, Bothell, WA) was used, provided by the ISS Human Research Facility. Superficial femoral artery (SFA), femoral vein (FV) flow spectra were obtained at mid-thigh level. Left ventricle was imaged through the apical 4-chamber view, with Color M-Mode to measure propagation velocity (V (p)). After 10 minutes of Bracelet-M use, data collection was repeated. All data were transmitted in DICOM format to ground for analysis. Results With Braslet-M, cardiac V(p) slope decreased (56ms to 42ms). A stagnation signature in the FV was seen suggesting impeded flow (rouleaux formation, too-low-to-measure velocity, and increase in diameter). Quadri-phasic flow in SFA was seen both before and after Braslet-M application. Velocities in the SFA decreased with Braslet-M (65cm/sec to 52cm/sec) and so did the time velocity integrals (16.97 to 12.4); the flow pattern spoke of resistivity increase in the vascular bed. Conclusion In the long duration ISS crewmember we observed effects of lower extremity venous occlusion through both central and peripheral indicators. A part of circulating volume transferred to peripheral potential vascular space. Impediment to venous outflow was demonstrated objectively, with a commensurate change in the flow pattern of the main feeding artery. Central volume reduction caused lower V(p). Additional studies are warranted to determine the time course of the changes and the dynamics in interstitial fluid sequestration, as well as the safe levels and duration of the compression forces.

Hamilton, Douglas R.↗

Open-source Techniques for Automated Landslide Inventory Generation for Rapid Response

Manual mapping is the most used method for generating landslide inventories. For rapid response scenario this method becomes tedious and time consuming. The Landslide team at NASA Goddard Space Flight Center has been developing open-source landslide mapping systems for rapid generation of landslide inventories. We have developed a Python-based landslide mapping framework known as the Semi-Automatic Landslide Detection (SALaD) system that uses Object-based Image Analysis and machine learning. For production of event-based inventories, SALaD was modified to include a change detection module (SALaD-CD). Utilizing high-resolution imagery form from Planet and Maxar, we have generated multiple rapid response landslide inventories that have been used by emergency responders on the ground, the NASA Disasters program, and academia. Currently, we are exploiting deep learning frameworks for landslide mapping. We are interested to learn about efficient way to harmonize multi-sensor data for creating a long-term record of landslides, training strategies and ongoing deep learning-based efforts for natural hazard characterization within NASA and UMD.

Pukar Amatya↗

Rotor-to-stator rub vibration in centrifugal compressor

One example of excessive vibration encountered during loading of a centrifugal compressor train (H type compressor with HP casing) is discussed. An investigation was made of the effects of the dynamic load on the bearing stiffness and the rotor-bearing system critical speed. The high vibration occurred at a "threshold load," but the machine didn't run smoothly due to rubs even when it had passed through the threshold load. The acquisition and discussion of the data taken in the field as well as a description of the case history which utilizes background information to identify the malfunction conditions is presented. The analysis shows that the failures, including full reverse precession rub and exact one half subharmonic vibration, were caused by the oversize bearings and displacement of the rotor center due to foundation deformation and misalignment between gear shafts, etc. The corrective actions taken to alleviate excessive vibration and the problems which remain to be solved are also presented.

Gao, J. J.↗

The effect of horizontal resolution on systematic errors of the GLA forecast model

Systematic prediction errors of the Goddard Laboratory for Atmospheres (GLA) forecast system are reduced when the higher-resolution (2 x 2.5 deg) model version is used. Based on a budget analysis of the 200-mb eddy streamfunction, the improvement of stationary eddy forecasting is seen to be caused by the following mechanism: by increasing the horizontal spatial resolution of the forecast model, atmospheric diabatic heating over the three tropical continents is changed in a way that intensifies the planetary-scale divergent circulations associated with the three pairs of divergent-convergent centers over these continents. The intensified divergent circulation results in an enhancement of vorticity sources in the Northern Hemisphere. The additional vorticity is advected eastward by a stationary wave train along 30 deg N, thereby reducing systematic errors in the lower-resolution (4 x 5 deg) GLA model.

Chen, Tsing-Chang↗