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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 523 records · Page 29

All sources NASA NTRS DOE OSTI

NASA NTRS1984

Experimental on-stream elimination of resonant whirl in a large centrifugal compressor

Resonant whirl condition during operation of a multi-stage centrifugal compressor at higher than anticipated speeds and loads was reported. The condition was diagnosed by a large scale computerized Machinery Condition Monitoring System (MACMOS). This computerized system verified that the predominant subsynchronous whirl frequency locked in on the first resonant frequency of the compressor rotor and did not vary with compressor speed. Compressor stability calculations showed the rotor system had excessive hearing stiffness and inadequate effective damping. An optimum bearing design which was developed to minimize the unbalance response and to maximize the stability threshold is presented.

Bhat, G. I.↗

NASA NTRS1985

Support systems design and analysis

The integration of Kennedy Space Center (KSC) ground support systems with the new launch processing system and new launch vehicle provided KSC with a unique challenge in system design and analysis for the Space Transportation System. Approximately 70 support systems are controlled and monitored by the launch processing system. Typical systems are main propulsion oxygen and hydrogen loading systems, environmental control life support system, hydraulics, etc. An End-to-End concept of documentation and analysis was chosen and applied to these systems. Unique problems were resolved in the areas of software analysis, safing under emergency conditions, sampling rates, and control loop analysis. New methods of performing End-to-End reliability analyses were implemented. The systems design approach selected and the resolution of major problem areas are discussed.

Ferguson, R. M.↗

NASA NTRS1987

Power-Switching Circuit

Functions of circuit breakers, meters, and switches combined. Circuit that includes power field-effect transistors (PFET's) provides on/off switching, soft starting, current monitoring, current tripping, and protection against overcurrent for 30-Vdc power supply at normal load currents up to 2 A. Has no moving parts.

Praver, Gerald A.↗

NASA NTRS1991

Orthostatic function during a stand test before and after head-up or head-down bedrest

The effects of head-down or head-up bedrest at -5, +10, +20, or +42 deg (simulating 0, 1/6, 1/3, and 2/3 g, respectively) for 6 hrs on four different days on the orthostatic tolerance were investigated by measuring relevant physiological reactions to orthostatic test taken before and after bedrest sessions. The multivariate analysis of variance statistical analyses indicates that there was no angle effect on any of the cardiovascular parameters monitored during the last 3 min of the stand test, suggesting that partial gravity loads would have no effect on the cardiovascular deconditioning exhibited postflight. There was, however, a significant elevation in the heart rate post-bedrest, and the heart rate increased on standing. Results from the stand test pre- and post-bedrest at -5 deg (but not at +10, +20, and +42 deg) were similar to those observed after space flight.

Lathers, Claire M.↗

NASA NTRS2004

Hierarchical Discrete Event Supervisory Control of Aircraft Propulsion Systems

This paper presents a hierarchical application of Discrete Event Supervisory (DES) control theory for intelligent decision and control of a twin-engine aircraft propulsion system. A dual layer hierarchical DES controller is designed to supervise and coordinate the operation of two engines of the propulsion system. The two engines are individually controlled to achieve enhanced performance and reliability, necessary for fulfilling the mission objectives. Each engine is operated under a continuously varying control system that maintains the specified performance and a local discrete-event supervisor for condition monitoring and life extending control. A global upper level DES controller is designed for load balancing and overall health management of the propulsion system.

Yasar, Murat↗

NASA NTRS2010

Method for Detecting Perlite Compaction in Large Cryogenic Tanks

Perlite is the most typical insulating powder used to separate the inner and outer shells of cryogenic tanks. The inner tank holds the low-temperature commodity, while the outer shell is exposed to the ambient temperature. Perlite minimizes radiative energy transfer between the two tanks. Being a powder, perlite will settle over time, leading to the danger of transferring any loads from the inner shell to the outer shell. This can cause deformation of the outer shell, leading to damaged internal fittings. The method proposed is to place strain or displacement sensors on several locations of the outer shell. Loads induced on the shell by the expanding inner shell and perlite would be monitored, providing an indication of the location and degree of compaction.

Youngquist, Robert↗

NASA NTRS2017

Simulation of the Ozone Monitoring Instrument Aerosol Index Using the NASA Goddard Earth Observing System Aerosol Reanalysis Products

We provide an analysis of the commonly used Ozone Monitoring Instrument (OMI) aerosol index (AI) product for qualitative detection of the presence and loading of absorbing aerosols. In our analysis, simulated top-of-atmosphere (TOA) radiances are produced at the OMI footprints from a model atmosphere and aerosol profile provided by the NASA Goddard Earth Observing System (GEOS-5) Modern-Era Retrospective Analysis for Research and Applications aerosol reanalysis (MERRAero). Having established the credibility of the MERRAero simulation of the OMI AI in a previous paper we describe updates in the approach and aerosol optical property assumptions. The OMI TOA radiances are computed in cloud-free conditions from the MERRAero atmospheric state, and the AI is calculated. The simulated TOA radiances are fed to the OMI aerosol retrieval algorithms, and its retrieved AI (OMAERUV AI) is compared to the MERRAero calculated AI. Two main sources of discrepancy are discussed: one pertaining the OMI algorithm assumptions of the surface pressure, which are generally different from what the actual surface pressure of an observation is, and the other related to simplifying assumptions in the molecular atmosphere radiative transfer used in the OMI algorithms. Surface pressure assumptions lead to systematic biases in the OMAERUV AI, particularly over the oceans. Simplifications in the molecular radiative transfer lead to biases particularly in regions of topography intermediate to surface pressures of 600hPa and 1013.25hPa. Generally, the errors in the OMI AI due to these considerations are less than 0.2 in magnitude, though larger errors are possible, particularly over land. We recommend that future versions of the OMI algorithms use surface pressures from readily available atmospheric analyses combined with high-spatial resolution topographic maps and include more surface pressure nodal points in their radiative transfer lookup tables.

remote sensing↗

NASA NTRSDate not supplied

Building Capacity to Use Earth Observations for Wildfire Risk Reduction and Resilience Applications: A Summary of NASA’s DEVELOP 2022 Wildfire Projects

NASA’s DEVELOP Program engages individuals and organizations in 10-week feasibility studies to apply NASA Earth observations (EO) to decision makers’ needs. DEVELOP maintains a balance of projects across nine application areas, one of which is Wildfires. DEVELOP's Wildfires application area supports pre-fire (fuel loading, fire risk), during (active fire detection), and post-fire (fire extent, intensity) monitoring and modeling. In 2022 so far, DEVELOP has conducted six projects with Wildfires as a primary or secondary component across a diverse set of study areas. This presentation introduces DEVELOP, its approach to capacity building, key partnerships, and project results highlighting the capabilities of EO for enhanced decision-making regarding wildfires.

Wildfire↗

NASA NTRS1996

Advanced Intelligent System Application to Load Forecasting and Control for Hybrid Electric Bus

The primary motivation for this research emanates from providing a decision support system to the electric bus operators in the municipal and urban localities which will guide the operators to maintain an optimal compromise among the noise level, pollution level, fuel usage etc. This study is backed up by our previous studies on study of battery characteristics, permanent magnet DC motor studies and electric traction motor size studies completed in the first year. The operator of the Hybrid Electric Car must determine optimal power management schedule to meet a given load demand for different weather and road conditions. The decision support system for the bus operator comprises three sub-tasks viz. forecast of the electrical load for the route to be traversed divided into specified time periods (few minutes); deriving an optimal 'plan' or 'preschedule' based on the load forecast for the entire time-horizon (i.e., for all time periods) ahead of time; and finally employing corrective control action to monitor and modify the optimal plan in real-time. A fully connected artificial neural network (ANN) model is developed for forecasting the kW requirement for hybrid electric bus based on inputs like climatic conditions, passenger load, road inclination, etc. The ANN model is trained using back-propagation algorithm employing improved optimization techniques like projected Lagrangian technique. The pre-scheduler is based on a Goal-Programming (GP) optimization model with noise, pollution and fuel usage as the three objectives. GP has the capability of analyzing the trade-off among the conflicting objectives and arriving at the optimal activity levels, e.g., throttle settings. The corrective control action or the third sub-task is formulated as an optimal control model with inputs from the real-time data base as well as the GP model to minimize the error (or deviation) from the optimal plan. These three activities linked with the ANN forecaster proving the output to the GP model which in turn produces the pre-schedule of the optimal control model. Some preliminary results based on a hypothetical test case will be presented for the load forecasting module. The computer codes for the three modules will be made available fe adoption by bus operating agencies. Sample results will be provided using these models. The software will be a useful tool for supporting the control systems for the Electric Bus project of NASA.

Momoh, James↗

NASA NTRS2011

Health Monitor for Multitasking, Safety-Critical, Real-Time Software

Health Manager can detect Bad Health prior to a failure occurring by periodically monitoring the application software by looking for code corruption errors, and sanity-checking each critical data value prior to use. A processor s memory can fail and corrupt the software, or the software can accidentally write to the wrong address and overwrite the executing software. This innovation will continuously calculate a checksum of the software load to detect corrupted code. This will allow a system to detect a failure before it happens. This innovation monitors each software task (thread) so that if any task reports "bad health," or does not report to the Health Manager, the system is declared bad. The Health Manager reports overall system health to the outside world by outputting a square wave signal. If the square wave stops, this indicates that system health is bad or hung and cannot report. Either way, "bad health" can be detected, whether caused by an error, corrupted data, or a hung processor. A separate Health Monitor Task is started and run periodically in a loop that starts and stops pending on a semaphore. Each monitored task registers with the Health Manager, which maintains a count for the task. The registering task must indicate if it will run more or less often than the Health Manager. If the task runs more often than the Health Manager, the monitored task calls a health function that increments the count and verifies it did not go over max-count. When the periodic Health Manager runs, it verifies that the count did not go over the max-count and zeroes it. If the task runs less often than the Health Manager, the periodic Health Manager will increment the count. The monitored task zeroes the count, and both the Health Manager and monitored task verify that the count did not go over the max-count.

Zoerner, Roger↗

NASA NTRS1992

Nondestructive monitoring damage in composites using scanning laser acoustic microscopy

Several Nicalon fiber reinforced LAS (lithium alumino-silicate) glass matrix composites were tested to study the relation between the residual strength and the different amounts of damage. The samples were fatigued by four-point cyclic loading at a 5 Hz rate at 500 C for a different number of cycles. 10 MHz scanning laser acoustic microscope (SLAM) images were taken to monitor damage on the samples. Our SLAM results indicate that there were defects already existing throughout the sample before fatigue, and the resultant damage pattern from fatigue could be related to the initial defect distribution in the sample. Finally, the fatigued samples were fractured and the residual strength data could not be explained by the cyclic fatigue alone. Rather, the damage patterns evident in the SLAM images were needed to explain the scatter in the data. The results show that SLAM is useful in nondestructively monitoring damage and estimating residual strength of fatigued ceramic composites.

Wey, A. C.↗

DOE OSTI2026

Knowledge-guided graph machine learning for spatially distributed prediction of daily discharge and nitrogen export dynamics

Spatially distributed prediction of streamflow and nitrogen export dynamics is essential for precision management of agricultural watersheds. While temporal deep learning models such as Long Short-Term Memory (LSTM) have shown strong performance at basin scales, their ability to generalize spatially is limited by insufficient representation of spatial dependencies and flow paths, particularly under data-scarce conditions. To address this gap, we propose HydroGraphNet, a knowledge-guided graph machine learning framework that integrates process-based knowledge and explicit spatial learning into temporal modeling. This framework incorporates directed graph topology to encode watershed connectivity and upstream inflows, with mass balance constraints to improve physical consistency. To enhance generalization in sparsely monitored regions, HydroGraphNet is pretrained on synthetic data generated by the SWAT+ (Soil and Water Assessment Tool Plus) model. We evaluated HydroGraphNet in the Upper Sangamon River Basin (44 HUC-12 subwatersheds, 2001–2020) against two LSTM baselines: a lumped basin-level model and a distributed variant. When benchmarked on SWAT+ simulations in pretraining, HydroGraphNet improved test NSEs by 8.9% (discharge) and 13.7% (NO₃–N load) in temporal extrapolation, and by 27.1% and 34.7% in spatial extrapolation, relative to the Lumped LSTM baseline. After fine-tuning with USGS monitoring data, the model achieved mean test NSE (KGE) scores of 0.768 (0.861) for discharge and 0.626 (0.664) for NO₃–N load, substantially outperforming baselines. Attribution analysis further highlighted the importance of upstream inflow representation and graph-based spatial learning in capturing cross-subwatershed dependencies. The model also reproduced seasonal hydrological and biogeochemical patterns consistent with known processes, demonstrating its robustness and process fidelity for spatially distributed prediction. Altogether, HydroGraphNet advances the integration of physical knowledge and spatially explicit learning in hydrological modeling, offering a generalizable framework for distributed modeling to support spatially targeted water quality management in data-scarce watersheds.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Real-time sensor measurements to evaluate impacts of load cycling on high-temperature fire-side corrosion in a PC boiler

The main objective of this research program is to design, manufacture, and demonstrate a miniaturized, multi-process, monitoring system (mMPMS) for boiler condition management and easy system deployment to obtain a higher spatial resolution. This system will facilitate a Condition-Based Maintenance (CBM) philosophy that actively monitors the health of assets to predict and prevent failures and maximize availability and generating capacity at a reduced cost. CBM systems can provide boiler data that the advanced process control (APC) system can utilize for plant performance optimization, which is increasingly relevant as coal power plants shift from predominantly base-load operation to predominantly transient operation involving large load swings. The mMPMS is based on an electrochemical sensor that provides a real-time indication of the risk of damage to key locations in the radiant or convective section of a coal-fired boiler such as metal loss rates, heat flux, metal surface temperature, and deposit thickness. These indications can be utilized to optimize boiler performance as well as improve boiler availability in conjunction with corresponding operating conditions. This monitoring system was developed and tested in the high-temperature regions of coal-fired utility boilers in this project but can be applied to many other industries and applications as well. This project leveraged the existing electrochemical noise-based monitoring system and the new sensor design is small enough to be installed through the webbing of the waterwalls without the need for long shut-downs to bend tubes and to make it feasible to obtain high spatial resolution in the boiler. Data is transferred to the plant distributed control system (DCS) and any other control system. The sensor body that houses the sensor assembly was designed to ensure good conductive contact with boiler tubes to ensure the sensor is held at an identical temperature to the tube surface temperature. The data acquisition and signal conditioning modules were redesigned into a small footprint with optimized cooling of the module. System software was developed specifically for the new signal conditioning module and is compatible with plant PLCs. After the preliminary testing at a pilot-scale facility, the three mMPMS were installed at a full-scale pulverized coal-fired plant, PacifiCorp’s Hunter 3. The systems were demonstrated over 20,000 hours at the plant during regular operation. Also, the sensor data was fed to the plant’s advanced process control system to evaluate the corrosion control by the operation changes and utilized to understand the impacts of load cycling with different ramping up and down speeds. At the end of the project, the systems were converted to the permanent installation at the power plant to be used with the advanced process control system installed at the plant.

Advanced Sensors, Corrosion, Ash Deposition, Optim↗

NASA NTRS2006

Structural Analysis and Testing of the Inflatable Re-entry Vehicle Experiment (IRVE)

The Inflatable Re-entry Vehicle Experiment (IRVE) is a 3.0 meter, 60 degree half-angle sphere cone, inflatable aeroshell experiment designed to demonstrate various aspects of inflatable technology during Earth re-entry. IRVE will be launched on a Terrier-Improved Orion sounding rocket from NASA s Wallops Flight Facility in the fall of 2006 to an altitude of approximately 164 kilometers and re-enter the Earth s atmosphere. The experiment will demonstrate exo-atmospheric inflation, inflatable structure leak performance throughout the flight regime, structural integrity under aerodynamic pressure and associated deceleration loads, thermal protection system performance, and aerodynamic stability. Structural integrity and dynamic response of the inflatable will be monitored with photogrammetric measurements of the leeward side of the aeroshell during flight. Aerodynamic stability and drag performance will be verified with on-board inertial measurements and radar tracking from multiple ground radar stations. In addition to demonstrating inflatable technology, IRVE will help validate structural, aerothermal, and trajectory modeling and analysis techniques for the inflatable aeroshell system. This paper discusses the structural analysis and testing of the IRVE inflatable structure. Equations are presented for calculating fabric loads in sphere cone aeroshells, and finite element results are presented which validate the equations. Fabric material properties and testing are discussed along with aeroshell fabrication techniques. Stiffness and dynamics tests conducted on a small-scale development unit and a full-scale prototype unit are presented along with correlated finite element models to predict the in-flight fundamental mod

Lindell, Michael C.↗

NASA NTRS2011

Inadequate Loading Stimulus on ISS Results in Bone and Muscle Loss

INTRODUCTION Exercise has been the primary countermeasure to combat musculoskeletal changes during International Space Station (ISS) missions. However, these countermeasures have not been successful in preventing loss of bone mineral density (BMD) or muscle volume in crew members. METHODS We examined lower extremity loading during typical days on-orbit and on Earth for four ISS crew members. In-shoe forces were monitored using force-measuring insoles placed inside the shoes. BMD (by DXA), muscle volumes (by MRI), and strength were measured before and after long-duration spaceflight (181 +/- 15 days). RESULTS The peak forces measured during ISS activity were significantly less than those measured in 1g for the same activities. Typical single-leg loads on-orbit during walking and running were 0.89 +/- 0.17 body weights (BW) and 1.28 +/- 0.18 BW compared to 1.18 +/- 0.11 BW and 2.36 +/- .22 BW in 1g, respectively [2]. Crew members were only loaded for an average of 43.17 +/- 14.96 min a day while performing exercise on-orbit even though 146.8 min were assigned for exercise each day. Areal BMD decreased in the femoral neck and total hip by 0.71 +/- 0.34% and 0.81 +/- 0.21% per month, respectively. Changes in muscle volume were observed in the lower extremity (-10 to -16% calf; -4 to -7% thigh) but there were no changes in the upper extremity (+0.4 to -0.8%). Decrements in isometric and isokinetic strength at the knee (range: -10.4 to -24.1%), ankle (range: -4 to -22.3%), and elbow (range: -7.5 to - 16.7%) were also observed. Knee extension endurance tests showed an overall decline in total work (-14%) but an increased resistance to fatigue post-flight. DISCUSSION AND CONCLUSIONS Our findings support the conclusion that the measured exercise durations and/or loading stimuli were insufficient to protect bone and muscle health.

Rice, A. J.↗

DOE OSTI2021

Data Challenges for Structural Health Monitoring of Electrical Machines [Slides]

Induction motors (ID) consist of a stator and a rotor. Induction motor slip decreases with decreasing load. Induction motor slip decreases with decreasing load. This talk will focus on removing closely coupled power grid frequencies in an effort to observe the true dynamic response signature of induction motors. Using the time difference between the zeros, we found the frequency as it changes over time for each of the 3 phases. The frequencies of the 3 phases were averaged to reduce the effects of sidebands on the instantaneous frequency. The frequencies of the 3 phases were averaged to reduce the effects of sidebands on the instantaneous frequency. The Kalman filter rapidly synchronizes with the expected output. The sidebands were recreated using spectral subtraction. The frequency domain shows the reduction in magnitude of the power grid frequency the Kalman output was subtracted out. Kalman filtering also reveals important data about the sidebands in healthy motors. The Continuous Wavelet Transform is an alternative to a Bandpass IIR filter used in the analysis of the acceleration data. Analysis of the acceleration data reveals 4 sidebands around the slip frequency.

42 ENGINEERING↗

NASA NTRS2021

A Dark Target research aerosol algorithm for MODIS observations over eastern China: increasing coverage while maintaining accuracy at high aerosol loading

Satellite aerosol products such as the Dark Target (DT) produced from the MODerate resolution Imaging Spectroradiometer (MODIS) are useful for monitoring the progress of air pollution. Unfortunately, the DT often fails to retrieve during the heaviest aerosol events as well as the more moderate events in winter. Some of the literature at-tributes this lack of retrieval to the cloud mask. However, we found this lack of retrieval is mainly traced to thresholds used for masking of inland water and snow. Modifications to these two masks greatly increase 50 % of the retrievals of aerosol optical depth at 0.55 μm (AOD) greater than 1.0. The “extra”-high-AOD retrievals tend to be biased when com-pared with a ground-based sun photometer (AErosol RObotic NETwork, AERONET). Reducing bias in new retrievals re-quires two additional steps. One is an update to the assumed aerosol optical properties (aerosol model); the haze in this region is both less absorbing and lower in altitude than what is assumed in the global algorithm. The second is account-ing for the scale height of the aerosol, specifically that the heavy-aerosol events in the region are much closer to the surface than what is assumed by the global DT algorithm. The resulting combination of modified masking thresholds, new aerosol model, and lower aerosol layer scale height was applied to 3 months of MODIS observations (January–March2013) over eastern China. After these two additional steps are implemented, the significant increase in new retrievals introduces no overall bias at a high-AOD regime but does degrade other overall validation statistics. We also find that the research algorithm is able to identify additional pollution events that AERONET instruments may not due to different spatial sampling. Mean AOD retrieved from the re-search algorithm increases from 0.11 to 0.18 compared to values calculated from the operational DT algorithm during January to March of 2013 over the study area. But near Beijing, where the severe pollution occurs, the new algorithm increases AOD by as much as 3.0 for each 0.5°grid box over the previous operational-algorithm values.

Dark Target↗

NASA NTRS2013

Master Console System Monitoring and Control Development

The Master Console internship during the spring of 2013 involved the development of firing room displays at the John F. Kennedy Space Center (KSC). This position was with the Master Console Product Group (MCPG) on the Launch Control System (LCS) project. This project is responsible for the System Monitoring and Control (SMC) and Record and Retrieval (R&R) of launch operations data. The Master Console is responsible for: loading the correct software into each of the remaining consoles in the firing room, connecting the proper data paths to and from the launch vehicle and all ground support equipment, and initializing the entire firing room system to begin processing. During my internship, I developed a system health and status display for use by Master Console Operators (MCO) to monitor and verify the integrity of the servers, gateways, network switches, and firewalls used in the firing room.

Brooks, Russell A.↗