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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

In-flight measurement of the National Oceanic and Atmospheric Administration (NOAA)-10 static Earth sensor error

Analysis performed in the Goddard Space Flight Center (GSFC) Flight Dynamics Division (FDD) measures error in the static Earth sensor onboard the National Oceanic and Atmospheric Administration (NOAA)-10 spacecraft using flight data. Errors are computed as the difference between Earth sensor pitch and roll angle telemetry and reference pitch and roll attitude histories propagated by gyros. The flight data error determination illustrates the effect on horizon sensing of systemic variation in the Earth infrared (IR) horizon radiance with latitude and season, as well as the effect of anomalies in the global IR radiance. Results of the analysis provide a comparison between static Earth sensor flight performance and that of scanning Earth sensors studied previously in the GSFC/FDD. The results also provide a baseline for evaluating various models of the static Earth sensor. Representative days from the NOAA-10 mission indicate the extent of uniformity and consistency over time of the global IR horizon. A unique aspect of the NOAA-10 analysis is the correlation of flight data errors with independent radiometric measurements of stratospheric temperature. The determination of the NOAA-10 static Earth sensor error contributes to realistic performance expectations for missions to be equipped with similar sensors.

Harvie, E.↗
NASA NTRS2019

Estimating Residual Uncertainties for Lunar Irradiance Measurements Due to Imaging Acquisition Parameters

Lunar calibration is a commonly used method to track a climate satellite sensor's long-term radiometric stability. We present a modeling approach to examine the satellite sensor lunar observation uncertainties due to several important aspects related to the lunar image acquisition by the satellite sensor: lunar pixel shift, point spread function (PSF), lunar orientation, pitch, and oversampling rates. Our analyses can be summarized as follows: (1) The sensor observed lunar irradiance can vary due to small lunar pixel shift if the PSF is less than ideal; (2) During lunar calibration, an unstable oversampling rate due to spacecraft control will result in errors in observed lunar irradiance. A drift in oversampling rate would result in a bias in observed lunar irradiance and a random variation in oversampling rate would cause random error in lunar irradiance. Increasing the overall oversampling rates can reduce random error in observed lunar irradiance but would not change the biases in the observation; (3) Furthermore, the biases can vary when the Moon is observed at different orientations. Our results show impacts on observed lunar irradiance are on the order of 0.1 percent, which is a significant part of the overall uncertainty for a lunar irradiance measurement of a climate satellite sensor.

Oversampling↗
DOE OSTI2025

Transformers and Long Short-Term Memory Transfer Learning for GenIV Reactor Temperature Time Series Forecasting

Automated monitoring of the coolant temperature can enable autonomous operation of generation IV reactors (GenIV), thus reducing their operating and maintenance costs. Automation can be accomplished with machine learning (ML) models trained on historical sensor data. However, the performance of ML usually depends on the availability of large amount of training data, which is difficult to obtain for GenIV, as this technology is still under development. We propose the use of transfer learning (TL), which involves utilizing knowledge across different domains, to compensate for this lack of training data. TL can be used to create pre-trained ML models with data from small-scale research facilities, which can then be fine-tuned to monitor GenIV reactors. In this work, we develop pre-trained Transformer and long short-term memory (LSTM) networks by training them on temperature measurements from thermal hydraulic flow loops operating with water and Galinstan fluids at room temperature at Argonne National Laboratory. The pre-trained models are then fine-tuned and re-trained with minimal additional data to perform predictions of the time series of high temperature measurements obtained from the Engineering Test Unit (ETU) at Kairos Power. The performance of the LSTM and Transformer networks is investigated by varying the size of the lookback window and forecast horizon. The results of this study show that LSTM networks have lower prediction errors than Transformers, but LSTM errors increase more rapidly with increasing lookback window size and forecast horizon compared to the Transformer errors.

LSTM↗
DOE OSTI2024

DECOVALEX-2023: Task C Final Report

The Full-scale Emplacement (FE) heater experiment at the Mont Terri Underground Rock Laboratory (URL) was designed and conducted by Nagra to replicate an emplacement tunnel of Nagra’s reference repository design at 1:1 scale. Alongside testing the technical feasibility of constructing disposal tunnels, emplacing waste containers in the tunnels and then backfilling them, the main goals of the FE experiment are (1) to obtain a better understanding of the coupled effects of induced thermo-hydro-mechanical (THM) processes that may occur and (2) to validate existing coupled THM models (Müller et al., 2017). A key aspect of ensuring safety for repositories located in low-permeability rock involves minimizing any damage to the rock itself, thereby preserving its integrity and promoting a stable environment Amongst a number of processes that could damage the rock is the increase in pore pressure due to thermal loading caused by heat emitted from the waste. To reduce the potential damage of the rock, it is important to analyse the evolution of heat over time due to the heat load of the containers and assess possible consequences by coupled THM models. The aim of Task C of DECOVALEX-2023 was to build 3D numerical models of the FE experiment, focussing in particular on the heating induced pore pressure change in the Opalinus Clay. Data from a large number of sensors were available from the FE experiment for model comparison. These sensors measured temperature and relative humidity in the bentonite around the heaters, and temperature, pressure and displacement/strain in the surrounding Opalinus clay. Data were available from the start of excavation (April 2012) up to August 2020 for most sensors (more than 5 years from the start of heating in December 2014). To fulfil the overall aim of the task, the work was broken down into a number of steps, starting with simpler models to build confidence in each team’s approach and then moving to more complex models that better represent the FE experiment. Step 0 consisted of 2D benchmark models, gradually increasing the number of processes that are represented from thermal (T) only models in Step 0a, to coupled thermal hydraulic (TH) models in Step 0b with a representation of changing porosity, to coupled thermo-hydro-mechanical (THM) models in Step 0c, where porosity changes are calculated by the mechanical model. A detailed specification of processes, parameters, initial and boundary conditions was provided for this step, with the ambition that all teams would work towards close agreement in their model results, thus building confidence in the model implementations. vi It was not straightforward to achieve agreement between the teams, so additional steps (Step 0b2, 0b3, 0c2, 0c3) were added along with derivation of some analytical solutions against which the models could be compared. The reasons for the differences between teams were investigated and found to be caused primarily by different conceptual model assumptions (including temperature dependence of the thermal expansion of water), different model formulations (including porosity evolution) and differences in modelled domain sizes, boundary conditions and grid discretisation. This demonstrates that comparisons between multiple modelling teams and/or comparison with analytical results and experimental data are highly beneficial in providing an indication of uncertainty in model predictions. At the conclusion of Step 0, almost all teams had achieved a close agreement in model results and those that had not achieved an agreement knew the reason for this. Step 1 moved from 2D models to 3D models of the FE experiment without adding technical features like shotcrete or EDZ, and only considering the heating phase. Initially the 3D model was tightly specified to continue to build confidence in the model implementations (Step 1a). The results of Step 1a were compared to the data from the FE-experiment without the teams seeing the data. The teams were then provided with a sub-set of the data from the FE-experiment and invited to consider how best to use the large dataset for model comparison (Step 1b). Teams were then asked to use the data provided to calibrate their models, only changing material property values rather than adding features or processes to their models (Step 1c). In Step 1, teams were asked to only model the heating phase of the experiment, so pressure in the Opalinus Clay was reported as change in pressure since the initial conditions were specified rather than modelled. The change from 2D to 3D models was accompanied by an increase in the dispersion of results between the teams. Some of this was resolved during the task, but some remained and is potentially due to model discretisation. Calibration of parameters was useful in improving the fit of the models to the data but the remaining differences indicated that the models were missing features or processes. In Step 2, the teams were asked to update their models with additional features and processes as well as calibrating parameters to try and improve the fit of the models to the data. Teams were encouraged to represent ventilation of the open FE tunnel prior to backfilling with heaters and bentonite and in Step 2, the absolute pressure in the Opalinus Clay was compared between the teams. Teams took different approaches, but there was consideration of adding shotcrete and an EDZ into the model, representing stress change during excavation and different approaches to modelling ventilation of the FE tunnel. Overall, the documented results showed a very good agreement for temperature. The results for porewater pressure evolution showed a significant improvement for most teams compared to Step 1c with a good agreement to the measurements for several teams whereas some teams overpredicted the pressure increase and others overpredicted the drainage effect especially for the sensors close to the heater. Step 3 was an opportunity for teams to use the models developed in Step 1 and Step 2 to make predictions about the temperature and pressure changes that will be expected at the FE experiment over the next few years in light of the planned changes in thermal output of the heaters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2009

Comparison of Transmission Line Methods for Surface Acoustic Wave Modeling

Surface Acoustic Wave (SAW) technology is low cost, rugged, lightweight, extremely low power and can be used to develop passive wireless sensors. For these reasons, NASA is investigating the use of SAW technology for Integrated Vehicle Health Monitoring (IVHM) of aerospace structures. To facilitate rapid prototyping of passive SAW sensors for aerospace applications, SAW models have been developed. This paper reports on the comparison of three methods of modeling SAWs. The three models are the Impulse Response Method (a first order model), and two second order matrix methods; the conventional matrix approach, and a modified matrix approach that is extended to include internal finger reflections. The second order models are based upon matrices that were originally developed for analyzing microwave circuits using transmission line theory. Results from the models are presented with measured data from devices. Keywords: Surface Acoustic Wave, SAW, transmission line models, Impulse Response Method.

Wilson, William↗
NASA NTRSDate not supplied

Applicability of a Framework for Estimating Performance and Associated Uncertainty for Modified Aircraft Configurations

As improvements are made to the accuracy and reliability of modeling and simulation techniques, certification by analysis becomes a more attractive alternative compared to traditional aircraft flight testing. Certification by analysis is especially cost-effective when one considers modifications to a previously certified aircraft. However, it is important that the models and methods used are applicable and accurate throughout the intended use domain. A framework for estimating the performance and associated uncertainty was introduced in an earlier paper. The factors and limitations of this framework for estimating the performance and associated model form uncertainty are explored to determine the range of applicability of the framework, particularly with respect to model form, process and sensor noise, and quality of available flight test data. This paper focuses on the general limitations and applicability of the framework and not the applicability of the individual methods to a range of modified configurations, which requires a large number of modified configurations and is an area for future work. The effects of these factors on the performance and uncertainty results are demonstrated using NASA’s Generic Transport Model aircraft.

uncertainty quantification↗
DOE OSTI2025

Observer-Based Nonlinear Control Scheme to Reduce Oscillations and Zero Crossing in Skid-Steer Vehicles

Motion sickness is a common condition experienced by drivers of skid-steer vehicles, primarily caused by zero crossing and oscillations in undamped systems. This study proposes an observer-based nonlinear control scheme to reduce transient oscillations and zero-crossing phenomena in skid-steer vehicles, thereby potentially alleviating motion sickness. Reducing transient oscillations and zero crossing in the transient response may alleviate motion sickness. A nonlinear damping controller is designed to improve transient response by reducing oscillations and zero-crossing. To design the controller, a reduced-order kinematic model based on coordinate transformation is developed. This transformation not only converts the system modeling into a controllable form but also enhances control performance. Modeling error is addressed by considering the distance between the center of the vehicle and the sensor location. Despite these improvements, model uncertainties and external disturbances remain, which may degrade control performance. To ensure robustness and estimate such disturbances, a high-order sliding mode observer (HOSMO) is incorporated. The effectiveness of the proposed method is validated through MATLAB/Simulink and TruckMaker simulations. From the simulation results, it was shown that the proposed method reduced the mean squared error of the tracking error to within 10 % compared to the state feedback controller with the HOSMO.

Seo, Jiwon [Chung-Ang University, Seoul (Korea, Re↗
NASA NTRS1982

Technology needs assessment of an atmospheric observation system for tropospheric research missions, part 1

The technology advancements needed to implement the atmospheric observation satellite systems for air quality research were identified. Tropospheric measurements are considered. The measurements and sensors are based on a model of knowledge objectives in atmospheric science. A set of potential missions and attendant spacecraft and sensors is postulated. The results show that the predominant technology needs will be in passive and active sensors for accurate and frequent global measurements of trace gas concentration profiles.

Alvarado, D. R.↗
NASA NTRS1989

Low-order design and high-order simulation of active closed-loop control for aerospace structures under construction

Partially constructed/assembled structures in space are complicated enough but their dynamics will also be operating in closed-loop with feedback controllers. The dynamics of such structures are modeled by large-scale finite element models. The model dimension L is extremely large (approximately 10,000) while the numbers of actuators (M) and sensors (P) are small. The model parameters M(sub m) mass matrix, D(sub o) damping matrix, and K(sub o) stiffness matrix, are all symmetric and sparse (banded). Thus simulation of open-loop structure models of very large dimension can be accomplished by special integration techniques for sparse matrices. The problem of simulation of closed-loop control of such structures is complicated by the addition of controllers. Simulation of closed-loop controlled structures is an essential part of the controller design and evaluation process. Current research in the following areas is presented: high-order simulation of actively controlled aerospace structures; low-order controller design and SCI compensation for unmodeled dynamics; prediction of closed-loop stability using asymptotic eigenvalue series; and flexible robot manipulator control experiment.

Balas, Mark J.↗
NASA NTRS1997

A Cognitive System Model for Human/Automation Dynamics in Airspace Management

NASA has initiated a significant thrust of research and development focused on providing the flight crew and air traffic managers automation aids to increase capacity in en route and terminal area operations through the use of flexible, more fuel-efficient routing, while improving the level of safety in commercial carrier operations. In that system development, definition of cognitive requirements for integrated multi-operator dynamic aiding systems is fundamental. In order to support that cognitive function definition, we have extended the Man Machine Integrated Design and Analysis System (MIDAS) to include representation of multiple cognitive agents (both human operators and intelligent aiding systems) operating aircraft, airline operations centers and air traffic control centers in the evolving airspace. The demands of this application require representation of many intelligent agents sharing world-models, and coordinating action/intention with cooperative scheduling of goals and actions in a potentially unpredictable world of operations. The MIDAS operator models have undergone significant development in order to understand the requirements for operator aiding and the impact of that aiding in the complex nondeterminate system of national airspace operations. The operator model's structure has been modified to include attention functions, action priority, and situation assessment. The cognitive function model has been expanded to include working memory operations including retrieval from long-term store, interference, visual-motor and verbal articulatory loop functions, and time-based losses. The operator's activity structures have been developed to include prioritization and interruption of multiple parallel activities among multiple operators, to provide for anticipation (knowledge of the intention and action of remote operators), and to respond to failures of the system and other operators in the system in situation-specific paradigms. The model's internal representation has been be modified so that multiple, autonomous sets of equipment will function in a scenario as the single equipment sets do now. In order to support the analysis requirements with multiple items of equipment, it is necessary for equipment to access the state of other equipment objects at initialization time (a radar object may need to access the position and speed of aircraft in its area, for example), and as a function of perception and sensor system interaction. The model has been improved to include multiple world-states as a function of equipment am operator interaction. The model has been used -1o predict the impact of warning and alert zones in aircraft operation, and, more critic-ally, the interaction of flight-deck based warning mechanisms and air traffic controller action in response to ground-based conflict prediction and alerting systems. In this operation, two operating systems provide alerting to two autonomous, but linked sets of operators, whose view of the system and whose dynamics in response are radically different. System stability and operator action was predicted using the MIDAS model.

Corker, Kevin M.↗
NASA NTRS2009

A Comparison of Surface Acoustic Wave Modeling Methods

Surface Acoustic Wave (SAW) technology is low cost, rugged, lightweight, extremely low power and can be used to develop passive wireless sensors. For these reasons, NASA is investigating the use of SAW technology for Integrated Vehicle Health Monitoring (IVHM) of aerospace structures. To facilitate rapid prototyping of passive SAW sensors for aerospace applications, SAW models have been developed. This paper reports on the comparison of three methods of modeling SAWs. The three models are the Impulse Response Method a first order model, and two second order matrix methods; the conventional matrix approach, and a modified matrix approach that is extended to include internal finger reflections. The second order models are based upon matrices that were originally developed for analyzing microwave circuits using transmission line theory. Results from the models are presented with measured data from devices.

Wilson, W. c.↗
NASA NTRS1975

Optical atmospheric scattering and absorption limitations on offset pointing from Earth Observatory Satellite /EOS/ sensors

The Braslau-Dave atmospheric model which calculates the upward monochromatic light fluxes leaving the top of the atmosphere as a function of viewing angle, sun angle, and ground reflectance was employed to study the effect of atmospheric scattering and attenuation on universal apparent contrast for two EOS remote sensors operated at very large offset or pointing angles: the Thematic Mapper (TM) and the High Resolution Pointable Imager (HRPI). The TM offset off nadir could be plus or minus 20 degrees with an 11 degree scan angle and the HRPI pointing angle off nadir could be plus or minus 45 degrees with a 3 degree scan angle. The reduction of universal apparent contrast of EOS imagery is studied as a function of sun elevation angle, atmospheric aerosol loading, radiation wavelength and sensor look angles.

Egan, W. G.↗
NASA NTRS1996

Automated Decomposition of Model-based Learning Problems

A new generation of sensor rich, massively distributed autonomous systems is being developed that has the potential for unprecedented performance, such as smart buildings, reconfigurable factories, adaptive traffic systems and remote earth ecosystem monitoring. To achieve high performance these massive systems will need to accurately model themselves and their environment from sensor information. Accomplishing this on a grand scale requires automating the art of large-scale modeling. This paper presents a formalization of [\em decompositional model-based learning (DML)], a method developed by observing a modeler's expertise at decomposing large scale model estimation tasks. The method exploits a striking analogy between learning and consistency-based diagnosis. Moriarty, an implementation of DML, has been applied to thermal modeling of a smart building, demonstrating a significant improvement in learning rate.

Williams, Brian C.↗
NASA NTRS1989

Automated model formulation for time-varying flexible structures

Presented here is an identification technique that uses the sensor information to choose a new model out of a finite set of discrete model space, in order to follow the observed changes to the given time varying flexible structure. Boundary condition sets or other information on model variations are used to organize the set of possible models laterally into a search tree with levels of abstraction used to order the models vertically within branches. An object-oriented programming approach is used to represent the model set in the search tree. A modified A (asterisk) best first search algorithm finds the model where the model response best matches the current observations. Several extensions to this methodology are discussed. Methods of possible integration of rules with the current search algorithm are considered to give weight to interpreted trends that may be found in a series of observations. This capability might lead, for instance, to identifying a model that incorporates a progressive damage rather than with incorrect paramenters such as added mass. Another new direction is to consider the use of noisy time domain sensor feedback rather than frequency domain information in the search algorithm to improve the real-time capability of the developed procedure.

Glass, B. J.↗
NASA NTRS2010

NASA Goddard Giovanni Support for YOTC

The fundamental challenges to overcoming our shortcomings in understanding and modeling/predicting tropical convection have been twofold: I) the need to represent the broad range of scales applicable to the tropical organization problem (i.e. cumulus to planetary), and II) the lack of observations that adequately and simultaneously characterize this broad range of scales and that also provide three-dimensional information on thermodynamic, radiative and dynamical interactions, including cloud microphysical processes. In regards to the second challenge, it should be stressed that this problem will not be solved through the production and examination of one or a few high quality long-term records of fundamental quantities (e.g., SST, water vapor, cloud fraction). Rather, an alternative and more comprehensive paradigm is needed, one that integrates the multitude of applicable resources and measures of tropical convection in a manner that that can be better utilized by the diagnostic, modeling and forecasting communities to more completely and coherently focus on the problem.Because the goal of YOTC involves examining a scientifically complex, multi-scale process , rather than documenting the characteristics of a single parameter (e.g., SST, cloud cover), YOTC has an IOP perspective that targets a period, May 2008 April 2010, long enough to encompass many cases of tropical convection activity in many of its most challenging yet influential forms. This includes mesoscale and synoptic variability, easterly waves and hurricanes, convectively coupled waves, the MJO and the culmination of these in terms of the monsoon, their interactions with the extra-tropics, and mean characteristics such as tropical-to-subtropical transitions. The YOTC time period and length are driven in part by the following: 1) keeping the multi-sensor/multi-platform and model-analyses data sets and associated infrastructure manageable, 2) facilitating a focused effort by the research and operational communities on a specific scientific problem, and 3) capitalizing on the recent key additions to the armada of satellites (e.g., CloudSat and CALIPSO). The proposed dissemination framework for the YOTC satellite data archive is based on the Giovanni system. Giovanni is a web-based application developed by the NASA Goddard Earth Science (GES) Data and Information Service Center (DISC) that provides a simple and intuitive way to visualize, analyze, and access/download vast amounts of Earth science remote sensing data. A prototype YOTC Giovanni System (hereafter YOTC-GS) is in the process of being developed. YOTC-GS will provide access to level 2 (i.e. swath level data) and/or level 3 (i.e. gridded/mapped data) forms of satellite data, the choice or both depending on what is appropriate and relevant. The former is needed and better suited for detailed process examination, exploiting the highest temporal-spatial resolutions available and comparison to regional cloud-system resolving model / cloud resolving model (CSRM/CRM) model output. The latter is needed and more well suited for examination of phenomena, conditions and processes on large to global scales, and for comparisons to global model analyses, prediction and simulation output.

Ostrenga, Dana↗
NASA NTRS1993

Gyroless yaw control system for a three axis stabilized, zero-momentum spacecraft

A satellite attitude control system is usable in the absence of any inertial yaw attitude reference, such as a gyroscope, and in the absence of a pitch bias momentum. Both the roll-yaw rigid body dynamics and the roll-yaw orbit kinematics are modelled. Pitch and roll attitude control are conventional. The model receives inputs from a roll sensor, and roll and yaw torques from reaction wheel monitors. The model produces estimated yaw which controls the spacecraft yaw attitude.

Stetson, Jr., John B.↗
NASA NTRS1999

Physical Control of Biological Productivity Off the Coast of Peru During the 1997-1998 El Nino

Satellite observations and an ecosystem model are used to understand the variability in the planktonic ecosystem off Peru for the period January 1996 to May 1998. The objective of this study is to quantify the changes in the ecosystem components, carbon pathways, and available food for small pelagic fish that occur associated with the change in physical forcing due to El Nino. Two periods are distinguished based on the observed sea level anomaly: a La Nina (LaN) period (1996) in which sea level was below normal and El Nino (EN), the average conditions for December 1997, in which the sea level was anomalously high. There are three phytoplankton size classes (pico-, nano-, and net-phytoplankton) which compete for nutrients and are eaten by three zooplankton size classes. The ecosystem model is forced by alongshore wind speed measured by the NASA Scatterometer (NSCAT) and the European Remote-sensing Satellites (ERS-1 and ERS-2). Larger, slower growing organisms are more sensitive to physical disturbance than smaller organisms (Carr, 1998]. In the present simulation as well, the primary effect of the El Nino (reduced nutrient supply, and increased temperature) is to reduce the biomass of large cells (netphytoplankton) and consequently of the zooplankton that rely on large cells as food source. EN conditions are accompanied by a rearrangement of carbon pathways: comparable uptake goes into reduced biomass accumulation, increased losses to respiration, reduced carbon export, and much reduced carbon available to fish. The star indicates the remotely sensed biomass (assuming a constant carbon to chlorophyll ratio of 60) as measured by the Ocean Color and Temperature Sensor (Nov.-Dec. 1996) and the Sea-viewing Wide Field-of-view Sensor (Dec. 1997). The model, which assumes no light limitation, overestimates total phytoplankton biomass. Additional Information is contained in the original.

Carr, Mary-Elena↗
NASA NTRS2007

Frequency Domain Modeling of SAW Devices

New SAW sensors for integrated vehicle health monitoring of aerospace vehicles are being investigated. SAW technology is low cost, rugged, lightweight, and extremely low power. However, the lack of design tools for MEMS devices in general, and for Surface Acoustic Wave (SAW) devices specifically, has led to the development of tools that will enable integrated design, modeling, simulation, analysis and automatic layout generation of SAW devices. A frequency domain model has been created. The model is mainly first order, but it includes second order effects from triple transit echoes. This paper presents the model and results from the model for a SAW delay line device.

Wilson, W. C.↗