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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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Generalized Predictive Control for Active Stability Augmentation and Vibration Reduction on an Aeroelastic Tiltrotor Model
Tiltrotor aircraft are defining the state-of-the-art in vertical lift technology as they have the potential to greatly expand rotary-wing operational boundaries. However, they are often limited in forward flight speed due to complex coupled rotor and wing dynamic instabilities. The U.S. Army and NASA have been developing a new wind tunnel model, the TiltRotor Aeroelastic Stability Testbed(TRAST), to test proprotors in the NASA Langley Research Center Transonic Dynamics Tunnel (TDT) to investigate aeroelastic stability in cruise. The test is intended to provide high-quality research data for analytical tool development and validation. In addition, the TRAST model will support, develop, and mature new technologies for the design of advanced proprotor aircraft. Stability augmentation and vibration reduction during testing is planned with the use of an active control methodology known as Generalized Predictive Control(GPC). GPC is an autoregressive control law that experimentally acquires a system identification to derive the input-output relation of controls and corresponding sensors. This type of control law is especially useful for complex dynamic interactions that are difficult to explicitly model such as proprotor pylon instability, often referred to as whirl flutter. GPC has been successfully employed on other tiltrotor vehicles to suppress whirl flutter instabilities and vibrations. To aid in the characterization of the wind-tunnel model and in tool development, an analytical representation of the wind-tunnel model was developed using the rotorcraft comprehensive analysis system (RCAS) that simulates structural dynamics and aerodynamics. RCAS was used to derive state-space estimates of the physical plant at various flight conditions to test control law effectiveness. This paper will present an overview of the test article development, a description of RCAS, an explanation of the GPC methodology, and results of GPC being applied to state-space plant estimates of the TRAST model. In these simulations, GPC was effective at stabilizing the aircraft beyond the whirl-flutter boundary while simultaneously reducing vibrations across the flight regime. Additionally, a modern advancement to GPC, termed advanced GPC (AGPC), is introduced that enables a self-adapting system identification. Preliminary results show that AGPC is successful at self-correction as the plant changes from what was used for system identification.
A temperature dependent fatigue failure criterion for graphite/epoxy laminates
A fatigue failure criterion applicable to composite materials is developed and applied to predict the fatigue behavior of graphite/epoxy laminates with particular emphasis on the influence of temperature. Tensile stress-strain curves and tension-tension fatigue curves for various unidirectional, angle-ply and symmetrically balanced laminates were developed at test temperatures of 25 C, 74 C, and 114 C. For most laminates a reduction in both static strength and fatigue strength is observed with increasing temperature. This reduction appeared more severe in fatigue loading than in static tensile loading and most severe where the shear stress in the lamina is the dominate failure mode. Through an analytical formulation of shifting functions for the influences of temperature, all fatigue data are shown to be capable of being reduced to a single reference curve at some temperature. Examples are given which demonstrate the capability of the fatigue failure criterion to predict failure of complex symmetrically balanced laminates from relevant parameters obtained from the observed behavior of unidirectional and angle-ply laminates.
An analysis of energy deposition in a tissue equivalent proportional counter onboard the space shuttle
An improved prediction for space radiations in the lower earth orbits measured by the shuttle TEPC is obtained when energy loss straggling and chord length distribution of the detector are considered. A generalized analytic model is used to describe the energy deposition of direct ion interaction events in a micron-size detector. The transport calculation accounting for the shuttle configuration is accomplished by using a new version of HZETRN that has been extensively verified with laboratory and flight data. The agreement of predicted and measured lineal energy spectra is within 70% for the region above 2 keV/micrometer but within a factor of 2.3 underpredicted for the region below this value. The inclusion of indirect delta ray events in the model is needed before possible causes for the underprediction below 2 keV/micrometer can be assessed.
Ground control system for the midcourse space experiment UTC clock
One goal of the Midcourse Space Experiment (MSX) spacecraft Operations Planning Center is to maintain the onboard satellite UTC clock (UTC(MSX)) to within 1 millisecond of UTC(APL) (the program requirement is 10 msec). The UTC(MSX) clock employs as its time base an APL built 5 MHz quartz oscillator, which is expected to have frequency instabilities (aging rate + drift rate + frequency offset) that will cause the clock to drift approximately two to ten milliseconds per day. The UTC(MSX) clock can be advanced or retarded by the APL MSX satellite ground control center by integer multiples of 1 millisecond. The MSX Operations Planning Center is developing software which records the drift of UTC(MSX) relative to UTC(APL) and which schedules the time of day and magnitude of UTC(MSX) clock updates up to 48 hours in advance. Because of the manner in which MSX spacecraft activities are scheduled, MSX clock updates are planned 24 to 48 hours in advance, and stored in the satellite's computer controller for later execution. Data will be collected on the drift of UTC(MSX) relative to UTC(APL) over a three to five day period. Approximately six times per day, the time offset between UTC(MSX) and UTC(APL) will be measured by APL with a resolution of less than 100 microseconds. From this data a second order analytical model of the clock's drift will be derived. This model will be used to extrapolate the offset of the MSX clock in time from the present to 48 hours in the future. MSX clock updates will be placed on the spacecraft's daily schedule whenever the predicted clock offset exceeds 0.5 milliseconds. The paper includes a discussion of how the empirical model of the MSX clock is derived from satellite telemetry data, as well as the algorithm used to schedule MSX clock updates based on the model.
Emphasizing Spectrum Management for Sustainable Development Research and Applications in Disaster Management
NASA's spaceborne Earth and Heliospheric Observatories and airborne sensors provide a plethora of measurements. These measurements are used in science research to understand the climatology of our home planet and the solar fluxes and cycle of the only star in our solar system 'Sun' which is critical driver for the retention of life on Earth. Specifically, these measurements help us to understand the water and energy cycle, the carbon cycle, weather and climate, atmospheric chemistry, solar variability, and solid Earth and interior to feed into sophisticated mathematical models to analyze and predict the Earth's behavior as an integrated system. The main thrust of this research is on improving the prediction capability in the areas of weather, long term climate and solid Earth processes, and further help the humanity and future generations in terms of societal benefits in managing natural disasters, sustainability issues and many more. This work is further linked with our contributions in the Global Earth Observing System of Systems (GEOSS) Specifically, the data and knowledge resulting from the Earth observing systems and analytical models of the Earth can be made available for assimilation into decision support systems to serve society for disaster management. Through partnerships with national and international agencies and organizations, NASA's Science Mission Directorate's, Applied Sciences Program contributes to benchmarking practical uses of observations and predictions from Earth science remote sensing systems research. The objective is to establish innovative solutions using Earth observations and science information to provide decision support that can be adapted in applications of national and international priority. We along with the international community will continue this critical field of investigation by using our existing and future sensors from space, airborne and insitue environment. In our quest to expanding our knowledge, there will be a need for deploying additional sensors to obtain high spatial, temporal and spectral resolution measurements. These sensors operate in multiple spectral band ranging from UV, visible, infrared, microwave and radio frequency ranges. Of a particular concern is the microwave frequency bands which play a key role in land, ocean, moisture sensing. This is because of a growing commercial demand in the area of high speed broadband communication all over the world, the electronic manufacturers are looking into high frequency microwave spectral bands. This may present a risk to the remote sensing sensors because of additional sources of noise that can impair the highly sensitive passive remote sensing instruments.
Improvements to a Response Surface Thermal Model for Orion Mated to the International Space Station
This study is an extension of previous work to evaluate the applicability of Design of Experiments (DOE)/Response Surface Methodology to on-orbit thermal analysis. The goal was to determine if the methodology could produce a Response Surface Equation (RSE) that predicted the thermal model temperature results within +/-10 F. An RSE is a polynomial expression that can then be used to predict temperatures for a defined range of factor combinations. Based on suggestions received from the previous work, this study used a model with simpler geometry, considered polynomials up to fifth order, and evaluated orbital temperature variations to establish a minimum and maximum temperature for each component. A simplified Outer Mold Line (OML) thermal model of the Orion spacecraft was used in this study. The factors chosen were the vehicle's Yaw, Pitch, and Roll (defining the on-orbit attitude), the Beta angle (restricted to positive beta angles from 0 to 75), and the environmental constants (varying from cold to hot). All factors were normalized from their native ranges to a non-dimensional range from -1.0 to 1.0. Twenty-three components from the OML were chosen and the minimum and maximum orbital temperatures were calculated for each to produce forty-six responses for the DOE model. A customized DOE case matrix of 145 analysis cases was developed which used analysis points at the factor corners, mid-points, and center. From this data set, RSE s were developed which consisted of cubic, quartic, and fifth order polynomials. The results presented are for the fifth order RSE. The RSE results were then evaluated for agreement with the analytical model predictions to produce a +/-3(sigma) error band. Forty of the 46 responses had a +/-3(sigma) value of 10 F or less. Encouraged by this initial success, two additional sets of verification cases were selected. One contained 20 cases, the other 50 cases. These cases were evaluated both with the fifth order RSE and with the analytical model. For the maximum temperature predictions, 12 of the 23 components had all predictions within +/-10 F and 17 were within +/-20 F. For the minimum temperature predictions, only 4 of the 23 components (the four radiator temperatures), were within the 10 F goal. The maximum temperature RSEs were then run through 59,049 screening cases. The RSE predictions were then filtered to find 55 cases that produced the hottest temperatures. These 55 cases were then analyzed using the thermal model and the results compared against the RSE predictions. As noted earlier, 12 of the 23 responses were within +/-10 F at 17 within +/-20 F. These results demonstrate that if properly formulated, an RSE can provide a reliable, fast temperature prediction. Despite this progress, additional work is needed to determine why the minimum temperatures responses and 6 of the hot temperature responses did not produce reliable RSEs. Recommend focus areas are the model itself (arithmetic vs. diffusion nodes) and seeking consultations with statistical application experts.
Effect of crossflow velocity on the generation of lift fan jet noise in VTOL aircraft
Analytical studies based on a turbulent mixing noise prediction technique indicate that jet noise power levels are increased when a jet is situated in a crossflow. V/STOL model transport acoustic test data obtained in the NASA Ames 40 ft. x 80 ft. wind tunnel confirmed this jet noise power level increase due to crossflow. Increases up to 6 db at a Strouhal number of 2.5 and crossflow velocity to jet velocity ratio of 0.58 were observed. The power level increases observed in the experimental data confirm the predicted power level increases.
Orbit transfer rocket engine technology program
An advanced near term (1990's) space-based Orbit Transfer Vehicle Engine (OTVE) system was designed, and the technologies applicable to its construction, maintenance, and operations were developed under Tasks A through F of the Orbit Transfer Rocket Engine Technology Program. Task A was a reporting task. In Task B, promising OTV turbomachinery technologies were explored: two stage partial admission turbines, high velocity ratio diffusing crossovers, soft wear ring seals, advanced bearing concepts, and a rotordynamic analysis. In Task C, a ribbed combustor design was developed. Possible rib and channel geometries were chosen analytically. Rib candidates were hot air tested and laser velocimeter boundary layer analyses were conducted. A channel geometry was also chosen on the basis of laser velocimeter data. To verify the predicted heat enhancement effects, a ribbed calorimeter spool was hot fire tested. Under Task D, the optimum expander cycle engine thrust, performance and envelope were established for a set of OTV missions. Optimal nozzle contours and quick disconnects for modularity were developed. Failure Modes and Effects Analyses, maintenance and reliability studies and component study results were incorporated into the engine system. Parametric trades on engine thrust, mixture ratio, and area ratio were also generated. A control system and the health monitoring and maintenance operations necessary for a space-based engine were outlined in Task E. In addition, combustor wall thickness measuring devices and a fiberoptic shaft monitor were developed. These monitoring devices were incorporated into preflight engine readiness checkout procedures. In Task F, the Integrated Component Evaluator (I.C.E.) was used to demonstrate performance and operational characteristics of an advanced expander cycle engine system and its component technologies. Sub-system checkouts and a system blowdown were performed. Short transitions were then made into main combustor ignition and main stage operation.
Monte Carlo Radiation Analysis of a Spacecraft Radioisotope Power System
A Monte Carlo statistical computer analysis was used to create neutron and photon radiation predictions for the General Purpose Heat Source Radioisotope Thermoelectric Generator (GPHS RTG). The GPHS RTG is being used on several NASA planetary missions. Analytical results were validated using measured health physics data.
Development of an On-board Failure Diagnostics and Prognostics System for Solid Rocket Booster
We develop a case breach model for the on-board fault diagnostics and prognostics system for subscale solid-rocket boosters (SRBs). The model development was motivated by recent ground firing tests, in which a deviation of measured time-traces from the predicted time-series was observed. A modified model takes into account the nozzle ablation, including the effect of roughness of the nozzle surface, the geometry of the fault, and erosion and burning of the walls of the hole in the metal case. The derived low-dimensional performance model (LDPM) of the fault can reproduce the observed time-series data very well. To verify the performance of the LDPM we build a FLUENT model of the case breach fault and demonstrate a good agreement between theoretical predictions based on the analytical solution of the model equations and the results of the FLUENT simulations. We then incorporate the derived LDPM into an inferential Bayesian framework and verify performance of the Bayesian algorithm for the diagnostics and prognostics of the case breach fault. It is shown that the obtained LDPM allows one to track parameters of the SRB during the flight in real time, to diagnose case breach fault, and to predict its values in the future. The application of the method to fault diagnostics and prognostics (FD&P) of other SRB faults modes is discussed.
Quantum Leap: Evaluating the Feasibility of Quantum Machine Learning Using NASA Earth Observational Data
This study explores the feasibility of leveraging quantum machine learning (QML) to analyze NASA Earth Observational (EO) data for climate change research, with a particular focus on the phenomenon of ”crop frosting” which has become more prevalent due to climate change. We implemented and evaluated two QML models, the Variational Quantum Classifier (VQC) and Quantum Support Vector Classifier (QSVC), in both simulated and real quantum computing environments using a 127 qubit IBM quantum processor. Our study emphasizes the scientific rigor in comparing these quantum models with a classical Support Vector Machine (SVM) classifier, highlighting their performance in processing climate data. The results offer valuable insights into the potential scientific advantages, limitations, and scalability of QML for analyzing EO datasets, thus paving the way for more advanced climate modeling and predictive analytics using quantum computing. We showcased how Environmental Interaction Knowledge Graphs (EIKGs) and Digital Twins (DTs) can be integrated into this study. This research underscores the transformative potential of Classical and QML leveraging KGs and DT to address the multifaceted challenges posed by climate change.
An integrated radiation physics computer code system.
An integrated computer code system for the semi-automatic and rapid analysis of experimental and analytic problems in gamma photon and fast neutron radiation physics is presented. Such problems as the design of optimum radiation shields and radioisotope power source configurations may be studied. The system codes allow for the unfolding of complex neutron and gamma photon experimental spectra. Monte Carlo and analytic techniques are used for the theoretical prediction of radiation transport. The system includes a multichannel pulse-height analyzer scintillation and semiconductor spectrometer coupled to an on-line digital computer with appropriate peripheral equipment. The system is geometry generalized as well as self-contained with respect to material nuclear cross sections and the determination of the spectrometer response functions. Input data may be either analytic or experimental.
A temperature dependent fatigue failure criterion for graphite/epoxy laminates
A fatigue failure criterion applicable to composite materials is developed and applied to predict the fatigue behavior of graphite/epoxy laminates with particular emphasis on the influence of temperature. Tensile stress-strain curves and tension-tension fatigue curves for various unidirectional, angle-ply and symmetrically balanced laminates were developed at test temperatures of 25 C, 74 C and 114 C. In general for most laminates a reduction in both static strength and fatigue strength is observed with increasing temperature. This reduction appeared more severe in fatigue loading than in static tensile loading and most severe where the shear stress in the lamina is the dominant failure mode. Through an analytical formulation of shifting functions for the influences of temperature, all fatigue data are shown to be capable of being reduced to a single reference curve at some temperature. Additionally, examples are given which demonstrate the capability of the fatigue failure criterion to predict failure of complex symmetrically balanced laminates from relevant parameters obtained from the observed behavior of unidirectional and angle-ply laminates.
Acoustic space occupancy: Combining ecoacoustics and lidar to model biodiversity variation and detection bias across heterogeneous landscapes
There is global interest in quantifying changing biodiversity in human-modified landscapes. Ecoacoustics may offer a promising pathway for supporting multi-taxa monitoring, but its scalability has been hampered by the sonic complexity of biodiverse ecosystems and the imperfect detectability of animal-generated sounds. The acoustic signature of a habitat, or soundscape, contains information about multiple taxa and may circumvent species identification, but robust statistical technology for characterizing community-level attributes is lacking. Here, we present the Acoustic Space Occupancy Model, a flexible hierarchical framework designed to account for detection artifacts from acoustic surveys in order to model biologically relevant variation in acoustic space use among community assemblages. We illustrate its utility in a biologically and structurally diverse Amazon frontier forest landscape, a valuable test case for modeling biodiversity variation and acoustic attenuation from vegetation density. We use complementary airborne lidar data to capture aspects of 3D forest structure hypothesized to influence community composition and acoustic signal detection. Our novel analytic framework permitted us to model both the assembly and detectability of soundscapes using lidar-derived estimates of forest structure. Our empirical predictions were consistent with physical models of frequency-dependent attenuation, and we estimated that the probability of observing animal activity in the frequency channel most vulnerable to acoustic attenuation varied by over 60%, depending on vegetation density. There were also large differences in the biotic use of acoustic space predicted for intact and degraded forest habitats, with notable differences in the soundscape channels predominantly occupied by insects. This study advances the utility of ecoacoustics by providing a robust modeling framework for addressing detection bias from remote audio surveys while preserving the rich dimensionality of soundscape data, which may be critical for inferring biological patterns pertinent to multiple taxonomic groups in the tropics. Our methodology paves the way for greater integration of remotely sensed observations with high-throughput biodiversity data to help bring routine, multi-taxa monitoring to scale in dynamic and diverse landscapes.
A new experimental method for the accelerated characterization of composite materials
A method which permits the prediction of long-term properties of graphite/epoxy laminates on the basis of short-term (15 min) laboratory tests is described. Demonstration of delayed viscoelastic fracture in one laminate configuration, and data on the time and temperature response of a matrix-dominated unidirectional laminate contributed to a characterization of the viscoelastic process in the graphite/epoxy composites. Master curves from short-term tests of certain laminate configurations can be employed to generate long-term master curves. In addition, analytical predictions from short-term results can be used to predict long-term (25-hour) laminate properties.
Analytic model for assessing thermal performance of SCUBA divers
To assist design of adequate protective clothing, mathematical model of man's thermoregulatory system has been developed so that body thermal responses under immersed conditions can be predicted accurately. Experimental data encompassed wide range of water temperatures, protective clothing, breathing-gas mixtures, and durations of immersion.
Integration of Condition-Based, Diagnostic, Prognostic, And Anomaly Detection Data into Reliability Models to Support a Predictive Maintenance Context
Reliability data employed in plant reliability models are an approximated integral representation of the past industrywide operational experience, and they neglect the present asset health status (available, for example, from online monitoring data and diagnostic assessments) and forecasted health projection (when available from prognostic models). Ideally, in a predictive maintenance context, system reliability models should support decision making by propagating actual health information from the asset to the system level in order to provide a quantitative snapshot of system health and identify the most critical assets. Asset health should be informed solely by that specific asset’s current and historical performance data and should not be an approximated integral representation of the past industrywide operational experience (as currently performed by system reliability models through Bayesian updating processes). This paper proposes a reliability modeling approach that relies on asset diagnostic and prognostic assessments, along with monitoring data to measure asset health. We show how state-of-the art condition-based, diagnostic, prognostic, and anomaly detection models can be linked to system reliability models not in probability terms, but in terms of margin where margin is defined as the “distance” between the present status and an undesired event (e.g., failure or unacceptable performance). Then, we show how the propagation of margin data from the asset to the system level is performed through classical reliability models such as fault trees or reliability block diagrams. The described method is in fact able to propagate heterogenous health data from the asset to the system level in order to analytically assess system health.