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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Measurement Techniques and Instruments Suitable for Life-prediction Testing of Photovoltaic Arrays

The validation of a 20-year service life for low-cost photovoltaic arrays is a critical requirement in the Low-Cost Solar Array (LSA) Project. The validation is accomplished through accelerated life-prediction tests. A two-phase study was conducted to address the needs before such tests are carried out. The results and recommended techniques from the Phase 1 investigation are summarized in the appendix. Phase 2 of the study is covered in this report and consisted of experimental evaluations of three techniques selected from these recommended as a results of the Phase 1 findings. The three techniques evaluated were specular and nonspecular optical reflectometry, chemiluminescence measurements, and electric current noise measurements.

Noel, G. T.↗
NASA NTRS2010

Confidence-Based Feature Acquisition

Confidence-based Feature Acquisition (CFA) is a novel, supervised learning method for acquiring missing feature values when there is missing data at both training (learning) and test (deployment) time. To train a machine learning classifier, data is encoded with a series of input features describing each item. In some applications, the training data may have missing values for some of the features, which can be acquired at a given cost. A relevant JPL example is that of the Mars rover exploration in which the features are obtained from a variety of different instruments, with different power consumption and integration time costs. The challenge is to decide which features will lead to increased classification performance and are therefore worth acquiring (paying the cost). To solve this problem, CFA, which is made up of two algorithms (CFA-train and CFA-predict), has been designed to greedily minimize total acquisition cost (during training and testing) while aiming for a specific accuracy level (specified as a confidence threshold). With this method, it is assumed that there is a nonempty subset of features that are free; that is, every instance in the data set includes these features initially for zero cost. It is also assumed that the feature acquisition (FA) cost associated with each feature is known in advance, and that the FA cost for a given feature is the same for all instances. Finally, CFA requires that the base-level classifiers produce not only a classification, but also a confidence (or posterior probability).

Wagstaff, Kiri L.↗
NASA NTRS1984

An emulator for minimizing computer resources for finite element analysis

A computer code, SCOPE, has been developed for predicting the computer resources required for a given analysis code, computer hardware, and structural problem. The cost of running the code is a small fraction (about 3 percent) of the cost of performing the actual analysis. However, its accuracy in predicting the CPU and I/O resources depends intrinsically on the accuracy of calibration data that must be developed once for the computer hardware and the finite element analysis code of interest. Testing of the SCOPE code on the AMDAHL 470 V/8 computer and the ELAS finite element analysis program indicated small I/O errors (3.2 percent), larger CPU errors (17.8 percent), and negligible total errors (1.5 percent).

Melosh, R.↗
NASA NTRS2009

Structural Dynamic Behavior of Wind Turbines

The structural dynamicist s areas of responsibility require interaction with most other members of the wind turbine project team. These responsibilities are to predict structural loads and deflections that will occur over the lifetime of the machine, ensure favorable dynamic responses through appropriate design and operational procedures, evaluate potential design improvements for their impact on dynamic loads and stability, and correlate load and control test data with design predictions. Load prediction has been a major concern in wind turbine designs to date, and it is perhaps the single most important task faced by the structural dynamics engineer. However, even if we were able to predict all loads perfectly, this in itself would not lead to an economic system. Reduction of dynamic loads, not merely a "design to loads" policy, is required to achieve a cost-effective design. The two processes of load prediction and structural design are highly interactive: loads and deflections must be known before designers and stress analysts can perform structural sizing, which in turn influences the loads through changes in stiffness and mass. Structural design identifies "hot spots" (local areas of high stress) that would benefit most from dynamic load alleviation. Convergence of this cycle leads to a turbine structure that is neither under-designed (which may result in structural failure), nor over-designed (which will lead to excessive weight and cost).

Thresher, Robert W.↗
NASA NTRS1987

A quantum theoretical study of polyimides

One of the most important contributions of theoretical chemistry is the correct prediction of properties of materials before any costly experimental work begins. This is especially true in the field of electrically conducting polymers. Development of the Valence Effective Hamiltonian (VEH) technique for the calculation of the band structure of polymers was initiated. The necessary VEH potentials were developed for the sulfur and oxygen atoms within the particular molecular environments and the explanation explored for the success of this approximate method in predicting the optical properties of conducting polymers.

Burke, Luke A.↗
NASA NTRS1998

Automated System Checkout to Support Predictive Maintenance for the Reusable Launch Vehicle

The Propulsion Checkout and Control System (PCCS) is a predictive maintenance software system. The real-time checkout procedures and diagnostics are designed to detect components that need maintenance based on their condition, rather than using more conventional approaches such as scheduled or reliability centered maintenance. Predictive maintenance can reduce turn-around time and cost and increase safety as compared to conventional maintenance approaches. Real-time sensor validation, limit checking, statistical anomaly detection, and failure prediction based on simulation models are employed. Multi-signal models, useful for testability analysis during system design, are used during the operational phase to detect and isolate degraded or failed components. The TEAMS-RT real-time diagnostic engine was developed to utilize the multi-signal models by Qualtech Systems, Inc. Capability of predicting the maintenance condition was successfully demonstrated with a variety of data, from simulation to actual operation on the Integrated Propulsion Technology Demonstrator (IPTD) at Marshall Space Flight Center (MSFC). Playback of IPTD valve actuations for feature recognition updates identified an otherwise undetectable Main Propulsion System 12 inch prevalve degradation. The algorithms were loaded into the Propulsion Checkout and Control System for further development and are the first known application of predictive Integrated Vehicle Health Management to an operational cryogenic testbed. The software performed successfully in real-time, meeting the required performance goal of 1 second cycle time.

Patterson-Hine, Ann↗
NASA NTRS1973

Q-FANSTM for general aviation aircraft

Continued growth of general aviation over the next 10 to 15 years is dependent on continuing improvement in aircraft safety, utility, performance and cost. Moreover, these advanced aircraft will need to conform to expected government regulations controlling propulsion system emissions and noise levels. An attractive compact low noise propulsor concept, the Q-FANTM when matched to piston, rotary combustion, or gas turbine engines opens up the exciting prospect of new, cleaner airframe designs for the next generation of general aviation aircraft which will provide these improvements and meet the expected noise and pollution restriction of the 1980 time period. New Q-FAN methodology which was derived to predict Q-FAN noise, weight and cost is presented. Based on this methodology Q-FAN propulsion system performance, weight, noise, and cost trends are discussed. Then the impact of this propulsion system type on the complete aircraft is investigated for several representative aircraft size categories. Finally, example conceptual designs for Q-FAN/engine integration and aircraft installations are presented.

Worobel, R.↗
NASA NTRS1993

The NASA/industry Design Analysis Methods for Vibrations (DAMVIBS) program : Bell Helicopter Textron accomplishments

Accurate vibration prediction for helicopter airframes is needed to 'fly from the drawing board' without costly development testing to solve vibration problems. The principal analytical tool for vibration prediction within the U.S. helicopter industry is the NASTRAN finite element analysis. Under the NASA DAMVIBS research program, Bell conducted NASTRAN modeling, ground vibration testing, and correlations of both metallic (AH-1G) and composite (ACAP) airframes. The objectives of the program were to assess NASTRAN airframe vibration correlations, to investigate contributors to poor agreement, and to improve modeling techniques. In the past, there has been low confidence in higher frequency vibration prediction for helicopters that have multibladed rotors (three or more blades) with predominant excitation frequencies typically above 15 Hz. Bell's findings under the DAMVIBS program, discussed in this paper, included the following: (1) accuracy of finite element models (FEM) for composite and metallic airframes generally were found to be comparable; (2) more detail is needed in the FEM to improve higher frequency prediction; (3) secondary structure not normally included in the FEM can provide significant stiffening; (4) damping can significantly affect phase response at higher frequencies; and (5) future work is needed in the areas of determination of rotor-induced vibratory loads and optimization.

Cronkhite, James D.↗
NASA NTRS1995

Integrated Logistics Support Analysis of the International Space Station Alpha, Background and Summary of Mathematical Modeling and Failure Density Distributions Pertaining to Maintenance Time Dependent Parameters

The process of predicting the values of maintenance time dependent variable parameters such as mean time between failures (MTBF) over time must be one that will not in turn introduce uncontrolled deviation in the results of the ILS analysis such as life cycle costs, spares calculation, etc. A minor deviation in the values of the maintenance time dependent variable parameters such as MTBF over time will have a significant impact on the logistics resources demands, International Space Station availability and maintenance support costs. There are two types of parameters in the logistics and maintenance world: a. Fixed; b. Variable Fixed parameters, such as cost per man hour, are relatively easy to predict and forecast. These parameters normally follow a linear path and they do not change randomly. However, the variable parameters subject to the study in this report such as MTBF do not follow a linear path and they normally fall within the distribution curves which are discussed in this publication. The very challenging task then becomes the utilization of statistical techniques to accurately forecast the future non-linear time dependent variable arisings and events with a high confidence level. This, in turn, shall translate in tremendous cost savings and improved availability all around.

Sepehry-Fard, F.↗
NASA NTRS1966

The adaptive prediction of time series.

Adaptive technique determination of optimum operations for pure prediction of discrete time series with respect to mean square error cost function

GAUSSIAN DISTRIBUTION↗
NASA NTRSDate not supplied

On the Application of an Actuator Line Model for Rotorcraft Outwash Predictions

As the next generation of Vertical Take-Off and Landing (VTOL) vehicles develops and the VTOL industry makes significant progress in utilizing them for public transportation, it is crucial to have validated and cost-effective computational models accessible to both industry professionals and academics in the rotorcraft community. This study investigates the implementation of a new actuator line model within NASA’s OVERFLOW computational fluid dynamics (CFD) solver, with a focus on predicting rotorcraft outwash. This reduced-order rotor model was developed to provide reasonably accurate outwash predictions while reducing computational costs compared to traditional blade-resolved CFD simulations. To validate the actuator line model for outwash predictions, the model was compared against existing experimental data across three validation cases: single rotor Out-of-Ground Effect (OGE), single rotor In-Ground Effect (IGE), and tandem rotor IGE. All three cases were based on the rotor geometry and configuration of the CH-47D. To evaluate the feasibility and advantages of using an actuator line model for outwash predictions the results were compared to a series of high-fidelity blade-resolved CFD simulations as well as comprehensive analyses simulations based on CHARM predictions. The results of this study demonstrate the feasibility of leveraging this new actuator line model for reasonably accurate outwash predictions. The outwash results obtained from the actuator line model closely matched those from high-fidelity blade-resolved simulations while significantly reducing the overall computational costs of the simulations. Results from this study further demonstrated the feasibility of using CHARM for efficient, and reasonably accurate time-averaged outwash predictions for multi-rotor configurations.

CFD↗
NASA NTRS1999

International Low-Earth-Orbit Spacecraft Materials Test Program Initiated for Better Prediction of Durability and Performance

Spacecraft in low Earth orbit (LEO) are subjected to many components of the environment, which can cause them to degrade much more rapidly than intended and greatly shorten their functional life. The atomic oxygen, ultraviolet radiation, and cross contamination present in LEO can affect sensitive surfaces such as thermal control paints, multilayer insulation, solar array surfaces, and optical surfaces. The LEO Spacecraft Materials Test (LEO-SMT) program is being conducted to assess the effects of simulated LEO exposure on current spacecraft materials to increase understanding of LEO degradation processes as well as to enable the prediction of in-space performance and durability. Using ground-based simulation facilities to test the durability of materials currently flying in LEO will allow researchers to compare the degradation evidenced in the ground-based facilities with that evidenced on orbit. This will allow refinement of ground laboratory test systems and the development of algorithms to predict the durability and performance of new materials in LEO from ground test results. Accurate predictions based on ground tests could reduce development costs and increase reliability. The wide variety of national and international materials being tested represent materials being functionally used on spacecraft in LEO. The more varied the types of materials tested, the greater the probability that researchers will develop and validate predictive models for spacecraft long-term performance and durability. Organizations that are currently participating in the program are ITT Research Institute (USA), Lockheed Martin (USA), MAP (France), SOREQ Nuclear Research Center (Israel), TNO Institute of Applied Physics (The Netherlands), and UBE Industries, Ltd. (Japan). These represent some of the major suppliers of thermal control and sensor materials currently flying in LEO. The participants provide materials that are exposed to selected levels of atomic oxygen, vacuum ultraviolet radiation, contamination, or synergistic combined environments at the NASA Lewis Research Center. Changes in characteristics that could affect mission performance or lifetime are then measured. These characteristics include changes in mass, solar absorptance, and thermal emittance. The durability of spacecraft materials from U.S. suppliers is then compared with those of materials from other participating countries. Lewis will develop and validate performance and durability prediction models using this ground data and available space data. NASA welcomes the opportunity to consider additional international participants in this program, which should greatly aid future spacecraft designers as they select materials for LEO missions.

Rutledge, Sharon K.↗
NASA NTRS1991

Energy requirements for the space frontier

The cost of delivering payloads to Mars orbital locations from LEO is determined and future launch cost reductions are projected. The performance necessary for future solar and nuclear space power options is predicted, categorizing the needs as survival, self-sufficiency, and industralization. The cost of present space power systems is determined and projections are made for future systems.

Brandhorst, Henry W., Jr.↗
NASA NTRS2002

Prediction of Aerodynamic Coefficient using Genetic Algorithm Optimized Neural Network for Sparse Data

Wind tunnels use scale models to characterize aerodynamic coefficients, Wind tunnel testing can be slow and costly due to high personnel overhead and intensive power utilization. Although manual curve fitting can be done, it is highly efficient to use a neural network to define the complex relationship between variables. Numerical simulation of complex vehicles on the wide range of conditions required for flight simulation requires static and dynamic data. Static data at low Mach numbers and angles of attack may be obtained with simpler Euler codes. Static data of stalled vehicles where zones of flow separation are usually present at higher angles of attack require Navier-Stokes simulations which are costly due to the large processing time required to attain convergence. Preliminary dynamic data may be obtained with simpler methods based on correlations and vortex methods; however, accurate prediction of the dynamic coefficients requires complex and costly numerical simulations. A reliable and fast method of predicting complex aerodynamic coefficients for flight simulation I'S presented using a neural network. The training data for the neural network are derived from numerical simulations and wind-tunnel experiments. The aerodynamic coefficients are modeled as functions of the flow characteristics and the control surfaces of the vehicle. The basic coefficients of lift, drag and pitching moment are expressed as functions of angles of attack and Mach number. The modeled and training aerodynamic coefficients show good agreement. This method shows excellent potential for rapid development of aerodynamic models for flight simulation. Genetic Algorithms (GA) are used to optimize a previously built Artificial Neural Network (ANN) that reliably predicts aerodynamic coefficients. Results indicate that the GA provided an efficient method of optimizing the ANN model to predict aerodynamic coefficients. The reliability of the ANN using the GA includes prediction of aerodynamic coefficients to an accuracy of 110% . In our problem, we would like to get an optimized neural network architecture and minimum data set. This has been accomplished within 500 training cycles of a neural network. After removing training pairs (outliers), the GA has produced much better results. The neural network constructed is a feed forward neural network with a back propagation learning mechanism. The main goal has been to free the network design process from constraints of human biases, and to discover better forms of neural network architectures. The automation of the network architecture search by genetic algorithms seems to have been the best way to achieve this goal.

Rajkumar, T.↗
NASA NTRS1979

JT8D and JT9D jet engine performance improvement program. Task 1: Feasibility analysis

JT8D and JT9D component performance improvement concepts which have a high probability of incorporation into production engines were identified and ranked. An evaluation method based on airline payback period was developed for the purpose of identifying the most promising concepts. The method used available test data and analytical models along with conceptual/preliminary designs to predict the performance improvements, weight, installation characteristics, cost for new production and retrofit, maintenance cost, and qualitative characteristics of candidate concepts. These results were used to arrive at the concept payback period, which is the time required for an airline to recover the investment cost of concept implementation.

Gaffin, W. O.↗
NASA NTRS1981

Radio frequency interference at the geostationary orbit

Growing demands on the frequency spectrum have increased the possibility of radio frequency interference (RFI). Various approaches to obtain in orbit RFI data are compared; this comparision indicates that the most practical way to obtain RFI data for a desired orbit (such as a geostationary orbit) is through the extrapolation of in orbit RFI measurements by a low orbit satellite. It is concluded that a coherent RFI program that uses both experimental data and analytical predictions provides accurate RFI data at minimal cost.

Sue, M. K.↗
NASA NTRS1981

Carbon/graphite composite material study. 3: Agency program activities. National Aeronautics and Space Administration (NASA)

The accidental release of carbon fibers from civil aircraft and the need for protection of civil aircraft systems from such fibers were studied. It was concluded that the electrical hazard from carbon fibers accidentally released in an aircraft crash fire pose no threat to human life. Overall costs associated with carbon fiber release are predicted to be extremely low. The risk of electrical or electronic failures due to carbon fibers is so minimal that future exploitation of carbon composites in aircraft should be continued. Additional protection of aircraft avionics to guard against carbon fibers is unnecessary. A program to develop alternate materials specifically to overcome the potential electrical hazard is not justified.

Source record↗