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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Flight survey of the 757 wing noise field and its effects on laminar boundary layer transition. Volume 2: Data compilation

A flight test program was performed using the Boeing 757 flight research airplane to investigate the effect of noise from wing mounted engines on laminar boundary layer transition. An NLF glove was installed on the right wing panel just outboard of the engine. The extent of laminar flow on the glove was measured as a function of engine power setting for a range of flight conditions. A combination of surface and probe microphones was distributed over the upper and lower wing surfaces to measure sound spectra. The flight test program was completed in June 1985 and the results of preliminary analysis indicate that a maximum of about 29 percent of chord laminar flow was obtained on the upper surface and about 28 percent on the lower surface (at a high sideslip condition). The engine speed was varied from about 2600 (idle) to about 4500 (maximum continuous power) r/min. This produced changes in sound pressure level up to 20 dB on the lower surface. On the upper surface, the noise levels were independent of engine power but sensitive to airplane Mach number. No effect of engine power setting on upper surface transition location was observed, and only a small forward movement of the transition location on the lower surface was observed at the high power settings. Volume 1 of this report contains the program description and data analysis. Volume 2 is a compilation of all of the flight test data.

Source record↗
NASA NTRS1992

Automatic differentiation as a tool in engineering design

Automatic Differentiation (AD) is a tool that systematically implements the chain rule of differentiation to obtain the derivatives of functions calculated by computer programs. AD is assessed as a tool for engineering design. The forward and reverse modes of AD, their computing requirements, as well as approaches to implementing AD are discussed. The application of two different tools to two medium-size structural analysis problems to generate sensitivity information typically necessary in an optimization or design situation is also discussed. The observation is made that AD is to be preferred to finite differencing in most cases, as long as sufficient computer storage is available; in some instances, AD may be the alternative to consider in lieu of analytical sensitivity analysis.

Barthelemy, Jean-Francois↗
NASA NTRS1993

Precise navigation for the Earth Observing System (EOS)-AM1 spacecraft using the TDRSS Onboard Navigation System (TONS)

As the baseline navigation system for the Earth Observing System (EOS)-AM1 spacecraft, the Tracking and Data Relay Satellite System (TDRSS) Onboard Navigation System (TONS) is required to provide precise position and velocity information for imaging instrument calibration and routine operations. This paper presents the results of real-time navigation performance evaluations with respect to TONS-based orbit and frequency determination to satisfy this requirement. Both covariance and simulation analysis of EOS-AM1 navigation accuracy and analysis using operational data from Landsat-4 are presented. Local (half orbit) and global (multiple orbits) tracking are considered using a way-forward link services. Improvements in navigation accuracies by using enhanced gravity models beyond the Goddard Earth Model (GEM)-T3 are also discussed. Key objectives of the analysis are to evaluate nominal performance and potential sensitivities and to address algorithm improvements such as TDRS ephemeris biasing, ionosphere model, and gravity process noise models slated for implementation. Results indicate that TONS can be configured to meet the proposed instrument navigation requirements of 20 meters, 3-sigma.

Folta, David C.↗
NASA NTRS2016

Determining the 3D Subsurface Density Structure of Taurus Littrow Valley Using Apollo 17 Gravity Data

Surface gravity surveys can detect subsurface density variations that can reveal subsurface geologic features. In 1972, the Apollo 17 (A17) mission conducted the Traverse Gravimeter Experiment (TGE) using a gravimeter that measured the local gravity field near Taurus Littrow Valley (TLV), located on the south-eastern rim of the Serenitatis basin. TLV is hypothesized to be a basaltfilled radial graben resulting from the impact that formed Mare Serenitatis. It is bounded by both the North and South Massifs (NM and SM) as well as other smaller mountains to the East that are thought to be mainly composed of brecciated highland material. The TGE is the first and only successful gravity survey on the surface of the Moon. Other more recent satellite surveys, such as NASA's Gravity Recovery and Interior Laboratory (GRAIL) mission (2011- 2012), have produced the best global gravity field to date (approx. 13km resolution). However, these satellite surveys are not sensitive enough to detect fine-scale (<1km) lunar subsurface structures. This underscores the value of the data collected at the surface by A17. In the original analysis of the data a 2D forward-modelling approach was used to derive a thickness of the subsurface basalt layer of 1.0 km by assuming a simple flat-faced rectangular geometry and using densities derived from Apollo lunar samples. We are investigating whether modern 3D modelling techniques in combination with high-resolution topographical and image datasets can reveal additional fine-scale subsurface structure in TLV.

TGE↗
NASA NTRS1982

Development of a helicopter rotor/propulsion system dynamics analysis

A time-domain analysis of coupled engine/drive train/rotor dynamics of a twin-engine, single main rotor helicopter model has been performed. The analysis incorporates an existing helicopter model with nonlinear simulations of a helicopter turboshaft engine and its fuel controller. System dynamic behavior is studied using the resulting simulation which included representations for the two engines and their fuel controllers, drive system, main rotor, tail rotor, and aircraft rigid body motions. Time histories of engine and rotor RPM response to pilot control inputs are studied for a baseline rotor and propulsion system model. Sensitivity of rotor RPM droop to fuel controller gain changes and collective input feed-forward gain changes are studied. Torque-load-sharing between the two engines is investigated by making changes in the fuel controller feedback paths. A linear engine model is derived from the nonlinear engine simulation and used in the coupled system analysis. This four-state linear engine model is then reduced to a three-state model. The effect of this simplification on coupled system behavior is shown.

Warmbrodt, W.↗
DOE OSTI2016

Evaluation of multiple reduced-order models to enhance confidence in global sensitivity analyses

Variance-based global sensitivity analysis (e.g., the Sobol' sensitivity index) can be used to identify the important parameters over the entire parameter space. However, one often cannot afford the computational costs of sampling-based approaches in combination with expensive high-fidelity forward models. Reduced-order models (ROM) can substantially accelerate calculation of these sensitivities. However, it is usually difficult to determine what type of ROM should be used and how accurately the ROM represents the high-fidelity model (HFM) results. Here in this paper, we propose to concurrently use multiple ROMs as a way to assess the robustness of the model-reduction method. Two sets of HFM simulations are needed, one set for building ROMs and the other for validating ROMs. Our goal is to keep the total number of HFM simulations to a minimum. Ideally some of the HFM simulations in the first set can be shared by different ROMs. Based on validation results, the ROMs can be combined with different schemes. We demonstrate that we can achieve the goal by using four different ROMs and still considerably save computational time compared to using traditional HFM simulation for calculating sensitivity indices. We apply the approach to an example problem of a large-scale geological carbon dioxide storage system, in which the objective is to calculate a sensitivity index to identify important parameters. For this problem, the locally best ROM provides better estimates than the weighted average from all ROMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Inverse Uncertainty Quantification of Reactor Simulation with Polynomial Chaos Surrogate Model

Reliable uncertainty quantification (UQ) and sensitivity analysis (SA) is significant part of modelling and simulation. This is particularly important in the nuclear community due to the fact that the licensing of nuclear installations has shifted from conservative to Best Estimate plus Uncertainty (BEPU) methodologies. UQ can be broadly classified as forward UQ and inverse UQ. Forward UQ is the process of quantifying the uncertainties in simulation outputs by propagating the uncertainties in input parameters. It requires knowledge in the input uncertainty, which is often specified by ad-hoc expert judgment which lacks mathematical rigor. The inverse UQ is the process to determine the uncertainty in input parameters given observations of the output. The purpose of this paper is to replace such ad-hoc expert judgment of the statistical properties of input model parameters in nuclear reactor simulation. This summary presents work on inverse UQ of a nonlinear Point Reactor Kinetics Equations - lumped thermal-hydraulics parameter coupled problem. Bayesian inference and Markov Chain Monte Carlo (MCMC) are used for the inverse UQ. Because MCMC requires a large number of simulations which is impractical for models that are computationally expensive, surrogate models is constructed by generalized Polynomial Chaos (PC) expansion technique. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Second-order adjoint sensitivity analysis methodology (2ND-ASAM) for computing exactly and efficiently first- and second-order sensitivities in large-scale systems - 14356

This work presents the second-order adjoint sensitivity analysis methodology (2.-ASAM) for computing exactly and efficiently the second-order functional derivatives ('sensitivities') of system responses to the system's model parameters. For a physical system comprising N{sub α} parameters and N{sub r} responses, forward methods require a total of at least (N{sup 2}{sub α}/2+3N{sub α}/2) large-scale computations for obtaining all of the first- and second-order sensitivities, for all N{sub r} system responses. On the other hand, for one functional-type system response, the 2.-ASAM requires one large-scale computation using the first-level adjoint sensitivity system (1.-LASS) for obtaining all of the first-order sensitivities, followed by at most (2N{sub α}+1) large-scale computations using the second-level adjoint sensitivity systems (2.-LASS) for obtaining all of the second-order sensitivities. The second-order sensitivities contribute decisively to causing asymmetries in the response distribution, since they are the leading contributors to the third-order response correlations (skewness). They also cause the 'expected value of the response' to differ from the 'computed nominal value of the response'. The implementation of the 2.-ASAM requires very little additional effort beyond the construction of the adjoint sensitivity system needed for computing the first-order sensitivities. Only the sources on the right-sides of the diffusion (differential) operator needed to be modified; the left-side of the differential equations (and hence the 'solver' in large-scale practical applications) remain unchanged. The application of the 2.-ASAM is illustrated on a benchmark heat conduction/convection problem, which makes transparent the underlying mathematical derivations. For this illustrative problem, 4 'large-scale' adjoint computations suffice for computing exactly all of the 6 first- and 21 distinct second-order derivatives. The 2.-ASAM presented in this work should enable the hitherto very difficult, if not intractable, exact computation of all of the second-order response sensitivities for large-systems involving many parameters, which is expected to affect significantly other fields that need efficiently computed second-order response sensitivities, such as optimization, data assimilation/adjustment, model calibration, and predictive modeling. (author)

42 ENGINEERING↗
NASA NTRSDate not supplied

Comparison of Corcos-based and experimentally-derived coherence factors for BFFs estimation

In this paper, high-spatial-resolution unsteady Pressure Sensitive Paint (uPSP) data are utilized to compare two methods for panel Buffet Forcing Functions (BFF) estimation for the Space Launch System (SLS). Such methods are based on discrete pressure measurements within a panel but employ coherence factors to account for partially-correlated fluctuating pressures across the whole panel. In one method, coherence factors are derived based on the Corcos model, whereas the second method utilizes experimentally-derived coherence factors. To simulate discrete measurements using uPSP data, suitable subsets of the data are extracted. When full uPSP resolution is retained, uPSP data provide a benchmark to assess discrete-measurements-based methods. The analysis focuses on the peak SLS buffet environment located downstream of the Forward Attachment Hardware (FAH) between the core stage and solid rocket boosters. Trends of Corcos-based and experimentally-derived coherence factors are in reasonable agreement with the benchmark. However, at certain frequencies, experimentally-derived coherence factors are sensitive to the separation distance between pressure measurements utilized to compute coherence lengths. Such sensitivity originates from deviation of the experimental-based coherence function from an exponential decay assumption. On the other hand, the present implementation of the Corcos model fails to capture certain non-turbulent boundary layer related environments, such as a subharmonic of FAH vortex-shedding. For all methods presented in this paper, at near transonic conditions, increased pressure coherence and spatial nonuniformity lead to BFF overestimation and sensitivity to the pressure measurement location within the panel.

transonic buffet↗
NASA NTRSDate not supplied

Comparison of Corcos-Based and Experimentally-Derived Coherence Factors for Buffet Forcing Functions Estimation

In this paper, high-spatial-resolution unsteady Pressure Sensitive Paint (uPSP) data are utilized to compare two methods for panel Buffet Forcing Functions (BFF) estimation for the Space Launch System (SLS). Such methods are based on discrete pressure measurements within a panel but employ coherence factors to account for partially-correlated fluctuating pressures across the whole panel. In one method, coherence factors are derived based on the Corcos model, whereas the second method utilizes experimentally-derived coherence factors. To simulate discrete measurements using uPSP data, suitable subsets of the data are extracted. When full uPSP resolution is retained, uPSP data provide a benchmark to assess discrete-measurements-based methods. The analysis focuses on the peak SLS buffet environment located downstream of the Forward Attachment Hardware (FAH) between the core stage and solid rocket boosters. Trends of Corcos-based and experimentally-derived coherence factors are in reasonable agreement with the benchmark. However, at certain frequencies, experimentally-derived coherence factors are sensitive to the separation distance between pressure measurements utilized to compute coherence lengths. Such sensitivity originates from deviation of the experimental-based coherence function from an exponential decay assumption. On the other hand, the present implementation of the Corcos model fails to capture certain nonturbulent boundary layer related environments, such as a subharmonic of FAH vortex-shedding. For all methods presented in this paper, at near transonic conditions, increased pressure coherence and spatial nonuniformity lead to BFF overestimation and sensitivity to the pressure measurement location within the panel.

buffet↗
NASA NTRS2023

Comparison of Corcos-Based and Experimentally-Derived Coherence Factors for Buffet Forcing Function Estimation

In this paper, high-spatial-resolution unsteady Pressure Sensitive Paint (uPSP) data are utilized to compare two methods for panel Buffet Forcing Function (BFF) estimation for the Space Launch System (SLS). Such methods are based on discrete pressure measurements within a panel but employ coherence factors to account for partially-correlated fluctuating pressures across the whole panel. In one method, coherence factors are derived based on the Corcos model, whereas the second method utilizes experimentally-derived coherence factors. To simulate discrete measurements using uPSP data, suitable subsets of the data are extracted. When full uPSP resolution is retained, uPSP data provide a benchmark to assess discrete-measurement-based methods. The analysis focuses on the peak SLS buffet environment located downstream of the Forward Attachment Hardware (FAH) between the core stage and solid rocket boosters. Trends of Corcos-based and experimentally-derived coherence factors are in reasonable agreement with the benchmark. However, at certain frequencies, experimentally-derived coherence factors are sensitive to the separation distance between pressure measurements utilized to compute coherence lengths. Such sensitivity originates from deviation of the experimentally-based coherence function from an exponential decay assumption. On the other hand, the present implementation of the Corcos model fails to capture certain nonturbulent boundary layer related environments, such as a subharmonic of FAH vortex-shedding. For all methods presented in this paper, at near transonic conditions, increased pressure coherence and spatial nonuniformity lead to BFF overestimation and sensitivity to the pressure measurement location within the panel.

transonic buffet↗
NASA NTRS2012

Reusable Solid Rocket Motor - V(RSRMV)Nozzle Forward Nose Ring Thermo-Structural Modeling

During the developmental static fire program for NASAs Reusable Solid Rocket Motor-V (RSRMV), an anomalous erosion condition appeared on the nozzle Carbon Cloth Phenolic nose ring that had not been observed in the space shuttle RSRM program. There were regions of augmented erosion located on the bottom of the forward nose ring (FNR) that measured nine tenths of an inch deeper than the surrounding material. Estimates of heating conditions for the RSRMV nozzle based on limited char and erosion data indicate that the total heat loading into the FNR, for the new five segment motor, is about 40-50% higher than the baseline shuttle RSRM nozzle FNR. Fault tree analysis of the augmented erosion condition has lead to a focus on a thermomechanical response of the material that is outside the existing experience base of shuttle CCP materials for this application. This paper provides a sensitivity study of the CCP material thermo-structural response subject to the design constraints and heating conditions unique to the RSRMV Forward Nose Ring application. Modeling techniques are based on 1-D thermal and porous media calculations where in-depth interlaminar loading conditions are calculated and compared to known capabilities at elevated temperatures. Parameters such as heat rate, in-depth pressures and temperature, degree of char, associated with initiation of the mechanical removal process are quantified and compared to a baseline thermo-chemical material removal mode. Conclusions regarding postulated material loss mechanisms are offered.

Clayton, J. Louie↗
DOE OSTI2014

Study of continuous-wave domain fluorescence diffuse optical tomography for quality control on agricultural produce

The importance of monitoring the quality of vegetables and fruits is prosperity by giving a competitive advantage for producer and providing a more healthy food for consumer. Diffuse Optical Tomography (DOT) is offering the possibility to detect the internal defects of the agricultural produce quality. Fluorescence diffuse optical tomography (FDOT) is the development of DOT, offering the possibilities to improve spatial resolution and to contrast image. The purpose of this research is to compare FDOT and DOT in forward analysis with continuous wave approach. The scattering and absorbing parameters of potatoes are used to represent the real condition. The object was illuminated by the NIR source from some positions on the boundary of object. A set of NIR detector are placed on the peripheral position of the object to measure the intensity of propagated or emitted light. In the simulation, we varied a condition of object then we analyzed the sensitivity of forward problem. The result of this study shows that FDOT has a better sensitivity than DOT and a better potential to monitor internal defects of agricultural produce because of the contrast value between optical and fluorescence properties of agricultural produce normal tissue and defects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1992

Integrated aerodynamic-structural-control wing design

The aerodynamic-structural-control design of a forward-swept composite wing for a high subsonic transport aircraft is considered. The structural analysis is based on a finite-element method. The aerodynamic calculations are based on a vortex-lattice method, and the control calculations are based on an output feedback control. The wing is designed for minimum weight subject to structural, performance/aerodynamic and control constraints. Efficient methods are used to calculate the control-deflection and control-effectiveness sensitivities which appear as second-order derivatives in the control constraint equations. To suppress the aeroelastic divergence of the forward-swept wing, and to reduce the gross weight of the design aircraft, two separate cases are studied: (1) combined application of aeroelastic tailoring and active controls; and (2) aeroelastic tailoring alone. The results of this study indicated that, for this particular example, aeroelastic tailoring is sufficient for suppressing the aeroelastic divergence, and the use of active controls was not necessary.

Rais-Rohani, M.↗
DOE OSTI2022

Matrix Approach to Land Carbon Cycle Modeling

Land ecosystems contribute to climate change mitigation by taking up approximately 30% of anthropogenically emitted carbon. However, estimates of the amount and distribution of carbon uptake across the world's ecosystems or biomes display great uncertainty. The latter hinders a full understanding of the mechanisms and drivers of land carbon uptake, and predictions of the future fate of the land carbon sink. The latter is needed as evidence to inform climate mitigation strategies such as afforestation schemes. To advance land carbon cycle modeling, we have developed a matrix approach. Land carbon cycle models use carbon balance equations to represent carbon exchanges among pools. Our approach organizes this set of equations into a single matrix equation without altering any processes of the original model. The matrix equation enables the development of a theoretical framework for understanding the general, transient behavior of the land carbon cycle. While carbon input and residence time are used to quantify carbon storage capacity at steady state, a third quantity, carbon storage potential, integrates fluxes with time to define dynamic disequilibrium of the carbon cycle under global change. The matrix approach can help address critical contemporary issues in modeling, including pinpointing sources of model uncertainty and accelerating spin-up of land carbon cycle models by tens of times. The accelerated spin-up liberates models from the computational burden that hinders comprehensive parameter sensitivity analysis and assimilation of observational data to improve model accuracy. Such computational efficiency offered by the matrix approach enables substantial improvement of model predictions using ever-increasing data availability. Overall, the matrix approach offers a step change forward for understanding and modeling the land carbon cycle.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2008

Algorithm Optimally Orders Forward-Chaining Inference Rules

People typically develop knowledge bases in a somewhat ad hoc manner by incrementally adding rules with no specific organization. This often results in a very inefficient execution of those rules since they are so often order sensitive. This is relevant to tasks like Deep Space Network in that it allows the knowledge base to be incrementally developed and have it automatically ordered for efficiency. Although data flow analysis was first developed for use in compilers for producing optimal code sequences, its usefulness is now recognized in many software systems including knowledge-based systems. However, this approach for exhaustively computing data-flow information cannot directly be applied to inference systems because of the ubiquitous execution of the rules. An algorithm is presented that efficiently performs a complete producer/consumer analysis for each antecedent and consequence clause in a knowledge base to optimally order the rules to minimize inference cycles. An algorithm was developed that optimally orders a knowledge base composed of forwarding chaining inference rules such that independent inference cycle executions are minimized, thus, resulting in significantly faster execution. This algorithm was integrated into the JPL tool Spacecraft Health Inference Engine (SHINE) for verification and it resulted in a significant reduction in inference cycles for what was previously considered an ordered knowledge base. For a knowledge base that is completely unordered, then the improvement is much greater.

James, Mark↗
DOE OSTI2018

Analyzing the impact of reaction models on the production of hydrocarbons from thermally upgraded oil shales

Reaction parameters significantly affect oil production from shales by means of heating and in-situ upgrading. In this work, we perform numerical simulations of two chemical reaction models, which are mainly used in the research of kerogen pyrolysis and subsequent hydrocarbon decomposition in organic-rich porous media. They are the Braun and Burnham model and Wellington model. In these forward numerical simulations, we present the influence of the two reaction models on hydrocarbon production. The Braun and Burnham reaction model shows more vigorous kerogen and subsequent decomposition reactions and more hydrocarbon production than the Wellington model. A local sensitivity analysis identifies the reaction parameters with the highest influence on productivity, and the most sensitive outputs. A data-worth analysis identifies the most valuable observation data to be measured for the best prediction of total hydrocarbon production. We find that the most valuable observation data is the cumulative production of heavy oil in the Braun and Burnham model and of light oil in the Wellington model, respectively. Finally, once we determine the maximum allowable prediction uncertainty and the expected measurement uncertainty, the observation data to be measured for the minimization of prediction uncertainty can be obtained.

04 OIL SHALES AND TAR SANDS↗
NASA NTRS2005

Adjoint Sensitivity Analysis of Orbital Mechanics: Application to Computations of Observables' Partials with Respect to Harmonics of the Planetary Gravity Fields

An approach is presented to the inversion of gravity fields based on evaluation of partials of observables with respect to gravity harmonics using the solution of adjoint problem of orbital dynamics of the spacecraft. Corresponding adjoint operator is derived directly from the linear operator of the linearized forward problem of orbital dynamics. The resulting adjoint problem is similar to the forward problem and can be solved by the same methods. For given highest degree N of gravity harmonics desired, this method involves integration of N adjoint solutions as compared to integration of N2 partials of the forward solution with respect to gravity harmonics in the conventional approach. Thus, for higher resolution gravity models, this approach becomes increasingly more effective in terms of computer resources as compared to the approach based on the solution of the forward problem of orbital dynamics.

gravity fields↗