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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 199 records · Page 11
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NASA NTRS2022

Satellite Precipitation Measurements: What Have We Learnt About Cloud-Precipitation Processes From Space?

Precipitation is one of the fundamental elements that define global and regional climatology. Precipitation systems consist of a broad spectrum of three-dimensional structures in which microphysical processes interact with macro-scale processes in the cloud system and the ambient environment that prescribe the evolution of the system. Since 1970s, satellite observations of precipitation have been a fundamental tool in quantifying this complex interaction. They have first quantified the frequency and intensity of global precipitation, including remote areas over open oceans and polar regions, thus providing today’s precipitation climatology. More recently, satellite observations of cloud and precipitation have been exploited for understanding the physical mechanisms governing precipitation systems. A subset of these studies also provided observation-based metrics to probe physical processes operating in cloud-precipitation systems and to apply them as diagnostic measures for evaluating the representation of the processes in numerical models for better projections of future climate. In this chapter, we first review the theoretical basis of precipitation remote sensing from space and describe how it is practically applied in satellite missions. In the first part of the chapter, an historical overview of the satellite missions is described, summarising the instruments and retrieval algorithms developed in the missions. In the second part, we introduce a set of studies discussing the fundamental mechanisms behind precipitation formation, highlighting what we have learnt to date on cloud-precipitation processes from satellite observations.

Precipitation↗
NASA NTRSDate not supplied

Avoiding Selection Bias in Generating Examples of Plans in the Presence of Heuristic Error

It is generally understood that heuristic error hurts the performance of search algorithms, measured in terms of search effort. Hence there is an interest in understanding how to reduce heuristic error. One way to do this is to learn a heuristic from a set of examples of plans generated offline, e.g. bootstrapping methods. In this paper, we consider how some methods for generating examples of plans may skew the training set in the presence of heuristic errors. Initial theoretical results show that duplicate detection is one source of selection bias in the canonical A* algorithm. We introduce a duplicate selection scheme for A* that avoids selection bias in generating cost-optimal examples, without compromising memory efficiency, and develop ideas in the satisficing setting. We evaluate our approach on n x m grids with multiple cost-optimal solutions and synthetic heuristic error. Finally, we attempt to extend these ideas to the problem of generating extreme examples of plans.

Alison S Paredes↗
NASA NTRS1998

Solar Flare Physics

We have continued our previous efforts in studies of fourier imaging methods applied to hard X-ray flares. We have performed physical and theoretical analysis of rotating collimator grids submitted to GSFC(Goddard Space Flight Center) for the High Energy Solar Spectroscopic Imager (HESSI). We have produced simulation algorithms which are currently being used to test imaging software and hardware for HESSI. We have developed Maximum-Entropy, Maximum-Likelihood, and "CLEAN" methods for reconstructing HESSI images from count-rate profiles. This work is expected to continue through the launch of HESSI in July, 2000. Section 1 shows a poster presentation "Image Reconstruction from HESSI Photon Lists" at the Solar Physics Division Meeting, June 1998; Section 2 shows the text and viewgraphs prepared for "Imaging Simulations" at HESSI's Preliminary Design Review on July 30, 1998.

Schmahl, Edward J.↗
NASA NTRS1975

Estimation of transonic aircraft aerodynamics to high angles of attack

A recently developed method for estimating transonic aircraft aerodynamics to high angles of attack which is especially suited to computerized aircraft design and optimization studies is described. Following theoretical and empirical guidelines, explicit nonlinear equations are formulated for subsonic, transonic, and supersonic speeds; new algorithms are used for assessing compressibility effects and for analyzing transonic, shock-dominated flows which adhere to Laitone's limit Mach-number criterion. Viscous dominated flows are not analyzed. The transonic influence of viscosity is indirectly accommodated by assigning designated inputs rather than extracted solutions for the chordwise locations of shock and separation. The method is extended to complete aircraft configurations by including accounts for nose lift, the wing downwash field, and tail lift. Several comparisons of experiment and estimate are included.

Axelson, J. A.↗
NASA NTRS1989

Users' manual for the Langley high speed propeller noise prediction program (DFP-ATP)

The use of the Dunn-Farassat-Padula Advanced Technology Propeller (DFP-ATP) noise prediction program which computes the periodic acoustic pressure signature and spectrum generated by propellers moving with supersonic helical tip speeds is described. The program has the capacity of predicting noise produced by a single-rotation propeller (SRP) or a counter-rotation propeller (CRP) system with steady or unsteady blade loading. The computational method is based on two theoretical formulations developed by Farassat. One formulation is appropriate for subsonic sources, and the other for transonic or supersonic sources. Detailed descriptions of user input, program output, and two test cases are presented, as well as brief discussions of the theoretical formulations and computational algorithms employed.

Dunn, M. H.↗
NASA NTRS1989

Boost-phase discrimination research activities

Theoretical research in two areas was performed. The aerothermodynamics research focused on the hard-body and rocket plume flows. Analytical real gas models to describe finite rate chemistry were developed and incorporated into the three-dimensional flow codes. New numerical algorithms capable of treating multi-species reacting gas equations and treating flows with large gradients were also developed. The computational chemistry research focused on the determination of spectral radiative intensity factors, transport properties and reaction rates. Ab initio solutions to the Schrodinger equation provided potential energy curves transition moments (radiative probabilities and strengths) and potential energy surfaces. These surfaces were then coupled with classical particle reactive trajectories to compute reaction cross-sections and rates.

Cooper, David M.↗
NASA NTRS1991

Turbulence modeling in aerodynamic shear flows - Status and problems

This paper briefly summarizes the status and problems of turbulence modeling for aerodynamical applications. For complex flows the 'approach of choice' is (increasingly) full second-order (Reynolds stress equation) closure. These closures have not yet developed to anywhere near their full potential, significant further research is required especially regarding length-scale equations, representation of pressure-strain correlations, and wall region treatments. Recent developments in computer capability, algorithms, numerical simulations, theory and quantitative flow visualization should assist in and hasten this research. Several problem areas such as shock interaction and discrete dynamic instabilities of turbulent flows may require mega-to-large eddy simulation or theoretical adjuncts.

Bushnell, D. M.↗
NASA NTRS2003

Noninvasive identification of the total peripheral resistance baroreflex

We propose two identification algorithms for quantitating the total peripheral resistance (TPR) baroreflex, an important contributor to short-term arterial blood pressure (ABP) regulation. Each algorithm analyzes beat-to-beat fluctuations in ABP and cardiac output, which may both be obtained noninvasively in humans. For a theoretical evaluation, we applied both algorithms to a realistic cardiovascular model. The results contrasted with only one of the algorithms proving to be reliable. This algorithm was able to track changes in the static gains of both the arterial and cardiopulmonary TPR baroreflex. We then applied both algorithms to a preliminary set of human data and obtained contrasting results much like those obtained from the cardiovascular model, thereby making the theoretical evaluation results more meaningful. This study suggests that, with experimental testing, the reliable identification algorithm may provide a powerful, noninvasive means for quantitating the TPR baroreflex. This study also provides an example of the role that models can play in the development and initial evaluation of algorithms aimed at quantitating important physiological mechanisms.

Non-NASA Center↗
NASA NTRS2012

Advancing Data Assimilation in Operational Hydrologic Forecasting: Progresses, Challenges, and Emerging Opportunities

Data assimilation (DA) holds considerable potential for improving hydrologic predictions as demonstrated in numerous research studies. However, advances in hydrologic DA research have not been adequately or timely implemented in operational forecast systems to improve the skill of forecasts for better informed real-world decision making. This is due in part to a lack of mechanisms to properly quantify the uncertainty in observations and forecast models in real-time forecasting situations and to conduct the merging of data and models in a way that is adequately efficient and transparent to operational forecasters. The need for effective DA of useful hydrologic data into the forecast process has become increasingly recognized in recent years. This motivated a hydrologic DA workshop in Delft, the Netherlands in November 2010, which focused on advancing DA in operational hydrologic forecasting and water resources management. As an outcome of the workshop, this paper reviews, in relevant detail, the current status of DA applications in both hydrologic research and operational practices, and discusses the existing or potential hurdles and challenges in transitioning hydrologic DA research into cost-effective operational forecasting tools, as well as the potential pathways and newly emerging opportunities for overcoming these challenges. Several related aspects are discussed, including (1) theoretical or mathematical aspects in DA algorithms, (2) the estimation of different types of uncertainty, (3) new observations and their objective use in hydrologic DA, (4) the use of DA for real-time control of water resources systems, and (5) the development of community-based, generic DA tools for hydrologic applications. It is recommended that cost-effective transition of hydrologic DA from research to operations should be helped by developing community-based, generic modeling and DA tools or frameworks, and through fostering collaborative efforts among hydrologic modellers, DA developers, and operational forecasters.

forecasting↗
NASA NTRS1985

Remote sensing of cloud-top pressure using reflected solar radiation in the oxygen A-band

An algorithm has been developed for using the reflection of solar radiation in the oxygen A-band to determine cloud-top altitude. Because of multiple scattering and molecular absorption inside the cloud, the reflection of clouds is substantially modified in comparison with a mirror cloud, which is assumed to have a 100 percent reflection. To infer true cloud-top altitude, therefore, it is necessary to accurately estimate the amount of 'photon penetration'. Theoretical calculations indicate that the amount of photon penetration depends on the altitude, the scaled volume scattering coefficient, and the scaled optical thickness of the cloud. Algorithms using the reflection in the oxygen A-band to determine the cloud-top pressure have been applied to an aircraft field experiment in conjunction with CCOPE, 1981. Results of this study are very encouraging, especially for extended clouds.

Wu, M.-L. C.↗
NASA NTRS1982

Measurement of soil moisture using remote sensing multisensor radiation techniques

Theoretical modeling as well as laboratory and field measurement were coupled with analysis of aircraft data obtained from controlled sites in an effort to enhance understanding of the microwave response due to soil moisture so as to specify sensor parameters and develop inversion algorithms. Models to predict the complex dielectric constant were produced which led to the interpretation of the results in terms of a matrix potential rather than simply moisture content. Similar advances were made in the development of coherent and incoherent radiative transfer models and rough surface scattering models.

Waite, W. P.↗
NASA NTRS1984

Determination of cloud parameters from infrared sounder data

The World Climate Research Programme (WCRP) plan is concerned with the need to develop a uniform global cloud climatology as part of a broad research program on climate processes. The International Satellite Cloud Climatology Project (ISCCP) has been approved as the first project of the WCRP. The ISCCP has the basic objective to collect and analyze satellite radiance data to infer the global distribution of cloud radiative properties in order to improve the modeling of cloud effects on climate. Research is conducted to explore an algorithm for retrieving cloud properties by utilizing the available infrared sounder data from polar-orbiting satellites. A numerical method is developed for computing cloud top heights, amount, and emissivity on the basis of a parameterized infrared radiative transfer equation for cloudy atmospheres. Theoretical studies were carried out by considering a synthetic atmosphere.

Yeh, H.-Y. M.↗
NASA NTRS1996

Wavelet Sparse Approximate Inverse Preconditioners

There is an increasing interest in using sparse approximate inverses as preconditioners for Krylov subspace iterative methods. Recent studies of Grote and Huckle and Chow and Saad also show that sparse approximate inverse preconditioner can be effective for a variety of matrices, e.g. Harwell-Boeing collections. Nonetheless a drawback is that it requires rapid decay of the inverse entries so that sparse approximate inverse is possible. However, for the class of matrices that, come from elliptic PDE problems, this assumption may not necessarily hold. Our main idea is to look for a basis, other than the standard one, such that a sparse representation of the inverse is feasible. A crucial observation is that the kind of matrices we are interested in typically have a piecewise smooth inverse. We exploit this fact, by applying wavelet techniques to construct a better sparse approximate inverse in the wavelet basis. We shall justify theoretically and numerically that our approach is effective for matrices with smooth inverse. We emphasize that in this paper we have only presented the idea of wavelet approximate inverses and demonstrated its potential but have not yet developed a highly refined and efficient algorithm.

Chan, Tony F.↗
DOE OSTI2026

Mixed stochastic-deterministic density functional theoretic decomposition of Kubo–Greenwood conductivities in the projector augmented wave formalism

Pairing the accuracy of the Kohn–Sham density-functional framework with the efficiency of a stochastic algorithmic approach, mixed stochastic-deterministic density functional theory (mDFT) achieves a favorable computational scaling with system sizes and electronic temperatures. We employ the recently developed mDFT formalism to investigate the dynamic charge-transport properties of systems in the warm dense matter regime. The optical conductivity spectra are computed for single- and multi- component mixtures of carbon, hydrogen, and beryllium using two complementary approaches: Kubo–Greenwood in the mDFT picture and real-time time-dependent mDFT. We further devise a decomposition of the Onsager coefficients leading up to the Kubo–Greenwood spectra to exhibit contributions from the deterministic, stochastic, and mixed electronic state transitions at different incident photon energies.

36 MATERIALS SCIENCE↗
NASA NTRS1974

Control of Finite-State, Finite Memory Stochastic Systems

A generalized problem of stochastic control is discussed in which multiple controllers with different data bases are present. The vehicle for the investigation is the finite state, finite memory (FSFM) stochastic control problem. Optimality conditions are obtained by deriving an equivalent deterministic optimal control problem. A FSFM minimum principle is obtained via the equivalent deterministic problem. The minimum principle suggests the development of a numerical optimization algorithm, the min-H algorithm. The relationship between the sufficiency of the minimum principle and the informational properties of the problem are investigated. A problem of hypothesis testing with 1-bit memory is investigated to illustrate the application of control theoretic techniques to information processing problems.

Sandell, Nils R.↗
NASA NTRS1991

Numerical aspects of computing high Reynolds number flows on unstructured meshes

An edge-data structure describing a mesh edge-wise given the vertices of each edge and neighboring cell information is used developing algorithms for the Navier-Stokes equations on triangular meshes. Edge formulas for the Galerkin and finite-element discretization of gradient, divergence, Hessian, and Laplacian operators are derived. A simple edge formula is derived for the discretization of the Laplacian operator, where precise theoretical conditions for a discrete maximum principle can be ascertained. Practical issues associated with solving the Navier-Stokes equations on unstructured meshes are addressed, along with issues concerning the generation of highly stretched triangular meshes and the modeling of turbulence on unstructured meshes. A turbulence modeling strategy is proposed, and numerical results for a high-Reynolds-number flow about single- and multielement airfoils are discussed.

Barth, Timothy J.↗
NASA NTRS1998

Theoretical Calculation and Validation of the Water Vapor Continuum Absorption

The primary objective of this investigation is the development of an improved parameterization of the water vapor continuum absorption through the refinement and validation of our existing theoretical formalism. The chief advantage of our approach is the self-consistent, first principles, basis of the formalism which allows us to predict the frequency, temperature and pressure dependence of the continuum absorption as well as provide insights into the physical mechanisms responsible for the continuum absorption. Moreover, our approach is such that the calculated continuum absorption can be easily incorporated into satellite retrieval algorithms and climate models. Accurate determination of the water vapor continuum is essential for the next generation of retrieval algorithms which propose to use the combined constraints of multispectral measurements such as those under development for EOS data analysis (e.g., retrieval algorithms based on MODIS and AIRS measurements); current Pathfinder activities which seek to use the combined constraints of infrared and microwave (e.g., HIRS and MSU) measurements to improve temperature and water profile retrievals, and field campaigns which seek to reconcile spectrally-resolved and broad-band measurements such as those obtained as part of FIRE. Current widely used continuum treatments have been shown to produce spectrally dependent errors, with the magnitude of the error dependent on temperature and abundance which produces errors with a seasonal and latitude dependence. Translated into flux, current water vapor continuum parameterizations produce flux errors of order 10 W/sq m, which compared to the 4 W/sq m magnitude of the greenhouse gas forcing and the 1-2 W/sq m estimated aerosol forcing is certainly climatologically significant and unacceptably large. While it is possible to tune the empirical formalisms, the paucity of laboratory measurements, especially at temperatures of interest for atmospheric applications, preclude tuning, the empirical continuum models over the full spectral range of interest for remote sensing and climate applications. Thus, we propose to further develop and refine our existing, far-wing formalism to provide an improved treatment applicable from the near-infrared through the microwave. Based on the results of this investigation, we will provide to the remote sensing/climate modeling community a practical and accurate tabulation of the continuum absorption covering the near-infrared through the microwave region of the spectrum for the range of temperatures and pressures of interest for atmospheric applications.

Ma, Qiancheng↗
NASA NTRS1998

Theoretical Calculation and Validation of the Water Vapor Continuum Absorption

The primary objective of this investigation is the development of an improved parameterization of the water vapor continuum absorption through the refinement and validation of our existing theoretical formalism. The chief advantage of our approach is the self-consistent, first principles, basis of the formalism which allows us to predict the frequency, temperature and pressure dependence of the continuum absorption as well as provide insights into the physical mechanisms responsible for the continuum absorption. Moreover, our approach is such that the calculated continuum absorption can be easily incorporated into satellite retrieval algorithms and climate models. Accurate determination of the water vapor continuum is essential for the next generation of retrieval algorithms which propose to use the combined constraints of multi-spectral measurements such as those under development for EOS data analysis (e.g., retrieval algorithms based on MODIS and AIRS measurements); current Pathfinder activities which seek to use the combined constraints of infrared and microwave (e.g., HIRS and MSU) measurements to improve temperature and water profile retrievals, and field campaigns which seek to reconcile spectrally-resolved and broad-band measurements such as those obtained as part of FIRE. Current widely used continuum treatments have been shown to produce spectrally dependent errors, with the magnitude of the error dependent on temperature and abundance which produces errors with a seasonal and latitude dependence. Translated into flux, current water vapor continuum parameterizations produce flux errors of order 10 W/ml, which compared to the 4 W/m' magnitude of the greenhouse gas forcing and the 1-2 W/m' estimated aerosol forcing is certainly climatologically significant and unacceptably large. While it is possible to tune the empirical formalisms, the paucity of laboratory measurements, especially at temperatures of interest for atmospheric applications, preclude tuning the empirical continuum models over the full spectral range of interest for remote sensing and climate applications. Thus, we propose to further develop and refine our existing far-wing formalism to provide an improved treatment applicable from the near-infrared through the microwave. Based on the results of this investigation, we will provide to the remote sensing/climate modeling community a practical and accurate tabulation of the continuum absorption covering the near-infrared through the microwave region of the spectrum for the range of temperatures and pressures of interest for atmospheric applications.

Ma, Qiancheng↗