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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Net Radiative Effects of Dust in the Tropical North Atlantic Based on Integrated Satellite Observations and in Situ Measurements

In this study, we integrate recent in situ measurements with satellite retrievals of dust physical and radiative properties to quantify dust direct radiative effects on shortwave (SW) and longwave (LW) radiation (denoted as DRESW and DRELW, respectively) in the tropical North Atlantic during the summer months from 2007 to 2010. Through linear regression of the CERES-measured top-of atmosphere (TOA) flux versus satellite aerosol optical depth (AOD) retrievals, we estimate the instantaneous DRESW efficiency at the TOA to be -49+/-7.1 W/sq.m AOD(exp -1) and -36+/-4:8W/sq.m AOD(exp -1) based on AOD from MODIS and CALIOP, respectively. We then perform various sensitivity studies based on recent measurements of dust particle size distribution (PSD), refractive index, and particle shape distribution to determine how the dust microphysical and optical properties affect DRE estimates and its agreement with the above-mentioned satellite-derived DREs. Our analysis shows that a good agreement with the observation-based estimates of instantaneous DRESW and DRELW can be achieved through a combination of recently observed PSD with substantial presence of coarse particles, a less absorptive SW refractive index, and spheroid shapes. Based on this optimal combination of dust physical properties we further estimate the diurnal mean dust DRE(sub SW) in the region of -10W/sq.m at TOA and -26W/sq.m at the surface, respectively, of which ~30% is canceled out by the positive DRE(sub LW). This yields a net DRE of about -6:9 and -18.3 W/sq.m at TOA and the surface, respectively. Our study suggests that the LW flux contains useful information on dust particle size, which could be used together with SW observations to achieve a more holistic understanding of the dust radiative effect.

Song, Qianqian↗
NASA NTRS2024

Harnessing Collaborative Learning Automata to Guide Multi-objective Optimization based Inverse Analysis for Structural Damage Identification

Structural damage identification based on physical models is often transformed into an optimization problem that minimizes the difference between measurement information of structure being monitored and the model prediction in the parametric space. However, the objective function in this context often exhibits multimodality, involving high-dimensional variables due to the reliance on finite element models for damage identification. These features pose challenges to optimization algorithms, where entrapment in local solutions can lead to false positives and false negatives in damage identification. In this research, we propose a reinforcement learning based multi-swarm optimizer to tackle such challenges in pursuit of a small yet diverse solution set that can capture the true damage scenario as one of the solutions. The proposed method leverages the flexibility of the particle swarm optimizer and incorporates novel strategies of metaheuristics to realize targeted improvement. To enable the particle swarm to adaptively select the appropriate search strategy based on the current environment, we adopt the learning automata technique, which sidesteps the need for reward strategy selection that is usually ad hoc at each step of the search. The integration harnesses the automatic learning and self-adaptation capabilities of learning automata, enabling the particles to navigate based on environmental signals. This leads to accumulated probabilities tied to advantageous movements, fostering an adaptive exploration of particles in the search space. The proposed approach is first validated through implementing into benchmark test cases with comparisons. It is then applied to structural damage identification with piezoelectric admittance experimental signals. `The results highlight the capability of the algorithm to identify a small solution set with high accuracy to match the actual damage scenario.

Yang Zhang↗
NASA NTRS1967

CINDA - Chrysler Improved Numerical Differencing Analyzer computer program

Dimensionless multioption systems compiler computer program constructs and analyzes a mathematical model of any arbitrary one, two, or three dimensional lumped parameter representation of a physical system. It automatically optimizes the utilization of computer core space and is more general and versatile than BETA.

Gaski, J. D.↗
NASA NTRS1995

Internal aerodynamics of a generic three-dimensional scramjet inlet at Mach 10

A combined computational and experimental parametric study of the internal aerodynamics of a generic three-dimensional sidewall compression scramjet inlet configuration at Mach 10 has been performed. The study was designed to demonstrate the utility of computational fluid dynamics as a design tool in hypersonic inlet flow fields, to provide a detailed account of the nature and structure of the internal flow interactions, and to provide a comprehensive surface property and flow field database to determine the effects of contraction ratio, cowl position, and Reynolds number on the performance of a hypersonic scramjet inlet configuration. The work proceeded in several phases: the initial inviscid assessment of the internal shock structure, the preliminary computational parametric study, the coupling of the optimized configuration with the physical limitations of the facility, the wind tunnel blockage assessment, and the computational and experimental parametric study of the final configuration. Good agreement between computation and experimentation was observed in the magnitude and location of the interactions, particularly for weakly interacting flow fields. Large-scale forward separations resulted when the interaction strength was increased by increasing the contraction ratio or decreasing the Reynolds number.

Holland, Scott D.↗
NASA NTRS1998

Multi-Satellite Estimates of Land-Surface Properties for Determination of Energy and Water Budgets

Using the WETNET database, existing methods for the estimation of surface wetness from SSM/I data have been assessed and further developed. A physical-statistical method for optimal estimation of daily surface heat flux and Bowen ratio on the mesoscale has been developed and tested. This method is based on observations of daytime planetary boundary layer (PBL) growth from operational ravansonde and daytime land-surface temperature amplitude from Geostationary Operational Environmental (GOES) satellites. The mesoscale patterns of these heat fluxes have been compared with an AVHRR-based vegetation index and surface wetness (separately estimated from SSM/I and in situ observations). Cases of the 1988 Midwest drought and a surface/atmosphere moisture gradient (dry-line) in the southern Plains were studied. The analyses revealed significant variations in sensible heat flux (S(sub 0), and Bowen ratio, B(sub 0)) associated with vegetation cover and antecedent precipitation. Relationships for surface heat flux (and Bowen ratio) from antecedent precipitation and vegetation index have been developed and compared to other findings. Results from this project are reported in the following reviewed literature.

Menzel, W. Paul↗
NASA NTRS2008

High Temperature Aerogels for Thermal Protection Systems

High temperature aerogels in the Al2O3-SiO2 system are being investigated as possible constituents for lightweight integrated thermal protection system (TPS) designs for use in supersonic and hypersonic applications. Gels are synthesized from ethoxysilanes and AlCl3.6H2O, using an epoxide catalyst. The influence of Al:Si ratio, solvent, water to metal and water to alcohol ratios on aerogel composition, morphology, surface area, and pore size distribution were examined, and phase transformation on heat treatment characterized. Aerogels have been fabricated which maintain porous, fractal structures after brief exposures to 1000 C. Incorporation of nanofibers, infiltration of aerogels into SiC foams, use of polymers for crosslinking the aerogels, or combinations of these, offer potential for toughening and integration of TPS with composite structure. Woven fabric composites having Al2O3-SiO2 aerogels as a matrix also have been fabricated. Continuing work is focused on reduction in shrinkage and optimization of thermal and physical properties.

Hurwitz, Frances I.↗
NASA NTRS2010

U.S. Air Force Research Laboratory's Need for Flow Physics and Control With Applications Involving Aero-Optics and Weapon Bay Cavities

To develop New Flow Control Techniques: a) Knowledge of the Flow Physics with and without control. b) How does Flow Control Effect Flow Physics (What Works to Optimize the Design?). c) Energy or Work Efficiency of the Control Technique (Cost - Risk - Benefit Analysis). d) Supportability, e.g. (size of equipment, computational power, power supply) (Allows Designer to include Flow Control in Plans).

Schmit, Ryan↗
NASA NTRS2012

Unsteady Adjoint Approach for Design Optimization of Flapping Airfoils

This paper describes the work for optimizing the propulsive efficiency of flapping airfoils, i.e., improving the thrust under constraining aerodynamic work during the flapping flights by changing their shape and trajectory of motion with the unsteady discrete adjoint approach. For unsteady problems, it is essential to properly resolving time scales of motion under consideration and it must be compatible with the objective sought after. We include both the instantaneous and time-averaged (periodic) formulations in this study. For the design optimization with shape parameters or motion parameters, the time-averaged objective function is found to be more useful, while the instantaneous one is more suitable for flow control. The instantaneous objective function is operationally straightforward. On the other hand, the time-averaged objective function requires additional steps in the adjoint approach; the unsteady discrete adjoint equations for a periodic flow must be reformulated and the corresponding system of equations solved iteratively. We compare the design results from shape and trajectory optimizations and investigate the physical relevance of design variables to the flapping motion at on- and off-design conditions.

Lee, Byung Joon↗
NASA NTRS2012

On Approaching the Ultimate Limits of Communication Using a Photon-Counting Detector

Coherent states achieve the Holevo capacity of a pure-loss channel when paired with an optimal measurement, but a physical realization of this measurement scheme is as of yet unknown, and it is also likely to be of high complexity. In this paper, we focus on the photon-counting measurement and study the photon and dimensional efficiencies attainable with modulations over classical- and nonclassical-state alphabets. We analyze two binary modulation architectures that improve upon the dimensional versus photon efficiency tradeoff achievable with the state-of-the-art coherent-state on-off keying modulation. We show that at high photon efficiency these architectures achieve an efficiency tradeoff that differs from the best possible tradeoff--determined by the Holevo capacity--by only a constant factor. The first architecture we analyze is a coherent-state transmitter that relies on feedback from the receiver to control the transmitted energy. The second architecture uses a single-photon number-state source.

photon-counting measurement↗
NASA NTRS2012

Approaching the Ultimate Limits of Communication Efficiency with a Photon-Counting Detector

Coherent states achieve the Holevo capacity of a pure-loss channel when paired with an optimal measurement, but a physical realization of this measurement is as of yet unknown, and it is also likely to be of high complexity. In this paper, we focus on the photon-counting measurement and study the photon and dimensional efficiencies attainable with modulations over classical- and nonclassical-state alphabets. We first review the state-of-the-art coherent on-off-keying (OOK) with a photoncounting measurement, illustrating its asymptotic inefficiency relative to the Holevo limit. We show that a commonly made Poisson approximation in thermal noise leads to unbounded photon information efficiencies, violating the conjectured Holevo limit. We analyze two binary-modulation architectures that improve upon the dimensional versus photon efficiency tradeoff achievable with conventional OOK. We show that at high photon efficiency these architectures achieve an efficiency tradeoff that differs from the best possible tradeoff--determined by the Holevo capacity--by only a constant factor. The first architecture we analyze is a coherent-state transmitter that relies on feedback from the receiver to control the transmitted energy. The second architecture uses a single-photon number-state source.

thermal noises↗
NASA NTRS2020

N+1 Systems Analysis Retrospective

“Systems analysis” refers to the study of operational components and the integrated interactions and impacts of the components within their environment. The use of systems analysis in general engineering studies has grown due to the broad applicability of the tools and methodologies to the design, evaluation, or optimization of conceptual systems (physical and otherwise). The increased use of systems analysis tools and methodologies has also led some to the merging of disciplines, as systems analysis and “systems engineering” are often used interchangeably. Since both disciplines use terms with distinct meanings and defined relationships, these terms are not used interchangeably in this retrospective.

NASA↗
NASA NTRS2003

UCLA parallel PIC framework

The UCLA Parallel PIC Framework (UPIC) has been developed to provide trusted components for the rapid construction of new, parallel Particle-in-Cell (PIC) codes. The Framework uses object-based ideas in Fortran95, and is designed to provide support for various kinds of PIC codes on various kinds of hardware. The focus is on student programmers. The Framework supports multiple numerical methods, different physics approximations, different numerical optimizations and implementations for different hardware. It is designed with "defensive" programming in mind, meaning that it contains many error checks and debugging helps. Above all, it is designed to hide the complexity of parallel processing. It is currently being used in a number of new Parallel PIC codes.

Norton, Charles D.↗
NASA NTRS2020

Underlying Fundamentals of Kalman Filtering for River Network Modeling

The grand challenge of producing hydrometeorological estimates every time and everywhere has motivated the fusion of sparse observations with dense numerical models, with a particular interest on discharge in river modeling. Ensemble methods are largely preferred as they enable the estimation of error properties, but at the expense of computational load and generally with underestimations. These imperfect stochastic estimates motivate the use of correction methods, that is, error localization and inflation, although the physical justifications for their optimality are limited. The purpose of this study is to use one of the simplest forms of data assimilation when applied to river modeling and reveal the underlying mechanisms impacting its performance. Our framework based on assimilating daily averaged in situ discharge measurements to correct daily averaged runoff was tested over a 4-yr case study of two rivers in Texas. Results show that under optimal conditions of inflation and localization, discharge simulations are consistently improved such that the mean values of Nash–Sutcliffe efficiency are enhanced from211.32 to 0.55 at observed gauges and from212.24 to21.10 at validation gauges. Yet, parameters controlling the inflation and the localization have a large impact on the performance. Further investigations of these sensitivities showed that optimal inflation occurs when compensating exactly for discrepancies in the magnitude of errors while optimal localization matches the distance traveled during one assimilation window. These results may be applicable to more advanced data assimilation methods as well as for larger applications motivated by upcoming river-observing satellite missions, such as NASA’s Surface Water and Ocean Topography mission.

Streamflow↗
NASA NTRSDate not supplied

Newly Available Single Field-of-view Sounder Atmospheric Product (SiFSAP) and Its Derivative Product

The Single Field-of-view Sounder Atmospheric product (SiFSAP) has been developed and delivered to NASA GES DISC. The SiFSAP Algorithm Theoretical Basis Documents (ATBD) and users manuals are ready to be released to public. This novel data product supplements other operational products such as AIRS version 7 and the Community Long-term Infrared Microwave Combined Atmospheric Product System (CLIMCAPS) from two main perspectives: 1) improving the spatial resolution of sounder Level-2 data to extend its usage in weather and dynamics focus area; 2) establishing radiance closure between Level-2 data and directly measured Level-1 radiances to facilitate the climate trend analysis. SiFSAP has 3-times higher spatial resolution and 9-times denser data products comparing to current NASA and NOAA operational IR sounder products. SiFSAP is derived using the optimal estimation method based physical retrieval algorithm. The Principal Component-based Radiative Transfer Model (PCRTM) which includes the cloud scattering simulation is used for the forward model so that the solution can fit the spectral radiances under all-sky conditions for individual single field-of-view (SFOV) measurements. A general introduction of the SiFSAP algorithm and corresponding validation work will be presented. Also introduced here is the Climate Fingerprinting Sounder product (ClimFiSP) that is the derivative product of SiFSAP and will be released in the near future. The ClimFiSP algorithm uses pre-constructed fingerprinting relationship to achieve a low-latency Level-3 data production and facilitate the fusion of data of different sounders.

Wan Wu↗
NASA NTRS2013

Extended Analytic Device Optimization Employing Asymptotic Expansion

Analytic optimization of a thermoelectric junction often introduces several simplifying assumptionsincluding constant material properties, fixed known hot and cold shoe temperatures, and thermallyinsulated leg sides. In fact all of these simplifications will have an effect on device performance,ranging from negligible to significant depending on conditions. Numerical methods, such as FiniteElement Analysis or iterative techniques, are often used to perform more detailed analysis andaccount for these simplifications. While numerical methods may stand as a suitable solution scheme,they are weak in gaining physical understanding and only serve to optimize through iterativesearching techniques. Analytic and asymptotic expansion techniques can be used to solve thegoverning system of thermoelectric differential equations with fewer or less severe assumptionsthan the classic case. Analytic methods can provide meaningful closed form solutions and generatebetter physical understanding of the conditions for when simplifying assumptions may be valid.In obtaining the analytic solutions a set of dimensionless parameters, which characterize allthermoelectric couples, is formulated and provide the limiting cases for validating assumptions.Presentation includes optimization of both classic rectangular couples as well as practically andtheoretically interesting cylindrical couples using optimization parameters physically meaningful toa cylindrical couple. Solutions incorporate the physical behavior for i) thermal resistance of hot andcold shoes, ii) variable material properties with temperature, and iii) lateral heat transfer through legsides.

Thermoelectric Generators↗
NASA NTRSDate not supplied

Retrieve Methane from IR sounder measurements Using Machine Learning-Enhanced Physical Inversion

The sensitivity of IR sounder measurements to atmospheric CH 4 is often limited due to interferences from signals of other trace gases, insufficient thermal contrast, and cloud blockage. In order to resolve the geographical and vertical distribution of atmospheric CH 4 profiles, accurate scene-dependent a priori information is critically needed to support an optimal estimation method-based physical inversion scheme. Following the principles of indexing, representation, and retrieval, a spectral fingerprinting methodology is developed to address the needs for both accuracy and computational efficiency in sounder-based CH 4 retrieval. Within this framework, a clustering method based on machine learning is first employed to stratify and identify the a priori state within the pre-constructed database, using optimized spectral radiances as predictors. The corresponding radiative kernel is then used to establish the physical inversion scheme for finding the solution. High-quality data from CH 4 data assimilation systems like the Carbon-Tracker and the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis, as well as the state-of-art sounder products are used to build the training database, including radiative kernels. We will demonstrate the results retrieved from CrIS observations and the associated validation work.

Wan Wu↗
NASA NTRS2005

Journal Bearing Analysis Suite Released for Planetary Gear System Evaluation

Planetary gear systems are an efficient means of achieving high reduction ratios with minimum space and weight. They are used in helicopter, aerospace, automobile, and many industrial applications. High-speed planetary gear systems will have significant dynamic loading and high heat generation. Hence, they need jet lubrication and associated cooling systems. For units operating in critical applications that necessitate high reliability and long life, that have very large torque loading, and that have downtime costs that are significantly greater than the initial cost, hydrodynamic journal bearings are a must. Computational and analytical tools are needed for sufficiently accurate modeling to facilitate optimal design of these systems. Sufficient physics is needed in the model to facilitate parametric studies of design conditions that enable optimal designs. The first transient journal bearing code to implement the Jacobsson-Floberg-Olsson boundary conditions, using a mass-conserving algorithm devised by Professor Emeritus Harold Elrod of Columbia University, was written by David E. Brewe of the U.S. Army at the NASA Lewis Research Center1 in 1983. Since then, new features and improved modifications have been built into the code by several contributors supported through Army and NASA funding via cooperative agreements with the University of Toledo (Professor Ted Keith, Jr., and Dr. Desikakary Vijayaraghavan) and National Research Council Programs (Dr. Vijayaraghavan). All this was conducted with the close consultation of Professor Elrod and the project management of David Brewe.

Brewe, David E.↗