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At least 1,801 records · Page 100

Verification and Analysis of Formulation 4 of Langley for the Study of Noise From High Speed Surfaces

There are several approaches to the prediction of the noise from sources on high speed surfaces. Two of these are the Kirchhoff and the Ffowcs williams-Hawkings methods. It can be shown that both of these methods depend on the solution of the wave equation with mathematically similar inhomogeneous source terms. Two subsonic solutions known as Formulation 1 and 1A of Langley are simple and efficient for noise prediction. The supersonic solution known as Formulation 3 is very complicated and difficult to code. Because of the complexity of the result, the computation time is longer than the subsonic formulas. Furthermore, it is difficult to assess the accuracy of noise prediction. We have been searching for a new and simpler supersonic formulation without these shortcomings. In the last AIAA Aeroacoustics Conference in Toulouse, Farassat, Dunn and Brentner presented a paper in which such a result was presented and called Formulation 4 of Langley. In this paper we will present two analytic tests of the validity this Formulation: 1) the noise from dipole distribution on the unit circle whose strength varies radially with the square of the distance from the center and 2) the noise from dipole distribution on the unit sphere whose strength varies with the cosine of the angle from the polar axis. We will discuss the question of singularities of Formulation 4.

Farassat, F.↗

Common Analysis Tool Being Developed for Aeropropulsion: The National Cycle Program Within the Numerical Propulsion System Simulation Environment

The NASA Lewis Research Center is developing an environment for analyzing and designing aircraft engines-the Numerical Propulsion System Simulation (NPSS). NPSS will integrate multiple disciplines, such as aerodynamics, structure, and heat transfer, and will make use of numerical "zooming" on component codes. Zooming is the coupling of analyses at various levels of detail. NPSS uses the latest computing and communication technologies to capture complex physical processes in a timely, cost-effective manner. The vision of NPSS is to create a "numerical test cell" enabling full engine simulations overnight on cost-effective computing platforms. Through the NASA/Industry Cooperative Effort agreement, NASA Lewis and industry partners are developing a new engine simulation called the National Cycle Program (NCP). NCP, which is the first step toward NPSS and is its initial framework, supports the aerothermodynamic system simulation process for the full life cycle of an engine. U.S. aircraft and airframe companies recognize NCP as the future industry standard common analysis tool for aeropropulsion system modeling. The estimated potential payoff for NCP is a $50 million/yr savings to industry through improved engineering productivity.

Follen, Gregory J.↗

INDUCTIVE SYSTEM HEALTH MONITORING WITH STATISTICAL METRICS

Model-based reasoning is a powerful method for performing system monitoring and diagnosis. Building models for model-based reasoning is often a difficult and time consuming process. The Inductive Monitoring System (IMS) software was developed to provide a technique to automatically produce health monitoring knowledge bases for systems that are either difficult to model (simulate) with a computer or which require computer models that are too complex to use for real time monitoring. IMS processes nominal data sets collected either directly from the system or from simulations to build a knowledge base that can be used to detect anomalous behavior in the system. Machine learning and data mining techniques are used to characterize typical system behavior by extracting general classes of nominal data from archived data sets. In particular, a clustering algorithm forms groups of nominal values for sets of related parameters. This establishes constraints on those parameter values that should hold during nominal operation. During monitoring, IMS provides a statistically weighted measure of the deviation of current system behavior from the established normal baseline. If the deviation increases beyond the expected level, an anomaly is suspected, prompting further investigation by an operator or automated system. IMS has shown potential to be an effective, low cost technique to produce system monitoring capability for a variety of applications. We describe the training and system health monitoring techniques of IMS. We also present the application of IMS to a data set from the Space Shuttle Columbia STS-107 flight. IMS was able to detect an anomaly in the launch telemetry shortly after a foam impact damaged Columbia's thermal protection system.

Iverson, David L.↗

Validation of Multi-Dimensional Stirling Engine Design Codes: Measurements in the 90-Degree Turn Test Section

The work to be presented herein was motivated largely by a desire to improve the understanding of oscillatory fluid mechanics inside a Stirling engine. To this end, a CFD project was undertaken at Cleveland State University with the goal of accurately predicting the fluid dynamics within an engine or engine component. Along with the CFD efforts, a code validation project was undertaken at the University of Minnesota. The material covered herein consists of four main parts. In section 1, an experimental investigation of a small aspect ratio impinging jet is discussed. Included in this discussion is a description of the test facilities and instrumentation. A presentation of the collected data is given and comments are made. Next, in section 2, a parallel experimental investigation is presented in which the same geometry as that of section 1 is used, but the flow conditions are changed from steady unidirectional flow to sinusoidally oscillating flow. In section Two, collected data are presented and comments are made. In section 3, a comparison is made between the results of sections 1 and 2, namely, sinusoidally oscillating flow results are compared to steady, unidirectional flow results from the same geometry. Finally, in section 4, a comparison is made between experimentally collected data (the main subject of this work) and CFD generated results. Furthermore, in appendix A, an introductory description of the primary measurement tool used in the experimental process the hot wire anemometer is given for the unfamiliar. The anemometer calibration procedure is described in appendix B. A portfolio of data reduction and data processing codes is provided in appendix C and lastly, a DVD and a roadmap of its contents is provided in an appendix D. 1.0 Unidirectional Flow Investigations 1.1 Introduction This unidirectional experimental program was undertaken to complement an oscillatory flow investigation conducted at the University of Minnesota. The oscillatory investigation is discussed thoroughly in section 2. We defer the description of the motivation behind these experiments until the introduction of section 2. The work that is discussed in this thesis began (chronologically) with oscillatory flow visualization experiments. It was decided that it would be valuable and important to investigate the flow under unidirectional conditions in the same geometry as that of the oscillatory experiments. The thought was that the unidirectional case would be less complicated to model with a CFD program (a moving boundary would be replaced with a steady state boundary condition). Thus, a series of unidirectional experiments were carried out to capture the important features of the flow within the test section. The purpose of these experiments was to provide a data set for comparison to CFD generated velocity fields. Hot-wire anemometry data were taken and flow visualization was conducted as a standard for code validation. The flow geometry was simple, such that it could be easily gridded in a CFD program. However, the geometry provided separation and transition zones, shear layers and recirculation zones. These characteristics made the flow complex and challenging for CFD computation. We comment that the order of experiments that produced this report is as follows: experimental flow visualization under oscillatory flow conditions was carried out; this was followed by unidirectional flow visualization and hot wire anemometry; finally, oscillatory hot wire anemometry was conducted. We present the results out of chronological order for the following reason: the unidirectional results are easier

Simon, Terrence W.↗

User-Defined Data Distributions in High-Level Programming Languages

One of the characteristic features of today s high performance computing systems is a physically distributed memory. Efficient management of locality is essential for meeting key performance requirements for these architectures. The standard technique for dealing with this issue has involved the extension of traditional sequential programming languages with explicit message passing, in the context of a processor-centric view of parallel computation. This has resulted in complex and error-prone assembly-style codes in which algorithms and communication are inextricably interwoven. This paper presents a high-level approach to the design and implementation of data distributions. Our work is motivated by the need to improve the current parallel programming methodology by introducing a paradigm supporting the development of efficient and reusable parallel code. This approach is currently being implemented in the context of a new programming language called Chapel, which is designed in the HPCS project Cascade.

physically distributed memory↗

Aeroelastic-Acoustics Simulation of Flight Systems

This paper describes the details of a numerical finite element (FE) based analysis procedure and a resulting code for the simulation of the acoustics phenomenon arising from aeroelastic interactions. Both CFD and structural simulations are based on FE discretization employing unstructured grids. The sound pressure level (SPL) on structural surfaces is calculated from the root mean square (RMS) of the unsteady pressure and the acoustic wave frequencies are computed from a fast Fourier transform (FFT) of the unsteady pressure distribution as a function of time. The resulting tool proves to be unique as it is designed to analyze complex practical problems, involving large scale computations, in a routine fashion.

Gupta, kajal K.↗

Complex Event Recognition Architecture

Complex Event Recognition Architecture (CERA) is the name of a computational architecture, and software that implements the architecture, for recognizing complex event patterns that may be spread across multiple streams of input data. One of the main components of CERA is an intuitive event pattern language that simplifies what would otherwise be the complex, difficult tasks of creating logical descriptions of combinations of temporal events and defining rules for combining information from different sources over time. In this language, recognition patterns are defined in simple, declarative statements that combine point events from given input streams with those from other streams, using conjunction, disjunction, and negation. Patterns can be built on one another recursively to describe very rich, temporally extended combinations of events. Thereafter, a run-time matching algorithm in CERA efficiently matches these patterns against input data and signals when patterns are recognized. CERA can be used to monitor complex systems and to signal operators or initiate corrective actions when anomalous conditions are recognized. CERA can be run as a stand-alone monitoring system, or it can be integrated into a larger system to automatically trigger responses to changing environments or problematic situations.

Fitzgerald, William A.↗

The Spatial Vision Tree: A Generic Pattern Recognition Engine- Scientific Foundations, Design Principles, and Preliminary Tree Design

New foundational ideas are used to define a novel approach to generic visual pattern recognition. These ideas proceed from the starting point of the intrinsic equivalence of noise reduction and pattern recognition when noise reduction is taken to its theoretical limit of explicit matched filtering. This led us to think of the logical extension of sparse coding using basis function transforms for both de-noising and pattern recognition to the full pattern specificity of a lexicon of matched filter pattern templates. A key hypothesis is that such a lexicon can be constructed and is, in fact, a generic visual alphabet of spatial vision. Hence it provides a tractable solution for the design of a generic pattern recognition engine. Here we present the key scientific ideas, the basic design principles which emerge from these ideas, and a preliminary design of the Spatial Vision Tree (SVT). The latter is based upon a cryptographic approach whereby we measure a large aggregate estimate of the frequency of occurrence (FOO) for each pattern. These distributions are employed together with Hamming distance criteria to design a two-tier tree. Then using information theory, these same FOO distributions are used to define a precise method for pattern representation. Finally the experimental performance of the preliminary SVT on computer generated test images and complex natural images is assessed.

Rahman, Zia-ur↗

Development of a Aerothermoelastic-Acoustics Simulation Capability of Flight Vehicles

A novel numerical, finite element based analysis methodology is presented in this paper suitable for accurate and efficient simulation of practical, complex flight vehicles. An associated computer code, developed in this connection, is also described in some detail. Thermal effects of high speed flow obtained from a heat conduction analysis are incorporated in the modal analysis which in turn affects the unsteady flow arising out of interaction of elastic structures with the air. Numerical examples pertaining to representative problems are given in much detail testifying to the efficacy of the advocated techniques. This is a unique implementation of temperature effects in a finite element CFD based multidisciplinary simulation analysis capability involving large scale computations.

Gupta, K. K.↗

Snowfall Rate Retrieval using NPP ATMS Passive Microwave Measurements

Passive microwave measurements at certain high frequencies are sensitive to the scattering effect of snow particles and can be utilized to retrieve snowfall properties. Some of the microwave sensors with snowfall sensitive channels are Advanced Microwave Sounding Unit (AMSU), Microwave Humidity Sounder (MHS) and Advance Technology Microwave Sounder (ATMS). ATMS is the follow‐on sensor to AMSU and MHS. Currently, an AMSU and MHS based land snowfall rate (SFR) product is running operationally at NOAA/NESDIS. Based on the AMSU/MHS SFR, an ATMS SFR algorithm has been developed recently. The algorithm performs retrieval in three steps: snowfall detection, retrieval of cloud properties, and estimation of snow particle terminal velocity and snowfall rate. The snowfall detection component utilizes principal component analysis and a logistic regression model. The model employs a combination of temperature and water vapor sounding channels to detect the scattering signal from falling snow and derive the probability of snowfall (Kongoli et al., 2014). In addition, a set of NWP model based filters is also employed to improve the accuracy of snowfall detection. Cloud properties are retrieved using an inversion method with an iteration algorithm and a two‐stream radiative transfer model (Yan et al., 2008). A method developed by Heymsfield and Westbrook (2010) is adopted to calculate snow particle terminal velocity. Finally, snowfall rate is computed by numerically solving a complex integral. The ATMS SFR product is validated against radar and gauge snowfall data and shows that the ATMS algorithm outperforms the AMSU/MHS SFR.

Meng, Huan↗

NPP ATMS Snowfall Rate Product

Passive microwave measurements at certain high frequencies are sensitive to the scattering effect of snow particles and can be utilized to retrieve snowfall properties. Some of the microwave sensors with snowfall sensitive channels are Advanced Microwave Sounding Unit (AMSU), Microwave Humidity Sounder (MHS) and Advance Technology Microwave Sounder (ATMS). ATMS is the follow‐on sensor to AMSU and MHS. Currently, an AMSU and MHS based land snowfall rate (SFR) product is running operationally at NOAA/NESDIS. Based on the AMSU/MHS SFR, an ATMS SFR algorithm has been developed recently. The algorithm performs retrieval in three steps: snowfall detection, retrieval of cloud properties, and estimation of snow particle terminal velocity and snowfall rate. The snowfall detection component utilizes principal component analysis and a logistic regression model. The model employs a combination of temperature and water vapor sounding channels to detect the scattering signal from falling snow and derive the probability of snowfall (Kongoli et al., 2015). In addition, a set of NWP model based filters is also employed to improve the accuracy of snowfall detection. Cloud properties are retrieved using an inversion method with an iteration algorithm and a two‐stream radiative transfer model (Yan et al., 2008). A method developed by Heymsfield and Westbrook (2010) is adopted to calculate snow particle terminal velocity. Finally, snowfall rate is computed by numerically solving a complex integral. NCEP CMORPH analysis has shown that integration of ATMS SFR has improved the performance of CMORPH‐Snow. The ATMS SFR product is also being assessed at several NWS Weather Forecast Offices for its usefulness in weather forecast.

Forecasting↗

Snowfall Rate Retrieval Using Passive Microwave Measurements and Its Applications in Weather Forecast and Hydrology

(AMSU), Microwave Humidity Sounder (MHS) and Advance Technology Microwave Sounder (ATMS). ATMS is the follow‐on sensor to AMSU and MHS. Currently, an AMSU and MHS based land snowfall rate (SFR) product is running operationally at NOAA/NESDIS. Based on the AMSU/MHS SFR, an ATMS SFR algorithm has also been developed. The algorithm performs retrieval in three steps: snowfall detection, retrieval of cloud properties, and estimation of snow particle terminal velocity and snowfall rate. The snowfall detection component utilizes principal component analysis and a logistic regression model. It employs a combination of temperature and water vapor sounding channels to detect the scattering signal from falling snow and derives the probability of snowfall. Cloud properties are retrieved using an inversion method with an iteration algorithm and a two‐stream radiative transfer model. A method adopted to calculate snow particle terminal velocity. Finally, snowfall rate is computed by numerically solving a complex integral. The SFR products are being used mainly in two communities: hydrology and weather forecast. Global blended precipitation products traditionally do not include snowfall derived from satellites because such products were not available operationally in the past. The ATMS and AMSU/MHS SFR now provide the winter precipitation information for these blended precipitation products. Weather forecasters mainly rely on radar and station observations for snowfall forecast. The SFR products can fill in gaps where no conventional snowfall data are available to forecasters. The products can also be used to confirm radar and gauge snowfall data and increase forecasters' confidence in their prediction.

Meng, Huan↗

Uncertainty and Sensitivity Analysis of Afterbody Radiative Heating Predictions for Earth Entry

The objective of this work was to perform sensitivity analysis and uncertainty quantification for afterbody radiative heating predictions of Stardust capsule during Earth entry at peak afterbody radiation conditions. The radiation environment in the afterbody region poses significant challenges for accurate uncertainty quantification and sensitivity analysis due to the complexity of the flow physics, computational cost, and large number of un-certain variables. In this study, first a sparse collocation non-intrusive polynomial chaos approach along with global non-linear sensitivity analysis was used to identify the most significant uncertain variables and reduce the dimensions of the stochastic problem. Then, a total order stochastic expansion was constructed over only the important parameters for an efficient and accurate estimate of the uncertainty in radiation. Based on previous work, 388 uncertain parameters were considered in the radiation model, which came from the thermodynamics, flow field chemistry, and radiation modeling. The sensitivity analysis showed that only four of these variables contributed significantly to afterbody radiation uncertainty, accounting for almost 95% of the uncertainty. These included the electronic- impact excitation rate for N between level 2 and level 5 and rates of three chemical reactions in uencing N, N(+), O, and O(+) number densities in the flow field.

West, Thomas K., IV↗

The SPECTRAL Ice Chamber: Application to Titan's Stratospheric Ice Clouds

An ice chamber for obtaining thin-film transmission spectra of Titan-relevant organic ices between 50 and 11,700 cm−1 (200–0.85 μm) is described in detail in this work. The ice chamber, called the SPECtroscopy of Titan-Related ice AnaLogs chamber, is located in the Spectroscopy for Planetary ICes Environments laboratory at NASA Goddard Space Flight Center. Organic vapors are typically deposited between 30 and 150 K via a variable leak valve onto a chemical vapor deposition diamond substrate, where condensation directly into the solid state occurs. Quantitative thin-film infrared transmission spectra of the given ice or ice mixture are then measured, from which optical constants (complex indices of refraction) are computed. These optical constants in turn provide the necessary input for interpreting radiative transfer analyses of Cassini’s Composite InfraRed Spectrometer observations of Titan’s organic stratospheric ice clouds to determine their chemical compositions, abundances, and vertical distributions as functions of Titan latitude and season.

Anderson, C. M.↗

The SPECTRAL Ice Chamber: Application to Titan's Stratospheric Ice Clouds

An ice chamber for obtaining thin-film transmission spectra of Titan-relevant organic ices between 50 and 11,700 cm(exp −1) (200–0.85 μm) is described in detail in this work. The ice chamber, called the SPECtroscopy of Titan-Related ice AnaLogs chamber, is located in the Spectroscopy for Planetary ICes Environments laboratory at NASA Goddard Space Flight Center. Organic vapors are typically deposited between 30 and 150 K via a variable leak valve onto a chemical vapor deposition diamond substrate, where condensation directly into the solid state occurs. Quantitative thin-film infrared transmission spectra of the given ice or ice mixture are then measured, from which optical constants (complex indices of refraction) are computed. These optical constants in turn provide the necessary input for interpreting radiative transfer analyses of Cassini’s Composite InfraRed Spectrometer observations of Titan’s organic stratospheric ice clouds to determine their chemical compositions, abundances, and vertical distributions as functions of Titan latitude and season.

C. M. Anderson↗

The SPECTRAL Ice Chamber: Application to Titan's Stratospheric Ice Clouds

An ice chamber for obtaining thin-film transmission spectra of Titan-relevant organic ices between 50 and 11,700 cm−1 (200 to 0.85 µm) is described in detail in this work. The ice chamber, called the SPECtroscopy of Titan-Related ice AnaLogs (SPECTRAL) chamber, is located in the Spectroscopy for Planetary ICes Environments (SPICE) laboratory at NASA Goddard Space Flight Center (GSFC). Organic vapors are typically deposited between 30 K and 150 K via a variable leak valve onto a chemical vapor deposition (CVD) diamond substrate, where condensation directly into the solid state occurs. Quantitative thin-film infrared transmission spectra of the given ice or ice mixture are then measured, from which optical constants (complex indices of refraction) are computed. These optical constants in turn provide the necessary input for interpreting radiative transfer analyses of Cassini’s Composite InfraRed Spectrometer (CIRS) observations of Titan’s organic stratospheric ice clouds to determine their chemical compositions, abundances, and vertical distributions as functions of Titan latitude and season.

C. M. Anderson↗

Quantum Mechanical Simulations of Dynamics of Electronic Excitations in Low-Dimensional Photovoltaics Materials

Dynamics of electronically excited states including exciton generation and relaxation, exciton-exciton interaction, and charge/energy transfer and transport, are critical to understanding and optimizing photovoltaic materials. Although considerable progress has been made, accurate experimental characterization of such crucial dynamics remains extremely challenging, especially in low-dimensional materials. In this talk, I will discuss how the advancement of quantum mechanical simulations of the dynamics of electronic excitations can reveal the physical mechanisms hindering or improving solar energy harvest. Specifically, we find that surface dangling-bond defects on silicon quantum dots cause rapid charge recombination and low carrier mobility in the inorganic-organic PV cells. Although small quantum dots are essentially free of defects, their optical gaps are too large. To solve this issue, a full-spectrum-light-absorption scheme is computationally designed, taking advantage of complexity and flexibility of low-dimensional materials consisting of different characteristics and dimensions. In this scheme the multifunctional ligands are used to (1) passivate against oxidation, (2) facilitate interfacial charge transfer, and (3) improve both charge transport and optical absorption. A joint theoretical and experimental study has demonstrated the feasibility of this approach. Finally, I will briefly talk about how this scheme and the well-tested quantum mechanical simulations can be employed to help improve energy-conversion efficiency in perovskite photovoltaics including perovskite-based tandem cells.

Zhigang Wu↗

Rapid Hypersonic Simulations using US3D and Pointwise

For hypersonic simulations, unstructured flow solvers typically have problems predicting surface heat fluxes when strong shocks are present. To address these issues, this paper outlines a workflow that applies best practices developed for structured grids to unstructured meshes. In addition, unstructured grid generation can significantly reduce the time required to create quality grids for complex geometries. Several examples are computed using DPLR, a structured grid flow solver, and US3D flow, an unstructured mesh solver. Results from the two codes are compared, and they show excellent agreement. Overall, the unstructured grid workflow offers a viable and attractive alternative for hypersonic simulations.

C. Tang↗

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