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The analysis of a layered planar structure consisting of different bianisotropic materials is performed, in the frequency domain. Reflection and transmission coefficients are determined via a chain-matrix algorithm. Numerical results are presented and discussed.
The periodic moment method (PMM) solution for the scattering from two-dimensional lossy dielectric bodies is developed in this paper. The purpose is to design microwave wedge absorber for low reflectivity so that one can improve the performance of anechoic chamber measurements. With PMM, the reflection and transmission coefficients of periodically distributed bodies illuminated by a plane wave have been accurately calculated using a Cray Y-MP supercomputer. Through these studies, some wedge absorber configurations have been designed, fabricated, and then tested in the OSU/ESL compact range measurement facility. Two 8 in. commercial wedges, a curved wedge, and a four-layer wedge are studied in this paper. In all cases, good agreement between calculations and measurements has been obtained.
The basic features of a new and improved bulk-microphysical parameterization capable of simulating the hydrometeor structure of convective systems in all types of large-scale environments (with minimal adjustment of coefficients) are studied. Reflectivities simulated from the model are compared with radar observations of an intense midlatitude convective system. Simulated reflectivities using the novel four-class ice scheme with a microphysical parameterization rain distribution at 105 min are illustrated. Preliminary results indicate that this new ice scheme works efficiently in simulating midlatitude continental storms.
Four local principles are proven for waves propagating in a layered medium with a variable wave speed. These principles are (1) that inhomogeneities increase the amplitude of waves generated by a source of fixed strength, (2) that inhomogeneities reduce spatial oscillation, or increase the wavelength, (3) that inhomogeneities decrease transmission, or increase reflection, and (4) that transmission increases monotonically with frequency. Definitions of inhomogeneity, local wave function, and local reflection and transmission coefficients are made as a basis for stating these principles.
A layered planar structure consisting of different bianisotropic materials separated by jump-immittance sheets is considered. Reflection and transmission coefficients are determined via a chain-matrix algorithm. Applications are important for radomes and radar-absorbing materials.
TFaNS is the Tone Fan Noise Design/Prediction System developed by Pratt & Whitney under contract to NASA Lewis (presently NASA Glenn). The purpose of this system is to predict tone noise emanating from a fan stage including the effects of reflection and transmission by the rotor and stator and by the duct inlet and nozzle. These effects have been added to an existing annular duct/isolated stator noise prediction capability. TFaNS consists of: The codes that compute the acoustic properties (reflection and transmission coefficients) of the various elements and write them to files. Cup3D: Fan Noise Coupling Code that reads these files, solves the coupling problem, and outputs the desired noise predictions. AWAKEN: CFD/Measured Wake Postprocessor which reformats CFD wake predictions and/or measured wake data so it can be used by the system. This volume of the report provides technical background for TFaNS including the organization of the system and CUP3D technical documentation. This document also provides information for code developers who must write Acoustic Property Files in the CUP3D format. This report is divided into three volumes: Volume I: System Description, CUP3D Technical Documentation, and Manual for Code Developers; Volume II: User's Manual, TFaNS Vers. 1.4; Volume III: Evaluation of System Codes.
TFaNS is the Tone Fan Noise Design/Prediction System developed by Pratt & Whitney under contract to NASA Lewis (presently NASA Glenn). The purpose of this system is to predict tone noise emanating from a fan stage including the effects of reflection and transmission by the rotor and stator and by the duct inlet and nozzle. These effects have been added to an existing annular duct/isolated stator noise prediction capability. TFaNS consists of: the codes that compute the acoustic properties (reflection and transmission coefficients) of the various elements and write them to files. CUP3D: Fan Noise Coupling Code that reads these files, solves the coupling problem, and outputs the desired noise predictions. AWAKEN: CFD/Measured Wake Postprocessor which reformats CFD wake predictions and/or measured wake data so it can be used by the system. This volume of the report provides information on code input and file structure essential for potential users of TFANS. This report is divided into three volumes: Volume 1. System Description, CUP3D Technical Documentation, and Manual for Code Developers; Volume 2. User's Manual, TFANS Vers. 1.4; Volume 3. Evaluation of System Codes.
TFANS is the Tone Fan Noise Design/Prediction System developed by Pratt & Whitney under contract to NASA Lewis (presently NASA Glenn). The purpose of this system is to predict tone noise emanating from a fan stage including the effects of reflection and transmission by the rotor and stator and by the duct inlet and nozzle. These effects have been added to an existing annular duct/isolated stator noise prediction capability. TFANS consists of: The codes that compute the acoustic properties (reflection and transmission coefficients) of the various elements and write them to files. Cup3D: Fan Noise Coupling Code that reads these files, solves the coupling problem, and outputs the desired noise predictions. AWAKEN: CFD/Measured Wake Postprocessor which reformats CFD wake predictions and/or measured wake data so it can be used by the system. This volume of the report evaluates TFANS versus full-scale and ADP 22" fig data using the semi-empirical wake modelling in the system. This report is divided into three volumes: Volume 1: System Description, CUP3D Technical Documentation, and Manual for Code Developers; Volume II: User's Manual, TFANS Version 1.4; Volume III: Evaluation of System Codes.
For scattering calculations involving nonspherical particles such as ice crystals, we show that the transverse wave condition is not applicable to the refracted electromagnetic wave in the context of geometric optics when absorption is involved. Either the TM wave condition (i.e., where the magnetic field of the refracted wave is transverse with respect to the wave direction) or the TE wave condition (i.e., where the electric field is transverse with respect to the propagating direction of the wave) may be assumed for the refracted wave in an absorbing medium to locally satisfy the electromagnetic boundary condition in the ray tracing calculation. The wave mode assumed for the refracted wave affects both the reflection and refraction coefficients. As a result, a nonunique solution for these coefficients is derived from the electromagnetic boundary condition. In this study we have identified the appropriate solution for the Fresnel reflection/refraction coefficients in light scattering calculation based on the ray tracing technique. We present the 3 x 2 refraction or transmission matrix that completely accounts for the inhomogeneity of the refracted wave in an absorbing medium. Using the Fresnel coefficients for an absorbing medium, we derive an asymptotic solution in an analytical format for the scattering properties of a general polyhedral particle. Numerical results are presented for hexagonal plates and columns with both preferred and random orientations. The asymptotic theory can produce reasonable accuracy in the phase function calculations in the infrared window region (wavelengths near 10 micron) if the particle size (in diameter) is on the order of 40 micron or larger. However, since strong absorption is assumed in the computation of the single-scattering albedo in the asymptotic theory, the single scattering albedo does not change with variation of the particle size. As a result, the asymptotic theory can lead to substantial errors in the computation of single-scattering albedo for small and moderate particle sizes. However, from comparison of the asymptotic results with the FDTD solution, it is expected that a convergence between the FDTD results and the asymptotic theory results can be reached when the particle size approaches 200 micron. We show that the phase function at side-scattering and backscattering angles is insensitive to particle shape if the random orientation condition is assumed. However, if preferred orientations are assumed for particles, the phase function has a strong dependence on scattering azimuthal angle. The single-scattering albedo also shows very strong dependence on the inclination angle of incident radiation with respect to the rotating axis for the preferred particle orientations.
TFaNS is the Tone Fan Noise Design/Prediction System developed by Pratt & Whitney under contract to NASA Glenn. The purpose of this system is to predict tone noise emanating from a fan stage including the effects of reflection and transmission by the rotor and stator and by the duct inlet and nozzle. The first version of this design system was developed under a previous NASA contract. Several improvements have been made to TFaNS. This users' manual shows how to run this new system. TFaNS consists of the codes that compute the acoustic properties (reflection and transmission coefficients) of the various elements and writes them to files, CUP3D Fan Noise Coupling Code that reads these files, solves the coupling problem, and outputs the desired noise predictions, and AWAKEN CFD/Measured Wake Postprocessor which reformats CFD wake predictions and/or measured wake data so they can be used by the system. This report provides information on code input and file structure essential for potential users of TFaNS.
A method of retrieving cloud microphysical properties using combined observations from both cloud radar and lidar is introduced. This retrieval makes use of an improvement to the traditional optimal estimation retrieval method, whereby a series of corrections are applied to the state vector during the search for an iterative solution. This allows faster convergence to a solution and is less processor intensive. The method is first applied to a synthetic cloud t o demonstrate its validity, and it is shown that the retrieval reliably reproduces vertical profiles of ice water content. The retrieval method is then applied to radar and lidar observations from the CRYSTAL-FACE experiment, and vertical profiles of ice crystal diameter, number concentration, and ice water content are retrieved for a cirrus cloud layers observed one day of that experiment. The validity of the relationship between visible extinction coefficient and radar reflectivity was examined. While synthetic tests showed such a functional relationship, the measured data only partially supported such a conclusion. This is due to errors in the forward model (as explained above) as well as errors in the data sets, including possible mismatch between lidar and radar profiles or errors in the optical depth. Empirical relationships between number concentrations and mean particle diameter were also examined. The results indicate that a distinct and robust relationship exists between these retrieved quantities and it is argued that such a relationship is more than an artifact of the retrieval process offering insight into the nature of the microphysical processes taking place in cirrus.
An efficient and powerful computational method is presented to synthesize a meta-material to specified electromagnetic properties. Using the periodicity of meta-materials, the Finite Element Methodology (FEM) is developed to estimate the reflection and transmission through the meta-material structure for a normal plane wave incidence. For efficient computations of the reflection and transmission over a wide band frequency range through a meta-material a Finite Difference Time Domain (FDTD) approach is also developed. Using the Nicholson-Ross method and the Genetic Algorithms, a robust procedure to extract electromagnetic properties of meta-material from the knowledge of its reflection and transmission coefficients is described. Few numerical examples are also presented to validate the present approach.
Based on a theoretical model of the propagation of electromagnetic waves through a hypersonically induced plasma, it has been demonstrated that the classical radiofrequency communications blackout that is experienced during atmospheric reentry can be mitigated through the appropriate control of an external magnetic field of nominal magnitude. The model is based on the kinetic equation treatment of Vlasov and involves an analytical solution for the electric and magnetic fields within the plasma allowing for a description of the attendant transmission, reflection and absorption coefficients. The ability to transmit through the magnetized plasma is due to the magnetic windows that are created within the plasma via the well-known whistler modes of propagation. The case of 2 GHz transmission through a re-entry plasma is considered. The coefficients are found to be highly sensitive to the prevailing electron density and will thus require a dynamic control mechanism to vary the magnetic field as the plasma evolves through the re-entry phase.
Joint interpretation of disparate geophysical datasets helps reduce drawbacks that can result from analyzing them individually. The Apollo seismic network was situated on the lunar nearside surface in a roughly equilateral triangle having sides approximately 1000 km long, with stations 12/14 nearly co-located at one corner. Due to this limited geographical extent, near-surface ray coverage from moonquakes is low, but increase with depth. In comparison, gravity surveys and their resulting gravity anomaly maps have traditionally offered optimal resolution at crustal depths. Gravimetric maps and seismic data sets are therefor well suited to joint inversion, since the complementary information reduces inherent model ambiguity. We will perform a joint inversion of Apollo seismic delay times and gravity data collected by GRAIL lunar gravity mission, in order to recover seismic velocity and density as a function of latitude, longitude and depth within the Moon. We will relate density (rho) to seismic velocity (v) using a linear relationship that is allowed to be depth-dependent. The corresponding coefficient (B) can reflect a variety of material properties that vary with depth, including temperature and composition. The inversion seeks to recover the set of rho, v, and B perturbations that minimize (in a least-squares sense) the difference between the observed and calculated data.
To probe a planet's interior, seismology provides the most direct constraints on the variables that govern the dynamic properties of the body. However, the GRAIL (Gravity Recovery and Interior Laboratory) mission's high-resolution measurements of the lunar gravity field provide constraints on crustal thickness, mantle structure, core radius and stratification, and core state (solid vs. molten). These data complement seismic investigations, and joint interpretation permits improved constraints on the Moon's internal structure. Joint interpretation of disparate geophysical datasets helps reduce drawbacks that can result from analyzing them individually. The Apollo seismic network was situated on the lunar nearside surface in a roughly equilateral triangle having sides approximately 1000 km long, with stations 12/14 nearly co-located at one corner. Due to this limited geographical extent, near-surface ray coverage from moonquakes is low, but increase with depth. In comparison, gravity surveys and their resulting gravity anomaly maps have traditionally offered optimal resolution at crustal depths. Gravimetric maps and seismic data sets are therefor well suited to joint inversion, since the complementary information reduces inherent model ambiguity. We will perform a joint inversion of Apollo seismic delay times and gravity data collected by GRAIL lunar gravity mission, in order to recover seismic velocity and density as a function of latitude, longitude and depth within the Moon. We will relate density (rho) to seismic velocity (v) using a linear relationship that is allowed to be depth-dependent. The corresponding coefficient (B) can reflect a variety of material properties that vary with depth, including temperature and composition. The inversion seeks to recover the set of rho, v, and B perturbations that minimize (in a least-squares sense) the difference between the observed and calculated data.
Joint interpretation of disparate geophysical datasets helps reduce drawbacks that can result from analyzing them individually. The Apollo seismic network was situated on the lunar nearside surface in a roughly equilateral triangle having sides approximately 1000 km long, with stations 12/14 nearly co-located at one corner. Due to this limited geographical extent, near-surface ray coverage from moonquakes is low, but increases with depth. In comparison, gravity surveys and their resulting gravity anomaly maps have traditionally offered optimal resolution at crustal depths. Gravimetric maps and seismic data sets are therefore well suited to joint inversion, since the complementary information reduces inherent model ambiguity. Previous joint inversions of the Apollo seismic data (seismic phase arrival times) and Clementine- or Lunar Prospector-derived gravity data (mass and moment of inertia) attempted to recover the subsurface structure of the Moon by focusing on hypothetical lunar compositions that explored the density/velocity relationship. These efforts typically searched for the best fitting thermodynamically calculated velocity/density model, and allowed variables like core size, velocity, and/or composition to vary freely. Seismic velocity profiles derived from the Apollo seismic data through travel time inversion vary both in the depth of the crust and mantle layers, and the seismic velocities and densities assigned to those layers. The lunar mass and moment of inertia likewise only constrain gross variations in the density profile beyond that of a uniform density sphere. As a result, composition and structure models previously obtained by jointly inverting these data retain the original uncertainties inherent in the input data sets. We perform a joint inversion of Apollo seismic delay times and gravity data collected by the GRAIL lunar gravity mission, in order to recover seismic velocity and density as a function of latitude, longitude, and depth within the Moon. We relate density (p) to seismic velocity (v) using a depth-dependent linear relationship. The corresponding coefficient (B) can reflect a variety of material properties, including temperature and composition. The inversion seeks to recover the set of p, v, and B perturbations that minimize (in a least-squares sense) the difference between the observed and calculated data.
An optical model of solar sail material originally derived at JPL in 1978 has since served as the de facto standard for NASA and other solar sail researchers. The optical model includes terms for specular and diffuse reflection, thermal emission, and non-Lambertian diffuse reflection. The standard coefficients for these terms are based on tests of 2.5 micrometer Kapton sail material coated with 100 nm of aluminum on the front side and chromium on the back side. The original derivation of these coefficients was documented in an internal JPL technical memorandum that is no longer available. Additionally more recent optical testing has taken place and different materials have been used or are under consideration by various researchers for solar sails. Here, where possible, we re-derive the optical coefficients from the 1978 model and update them to accommodate newer test results and sail material. The source of the commonly used value for the front side non-Lambertian coefficient is not clear, so we investigate that coefficient in detail. Although this research is primarily designed to support the upcoming NASA NEA Scout and Lunar Flashlight solar sail missions, the results are also of interest to the wider solar sail community.
The NASA Short-term Prediction Research and Transition (SPoRT) Center has begun to develop products to address operational challenges and enhance safety during the lifecycle of lightning activity, and conduct evaluations in concentrated R2O/O2R efforts. The product evaluated for this study is Lightning Artificial Intelligence (A.I.), which predicts the probability of lightning out to 15 minutes in advance and spatially maps it using filled color contours. Lightning A.I. uses reflectivity, differential reflectivity, and correlation coefficient data from a subset of radars within the NEXRAD network to generate lightning probabilities at approximately 2 km resolution. The domains, spanning 145 x 145 km are centered over NASA-affiliated centers across the CONUS and use radar data which are closest in proximity. Lightning A.I. was developed with intended use by emergency managers at NASA centers. However, National Weather Service (NWS) offices are also often tasked with monitoring and forecasting the threat for lightning within their County Warning Areas for various impact-based decision support services. These forecasts are typically provided for aviation operations and large-scale, outdoor events, which may have varying safety requirements for decision-making based on lightning proximity and recency. The NASA SPoRT center conducted an assessment of the operational uses of Lightning A.I by various collaborative NWS Offices from late July into early September. This assessment included feedback from participants on both the product itself as well as its accessibility within the new, interactive NASA SPoRT Lightning Viewer. This presentation will include background information about Lightning A.I. and highlight results from this assessment. The feedback from the assessment will be used to inform research on any necessary modifications to this and future lightning products to assist end users.