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Flow fields in two- and three-dimensional axisymmetric supersonic inlets are calculated with computer program that uses method of characteristics to compute array of points in flow field. At each point, local pressure, local Mach number, local flow angle, and static pressure are calculated. Program can be used to design and analyze supersonic inlets by determining surface compression rates and throat flow properties.
The aluminide intermetallic compounds are considered potential structural materials for aerospace applications. The B2 binary aluminide FeAl has a melting point in excess of 1500 K, is of simple cubic structure, exits over a wide range of composition with solubility for third elements and is potentially self-protecting in extreme environments. The B2 FeAl compound has been alloyed with 1 to 5 at % ternary additions of Si, Ti, Zr, Hf, Cr, Ni, Co, Nb, Ta, Mo, W, and Re. The alloys were prepared by blending a third elemental powder with prealloyed binary FeAl powder. Consolidation was by hot extrusion at 1250 K. Annealing studies on the extruded rods showed that the third element addition can be classified into three categories based upon the amount of homogenization and the extent of solid solutioning. Constant strain rate compression tests were performed to determine the flow stress as a function of temperature and composition. The mechanical strength behavior was dependent upon the third element homogenization classification.
The aluminide intermetallic compounds are considered potential structural materials for aerospace applications. The B2 binary aluminide FeAl has a melting point in excess of 1500 K, is of simple cubic structure, exists over a wide range of composition with solubility for third elements and is potentially self-protecting in extreme environments. The B2 FeAl compound has been alloyed with 1 to 5 at. pct ternary additions of Si, Ti, Zr, Hf, Cr, Ni, Co, Nb, Ta, Mo, W, and Re. The alloys were prepared by blending a third elemental powder with pre-alloyed binary FeAl powder. Consolidation was by hot extrusion at 1250 K. Annealing studies on the extruded rods showed that the third element addition can be classified into three categories based upon the amount of homogenization and the extent of solid solutioning. Constant strain rate compression tests were performed to determine the flow stress as a function of temperature and composition. The mechanical strength behavior was dependent upon the third element homogenization classification.
The operation of the spaceborne imaging radar-C (SIR-C) is discussed. The SIR-C instrument has been designed to obtain simultaneous multifrequency and simultaneous multipolarization radar images from a low earth orbit. It is a multiparameter imaging radar which will be flown during at least two different seasons. The instrument has been designed to operate in innovative modes such as the squint alignment mode, the extended aperture mode, the scansar mode, and the interferometry mode. The instrument has been designed to demonstrate innovative engineering techniques such as beam nulling for echo tracking, pulse-repetition frquency hopping for Doppler centroid tracking, generating the frequency step chirp for radar parameter flexibility, block floating point quantizing for data rate compression, and elevation beamwidth broadening for increasing the swath illumination.
Proposed scheme under development for transmission of vector-quantized digital video images, vector quantizer codebook updated to adapt quantizer to changing signal statistics. Intended to be realized with electronic neural network. Codebook, which consists of patterns constituting video images, will undergo training during operation and scheme will develop codebooks ordered during training. System enables coding more compact, more immune to noise, and supports variable rate compression.
The Spaceborne Imaging Radar-C is the next radar in the series of spaceborne radar experiments, which began with Seasat and continued with SIR-A and SIR-B. The SIR-C instrument has been designed to obtain simultaneous multifrequency and simultaneous multipolarization radar images from a low earth orbit. It is a multiparameter imaging radar that will be flown during at least two different seasons. The instrument operates in the squint alignment mode, the extended aperture mode, the scansar mode, and the interferometry mode. The instrument uses engineering techniques such as beam nulling for echo tracking, pulse repetition frequency hopping for Doppler centroid tracking, generating the frequency step chirp for radar parameter flexibility, block floating-point quantizing for data rate compression, and elevation beamwidth broadening for increasing the swath illumination.
The perceived quality of images reconstructed from low bit rate compression is severely degraded by the appearance of transform coding artifacts. This paper proposes a method for producing higher quality reconstructed images based on a stochastic model for the image data. Quantization (scalar or vector) partitions the transform coefficient space and maps all points in a partition cell to a representative reconstruction point, usually taken as the centroid of the cell. The proposed image estimation technique selects the reconstruction point within the quantization partition cell which results in a reconstructed image which best fits a non-Gaussian Markov random field (MRF) image model. This approach results in a convex constrained optimization problem which can be solved iteratively. At each iteration, the gradient projection method is used to update the estimate based on the image model. In the transform domain, the resulting coefficient reconstruction points are projected to the particular quantization partition cells defined by the compressed image. Experimental results will be shown for images compressed using scalar quantization of block DCT and using vector quantization of subband wavelet transform. The proposed image decompression provides a reconstructed image with reduced visibility of transform coding artifacts and superior perceived quality.
Coherent Vortex Simulation (CVS) filtering has been applied to Direct Numerical Simulation (DNS) data of forced and unforced time-developing turbulent mixing layers. CVS filtering splits the turbulent flow into two orthogonal parts, one corresponding to coherent vortices and the other to incoherent background flow. We have shown that the coherent vortices can be represented by few wavelet modes and that these modes are sufficient to reproduce the vorticity probability distribution function (PDF) and the energy spectrum over the entire inertial range. The remaining incoherent background flow is homogeneous, has small amplitude, and is uncorrelated. These results are compared with those obtained for the same compression rate using large eddy simulation (LES) filtering. In contrast to the incoherent background flow of CVS filtering, the LES subgrid scales have a much larger amplitude and are correlated, which makes their statistical modeling more difficult.
The greatest advantage gained from hyperspectral imagery is that narrow spectral features can be used to give more information about materials than was previously possible with broad-band multispectral imagery. For many applications, the new larger data volumes from such hyperspectral sensors, however, present a challenge for traditional processing techniques. For example, the actual identification of each ground surface pixel by its corresponding reflecting spectral signature is still one of the most difficult challenges in the exploitation of this advanced technology, because of the immense volume of data collected. Therefore, conventional classification methods require a preprocessing step of dimension reduction to conquer the so-called "curse of dimensionality." Spectral data reduction using wavelet decomposition could be useful, as it does not only reduce the data volume, but also preserves the distinctions between spectral signatures. This characteristic is related to the intrinsic property of wavelet transforms that preserves high- and low-frequency features during the signal decomposition, therefore preserving peaks and valleys found in typical spectra. When comparing to the most widespread dimension reduction technique, the Principal Component Analysis (PCA), and looking at the same level of compression rate, we show that Wavelet Reduction yields better classification accuracy, for hyperspectral data processed with a conventional supervised classification such as a maximum likelihood method.
While the IDSS standard is specified to enable androgynous docking resulting in a seal-on-seal (SoS) mated configuration, current docking systems and their seals were not certified to do so. This IRAD project goal is to characterize SoS performance including leak rates, compression loads, and adhesion loads under aligned and misaligned conditions at subscale as an initial step toward androgynous docking certification.
Keeping a driver focused on the road is one of the most critical steps in insuring the safe operation of a vehicle. The Strategic Highway Research Program 2 (SHRP2) has over 3,100 recorded videos of volunteer drivers during a period of 2 years. This extensive naturalistic driving study (NDS) contains over one million hours of video and associated data that could aid safety researchers in understanding where the driver s attention is focused. Manual analysis of this data is infeasible, therefore efforts are underway to develop automated feature extraction algorithms to process and characterize the data. The real-world nature, volume, and acquisition conditions are unmatched in the transportation community, but there are also challenges because the data has relatively low resolution, high compression rates, and differing illumination conditions. A smaller dataset, the head pose validation study, is available which used the same recording equipment as SHRP2 but is more easily accessible with less privacy constraints. In this work we report initial head pose accuracy using commercial and open source face pose estimation algorithms on the head pose validation data set.
Reducing parameter redundancies in neural network architectures is crucial for achieving feasible computational and memory requirements during train and inference of large networks. Given its easy implementation and flexibility, one promising approach is layer factorization, which reshapes weight tensors into a matrix format and parameterizes it as the product of two rank-r matrices. However, this family of approaches often requires an initial full-model warm-up phase, prior knowledge of a feasible rank, and it is sensitive to parameter initialization.In this work, we introduce a novel approach to train the factors of a Tucker decomposition of the weight tensors. Our training proposal proves to be optimal in locally approximating the original unfactorized dynamics and stable for the initialization. Furthermore, the rank of each mode is dynamically updated during training.We provide a theoretical analysis of the algorithm, showing convergence, approximation and local descent guarantees. The method's performance is further illustrated through a variety of experiments, showing remarkable training compression rates and comparable or even better performance than the full baseline and alternative layer factorization strategies.
Here, the mechanical properties and deformation mechanisms of single crystal magnesium under c-axis quasi-static and high-strain rate compressions are investigated through in situ scanning electron microscope (SEM) experiments and post-mortem transmission electron microscope (TEM) characterization. The findings revealed that ductility and high rates of hardening are preserved for pillars as large as 15 μm. Furthermore, rate effects result in a mild increase in flow stress with plastic deformations controlled primarily by the slip of type dislocations. Importantly and in contrast to other literature reports, plastic deformation occurs in the absence of twining. As the strain increases and plastic deformation exceeds about 4%, crystal rotation activates basal slip, <$\mathrm{a}$> type dislocations, resulting in a more rate independent flow stress. TEM observation on micropillars compressed at a strain rate of 250/s, revealed the activation of {${11}$$\bar{2}$$\bar{2}$} < $\bar{1}$$\bar{1}23$ > slip systems and high mobility of screw dislocations as major contributors to plastic strains in excess of 10% without fracture. These findings are relevant to the design of lightweight materials used in transportation systems, e.g., selection of material grain size. Moreover, the experimental data here reported provides the materials science community with a unique opportunity to validate discrete dislocation dynamics (DDD) formulations employed in multiscale design of materials.
Image compression schemes abound with little work which compares their bit-rate performance based on subjective fidelity measures. Statistical measures of image fidelity, such as squared error measures, do not necessarily correspond to subjective measures of image fidelity. Most previous comparisons of compression techniques have been based on these statistical measures. A psychophysical method has been used to estimate, for a number of compression techniques, a threshold bit-rate yielding a criterion level of performance in discriminating original and compressed images. The compression techniques studied include block truncation, Laplacian pyramid, block discrete cosine transform, with and without a human visual system scaling, and cortex transform coders.
Here, iron was ramp-compressed over timescales of 3 ≤ t(ns) ≤ 300 to study the time-dependence of the α→ε (bcc→hcp) phase transformation. Onset stresses (σ α→ε ) for the transformation ~14.8-38.4 GPa were determined through laser and magnetic ramp-compression techniques where the transition strain-rate was varied between 10 6 ≤ $\dot{μ}$ α→ε (s ₋1 ) ≤ 5×10 8 . We find σ α→ε = 10.8 + 0.55 ln($\dot{μ}$ α→ε ) for $\dot{μ}$ α→ε < 10 6 /s and σ α→ε = 1.15($\dot{μ}$ α→ε ) 0.18 for $\dot{μ}$ α→ε > 10 6 /s. This $\dot{μ}$ response is quite similar to recent results on incipient plasticity in Fe suggesting that under high rate ramp compression the α→ε phase transition and plastic deformation occur through similar mechanisms, e.g., the rate limiting step for $\dot{μ}$ > 10 6 /s is due to phonon scattering from defects moving to relieve strain. We show that over-pressurization of equilibrium phase boundaries is a common feature exhibited under high strain-rate compression of many materials encompassing many orders of magnitude of strain-rate.
An image compression system recently developed for compression of digital images dominated by point sources is presented. Encoding consists of minimum-mean removal, vector quantization, adaptive threshold truncation, and modified Huffman encoding. Simulations are presented showing that the peaks corresponding to point sources can be transmitted losslessly for low signal-to-noise ratios (SNR) and high point source densities while maintaining a reduced output bit rate. Encoding and decoding hardware has been built and tested which processes 552,960 12-bit pixels per second at compression rates of 10:1 and 4:1. Simulation results are presented for the 10:1 case only.
Polymers are increasingly being utilized as monolithic materials and composite matrices for structural applications historically reserved for metals. High strain and high strain-rate applications in aerospace, defense, and automotive industries have lead to interest in utilizing the ability of many polymers to withstand extensions to failure of several hundred percent, often without localization or necking and their strong rate dependence. A broad range of characterization techniques will be presented for semi-crystalline polymers and composites including elastic-plastic fracture, split Hopkinson pressure bar (SHPB), plate impact including soft-recovery and lateral gage measurements and Taylor Impact. Gas-launched, plate impact experiments have been performed on pedigreed PTFE 7C, mounted in momentum-trapped, shock assemblies, with impact pressures above and below the phase II to phase III crystalline transition to probe subtle changes in the crystallinity, microstructure, and mechanical response of PTFE. Observed strong anisotropy on the hugoniot and spall behavior of fiber-reinforced composites will be discussed. Polymers are known to exhibit a strong dependence of the yield stress on temperature and strain-rate that are often observed to be linear for temperature and logarithmic for strain-rate. Temperature and strain-rate dependence will be reviewed in terms of classic time-temperature superposition and an empirical mapping function for superposition between temperature and strain-rate. The recent extension of the new Dynamic-Tensile-Extrusion (Dyn-Ten-Ext) technique to probe the dynamic tensile responses of polymers will be discussed, where more irregular deformation and stochastic-based damage and failure mechanisms than the stable plastic elongation and shear instabilities observed that in metals. The opportunity to use of Dyn-Ten-Ext to probe incipient damage at very high strain-rate by linking in situ and post mortem experimental observations with high-fidelity simulation will be introduced. The potential to study polymer deformation under even more extreme conditions by employing explosive drive to induce Rayleigh-Taylor (RT) growth linking with in situ diagnosis by proton radiography will be proposed. Finally, a case study of collaboration between experimentalists and modelers to study the shock induced phase transition of PTFE presented. Building on a history of shock and Diamond Anvil Cell data it has long been know that PTFE exhibits a pressure induced phase transition at 0.7 GPa. The transition has historically been assumed and reported to be dependent on the hydrostatic pressure. However, studies employing neutron diffraction have suggested the phase transition is driven by only the principle stress applied to the compliant direction of crystalline domain. A multiphase model based on the Maxwell-type viscoelastic formulation was developed to include the stress deviator to drive potential martensitic transition and time to reflects the kinetic nature of the transitions demonstrating the need to account for both a martensitic nature and kinetics of the transition to capture subtle experimental observables.
Abstract not provided.