A nonintrusive measure of the exhaust plume and immediate sound field produced by a cluster of two thrust optimized parabolic contour nozzles is studied during two steady-state conditions. The first condition is at a nozzle pressure ratio of 25, at which point the flow is in a restricted-shock separated state. The second condition is at a nozzle pressure ratio of 37 and is when the flow and internal shock pattern transition rapidly between free-shock separated flow and the end-effects regime. These end-effects regime pulsations produce significant vibroacoustic loads due to the intermittent breathing of the last trapped annular separation bubble with the ambient. The exhaust plumes and surrounding sound field are first visualized by way of retroreflective shadowgraphy. Radon transforms of the spatially resolved shadowgraphy images are then used to characterize the statistical behavior of the acoustic wave fronts that reside within the hydrodynamic periphery of the nozzle flow. The findings reveal quantitative evidence of the sources of most intense vibroacoustic loads during the end-effects regime of clustered rockets.
Critical path analysis (CPA), originally developed to describe electrical conductance in semiconductors, has been shown recently to hold some promise in describing transport properties of porous media. I applied some previously developed concepts in CPA and percolation theory to predict permeability in a suite of sandstone, carbonate, and clay-rich samples. I assumed that the pore sizes in my samples exhibited fractal scaling and expressed the electrical formation factor as a function of porosity using universal scaling from percolation theory. The resulting CPA permeability predictions match the measured values very well. In addition, I show how considering the scale-dependence of the percolation threshold yields two characteristic length scales for transport properties: the critical pore size, and the sample size. This work suggests that the CPA framework is appropriate for describing transport properties of natural porous media, and provides a theoretical basis for understanding the permeability of tight rocks like shale in which laboratory permeability measurements are difficult.
Raman spectroscopy (RS) is proving to be a valuable tool for real time noninvasive skin cancer detection via optical fiber probe. However, current methods utilizing RS for skin cancer diagnosis rely on statistically based algorithms to provide tissue classification and do not elucidate the underlying biophysical changes of skin tissue. Therefore, we aim to use RS to explore skin biochemical and structural characteristics and then correlate the Raman spectrum of skin tissue with its disease state. We have built a custom confocal micro-Raman spectrometer system with an 830nm laser light. The high resolution capability of the system allows us to measure spectroscopic features from individual tissue components in situ. Raman images were collected from human skin samples from Mohs surgical biopsy, which were then compared with confocal laser scanning, two-photon fluorescence and hematoxylin and eosin-stained images to develop a linear model of skin tissue Raman spectra. In this model, macroscopic tissue spectra obtained from RS fiber probe were fit into a linear combination of individual basis spectra of primary skin constituents. The fit coefficient of the model explains the biophysical changes spanning a range of normal and various disease states. The model allows for determining parameters similar to that a pathologist is familiar reading and will be a significant guidance in developing RS diagnostic decision schemes.
The spatial evolution of acoustic waveforms produced by a laboratory-scale Mach 3 jet are investigated using both 1∕4 in. and 1∕8 in. pressure field microphones located along rays emanating from the postpotential core where the peak sound emission is found to occur. The measurements are acquired in a fully anechoic chamber, where ground or other large surface reflections are minimal. Various statistical metrics are examined along the peak emission path, where they are shown to undergo rapid changes within 2m from the source region. An experimentally validated wave-packet model is then used to confirm the location where the pressure amplitude along the peak emission path transitions from cylindrical to spherical decay. Various source amplitudes, provided by the wave-packet model, are then used to estimate shock formation distance and Gol’dberg numbers for diverging waves. The findings suggest that cumulative nonlinear distortion is likely to occur at laboratory scale near the jet flow, where the waveform amplitude decays cylindrically, but less likely to occur farther from the jet flow, where the waveform amplitude decays spherically. Direct inspection of the raw time series reveals how steepened waveforms are generated by rogue like waves that form from the constructive interference of waves from neighboring sources as opposed to classical cumulative nonlinear distortion.
Abstract. We illustrate wide-field imaging of skin using a structured light (SL) approach that highlights the contrast from superficial tissue scattering. Setting the spatial frequency of the SL in a regime that limits the penetration depth effectively gates the image for photons that originate from the skin surface. Further, rendering the SL images in a color format provides an intuitive format for viewing skin pathologies. We demonstrate this approach in skin pathologies using a custom-built handheld SL imaging system.
Nitrogen sorption isotherms measured at 77K are widely used for pore-scale characterization of shale and other porous materials with nanometer scale pore size range. We previously built a pore throat network for simulation of nitrogen sorption that modeled different types of pore size distribution and connectivity (specifically of porous media with bimodal pore sizes), but assumed spherical pore and cylindrical throat shapes. In a separate work, we recently applied a modified lattice density functional theory (LDFT) to adsorption modeling for pores with different shapes. The model was implemented for an ideal porous material with a uniform pore size. In this study we combine the pore network with LDFT theory to study the effects of pore size, shape, connectivity and surface chemistry heterogeneity on nitrogen adsorption and desorption isotherms. A multi-scale network model is modified with pores of bimodal size distribution (representing inter-granular, intra-granular and/or organic matter pores). LDFT theory is applied to every pore in the network. This model is further applied to sorption analysis of core samples from Woodford shale, Cameo coal and tight Middle East carbonate. By matching simulated nitrogen sorption curves with experimental ones, we obtain not only the pore size distribution, but also pore shape, connectivity and surface energy. Results show that for Cameo coal both slit and cylindrical pore networks give a good match, while for Woodford shale and tight Middle East carbonate, the best match is achieved with a cylindrical pore network. The developed model aids formation evaluation and reservoir productivity estimation. Parameters obtained from this model can serve as important input into reservoir-scale numerical simulators. Results on the effects of heterogeneity (pore size, shape, and surface energy) can be recorded in look-up tables, thus accelerating applications in petrophysical characterization.
Nuclear magnetic resonance (NMR) relaxation time distributions are frequently combined with mercury intrusion capillary pressure (MICP) measurements to allow determination of pore or pore throat size distributions directly from the NMR data. The combination of these two measurements offers an advantage over high-resolution imaging techniques in terms of cost and measurement time, and can provide estimates of pore sizes for pores below imaging resolution. However, the methods that are typically employed to combine NMR and MICP measurements do not necessarily honor the way in which the two different measurements respond to the size distribution and connectivity of the pore system. We present a method for combining NMR and MICP data that is based on percolation theory and the relationship between bond occupation probability and the probability that a bond is part of a percolating cluster. The method yields results that compare very well with pore sizes measured by high-resolution microtomography, and provides particular improvement in media with broad pore size distributions and large percolation thresholds.