686 research outputs found

    Effect of Mass Transfer on Aeroheating in Hypersonic Chemically Reacting Boundary Layers

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    Heat flux characterization of high-enthalpy boundary layer flows is key to optimize the performance and design of Thermal Protection System of next generation aerospace vehicles [1]. At atmospheric entry hypersonic speeds, ablation as well as surface catalycity impact boundary layer aeroheating. Out-gassing occurring from an ablative surface in planetary entry environment introduces a rich set of problems in thermodynamic, fluid dynamic, and material pyrolysis. Ablation leads to out-gassing and surface roughness, both of which are known to affect surface heating in hypersonic chemically reacting boundary layers via three main routes: gas blowing into the boundary layer from the wall, changing the surface heat transfer due to wall-flow chemical reactions, and modifying surface roughness via ablative processes

    Comparison of the Efficacy of two Anticonvulsants, Phenytoin and Valproate to Improve PCP and d-amphetamine Induced Deficits in a Reversal Learning Task in the Rat

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    Recent studies in our laboratory have shown that PCP (phencyclidine) and d-amphetamine induce a cognitive deficit in rats, in a paradigm of potential relevance for the pathology of schizophrenia. Atypical, but not classical antipsychotics and the anticonvulsant, lamotrigine have been shown to prevent a selective reversal learning deficit induced by PCP. In contrast, only haloperidol reversed the d-amphetamine-induced deficit. The present study aimed to explore the ability of two anticonvulsants with differing mechanism of action, valproate and phenytoin to attenuate the cognitive deficits induced by PCP and d-amphetamine in the reversal learning paradigm. PCP at 1.5 mg/kg and d-amphetamine at 0.5 mg/kg both produced a selective and significant reduction in performance of the reversal phase with no effect on the initial phase of the task in female-hooded Lister rats. Valproate (25–200 mg/kg) and phenytoin (25–50 mg/kg) had no effect on performance when administered alone. Valproate (100–200 mg/kg), whose principle action is thought to be the enhancement of GABA transmission, was unable to prevent the cognitive deficit induced by either PCP or d-amphetamine. Conversely, phenytoin (50 mg/kg), a use-dependent sodium channel inhibitor, significantly prevented the deficit induced by PCP, but not d-amphetamine. These results add to our earlier work with lamotrigine, and suggest that sodium channel blockade may be a mechanism by which some anticonvulsant drugs can prevent the PCP-induced deficit. These data have implications for the use of anticonvulsant drugs in the treatment of cognitive or psychotic disorders

    Microscale Analysis of Spacecraft Heat Shields

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    Imagine entering Earths atmosphere after returning from the outer solar system. A heat shield less than 2 inches thick protects you from temperatures up to 2,900 Celsius (5,252 Fahrenheit). Such conditions were experienced by NASAs Stardust capsule during reentry in 2006. The only materials capable of providing the necessary protection are composites with complex microstructures. Evaluating these materials is difficult, requiring precise knowledge of their properties. To this end, NASA scientists are developing research codes to compute material properties and simulate ablation at the microscale using agency supercomputers. Utilizing these tools, along with experiments, researchers are working to push the limits of spaceflight, allowing for greater flexibility in future space missions

    Preliminary Measurements of the Motion of Arcjet Current Channel Using Inductive Magnetic Probes

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    This paper covers the design and first measurements of non-perturbative, external inductive magnetic diagnostics for arcjet constrictors which can measure the motion of the arc current channel. These measurements of arc motion are motivated by previous simulations using the ARC Heater Simulator (ARCHeS), which predicted unsteady arc motion due to the magnetic kink instability. Measurements of the kink instability are relevant to characterizing motion of the enthalpy profile of the arcjet, the arcjet operational stability, and electrode damage due to associated arc detachment events. These first measurements indicate 4 mm oscillations at 0.5-2 kHz of the current profile

    Tortuosity Computations of Porous Materials using the Direct Simulation Monte Carlo

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    Low-density carbon fiber preforms, used as thermal protection systems (TPS) materials for planetary entry systems, have permeable, highly porous microstructures consisting of interlaced fibers. Internal gas transport in TPS is important in modeling the penetration of hot boundary-layer gases and the in-depth transport of pyrolysis and ablation products. The gas effective diffusion coefficient of a porous material must be known before the gas transport can be modeled in material response solvers; however, there are very little available data for rigid fibrous insulators used in heritage TPS.The tortuosity factor, which reflects the efficiency of the percolation paths, can be computed from the effective diffusion coefficient of a gas inside a porous material and is based on the micro-structure of the material. It is well known, that the tortuosity factor is a strong function of the Knudsen number. Due to the small characteristic scales of porous media used in TPS applications (typical pore size of the order of 50 micron), the transport of gases can occur in the rarefied and transitional regimes, at Knudsen numbers above 1. A proper way to model the gas dynamics at these conditions consists in solving the Boltzmann equation using particle-based methods that account for movement and collisions of atoms and molecules.In this work we adopt, for the first time, the Direct Simulation Monte Carlo (DSMC) method to compute the tortuosity factor of fibrous media in the rarefied regime. To enable realistic simulations of the actual transport of gases in the porous medium, digitized computational grids are obtained from X-ray micro-tomography imaging of real TPS materials. The SPARTA DSMC solver is used for simulations. Effective diffusion coefficients and tortuosity factors are obtained by computing the mean-square displacement of diffusing particles.We first apply the method to compute the tortuosity factors as a function of the Knudsen number for computationally designed materials such as random cylindrical fibers and packed bed of spheres with prescribed porosity. Results are compared to literature values obtained using random walk methods in the rarefied and transitional regime and a finite-volume method for the continuum regime. We then compute tortuosity factors for a real carbon fiber material with a transverse isotropic structure (FiberForm), quantifying differences between through-thickness and in-plain tortuosities at various Knudsen regimes

    Cell-graph mining for breast tissue modeling and classification

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    We consider the problem of automated cancer diagnosis in the context of breast tissues. We present graph theoretical techniques that identify and compute quantitative metrics for tissue characterization and classification. We segment digital images of histopatological tissue samples using k-means algorithm. For each segmented image we generate different cell-graphs using positional coordinates of cells and surrounding matrix components. These cell-graphs have 500-2000 cells(nodes) with 1000-10000 links depending on the tissue and the type of cell-graph being used. We calculate a set of global metrics from cell-graphs and use them as the feature set for learning. We compare our technique, hierarchical cell graphs, with other techniques based on intensity values of images, Delaunay triangulation of the cells, the previous technique we proposed for brain tissue images and with the hybrid approach that we introduce in this paper. Among the compared techniques, hierarchical-graph approach gives 81.8% accuracy whereas we obtain 61.0%, 54.1% and 75.9% accuracy with intensity-based features, Delaunay triangulation and our previous technique, respectively. © 2007 IEEE

    Radiative Heat Transfer Modeling in Fibrous Porous Media

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    Phenolic-Impregnated Carbon Ablator (PICA) was developed at NASA Ames Research Center as a lightweight thermal protection system material for successful atmospheric entries. The objective of the current work is to compute the effective radiative conductivity of fibrous porous media, such as preforms used to make PICA, to enable the efficient design of materials that can meet the thermal performance goals of forthcoming space exploration missions
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