968 resultados para Neural modeling
Resumo:
Power densities required to operate active-matrix organic-light-emitting diode (AMOLED) based displays for high luminance applications, lead to temperature rise due to self heating. Temperature rise leads to significant degradation and consequent reduction in life time. In this work numerical techniques based computational fluid dynamics (CFD) is used to determine the temperature rise and its distribution for an AMOLED based display for a given power density and size. Passive cooling option in form of protruded rectangular fins is implemented to reduce the display temperature.
Resumo:
Biomolecular recognition underlying drug-target interactions is determined by both binding affinity and specificity. Whilst, quantification of binding efficacy is possible, determining specificity remains a challenge, as it requires affinity data for multiple targets with the same ligand dataset. Thus, understanding the interaction space by mapping the target space to model its complementary chemical space through computational techniques are desirable. In this study, active site architecture of FabD drug target in two apicomplexan parasites viz. Plasmodium falciparum (PfFabD) and Toxoplasma gondii (TgFabD) is explored, followed by consensus docking calculations and identification of fifteen best hit compounds, most of which are found to be derivatives of natural products. Subsequently, machine learning techniques were applied on molecular descriptors of six FabD homologs and sixty ligands to induce distinct multivariate partial-least square models. The biological space of FabD mapped by the various chemical entities explain their interaction space in general. It also highlights the selective variations in FabD of apicomplexan parasites with that of the host. Furthermore, chemometric models revealed the principal chemical scaffolds in PfFabD and TgFabD as pyrrolidines and imidazoles, respectively, which render target specificity and improve binding affinity in combination with other functional descriptors conducive for the design and optimization of the leads.
Resumo:
A comprehensive numerical investigation on the impingement and spreading of a non-isothermal liquid droplet on a solid substrate with heterogeneous wettability is presented in this work. The time-dependent incompressible Navier-Stokes equations are used to describe the fluid flow in the liquid droplet, whereas the heat transfer in the moving droplet and in the solid substrate is described by the energy equation. The arbitrary Lagrangian-Eulerian (ALE) formulation with finite elements is used to solve the time-dependent incompressible Navier-Stokes equation and the energy equation in the time-dependent moving domain. Moreover, the Marangoni convection is included in the variational form of the Navier-Stokes equations without calculating the partial derivatives of the temperature on the free surface. The heterogeneous wettability is incorporated into the numerical model by defining a space-dependent contact angle. An array of simulations for droplet impingement on a heated solid substrate with circular patterned heterogeneous wettability are presented. The numerical study includes the influence of wettability contrast, pattern diameter, Reynolds number and Weber number on the confinement of the spreading droplet within the inner region, which is more wettable than the outer region. Also, the influence of these parameters on the total heat transfer from the solid substrate to the liquid droplet is examined. We observe that the equilibrium position depends on the wettability contrast and the diameter of the inner surface. Consequently. the heat transfer is more when the wettability contrast is small and/or the diameter of inner region is large. The influence of the Weber number on the total heat transfer is more compared to the Reynolds number, and the total heat transfer increases when the Weber number increases. (C) 2015 Elsevier Ltd. All rights reserved.
Resumo:
Affine transformations have proven to be very powerful for loop restructuring due to their ability to model a very wide range of transformations. A single multi-dimensional affine function can represent a long and complex sequence of simpler transformations. Existing affine transformation frameworks like the Pluto algorithm, that include a cost function for modern multicore architectures where coarse-grained parallelism and locality are crucial, consider only a sub-space of transformations to avoid a combinatorial explosion in finding the transformations. The ensuing practical tradeoffs lead to the exclusion of certain useful transformations, in particular, transformation compositions involving loop reversals and loop skewing by negative factors. In this paper, we propose an approach to address this limitation by modeling a much larger space of affine transformations in conjunction with the Pluto algorithm's cost function. We perform an experimental evaluation of both, the effect on compilation time, and performance of generated codes. The evaluation shows that our new framework, Pluto+, provides no degradation in performance in any of the Polybench benchmarks. For Lattice Boltzmann Method (LBM) codes with periodic boundary conditions, it provides a mean speedup of 1.33x over Pluto. We also show that Pluto+ does not increase compile times significantly. Experimental results on Polybench show that Pluto+ increases overall polyhedral source-to-source optimization time only by 15%. In cases where it improves execution time significantly, it increased polyhedral optimization time only by 2.04x.
Resumo:
Thermal decomposition studies of 3-carene, a bio-fuel, have been carried out behind the reflected shock wave in a single pulse shock tube for temperature ranging from 920 K to 1220 K. The observed products in thermal decomposition of 3-carene are acetylene, allene, butadiene, isoprene, cyclopentadiene, hexatriene, benzene, toluene and p-xylene. The overall rate constant for 3-carene decomposition was found to be k/s(-1) = 10((9.95 +/- 0.54)) exp(-40.88 +/- 2.71 kcal mol(-1) /RT). Ab-initio theoretical calculations were carried out to find the minimum energy pathway that could explain the formation of the observed products in the thermal decomposition experiments. These calculations were carried out at B3LYP/6-311 + G(d,p) and G3 level of theories. A kinetic mechanism explaining the observed products in the thermal decomposition experiments has been derived. It is concluded that the linear hydrocarbons are the primary products in the pyrolysis of 3-carene.
Resumo:
There has been much interest in understanding collective dynamics in networks of brain regions due to their role in behavior and cognitive function. Here we show that a simple, homogeneous system of densely connected oscillators, representing the aggregate activity of local brain regions, can exhibit a rich variety of dynamical patterns emerging via spontaneous breaking of permutation or translational symmetries. Upon removing just a few connections, we observe a striking departure from the mean-field limit in terms of the collective dynamics, which implies that the sparsity of these networks may have very important consequences. Our results suggest that the origins of some of the complicated activity patterns seen in the brain may be understood even with simple connection topologies.
Resumo:
This study presents a plausible dual-site mechanism and microkinetic model for CO oxidation over palladium-substituted ceria incorporating the theoretical oxygen storage capacity of different-catalysts into the kinetic model. A rate expression without prior assumption of rate-determining steps has been developed for the proposed microkinetic model using reaction route analysis. Experiments were conducted using various percentages of palladium in ceria that were synthesized by solution combustion. Obtained catalysts were characterized by X-ray diffraction, X-ray photoelectron spectra, and Brunauer-Emmett-Teller surface area measurements. A detailed mechanism was, developed, and the kinetic parameters and rate expression were validated with the conversion data obtained in the presence of the catalysts. Furthermore, a reduced rate expression based on rate-determining step and most abundant reactive intermediate approximation was obtained and tested against the original rate expression for different experimental conditions. From the results obtained it was concluded that the simulated rate predictions matched the experimental trend with reasonable accuracy, validating the kinetic parameters proposed it this study.
Resumo:
Numerical simulation of separated flows in rocket nozzles is challenging because existing turbulence models are unable to predict it correctly. This paper addresses this issue with the Spalart-Allmaras and Shear Stress Transport (SST) eddy-viscosity models, which predict flow separation with moderate success. Their performances have been compared against experimental data for a conical and two contoured subscale nozzles. It is found that they fail to predict the separation location correctly, exhibiting sensitivity to the nozzle pressure ratio (NPR) and nozzle type. A careful assessment indicated how the model had to be tuned for better, consistent prediction. It is learnt that SST model's failure is caused by limiting of the shear stress inside boundary layer according to Bradshaw's assumption, and by over prediction of jet spreading rate. Accordingly, SST's coefficients were empirically modified to match the experimental wall pressure data. Results confirm that accurate RANS prediction of separation depends on the correct capture of the jet spreading rate, and that it is feasible over a wide range of NPRs by modified values of the diffusion coefficients in the turbulence model. (C) 2015 Elsevier Masson SAS. All rights reserved.
Resumo:
With the advances in technology, seismological theory, and data acquisition, a number of high-resolution seismic tomography models have been published. However, discrepancies between tomography models often arise from different theoretical treatments of seismic wave propagation, different inversion strategies, and different data sets. Using a fixed velocity-to-density scaling and a fixed radial viscosity profile, we compute global mantle flow models associated with the different tomography models and test the impact of these for explaining surface geophysical observations (geoid, dynamic topography, stress, and strain rates). We use the joint modeling of lithosphere and mantle dynamics approach of Ghosh and Holt (2012) to compute the full lithosphere stresses, except that we use HC for the mantle circulation model, which accounts for the primary flow-coupling features associated with density-driven mantle flow. Our results show that the seismic tomography models of S40RTS and SAW642AN provide a better match with surface observables on a global scale than other models tested. Both of these tomography models have important similarities, including upwellings located in Pacific, Eastern Africa, Iceland, and mid-ocean ridges in the Atlantic and Indian Ocean and downwelling flows mainly located beneath the Andes, the Middle East, and central and Southeast Asia.
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Recent studies have evaluated closed-loop supercritical carbon dioxide (s-CO2) Brayton cycles to be a higher energy density system in comparison to conventional superheated steam Rankine systems. At turbine inlet conditions of 923K and 25 MPa, high thermal efficiency (similar to 50%) can be achieved. Achieving these high efficiencies will make concentrating solar power (CSP) technologies a competitive alternative to current power generation methods. To incorporate a s-CO2 Brayton power cycle in a solar power tower system, the development of a solar receiver capable of providing an outlet temperature of 923 K (at 25 MPa) is necessary. The s-CO2 will need to increase in temperature by similar to 200 K as it passes through the solar receiver to satisfy the temperature requirements of a s-CO2 Brayton cycle with recuperation and recompression. In this study, an optical-thermal-fluid model was developed to design and evaluate a tubular receiver that will receive a heat input similar to 2 MWth from a heliostat field. The ray-tracing tool SolTrace was used to obtain the heat-flux distribution on the surfaces of the receiver. Computational fluid dynamics (CFD) modeling using the Discrete Ordinates (DO) radiation model was used to predict the temperature distribution and the resulting receiver efficiency. The effect of flow parameters, receiver geometry and radiation absorption by s-CO2 were studied. The receiver surface temperatures were found to be within the safe operational limit while exhibiting a receiver efficiency of similar to 85%.
Contimuum Mesomechanical Finite Element Modeling in Materials Development: A State-of-the-Art Review
Resumo:
Aimed at brittle composites reinforced by randomly distributed short-fibers with a relatively large aspect ratio, stiffness modulus and strength, a mesoscopic material model was proposed. Based on the statistical description, damage mechanisms, damage-induced anisotropy, damage rate effect and stress redistribution, the constitutive relation were derived. By taking glass fiber reinforced polypropylene polymers as an example, the effect of initial orientation distribution of fibers, damage-induced anisotropy, and damage-rate effect on macro-behaviors of composites were quantitatively analyzed. The theoretical predictions compared favorably with the experimental results.
Resumo:
The multi-layers feedforward neural network is used for inversion of material constants of fluid-saturated porous media. The direct analysis of fluid-saturated porous media is carried out with the boundary element method. The dynamic displacement responses obtained from direct analysis for prescribed material parameters constitute the sample sets training neural network. By virtue of the effective L-M training algorithm and the Tikhonov regularization method as well as the GCV method for an appropriate selection of regularization parameter, the inverse mapping from dynamic displacement responses to material constants is performed. Numerical examples demonstrate the validity of the neural network method.
Resumo:
Modeling study is performed to compare the flow and heat transfer characteristics of laminar and turbulent argon thermal-plasma jets impinging normally upon a flat plate in ambient air. The combined-diffusion-coefficient method and the turbulence-enhanced combined-diffusion-coefficient method are employed to treat the diffusion of argon in the argon-air mixture for the laminar and the turbulent cases, respectively. Modeling results presented include the flow, temperature and argon concentration fields, the air mass flow-rates entrained into the impinging plasma jets, and the distributions of the heat flux density on the plate surface. It is found that the formation of a radial wall jet on the plate surface appreciably enhances the mass flow rate of the ambient air entrained into the laminar or turbulent plasma impinging-jet. When the plate standoff distance is comparatively small, there exists a significant difference between the laminar and turbulent plasma impinging-jets in their flow fields due to the occurrence of a large closed recirculation vortex in the turbulent plasma impinging-jet, and no appreciable difference is found between the two types of jets in their maximum values and distributions of the heat flux density at the plate surface. At larger plate standoff distances, the effect of the plate on the jet flow fields only appears in the region near the plate, and the axial decaying-rates of the plasma temperature, axial velocity and argon mass fraction along the axis of the laminar plasma impinging-jet become appreciably less than their turbulent counterparts.
Resumo:
This paper studies the stability of jointed rock slopes by using our improved three-dimensional discrete element methods (DEM) and physical modeling. Results show that the DEM can simulate all failure modes of rock slopes with different joint configurations. The stress in each rock block is not homogeneous and blocks rotate in failure development. Failure modes depend on the configuration of joints. Toppling failure is observed for the slope with straight joints and sliding failure is observed for the slope with staged joints. The DEM results are also compared with those of limit equilibrium method (LEM). Without considering the joints in rock masses, the LEM predicts much higher factor of safety than physical modeling and DEM. The failure mode and factor of safety predicted by the DEM are in good agreement with laboratory tests for any jointed rock slope.