Cure processing modeling and cure cycle simulation of epoxy-terminated poly(phenylene ether ketone) .4. Cure cycle simulation

Epoxy-terminated poly(phenylene ether ketone) (E-PEK) developed in this Institute is a candidate matrix resin for polymer composites as structural materials. Cure cycles for this reaction system were simulated according to the previously established processing model. It is found that for the E-PEK system, the curing process is best completed by a stepwise cure cycle comprising two isothermal processes at different temperatures, T-1 and T-2. The cure cycles over a wide range of processing parameters simulated, based on the established processing model, indicate that the processing window is width-adjustable. Analysis of the mechanical properties of the composite sheets showed that the simulated cure cycles are acceptable and reliable. (C) 1997 John Wiley & Sons, Inc.

APPLICATION OF THE KHOKHLOV-ZABOLOTSKAYA-KUZNETSOV EQUATION TO MODELING HIGH-INTENSITY FOCUSED ULTRASOUND BEAMS

High-intensity focused ultrasound is a form of therapeutic ultrasound which uses high amplitude acoustic waves to heat and ablate tissue. HIFU employs acoustic amplitudes that are high enough that nonlinear propagation effects are important in the evolution of the sound field. A common model for HIFU beams is the Khokhlov-Zabolotskaya-Kuznetsov (KZK) equation which accounts for nonlinearity, diffraction, and absorption. The KZK equation models diffraction using the parabolic or paraxial approximation. Many HIFU sources have an aperture diameter similar to the focal length and the paraxial approximation may not be appropriate. Here, results obtained using the “Texas code,” a time-domain numerical solution to the KZK equation, were used to assess when the KZK equation can be employed. In a linear water case comparison with the O’Neil solution, the KZK equation accurately predicts the pressure field in the focal region. The KZK equation was also compared to simulations of the exact fluid dynamics equations (no paraxial approximation). The exact equations were solved using the Fourier-Continuation (FC) method to approximate derivatives in the equations. Results have been obtained for a focused HIFU source in tissue. For a low focusing gain transducer (focal length 50λ and radius 10λ), the KZK and FC models showed excellent agreement, however, as the source radius was increased to 30λ, discrepancies started to appear. Modeling was extended to the case of tissue with the appropriate power law using a relaxation model. The relaxation model resulted in a higher peak pressure and a shift in the location of the peak pressure, highlighting the importance of employing the correct attenuation model. Simulations from the code that were compared to experimental data in water showed good agreement through the focal plane.

Structural Analysis of Network Traffic Flows

Network traffic arises from the superposition of Origin-Destination (OD) flows. Hence, a thorough understanding of OD flows is essential for modeling network traffic, and for addressing a wide variety of problems including traffic engineering, traffic matrix estimation, capacity planning, forecasting and anomaly detection. However, to date, OD flows have not been closely studied, and there is very little known about their properties. We present the first analysis of complete sets of OD flow timeseries, taken from two different backbone networks (Abilene and Sprint-Europe). Using Principal Component Analysis (PCA), we find that the set of OD flows has small intrinsic dimension. In fact, even in a network with over a hundred OD flows, these flows can be accurately modeled in time using a small number (10 or less) of independent components or dimensions. We also show how to use PCA to systematically decompose the structure of OD flow timeseries into three main constituents: common periodic trends, short-lived bursts, and noise. We provide insight into how the various constituents contribute to the overall structure of OD flows and explore the extent to which this decomposition varies over time.

Accommodating curvature in a highly ordered functionalized metal oxide nanofiber: synthesis, characterization and multi-scale modeling of layered nanosheets

A key element in the rational design of hybrid organic-inorganic nanostructures, is control of surfactant packing and adsorption onto the inorganic phase in crystal growth and assembly. In layered single crystal nanofibers and bilayered 2D nanosheets of vanadium oxide, we show how the chemisorption of preferred densities of surfactant molecules can direct formation of ordered, curved layers. The atom-scale features of the structures are described using molecular dynamics simulations that quantify surfactant packing effects and confirm the preference for a density of 5 dodecanethiol molecules per 8 vanadium attachment sites in the synthesised structures. This assembly maintains a remarkably well ordered interlayer spacing, even when curved. The assemblies of interdigitated organic bilayers on V2O5 are shown to be sufficiently flexible to tolerate curvature while maintaining a constant interlayer distance without rupture, delamination or cleavage. The accommodation of curvature and invariant structural integrity points to a beneficial role for oxide-directed organic film packing effects in layered architectures such as stacked nanofibers and hybrid 2D nanosheet systems.

Nonparametric estimation of structural models for high-frequency currency market data

Empirical modeling of high-frequency currency market data reveals substantial evidence for nonnormality, stochastic volatility, and other nonlinearities. This paper investigates whether an equilibrium monetary model can account for nonlinearities in weekly data. The model incorporates time-nonseparable preferences and a transaction cost technology. Simulated sample paths are generated using Marcet's parameterized expectations procedure. The paper also develops a new method for estimation of structural economic models. The method forces the model to match (under a GMM criterion) the score function of a nonparametric estimate of the conditional density of observed data. The estimation uses weekly U.S.-German currency market data, 1975-90. © 1995.

Modeling the dynamics of Magnetic Semilevitation Melting

In semilevitation melting, a cylindrical metal ingot is melted by a coaxial a.c. induction coil. A watercooled solid base supports the ingot, while the top and side free surface is confined by the magnetic forces as the melting front progresses. The dynamic interplay between gravity, hydrodynamic stress, and the Lorentz force in the fluid determines the instantaneous free surface shape. The coupled nonstationary equations for turbulent flow, heat with phase change, and high-frequency electromagnetic field are solved numerically for the axisymmetric time-dependent domain by a continuous mesh transformation, using a pseudospectral method. Results are obtained for the two actually existing coil configurations and several validation cases.

Multiphysics modeling and its application to the casting process

A modeling strategy is presented to solve the governing equations of fluid flow, temperature (with solidification), and stress in an integrated manner. These equations are discretized using finite volume methods on unstructured grids, which provide the capability to represent complex domains. Both the cell-centered and vertex-based forms of the finite volume discretization procedure are explained, and the overall integrated solution procedure using these techniques with suitable solvers is detailed. Two industrial processes, based on the casting of metals, are used to demonstrate the capabilities of the resultant modeling framework. This manufacturing process requires a high degree of coupling between the governing physical equations to accurately predict potential defects. Comparisons between model predictions and experimental observations are given.

Explicit finite volume modeling of aircraft anti-icing and de-icing

In this paper, a runback water and ice prediction model is extended to anti-icing and thermal de-icing situations. The resulting coupled equations that govern thin-film flow, ice accretion, and heat conduction in the multilayered system substrate-ice-water are solved using an explicit finite volume approach. The procedure is implemented in the three-dimensional icing code ICECREMO2, and both structured and unstructured grids can be considered. Numerical results are presented to compare the present code simulations to some data provided by other ice prediction codes and to show the capabilities of the present numerical tool.

Nonisothermal moisture transport in hygroscopic building materials: modeling for the determination of moisture transport coefficients

A mathematical model for calculating the nonisothermal moisture transfer in building materials is presented in the article. The coupled heat and moisture transfer problem was modeled. Vapor content and temperature were chosen as principal driving potentials. The coupled equations were solved by an analytical method, which consists of applying the Laplace transform technique and the Transfer Function Method. A new experimental methodology for determining the temperature gradient coefficient for building materials was also proposed. Both the moisture diffusion coefficient and the temperature gradient coefficient for building material were experimentally evaluated. Using the measured moisture transport coefficients, the temperature and vapor content distribution inside building materials were predicted by the new model. The results were compared with experimental data. A good agreement was obtained.

Uncertainty and Sensitivity Analysis in Aircraft Operating Costs in Structural Design Optimization

The paper focuses on the development of an aircraft design optimization methodology that models uncertainty and sensitivity analysis in the tradeoff between manufacturing cost, structural requirements, andaircraft direct operating cost.Specifically,ratherthanonlylooking atmanufacturingcost, direct operatingcost is also consideredintermsof the impact of weight on fuel burn, in addition to the acquisition cost to be borne by the operator. Ultimately, there is a tradeoff between driving design according to minimal weight and driving it according to reduced manufacturing cost. Theanalysis of cost is facilitated withagenetic-causal cost-modeling methodology,andthe structural analysis is driven by numerical expressions of appropriate failure modes that use ESDU International reference data. However, a key contribution of the paper is to investigate the modeling of uncertainty and to perform a sensitivity analysis to investigate the robustness of the optimization methodology. Stochastic distributions are used to characterize manufacturing cost distributions, andMonteCarlo analysis is performed in modeling the impact of uncertainty on the cost modeling. The results are then used in a sensitivity analysis that incorporates the optimization methodology. In addition to investigating manufacturing cost variance, the sensitivity of the optimization to fuel burn cost and structural loading are also investigated. It is found that the consideration of manufacturing cost does make an impact and results in a different optimal design configuration from that delivered by the minimal-weight method. However, it was shown that at lower applied loads there is a threshold fuel burn cost at which the optimization process needs to reduce weight, and this threshold decreases with increasing load. The new optimal solution results in lower direct operating cost with a predicted savings of 640=m2 of fuselage skin over the life, relating to a rough order-of-magnitude direct operating cost savings of $500,000 for the fuselage alone of a small regional jet. Moreover, it was found through the uncertainty analysis that the principle was not sensitive to cost variance, although the margins do change.

Measurements, modeling and simulation of the off-body radio channel for the implementation of bodyworn antenna diversity at 868 MHz

This paper presents a systematic measurement campaign of diversity reception techniques for use in multiple-antenna wearable systems operating at 868 MHz. The experiments were performed using six time-synchronized bodyworn receivers and considered mobile off-body communications in an anechoic chamber, open office area and a hallway. The cross-correlation coefficient between the signal fading measured by bodyworn receivers was dependent upon the local environment and typically below 0.7. All received signal envelopes were combined in post-processing to study the potential benefits of implementing receiver diversity based upon selection combination, equal-gain and maximal-ratio combining. It is shown that, in an open office area, the 5.7 dB diversity gain obtained using a dual-branch bodyworn maximal-ratio diversity system may be further improved to 11.1 dB if a six-branch system was used. First-and second-order theoretical equations for diversity reception techniques operating in Nakagami fading conditions were used to model the postdetection combined envelopes. Maximum likelihood estimates of the Nakagami-parameter suggest that the fading conditions encountered in this study were generally less severe than Rayleigh. The paper also describes an algorithm that may be used to simulate the measured output of an M-branch diversity combiner operating in independent and identically-distributed Nakagami fading environments.

Rhodopsin and the Others: A Historical Perspective on Structural Studies of G Protein-Coupled Receptors

The role of rhodopsin as a structural prototype for the study of the whole superfamily of G protein-coupled receptors (GPCRs) is reviewed in an historical perspective. Discovered at the end of the nineteenth century, fully sequenced since the early 1980s, and with direct three-dimensional information available since the 1990s, rhodopsin has served as a platform to gather indirect information on the structure of the other superfamily members. Recent breakthroughs have elicited the solution of the structures of additional receptors, namely the beta 1- and beta 2-adrenergic receptors and the A(2A) adenosine receptor, now providing an opportunity to gauge the accuracy of homology modeling and molecular docking techniques and to perfect the computational protocol. Notably, in coordination with the solution of the structure of the A(2A) adenosine receptor, the first "critical assessment of GPCR structural modeling and docking" has been organized, the results of which highlighted that the construction of accurate models, although challenging, is certainly achievable. The docking of the ligands and the scoring of the poses clearly emerged as the most difficult components. A further goal in the field is certainly to derive the structure of receptors in their signaling state, possibly in complex with agonists. These advances, coupled with the introduction of more sophisticated modeling algorithms and the increase in computer power, raise the expectation for a substantial boost of the robustness and accuracy of computer-aided drug discovery techniques in the coming years.

Neural Network Modeling of Rheological Parameters of Grouts Containing Viscosity-Modifying Agent

The development of artificial neural network (ANN) models to predict the rheological behavior of grouts is described is this paper and the sensitivity of such parameters to the variation in mixture ingredients is also evaluated. The input parameters of the neural network were the mixture ingredients influencing the rheological behavior of grouts, namely the cement content, fly ash, ground-granulated blast-furnace slag, limestone powder, silica fume, water-binder ratio (w/b), high-range water-reducing admixture, and viscosity-modifying agent (welan gum). The six outputs of the ANN models were the mini-slump, the apparent viscosity at low shear, and the yield stress and plastic viscosity values of the Bingham and modified Bingham models, respectively. The model is based on a multi-layer feed-forward neural network. The details of the proposed ANN with its architecture, training, and validation are presented in this paper. A database of 186 mixtures from eight different studies was developed to train and test the ANN model. The effectiveness of the trained ANN model is evaluated by comparing its responses with the experimental data that were used in the training process. The results show that the ANN model can accurately predict the mini-slump, the apparent viscosity at low shear, the yield stress, and the plastic viscosity values of the Bingham and modified Bingham models of the pseudo-plastic grouts used in the training process. The results can also predict these properties of new mixtures within the practical range of the input variables used in the training with an absolute error of 2%, 0.5%, 8%, 4%, 2%, and 1.6%, respectively. The sensitivity of the ANN model showed that the trend data obtained by the models were in good agreement with the actual experimental results, demonstrating the effect of mixture ingredients on fluidity and the rheological parameters with both the Bingham and modified Bingham models.

Molecular Modeling on Inhibitor Complexes and Active-Site Dynamics of Cytochrome P450 C17, a Target for Prostate Cancer Therapy

A molecular model for the P450 enzyme cytochrome P450 C17 (CYP17) is presented based on sequence alignments of multiple template structures and homology modeling. This enzyme plays a central role in the biosynthesis of testosterone and is emerging as a major target in prostate cancer, with the recently developed inhibitor abiraterone currently in advanced clinical trials. The model is described in detail, together with its validation, by providing structural explanations to available site-directed mutagenesis data. The CYP17 molecule in this model is in the form of a triangular prism, with an edge of similar to 55 angstrom and a thickness of similar to 37 angstrom. It is predominantly helical, comprising 13 alpha helices interspersed by six 3(10) helices and 11 beta-sheets. Multinanosecond molecular dynamics simulations in explicit solvent have been carried out, and principal components analysis has been used to reveal the details of dynamics around the active site. Coarse-grained methods have also been used to verify low-frequency motions, which have been correlated with active-site gating. The work also describes the results of docking synthetic inhibitors, including the drug abiraterone and the natural substrate pregnenolone, in the CYP17 active site together with molecular dynamics simulations on the complexes. (C) 2010 Elsevier Ltd. All rights reserved.

On how structural model variability influence transonic aeroelasticity stability.

This paper considers the ways in which structural model parameter variability can in?uence aeroelastic stability. Previous work on formulating the stability calculation (with the Euler equations providing the aerodynamic predictions) is exploited to use Monte Carlo, Interval and Perturbation calculations to allow this question to be investigated. Three routes are identi?ed. The ?rst involves variable normal mode frequencies only. The second involves normal mode frequencies and mode shapes. Finally, the third, in addition to normal mode frequencies and mode shapes, also includes their in?uence on the static equilibrium. Previous work has suggested only considering route 1, which allows signi?cant gains in computational e?ciency if reduced order models can be built for the aerodynamics. However, results in the current paper show that neglecting route 2 can give misleading results for the ?utter onset prediction.