Liquid phase behavior of ionic liquids with alcohols: Experimental studies and modeling

Ionic liquids (ILs) have been suggested as potential

Switched Diversity Techniques for Indoor Off-body Communications Channels: An Experimental Analysis and Modeling

This paper investigates the potential improvement in signal reliability for indoor off-body communications channels operating at 5.8 GHz using switched diversity techniques. In particular we investigate the performance of switch-and-stay combining (SSC), switch-and-examine combining (SEC) and switch-and-examine combining with post-examining selection (SECps) schemes which utilize multiple spatially separated antennas at the base station. During the measurements a test subject, wearing an antenna on his chest, performed a number of walking movements towards and then away from a uniform linear array. It was found that all of the considered diversity schemes provided a worthwhile signal improvement. However, the performance of the diversity systems varied according to the switching threshold that was adopted. To model the fading envelope observed at the output of each of the combiners, we have applied diversity specific equations developed under the assumption of Nakagami-$m$ fading. As a measure of the goodness-of-fit, the Kullback-Leibler divergence between the empirical and theoretical probability density functions (PDFs) was calculated and found to be close to 0. To assist with the interpretation of the goodness-of-fit achieved in this study, the standard deviation, $\sigma$, of a zero-mean, $\sigma^2$ variance Gaussian PDF used to approximate a zero-mean, unit variance Gaussian PDF is also presented. These were generally quite close to 1 indicating that the theoretical models provided an adequate fit to the measured data.

Differential Scanning Calorimetry Study and Computer Modeling of b a Phase Transformation in Ti-6Al-4V Alloy

The relationship between heat-treatment parameters and microstructure in titanium alloys has so far been mainly studied empirically, using characterization techniques such as microscopy. Calculation and modeling of the kinetics of phase transformation have not yet been widely used for these alloys. Differential scanning calorimetry (DSC) has been widely used for the study of a variety of phase transformations. There has been much work done on the calculation and modeling of the kinetics of phase transformations for different systems based on the results from DSC study. In the present work, the kinetics of the transformation in a Ti-6Al-4V titanium alloy were studied using DSC, at continuous cooling conditions with constant cooling rates of 5 °C, 10 °C, 20 °C, 30 °C, 40 °C, and 50 °C/min. The results from calorimetry were then used to trace and model the transformation kinetics in continuous cooling conditions. Based on suitably interpreted DSC results, continuous cooling–transformation (CCT) diagrams were calculated with lines of isotransformed fraction. The kinetics of transformation were modeled using the Johnson–Mehl–Avrami (JMA) theory and by applying the "concept of additivity." The JMA kinetic parameters were derived. Good agreement between the calculated and experimental transformed fractions is demonstrated. Using the derived kinetic parameters, the transformation in a Ti-6Al-4V alloy can be described for any cooling path and condition. An interpretation of the results from the point of view of activation energy for nucleation is also presented.

Effector dynamics of rhythmic wrist activity and its implications for (modeling) bimanual coordination

To examine the role of the effector dynamics of the wrist in the production of rhythmic motor activity, we estimated the phase shifts between the EMG and the task-related output for a rhythmic isometric torque production task and an oscillatory movement, and found a substantial difference (45-52degrees) between the two. For both tasks, the relation between EMG and task-related output (torque or displacement) was adequately reproduced with a physiologically motivated musculoskeletal model. The model simulations demonstrated the importance of the contribution of passive structures to the overall dynamics and provided an account for the observed phase shifts in the dynamic task. Additional simulations of the musculoskeletal model with added load suggested that particular changes in the phase relation between EMG and movement may follow largely from the intrinsic muscle dynamics, rather than being the result of adaptations in the neural control of joint stiffness. The implications of these results are discussed in relation to (models of) interlimb coordination in rhythmic tasks. (C) 2004 Elsevier B.V. All rights reserved.

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.

A time-domain approach to the analysis and modeling of on-body propagation characteristics using synchronized measurements at 2.45 GHz

Modeling of on-body propagation channels is of paramount importance to those wishing to evaluate radio channel performance for wearable devices in body area networks (BANs). Difficulties in modeling arise due to the highly variable channel conditions related to changes in the user's state and local environment. This study characterizes these influences by using time-series analysis to examine and model signal characteristics for on-body radio channels in user stationary and mobile scenarios in four different locations: anechoic chamber, open office area, hallway, and outdoor environment. Autocorrelation and cross-correlation functions are reported and shown to be dependent on body state and surroundings. Autoregressive (AR) transfer functions are used to perform time-series analysis and develop models for fading in various on-body links. Due to the non-Gaussian nature of the logarithmically transformed observed signal envelope in the majority of mobile user states, a simple method for reproducing the failing based on lognormal and Nakagami statistics is proposed. The validity of the AR models is evaluated using hypothesis testing, which is based on the Ljung-Box statistic, and the estimated distributional parameters of the simulator output compared with those from experimental results.

Modeling the geometric characteristics of five-dimensionally woven composites

An analytical modeling approach for the prediction of the geometric characteristics of five-dimensional (5D) woven composites has been formulated. The model is driven by readily available data including the weaving parameters and constituent material properties. The new model calculates the individual proportions of fiber in each direction, areal density, overall fiber volume fraction, and laminate thickness. This information is useful for the engineer in the design and manufacture of 5D woven composites. In addition the present model outputs the mathematical definition of the 5D woven composite unit cell, which could be implemented as the geometric input for a downstream analytical model that is capable of predicting the elastic stiffness of 5D woven composites. Input parameters have been sourced from existing published work and the subsequent predictions made by the model are compared with the available experimental data on 5D woven composites.

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.

Wavelength Dependence of Raman Enhancement from Gold Nanorod Arrays: Quantitative Experiment and Modeling of a Hot Spot Dominated System

Surface-enhanced Raman scattering (SERS) spectra from molecules adsorbed on the surface of vertically aligned gold nanorod arrays exhibit a variation in enhancement factor (EF) as a function of excitation wavelength that displays little correlation with the elastic optical properties of the surface. The key to understanding this lack of correlation and to obtaining agreement between experimental and calculated EF spectra lies with consideration of randomly distributed, sub-10 nm gaps between nanorods forming the substrate. Intense fields in these enhancement “hot spots” make a dominant contribution to the Raman scattering and have a very different spectral profile to that of the elastic optical response. Detailed modeling of the electric field enhancement at both excitation and scattering wavelengths was used to quantitatively predict both the spectral profile and the magnitude of the observed EF.

Experimental Investigation of Stretch Blow Molding, Part 1: Instrumentation in an Industrial Environment

In spite of intensive research, computational modeling of the injection stretch blow molding (ISBM) still cannot match the accuracy of other polymer processes such as injection molding. There is a lack of understanding of the interdependence among the machine parameters set up by the operators, process parameters, material behavior, and the resulting final thickness distribution and performance of the molded product. The work presented in this paper describes a set of instrumentation tools developed for investigation of the ISBM process in an industrial setting. Results are presented showing the pressure and air temperature evolution inside the mold, the stretch rod force and displacement history, and the moment of contact of the polymer with seven discrete locations on the mold.

Dynamic grey-box modeling for online monitoring of extrusion viscosity

Melt viscosity is a key indicator of product quality in polymer extrusion processes. However, real time monitoring and control of viscosity is difficult to achieve. In this article, a novel “soft sensor” approach based on dynamic gray-box modeling is proposed. The soft sensor involves a nonlinear finite impulse response model with adaptable linear parameters for real-time prediction of the melt viscosity based on the process inputs; the model output is then used as an input of a model with a simple-fixed structure to predict the barrel pressure which can be measured online. Finally, the predicted pressure is compared to the measured value and the corresponding error is used as a feedback signal to correct the viscosity estimate. This novel feedback structure enables the online adaptability of the viscosity model in response to modeling errors and disturbances, hence producing a reliable viscosity estimate. The experimental results on different material/die/extruder confirm the effectiveness of the proposed “soft sensor” method based on dynamic gray-box modeling for real-time monitoring and control of polymer extrusion processes. POLYM. ENG. SCI., 2012. © 2012 Society of Plastics Engineers

A micromechanics approach for damage modeling of polymer matrix composites

A new model for damage evolution in polymer matrix composites is presented. The model is based on a combination of two constituent-level models and an interphase model. This approach reduces the number of empirical parameters since the two constituent- level models are formulated for isotropic materials, namely fiber and matrix. Decomposition of the state variables down to the micro-scale is accomplished by micromechanics. Phenomenological damage evolution models are then postulated for each constituent. Determination of material parameters is made from available experimental data. The required experimental data can be obtained with standard tests. Comparison between model predictions and additional experimental data is presented.

Modeling colloid deposition on a protein layer adsorbed to iron-oxide-coated sand

Our recent study reported that conformation change of granule-associated Bovine Serum Albumin (BSA) may influence the role of the protein controlling colloid deposition in porous media (Flynn et al., 2012). The present study conceptualized the observed phenomena with an ellipsoid morphology model, describing BSA as an ellipsoid taking a side-on or end-on conformation on granular surface, and identified the following processes: (1) at low adsorbed concentrations, BSA exhibited a side-on conformation blocking colloid deposition; (2) at high adsorbed concentrations, BSA adapted to an end-on conformation promoted colloid deposition; and (3) colloid deposition on the BSA layer may progressively generate end-on molecules (sites) by conformation change of side-on BSA, resulting in sustained increasing deposition rates. Generally, the protein layer lowered colloid attenuation by the porous medium, suggesting the overall effect of BSA was inhibitory at the experimental time scale. A mathematical model was developed to interpret the ripening curves. Modeling analysis identified the site generation efficiency of colloid as a control on the ripening rate (declining rate in colloid concentrations), and this efficiency was higher for BSA adsorbed from a more dilute BSA solution. © 2012 Elsevier B.V.