The Influence and Interpretation of Surface Parameters for Wetting Transitions in Ternary Mixtures

Starting from a microscopic Hamiltonian defined on a semi-infinite cubic lattice, and employing a mean-field approximation, the surface parameters relevant for wetting in confined ternary mixtures are derived. These are found in terms of the microscopic coupling constants, and yield a physical interpretation of their origins. In comparison with the standard expression for the surface free-energy density, several new terms arising from the derivation are identified. The influence of the surface parameters on a predicted unbinding transition in a mixture of oil, water, and amphiphile demonstrate that existing results are robust to the addition of the extra surface terms.     

River Bifurcation Analysis by Physical and Numerical Modeling

In the framework of a river regulation design of the Po River Delta (Northern Italy), a study on a large physical model of the bifurcation Po di Goro-Po di Venezia was conducted with the main objective of determining the discharge subdivision rate at the river node, in order to assess the inflow conditions in the Po di Goro River for flood risk analysis. In this context, a two-dimensional depth averaged numerical model was tested against measured values, with reference to the prototype. In this paper a comprehensive analysis and discussion of the results is reported in order to highlight the applicability of numerical models in comparison with physical ones in river engineering applications.     

A stochastic model for localized disturbances and its applications

A stochastic model for local disturbances, particularly for a temporal harmonic with random modulations in amplitude and/or phase, is proposed in this paper. Results for the second moment responses of a linear single-degree-of-freedom system to this type of stochastic loading demonstrate a significant change in response characteristics due to a small uncertainty. A local phenomenon may last much longer and resonance may be smeared to a broad range. Integrated with wavelet transform, the proposed approach may be used to model a random process with non-stationary frequency content. Especially, it can be effectively used for Monte Carlo simulation to generate large size of samples that have similar characteristics in time and frequency domains as a pre-selected mother sample has. The technique has a great potential for the case where uncertainty study is warranted but the available samples are limited.     

PLC 控制电梯教学模型的设计与调试

主要介绍了8层集选电梯的PLC控制系统的总体设计方案、组成，PLC的控制方案及模块化程序设计、在实际的安装与调试中遇到的问题，以及制作该教学模型的现实意义。     

Probabilistic analysis of a static frame model

This paper describes our efforts during our participation in the Sandia Validation Workshop. The focus of the paper is the calibration of material models and simulation of random fields to characterize the variations of material properties across spatial field. Both parametric and non-parametric methods were used to represent uncertainty. Part of the challenge of this problem is the small amount of data that is available for the necessary probabilistic analyses in support of calibration, validation, accreditation and prediction activities. The analysis methods and corresponding results are described.     

Assessing continuous bivariate effects among different groups through nonparametric regression models: An application to breast cancer detection

In many applications, the joint effect of two continuous covariates on the target binary response may vary across groups defined by levels of a given factor. A testing procedure that would enable this type of surface-by-factor interactions to be detected has been designed. To accomplish this goal, a logistic generalized additive model (GAM) with bivariate continuous interactions varying across groups defined by levels of a factor is considered. A local scoring algorithm based on local linear kernel smoothers was implemented to estimate the proposed logistic GAM. Bootstrap resampling techniques were used for the purpose of testing for factor-by-surface interactions. Given the high computational cost involved, binning techniques were used to speed up computation in the estimation and testing processes. The adequacy of the bootstrap-based test was assessed by means of a simulation study. If a factor-by-surface interaction is detected in the model, it is then established that the use of the odds-ratio curves is very useful in obtaining a direct interpretation of the fitted model. The benefits of using this methodology when analyzing real data are illustrated by applying the technique to the outputs produced by a computerized system dedicated to the early detection of breast cancer.     

Real-Time Three-Dimensional Occupancy Grid Modeling for the Detection and Tracking of Construction Resources

Awareness of the construction environment can be improved by automatic three-dimensional (3D) sensing and modeling of job sites in real time. Commercially available 3D modeling approaches based on range scanning techniques are capable of modeling static objects only, and thus cannot model dynamic objects in real time in an environment comprised of moving humans, equipment, and materials. Emerging prototype video range cameras offer an alternative by facilitating affordable, wide field of view, dynamic object tracking at frame rates better than 1?Hz (real time). This paper describes a methodology to model, detect, and track the position of static and moving objects in real time, based on data obtained from video range cameras. Experiments with this technology have produced results that indicate that video rate 3D data acquisition and analysis of construction environments can support effective modeling, detection, and tracking of project resources. This approach to job site awareness has inherent value and broad application. In combination with effective management practices and other sensing techniques, this technology has the potential to significantly improve safety on construction job sites.     

Challenges in the Application of Stochastic Modal Identification Methods to a Cable-Stayed Bridge

This paper presents an analysis of the data collected in the ambient vibration test of the International Guadiana cable-stayed Bridge, which links Portugal and Spain, based on different output-only identification techniques: peak-picking, frequency domain decomposition, covariance-driven stochastic subspace identification, and data-driven stochastic subspace identification. The purpose of the analysis is to compare the performance of the four techniques and evaluate their efficiency in dealing with specific challenges involved in the modal identification of the tested cable-stayed bridge, namely the existence of closely spaced modes, the perturbation produced by the local vibration of stay-cables, and the variation of modal damping coefficients with wind velocity. The identified natural frequencies and mode shapes are compared with the corresponding modal parameters provided by a previously developed numerical model. Additionally, the variability of some modal damping coefficients is related with the variation of the wind characteristics and associated with a component of aerodynamic damping.