2 resultados para nonlinear mixed effects models
em DRUM (Digital Repository at the University of Maryland)
Resumo:
This research includes parametric studies performed with the use of three-dimensional nonlinear finite element models in order to investigate the effects of cantilever wingwall configurations on the behavior of integral abutment bridges located on straight alignment and zero skew. The parametric studies include all three types of cantilever wingwalls; inline, flared, and U-shaped wingwalls. Bridges analyzed vary in length from 100 to 1200 feet. Soil-structure and soil-pile interaction are included in the analysis. Loadings include dead load in combination with temperature loads in both rising and falling temperatures. Plasticity in the integral abutment piles is investigated by means of nonlinear plasticity models. Cracking in the abutments and stresses in the reinforcing steel are investigated by means of nonlinear concrete models. The effects of wingwall configurations are assessed in terms of stresses in the integral abutment piles, cracking in the abutment walls, stresses in the reinforcing steel of abutment walls, and axial forces induced in the steel girders. The models developed are analyzed for three types of soil behind the abutments and wingwalls; dense sand, medium dense sand, and loose sand. In addition, the models consider both the case of presence and absence of predrilled holes at the top nine feet of piles. The soil around the piles below the predrilled holes consists of very stiff clay. The results indicate that for the stresses in the piles, the critical load is temperature contraction and the most critical parameter is the use of predrilled holes. However, for both the stresses in the reinforcing steel and the axial forces induced in the girders, the critical load is temperature expansion and the critical parameter is the bridge length. In addition, the results indicate that the use of cantilever wingwalls in integral abutment bridges results in an increase in the magnitude of axial forces in the steel girders during temperature expansion and generation of pile plasticity at shorter bridge lengths compared to bridges built without cantilever wingwalls.
Resumo:
This dissertation proposes statistical methods to formulate, estimate and apply complex transportation models. Two main problems are part of the analyses conducted and presented in this dissertation. The first method solves an econometric problem and is concerned with the joint estimation of models that contain both discrete and continuous decision variables. The use of ordered models along with a regression is proposed and their effectiveness is evaluated with respect to unordered models. Procedure to calculate and optimize the log-likelihood functions of both discrete-continuous approaches are derived, and difficulties associated with the estimation of unordered models explained. Numerical approximation methods based on the Genz algortithm are implemented in order to solve the multidimensional integral associated with the unordered modeling structure. The problems deriving from the lack of smoothness of the probit model around the maximum of the log-likelihood function, which makes the optimization and the calculation of standard deviations very difficult, are carefully analyzed. A methodology to perform out-of-sample validation in the context of a joint model is proposed. Comprehensive numerical experiments have been conducted on both simulated and real data. In particular, the discrete-continuous models are estimated and applied to vehicle ownership and use models on data extracted from the 2009 National Household Travel Survey. The second part of this work offers a comprehensive statistical analysis of free-flow speed distribution; the method is applied to data collected on a sample of roads in Italy. A linear mixed model that includes speed quantiles in its predictors is estimated. Results show that there is no road effect in the analysis of free-flow speeds, which is particularly important for model transferability. A very general framework to predict random effects with few observations and incomplete access to model covariates is formulated and applied to predict the distribution of free-flow speed quantiles. The speed distribution of most road sections is successfully predicted; jack-knife estimates are calculated and used to explain why some sections are poorly predicted. Eventually, this work contributes to the literature in transportation modeling by proposing econometric model formulations for discrete-continuous variables, more efficient methods for the calculation of multivariate normal probabilities, and random effects models for free-flow speed estimation that takes into account the survey design. All methods are rigorously validated on both real and simulated data.