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Full-Text Articles in Engineering
Artificial Neural Network Model For Bridge Deterioration And Assessment, G. Ali, A. Elsayegh, R. Assaad, Islam H. El-Adaway, I. S. Abotaleb
Artificial Neural Network Model For Bridge Deterioration And Assessment, G. Ali, A. Elsayegh, R. Assaad, Islam H. El-Adaway, I. S. Abotaleb
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Missouri has the seventh largest number of bridges nationwide, yet must maintain its inventory with funding from just the fourth lowest gasoline tax in the country. Estimation and prediction of the condition of bridges is necessary to create and optimize future maintenance, repair, and rehabilitation plans as well as to assign the necessary associated budgets. Previous studies have used statistical analysis, fuzzy logic, and Markovian models to develop algorithms for predicting future bridge conditions. Due to the non-linear nature of the relationship between the characteristics of bridges and their deterioration behavior, Artificial Neural Networks (ANN) have shown to be more …
Extending Time Series Forecasting Methods Using Functional Principal Components Analysis, Isaac Michael Wagner-Muns
Extending Time Series Forecasting Methods Using Functional Principal Components Analysis, Isaac Michael Wagner-Muns
Masters Theses
"Traffic volume forecasts are used by many transportation analysis and management systems to better characterize and react to fluctuating traffic patterns. Most current forecasting methods do not take advantage of the underlying functional characteristics of the time series to make predictions. This paper presents a methodology that uses Functional Principal Components Analysis (FPCA) to create smooth and differentiable daily traffic forecasts. The methodology is validated with a data set of 1,813 days of 15 minute aggregated traffic volume time series. Both the FPCA based forecasts and the associated prediction intervals outperform traditional Seasonal Autoregressive Integrated Moving Average (SARIMA) based methods"--Abstract, …
Parametric Analysis Of Resilient Modulus Modeling For Recycled Asphalt Pavement In Base Layer, Ehab Noureldin, Magdy Abdelrahman
Parametric Analysis Of Resilient Modulus Modeling For Recycled Asphalt Pavement In Base Layer, Ehab Noureldin, Magdy Abdelrahman
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
The resilient modulus (MR) has been found to be the most important parameter in the Mechanistic-Empirical Pavement Design Guide (MEPDG) for the base layer. A literature review showed that the use of recycled asphalt pavement (RAP) in the base layer had many economic and structural benefits. The prediction of MR with the specific MEPDG model for the base layer mixed with RAP was found to be reliable for several field conditions. However, further studies of the MEPDG model are needed for an understanding of the physical meaning of each parameter in the model. The most important factor …
Dynamics And Dislodgment From Pore Constrictions Of A Trapped Nonwetting Droplet Stimulated By Seismic Waves, Wen Deng, M. Bayani Cardenas
Dynamics And Dislodgment From Pore Constrictions Of A Trapped Nonwetting Droplet Stimulated By Seismic Waves, Wen Deng, M. Bayani Cardenas
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Seismic waves affect fluid flow and transport processes in porous media. Therefore, quantitative understanding of the role of seismic waves in subsurface hydrodynamics is important for the development of practical applications and prediction of natural phenomena. We present a theoretical fluid dynamics model to describe how low-frequency elastic waves mobilize isolated droplets trapped in pores by capillary resistance. The ability of the theoretical model to predict the critical mobilization amplitudes (Ac) and the displacement dynamics of the nonwetting droplet are validated against computational fluid dynamics (CFD) simulations. Our theory has the advantage of rapid calculation of Ac …