Development and improvement of warm-mix asphalt technology

Traditionally, asphalt mixtures were produced at high temperatures (between 150°C to 180°C) and therefore often referred to as Hot Mix Asphalt (HMA). Recently, a new technology named Warm Mix Asphalt (WMA) was developed in Europe that allows HMA to be produced at a lower temperature. Over years of research efforts, a few WMA technologies were introduced including the foaming method using Aspha-min® and Advera® WMA; organic additives such as Sasobit® and Asphaltan B®; and chemical packages such as Evotherm® and Cecabase RT®. Benefits were found when lower temperatures were used to produce asphalt mixtures, especially when it comes to environmental and energy savings. Even though WMA has shown promising results in energy savings and emission reduction, however, only limited studies and laboratory tests have been conducted to date. The objectives of this project are to 1) develop a mix design framework for WMA by evaluating its mechanical properties; 2) evaluate performance of WMA containing high percentages of recycled asphalt material; and 3) evaluate the moisture sensitivity in WMA. The test results show that most of the WMA has higher fatigue life and TSR which indicated WMA has better fatigue cracking and moisture damage resistant; however, the rutting potential of most of the WMA tested were higher than the control HMA. A recommended WMA mix design framework was developed as well. The WMA design framework was presented in this study to provide contractors, and government agencies successfully design WMA. Mixtures containing high RAP and RAS were studied as well and the overall results show that WMA technology allows the mixture containing high RAP content and RAS to be produced at lower temperature (up to 35°C lower) without significantly affect the performance of asphalt mixture in terms of rutting, fatigue and moisture susceptibility. Lastly, the study also found that by introducing the hydrated lime in the WMA, all mixtures modified by the hydrated lime passed the minimum requirement of 0.80. This indicated that, the moisture susceptibility of the WMA can be improved by adding the hydrated lime.

THE PERFORMANCE AND MODIFICATION OF RECYCLED ELECTRONIC WASTE PLASTICS FOR THE IMPROVEMENT OF ASPHALT PAVEMENT MATERIALS

Bulk electric waste plastics were recycled and reduced in size into plastic chips before pulverization or cryogenic grinding into powders. Two major types of electronic waste plastics were used in this investigation: acrylonitrile butadiene styrene (ABS) and high impact polystyrene (HIPS). This research investigation utilized two approaches for incorporating electronic waste plastics into asphalt pavement materials. The first approach was blending and integrating recycled and processed electronic waste powders directly into asphalt mixtures and binders; and the second approach was to chemically treat recycled and processed electronic waste powders with hydro-peroxide before blending into asphalt mixtures and binders. The chemical treatment of electronic waste (e-waste) powders was intended to strengthen molecular bonding between e-waste plastics and asphalt binders for improved low and high temperature performance. Superpave asphalt binder and mixture testing techniques were conducted to determine the rheological and mechanical performance of the e-waste modified asphalt binders and mixtures. This investigation included a limited emissions-performance assessment to compare electronic waste modified asphalt pavement mixture emissions using SimaPro and performance using MEPDG software. Carbon dioxide emissions for e-waste modified pavement mixtures were compared with conventional asphalt pavement mixtures using SimaPro. MEPDG analysis was used to determine rutting potential between the various e-waste modified pavement mixtures and the control asphalt mixture. The results from this investigation showed the following: treating the electronic waste plastics delayed the onset of tertiary flow for electronic waste mixtures, electronic waste mixtures showed some improvement in dynamic modulus results at low temperatures versus the control mixture, and tensile strength ratio values for treated e-waste asphalt mixtures were improved versus the control mixture.

Three dimensional finite element simulation of polymer melting and flow in a single-screw extruder : optimization of screw channel geometry

Single-screw extrusion is one of the widely used processing methods in plastics industry, which was the third largest manufacturing industry in the United States in 2007 [5]. In order to optimize the single-screw extrusion process, tremendous efforts have been devoted for development of accurate models in the last fifty years, especially for polymer melting in screw extruders. This has led to a good qualitative understanding of the melting process; however, quantitative predictions of melting from various models often have a large error in comparison to the experimental data. Thus, even nowadays, process parameters and the geometry of the extruder channel for the single-screw extrusion are determined by trial and error. Since new polymers are developed frequently, finding the optimum parameters to extrude these polymers by trial and error is costly and time consuming. In order to reduce the time and experimental work required for optimizing the process parameters and the geometry of the extruder channel for a given polymer, the main goal of this research was to perform a coordinated experimental and numerical investigation of melting in screw extrusion. In this work, a full three-dimensional finite element simulation of the two-phase flow in the melting and metering zones of a single-screw extruder was performed by solving the conservation equations for mass, momentum, and energy. The only attempt for such a three-dimensional simulation of melting in screw extruder was more than twenty years back. However, that work had only a limited success because of the capability of computers and mathematical algorithms available at that time. The dramatic improvement of computational power and mathematical knowledge now make it possible to run full 3-D simulations of two-phase flow in single-screw extruders on a desktop PC. In order to verify the numerical predictions from the full 3-D simulations of two-phase flow in single-screw extruders, a detailed experimental study was performed. This experimental study included Maddock screw-freezing experiments, Screw Simulator experiments and material characterization experiments. Maddock screw-freezing experiments were performed in order to visualize the melting profile along the single-screw extruder channel with different screw geometry configurations. These melting profiles were compared with the simulation results. Screw Simulator experiments were performed to collect the shear stress and melting flux data for various polymers. Cone and plate viscometer experiments were performed to obtain the shear viscosity data which is needed in the simulations. An optimization code was developed to optimize two screw geometry parameters, namely, screw lead (pitch) and depth in the metering section of a single-screw extruder, such that the output rate of the extruder was maximized without exceeding the maximum temperature value specified at the exit of the extruder. This optimization code used a mesh partitioning technique in order to obtain the flow domain. The simulations in this flow domain was performed using the code developed to simulate the two-phase flow in single-screw extruders.

Towards greater accuracy in individual-tree mortality regression

Background mortality is an essential component of any forest growth and yield model. Forecasts of mortality contribute largely to the variability and accuracy of model predictions at the tree, stand and forest level. In the present study, I implement and evaluate state-of-the-art techniques to increase the accuracy of individual tree mortality models, similar to those used in many of the current variants of the Forest Vegetation Simulator, using data from North Idaho and Montana. The first technique addresses methods to correct for bias induced by measurement error typically present in competition variables. The second implements survival regression and evaluates its performance against the traditional logistic regression approach. I selected the regression calibration (RC) algorithm as a good candidate for addressing the measurement error problem. Two logistic regression models for each species were fitted, one ignoring the measurement error, which is the “naïve” approach, and the other applying RC. The models fitted with RC outperformed the naïve models in terms of discrimination when the competition variable was found to be statistically significant. The effect of RC was more obvious where measurement error variance was large and for more shade-intolerant species. The process of model fitting and variable selection revealed that past emphasis on DBH as a predictor variable for mortality, while producing models with strong metrics of fit, may make models less generalizable. The evaluation of the error variance estimator developed by Stage and Wykoff (1998), and core to the implementation of RC, in different spatial patterns and diameter distributions, revealed that the Stage and Wykoff estimate notably overestimated the true variance in all simulated stands, but those that are clustered. Results show a systematic bias even when all the assumptions made by the authors are guaranteed. I argue that this is the result of the Poisson-based estimate ignoring the overlapping area of potential plots around a tree. Effects, especially in the application phase, of the variance estimate justify suggested future efforts of improving the accuracy of the variance estimate. The second technique implemented and evaluated is a survival regression model that accounts for the time dependent nature of variables, such as diameter and competition variables, and the interval-censored nature of data collected from remeasured plots. The performance of the model is compared with the traditional logistic regression model as a tool to predict individual tree mortality. Validation of both approaches shows that the survival regression approach discriminates better between dead and alive trees for all species. In conclusion, I showed that the proposed techniques do increase the accuracy of individual tree mortality models, and are a promising first step towards the next generation of background mortality models. I have also identified the next steps to undertake in order to advance mortality models further.