Improved understanding of rutting resistance of a rubberized asphalt concrete pavement that contains reclaimed asphalt pavement ͑RAP͒ is important to stimulating the use of rubberized asphalt mixtures. Use of RAP in the past has proved to be economical, environmentally sound, and effective in increasing the rutting resistance of asphalt mixtures. Rubberized asphalt has been used successfully in improving the mechanical characteristics, such as rutting resistance, of typical hot mix asphalt ͑HMA͒ mixture around the country and the world. The objective of this research was to investigate the rutting resistance characteristics of the rubberized asphalt mixtures through a laboratory testing program. The experimental design included use of two rubber types ͑ambient and cryogenically produced͒, four rubber contents, and three crumb rubber sizes. The results of the experiments indicated that the use of RAP and crumb rubber in the HMA can effectively improve the rut resistance of these mixes.

SUMMARYThis article presents a new vertex-to-face contact searching algorithm for the three-dimensional (3-D) discontinuous deformation analysis (DDA). In this algorithm, topology is applied to the contact rule when any two polyhedrons are close to each other. Attempt is made to expand the original contact searching algorithm from two-dimensional (2-D) to 3-D DDA. Examples are provided to demonstrate the new contact rule for vertex-to-face contacts between two polyhedrons with planar boundaries.

SUMMARYMathematical interpretation of the pore sue distribution (PSD) data as measured by mercury intrusion porosimetry was revealed in detail. The PSD data were commonly presented as cumulative intruded volume per gram of specimen versus pore size. In this paper, however, they were expressed in a dimensionless term for convenient mathematical operations. The pore size density function was deduced from the PSD data using the finite difference approximation and curve-fitting technique. For the prediction of permeability, first the published correlations between permeability and pore geometry were critically reviewed. A probabilistic permeability model based on the pore size density function was then developed, which can be thought of as a generalization of Childs and Collis-George's model. Predictions of permeability of the compacted soils studied using the developed model were very good for a wide range of permeabilities.

The purpose of this study was to use conjoint analysis to determine the importance of specific dental benefit plan features for University of Iowa (UI) staff and to build a model to predict enrollment. From a random sample of 2000 UI staff, 40 percent responded (N = 773). The survey instrument was developed using seven attributes (five dental benefit plan features and two facility characteristics) each offered at three levels (e.g., premium = $20, $15, $10/month). Pilot testing was used to find a realistic range of plan options. Twenty‐seven hypothetical dental benefit plans were developed using fractional factorial combinations of the three levels for each of the seven attributes. For all of the hypothetical plans, dental care was to be provided in the UI predoctoral dental clinic. Plan profiles were arranged four per page by combining the existing plan with three hypothetical plans, for a total of nine pages. Respondents' task was to select one plan from each set of four. A regression‐like statistical model (Multinomial Logit) was used to estimate importance of each attribute and each attribute level. Relative importance (and coefficients) for each of the seven attributes are as follows: maximum annual benefit (.98), orthodontic coverage (.72), routine restorative (.70), major restorative (.67), time to complete treatment (.61), clinic hours of operation (.47), premium (.18). For each attribute, relative importance of each of three levels will also be presented. These coefficients for each level are used to predict enrollment for plans with specific combinations of the dental benefit plan features.