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As construction and remediation take place throughout New Jersey, the amount of construction and demolition debris increases, while the availability of landfill space decreases. A viable solution for disposing of these materials is to incorporate them into base and subbase applications. An extensive laboratory program was conducted on two types of construction and demolition debris: recycled concrete aggregate (RCA) and recycled asphalt pavement aggregate (RAP). These two materials were compared with dense-graded aggregate base coarse (DGABC), which currently is being used in roadway base applications in New Jersey. Both RCA and RAP were mixed at various percentages with the DGABC to evaluate whether an optimum mix blend could be formulated. The materials were evaluated under a traffic-type loading scheme that included resilient modulus and permanent deformation via cyclic triaxial testing. Laboratory tests indicated that the RAP, RCA, and DGABC blended materials all obtained higher resilient modulus values than the currently used DGABC. The permanent deformation results indicated that the RCA mixed samples obtained the lowest amount of permanent deformation when the material was cyclically loaded to 100,000 cycles. In contrast, the permanent deformation testing on RAP mixed samples resulted in the highest amount of permanent deformation at the same number of cycles. Existing models currently used for quarried base and subbase materials were used to predict the permanent deformation in the recycled materials. Laboratory test results indicated that these models could be used for predicting permanent deformation in unbound recycled materials.

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The condition of bridges is critical for the safety of the traveling public. Bridges deteriorate with time as a result of material aging, excessive loading, environmental effects, and inadequate maintenance. The current practice of nondestructive evaluation (NDE) of bridge decks cannot meet the increasing demands for highly efficient, cost-effective, and safety-guaranteed inspection and evaluation. In this paper, a mechatronic systems design for an autonomous robotic system for highly efficient bridge deck inspection and evaluation is presented. An autonomous holonomic mobile robot is used as a platform to carry various NDE sensing systems for simultaneous and fast data collection. The robot's NDE sensor suite includes ground penetrating radar arrays, acoustic/seismic arrays, electrical resistivity sensors, and video cameras. Besides the NDE sensors, the robot is also equipped with various onboard navigation sensors such as global positioning system (GPS), inertial measurement units (IMU), laser scanner, etc. An integration scheme is presented to fuse the measurements from the GPS, the IMU and the wheel encoders for high-accuracy robot localization. The performance of the robotic NDE system development is demonstrated through extensive testing experiments and field deployments.

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This paper addresses the placement of multicast nodes in wavelength-routed all-optical networks. This problem is motivated by the expected high cost of optical multicast cross-connects due to fabrication complexity and power considerations. An analytical model for the approximate blocking probability in multicast networks is developed. The blocking performance is used to guide an iterative algorithm, Multicast-ADD, for the placement of multicast nodes. We provide validation of the model and the techniques used. In addition, a simulation study is provided to evaluate the performance of the heuristic. Insights obtained from the simulation results reveal that: 1) only a subset of the nodes (found to be 50%) need to be multicast-capable for acceptable blocking performance; 2) the blocking performance of Multicast-ADD outperforms that of random placement; and 3) employing alternate routing trees is not helpful in the optimization procedure.

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