2016 Erector Set-Iowa State University Construction Engineering Program

Faculty Research 2015-2016 (Cont.) submittals. Constructability is hard to understand because the current process is lagging behind available technology. This research will investigate what is really needed on construction plans, what the contractor really needs to build, and what is proposed. It will also identify the necessary requirements to provide for construction plans. The requirements need to change and may be a sliding scale based on the project being constructed. What goes in a plan set for a total reconstruction might look different than what goes in the set or what is required for a total reconstruction. This research will assist the Minnesota Department of Transporation (MnDOT) engineers in getting a better understanding of how and which types of plans, models, and other bid documents are used and delivered electronically in the construction industry, and how these practices can be employed in MnDOT business practices.

Midwest Transportation Center, Terrestrial Laser Scanning-Based Bridge Structural Condition Assessment PI: Yelda Turkan, Co-PI: Simon Laflamme (Structures Division) Contract: 07/01/2014 – 12/31/2015 Project Total: $64,115 Objective, accurate, and fast assessment of bridge structural condition is critical to timely assess safety risks. Current practices for bridge condition assessment rely on visual observations and manual interpretation of reports and sketches prepared by inspectors in the field. Visual observation, manual reporting and interpretation has several drawbacks, such as being labor intensive, subject to personal judgment and experience, and prone to error. Terrestrial laser scanners (TLS) are promising sensors to automatically identify structural condition indicators, such as cracks, displacements and deflected shapes, as they are able to provide high coverage and accuracy at long ranges. However, there is limited research conducted on employing TLS to detect cracks for bridge condition assessment, which mainly focused on manual detection and measurements of cracks, displacements or shape deflections from the laser scan point clouds. TLS is an advance 3D imaging technology that is used to rapidly measure the 3D coordinates of densely scanned points within a scene. The data gathered by a TLS is provided in the form of 3D point clouds with color and intensity data often associated with each point within the cloud.

In this project, a novel adaptive Wavelet Neural Network (WNN) based approach to automatically detect concrete cracks from TLS point clouds for bridge structural condition assessment has been developed. The adaptive WNN is designed to self-organize, self-adapt, and sequentially learn a compact reconstruction of the 3D point cloud. The architecture of the network is based on a single-layer neural network consisting of Mexican hat wavelet functions. The approach was tested on a cracked concrete specimen. The preliminary experimental results show that the proposed approach is promising as it enables detecting concrete cracks accurately from TLS point clouds. Using the proposed method for crack detection would enable automatic and remote assessment of bridge condition. This would, in turn, result in reducing costs associated with infrastructure management and improve the overall quality of our infrastructure by enhancing maintenance operations.

National Cooperative Highway Research Program (NCHRP), Standard Definitions for Comparable Pavement Cracking Data PI: Omar Smadi (Transportation Division), Co-PIs: Halil Ceylan (Geotech Division), Yelda Turkan Contract: 04/01/2015 – 12/01/2016 Project Total: $300,000 The objective of this research is to develop standard, discrete definitions for common cracking types in 22