Introduction to Prefabrication and Automation in Construction

New developments and recent advances in construction methods have the potential to change the future of the architecture, engineering and construction industry. Prefabrication, along with modular construction, provides a safe and controlled environment for the production of building construction elements and raises the need for improved collaboration and coordination from design to manufacturing and from transportation to final assembly. Prefabrication also provides relief from the skilled construction labor shortage while opening up new opportunities for mass customization within the building industry. Prefabrication and modular construction automation are emerging expansion routes for the construction industry. In addition, integral to developing the knowledge of the design and construction workforce is learning more about emerging construction techniques, in special prefabrication and modular construction and automation processes, through the engagement of lifelong learning

Applied Ergonomics

The ergonomic injuries and solutions have been extensively studied in the construction industry; however, the prevalence of work-related injuries, risky activities, and effective solutions in the transportation industry are not understood. This study aims to explore the prevalence of work-related injuries, risky activities, and potentially ergonomic solutions among transportation workers. The approach to this study included exploration of worker type, injury types, and activities of top concern through historical injury data and an online survey, and proposal and evaluation of ergonomic solutions through onsite observations and field experiments. Results from this study found that back injuries were the most common type of injury sustained. Performing lifting and pushing/pulling activities have caused the most injuries. Back exoskeletons and ergonomic handles were identified as potential solutions to help reduce the risk of injury. Additionally, higher platforms were also suggested to help prevent workers from being forced to perform activities by exerting their back excessively

Automated code compliance checking in the construction domain using semantic natural language processing and logic-based reasoning

Construction projects must comply with various regulations. The manual process of checking the compliance with regulations is costly, time consuming, and error prone. With the advancement in computing technology, there have been many research efforts in automating the compliance checking process, and many software development efforts led by industry bodies/associations, software companies, and/or government organizations to develop automated compliance checking (ACC) systems. However, two main gaps in the existing ACC efforts are: (1) manual effort is needed for extracting requirements from regulatory documents and encoding these requirements in a computer-processable rule format; and (2) there is a lack of a semantic representation for supporting automated compliance reasoning that is non-proprietary, non-hidden, and user-understandable and testable. To address these gaps, this thesis proposes a new ACC method that: (1) utilizes semantic natural language processing (NLP) techniques to automatically extract regulatory information from building codes and design information from building information models (BIMs); and (2) utilizes a semantic logic-based representation to represent and reason about the extracted regulatory information and design information for compliance checking. The proposed method is composed of four main methods/algorithms that are combined in one computational framework: (1) a semantic, rule-based method and algorithm that leverage NLP techniques to automatically extract regulatory information from building codes and represent the extracted information into semantic tuples, (2) a semantic, rule-based method and algorithm that leverage NLP techniques to automatically transform the extracted regulatory information into logic rules to prepare for automated reasoning, (3) a semantic, rule-based information extraction and information transformation method and algorithm to automatically extract design information from BIMs and transform the extracted information into logic facts to prepare for automated reasoning, and (4) a logic-based information representation and compliance reasoning schema to represent regulatory and design information for enabling the automated compliance reasoning process. To test the proposed method, a building information model test case was developed based on the Duplex Apartment Project from buildingSMARTalliance of the National Institute of Building Sciences. The test case was checked for compliance with a randomly selected chapter, Chapter 19, of the International Building Code 2009. Comparing to a manually developed gold standard, 87.6% precision and 98.7% recall in noncompliance detection were achieved, on the testing data

Multi-source adversarial transfer learning based on similar source domains with local features

Transfer learning leverages knowledge from other domains and has been successful in many applications. Transfer learning methods rely on the overall similarity of the source and target domains. However, in some cases, it is impossible to provide an overall similar source domain, and only some source domains with similar local features can be provided. Can transfer learning be achieved? In this regard, we propose a multi-source adversarial transfer learning method based on local feature similarity to the source domain to handle transfer scenarios where the source and target domains have only local similarities. This method extracts transferable local features between a single source domain and the target domain through a sub-network. Specifically, the feature extractor of the sub-network is induced by the domain discriminator to learn transferable knowledge between the source domain and the target domain. The extracted features are then weighted by an attention module to suppress non-transferable local features while enhancing transferable local features. In order to ensure that the data from the target domain in different sub-networks in the same batch is exactly the same, we designed a multi-source domain independent strategy to provide the possibility for later local feature fusion to complete the key features required. In order to verify the effectiveness of the method, we made the dataset "Local Carvana Image Masking Dataset". Applying the proposed method to the image segmentation task of the proposed dataset achieves better transfer performance than other multi-source transfer learning methods. It is shown that the designed transfer learning method is feasible for transfer scenarios where the source and target domains have only local similarities.Comment: Submitted to Information Fusio

16-01 Paths to ADA-Compliance: the Performance and Cost Efficiency of Measurement Technologies that Support ADA-Mandated, Self-Evaluations of Pedestrian Rights of Way

This study used terrestrial laser scanner and open source processing algorithms to develop an approach to automate the evaluation of transportation infrastructure in public rights of way. We estimated compliance or noncompliance of specific roadway features with the design standards adopted by the US Access Board and required under the Americans with Disabilities Act (ADA) such as minimum sidewalk width, maximum cross slopes and presence/absence of pedestrian connectivity automatically with extracting roadway features from point cloud data (PCD). We then compared the accuracy and cost efficiency of the automated with more conventional evaluative techniques to identify the potential risks, gains and the overall efficacy of these approaches. The collected raw data were processed through a sequential process including simplification, optimization, segmentation, and road feature categorization. Finally, the road elements were detected as the road feature objects. By developing a more thorough assessment process, this research provided communities with the information necessary to strategically plan transportation infrastructure improvements for people with limited mobility

A New Domain Decomposition Parallel Algorithm for Convection–Diffusion Problem

Basing on overlapping domain decomposition, we construct a new parallel algorithm combined the method of subspace correction with least-squares procedure for solving time-dependent convection–diffusion problem. This algorithm is fully parallel. We analyze the convergence of approximate solution, and study the dependence of the convergent rate on the spacial mesh size, time increment, iteration number and sub-domains overlapping degree. Both theoretical analysis and numerical results suggest that only one or two iterations are needed to reach to given accuracy at each time step

Synthesis Study on Employing Snowplow Driving Simulators in Training

Departments of Transportation (DOTs) need to mobilize workers under harsh weather conditions for winter operations. Traditional snowplow driver training at INDOT is usually conducted annually before the snow season; therefore, it does not replicate the conditions which drivers will be exposed to during winter operations. To this point, some state DOTs have incorporated simulators in their snowplow driver training. Despite this raised interest, few studies have (1) surveyed other state DOTs about the use of this equipment in winter operations driver training, or (2) provided a systematic consideration of all factors involved in the decision to use driving simulators in snowplow driver training. To fill these gaps, the present study synthesizes information from previous literature, revises current information from INDOT, and surveys other state DOTs to identify the benefits and challenges of driving simulators for snowplow driver training. A mixed methods approach was utilized including a review of current INDOT practices, interviews with stakeholders, a survey of other state DOTs, and results from a pilot training. Based on the findings, the researchers recommend that INDOT continues to explore the use of driving simulators for training purposes in addition to the yearly snowplow driver training, due the ability to reinforce learning in a safe environment. Moreover, the research team suggests the following areas for further research: evaluating optimal simulator “seat time,” peer learning in simulator training, and the impact of experience level and work assignment in the perception of driving simulator training effectiveness

BIM Standards for Roads and Related Transportation Assets

With the industry foundation classes (IFC) building information modeling (BIM) standard (ISO 16739) being adopted by AASHTO as the national standard for modeling bridge and road infrastructure projects, there comes a great opportunity to upgrade the INDOT model development standard of roads and related assets to 2D+3D BIM. This upgrade complies with the national standard and creates a solid foundation for preserving accurate asset information for lifecycle data needs. This study reviewed the current modeling standards for drainage and pavement at different state DOTs and investigated the interoperability between state-of-the-art design modeling software and IFC. It was found that while the latest modeling software is capable of supporting interoperability with IFC, there remain gaps that must be addressed to achieve smooth interoperability for supporting life cycle asset data management. Specifically, the prevalent use of IfcBuildingElementProxy and IfcCourse led to a lack of differentiation in the use of IFC entities for the representations of different components, such as inlets, outfalls, conduits, and different concrete pavement layers. This, in turn, caused challenges in the quality assurance (QA) of IFC models and rendered the conventional model view definition (MVD)-based model checking insufficient. To address these gaps and push forward BIM for infrastructure at INDOT, efforts were made in this project to initially create model development instruction manuals that can serve as the foundation for further development and the eventual establish a consistent and comprehensive IFC-based modeling standards and protocols. In addition, automated object classification leveraging invariant signatures of architecture, engineering, and construction (AEC) objects was investigated. Correspondingly, a QA method and tool was developed to check and identify the different components in an IFC model. The developed tool achieved 91% accuracy on drainage and 100% accuracy in concrete pavement in its tested performance. These solutions aim to support the lifecycle management of INDOT transportation infrastructure projects using BIM and IFC

Life Cycle Integration of Building Information Modeling in Infrastructure Projects

Building Information Modeling (BIM) can provide solutions to many challenges of asset management, such as missing data, incompatible software, and an unclear business process. However, current implementation of BIM in infrastructure projects has only considers limited factors, such as technology application and digital information delivery, while issues of system compatibility and information needs are still missing. Different aspects of a business are interdependent and an incompatible development of various factors might result in different levels of BIM implementation or even project failure. Comprehensive research is needed to explore the key factors and challenges of BIM implementation in infrastructure projects. This study conducted interviews and surveys with key stakeholders of infrastructure projects to explore the challenges and potential solutions of BIM implementation. Interviews were conducted with 37 professionals and surveys were conducted with 102 professional stakeholders, including owners, designers, contractors, and software vendors. Four main factors, challenges, and potential solutions were identified from content analysis of the interviews and further validated by the surveys. These factors include process factor (when), technology factor (how), people factor (who), and information factor (what). Corresponding solutions are proposed to refine the current workflow and practices

Life Cycle Integration of Building Information Modeling in Infrastructure Projects

Building Information Modeling (BIM) can provide solutions to many challenges of asset management, such as missing data, incompatible software, and an unclear business process. However, current implementation of BIM in infrastructure projects has only considers limited factors, such as technology application and digital information delivery, while issues of system compatibility and information needs are still missing. Different aspects of a business are interdependent and an incompatible development of various factors might result in different levels of BIM implementation or even project failure. Comprehensive research is needed to explore the key factors and challenges of BIM implementation in infrastructure projects. This study conducted interviews and surveys with key stakeholders of infrastructure projects to explore the challenges and potential solutions of BIM implementation. Interviews were conducted with 37 professionals and surveys were conducted with 102 professional stakeholders, including owners, designers, contractors, and software vendors. Four main factors, challenges, and potential solutions were identified from content analysis of the interviews and further validated by the surveys. These factors include process factor (when), technology factor (how), people factor (who), and information factor (what). Corresponding solutions are proposed to refine the current workflow and practices