Guidelines for Failure Investigations, Volume 2
Friday, November 4
8:00 am–12:00 pm
Instructors: Randall P. Bernhardt, P.E., S.E., F.SEI, F.ASCE; Richard S. Barrow, P.E., S.I.; Chase Anderson, P.E., M.ASCE
“Guidelines for Failure Investigation” Volume 1, written by the Committee on Forensic Investigation of the Forensic Engineering Division, American Society of Civil Engineers, provides an overview of the planning, analysis, and reporting components of a successful civil engineering failure investigation. This workshop will address the content in Volume 2 of the “Guidelines” which is currently being written. Volume 2 will provide guidance for conducting a forensic investigation based upon the type of construction materials or structures involved in the failure. This workshop will provide a description of unique material properties, construction and fabrication techniques, common failure modes, means of deterioration, inspection techniques and laboratory tests for common construction materials. Additionally, the workshop will address building envelopes and construction practices as they relate to failure investigations.
Resources for Practitioners to Reduce Claims
Friday, November 4
1:00 pm–5:00 pm
Instructors: Jim Harris, Dan Becker, Dan Harpstead, and Ron Anthony
This workshop will involve participants in discussions for reducing the frequency of claims through education and managing those claims that do occur through the claims resolution process. Organized by the ASCE Committee on Claims Reduction and Management (CCRM), case studies of claims against engineers on several subjects, including examples of retaining walls, expansive soils, thermal break connectors for concrete slabs, storm water detention products, corrosion and other forms of deterioration of structural materials, bracing for temporary construction loads, excessive deflections, and differential volume changes, will be used to illustrate the lessons and to generate participation among the workshop attendees. Cryptically, it is less costly for the practicing engineer to learn from the mistakes of others than to learn by making the same mistake on their own. Recent activities of CCRM, such as the Agreement Basics guide will be included in the discussion.
Workshop Leaders, all who are members of CCRM:
- Ronald Anthony, President, Anthony & Associates, Fort Collins, CO
- Daniel Becker, DBecker Consulting, LLC
- Daniel Harpstead, Senior Vice President, Kleinfelder
- James Robert Harris, Principal, J. R. Harris & Company, Denver, CO
Machine Learning and Emerging Technologies for Forensic Engineering
Friday, November 4
8:00 am–5:00 pm
Instructors: Rui Liu, Ph.D, P.E., M.ASCE; Mirian Velay-Lizancos, Ph.D., Glenn Katz, M. ASCE, Nina Anani-Manyo Ballinger, Pengkun Liu
Abstract
Machine learning, deep learning, and other emerging technologies, e.g., virtual reality (VR), augmented reality (AR), and mixed reality (MR), have been reported to boost architects, engineers, construction managers, and builders’ decision-making capacities. For example, artificial intelligence systems, i.e., computer vision algorithms, have been developed to analyze drone images taken after earthquakes or hurricanes to evaluate damages and identify critical areas quickly. Inspection images could be processed to detect defects in civil infrastructure. Natural disasters could be simulated and experienced in a virtual environment. Mixed realities have the potentials to enable inspectors to “visualize” hidden construction components. The workshop offers an opportunity for participants to learn fundamental concepts of machine learning, deep learning, mixed reality, and their potential applications in forensic engineering. Workshop participants are expected to receive hands-on training on coding with algorithms of machine learning and deep learning to process various data, including material properties tested in the lab, and inspection images. The workshop will engage participants to discuss the impacts on the future practices of forensic engineering and how to be prepared for the potentially dramatic changes. The one-day short course is composed of three parts:
- Machine learning and deep learning for forensic engineering (4 hrs)
- VR, AR and MR for forensic engineering (2.5 hrs)
- Discussions on future practices of forensic engineering driven by emerging technologies (1.5 hrs)
Learning outcomes
- Fundamentals of machine learning, deep learning, and artificial intelligence
- Hand-on coding using Tensorflow to build a convolutional neural network for image processing
- Understanding of VR, AR, and MR technologies
- Learning the workflow to deploy virtual models onto VR, AR and/or MR devices
- Interpreting impacts of emerging technologies on future practices of forensic engineering