Muntasir

Muntasir Billah

Positions

Associate Professor

Schulich School of Engineering, Department of Civil Engineering

Contact information

Email

muntasir.billah@ucalgary.ca

Web presence

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Research Gate

LinkedIn

Location

Office: CNRL Engineering ComplexENF284

Preferred method of communication

Please contact me via email

Background

Credentials

Professional Engineer (P.Eng.), Association of Professional Engineers and Geoscientists of Alberta (APEGA),

Educational Background

PhD The University of British Columbia, 2015

MSc The University of British Columbia, 2011

BSc Military Institute of Science and Technology, 2008

Biography

Dr. Muntasir Billah, P.Eng., is a tenured associate professor in The Department of Civil Engineering at the University of Calgary. Before joining at the University of Calgary, he was an assistant professor in the Department of Civil Engineering at Lakehead University (2018-2022). He received his PhD and MSc in structural engineering from the University of British Columbia, Canada. Before joining academia, Dr. Billah worked as a Structural (Bridge) Engineer at Parsons, Vancouver, BC. He was involved in various large-scale infrastructure projects in North America including the SW Calgary Ring Road, California High-Speed Rail Project, Turcot Interchange, and Regina Bypass project. He is the recipient of many awards and scholarships. He was awarded the 2016 UBC Governor General’s Gold Medal—one of Canada’s most prestigious academic awards. He is the vice-chair of the Engineering Mechanics and Materials (EMM) division of CSCE, member of ACI Committee 341, Earthquake-Resistant Concrete Bridges, Member of American Society of Civil Engineers and Structural Engineers Association of British Columbia.

 

Research

Areas of Research

Resilient Infrastructure; Artificial Intelligence in Structural Engineering; Smart Structures; Infrastructure Protection

Dr. Billah’s research is focused towards improving our understanding of the behavior of civil infrastructures under various extreme load conditions. His research is drawn towards the development and application of advanced and novel materials in civil engineering structures and its experimental investigation, advances in numerical and experimental earthquake engineering along with development of advance modeling tools and techniques using artificial intelligence. He is particularly interested in:

Resilient Infrastructure
Structural design for extreme event, Multihazard performance assessment and design, Risk and vulnerability assessment
Artificial Intelligence in Structural Engineering
Innovation in structural design using AI, Data driven structural design, Failure mode prediction, Identification of performance limit states
Smart Structures
Smart materials and structural application, Adaptive structural system, Smart infrastructure monitoring
Infrastructure Protection
Performance-based design, Climate resilient design, Retrofit of deficient infrastructure

Courses

Course number Course title Semester
ENCI 551 Structural Engineering II Fall 2022
ENCI 610 Natural Hazards; Risks and Impacts Winter 2023
ENCI 317 Mechanics of Solids Fall 2023
ENCI 619 Earthquake Engineering for Structures Winter 2024

Projects

Multihazard Resilient Design of Highway Bridges

Extreme climate and natural hazard events are rare and occur largely unanticipated. These events not only cause economic losses by damaging infrastructure and other facilities but also adversely affect post disaster response capability. Current design codes and guidelines fail to consider the complex and intertwined effects of multiple hazards. This research program is designed to develop a performance based approach for multihazard resilient bridge systems to ensure enhanced resilience and robustness, thus minimizing the adverse social and economic impacts of multiple hazards. This research focuses on identifying synergies between hazards that make an integrated multihazard design approach possible through a structured design process.

Structural Performance Assessment using Data Driven Machine Learning Techniques

Artificial intelligence is proving to be an efficient alternative approach to classical modeling techniques which refers to the branch of computer science that develops machines and software with human-like intelligence. Among the different artificial intelligence techniques, machine learning (ML) has recently acquired considerable attention and are establishing themselves as a new class of intelligent methods for use in all engineering domains. In recent years, there has been a growing interest towards the application of ML techniques in civil engineering practices especially in the structural damage assessment area. For structural engineers and designers, it is of paramount importance to identify the anticipated failure mode of any structure. Our group is working towards developing data-driven machine learning algorithms for structural failure mode identification, performance prediction as well as condition assessment.

Fragility and Risk quantifications of highway bridges

Safety and serviceability of highway bridges, during and after an earthquake, is a prerequisite to ensure continuous transport facilities, emergency and evacuation routes. This research is focused on seismic fragility assessment and risk quantification of existing bridges and as well as new bridges with smart structural components. Our work ranges from evaluating the seismic risk and vulnerability of bridges with smart materials, such as SMA as reinforcement, SMA based seismic isolators and bridge restrainers, to investigate the efficiency of such novel materials in reducing the seismic collapse risk of bridges. Our group is working on developing collapse vulnerability assessment methodology for bridges to facilitate the collapse risk identification of existing bridges as well as framework for developing hybrid fragility curves which is more suited for regional fragility assessment.

Design of Exposed Column Base Connections Subjected to Axial Load and Bi-Axial Bending

In steel moment-resisting frames, column base connections are one of the most critical structural components that transfer axial forces, shear forces, and moments from the entire building into the foundation. Under dynamic loading, such as earthquake and wind, the dynamic effects are transferred to the structure through these base plates and failure of these base plate connections have resulted in the collapse of entire frames as it affects the ductility demand and force distribution in the structure. The overarching objective of this research is to develop a simplified design guideline for exposed column base plates under combined axial load and bi-axial bending. This will be achieved through the pursuit of the following objectives: 1) experimental investigation of column base plates under combined axial load and bi-axial bending; 2) finite element simulation of base plates under combined axial load and bi-axial bending; 3) comprehensive parametric study to identify the parameters that influence the behavior of exposed column base plates, and 4) developing interaction equations, design methods, and simplified tools for practicing engineers.

Awards

  • Contribution to Teaching Award, Lakehead University. 2021
  • Merit Award for Research Excellence, Lakehead University. 2021
  • Outstanding Reviewer Award, ASCE Journal of Bridge Engineering. 2020
  • Governor General’s Gold Medal, The University of British Columbia. 2016
  • Graduate Dean’s Thesis Fellowship, The University of British Columbia. 2015
  • NSERC Industrial Postgraduate Scholarship (IPS), Natural Sciences and Engineering Research Council of Canada. 2012
  • University Graduate Fellowship (UGF), The University of British Columbia. 2014
  • University Graduate Fellowship (UGF, The University of British Columbia. 2011
  • Graduate Dean’s Entrance Scholarship (GDES), The University of British Columbia. 2010

Publications

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