Research Details

I had the privilege of working as a MITACS Accelerate Intern with the Lafarge Canada Ltd. and Eagle Builders Ltd., two partners company of Canadian Precast Concrete Institute (CPCI). Through this research internship, my objective was to understand precast products production process. At the same time I was working towards developing a solution algorithm that can capture valuable human experience in the complex, dynamic, tightly constrained application setting and turn it into logic-driven analytical decision support systems so to identify the optimum product sequence, generate the best resource allocation plan, synchronize multilevel schedules for different-level management and stakeholders.

MITACS Featured Page: Click Here

Click here to read the research problem statement from Imgineering Magazine.

In Canada, a large portion of infrastructure investment is seen in the school building projects either for a new school or renovations in the last decade. Many have resulted from addressing evolving capacity needs due to student growth, changes in regional demographics and boundaries, meeting the improvements necessitated by operating half a century-old building systems, and recognizing the need for an improved facility to provide a 21-century learning environment to the students. Due to limited resources and budget, agencies are responsible for prioritizing the most crucial need to fund these capital projects. While a vast amount of work is being published to prioritize the capital projects, school building projects show a unique type of need, and the framework for prioritizing the capital is yet to be formalized. The aim of this project is to develop a fuzzy expert system framework for evaluating the school infrastructure project prioritization process based on the need. 

Publications

• Monjurul Hasan and Ross Newton (2022) "An Automation Solution for Evaluating School Capital Projects Based on Fuzzy Expert System" Canadian Journal of Civil Engineering, Link

• Monjurul Hasan, and Ross Newton, (2021) "A Framework to Evaluate the School Infrastructure Project Need Using Fuzzy Expert System," Lecture Notes in Civil Engineering: Construction Speciality, CSCE & CRC 2021, Springer Nature. Walbridge, S., Nik-Bakht, M., Ng, K.T.W., Shome, M., Alam, S., El-Damatty, A., and Lovegrove, G. (Eds), Vol. 251, Chap. 34 (1-10). Link

As a Ph.D. student researcher, I was involved in a collaborative research and development (CRD) project sponsored by NSERC at EPCOR. The primary objective of my engagement was to structure one practical research problem statement. The research problem identified is to address the crew-job matching planning and crew use scheduling need in the application context of providing short-term drainage maintenance services by a typical municipal infrastructure maintenance organization like EPCOR. The specific research questions identified are 1) how to assign, sequence and schedule a set of known jobs for a limited number of crews, 2) how to assign competent crews to execute particular jobs so to maximize total crew utilization while at the same time finding the best overall matching between crews and jobs according to crew competence assessment by an experienced planner. I developed one solver template as the prototype optimization solution to address the research questions, as mentioned earlier. The prototype solution is currently in the testing phase and has the potential to be implemented on a large scale.

Publication

• Monjurul Hasan, Ming Lu, Simaan AbouRizk, and Jason Neufeld (2020) “Planning and Scheduling Drainage Infrastructure Maintenance Operations Under Hard and Soft Constraints: A Simulation Study.” Winter Simulation Conference 2020, Orlando, Florida, USA, December 13-16, 2020, 2505 - 2516.

I worked with the Supreme Group on a summer project in the year of 2017. I worked on developing a dynamic simulation application in modeling complex workflows of a bridge girder fabrication shop based on a three-tiered modeling framework. The objective of this framework was to produce straightforward, adaptive simulation models that can sufficiently represent essential operational details on the shop floor from the perspective of a shop superintendent. Simplified Discrete Event Simulation Approach (SDESA) is as the simulation engine for this project. First, as part of the CRD research team, I helped to capture and document the dynamic workflow of the steel girder fabrication process and developed the first version of the workflow model using the SDESA platform. 

Publications

• Monjurul Hasan, Ming Lu, and Chris Ritcey (2019) “Simulation-Based Approach to Systematic Project Planning and Scheduling at a Bridge Fabrication Shop.” Winter Simulation Conference 2019, National Harbor, MD, USA, December 8-11, 2019, 3019-3030.

• Monjurul Hasan, Ming Lu, and Ken Brid (2019) “Implementing Shop-Floor Operations Simulation in Planning and Scheduling Fabrication of Steel Girders for Bridge Projects” 2019 European Conference on Computing in Construction Chania, Crete, Greece July 10-12, 2019, 75-84.

• Ming Lu, Monjurul Hasan, and Arash Mohsenijam (2019) “Three-Tiered Simulation Framework for Modeling Bridge Girders Fabrication Processes in a Steel Fabrication Shop.” 2019 ASCE International Conference on Computing in Civil Engineering, Atlanta, Georgia, U.S.A June 17 - 19, 2019, 553-560.

This research is focused on accurate positioning of excavator’s bucket tip in real-time by advanced computing schemes, plus associated planning aimed to utilize the excavator as a survey robot while conducting its operations in the field extensively. This solution doesn't need the expensive infrastructure; just the operator of the excavator is sufficient. There is no need for any other specialist or highly regulated operator’s licenses to conduct the survey by UAV or high-precision RTK GPS; no limitation on battery use life, no safety hazards, or privacy concerns in flying UAV above. The proposed solution is to take full advantage of real-time computing based on taking straightforward measurements from the simplest, low-cost sensors while achieving sufficient accuracy and reliability in targeted applications. The new approach for precise position tracking of the excavator's bucket tip can be used to plan the operation trajectory of the excavator's arm to streamline its movement and track its cycle time during the period of its field operation. At the same time, this study presents a framework for the work planning of a backhoe excavator, which explains how the proposed technology can be adopted in the field. The operation algorithm developed for such excavator is not only limited to an excavator retrofitted with sensors but can also be readily adapted for a complete autonomous excavator in the future.

Commercial Feasibility

The work has several unique features. It is not susceptible to the obstructed line of sight, climatic variation. It presents a methodology to quantify the positioning uncertainty accumulated from the sensors' data and plan for calibration of errors as part of the generated work plan. Finally, it shows how this technology can be efficiently integrated with analytical work planning for an excavator extensively. 

Publications 

• Monjurul Hasan, and Ming Lu, "Planning Work for a Self-Tracking Excavator Capable of Automatic Field Survey", 17th International Conference on Computing in Civil and Building Engineering (ICCCBE), 2018/5. 

• Monjurul Hasan, and Ming Lu, (2017) "Error Quantification and Visualization in Using Sensors to Position Backhoe Excavator", ASCE book "Computing in Civil Engineering in 2017: Smart Safety, Sustainability, and Resilience.", Lin, KY, El-Gohery, N, and Tang, P. (Eds) pp 150-157.

I was engaged in research with the Government of Alberta on a project titled “Tunneling Safe: Developing a training program to enhance safety awareness in tunnel construction and maintenance operations." The objective of the project was to produce and easy learning platform for occupational health and safety (OHS) training regarding tunnel construction. All through the project, I lead a team of three students (one undergrad and two graduate students) to find the best OHS best code of practice for tunneling. Later I developed one web-based training module (website) by compiling all the research findings. 

The developed web content was directly used to give one seminar lecture and guide a take-home group-based study for a University of Alberta, Construction Engineering and Management” graduate-level class (CIV E 601: “Analytical Methods Project Management” course) in Fall, 2018.

Training Website: https://sites.google.com/a/ualberta.ca/ohst/home

Publication

• Ming Lu, and Monjurul Hasan (2018) “Developing a cost-effective and adaptive training program to enhance construction safety in tunneling construction” Construction Research Congress, New Orleans, Louisiana, USA, April 2 -4, 635 - 644.

Technical Report

• Ming Lu, and Monjurul Hasan (2018) “Tunneling Safe: Developing a Training Program to Enhance Safety Awareness in Tunnel Construction and Maintenance Operations” University of Alberta, Edmonton, Canada.

In a deep beam, a significant amount of the load is transferred to the supports by a compression thrust. The problem exerted by the RC deep beams is that a number of variables affecting shear behavior have led to a limited understanding of shear failure mechanism and prediction of exact shear strength. Although a large number of research works exist, there is no agreed rational procedure to predict the strength of reinforced concrete deep beams. Recently, Artificial Intelligent (AI) techniques became popular in case of solving various nonlinear problems including civil engineering. In this work, Artificial Neural Network (ANN) will be used to model and evaluate the shear strength of reinforced concrete deep beams, and the performance of the network will be assessed by comparing the constructed ANN model with the existing formulas. Engineering programming package MATLAB will be used for ANN construction and performance evaluation.

Objectives:

• Determination of the shear strength of deep beam using different codes and recent formulas

• Construction of a neural network model which can predict the ultimate shear strength of deep beams.

• Compare the prediction results for different loading conditions

• Compare the predicted strength of deep beams using ANN with the existing popular formulas

• Using the trained ANN for analyzing the significance of different parameters affecting the shear strength of deep beam and use the results for deriving a new handy approach for determination of shear strength of deep beams.

• Compare the proposed formula-based results with the ANN predicted results.

Brick aggregate has vast popularity in Bangladesh and used as the alternate source of coarse aggregate. This research is focused on making a review of the mechanical properties of brick aggregate concrete and its use as a sustainable construction material. This research has also interest in finding out the possibility of making high strength concrete with brick aggregate.

Collaborator: Dr. Rezaul Karim, Associate Professor, DUET

Publications

• Monjurul Hasan, Golam Kibria, and Abdus Salam, (2016) "Study on Brick Aggregate made Pervious Concrete at Zero Fine Level", International Journal of Materials and Metallurgical Engineering, Vol. 3, No. 1. 4 pages

• Robiul Islam, Monjurul Hasan, Rezaul Karim and M.F.M. Zain (2015) “Properties of Fly Ash Brick Prepared in Local Environment of Bangladesh”, International Journal of Civil, Environmental, Structural, Construction, and Architectural Engineering Vol:9, No:12, pp. 1387 - 1391.

• Md Shafiullah, Monjurul Hasan, and Rezaul Karim, (2015) "Properties of Non-cement Binder Containing Slag, Fly Ash, Rice Husk Ash and Coconut Fiber with Chemical Activator". First International Conference on Advances in Civil Infrastructure and Construction Materials (CICM-2015), MIST, Dhaka, December 14-15.

In the last decade, Bangladesh’s economy has seen a robust expansion of the Readymade Garments (RMG) sector with approximately 5600 garments factory and an estimated 4 million workers working under this sector. In the financial year 2012, Ready Made Garments (RMG) industry exported garment products of 19.1 billion USD, a total that accounted for 13% of the country’s GDP. Despite the contribution of this industry to our country's economy, we can not think of being a developed country. In recent years it has seen that some fire collapse grows the attention of present fire risk of these industries. This research is about to figure out the present scenario of the fire risk of the garment factories of Bangladesh.

Undergrad Students

    Md. Akram Ali; Email: en.akram13@gmail.com

    Rafsan Jany; Email: rafsanjany50@gmail.com

In the construction process, it is always important to know the concrete compressive strength. The recommended procedure to ensure the concrete strength is to perform a cylinder test. The test result of the concrete cylinder on the 28th day represents the characteristic strength of the concrete that has been prepared and cast to form the concrete work. Usually, two concrete cylinders (specimens) are cast for each day’s representative strength test. The 3-days or 7-days tests are done to assess the early gain of concrete strength. However, 28-days tests are mandatory as per design/construction code requirements. Waiting 28 days is quite a time consuming while it is important to ensure the quality control process. This research is an attempt to develop a simple mathematical model based on concrete’s nature of strength gain to predict the compressive strength of concrete on the 28th day from early age results. The model is a simple equation known as a rational polynomial. The proposed model has a good potential to predict concrete strength at different ages with high accuracy.

Publications

1. Ahsanul Kabir, Monjurul Hasan, and Md Khasro Miah, "Strength Prediction Model for Concrete", International Journal on Civil and Environmental Engineering, Vol. 2, No. 1, August 2013, pp. 14-19.

2. Monjurul Hasan and Ahsanul Kabir, “Artificial Neural Network for Concrete Mix Design”, Proceedings of UKIERI Concrete Congress, Jalandhar, Punjab, India, March 5 - 8, 2013, pp. 1754-1764.

3. Monjurul Hasan and Ahsanul Kabir, “Prediction of Compressive Strength of Concrete from Early Age Test Result”, Proceedings of 4th Annual Paper Meet and 1st Civil Engineering Congress, Dhaka, Bangladesh, December 22-24, 2011, pp. 01-07.