PhD Civil Engineering

The PhD program in Civil Engineering allows for the intensive learning of application of civil engineering concepts among the candidates so that they become technically aware of the wide range of usages of technology in the field of civil engineering.

The candidates enrolling in this program are looking forward not only to master the building and designing of construction materials but are looking forward to pursue leadership roles in the same domain. To fulfill this requirement of the candidates, Queensville University has included research based projects which allows for learning of several principles in civil engineering thus giving in-depth knowledge on the subject.

 

What will you learn from this course

Through this PhD program you will be able to do the following

  • You will work on research based project.
  • You will able to apply engineering principles within and outside the classroom
  • Develop skill set relevant to employers need
  • Students are able to take leadership roles and move up the career ladder more quickly
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Information Research Strategies 2 Introduction to information research including electronic resources. This course is designed to help researchers locate, evaluate, and use information. It includes exploration of the research process, search strategies, locating resources, source documentation, and organization of research.
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Statistical Modeling and Analysis for Complex Data Problems 2 reviews some of today’s more complex problems, and reflects some of the important research directions in the field. work in areas of theoretical statistics, applied statistics, probability theory, and shastic processes – present survey chapters on various theoretical and applied problems of importance and interest to researchers and students across a number of academic domains.
Optimal Experimental Design 2 Introduces the philosophy of experimental design, provides an easy process for constructing experimental designs, calculating necessary sample size using R programs and teaches by example using a custom made R program package:
Mathematical Modeling 2 complete range of basic modeling techniques: it provides a consistent transition from simple algebraic analysis methods to simulation methods used for research. Such an overview of the spectrum of modeling techniques is very helpful for the understanding of how a research problem considered can be appropriately addressed.
Research Methods and Design 2 Learners gain a thorough understanding of statistical tests appropriate to their dissertation topic and design, how to interpret the results of the tests and how to conduct follow-up analyses, as appropriate. This course includes guidelines and "best practices" for collecting data. Power analysis, what it is, why do it, and how to use available software is covered. Data preparation, use of software to analyze data, and understanding the calculated results are covered. Experience with computer-based statistical analysis techniques is stressed. Emphasizes what is applicable to the Learner’s proposed research questions, design, construct/variable definitions and properties of measurements. Satisfactory/Unsatisfactory grade only.
Dissertation Planning, Writing, and Defending 2 step-by-step through the dissertation process, with checklists, illustrations, sample forms, and updated coverage of ethics, technology, and the literature review.
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Pavement Management Systems 2 Principles of pavement management, including inventory, condition assessment, needs determination, and budget analysis. Emphasis on field condition assessment techniques. Presents database design to illustrate data handling techniques and introduces several software packages.
Decision-Making in Complex Dynamic Systems 2 Introduces students to the theory and application of modeling techniques and simulations in the analysis of decision alternatives in complex engineering problems. Topics include queuing theory, system dynamics modeling, agent-based modeling, discrete event simulations, etc. Students will be required to conceptualize and implement an appropriate research/engineering problem of choice (this could be a dissertation/thesis problem).
Introduction to System identification 2 Introductory course in system identification theory, emphasis on fitting classical and modern control-theory models to collected data using least squares and ERA. Preliminary topics include sampling theory and frequency domain math.
Stability of Earth Structures 2 Investigates the stability of both natural and anthropogenic derived structures. Studies include the application of engineering geology to slope issues, slope stability analysis procedures, computational methods. Also covers the design and analysis of soil nail walls.
Engineering with Developing Communities 2 Study of applying appropriate, community-based, and sustainable engineering in developing communities. Concepts of human-centered design and sustainable development are covered. Topics are drawn from several areas of engineering, including water and wastewater treatment, construction materials, solid waste, energy, and information systems.
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Steel Design 3 Additional topics in steel design including beam-columns, floor vibrations, diaphragms, buckling behavior of thin elements, torsional buckling, and beam and column bracing. Includes an introduction to cold-formed steel design.
Public Transit 3 An introduction to public transit, user characteristics, management, transit modes, data collection and surveys, planning, operations, scheduling, transit finances, and future trends.
Soil Mechanics and Foundations 3 Explains basic concepts and fundamental principles of basic mechanics, physics, and mathematics from Practical Situations and Essential Points to Practical Examples,
Stormwater Management and LID 3 Design techniques for stormwater collection, conveyance, infiltration, and detention storage systems are discussed, both traditional stormwater management systems and newer approaches based on the philosophy of low impact development (LID) that seek not to alter the natrual ecology of a site.
Probabilistic Analysis and Reliability 3 Examines probabilistic analysis of engineering systems including first-order methods, Monte Carlo simulation, and time-to-failure analysis. Reliability analysis will include capacity/demand reliability and system reliability. Emphasis will be on civil and environmental engineering systems.
Mathematical Modeling of Earth Systems 3 Introduction to numerical techniques for mathematical modeling of various earth-system phenomena, including groundwater flow, heat transfer, and atmospheric transport. Numerical techniques covered include finite-difference, finite-element, collocation, and characteristic methods. Students write their own mathematical models. Prerequisite
Advanced Soil Mechanics 3 Provides advanced studies in the topics of soil compressibility and soil strength. Develop advanced procedures for determining stress distribution and stress changes from a fundamental basis. Students are strongly advised to take CE5820 concurrently.
Fundamentals of Soil Behavior 3 Develop an understanding of the factors determining and controlling the engineering properties of a soil. Topics include crystal structure and surface characteristics, soil mineralogy, soil formation, rock weathering, soil composition, soil water, clay-water electrolyte systems, soil structure and stability, volume change behavior, and strength and deformation behavior.
Engineering Design Practicum 3 Advanced independent study for students in the Master of Engineering program. In consultation with student's advisor, develop and execute a project demonstrating capabilities in problem solving, communications, and decision making. The practicum can be done on campus or at the site of a Michigan Tech corporate partner.
Advanced Structural Concrete Design 3 Advanced topics in behavior of reinforced-concrete structures and relationships with design. Code requirements, reasoning behind theoretical and experimental studies for understanding structural behavior, and current research issues. Other topics include strut and tie, deep beams, corbel design, and yield-line analysis.
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Concept Paper 2 Ethical issues in research are studied and the Learner evaluates the research plan developed in modules RSH8951-RSH8953 against accepted ethical principles and practices in the field. The material developed in the modules is integrated into a summarizing document called the Dissertation Research Proposal. The proposal is comprised of Chapter I (Introduction), Chapter II (Literature Review), and Chapter III (Methodology). The Learner develops the Dissertation Research Proposal under the supervision of the faculty mentor, with a focus on the conceptual and methodological clarity of the research plan for the Learner’s dissertation topic. Once acceptable to the Learner and the faculty mentor, the draft of the Research Proposal is reviewed by the Learner’s Dissertation Committee and the University’s Ethics Committee. Satisfactory/Unsatisfactory grade only.
Doctoral Comprehensive Examination 2 Assures that the Learner has mastered knowledge of his or her discipline, specialization, and can demonstrate applications of that knowledge before formal candidacy status is granted and research in support of the dissertation is initiated. Satisfactory/Unsatisfactory grade only.
Doctoral Dissertation Research l 2 Continuation of RSH8954-P. The draft of the Dissertation Research Proposal is finalized and approved by the Learner’s Dissertation Committee and the University’s Ethics Committee. All steps necessary to begin data collection, including any necessary pilot testing, are completed. Candidates for the Ph.D. must maintain continuous enrollment. Satisfactory/Unsatisfactory grade only.
Doctoral Dissertation Research ll 2 Dissertation data are collected and analyzed. Candidates for the Ph.D. must maintain continuous enrollment. Satisfactory/Unsatisfactory grade only.
Doctoral Dissertation Research lll 2 the dissertation process is completed. The manuscript is prepared, accepted by the Learner’s Dissertation Committee, and the oral defense is conducted. Candidates for the Ph.D. must maintain continuous enrollment.