Course Content

Course Content

Presentation of preliminary investigations necessary to form a conceptual and/or programmatic basis towards the final research report, the thesis.. Semester work conducted as bi-weekly rehearsals leading to fully-structured textual submissions. Attendance mandatory.

Course Content

Research: What it is and what it is not. Research ethics: over and covert plagiarism. Finding/choosing a research topic and the mechanics of conducting it. Reference sources: compilation for various types of bibliography. Citations and quotations. Paraphrasing and summaries. Working outlines. Research papers/reports, theses and dissertations. Use of writing manuals: Style, grammar and punctuation. Internet and computer software. Thesis abstracts. The final report.

Course Content

The problem: where it lies; what be its ‘parts’; how best describe it. Information: sources, modes, types and cost(s). Objectives: formulation and realization. Data: measures of location and dispersion; reliability and consistency; interpretation and inference. Data: frequency and other distributions. Probability: dependent and independent events; the random experiment, observation and variable. The design of research and experiments: population and sample; parameters and statistics; systematic sampling and sampling distributions; the sample variance and confidence intervals. The Hypothesis: formulation, tests, errors and level of significance. Quantitative and qualitative methodologies.

Course Content

A seminar consisting of weekly submissions by students on topics selected from among the following: office and site organization, site layout, subcontract management, management of legal and liability affairs, site security, management information systems, financial management, purchasing and materials management, stock control, cost control, prefabrication plant management, repair shop management, quality control, project scheduling and management, resource management, etc.

Course Content

Classification of large scale structural forms and their development through the ages. Descriptive aspects of the study of form and shape. Morphological analysis of basic forms in architecture. Concepts and models bridging geometric morphology and architecture. Hierarchies of dimensional spaces. Planar and spatial orders. The interaction between the geometric morphological characteristics of selected structures and their physical-structural characteristics: spatial truss structures, membrane and shell structures, folding plate structures, etc.

Course Content

Structural systems; framed, wall, and combined structures, floor slabs (one and two-way slabs with beams, joist slabs, flat slabs and flat plates, waffle slabs). Earthquake safe architectural design concept. Building code requirements for reinforced concrete structures. Design example.

Course Content

Basic principles for analytical modeling of structural systems. Hierarchy of models. Techniques for understanding behavior of structural elements. Material behavior, element behavior. Use of elements in frames, walls, plates, shells and 3-D solid modeling. Linear analysis of statically determinate and indeterminate structures; calculation of elastic displacements. Introduction to seismic analysis of building structures: basic concepts and, methods of solution. Checking the model and evaluating the results.

Course Content

Definition, emergence and historical background of tall buildings. Planning and design considerations. Lateral loads; wind and earthquake effects; aerodynamic modifications against wind. Steel, reinforced concrete and composite tall buildings. Structural systems used in architectural design of tall buildings; frame systems, braced frame and
shear walled frame systems, outrigger systems, framed-tube systems, braced-tube systems and bundled tube systems. Buildings with twisted
facades. The course is conducted through lectures, case studies and discussions and aims the student to realize that the design of tall buildings starts with the architect and requires high level of interdisciplinary approach.

Course Content

Various project planning techniques CPM, PERT, PDM, resource allocation and scheduling; budgeting for construction; material flow, planning and control, decision making techniques.

Course Content

Individual tutoring by staff other than the thesis advisor on specific topics related to unique and special interests of graduate students.

Course Content

The need for sustainability in Construction, Green Building Assessment Tools, Site Selection Strategies, Water Efficiency Strategies, Material Selection Strategies, Indoor Environmental Quality Strategies, Operations & Management of Sustainable Buildings, Economic Analysis of Sustainable Buildings, Future of Sustainability in Construction.

Course Content

Course Content

Independent work on a selected research topic. Final paper is written and presented in departmental seminars at the end of the semester.

Course Content

Individual tutoring by staff other than the thesis advisor on unique and/or specialized topics or on problems related to the research work of post-graduate students.

Course Content

Building Information Modeling (BIM),Integrated Design and Delivery, Product and Process Modelling, Model Development, High Performance Building Design, Quantity Extraction and Cost Estimation, Scheduling and 4D Simulations, Clash Detection, Facilities Management, Challenges and Opportunities of BIM.

Course Content

Experiment Design, Analysis of Structural Behaviour, Dynamics of structural/non-structural members, Climate and Weather Analysis, Wind and Airflow Analysis, Aerodynamics of Buildings, Acoustical Analysis, Building Energy Use, Passive and Active Solar Design Strategies, Conceptual Energy Analysis, Whole Building Energy Simulation, Sun and Shadow Studies, Solar Radiation Analysis, Material and Product Selection, Life Cycle Assessment, Materials Performance Assessment, Thermal Performance Assessment, Non-Destructive Testing, Daylight Analysis, Earthquake Simulation.

Course Content

Introduction to Energy Efficiency, Principles of Energy Efficient Construction, Site Selection and Design, Green Neighbourhood, Integrated Building Design, Theory Practice of Energy Simulations, Energy Economics, Laboratory Experiments for Energy Efficieny, Sustainable Facade Systems for Energy Efficient Buildings, Life Cycle Analysis and Carbon Emissions, Measuring Energy Efficency in Buildings, Efficient Lighting for Buildings, Building Automation Smart Metering, Net Zero Net Positive Energy Buildings, Introduction to Passive Systems, Heating, Ventilation and Cooling System Technologies, Buildings with Renewable Energy, Legal Framework of Energy Efficiency, International Collaborative Design Exercise.

Course Content

The course aims to develop an understanding of machine learning in general terms and its potential relation with computational design and architecture. In this course, firstly the notions such as function, parameter, variable, algorithm, data, problem-space, dimension and features are discussed in relation with design disciplines. The discussion is elaborated with basic introduction to probability and optimization theory and corresponding methods to form a basis for machine learning algorithms. Thereafter, the traditional machine learning strategies, models and algorithms are exemplified with their uses in architecture. Followed by the hands-on tutorial for machine learning implementations in a visual programming language, the students are expected to complete a term-project which focuses on a particular problem in the field of architecture by means of a machine learning algorithm.

Course Content

This is an experimental computational design research couese. This course outlines the basic knowledge on nature-informed computational design which is a rapidly developing approach not only in architecture but in many disciplines. In this course along with many well-known approaches, some of the significant examples will be studied in the context of data and act of modelling which are the state-of-art discussions of the computational design today. By conducting a hands-on project and providing a research paper on project, it is aimed to enable students to obtain not only the targeted knowledge and skills, but also the critical point of view to the field.

Course Content

This is an experimental computational design course. This course outlines the basic knowledge on folding in the state of art kinetic, responsive and resilient systems in architecture. In this course, along with mathematics of folding, computational design techniques will be employed to explore not only the mechanisms in digital environment but also in physical one. By conducting a series of hands-on project and providing a research paper on the project, it is aimed to enable students to obtain the targeted knowledge and skills.

Course Content

Advanced use of computational models in the architectural design process, use of CAD/CAM in exploring new forms, structures, materials, new soft tools transforming the design process, ability to deal with complexity and precision of solid models, making of complex forms, understanding how the act of making (fabrication/manufacturing) by CAM determines the transition of CAD model from virtual (immaterial material) space to physical (material), customization of fabrication, exploration of various advance fabrication techniques to point out how these techniques effect the end product (from form to structure, from material to performance).