COURSE UNIT TITLE

: ADVANCED INFORMATION TECHNIQUES IN ARCHITECTURE

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
ELECTIVE

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSISTANT PROFESSOR ERDEM YILDIRIM

Offered to

Architectural Design
Architectural Design

Course Objective

Despite the fact that the experimental use of computers in architecture dates back to the 1960s, its sectoral use has been known as "Computer Aided Design - CAD" for roughly 40 years. With the rise of hardware and computational design, parametric design has been implemented in architectural applications for approximately 20 years. On the other hand, the current development of artificial intelligence technologies has the potential to solve much more complex contextual problems in design fields. Within the scope of this course, the fundamentals of parametric design in architecture are first explained, followed by the methods utilizing artificial intelligence in design and the industry 4.0 tools such as microprocessors, sensors, actuators, 3D printing, and virtual reality. After these introductions, students are expected to complete assignments involving parametric design methods pertinent to the fields they wish to pursue. Within the constant evolution of technological advancements, course topics (weekly schedule, supplementary resources, and other course materials) can be updated annually.

Learning Outcomes of the Course Unit

1   1. To be able to explain the architectural concepts emerging from technological approaches,
2   2. To effectively employ parametric design methods in architecture,
3   3. To be able to utilize multiple artificial intelligence algorithms during the design development process.
4   4. To acquire design development skills utilizing algorithmic optimization techniques.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to Informatics in Architecture and Parametric Design Introduction to the use of computers in architecture, computational methods, parametric design, and Rhinoceros / Grasshopper software.
2 Architextural Visualisation via Text-to-Image A.I. Creating an inspiration board during concept development with artificial intelligence platforms via text-to-image generation
3 Microprocessors, Sensors and Virtual Reality in Parametric Design Contextual data acquisition using Arduino microprocessors and sensors connected to them. Transferring anthropometric data to parametric design with Kinect sensor, parametric design in virtual reality environment
4 Simulation in Parametric Design Simulation techniques with various parametric design plug-ins
5 Attractors in Parametric Design Causality in parametric design, architecture based on context, and force transition to the attractors
6 Optimization and Genetic Algorithm in Parametric Design Optimizing using genetic algorithms, performance-based problem solving in design
7 Machine Learning and Neural Networks in Design Artificial intelligence based fact identification using machine learning and neural networks in parametric design environment
8 Mesh and 3D Printing Preparation of complex forms for 3D printing with mesh modeling, organic sculptural modeling software introduction
9 Computer Aided Manufacturing (CAM) with Parametric Design Developing/adapting algorithms for contemporary production methods. Introduction of slicer softwares
10 Assignment Critiques Giving critiques to students for term assignment
11 Assignment Critiques Giving critiques to students for term assignment
12 Assignment Submission and Evaluation Submission and evaluation of students' term assignments
13 Assignment Report Critiques Critiques of research articles created by students from term assignments
14 Final Report Submission Final Submission and Evaluation

Recomended or Required Reading

Textbook(s)/References/Materials:
Main Resource:
Tedeschi, A. (2014). AAD - Algorithms-aided design: parametric
strategies using grasshopper. Brienza: Le Penseur publisher.

Additional Resourcess:
Anadol, R. (2022). Space in the Mind of a Machine: Immersive Narratives. Architectural Design, 92(3), 28 37. https://doi.org/https://doi.org/10.1002/ad.2810
Akipek, F. Ö. (2004). Bilgisayar teknolojilerinin mimarlıkta tasarım geliştirme aracı
olarak kullanımı. Doktora Tezi, Yıldız Teknik Üniversitesi, Istanbul.
Alexander, C. (1964). Notes on the synthesis of form . Massachusetts: Harvard
University Press.
Allen, C. (1966). Computer-aided drawing and design. Production Engineer, 45(8),
442-456.
Andia, A. (2001). Integrating digital design and architecture during the past three
decades. Proceeding. Seventh International Conference on Virtual Systems and
Multimedia içinde (677 686). Berkeley: IEEE.
Baudrillard, J. (1994). Simulacra and Simulation, trans. S. F. Glaser. Michigan: The University of Michigan Press.
Beesley, P., Hirosue, S. ve Ruxton, J. (2006). Toward responsive architectures.
Responsive architectures: Subtle technologies, 1, 3 11
Boldrin, N. (2014). Dynamic inevitability in computational design. Yüksek Lisans
Tezi, University of Cincinnati, Ohio.
Carpo, M. (2011). The Alphabet and the Algorithm. Cambridge, MA: The MIT Press.
Kolarevic, B. ve diğer. (2000). Digital architectures. ACADIA 2000, 126(1), 123-130.
Leach, N. (2022). Architecture in the Age of Artificial Intelligence: An Introduction to AI for Architects. Bloomsbury.
Schumacher, P. (2009). Parametricism: A new global style for architecture and urban
design. Architectural Design, 79(4), 14 23.
Yazar, T. ve Uysal, S. (2016). Grasshopper ile parametrik modelleme. Istanbul: Pusula.
Yildirim, T., & Yavuz, A. O. (2012). Comparison of Traditional and Digital Visualization Technologies in Architectural Design Education. Procedia - Social and Behavioral Sciences, 51, 69 73.
Yıldırım, E. (2019). Yaya Davranışlarının Algoritmik Yaklaşımla Analizi Ve Tasarıma Aktarılması (PhD). Dokuz Eylul University, Izmir.
Yıldırım, E. (2022a). A.I. s Vision of Future Cities. Urbanizm, 27(7), 72 83.
Yıldırım, E. (2022b). Text-to-Image Generation A.I. in Architecture. In Art and Architecture: Theory, Practice and Experience (pp. 97 120). Lyon: Livre de Lyon.
Yıldırım, E. (2022c). Topology Optimization in Architecture Practices. In O. P. Bicer & F. Y. Gurani (Eds.), Research & Reviews In Architecture, Planning And Design (Vol. 1, pp. 117 139). Ankara: Gece. Retrieved from
Yıldırım, E. (2022d). Yapay Karşılaşma: Le Corbusier ve Parametrisizm. Yapı, 482(7), 20 24.

Course Materials: Personal Laptop, Arduino Uno or Mega education set.

Materials: Weekly materials for class discussions will be announced at the beginning of the term.

Planned Learning Activities and Teaching Methods

Lecture, discussion, individual research, research assignment, paper (research article)

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 ASG ASSIGNMENT
2 PAR PARTICIPATION
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE ASG * 0.40 +PAR * 0.10 +FIN * 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) ASG * 0.40 +PAR * 0.10 + RST * 0.50


Further Notes About Assessment Methods

Course Policies and Rules:
The weekly topics are diverse, but interconnected and cumulative. Absence from class results in an inability to follow the intensive information transfer and class discussions. Students are expected to attend each class with relevant research and notes, and to participate actively in class presentations and discussions.
Absence from class will not be accepted as an acceptable excuse for late submission of assignments and work. Late submissions will be evaluated differently.
Any instance of plagiarism will result in disciplinary action.

Assessment Criteria

HOMEWORK-PRESENTATION %40
ACTIVE PARTICIPATION TO THE LECTURE %10
FINAL EXAM %50
--
MAKE-UP %50

Further Notes about Assessment Methods:
This course consists of lectures delivered by the course coordinator and discussions of assignments conducted primarily by students. Required student participation must be intense. The course is centered around advanced parametric design techniques. Prior to class, students are required to conduct research on related algorithms. As homework and as a presentation of the homework, students conduct research on the technique/tool they wish to improve within the scope of this course and develop algorithms utilizing a variety of plug-ins. The course instructor provides individual feedback on how to continue research based on the submitted suggestions. Students are expected to submit their final paper as a presentation and research paper in which they develop and receive feedback on their own suggestions.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

e-mail: erdem.yildirim@deu.edu.tr
tel: 0 232 301 83 91
ig: the.arkitek
yt: erdem yildirim

Office Hours

It will be announced at the beginning of the term.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 2 26
Preparations before/after weekly lectures 13 9 117
Preparing assignments 1 20 20
Preparation for final exam 1 20 20
Final 1 2 2
Project Assignment 1 2 2
TOTAL WORKLOAD (hours) 187

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.155555
LO.2555
LO.3555
LO.4555

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

Copyright 2015 DEÜ. BİD

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