2024 Faculty Courses School of Environment and Society Undergraduate major in Architecture and Building Engineering
Mathematical Methods in Architectural Planning and Engineering
- Academic unit or major
- Undergraduate major in Architecture and Building Engineering
- Instructor(s)
- Toshihiro Osaragi / Takashi Asawa / Takuya Oki / Tsubasa Okaze / Wataru Umishio
- Class Format
- Lecture (Face-to-face)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 7-8 Tue / 1-2 Fri
- Class
- -
- Course Code
- ARC.A205
- Number of credits
- 200
- Course offered
- 2024
- Offered quarter
- 4Q
- Syllabus updated
- Mar 17, 2025
- Language
- Japanese
Syllabus
Course overview and goals
To learn mathematical techniques in architectural design and research.
Course description and aims
To acquire mathematical skills contributing architectural design and research.
Keywords
Mathematics
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
Lecture.
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | Mathematics and physics of heat conduction | Learn differential and difference method, Taylor expansion, and Fourier's law for heat conduction analysis. |
| Class 2 | Basics of land use | building coverage ratio, lot area, road area ratio, floor area ratio, access cost, location requirement, bid rent curve |
| Class 3 | Mathematics and physics of convection | Learn mathematics and physics of convective heat transfer in architectural spaces. |
| Class 4 | Land use change | revenue and expenses, supply and demand, land price factors, land market |
| Class 5 | Mathematics and physics of convection-diffusion equation | Learn mathematics and physics of convection-diffusion equation by discretizing and solving one-dimensional equation as an example. |
| Class 6 | Land use data and models | land use data, aggregated model, disaggregated model |
| Class 7 | Fundamental of statistical analysis | Learn probability distribution, probability density function, central limit theorem, and confidence interval for analyzing built environmental data. |
| Class 8 | Planning of facility location | Learn how to determine the optimum location of facilities. |
| Class 9 | Error analysis and hypothesis test | Learn error analysis and hypothesis test for environmental and social data. |
| Class 10 | Planning of facility size | Learn how to plan facility size based on the estimated number of users. |
| Class 11 | Estimation of regional population | Learn how to estimate the regional population. |
| Class 12 | Regression analysis | Learn least square method, regression analysis, correlation coefficient, and multiple regression analysis for environmental and social data. |
| Class 13 | Estimation of the number of facility users | Learn how to estimate the number of facility users using choice behavior models. |
| Class 14 | Application of statistical analysis | Learn the application of statistical analysis using health data in houses |
Study advice (preparation and review)
To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.
Textbook(s)
Handout
Reference books, course materials, etc.
Handout
Evaluation methods and criteria
Report, Quiz, etc.
Related courses
- ARC.P301 ： Architectural Planning II
- ARC.S303 ： Structural Design III
- ARC.E201 ： Environmental Engineering
Prerequisites
N/A