SYKK1310 Administration of Medicine Course description

The rapid advancement of digital twins, machine learning, and optimization methods is transforming sustainable building design. These technologies enable precise prediction and analysis of energy consumption, occupant comfort levels such as Predicted Percentage of Dissatisfied (PPD), and environmental impacts. Tools such as Life Cycle Assessment (LCA) provide critical insights into the long-term sustainability of building materials and design choices. Genetic Algorithm (GA) optimization identifies solutions that balance energy efficiency, comfort, and environmental performance. These innovations address the demands of climate adaptation and resource efficiency, fostering robust and sustainable design strategies.

This course aims to equip students with the knowledge and skills necessary to address complex challenges in designing energy-efficient, climate-resilient, and sustainable building envelopes. The course emphasizes the integration of advanced technologies with traditional building physics principles, exploring the interaction between materials, components, and environmental impacts. Building on foundational insights from MABY4200 Building Physics and Climate Adaptation of Buildings and MABY4700 Life Cycle Assessment for Built Environment, the course combines theoretical frameworks with practical applications. Students will learn to use digital twins, machine learning, and optimization methods alongside sustainability assessments and life cycle analyses to create innovative and efficient building solutions. The following topics are addressed in particular:

• Digital twin technology for predicting and optimizing energy performance and occupant comfort.
• Machine learning for forecasting energy use, occupant discomfort (e.g., PPD), and environmental impacts.
• Genetic algorithm (GA) optimization to balance energy efficiency, comfort, and sustainability in building design.
• Life cycle assessment (LCA) for evaluating environmental impacts and improving design decisions.
• Relevant standards and regulations.
• Principles of zero emission buildings, passive- and plus-house building design.
• Integration of building physics principles in the holistic design of building envelopes.
• Thermal storage in conventional and innovative building materials (e.g., PCMs).
• Dynamic building energy simulations.

On successful completion of this course the students are expected to have these learning outcomes acquired:

Knowledge:

The candidate can

• discuss and describe user experience using phenomenological, cognitive and behavioral theoretical concepts
• choose relevant methods for exploration of design for experience

Skills:

The candidate can:

• organize and plan design process using phenomenological, cognitive and behavioral theoretical concepts
• implement experiments, user testing and probing in lab conditions and in the field
• design product features and service components considering experience as a key factor
• critically assess their designs, product features, service components and implications of the design intervention for the experience

General competence:

The candidate can:

• critically assess wider societal perspective about the effect of experience of products and services
• practice evaluation of ethical issues and cultural relevance when conceptualizing and developing design for experience

The teaching will largely consist of digital and physical lectures, software demonstration and exercises. Students will also be given a major project assignment in which they are to design an sustainable building with regards to building physics, climate adaptation, energy efficiency and indoor environment as well as CO2 emissions.

Digital lectures will be recorded, and the material will be made available to students on CANVAS.

No work requirement.

Project report prepared in groups of 2 students, approx. 80 - 100 pages (excl. appendices).

The exam can be appealed.

All aids permitted.

Grade scale A-F.

Two internal examiner. (External examiners are used regulary).

Michael Long

Etter fullført emne har studenten følgende læringsutbytte definert i kunnskaper, ferdigheter og generell kompetanse:

Kunnskap

Studenten

• kan gjøre rede for sykepleiers rolle og ansvar innenfor et avgrenset fordypningsområde
• kan oppsummere relevant forskning og fagutvikling innenfor valgte fordypningsområde

Ferdigheter

Studenten

• kan utarbeide en prosjektbeskrivelse som konkretiserer tidsplan og hvordan bacheloroppgaven skal gjennomføres med tilgjengelige ressurser
• kan formulere en tydelig sykepleiefaglig problemstilling som er mulig å besvare innenfor oppgavens ramme
• kan gjennomføre en avgrenset systematisk litteraturstudie i tråd med gjeldende vitenskapelige normer
• kan avklare begreper, analysere og vurdere ulike kunnskapskilder og anvende disse til å formulere faglige resonnementer
• kan presentere fagstoff på en selvstendig, logisk, kritisk og systematisk måte

Generell kompetanse

Studenten

• kan formidle og argumentere for styrker og svakheter ved egen studie, substansielt og metodisk
• kan reflektere over forskningsetiske problemstillinger