Sustainability-driven structural design using artificial intelligence
Paper in proceedings, 2019

The construction industry is responsible for a large share of the global environmental impact. The need for addressing sustainability and increased competition calls for the development of innovative design methods that include sustainability in a transparent way. The aim of this work is to propose a framework to use machine learning and artificial intelligence (AI) for structural design optimization based on sustainability and buildability criteria. AI opens up new possibilities to optimize and assess structures early in the planning and design stages. In that way, it is possible to decrease the negative and enhance the positive environmental, economic and social impacts and create a more time‐ and cost‐effective design process. The work is meant to serve as a first step toward the development of AI‐based methods in the construction industry, which can bring digitalization in the construction industry to a new level and create new services and business models.

set‐based design

structural design optimization

life cycle sustainability assessment

artificial intelligence

Sustainability

construction

multi‐criteria decision analysis

Author

Alexandre Mathern

Chalmers, Architecture and Civil Engineering, Structural Engineering

Kristine Ek

Chalmers, Architecture and Civil Engineering, Structural Engineering

Rasmus Rempling

Chalmers, Architecture and Civil Engineering, Structural Engineering

IABSE Congress New York City 2019 - The Evolving Metropolis

1058-1065 16517

IABSE Congress New York City 2019 - The Evolving Metropolis
New York City, USA,

A pilot - Sustainability driven building design based on Artificial Intelligence

Formas, 2018-12-01 -- 2019-09-30.

Sustainable design and production planning

NCC AB, 2017-11-01 -- 2020-05-29.

Swedish Transport Administration, 2017-11-01 -- 2020-05-29.

VINNOVA, 2017-11-01 -- 2020-02-29.

Driving Forces

Sustainable development

Areas of Advance

Transport

Building Futures (2010-2018)

Subject Categories

Civil Engineering

Social Sciences Interdisciplinary

Construction Management

Infrastructure Engineering

Environmental Management

Environmental Analysis and Construction Information Technology

More information

Latest update

4/20/2020