An ontology-based approach supporting holistic structural design with the consideration of safety, environmental impact and cost

Early stage decision-making for structural design critically influences the overall cost and environmental performance of buildings and infrastructure. However, the current approach often fails to consider the multi-perspectives of structural design, such as safety, environmental issues and cost in a comprehensive way. This paper presents a holistic approach based on knowledge processing (ontology) to facilitate a smarter decision-making process for early design stage by informing designers of the environmental impact and cost along with safety considerations. The approach can give a reasoning based quantitative understanding of how the design alternatives using different concrete materials can affect the ultimate overall performance. Embodied CO2 and cost are both considered along with safety criteria as indicative multi-perspectives to demonstrate the novelty of the approach. A case study of a concrete structural frame is used to explain how the proposed method can be used by structural designers when taking multi performance criteria into account. The major contribution of the paper lies on the creation of a holistic knowledge base which links through different knowledge across sectors to enable the structural engineer to come up with much more comprehensive decisions instead of individual single objective targeted delivery

Semantic data mining and linked data for a recommender system in the AEC industry

Even though it can provide design teams with valuable performance insights and enhance decision-making, monitored building data is rarely reused in an effective feedback loop from operation to design. Data mining allows users to obtain such insights from the large datasets generated throughout the building life cycle. Furthermore, semantic web technologies allow to formally represent the built environment and retrieve knowledge in response to domain-specific requirements. Both approaches have independently established themselves as powerful aids in decision-making. Combining them can enrich data mining processes with domain knowledge and facilitate knowledge discovery, representation and reuse. In this article, we look into the available data mining techniques and investigate to what extent they can be fused with semantic web technologies to provide recommendations to the end user in performance-oriented design. We demonstrate an initial implementation of a linked data-based system for generation of recommendations

Galileo was wrong: The geometrical design of masonry arches

Since antiquity master builders have used always simple geometrical rules for designing arches. Typically, for a certain form, the thickness is a fraction of the span. This is a proportional design independent of the scale: the same ratio thickness/span applies for spans of 10 m or 100 m. The same kind of rules was also used for more complex problems, like the design of a buttress for a spatial cross-vault. Galileo attacked this kind of proportional design in his Dialogues. He stated the so-called square-cube law: internal stresses grow linearly with scale and therefore the elements of the structures must become thicker in proportion. This law has been accepted many times uncritically for engineering historians, who have considered the traditional geometrical design as unscientific and incorrect. In fact, Galileo’s law applies only to strength problems. Stability problems, such as the masonry arch problem, are governed by geometry. Therefore, Galileo was wrong in applying his reasoning to masonry buildings

Supporting decision-making in the building life-cycle using linked building data

The interoperability challenge is a long-standing challenge in the domain of architecture, engineering and construction (AEC). Diverse approaches have already been presented for addressing this challenge. This article will look into the possibility of addressing the interoperability challenge in the building life-cycle with a linked data approach. An outline is given of how linked data technologies tend to be deployed, thereby working towards a “more holistic” perspective on the building, or towards a large-scale web of “linked building data”. From this overview, and the associated use case scenarios, we conclude that the interoperability challenge cannot be “solved” using linked data technologies, but that it can be addressed. In other words, information exchange and management can be improved, but a pragmatic usage of technologies is still required in practice. Finally, we give an initial outline of some anticipated use cases in the building life-cycle in which the usage of linked data technologies may generate advantages over existing technologies and methods