Computational design and digital fabrication of folded timber sandwich structures

Alqaryouti, Yousef; Baber, Kim; Gattas, Joseph M.

doi:10.1016/j.autcon.2019.01.008

Cited by 12 publications

(8 citation statements)

References 12 publications

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“…This variety of terms and concepts are a sample of a target application of Optimization and AI technology. Some application-specific in prefabrication are also suggested [7], [87]- [89]. concret, learn, machin.…”

Section: Discussionmentioning

confidence: 99%

Towards an AEC-AI Industry Optimization Algorithmic Knowledge Mapping: An Adaptive Methodology for Macroscopic Conceptual Analysis

Maureira¹,

Pinto

Yepes³

et al. 2021

IEEE Access

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The Architecture, Engineering, and Construction (AEC) Industry is one of the most important productive sectors, hence also produce a high impact on the economic balances, societal stability, and global challenges in climate change. Regarding its adoption of technologies, applications and processes is also recognized by its status-quo, its slow innovation pace, and the conservative approaches. However, a new technological era -Industry 4.0 fueled by AI-is driving productive sectors in a highly pressurized global technological competition and sociopolitical landscape. In this paper, we develop an adaptive approach to mining text content in the literature research corpus related to the AEC and AI (AEC-AI) industries, in particular on its relation to technological processes and applications. We present a first stage approach to an adaptive assessment of AI algorithms, to form an integrative AI platform in the AEC industry, the AEC-AI industry 4.0. At this stage, a macroscopic adaptive method is deployed to characterize "Optimization", a key term in AEC-AI industry, using a mixed methodology incorporating machine learning and classical evaluation process. Our results show that effective use of metadata, constrained search queries, and domain knowledge allows getting a macroscopic assessment of the target concept. This allows the extraction of a high-level mapping and conceptual structure characterization of the literature corpus. The results are comparable, at this level, to classical methodologies for the literature review. In addition, our method is designed for an adaptive assessment to incorporate further stages.

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Section: Discussionmentioning

confidence: 99%

Towards an AEC-AI Industry Optimization Algorithmic Knowledge Mapping: An Adaptive Methodology for Macroscopic Conceptual Analysis

Maureira¹,

Pinto

Yepes³

et al. 2021

IEEE Access

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“…Building Transfer Language (BTL) is an open standard that is developed and maintained by SEMA and CadWork. It provides a parametric description of the geometry of a timber building component (Al-Qaryouti et al 2019). There are two available variants: BTL and BTLx.…”

Section: Practices In Timber Fabricationmentioning

confidence: 99%

Joint Descriptive Modeling (JDM) for Assembly-Aware Timber Structure Design

Lharchi¹,

Thomsen²,

Tamke³

2021

Proceedings of the 2021 DigitalFUTURES

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Joints design is an essential step in the process of designing timber structures. Complex architectural topologies require thorough planning and scheduling, as it is necessary to consider numerous factors such as structural stability, fabrication capabilities, and ease of assembly. This paper introduces a novel approach to timber joints design that embed both fabrication and assembly considerations within the same model to avoid mistakes that might cause delays and further expenses. We developed a workflow that allows us to identify the fundamental data to describe a given joint geometry, machine-independent fabrication procedures, and the assembly sequence. Based on this, we introduce a comprehensive descriptive language called Joint Descriptive Model (JDM) that leverages industry standards to convert a joint into a usable output for both fabrication and assembly simulations. Finally, we suggest a seed of a joint’s library with some common joints.

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“…A strategy to improve structural load transfer at joint locations was also recently proposed by the authors, utilising a hybrid material system [35].…”

Section: Introductionmentioning

confidence: 99%