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Evolutionary topology optimization of continuum structures
Evolutionary Topology Optimization of Continuum Structures treads new ground with a comprehensive study on the techniques and applications of evolutionary structural optimization (ESO) and its later version bi-directional ESO (BESO) methods.
eBook
Mechanical Behavior and Design Properties of Ultra-High- Performance Concrete (Open Source)
The appropriate and efficient design of structural components made with ultra-high-performance concrete (UHPC) requires the establishment of key design properties and material models that engage UHPC's distinct mechanical properties, as compared to conventional concrete. This paper presents the results of an extensive program of compression and tension property assessment executed according to existing testing methods to assess the mechanical characteristics of several commercially available UHPC products. The experimental results are then used to propose suitable mechanical models and design parameters that are foundational for the structural-level application of UHPC. The models rely on a set of experimentally identified mechanical performance properties that distinguish UHPC from conventional concrete and establish the basis of the material qualification for use in structural design. As such, this work constitutes a fundamental step in ongoing efforts to develop UHPC structural design guidance in the United States. Keywords: compression properties; mechanical models; structural design parameters; tension properties; ultra-high-performance concrete (UHPC).
Journal Article
Two-stage automatic structural design of steel frames based on parametric modeling and multi-objective optimization
Traditional structural design involves drawing recognition, repeated modeling, parameter tuning, and numerous mechanical analyses by skilled designers, which is time-consuming and inefficient. To address those problems, a two-stage automatic structural design of the steel frame based on expert experiences is proposed. In the first stage, from the computer-aided design plain drawing, semantic features (walls and openings) and geometrical information of architectural elements are extracted by a layer classification method. The segmentation of rooms is conducted by an enclosed region detection method and the connectivity graph is generated using the connected component analysis method. Based on expert experiences considering both structure and architectural function requirements, the structural member configuration and the floor load distribution are automatically established to obtain the parametric structural model. In the second stage, a modified particle swarm optimization (MPSO) based on expert experiences is proposed for single-objective structural optimization according to the design codes. Then based on MPSO, a hierarchical multi-objective optimization method is adopted to obtain more available solutions with different economic benefit and redundant safety. The results show that the proposed two-stage structural design framework is fully automatic and highly efficient. It integrates parametric modeling and structural optimization, and also enables effective transfer of different data items including architectural plan and structural model. It provides a guideline to automatic structural design of steel frames.
Journal Article
Integrated Schematic Design Method for Shear Wall Structures: A Practical Application of Generative Adversarial Networks
The intelligent design method based on generative adversarial networks (GANs) represents an emerging structural design paradigm where design rules are not artificially defined but are directly learned from existing design data. GAN-based methods have exhibited promising potential compared to conventional methods in the schematic design phase of reinforced concrete (RC) shear wall structures. However, for the following reasons, it is challenging to apply GAN-based approaches in the industry and to integrate them into the structural design process. (1) The data form of GAN-based methods is heterogeneous from that of the widely used computer-aided design (CAD) methods, and (2) GAN-based methods have high requirements on the hardware and software environment of the user’s computer. As a result, this study proposes an integrated schematic design method for RC shear wall structures, providing a workable GAN application strategy. Specifically, (1) a preprocessing method of architectural CAD drawings is proposed to connect the GAN with the upstream architectural design; (2) a user-friendly cloud design platform is built to reduce the requirements of the user’s local computer environment; and (3) a heterogeneous data transformation method and a parametric modeling procedure are proposed to automatically establish a structural analysis model based on GAN’s design, facilitating downstream detailed design tasks. The proposed method makes it possible for the entire schematic design phase of RC shear wall structures to be intelligent and automated. A case study reveals that the proposed method has a heterogeneous data transformation accuracy of 97.3% and is capable of generating shear wall layout designs similar to the designs of a competent engineer, with 225 times higher efficiency.
Journal Article