Integrating computational fluid dynamics and topological optimization for generative design of artificial reefs

This paper explores the development and optimization of artificial reefs by introducing a novel generative design method incorporating Computational Fluid Dynamics (CFD) and Optimization (BESO). Since the 1950s, efforts to create artificial reefs have been pursued to improve marine ecosystems. Our study first surveyed the existing design of artificial reefs. Addressing the limitations in existing design methods, this research employs a topological optimization strategy, focusing on optimizing space allocation for polyphony expansion within these reefs. By analyzing fluid dynamics and connecting it with an iterative optimization process, we assess the effectiveness of material exchange in these artificial structures. This is critical for the design process, considering constraints from advanced manufacturing to allow for quick production with natural-like geometries. To advance the design of artificial reefs and explore new possibilities, we introduce a novel generative design approach, where the design of the reef emerges from the interaction between CFD and BESO, through an iterative process of material removal and addition in response to the external loading condition. The artificial reef generated is compared against benchmarks of current artificial design to assess its material efficiency, structure performance, and geometrical characteristics in complex underwater conditions.

Taihu stone is the most famous one among the top four stones in China. It is formed by the water's erosion in Taihu Lake for hundreds or even thousands of years. It has become a common ornamental stone in classical Chinese gardens because of its porous and intricate forms. At the same time, it has become a cultural symbol through thousands of years of history in China; later, people researched its spatial aesthetics; there are also some studies on its structural properties. For example, it has been found that the opening of Taihu stone caves has a steady-state effect which people develop its value in the theory of Poros City, Porosity in Architecture and some cultural symbols based on the original ornamental value of Taihu stone. This paper introduces a hybrid generative design method that integrates the Computational Fluid Dynamics (CFD) and Bi-directional Evolutionary Structural Optimization (BESO) techniques. Computational Fluid Dynamics (CFD) simulation enables architects and engineers to predict and optimise the performance of buildings and environment in the early stage of the design and topology optimisation techniques BESO has been widely used in structural design to evolve a structure from the full design domain towards an optimum by gradually removing inefficient material and adding materials simultaneously. This research aims to design the artificial Taihu stone based on the environmental data-driven performance feedback using the topological optimisation method. As traditional and historical ornament craftwork in China, the new artificial Taihu stone stimulates thinking about the new value and unique significance of the cultural symbol of Taihu stone in modern society. It proposes possibilities and reflections on exploring the related fields of Porosity in Architecture and Poros City from the perspective of structure.

<em>Abstract</em>.—Most artificial reef deployments to date have been directed toward fish assemblage enhancement, with only a few that are fisheries- or species-specific. The ostensible rationale for this approach is that when the artificial reef fish assemblage increases in a given area, the component target species will also increase. This premise also implies that the target species is characteristically reef- or structure-associated. Targeted species may not be niche-specific with regard to their association with reef attributes; however, trophic groups may be niche generalists for a suite of reef attributes. Artificial reef designs could be directed toward trophic groups and not individual species or the entire assemblage. This would allow more efficient optimization of artificial reef designs directed toward generalized life history features common among species within a trophic group. The delineation of species according to reef niche should include attributes based on trophic features that will allow optimal management through trophic-group-oriented artificial reef deployments. If successful, trophic groups within an assemblage could be more efficiently managed to allow the full integration of artificial reefs into fisheries management on a worldwide basis. Thus, the application of artificial reef design principles could become universal for targeted trophic groups.

Smoothing topology optimization results using pre-built lookup tables

Artificial reefs have been constructed and deployed worldwide to enhance marine habitat, primarily to increase socio-economic benefits stemming from associated fishing and diving activities, but also for habitat restoration and mitigation purposes. As a result, the majority of studies focused on artificial reefs to date have centered on measuring performance, with metrics such as species' richness and abundance compared to natural reefs, or economic benefits to local users. While there may be demonstrable benefits to artificial reef development, there may also be unforeseen consequences. This study investigates the impacts Florida artificial reefs may have on sea turtle populations, such as increased predation stemming from altered predator complexes, mortality due to entrapment, and entanglement issues. Based on some of the associated effects artificial reef development may have on sea turtles, management recommendations to minimize potential impacts are offered for consideration.

The purpose of this study was to develop a new element removal method for ESO (Evolutionary Structural Optimization), which is one of the topology optimization methods, ESO starts with the maximum allowable design space and the optimal topology emerges by a process of removal of lowly stressed elements. The element removal ratio of ESO is fixed throughout topology optimization at 1 or 2%. BESO (bidirectional ESO) starts with either the least number of elements connecting the loads to the supports, or an initial design domain that fits within the maximum allowable domain, and the optimal topology evolves by adding or subtracting elements. But the convergence rate of BESO is also very slow. In this paper, a new element removal method for ESO was developed for improvement of the convergence rate. Then it was applied to the same problems as those in papers published previously. From the results, it was verified that the convergence rate was significantly improved compared with ESO as well as BESO.

In recent years, with the scale and standardization of Stichopus japonicus mariculture, artificial reefs are increasingly used in S. japonicus farming to promote the development of the S. japonicus aquaculture industry. To provide shelter and improve the habitat environment for S. japonicus, three types of artificial reefs (box-shaped reef, triangular-shaped reef, and trapezoidal-shaped reef) were designed according to the ecological habitats of S. japonicus and the marine environment of Haizhou Bay (China) in the present study. After comprehensively comparing the three reef structures, we found that the trapezoidal-shaped reef has good permeability, a larger attachment area, and excellent anti-slip and anti-overturning properties. Further, the flow field characteristics surrounding a trapezoidal-shaped reef at different angles and flow velocities are investigated by three-dimensional numerical simulations. Then, the impact of the placement distance on the flow field surrounding the artificial reef combination was investigated. At the head-on angle θ = 0°, the upwelling volume increases as the flow velocity increases and then decreases, and the back eddy volume remains relatively constant. At the longitudinal spacing D = 4 L, the large slow-flow area surrounding the reef under this condition is more suitable for the S. japonicus habitat. In this study, the trapezoidal-shaped reef design is suitable and beneficial for S. japonicus aquaculture. Moreover, this study will contribute theoretical references to the design and arrangement of artificial reefs in coastal areas.

Electro-thermal-compliant mechanisms are mechanisms onto which electric voltage is applied as input. This mechanism is based on the thermal expansion properties of the materials. This study considered all of the convection effects according to layouts produced after each topology optimization process. A new material mixing method based on bi-directional evolutionary structural optimization (BESO) was suggested to obtain optimal topologies for compliant mechanisms composed of two materials. Reliability-based topology optimization (RBTO) based on BESO was also applied to the topology optimizations of the mechanisms. Performance measurement approach (PMA), which estimates has probabilistic constraints that are formulated in terms of the reliability index, was adopted to evaluate the probabilistic constraints. The procedure has been tested in numerical applications, and the results were compared with those obtained by the level set and solid isotropic material with penalization (SIMP) methods for validation of the proposed approaches.

A geometrically nonlinear topology optimization method is presented in this paper for steel I-section beams, incorporating large displacement analysis to capture realistic structural behavior under flexural loads. The developed framework aims to enhance structural performance and material efficiency by optimizing the web region while preserving critical load paths. The optimization process is driven by enhancing the Bi-directional Evolutionary Structural Optimization (BESO) algorithm implemented in MATLAB and coupled with ABAQUS. Three beam configurations are analyzed under identical boundary and loading conditions to compare the performance of the optimized layout against traditional designs. To further assess the robustness of the proposed algorithm, two additional load scenarios, including a four-point bending test and a uniformly distributed load, are investigated. The results demonstrate that the optimized beam configurations reduce web material by 60 % (volume fraction = 0.40) under 45 kN mid-span load while sustaining 55 % higher load than the circular-opening beam (45 kN vs. 29 kN) with mean stress of 203.1 MPa, achieving 20 % less web material than the conventional design and 18 % higher complementary work (1.89 × 10⁵ N·mm) than the plain-web beam. The findings underline the value of incorporating geometric nonlinearity into topology optimization for producing high-performance, lightweight steel structures suitable for real-world engineering applications.

With the rapid development of computers and technology in the 20th century, the topological optimisation (TO) method has spread worldwide in various fields.This novel structural optimisation approach has been applied in many disciplines, including architectural form-finding.Especially Bi-directional Evolutionary Structural Optimisation (BESO), which was proposed in the 1990s, is widely used by thousands of engineers and architects worldwide to design innovative and iconic buildings.To integrate topological optimisation with artificial intelligence (AI) algorithms and to leverage its power to improve the diversity and efficiency of the BESO topological optimisation method, this research explores a non-iterative approach to accelerate the topology optimisation process of structures in architectural form-finding via conditional generative adversarial networks (GANs), which is named as OptiGAN.Trained with topological optimisation results generated through Ameba software, OptiGAN is able to predict a wide range of optimised architectural and structural designs under defined conditions.

A new topology optimization scheme based on a Harmony search (HS) as a metaheuristic method was proposed and applied to static stiffness topology optimization problems. To apply the HS to topology optimization, the variables in HS were transformed to those in topology optimization. Compliance was used as an objective function, and harmony memory was defined as the set of the optimized topology. Also, a parametric study for Harmony memory considering rate (HMCR), Pitch adjusting rate (PAR), and Bandwidth (BW) was performed to find the appropriate range for topology optimization. Various techniques were employed such as a filtering scheme, simple average scheme and harmony rate. To provide a robust optimized topology, the concept of the harmony rate update rule was also implemented. Numerical examples are provided to verify the effectiveness of the HS by comparing the optimal layouts of the HS with those of Bidirectional evolutionary structural optimization (BESO) and Artificial bee colony algorithm (ABCA). The following conclusions could be made: (1) The proposed topology scheme is very effective for static stiffness topology optimization problems in terms of stability, robustness and convergence rate. (2) The suggested method provides a symmetric optimized topology despite the fact that the HS is a stochastic method like the ABCA. (3) The proposed scheme is applicable and practical in manufacturing since it produces a solid-void design of the optimized topology. (4) The suggested method appears to be very effective for large scale problems like topology optimization.

Detail control strategies for topology optimization in architectural design and development

A 2-year study was conducted in Hong Kong to examine the effects of substratum, season and length of submersion on the development of a subtidal epibiotic community using four types of settlement panels (concrete, steel, wood and tyre). The season and length of submersion had a strong influence on the total biomass and on community structure while the type of substratum had very little impact on the total biomass or the structure of the epibiotic community. The season of submersion determined the species composition of the newly submerged surfaces. In the spring and summer, tubeworms were the most abundant. In the autumn and winter, barnacles and tunicates dominated. Community succession was not obvious in the first year of submersion as it was intermingled with strong seasonal settlement, growth and death of barnacles and tunicates. In the second year of submersion, green mussels and tunicates settled and grew to occupy most of the panel surfaces, forming an assemblage that was characteristic of climax communities in the local subtidal waters. The results suggest that the type of construction material has limited impact on the development of epibiotic communities on artificial reefs deployed in Hong Kong; the season of submersion may affect community structure in the early successional stage, but not the characteristics of the climax communities. This study indicates that the type of substratum should not be of concern when deploying artificial reefs in the subtidal waters in this region. The design of artificial reefs should focus more on other physical and economical aspects such as durability, flow dynamics, stability, cost, and effects on the ambient environment.

Stress-based topology optimization and nonlinear structural topology optimization is gaining increasing attention in order to make topology optimization more realistic. Thus, this paper extends current concepts of topology optimization to the design of structures made of nonlinear materials. An extended bi-directional evolutionary structural optimization (BESO) method for stress minimization topology optimization of material nonlinear structures is proposed in this work. BESO method based on discrete variables can effectively avoid the well-known singularity problem in density-based methods with low-density elements. The maximum von Mises stress is approximated by the p-norm global stress. The sensitivity information for designing variable updates is derived in detail by adjoint method. As for the highly nonlinear stress behavior, the updated scheme takes advantages from two filters respectively of the sensitivity and topological variables to improve convergence. Moreover, the filtered sensitivity numbers are combined with their historical sensitivity information to further stabilize the optimization process. The effectiveness of the proposed method is demonstrated by several 2D benchmark design problems.

The topology optimization method has been widely applied study the optimization of the dynamic behavior of multiphysics systems, such as systems with fluid-structure interaction, in order to produce efficient and reliable designs. Within this context, this work aims to contribute to the study of the topology optimization of these coupled systems through the optimization of a fluid-structure system subject to a structural volume constraint, by maximizing the natural frequency of the system considering interpolations of the material domains. To this end, the methodology involves the application of algorithms developed in fluid-structure systems with a nonsymmetrical matrix formulation, in displacement u of the structure and pressure p of the fluid, with movable boundary interface. Topology optimization is developed using the BESO (Bi-Directional Evolutionary Structural Optimization) method and implemented in a numerical computing environment, while finite element analysis is performed using a parametric programming language to customize simulations in FEM software. The results obtained demonstrate the applicability of the codes developed for natural frequency optimization problems in fluid-structure coupled systems, using different material interpolations, and the influence of the participation of fluid terms and left eigenvectors in the sensitivity analysis, highlighting that interpolation using the SIMP method showed convergence with consistent final topologies.