Freeform Structures Research Articles

Multi-objective optimization of assembly free-form cable-stiffened reticulated shell considering the influence of initial states

In this study, we propose a geometric model of free-form grid structures based on the sliding translation method. Furthermore, an end-flattened inserted-plate joint could be applied to a quadrilateral free-form grid structure. The height of the control point was considered as the optimization variable, while the strain energy, geometric integrated index, and ultimate bearing capacity were considered as the optimization objectives. The results demonstrated the influence of the initial prestress and joint stiffness using multi-objective optimization. Based on the effects of the initial prestress, joint stiffness, and initial geometric imperfections, we propose a multi-objective optimization method for the assembly of a free-form cable-stiffened reticulated shell. The feasibility of the optimization method was verified using examples. Compared with the results of the shape optimization, structures having superior mechanical properties and mesh quality were obtained via the combined method for optimizing the shape and initial prestress, which verified the necessity and effectiveness of the combined optimization method. The mechanical properties of the optimized structures were improved by increasing the joint stiffness; in particular, the ultimate bearing capacity was improved. On using the multi-objective optimization method while considering the initial geometric imperfections, the properties of the structure were improved effectively, and the mechanical properties can be guaranteed even after geometric imperfections are applied.

Glass Fibre Reinforced Concrete (GFRC) Materials and Its Applications

In the 1940’s, potential of glass as a construction material was realized and improvement continued with the addition of zirconium dioxide in 1960's for harsh alkali conditions. The development of new glass fibre generations is focused on improving the process of material durability. In order to meet various needs, glass fibre reinforced concrete, or GFRC, was thus introduced into production. Research and experiments conducted on GFRC have demonstrated that the material quality and production precision have an impact on the material's mechanical and physical characteristics. GFRC can be applied anywhere an impermeable, weather-resistant, fire-resistant, light-weight, and robust material is required. With the development of technology, it may be possible to construct sophisticated freeform structures and entire buildings at a reasonable cost. Recently, research has been done on the impact of glass fibres in hybrid mixtures for high-performance concrete (HPC), a newly developed technology that is gaining popularity in the building sector.

Geometric deep learning for statics-aware grid shells

This paper introduces a novel method for shape optimization and form-finding of free-form, triangular grid shells, based on geometric deep learning. We define an architecture which consumes a 3D mesh representing the initial design of a free-form grid shell, and outputs vertex displacements to get an optimized grid shell that minimizes structural compliance, while preserving design intent. The main ingredients of the architecture are layers that produce deep vertex embeddings from geometric input features, and a differentiable loss implementing structural analysis. We evaluate the method performance on a benchmark of eighteen free-form grid shell structures characterized by various size, geometry, and tessellation. Our results demonstrate that our approach can solve the shape optimization and form finding problem for a diverse range of structures, more effectively and efficiently than existing common tools.

A generative design method based on spline scanning for additive manufacturing

While additive manufacturing (AM) provides design flexibility, challenges persist in handling intricate freeform shapes, especially those laden with fine details. Conventional AM processes, such as slicing stereolithography (STL) format models, generating line segment toolpaths, and polyline-based printing, prove costly and compromise accuracy. This paper proposes a solution: the spline scanning generative design method. Utilizing spline patterns to construct smooth toolpaths directly, it enables seamless curved printing, significantly reducing computational expenses while maintaining high accuracy through spline control points. Experimental implementation, supported by dedicated algorithms, attests to its efficacy, emphasizing its potential for intricate freeform structure design and printing.

Geometric characteristics, deployment mechanisms, and digital fabrication methods of a free-form deployable membrane system based on CNC-knitted fabrics and CNC-bent frames

ABSTRACT Deployable membrane structures have played a vital role in creating flexible and adaptable urban and architectural spaces. However, the geometries of deployable membrane structures are often confined to symmetrical and regular shapes, due to the complex interdependencies between structure, material, motion, and geometry. To overcome this challenge, this research proposes a new category of deployable membrane structures that enables a broad range of deployment geometries, including free forms. The proposed system facilitates the transformation of arbitrary free-form surfaces into structural models, simplifies kinematic analysis for free-form deployment, and reduces structural calculations for free-form deployable structures. This study systematically investigated the proposed deployable membrane system in terms of geometric characteristics, deployment mechanisms, and digital manufacturing methods, including investigations of the generation method and geometric categories, summarizations of the folding mode and foldability conditions, and explorations of the CNC manufacturing logic and the G-code generation method. Finally, a full-scale physical prototype is studied to validate the proposed system and related methods.

Antireflective Multi‐Dielectric Metasurfaces Operating in the Visible

AbstractAs increasingly more demanding photonics applications are brought on‐chip, more complex design solutions are employed to deliver enhanced performance: e.g., meta‐molecules, inverse‐designed freeform structures, and multilayer metasurfaces. Instead, this study introduces anti‐reflective metasurfaces fabricated in a single nanolithography step that follows deposition of multiple dielectrics onto a substrate. Anti‐reflective metasurfaces offer fundamentally better transmission efficiencies compared to conventional equivalents. Conventional and anti‐reflective metalenses, both fabricated in the Ta2O5/SiO2 material platform for 461 nm operation, show an improvement in focusing efficiencies from ≈ 55% to ≈ 90% at low numerical apertures and from ≈ 35% to ≈ 65% at high numerical apertures. Simulations of ideal and imperfect metalenses indicate that anti‐reflective metasurfaces not only improve transmission at the design library level, but also reduce spurious diffraction and protect against higher‐order scattering.

Repurposing existing skeletal spatial structure (SkS) system designs using the Field Information Modeling (FIM) framework for generative decision-support in future construction projects

Skeletal spatial structure (SkS) systems are modular systems which have shown promise to support mass customization, and sustainability in construction. SkS have been used extensively in the reconstruction efforts since World War II, particularly to build geometrically flexible and free-form structures. By employing advanced digital engineering and construction practices, the existing SkS designs may be repurposed to generate new optimal designs that satisfy current construction demands of contemporary societies. To this end, this study investigated the application of point cloud processing using the Field Information Modeling (FIM) framework for the digital documentation and generative redesign of existing SkS systems. Three new algorithms were proposed to (i) expand FIM to include generative decision-support; (ii) generate as-built building information modeling (BIM) for SkS; and (iii) modularize SkS designs with repeating patterns for optimal production and supply chain management. These algorithms incorporated a host of new AI-inspired methods, including support vector machine (SVM) for decision support; Bayesian optimization for neighborhood definition; Bayesian Gaussian mixture clustering for modularization; and Monte Carlo stochastic multi-criteria decision making (MCDM) for selection of the top Pareto front solutions obtained by the non-dominant sorting Genetic Algorithm (NSGA II). The algorithms were tested and validated on four real-world point cloud datasets to solve two generative modeling problems, namely, engineering design optimization and facility location optimization. It was observed that the proposed Bayesian neighborhood definition outperformed particle swarm and uniform sampling by 34% and 27%, respectively. The proposed SVM-based linear feature detection outperformed k-means and spectral clustering by 56% and 9%, respectively. Finally, the NSGA II algorithm combined with the stochastic MCDM produced diverse “top four” solutions based on project-specific criteria. The results indicate promise for future utilization of the framework to produce training datasets for generative adversarial networks that generate new designs based only on stakeholder requirements.

Exploring the three-dimensional space with modular concrete shells: Form-finding, design and structural analysis

Thin concrete shells can span large distances thanks to their structural efficiency, following the optimum force flow. Despite the efficient use of material of well-designed shells, their construction suffers from labor-intensive and time-consuming fabrication techniques. This research therefore proposes a design method for the facilitated manufacturing of freeform shell structures. The manufacturing process has been considered from the design phase on, by generating an extensive range of different shell configurations based on a limited set of form-found modules and thus formworks. The challenge was to define which curved module geometries, after assembly, lead to the largest variety of freeform surfaces. More than sixty configurations resulted from a set of four modules only. This paper will discuss the form-finding process as well as the geometrical arrangement using tessellation patterns for the achievement of those modular configurations, going from domed to undulating shell shapes. In order to evaluate the structural efficiency of the shapes, twenty modular configurations were selected and analyzed under self-weight, using finite element simulations. To conclude, a prototype of one modular base element has been built, using a reusable casting wax in combination with a grid shell box, as the main parts of the formwork. The results demonstrate the structural feasibility and limitations of the modular shell design strategy. The modular approach contributes to circularity by encouraging reuse and allowing various combinations with a repeating set of modules, striving as such towards resource-effective innovative shell structures.

Rheological modeling of frontal-polymerization-based direct ink writing of thermoset polymers

Ensuring a high degree of dimensional accuracy of the printed part is critical in the development of additive manufacturing techniques. The advent of computational tools to simulate additive manufacturing has provided a robust way to predict part quality during the entire process. In this paper, a multiphysics model is introduced for the novel additive manufacturing technique of frontal polymerization-based direct ink writing, which enables rapid printing of complex free-form thermoset polymeric structures with excellent strength and stiffness. In direct ink writing, the fluid should possess suitable yield stress behavior to be successfully extruded and cured, and swelling of the fluid upon extrusion impacts the dimension of the printed filament. This model describes the thermo-chemo-rheological behavior of the printing gel during extrusion and polymerization, based on experimental measurements of the nonlinear viscoelastic and cure kinetics behavior. This model is applied to the FP-based printing process by considering an Eulerian domain that follows the motion of the printer head. Simulation results are presented for the vertical printing of both cylindrical filaments and annular tubes. The effect of process parameters on the dimensional accuracy of the printed part and the position of the polymerization front downstream from the printer head are investigated under steady and unsteady print speeds. Measurements from printing experiments validate the accuracy of the model.

In Silico Design of Freeform Solar Cell Structures from High‐Throughput Artificial Intelligence‐Generated Configurations

In Silico Design of Freeform Solar Cell Structures from High‐Throughput Artificial Intelligence‐Generated Configurations

Inverse design and optical vortex manipulation for thin-film absorption enhancement

Abstract Optical vortices (OVs) have rapidly varying spatial phase and optical energy that circulates around points or lines of zero optical intensity. Manipulation of OVs offers innovative approaches for various fields, such as optical sensing, communication, and imaging. In this work, we demonstrate the correlation between OVs and absorption enhancement in two types of structures. First, we introduce a simple planar one-dimensional (1D) structure that manipulates OVs using two coherent light sources. The structure shows a maximum of 6.05-fold absorption gap depending on the presence of OVs. Even a slight difference in the incidence angle can influence the generation/annihilation of OVs, which implies the high sensitivity of angular light detection. Second, we apply inverse design to optimize two-dimensional (2D) perfect ultrathin absorbers. The optimized free-form structure achieves 99.90 % absorptance, and the fabricable grating structure achieves 97.85 % at 775 nm wavelength. To evaluate OV fields and their contribution to achieving absorption enhancement, we introduce a new parameter, OV circularity. The optimized structures generate numerous OVs with a maximum circularity of 95.37 % (free-form) and 96.14 % (grating), superior to our 1D structure. Our study reveals the role of high-circularity localized OVs in optimizing nano-structured absorbers and devices for optical sensing, optical communication, and many other applications.

Reducing the Number of Different Faces in Free-Form Surface Approximations Through Clustering and Optimization

Free-form structures are highly valued for their aesthetic appeal in architecture, but they typically comprise panels of many different shapes, which can pose great challenges for building construction. In this study, we aim to address this issue by proposing a novel clustering–optimization method to reduce the number of different n-gonal faces in free-form surface approximations. The method partitions the faces into several groups of similar shapes through clustering and transforms the ones within each group toward congruent forms through optimization. By utilizing this approach, the number of geometrically different panels can be reduced while also satisfying a user-specified error threshold. The potential practical application of this method is demonstrated by redesigning the façade of a real architectural project to achieve cost-effective solutions.

The influence of inelastic materials on freeform kerf structures

Kerfing or relief cutting is a fabrication approach to create moldable surfaces out of wood and metal panels. The kerf panels with pre-defined microstructural topology enable the creation of freeform kerf structures of complex geometries, which found many applications in building constructions. This study investigates the influence of inelastic materials, i.e., plastic deformation of stainless steel and viscoelastic wood, and microstructural topology on the overall moldability of kerf panels. Kerf unit cells fabricated from stainless steel (SS) and medium-density fiber (MDF) with different cut patterns, cut densities, and cell sizes are first studied. Experimental tests and mathematical models are used to examine the deformations of the kerf unit cells. Kerf panels of various microstructural topology, which depends on the cut patterns, cut densities, cell sizes, and cell arrangements, are then modeled to create freeform shapes. The effect of inelastic deformations, i.e., shape reconfiguration due to creep of MDF and utilizing inelastic deformations of SS to form the freeform shapes, are studied. When only an elastic deformation is considered, increasing the flexibility in kerf panels by increasing cut densities enables easy shape configurations. However, when a plastic deformation is utilized to form the shape, flexible kerf structures are less effective due to the relatively small stresses in the flexible SS kerf structures to induce plastic deformations. Flexible MDF kerf structures can experience significant creep deformations, inducing nonnegligible shape reconfigurations. To avoid shape reconfigurations due to the creep effect when using viscoelastic wood, one approach is to consider developable surfaces.

Textile reinforced concrete members subjected to tension, bending, and in-plane loads: Experimental study and numerical analyses

Textile reinforced concrete has raised increasing research interest during the last years, mainly due to its potential to be used for freeform shell structures involving complex load situations. Yet, most experimental work has focused on test setups with primarily uniaxial loading. In the current work, such setups are complemented with a novel test setup of deep beams, including in-plane bending and shear. Further, nonlinear finite element analyses were carried out, applying an earlier calibrated bond-slip relation and efficiency factors for strength and stiffness of the textile reinforcement. It was found that the structural behaviour in terms of the overall stiffness, ultimate load and deformation, number of cracks, and total (summed) crack width, could be described with reasonably good accuracy. The inclusion of a calibrated efficiency factor for the stiffness of the yarn was shown to be vital. Moreover, it was shown to be important to weaken and randomise the material properties of the concrete at the location of transverse yarns, to trigger localisation (cracking) in the numerical model.

Small-size LD-based automobile headlamp design with long illumination distance and wide illumination range.

Due to the large size of an automobile headlamp that has a laser as the light source, it is difficult to reflect the advantages of high laser brightness into the effect of automobile illumination, so it has not been promoted. We propose a laser headlamp system that integrates low-beam and high-beam structures with superior illumination effects (longer illumination distance and wider illumination range) by designing freeform optical components and optical structure. The small-volume headlamp can meet the requirements of the Economic Commission for Europe regulation (ECE) R112. The structure volume of the headlamp proposed in this study is only 100∗70∗70m m 3, and the maximum luminance is 120lx (simulation result) and 78.5lx (test result). The view angle of the low beam is 13.6°, and the high beam is 15.6°, indicating that the solution is suitable for automotive illumination.

Dragging 3D printing technique controls pore sizes of tissue engineered blood vessels to induce spontaneous cellular assembly

To date, several off-the-shelf products such as artificial blood vessel grafts have been reported and clinically tested for small diameter vessel (SDV) replacement. However, conventional artificial blood vessel grafts lack endothelium and, thus, are not ideal for SDV transplantation as they can cause thrombosis. In addition, a successful artificial blood vessel graft for SDV must have sufficient mechanical properties to withstand various external stresses. Here, we developed a spontaneous cellular assembly SDV (S-SDV) that develops without additional intervention. By improving the dragging 3D printing technique, SDV constructs with free-form, multilayers and controllable pore size can be fabricated at once. Then, The S-SDV filled in the natural polymer bioink containing human umbilical vein endothelial cells (HUVECs) and human aorta smooth muscle cells (HAoSMCs). The endothelium can be induced by migration and self-assembly of endothelial cells through pores of the SDV construct. The antiplatelet adhesion of the formed endothelium on the luminal surface was also confirmed. In addition, this S-SDV had sufficient mechanical properties (burst pressure, suture retention, leakage test) for transplantation. We believe that the S-SDV could address the challenges of conventional SDVs: notably, endothelial formation and mechanical properties. In particular, the S-SDV can be designed simply as a free-form structure with a desired pore size. Since endothelial formation through the pore is easy even in free-form constructs, it is expected to be useful for endothelial formation in vascular structures with branch or curve shapes, and in other tubular tissues such as the esophagus.

Computational morphogenesis of three-dimensional free-form structures using isosurfaces based on space mapping

This paper presented a novel computational morphogenesis method based on space mapping that employed isosurfaces to generate three-dimensional free-form continuum structures from design domains of arbitrary complexity. To achieve the interaction between form and performance, a mapping was established between the parameter space and the physical space of the design domain using B-spline volume modelling. Two assumptions were introduced to ensure that the entire parameter space has mechanical properties equivalent to those of the physical space. The isosurfaces of criterion thresholds were extracted from the entire parameter space and mapped into the physical space as the boundaries of the new design. The proposed methodology effectively addresses the limitations of the non-orthogonal body-fitted meshes for structural analysis. It comprehensively reflected the redistribution of mechanical performance and yielded an optimal design at the global-structural level. Furthermore, a geometric matrix was developed for the marching cubes algorithm, which streamlines the process of extracting isosurfaces. Numerical examples were presented to validate the method, demonstrating its ability to generate free-form structures with smooth boundaries, innovative shapes, and rational topology. The unexpected architectural form can provide valuable references for conceptual design in engineering applications.

Aesthetic Assessment of Free-Form Space Structures Using Machine Learning Based on the Expert’s Experiences

Parametric form findings of free-form space structures and qualitative assessment of their aesthetics are among the concerns of architects. This study aims to evaluate the aesthetic aspect of these structures using ML algorithms based on the expert’s experiences. First, various datasets of forms were produced using a parametric algorithm of free-form space structures written in Grasshopper. Then, three multilayer perceptron ANN models were adjusted in their most optimal modes using the results of the preference test based on the aesthetic criteria including simplicity, complexity, and practicality. The results indicate that the ANN models can quantitatively evaluate the aesthetic value of free-form space structures.

Isogeometric double-objective shape optimization of free-form surface structures with Kirchhoff–Love shell theory

Free-form surface structures are extensively utilized in practical engineering due to their rich architectural expression and strong visual impact. However, ensuring good mechanical behavior during the generation process of free-form surface structures has become a critical problem in the scientific community. Isogeometric analysis (IGA) is a widely adopted approach in various fields owing to its numerous advantages, such as geometric accuracy, high-order continuity, high precision, without traditional meshing, and ease of integration with CAD. The presented work adopts the NURBS surfaces to create geometric models, and developes an isogeometric discretization for free-form surfaces by formulating a shell analysis method based on Kirchhoff–Love hypothesis. The structural strain energy and the first natural frequency of the free-form surfaces are selected as the static and dynamic performance evaluation indices. The optimization objectives are to minimize the structural strain energy and maximize the first natural frequency, with the control point coordinates considered as the optimization variable. The double-objective shape optimization of the free-form surface structure is carried out using the particle swarm optimization technique. The effectiveness and performance of the proposed method are verified through five numerical examples, and the mechanical properties of the optimized structure are substantially improved.

In Silico Design of Freeform Solar Cell Structures from High‐Throughput Artificial Intelligence‐Generated Configurations

Recent advances in artificial intelligence‐generated configurations (AIGC) have transformed various fields in science and technology domains and enabled the inverse design of materials and structures for enhanced performance with minimal human input. The patterned micro‐/nanostructures are widely adopted to increase power conversion efficiencies in thin‐film organic solar cells (OSCs), making these structures highly suitable for AIGC applications. Although the computational cost of traditional numerical simulations is a barrier to making AIGC high throughput, this issue is addressed by integrating the high‐speed automated machine learning (AutoML) Analyzer with genetic algorithm‐based topology optimization algorithms. Compared to standard numerical solutions, the AutoML Analyzer in the proposed system predicts outcomes ≈22 700 times faster, resulting in a 98.47% reduction in computation costs, while maintaining high average accuracies of ≈99%. By evaluating an extensive dataset of 600 000 AIGCs, an optimized PM6:Y6 OSC device design with a power conversion efficiency of 17.58% is identified, significantly outperforming the 14.70% baseline efficiency of the OSC device without the poly methyl methacrylate scattering and substrate layers. Results underscore the potential of AIGC techniques for efficiently enhancing the performance of photovoltaic devices in renewable energy applications.