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Fibrous porous media have a wide variety of applications in insulation, filtration, acoustics, sensing, and actuation. To design such materials, computational modeling methods are needed to engineer the properties systematically. There is a lack of efficient approaches to build and modify those complex structures in computers. The paper aims to discuss these issues.

In this paper, the authors generalize a previously developed periodic surface (PS) model so that the detailed shapes of fibers in porous media can be modeled. Because of its periodic and implicit nature, the generalized PS model is able to efficiently construct the three-dimensional representative volume element (RVE) of randomly distributed fibers. A physics-based empirical force field method is also developed to model the fiber bending and deformation.

Integrated with computational fluid dynamics (CFD) analysis tools, the proposed approach enables simulation-based design of fibrous porous media.

In the future, the authors will investigate robust approaches to export meshes of PS models directly to CFD simulation tools and develop geometric modeling methods for composite materials that include both fibers and resin.

The proposed geometric modeling method with implicit surfaces to represent fibers is unique in its capability of modeling bent and deformed fibers in a RVE and supporting design parameter-based modification for global configuration change for the purpose of macroscopic transport property analysis.

The purpose of this paper is to develop a general mathematic approach to model the microstructures of porous structures produced by additive manufacturing (AM), which will result in fractal surface topography and higher roughness that have greater influence on the performance of porous structures.

The overall shapes of pores were modeled by triply periodic minimal surface (TPMS), and the micro-roughness details attached to the overall pore shapes were represented by Weierstrass–Mandelbrot (W-M) fractal representation, which was integrated with TPMS along its normal vectors. An index roughly reflecting the irregularity of fractal TPMS was proposed, based on which the influence of the fractal parameters on the fractal TPMS was qualitatively analyzed. Two complex samples of real porous structures were given to demonstrate the feasibility of the model.

The fractal surface topography should not be neglected at a micro-scale level. In addition, a decrease in the fractal dimension D_s may exponentially make the topography rougher; an increase in the height-scaling parameter G may linearly increase the roughness; and the number of the superposed ridges has no distinct influence on the topography. Furthermore, the synthesis method is general for all implicit surfaces.

The method provides an alternative way to shift the posteriori design paradigm of porous media to priori design mode through numeric simulation. Therefore, the optimization of AM process parameters, as well as the porous structure, can be potentially realized according to specific functional requirement.

The synthesis of TPMS and W-M fractal geometry was accomplished efficiently and was general for all implicit freeform surfaces, and the influence of the fractal parameters on the fractal TPMS was analyzed more systematically.

This paper aims to clarify the relationship between mechanical behaviors and the underlying geometry of periodic cellular structures. Particularly, the answer to the following research question is investigated: Can seemingly different geometries of the repeating unit cells of periodic cellular structure result in similar functional behaviors? The study aims to cluster the geometry-functional behavior relationship into different categories.

Specifically, the effects of the geometry on the compressive deformation (mechanical behavior) responses of multiple standardized cubic periodic cellular structures (CPCS) at macro scales are investigated through both physical tests and finite element simulations of three-dimensional (3D) printed samples. Additionally, these multiple CPCS can be further nested into the shell of 3D models of various mechanical domain parts to demonstrate the influence of their geometries in practical applications.

The paper provides insights into how different CPCS (geometrically different unit cells) influence their compressive deformation behaviors. It suggests a standardized strategy for comparing mechanical behaviors of different CPCS.

This paper is the first work in the research domain to investigate if seemingly different geometries of the underlying unit cell can result in similar mechanical behaviors. It also fulfills the need to infill and lattify real functional parts with geometrically complex unit cells. Existing work mainly focused on simple shapes such as basic trusses or cubes with spherical holes.

Additive Manufacturing (AM) conventionally necessitates an intermediary slicing procedure using the standard tessellation language (STL) data, which can be computationally burdensome, especially for intricate microcellular architectures. This study aims to propose a direct slicing method tailored for digital light processing-type AM processes for the efficient generation of slicing data for microcellular structures.

The authors proposed a direct slicing method designed for microcellular structures, encompassing micro-lattice and triply periodic minimal surface (TPMS) structures. The sliced data of these structures were represented mathematically and then convert into 2D monochromatic images, bypassing the time-consuming slicing procedures required by 3D STL data. The efficiency of the proposed method was validated through data preparations for lattice-based nasopharyngeal swabs and TPMS-based ellipsoid components. Furthermore, its adaptability was highlighted by incorporating 2D images of additional features, eliminating the requirement for complex 3D Boolean operations.

The direct slicing method offered significant benefits upon implementation for microcellular structures. For lattice-based nasopharyngeal swabs, it reduced data size by a factor of 1/300 and data preparation time by a factor of 1/8. Similarly, for TPMS-based ellipsoid components, it reduced data size by a factor of 1/60 and preparation time by a factor of 1/16.

The direct slicing method allows for bypasses the computational burdens associated with traditional indirect slicing from 3D STL data, by directly translating complex cellular structures into 2D sliced images. This method not only reduces data volume and processing time significantly but also demonstrates the versatility of sliced data preparation by integrating supplementary features using 2D operations.

The three-dimensional porous scaffold is an important concept in tissue engineering and helps to restore or regenerate a damaged tissue. Additive manufacturing (AM) technology makes the production of custom-designed scaffolds possible. However, modeling scaffolds with intricate architecture and customized pore size and spatial distribution presents a challenge. This paper aims to achieve coupling control of pore size and spatial distribution in bone scaffolds for AM.

First, the proposed method assumes that pore size and spatial distribution have already been transformed from the requirements of scaffolds as inputs. Second, the structural characteristics of scaffolds are explicitly correlated with an all-hexahedron meshing method for scaffold design so that the average pore size could be controlled. Third, the highly coupled internal mesh vertices are adjusted based on a random strategy so that the pore size and spatial distribution conform to their respective desired values. Fourth, after the adjustment, the unit pore cell based on a triply periodic minimal surface was mapped into the hexahedrons through a shape function, thereby ensuring the interconnectivity of the porous scaffold.

The case studies of three bone scaffolds demonstrate that the proposed approach is feasible and effective to simultaneously control pore size and spatial distribution in porous scaffolds.

The proposed method may make it more flexible to design scaffolds with controllable internal pore architecture for AM.

In the control approach, the highly coupled mesh vertices are adjusted through a random strategy, which can determine the moving direction and range of a vertex dynamically and biasedly, thus ensuring the feasibility and efficiency of the proposed method.

This paper aims to propose the new two-step adaptive direct slicing method for building bio-scaffold with digital micro-mirror device (DMD)-based MPμSLA systems.

In this paper, the authors proposed a new approach to directly slice a scaffold’s CAD model (i.e the three-dimensional model built by computer-aided design platforms) and save the slices’ data as BMP (bitmap, i.e. the data format used in DMD) files instead of other types of two-dimensional patterns as an intermediary. The proposed two-step strategy in this paper, i.e. a CAD model’s exterior surface and internal architecture were sliced, respectively, at first, and then assembled together to obtain one intact slice. The assembly process is much easier and convenient based on the slice data in BMP format. To achieve the adaptive slicing for both the exterior part and internal part, two new indices, the exterior surface-dominated index and internal architecture-dominated index, are, respectively, utilized as the error estimation indices. The proposed approach in this paper is developed on SolidWorks platform, but it can also be implemented on other platforms.

The authors found that the approach is not only more accurate but also more efficient by avoiding the repeated running of those inefficient rasterization programs. The approach is able to save computer resource and time, and enhance the robustness of slicing program, as well as is appropriate for the scaffolds’ model with internal pore architecture and external free-form surface.

Bio-scaffolds in tissue engineering require precise control over material distribution, such as the porosity, connectivity, internal pore architecture and external free-form surface. The proposed two-step adaptive direct slicing approach is a good balance of slicing efficiency and accuracy and can be useful for slicing bio-scaffolds’ models.

This paper gives supports to build bio-scaffold with DMD-based MPμSLA systems.

The purpose of this paper is to describe a novel design method to construct lattice structure computational models composed of a set of unit cells including simple cubic, body-centered cubic, face-centered cubic, diamond cubic and octet cubic unit cell.

In this paper, the authors introduce a new implicit design algorithm based on the computation of volumetric distance field (VDF). All the geometric components including lattice core structure and outer skin are represented with VDFs in a given design domain. This enables computationally efficient design of a computational model for an arbitrarily complex lattice structure. In addition, the authors propose a hybrid method based on the VDF and parametric solid models to construct a conformal lattice structure, which is oriented in accordance with the geometric form of the exterior surface. This method enables the authors to design highly complex lattice structure, computational models, in a consistent design framework irrespective of the complexity in geometric representations without sacrificing accuracy and efficiency.

Experimental results are shown for a variety of geometries to validate the proposed design method along with illustrative several lattice structure prototypes built by additive manufacturing techniques.

This method enables the authors to design highly complex lattice structure, computational models, in a consistent design framework irrespective of the complexity in geometric representations without sacrificing accuracy and efficiency.

The purpose of this paper is to extend existing knowledge of 4D printing, in line with Khoo et al. (2015) who defined the production of 4D printing using a single material, and 4D printing of multiple materials. It is proposed that 4D printing can be achieved through the use of functionally graded materials (FGMs) that involve gradational mixing of materials and are produced using an additive manufacturing (AM) technique to achieve a single component.

The latest state-of-the-art literature was extensively reviewed, covering aspects of materials, processes, computer-aided design (CAD), applications and made recommendations for future work.

This paper clarifies that functionally graded additive manufacturing (FGAM) is defined as a single AM process that includes the gradational mixing of materials to fabricate freeform geometries with variable properties within one component. The paper also covers aspects of materials, processes, CAD, applications and makes recommendations for future work.

This paper examines the relationship between FGAM and 4D printing and defines FGAM as a single AM process involving gradational mixing of materials to fabricate freeform geometries with variable properties within one component. FGAM requires better computational tools for modelling, simulation and fabrication because current CAD systems are incapable of supporting the FGAM workflow.

It is also identified that other factors, such as strength, type of materials, etc., must be taken into account when selecting an appropriate process for FGAM. More research needs to be conducted on improving the performance of FGAM processes through extensive characterisation of FGMs to generate a comprehensive database and to develop a predictive model for proper process control. It is expected that future work will focus on both material characterisation as well as seamless FGAM control processes.

This paper examines the relationship between FGAM and 4D printing and defines FGAM as a single AM process that includes gradational mixing of materials to fabricate freeform geometries with variable properties within one component.

This paper aims to numerically investigate the impact of gas diffusion layer (GDL) anisotropic transport properties on the overall and local performance of polymer electrolyte fuel cells (PEFCs).

A three-dimensional numerical model of a polymer electrolyte fuel cell with a single straight channel has been developed to investigate the sensitivity of the fuel cell performance to the GDL anisotropic transport properties – gas permeability, diffusivity, thermal conductivity and electrical conductivity. Realistic experimentally estimated GDL transport properties were incorporated into the developed PEFC model, and a parametric study was performed to show the effect of these properties on fuel cell performance and the distribution of the key variables of current density and oxygen concentration within the cathode GDL.

The results showed that the anisotropy of the GDL must be captured to avoid overestimation/underestimation of the performance of the modelled fuel cell. The results also showed that the fuel cell performance and the distributions of current density and oxygen mass fraction within the cathode GDL are highly sensitive to the through-plane electrical conductivity of the GDL and, to a lesser extent, the through-plane diffusivity, and the thermal conductivity of the GDL. The fuel cell performance is almost insensitive to the gas permeability of the GDL.

This study improves the understanding of the importance of the GDL anisotropy in the modelling of fuel cells and provides useful insights on improving the efficiency of the fuel cells.

Realistic experimentally estimated GDL transport properties have been incorporated into the PEFC model for the first time, allowing for more accurate prediction of the PEFC performance.