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1. Additive manufacturing of stiff and strong structures by leveraging printing-induced strength anisotropy in topology optimization

   https://doi.org/10.1016/j.addma.2023.103730  

   Kundu, Rahul Dev ; Zhang, Xiaojia Shelly ( August 2023 , Additive Manufacturing)

   Anisotropy in additive manufacturing (AM), particularly in the material extrusion process, plays a crucial role in determining the actual structural performance, including the stiffness and strength of the printed parts. Unless accounted for, anisotropy can compromise the objective performance of topology-optimized structures and allow premature failures for stress-sensitive design domains. This study harnesses process-induced anisotropy in material extrusion-based 3D printing to design and fabricate stiff, strong, and lightweight structures using a two-step framework. First, an AM-oriented anisotropic strength-based topology optimization formulation optimizes the structural geometry and infill orientations, while assuming both anisotropic (i.e., transversely isotropic) and isotropic infill types as candidate material phases. The dissimilar stiffness and strength interpolation schemes in the formulation allow for the optimized allocation of anisotropic and isotropic material phases in the design domain while satisfying their respective Tsai–Wu and von Mises stress constraints. Second, a suitable fabrication methodology realizes anisotropic and isotropic material phases with appropriate infill density, controlled print path (i.e., infill directions), and strong interfaces of dissimilar material phases. Experimental investigations show up to 37% improved stiffness and 100% improved strength per mass for the optimized and fabricated structures. The anisotropic strength-based optimization improves load-carrying capacity by simultaneous infill alignment along the stress paths and topological adaptation in response to high stress concentration. The adopted interface fabrication methodology strengthens comparatively weaker anisotropic joints with minimal additional material usage and multi-axial infill patterns. Furthermore, numerically predicted failure locations agree with experimental observations. The demonstrated framework is general and can potentially be adopted for other additive manufacturing processes that exhibit anisotropy, such as fiber composites. 

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2. Performative Porosity – adaptive infills for concrete parts

   BERNHARD, Mathias ; BOLHASSANI, Mohammad ; AKBARZADEH, Masoud ( October 2021 , International Association of Shell and Spatial Structures)

   This research investigates the design of structurally performant, lightweight architectural elements produced through concrete 3D printing (C3DP). Traditionally, concrete requires dense and sturdy formwork, whose production adds significantly to the total cost and results in massive and heavy parts after demolding. C3DP offers the unique opportunity to both eliminate the need for formwork and to create lighter parts by introducing internal voids and cavities. The advent of additive manufacturing in a broad range of scales, materials, industries, and applications, led to increased interest and intense research into different types of porous structures, their geometry, and structural performance under various boundary conditions. Precise control over the sparse distribution of material allows not only for parts with similar strength at reduced mass but even for modifications of mechanical properties, like turning brittle materials into elastic or shock-absorbent ones. While with powder-based additive manufacturing processes like metal 3D printing, truss-based lattices have become very popular for the light-weighting of parts or to provide tissue growth scaffolds for medical implants, their geometry – a sparse space frame resulting in numerous individual contour islands and accentuated overhangs – cannot as easily be produced by C3DP, which is based on a continuous material extrusion. Alternative types of micro-structures, so-called triply periodic minimal surfaces (TPMS), are better suited for this process as they are, as their name suggests, consisting of one continuous surface dividing space into two separate but interwoven subspaces. TPMS are therefore very popular for the efficient design of heat exchangers. We develop and present a continuous and integrated workflow, in which the architectural elements and their structural requirements are designed through transitioning back and forth between the force and the form diagram using 3D graphic statics [1]. The members and their topology from the abstract graph of the conceptual form diagram are seamlessly connected to the volumetric modeling (VM) framework, responsible for the definition of the part geometry [2]. VM represents form assigned distance functions (SDF) and can easily handle complex topologies and flawless Boolean operations of not only the outer shell geometry but also the internal micro-structural infill patterns (Fig. 1, a). In an iterative feedback loop, the infill can be further optimized to leave the material only along certain internal stress trajectories (force flows). This functional grading controlling the relative density is done based on the FE analysis results. The stress distribution is thereby defined as a three-dimensional field (Fig. 1, b). Its values can factor into the SDF equation and be used to modify the wavelength (periodicity) of the TPMS, the local thickness of the surface shell, the solid to void fraction by shifting the threshold iso-value or even the alignment and orientation of the unit cells (Fig. 1, c). They can be arranged in an orthogonal, polar- or even spherical coordinate system to optimally adapt to structural necessities. The TPMS pattern can also gradually transition from one type into another type along the gradient of a spatial function. 

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3. 3D Printing of a Biocompatible Double Network Elastomer with Digital Control of Mechanical Properties

   https://doi.org/10.1002/adfm.201910391  

   Wang, Pengrui ; Berry, David B. ; Song, Zhaoqiang ; Kiratitanaporn, Wisarut ; Schimelman, Jacob ; Moran, Amy ; He, Frank ; Xi, Brian ; Cai, Shengqiang ; Chen, Shaochen ( February 2020 , Advanced Functional Materials)

   The majority of 3D‐printed biodegradable biomaterials are brittle, limiting their application to compliant tissues. Poly(glycerol sebacate) acrylate (PGSA) is a synthetic biocompatible elastomer and compatible with light‐based 3D printing. In this article, digital‐light‐processing (DLP)‐based 3D printing is employed to create a complex PGSA network structure. Nature‐inspired double network (DN) structures consisting of interconnected segments with different mechanical properties are printed from the same material in a single shot. Such capability has not been demonstrated by any other fabrication techniques so far. The biocompatibility of PGSA is confirmed via cell‐viability analysis. Furthermore, a finite‐element analysis (FEA) model is used to predict the failure of the DN structure under uniaxial tension. FEA confirms that the DN structure absorbs 100% more energy before rupture by using the soft segments as sacrificial elements while the hard segments retain structural integrity. Using the FEA‐informed design, a new DN structure is printed and tensile test results agree with the simulation. This article demonstrates how geometrically‐optimized material design can be easily and rapidly constructed by DLP‐based 3D printing, where well‐defined patterns of different stiffnesses can be simultaneously formed using the same elastic biomaterial, and overall mechanical properties can be specifically optimized for different biomedical applications.

    

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4. Multi-Objective Optimization of Predicted Magnetic Properties From Multifield Processing Conditions in Polymer Matrix Particle Composites

   https://doi.org/10.1115/SMASIS2022-91175  

   Widdowson, Denise ; Erol, Anil ; Papula, Dashiell ; Ounaies, Zoubeida ; von Lockette, Paris ( September 2022 , Proceedings of the ASME 2022 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. ASME 2022 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. Dearborn, Michigan, USA. September 12–14, 2022. V001T02A008. ASME.)

   Additive manufacturing, no longer reserved exclusively for prototyping components, can create parts with complex geometries and locally tailored properties. For example, multiple homogenous material sources can be used in different regions of a print or be mixed during printing to define properties locally. Additionally, heterogeneous composites provide an opportunity for another level of tuning properties through processing. For example, within particulate-filled polymer matrix composites before curing, the presence of an applied electric and/or magnetic fields can reorient filler particles and form hierarchical structures depending on the fields applied. Control of particle organization is important because effective material properties are highly dependent on the distribution of filler material within composites once cured. While previous work in homogenization and effective medium theories have determined properties based upon ideal analytic distributions of particle orientations and spatial location, this work expands upon these methods generating discrete distributions from quasi-Monte Carlo simulations of the electromagnetic processing event. Results of simulations provide predicted microarchitectures from which effective properties are determined via computational homogenization.

   These particle dynamics simulations account for dielectric and magnetic forces and torques in addition to hydrodynamic forces and hard particle separation. As such, the distributions generated are processing field dependent. The effective properties for a composite represented by this distribution are determined via computational homogenization using finite element analysis (FEA). This provides a path from constituents, through processing parameters to effective material properties. In this work, we use these simulations in conjunction with a multi-objective optimization scheme to resolve the relationships between processing conditions and effective properties, to inform field-assisted additive manufacturing processes.

   The constituent set providing the largest range of properties can be found using optimization techniques applied to the aforementioned simulation framework. This key information provides a recipe for tailoring properties for additive manufacturing design and production. For example, our simulation results show that stiffness for a 10% filler volume fraction can increase by 34% when aligned by an electric field as compared to a randomly distributed composite. The stiffness of this aligned sample is also 29% higher in the direction of the alignment than perpendicular to it, which only differs by 5% from the random case [1]. Understanding this behavior and accurately predicting composite properties is key to producing field processed composites and prints. Material property predictions compare favorably to effective medium theory and experimentation with trends in elastic and magnetic effective properties demonstrating the same anisotropic behavior as a result of applied field processing. This work will address the high computational expense of physics simulation based objective functions by using efficient algorithms and data structures. We will present an optimization framework using nested gradient searches for micro barium hexaferrite particles in a PDMS matrix, optimizing on composite magnetization to determine the volume fraction of filler that will provide the largest range of properties by varying the applied electric and magnetic fields.

    

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5. Mechanical behavior of bio‐inspired composites made of co‐continuous geopolymer and 3D‐printed polymer

   https://doi.org/10.1002/appl.202300097  

   Pang, Siyuan ; Mahrous, Mahmoud A. ; Trindade, Ana Carolina Constancio ; Kozych, Andrij ; Kale, Nupur ; Kriven, Waltraud M. ; Jasiuk, Iwona ( March 2024 , Applied Research)

   Geopolymers (GPs) are emerging, low‐density ceramic materials that are simple to manufacture, with high elastic modulus and strength, albeit with low toughness. Fiber reinforcements have been used to achieve varied ductile behaviors, but little is known about the GP addition to polymeric frame structures. Thus, drawing inspiration from the nanostructure of bones, this paper investigated an interpenetrating, co‐continuous composite consisting of a GP as the stiff but brittle phase, and a 3D‐printed polymer (PA12 White) as the soft and deformable phase. The composite mechanical properties and failure modes were studied experimentally using uniaxial compression and four‐point bending tests. The co‐continuous network constrained brittle cracking within the GP and reduced strain localization in the polymer. The results showed that the composite had higher strength (56.11 ± 2.12 MPa) and elastic modulus (6.08 ± 1.37 GPa) than the 3D‐printed polymer and had higher toughness (5.98 ± 0.24 MJ/mm³) than the GP for the specific geometries examined. The shape effect study demonstrated that cubic structures had higher elastic modulus and strength but at the expense of lower toughness when compared to rectangular prism structures. The study of scale effects indicated that increasing the number of periodic unit cells while maintaining consistent bulk dimensions led to augmented strength and toughness, albeit without statistically significant alterations in elastic modulus. Thus, this paper presents an experimental realization of a novel, bio‐inspired, interpenetrating, GP–polymer composite design, offering improved strength and toughness. It also provides valuable insights into the shape and size effects on the mechanical properties of this new composite.

    

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