Stiffness optimisation of sandwich structures with elastically isotropic lattice core

The sustainability of additive manufacturing (AM) has attracted attention nowadays, with different aspects needed to be considered. A key effort in this direction is the replacement of fossil fuel–originating polymers with biologically derived polymers. To achieve this, biologically derived polymers should exhibit a performance similar to that of commonly used polymers. Bacterially produced pure polyhydroxyalkanoate (PHA) was recently proposed by filament vendors for material extrusion (MEX) AM. Despite extensive research on the utilization of PHA in polymeric blends, the literature on the printability metrics of pure PHA is limited. At the same time, it has a high potential as an alternative to common petrochemical polymers. In this study, the impact of the main generic settings on the mechanical response of pure bio-sourced PHA in MEX AM was investigated. Four critical 3D printing parameters (print speed, layer height, nozzle temperature, and strand width) were evaluated using a robust design to optimize the tensile and impact metrics. Regression modeling was performed, and predictive equations were compiled and verified using validation testing. The quality of the samples was evaluated using electron microscopy. The analysis proved the importance of layer thickness in the tensile score, whereas nozzle temperature was found to be the most influential setting for impact loading. An increase of approximately 20% can be achieved by selecting appropriate 3D printing settings in the tensile test, whereas the impact strength can be radically improved by up to 550%.Graphical

We perform extensive molecular dynamics simulations of dense liquids composed of bidisperse dimer- and ellipse-shaped particles in two dimensions that interact via purely repulsive contact forces. We measure the structural relaxation times obtained from the long-time α decay of the self part of the intermediate scattering function for the translational and rotational degrees of freedom (DOF) as a function of packing fraction φ, temperature T, and aspect ratio α. We are able to collapse the packing-fraction and temperature-dependent structural relaxation times for disks, and dimers and ellipses over a wide range of α, onto a universal scaling function F(±)(|φ-φ(0)|,T,α), which is similar to that employed in previous studies of dense liquids composed of purely repulsive spherical particles in three dimensions. F(±) for both the translational and rotational DOF are characterized by the α-dependent scaling exponents μ and δ and packing fraction φ(0)(α) that signals the crossover in the scaling form F(±) from hard-particle dynamics to super-Arrhenius behavior for each aspect ratio. We find that the fragility of structural relaxation at φ(0), m(φ(0)), decreases monotonically with increasing aspect ratio for both ellipses and dimers. For α>α(p), where α(p) is the location of the peak in the packing fraction φ(J) at jamming onset, the rotational DOF are strongly coupled to the translational DOF, and the dynamic scaling exponents and φ(0) are similar for the rotational and translational DOF. For 1<α<α(p), the translational DOF become frozen at higher temperatures than the rotational DOF, and φ(0) for the rotational degrees of freedom increases above φ(J). Moreover, the results for the slow dynamics of dense liquids composed of dimer- and ellipse-shaped particles are qualitatively the same, despite the fact that zero-temperature static packings of dimers are isostatic, while static packings of ellipses are hypostatic. Thus, zero-temperature contact counting arguments do not apply to structural relaxation of dense liquids of anisotropic particles near the glass transition.

Digital manufacturing techniques, such as computer numerically controlled (CNC) machining and additive manufacturing (AM), have greatly increased the design space available to engineers with respect to both geometry and materials. Obviously, certain geometries cannot be realized by anything other than a layer-by-layer AM process, and certain materials can only be formed using traditional subtractive approaches, leaving designers with little choice. However, for the wide array of structures that could be realized in a variety of different ways, the choice of manufacturing process is just another faction in the overall design process. Planar lattice structures have complex repeating geometric features which are best designed using computer aided design (CAD) tools, and these structures can easily be manufactured using a variety of different digital manufacturing processes. For this study a set of planar lattice structures were designed and fabricated from acrylonitrile butadiene styrene (ABS) plastic using both a CNC milling machine and a material extrusion AM machine. All test lattices were then loaded in tension to failure to determine their mechanical performance. The determined properties were then compared to analytical predictions from the literature, and an analysis of the impact of a chosen manufacturing process was performed. The results obtained show good agreement with publish models for lattice performance, and additionally suggest that the choice of manufacturing process has a measurable effect on the mechanical performance of the resulting structures for this specific material and geometry combination, but it is important to note that this study is just an example of how to mitigate the uncertainties associated with the freedoms offered by advanced manufacturing processes, and more work in needed in this important area of study.

Lightweight design is often assumed to be the leading strategy to improve the sustainability of parts produced by additive manufacturing. The present study confutes such an assumption by a cradle-to-gate life cycle assessment of different lightweight strategies applied to a specific case study in the medical field. In particular, a patient-specific finger splint made of polyamide is redesigned by means of generative design, topology optimization and lattice structures. The analysis investigates two markedly different deposition processes, namely Arburg plastic freeforming and fused filament fabrication. The former is carried out on an industrial-grade machine, while a desktop printer is used for the latter. This allows for observing the impact of the redesign in two quite distinct scenarios. Findings demonstrate that, since environmental impacts are mainly driven by building time, the adoption of automated design algorithms can be detrimental to the sustainability of the process. On the other hand, relevant benefits on environmental impacts were achieved by reducing the infill percentage of parts. The results of this work highlight the most relevant aspects which must be considered to limit environmental impacts when designing parts for deposition-based additive manufacturing. This information can be used by designers to drive weight reduction towards sustainability.

Mechanical fasteners, such as bolted joints, are standard in many aerospace engineering applications when joining structural components. The use of bolted joints ranges from non-structural components up to secondary and primary load-bearing structures. Therefore, the designer must understand the load carrying capacity with high reliability in the joint. Sandwich composites of aluminum honeycomb cores with carbon fiber-reinforced facesheets often use metallic inserts when mechanically fastening sandwich components via bolted joints. This study investigates combining novel additive-manufactured (AM) inserts with sandwich composites. The AM inserts are made from high-temperature resistant ULTEM resin and feature specially designed channels for the distribution of the adhesive to form an integrated joint between the insert and the sandwich structure. The additive manufacturing process allows the design to increase geometric stiffness gradually and overlap the facesheets onto the insert, both contributing to minimizing stress concentrations at the interface between the core and insert. The experimental investigation, coupled with 3D digital image correlation (DIC) and numerical simulations, explores the influence the new insert geometry has on the structural response of a sandwich composite under single-lap shear loading. Various failure modes were observed while analyzing the experimental results, with facesheet debonding being the first visible failure mode. Finite element (FE) models and digital image correlation investigate the stress fields in the honeycomb core and overall panel deflections, validating the mechanics observed experimentally. When comparing the AM inserts to standard inserts, there is an increase in stiffness, maximum force, and total energy absorption of 15%, 209%, and 581%, respectively. These results illustrate the superior potential of this integrated approach to joining technology in sandwich structures.

Shrinkage evaluation and geometric accuracy assessment on 17–4 PH samples made by material extrusion additive manufacturing

Development of an architecture-property model for triply periodic minimal surface structures and validation using material extrusion additive manufacturing with polyetheretherketone (PEEK)

Among all the additive manufacturing (AM) technologies, the material extrusion-based AM is the most popular, and widely used for prototyping, rapid tooling, and direct part production in the current scenario. In material extrusion AM (MEAM), a solid form of material is converted to a semi-molten form and extruded out of a nozzle to deposit in a layer-by-layer manner. Nowadays MEAM three-dimensional (3D) printers are very popular among different application sectors. This motivates us to develop various commercial as well as open-source entry-level 3D printers such as the development of filament extruder 3D printers, pellet extruder 3D printer, or a combination of both. However, to develop or operate these printers, preliminary knowledge of various extrusion parameters is required to obtain the desired quality in the fabricated parts. Therefore, an initial attempt has been made to provide information related to various extrusion parameters such as definition, working range, and the effect of these parameters on performance measured. The impact of process parameters on the performance of either filament extrusion AM or pellet/granules extrusion AM has only been investigated in the studies available in the literature. However, this study provides a comprehensive review of the effects of process parameters on performance measurements for both types of extrusion-based AM processes. In this research work, along with a detailed review of previous works, a study of various process parameters, modeling, and methodology has been provided. The statistical modeling approach, histogram normal plots have been provided along with mean, standard deviation, and percentage to decide the optimum process parameters based on data available in the existing literature.

Characterization of mechanical properties and fracture mode of additively manufactured carbon fiber and glass fiber reinforced thermoplastics

Chapter 6 - Polymer and composites additive manufacturing: material extrusion processes

Graphene is emerging as an excellent material choice for high-performance electrical and electrochemical devices such as humidity sensors. The rapid technological evolution in additive manufacturing (AM) enables freedom to design and process multiple materials for scalable fabrication of sensors. Herein, we introduce a hybrid AM approach to fabricate a graphene-based humidity sensor and study its sensing performance. A powder-bed binder-jetting AM technique is used to build a porous 3D-structure of thermally reduced graphene oxide as the humidity sensing element. In parallel, a material extrusion AM approach is used to make a silicone-based hollow cube as the housing of the graphene structure. The AM fabricated sensor shows high sensitivity when tested in the relative humidity (RH) range of 6.4–97.3% with a rapid response time of 7 s at 45% RH due to the open porous structure formed by the binder-jetting approach. Sensing performance was investigated at low and medium RH in the temperature range of 25–80 °C and the device demonstrated a negligible temperature dependence. The presented graphene-based humidity sensor also shows good repeatability in RH measurements.

This paper shows the three-point bending strength analysis of a composite material consisting of polyamide doped with chopped carbon fiber and reinforced with continuous carbon fiber produced by means of the material extrusion (MEX) additive manufacturing technique. For a comparison, two types of specimens were produced: unreinforced and continuous fiber-reinforced (CFR) with the use of carbon fiber. The specimens were fabricated in two orientations that assure the highest strength properties. Strength analysis was supplemented by additional digital image correlation (DIC) analysis that allowed for the identification of regions with maximum strain within the specimens. The utilization of an optical microscope enabled a fractographic examination of the fracture surfaces of the specimens. The results of this study demonstrated a beneficial effect of continuous carbon fiber reinforcement on both the stiffness and strength of the material, with an increase in flexural strength from 77.34 MPa for the unreinforced composite to 147.03 MPa for the composite reinforced with continuous carbon fiber.

The design of modern mechanical components often requires the use of low-density and high-strength parts. Additive manufacturing presents competence in obtaining format complexity internally (voids, ducts, channels) and externally (shape, holes). However, parts obtained by material extrusion additive manufacturing are highly anisotropic and relatively weak. This paper aims to present a new mechanical design technique that combines the high geometry flexibility of additive manufacturing with internal structuring reinforcement by high-strength materials, which enables optimized parts with reinforcement in the most mechanical stressed areas during service, through adopting structured internal geometry filled with reinforcement material. Dense test specimens and test specimens with internal structural canals filled with reinforcement material (epoxy resin and carbon fibers) were designed, fabricated and tested physically and virtually. The obtained results provide property values for 3D-printed acrylonitrile butadiene styrene (typical material of additive manufacturing) and for this polymer reinforced with various reinforcement material configurations (useful for mechanical design). The reinforcement decreased anisotropy and improved mechanical properties. Optimized parts filled with resin and long carbon fibers had maximum flexural resistance of 112 MPa, with a specific weight of 1.1 g/cm3. This reinforcement provided parts with specific flexural strength similar to structural aluminum alloys, preserving the geometry and external dimension of the printed parts. The technique presented here shows the possibility of new conceptions in mechanical components design and strength optimization by internal reinforcement canals in parts. The technique is useful for mechanical design activity and allows for new product conceptions based on additive manufacturing.

Designing efficient closed-loop control algorithms is a key issue in Additive Manufacturing (AM), as various aspects of the AM process require continuous monitoring and regulation, with temperature being a particularly significant factor. Here we study closed-loop control for the temperatures in the extruder of a Material Extrusion AM system, specifically a Big Area Additive Manufacturing (BAAM) system. Previous approaches for temperature control in AM either require the knowledge of exact model parameters, or involve discretisation of the state and action spaces to employ traditional data-driven control techniques. On the other hand, modern algorithms that can handle continuous state and action space problems require a large number of hyperparameter tuning to ensure good performance. In this work, we circumvent the above limitations by making use of a state space temperature model while focusing on both model-based and data-driven methods. We adopt the Linear Quadratic Tracking (LQT) framework and utilise the quadratic structure of the value function in the model-based analytical solution to produce a data-driven approximation formula for the optimal controller. We demonstrate these approaches using a simulator of the temperature evolution in the extruder of a BAAM system and perform an in-depth comparison of the performance of these methods. We find that we can learn an effective controller using solely simulated input–output process data. Our approach achieves parity in performance compared to model-based controllers and so lessens the need for estimating a large number of parameters of the often intricate and complicated process model. We believe this result is an important step towards achieving autonomous intelligent manufacturing.

Material extrusion additive manufacturing (MEAM) is an advanced manufacturing method that produces parts via layer-wise addition of material. The potential of MEAM to prototype lattice structures is remarkable, but restrictions imposed by manufacturing processes lead to practical limits on the form and dimension of structures that can be produced. For this reason, such structures are mainly manufactured by selective laser melting. Here, the capabilities of fused filament fabrication (FFF) to produce custom-made lattice structures are explored by combining the 3D printing process, including computer-aided design (CAD), with the finite element method (FEM). First, we generated four types of 3D CAD scaffold models with different geometries (reticular, triangular, hexagonal, and wavy microstructures) and tunable unit cell sizes (1–5 mm), and then, we printed them using two nozzle diameters (i.e., 0.4 and 0.8 mm) in order to assess the printability limitation. The mechanical behavior of the above-mentioned lattice scaffolds was studied using FEM, combining compressive modulus (linear and nonlinear) and shear modulus. Using this approach, it was possible to print functional 3D polymer lattice structures with some discrepancies between nozzle diameters, which allowed us to elucidate critical parameters of printing in order to obtain printed that lattices (1) fully comply with FFF guidelines, (2) are capable of bearing different compressive loads, (3) possess tunable porosity, and (3) overcome surface quality and accuracy issues. In addition, these findings allowed us to develop 3D printed wrist brace orthosis made up of lattice structures, minimally invasive (4 mm of thick), lightweight (&lt;20 g), and breathable (porosity &gt;80%), to be used for the rehabilitation of patients with neuromuscular disease, rheumatoid arthritis, and beyond. Altogether, our findings addressed multiple challenges associated with the development of polymeric lattice scaffolds with FFF, offering a new tool for designing specific devices with tunable mechanical behavior and porosity.