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This letter examines the contact and constriction resistance phenomena in the context of 3-D-printed electronics, with a focus on exploring the use of constriction resistance for force sensing. We design and manufacture a sensor using carbon-black conductive thermoplastic polyurethan on a fused deposition modeling 3-D printer and test it using a geometry-based resistive model to fit the data to a number of possible force–resistance relations found in the literature. The sensor exhibits low hysteresis between force and resistance, and good sensitivity at low forces, while at high forces, it displays consistent contact and stable resistance. We analyze the design methodology and offer recommendations for future sensor design and fitting options, as well as put forward approaches to maximizing force sensitivity. Although the exact model derived in this letter is not directly transferable to other sensors, the workflow can serve as a useful guide for future research.

This paper investigates the stability of deformable layers produced by material extrusion additive manufacturing. A Computational Fluid Dynamics (CFD) model is developed to predict the deposition flow of viscoplastic materials such as ceramic pastes, thermosets, and concrete. The viscoplastic materials are modelled with the Bingham rheological equations and implemented with a generalized Newtonian fluid model. The developed CFD model applies a scalar approach to differentiate the rheology of two layers in order to capture the deposition of a wet layer onto a semi solidified printed layer (i.e., wet-on-semisolid printing). The semi solidification is modelled by a yield stress buildup. The cross-sectional shapes of the deposited layers are predicted, and the relative deformation of the first layer is studied for different yield stress buildups and processing conditions such as printing- and extrusion-speed, layer height, and nozzle diameter. The results of the CFD model illustrate that the relative deformation of the first layer decreases non-linearly with an increase in yield stress, and that stable prints can be obtained when taking into account the semi solidification. Furthermore, it is found that the deformation is dependent on a non-trivial interplay between the extrusion pressure, the shape of the cross-section, and the contact area between the layers. Finally, the results highlight which process conditions can be changed with benefit in order to limit the requirement on the yield stress buildup and still provide stable prints.

Mixing in extrusion is a vital part of achieving consistent and high-quality extrudates, with residence time being an elucidative measure of the mixing performance. Recent studies around numerical modeling of residence time distributions in single-screw extruders appear to consider flooded extruders mainly. This paper introduces a new and general CFD model to characterize the extruder fill length and residence time distribution for a viscoplastic ceramic material in a starve-fed extruder, including free surface tracking. The CFD model simulates a pulse-injection test, where a fluid parcel is injected at the inlet, with subsequent outlet concentration measured over time. The study includes material characterization and model validation based on laboratory tests. Results quantify the impact of accounting for the partially filled extruder instead of assuming it to be flooded, addressing the potential error when only considering simple analytical approximations to calculate system average residence times. Results further show the ability to fit simulation results to more simple analytical models. This underlines the importance of including the entire extrusion system and forming the basis for further work toward enabling real-time model predictions in starve-fed extrusion systems.

Robocasting and 3D concrete printing are technologies that belong under the umbrella term material extrusion additive manufacturing. These two free-form fabrication methods are used to produce 3D structures/components in materials such as ceramic pastes, thermosets, and concrete. Common for the materials is their viscoplastic behavior during deposition and structural buildup (i.e., increase in yield stress) after deposition. The material’s complex nature makes it a non-trivial task to ensures that printed layers do not deform when depositing additional layers on top. In this article, we numerically investigate the influence of the yield stress buildup of viscoplastic materials on the stability of the bottom layer during multilayer printing. Specifically, we have developed a computational flssssuid dynamics model that applies a scalar approach to alter the yield stress. The novel model provides fundamental knowledge on how to design the material’s rheology, so the bottom layer can withstand both the hydrostatic and extrusion pressure.

Over the last 70 years, pultrusion has matured into an industry-leading process when it comes to providing high throughput and automated composite manufacture at a competitive price point. In this paper, we review recent innovations that have advanced pultrusion to a versatile manufacturing technology and thereby allowed composite materials to penetrate markets in, e.g., the automotive, construction, aerospace, and wind turbine industries. We accompany our review with discussions on how pultrusion has enabled new innovations within additive manufacturing and sustainable composite manufacturing, and finally, we provide an outlook and suggestions for where we see the potential for research and new industrial applications of pultrusion technology., Composites Part B: Engineering, 246, ISSN:1359-8368, ISSN:1879-1069

The influence of the bulk modulus of metal forming lubricants on their load-carrying capacity during model asperity flattening under bi-axial subsurface deformation was experimentally and numerically studied. The experimental results showed that lubricants with different bulk moduli do not change the asperity flattening noticeably when subsurface deformation occurs. Numerical simulations revealed that a substantial change could only be obtained by very low theoretical bulk moduli. If the bulk modulus remains the same and material strength varies instead, it is seen that harder materials experience more flattening than the softer ones when being compared at the same strain.

This paper presents a new modelling approach for liquid lubricant behavior in metal forming operations by focusing on the hydrodynamic pressure build-up in micro pockets. Theoretical and numerical fundamentals of the proposed approach are introduced, and upsetting of an aluminum cylinder with an artificial lubricant pocket is presented as a validation case. The proposed numerical framework splits the fluid-solid interaction model into a computational fluid dynamics and solid mechanics part. While the solid mechanics part employs the Lagrangian finite element flow formulation for plastic deformation, the fluid dynamics part is built upon the set of Navier-Stokes equations applying an Eulerian finite element method in combination with an Arbitrary Langagian Eulerian formalism. The latter enables the displacement based coupling from the solid to the fluid. The fluid-to-solid coupling is pressure based and enabled by the finite element flow formulation’s inherent velocity-pressure characteristics. The weak coupling avoids ill-conditioning of the system matrix and makes it possible to benefit from both Lagrangian and Eulerian meshes.

Friction in sheet metal forming is largely governed by the flattening of surface asperities. Liquid lubricants can reduce flattening and friction by filling the surface valleys and carry a substantial amount of the pressure. Experimental and numerical work is presented for investigating the influence of the compressibility of the lubricant and the material strength on the deformation of a simple cylinder with an enlarged surface pocket filled with oil. Results show that deformation is not sensitive to differences in compressibility of typical lubrication oils under hydrostatic pressure conditions. This was observed independent of the material strength.

Volumetric additive manufacturing has a number of advantages as compared to conventional additive manufacturing methods, but it can still suffer from premature sedimentation in which the part sinks down during the printing process - especially in the final seconds- affecting the method’s geometric fidelity, resolution, and limits its applicability only to high-viscosity resins. In this study, a numerical model has been developed to investigate the effect of different material properties and process parameters on the sedimentation of the printed part. After a qualitative validation of the model, the role of the resin viscosity in the sedimentation phenomenon is elucidated, and it is shown how a rise in the cross-section ratio of the printed geometry to the container can reduce the sedimentation, while an increase in the curing time and the container’s rotation velocity can escalate the sinking of the part. Furthermore, it is found that raising the final density and viscosity of the curing material at the end of the print will worsen and mitigate the sinking effect, respectively. Finally, the effect of the orientation of the printed part on the sedimentation ratio is explored. The model developed herein illuminates a new avenue for better understanding the physics taking place during volumetric additive manufacturing, which is essential to further improve the applicability of the technology.

Limiting shape distortions and residual stresses are of utmost importance when ensuring the structural integrity and the quality of fibre-reinforced thermoset composites. This paper presents a novel method for 3D thermo-chemical-mechanical analysis of pultrusion processes to analyse process-induced stresses and deformations. As opposed to established methods that rely on coupling a 3D transient Eulerian thermo-chemical analysis with a Lagrangian mechanical analysis, this framework presents a novel method to simultaneously solve for all variables in the same Eulerian domain. As demonstrated in the paper, the framework benefits from significant improvements in computation times (a reduction of 95% compared to established methods) without sacrificing solution accuracy.

Manufactured sand is increasingly used in concrete and predicting the rheology of such suspensions based on their composition are necessary. In this study, emphasis is on cement pastes with manufactured sand and silica fume. An artificial neural network, namely multilayer perceptron, is compared with nine suspension models: two liquid thickness models, the relative concentration of solids and six relative viscosity models based on the relative concentration of solids. Measurements on 107 mixes with filler (0–125 µm) from manufactured sand are conducted, acquiring yield stress, plastic viscosity, flow resistance ratio and mini slump flow. None of the suspension models offer good correlations to the measured parameters for all mixes, but an increase in prediction accuracy is seen for subsets of materials, especially mixes without silica fume. The artificial neural network outperforms the suspension models, providing a coefficient of determination between 0.84 and 0.91 for all mixes, thus illuminating a new pathway for cement paste rheology modelling.

Additive manufacturing of thermoplastic conductive polymer composites offers interesting opportunities for customizing compliant flexural sensors. The study aimed to show that additive manufacturing could be used to fabricate flexural sensors for evaluating the effect of sensor geometry on the sensor output. Prior literature has primarily focused on material optimization rather than geometrical design. The results of this paper show that the signal amplitude between geometrically different flexural sensors with the same footprint can increase ∼28 times. In addition, the bending force is found proportional to the signal amplitude. Thus, concentrating the bending to a small section increases the signal amplitude but also increases the effect of material relaxation broadening the hysteresis loop. This study highlights the importance of considering the geometrical design when fine-tuning additive manufactured flexural sensors. In future work, it is paramount to improve reproducibility, signal linearity, and investigate the effects of geometry on other sensor parameters.

Soft and electrically active materials are currently being utilized for intelligent systems, including electronic skin, cybernetics, soft robotics, and wearable devices. However, fabricating materials that fulfill the complex requirements of such advanced applications remains a challenge. These attributes include electronic, adhesive, self-healing, flexible, moldable, printable, and strong mechanical properties. Inspired by the recent interest in transforming monofunctional materials into multifunctional ones through nanoreinforcement and mussel-inspired chemistry, we have designed a simple two-step methodology based on halloysite nanotube (HNT) and polydopamine (PDA) to address the grand challenges in the field. In brief, HNTs were coated with PDA and embedded within a poly(vinyl alcohol) (PVA)-based polymeric matrix in combination with ferric ions (Fe

This paper concerns non-isothermal flow in a thermoset resin-injection pultrusion process. Supported by temperature measurements from an industrial pultrusion line and a material characterisation study (curing kinetics, chemorheology, and permeability), the material flow was analysed for the manufacture of a thick glass-fibre profile saturated with a pultrusion-specific polyurethane resin. A central finding is that the heating configuration, together with the strongly convective flow near inlets resulted in phase transitions that were both concave and convex-shaped. This is different from existing literature that commonly describes curing being initiated from die-walls, resulting in the concave phase-transitions.

In this paper, a 2D numerical framework for the simulation of flows in porous media that are characterised by a sharp transition between the saturated and unsaturated zone is presented. Using a finite volume scheme and the level-set method, the framework is derived based on a conventional, implicit solution of Darcys law for the pressure field, while the level-set function is advected explicitly locally at the flow front. With the main application to liquid composite moulding (LCM) in mind, the numerical framework is verified against analytical solutions, experiments, and other benchmark cases for a variety of situations that occur in this composite manufacturing process. The cases include local changes in permeability related to edge-effects, merging of flow fronts, and continuous manufacturing processes. It is highlighted that the numerical framework achieves convergence with a spatial accuracy between 1st and 2nd-order; the level-set operations only take about 20% of the total CPU time; and the propagation of the resin front can be achieved with CFL-sized time steps without overfilling cells and without applying any artificial smoothing.

This study demonstrates a two-step approach that enables quantification of concrete printability through dynamics mode rheological measurements; I) modeling shearing history during extrusion; II) monitoring the hardening evolution of deposited material by applying a strain smaller than the critical strain. It is shown that the shearing history of the material is removed by imposing a pre-shearing above the critical strain, and zero value yield stress is measured for all specimens. At step II, a linear extrapolation of the green strength development can quantify the static yield stress at the origin, which we used to quantify the material printability. As far as this yield stress surpasses the stress level that exists in the printed structure, the material retains its shape stability. We show the performance of the model on a series of geopolymer mortars with a wide range of rheological properties as a function of material composition, aging, and pre-shearing consequences.

This paper presents a computational fluid dynamics model fit for multi-layer 3D Concrete Printing. The numerical model utilizes an elasto-visco-plastic constitutive model to mimic the flow behaviour of the cementitious material. To validate the model, simulation data is compared to experimental data from 3D printed walls. The obtained results show that the numerical model can reproduce the experimental results with high accuracy and quantify the extrusion load imposed upon the layers. Such load is found to exceed the material’s yields stress in certain regions of previously printed layers, leading to layer deformation/flow. The developed and validated numerical model can assist in identifying optimal printing strategies, reducing the number of costly experimental print failures and human-process interaction. By doing so, the findings of this paper helps 3D Concrete Printing move a step closer to a truly digital fabrication process.

Process-induced stress and deformation are critical factors when ensuring product quality and structural integrity of composite profiles manufactured using thermoset pultrusion processes. In this paper, we present a new steady-state 3D-Eulerian numerical framework that enables 9–35 times faster computations compared to the current state-of-the-art quasi-static 3D-methods. In addition, we show how process-induced effects from the profile-advancing pulling force and an initial compressive stress state can be modelled. We demonstrate in theoretical parameter studies that the pulling force advances die-detachment and reduces die-swelling, while the initial compressive stress state has the opposite but a more pronounced effect.

There is a need for simple but precise prediction models for proportioning concrete with manufactured sand, for use in ready-mix concrete production. For the last two decades, the particle-matrix model has been used in Norway for proportioning and prediction of concrete flow based on the properties and proportions of two concrete phases: coarse particles and filler modified cement paste (matrix). This paper presents experimental testing of 117 cement pastes of which 107 contain filler, i.e. particles < 125 microns, from manufactured sand. Based on compositions and properties of ingoing materials in these mixes, an empirical equation is developed that predicts the rheological properties plastic viscosity, yield stress, flow resistance ratio and mini slump flow. Optimization by regression analysis provides a practical microproportioning equation that readily can be used as input in concrete proportioning with the particle-matrix model. The equation provides a coefficient of determination R2 = 0.98 for plastic viscosity, R2 = 0.95 for mini slump flow, R2 = 0.91 for flow resistance ratio and R2 = 0.80 for yield stress.

Contains fulltext : 238926.pdf (Publisher’s version ) (Closed access) Soft and electrically active materials are currently being utilized for intelligent systems, including electronic skin, cybernetics, soft robotics, and wearable devices. However, fabricating materials that fulfill the complex requirements of such advanced applications remains a challenge. These attributes include electronic, adhesive, self-healing, flexible, moldable, printable, and strong mechanical properties. Inspired by the recent interest in transforming monofunctional materials into multifunctional ones through nanoreinforcement and mussel-inspired chemistry, we have designed a simple two-step methodology based on halloysite nanotube (HNT) and polydopamine (PDA) to address the grand challenges in the field. In brief, HNTs were coated with PDA and embedded within a poly(vinyl alcohol) (PVA)-based polymeric matrix in combination with ferric ions (Fe(3+)). The final composite displayed a 3-fold increase in electrical conductivity, a 20-fold increase in mechanical stiffness, and a 7-fold increase in energy dissipation in comparison to their nonfunctional counterparts, which arose from a combination of nanotube alignment and mussel-inspired chemistry. Moreover, the developed composite could elongate up to 30000% of its original length, maintain its electrical properties after 600% strain, self-heal within seconds (both electrically and mechanically), and display strain-sensitivity. Finally, it was 3D-printable and thus amenable for engineering of customized wearable electronics.

Characterisation of model asperity flattening under longitudinal subsurface elongation is presented with a variety of normal pressure, flank angle and strain hardening behaviour. A systematic investigation outlines an optimal specimen design to ensure a homogenous deformation field in the workpiece under stress-strain conditions, which are typical in sheet metal forming. Asperity flattening increases with normal pressure, and the longitudinal subsurface strain reduces the necessary yield pressure and promotes asperity flattening. When the flank angle is increased, the longitudinal stress component due to elongation gets smaller in the asperity, reducing the effect of longitudinal straining. Strain hardening decreases the asperity flattening rate as strain hardening extends the deformation field further into the underlying material, which results in less asperity flattening.

The concrete industry is facing new digital shaping processes that still have to be optimized and that require cement-based materials, for which fresh properties requirements are yet to be defined. In this paper, we first present the state of the art in the field of numerical simulations of concrete flow. We then focus on the literature on numerical simulations of extrusion-based additive manufacturing processes for concrete. Our review shows that the available numerical modelling tools are able to detect and predict various type of failures through the printing process, no matter if these happen at the scale of the nozzle, of one printed layer or of the entire object being printed. As they allow for a systematic evaluation of the influence of the entire range of material, geometric and process parameters, numerical modelling is a valid option to optimize both process and material.

Advancements in material extrusion additive manufacturing are driven by the need of fast production of high-quality parts. A key innovation was the introduction of short fibers into the built filament, which substantially improve the strength of manufactured components. However, the presence of fibers also affects the viscosity and thermal conductivity of the filament, which are important parameters for the extrusion flow and thus the maximum printing speed. In this paper, we numerically study the effect of fibers on the polymer flow and pressure drop inside the nozzle, which determines the maximum extrusion rate. The thermoplastic polymer flow is simulated with a non-isothermal computational fluid dynamics model and the inclusion of fibers is treated with a continuum approach. The simulations are performed for ABS polymer with short carbon fibers, however, other thermoplastic systems with short fibers (e.g. glass, wood, or nylon) can be integrated into the model. The model provides a virtual window into the process and illustrates that while fibers increase the viscosity of the filament and the pressure drop, they also improve the thermal conductivity and lead to faster melting of the polymer, which has an opposite effect on the pressure drop. Finally, the model quantifies the relationship between the fiber volume fraction and the maximum extrusion rate.

Air-texturisation is a process that adds bulkiness to bundles of fibres. In this study, the permeability and compaction behaviour of air-texturised glass fibre rovings are experimentally characterised and compared to conventional unidirectional rovings. Based on radial impregnation experiments and single-step compaction/decompaction tests, the following main findings are highlighted: Compared to conventional unidirectional-rovings, the normalised permeability of the air-texturised rovings was approximately three times higher along the fibre direction and 40 times higher transverse to the fibre direction. Accordingly, the degree of anisotropy was approximately one magnitude lower. At a compaction pressure of 1 and 5 bar, the air-texturised rovings were compacted to a volume fraction of Vf=0.34 and 0.43, respectively, which was approximately 30% lower than the volume fraction achieved for the conventional unidirectional-rovings. Finally, it was observed that the decompaction of air-texturised rovings exhibits a more distinct elastic response when unloaded., Journal of Composite Materials, 54 (27), ISSN:0021-9983, ISSN:1530-793X

This work presents Computational Fluid Dynamics (CFD) simulations of the polymer flow inside the hot-end during material extrusion additive manufacturing. Two CFD models are investigated: a previously-published one-phase model, where the entire domain is filled with liquid, and a novel model, where the free surface of the polymer inside the channel is resolved. Both models predict a recirculation region between the nozzle wall and the incoming filament. With the free surface resolved, melting of the solid filament and filling of an empty liquefier channel are shown in detail. Moreover, the simulations predict the pressure and temperature distributions inside the channel. The molten polymer (ABS) is simulated as a Generalized Newtonian Fluid with shear- and temperature-dependent viscosity. The numerical results are compared with the experimental measurements of the filament feeding force, which relates to the pressure inside the flow channel. An inverse analysis of the heat transfer coefficient is performed to estimate the thermal resistance at the channel’s wall. It is shown that the model which resolves the free surface is able to predict the feeding force for typical working conditions with a reasonable accuracy. Moreover, it captures the change of the flow regime from stable to unstable extrusion at high feeding rates. A hypothesis that explains the pressure and melt zone oscillations that occur during unstable extrusion is given. The influence of the liquefier temperature, liquefier length and nozzle diameter on the flow are discussed. The predictions of the model become less accurate when different channel geometries are simulated, which is attributed to the simplified material model that does not capture viscoelastic effects and possible buckling of the solid filament.

This paper presents the numerical simulation results of a computational fluid dynamics (CFD) model that describes the layer shape in extrusion-based 3D Concrete Printing (3DCP). The simulation outcome is validated through an experimental program in which we investigated the influence of 3DCP processing parameters on the geometry of a single layer. Specifically, a set of single layers were printed using a O25 mm nozzle mounted on an 6-axis industrial robotic arm travelling at different speeds and with different layer heights. A fresh concrete – comprising CEM I 52,5 R - SR 5 (EA), limestone filler, fine sand, water, and admixtures (i.e. viscosity modifying agent, high-range water-reducing admixtures and a hydration retarder) – was pumped and extruded at a fixed volumetric rate. Once hardened, the extruded layers were sliced to examine the resulting cross-sections. Specifically, the cross-sections’ geometry were obtained by a custom image processing algorithm. Next, the extrusion flow was modelled with a CFD simulation using the software FLOW-3D®. The constitutive behavior of fresh concrete was modelled as a Bingham fluid, while the volume-of-fluid method was used to predict the free surface of the concrete and, thus, the layer geometry. The numerical results agree qualitatively with the experimental observations, enabling us to identify two non-dimensional 3DCP processing parameters that influence the overall cross-sectional shapes: 1) the geometric ratio between layer height and nozzle diameter, and 2) the ratio between the nozzle velocity and the extrusion volumetric flux. These findings – when complemented with a model describing the overall deformation of stacked layers – serve as the basis for correlating material rheological properties to 3DCP process parameters, promoting a better link between design and fabrication in a 3DCP context.

Numerical modeling is one of the key components in the development of digital twins of Additive Manufacturing (AM) processes, encompassed in the concept of Industry 4.0. Numerical simulations also have a role to play in the improvement of contemporary AM techniques, among which material extrusion is very popular. Computational Fluid Dynamics (CFD) models have recently proven successful for simulating the deposition flow in extrusion AM. Previous modeling works using CFD have been able to predict the influence of processing parameters on the cross-sectional shape of the printed strand, as well as the mesostructure formation resulting from their deposition and fusing. The present study focuses on using CFD simulations to quantify the waviness of a strand extruded on top of a previous layer with an orthogonal print direction, which often occurs when printing a part with a rectilinear infill pattern and alternate 0°/90° raster angles from layer to layer. The variations in the strand width and thickness of the second layer were found to depend on the strand-to-strand gap in the first layer. The CFD model was also used to determine the interlayer penetration depth, which enhances mechanical performances.