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The purpose of this paper is to investigate, develop and validate a three‐dimensional modelling strategy for the efficient generation of conformal textile data suitable for additive manufacture.

A series of additive manufactured (AM) textiles samples were modelled using currently available computer‐aided design software to understand the limitations associated with the generation of conformal data. Results of the initial three‐dimensional modelling processes informed the exploration and development of a new dedicated efficient modelling strategy that was tested to understand its capabilities.

The research demonstrates the dramatically improved capabilities of the developed three‐dimensional modelling strategy, over existing approaches by accurately mapping complex geometries described as STL data to a mapping mesh without distortion and correctly matching the orientation and surface normal.

To date the generation of data for AM textiles has been seen as a manual and time‐consuming process. The research presents a new dedicated methodology for the efficient generation of complex and conformal AM textile data that will underpin further research in this area.

Optimised concrete components are often of complex geometries, which are difficult and costly to cast using traditional formworks. This paper aims to propose an innovative formwork system for optimised concrete casting, which is eco-friendly, recyclable and economical.

In the proposed formwork system, ice is used as mould pattern to create desired geometry for concrete member, then sand mould is fabricated based on the ice pattern. A mix design and a mixing procedure for the proposed sand mould are developed, and compression tests are also performed to ensure sufficient strength of the sand mould. Furthermore, surface preparation of the sand mould is investigated for easy demoulding and for achieving good concrete surface quality. Additionally, recyclability of the proposed sand mould is tested.

The proposed mix design and mixing procedure can provide sufficient strength for sand mould in concrete casting. The finished components exhibit smooth surfaces and match designed geometries, and the proposed sand mould can be fully recycled with satisfactory strength.

To the best of the authors’ knowledge, this is the first study that combines ice pattern and sand mould to create recyclable formwork system for concrete casting. The new techniques developed in this research has great potential to be applied in the fabrication of large-scale concrete structures with complex geometries.

The main purpose of this paper is presenting Thin Plates Spline-based Differential Quadrature (TPS-DQM) as a meshless numerical method to solve the steady and transient groundwater equation in complex geometry.

The computational nodes are randomly distributed in domain, and the governing equations of groundwater flow are solved, relying on the capability of present model for solving the partial differential equations (PDEs) in irregular domains. To show the accuracy of the proposed model, several seepage problems in both homogenous and non-homogenous soils are solved, and the results are compared with those existing analytical solution and well-known finite element-based software SEEP/W.

The results indicate that the present meshless method is capable of simulating steady-state and unsteady seepage problems, especially in complex geometry and it provides sufficient accuracy and reliability, despite the low computational effort and no need for additional parameters like shape factor.

The main advantage of the method is its meshless characteristic, which does not require structured grid generation and able to solve governing equation in arbitrary geometry.

Injection molding is a very mature technology, but the growth of layer‐build, additive, manufacturing technologies (rapid prototypying) has the potential of expanding injection molding into areas not commercially feasible with traditional molds and molding techniques. This integration of injection molding with rapid prototyping has undergone many demonstrations of potential. What is missing is the fundamental understanding of how the modifications to the mold material and mold manufacturing process impact both the mold design and the injection molding process. This work expanded on an approach to utilize current numerical simulation programs and created a tool for optimizing the creation and use of non‐metal molds for injection molding. Verification and validation work is presented. The model was exercised by studying the effect of varying the thermal conductivity on final‐part distortions. This work clearly showed that one could not obtain reasonable results by simply changing a few input parameters in the current simulations. Although the approach did produce more realistic results, more work will be required for a tool capable of accurate, quantitative predictions.

New applications of solid freeform fabrication (SFF) are arising, such as functional rapid prototyping and in situ fabrication, which push SFF to its limits in terms of geometrical fidelity due to the applications' inherent process uncertainties. Current closed‐loop feedback control schemes monitor and manipulate SFF techniques at the process level, e.g. envelope temperature, feed rate. “Closing the loop” on the process level, instead of the overall part geometry level, leads to limitations in the types of errors that can be detected and corrected. The purpose of this paper is to propose a technique called greedy geometric feedback (GGF) control which “closes the loop” on the overall part geometry level.

The overall part geometry is monitored throughout the print and, using a greedy algorithm, real‐time decisions are made to serially determine the locations of subsequent droplets, i.e. overall part geometry is directly manipulated. A computer simulator and a physical experimental platform were developed to compare the performance of GGF to an open‐loop control scheme. Root mean square surface height errors were measured under controlled uncertainties in droplet height, droplet radius of curvature, droplet positioning and mid‐print part deformations.

The GGF technique outperformed open‐loop control under process uncertainties in droplet shape, droplet placement and mid‐print part deformations. The disparity between performances is dependant on the nature and extent of the imposed process uncertainties.

Future research will focus on improving the performance of GGF for specific cases by designing more complex greedy algorithmic scoring heuristics. Also, the technique will be generalized beyond heightmap representations of 3D spaces.

The GGF technique is the first to “close the loop” on the overall part geometry level. GGF, therefore, can compensate for a broader range of errors than existing closed‐loop feedback control schemes. Also, since the technique only requires the real‐time update of a very limited set of heights, the technique is computationally inexpensive and widely applicable. By developing a closed‐loop feedback scheme that addressed part geometry‐level errors, SFF can be applied to more challenging in situ fabrication scenarios with less conventional materials.

The performance of three frequently used level set-based segmentation methods is examined for the purpose of defining features and boundary conditions for image-based Eulerian fluid and solid mechanics models. The focus of the evaluation is to identify an approach that produces the best geometric representation from a computational fluid/solid modeling point of view. In particular, extraction of geometries from a wide variety of imaging modalities and noise intensities, to supply to an immersed boundary approach, is targeted.

Two- and three-dimensional images, acquired from optical, X-ray CT, and ultrasound imaging modalities, are segmented with active contours, k-means, and adaptive clustering methods. Segmentation contours are converted to level sets and smoothed as necessary for use in fluid/solid simulations. Results produced by the three approaches are compared visually and with contrast ratio, signal-to-noise ratio, and contrast-to-noise ratio measures.

While the active contours method possesses built-in smoothing and regularization and produces continuous contours, the clustering methods (k-means and adaptive clustering) produce discrete (pixelated) contours that require smoothing using speckle-reducing anisotropic diffusion (SRAD). Thus, for images with high contrast and low to moderate noise, active contours are generally preferable. However, adaptive clustering is found to be far superior to the other two methods for images possessing high levels of noise and global intensity variations, due to its more sophisticated use of local pixel/voxel intensity statistics.

It is often difficult to know a priori which segmentation will perform best for a given image type, particularly when geometric modeling is the ultimate goal. This work offers insight to the algorithm selection process, as well as outlining a practical framework for generating useful geometric surfaces in an Eulerian setting.

The purpose of this paper is to present a new approach of meshless local B-spline based finite difference (FD) method for solving two dimensional transient heat conduction problems.

In the present method, any governing equations are discretized by B-spline approximation which is implemented in the spirit of FD technique using a local B-spline collocation scheme. The key aspect of the method is that any derivative is stated as neighbouring nodal values based on B-spline interpolants. The set of neighbouring nodes are allowed to be randomly distributed thus enhanced flexibility in the numerical simulation can be obtained. The method requires no mesh connectivity at all for either field variable approximation or integration. Time integration is performed by using the Crank-Nicolson implicit time stepping technique.

Several heat conduction problems in complex domains which represent for extended surfaces in industrial applications are examined to demonstrate the effectiveness of the present approach. Comparison of the obtained results with solutions from other numerical method available in literature is given. Excellent agreement with reference numerical method has been found.

The method is presented for 2D problems. Nevertheless, it would be also applicable for 3D problems.

A transient two dimensional heat conduction in complex domains which represent for extended surfaces in industrial applications is presented.

The presented new meshless local method is simple and accurate, while it is also suitable for analysis in domains of arbitrary geometries.

The use of stent‐grafts to canalize aortic blood flow for patients with aortic aneurysms is subject to serious failure mechanisms such as a leak between the stent‐graft and the aorta (Type I endoleak). The purpose of this paper is to describe a novel computational approach to understand the influence of relevant variables on the occurrence of stent‐graft failure and quantify the probability of failure for aneurysm patients.

A parameterized fluid‐structure interaction finite element model of aortic aneurysm is built based on a multi‐material formulation available in LS‐DYNA. Probabilities of failure are assessed using an explicit construction of limit state functions with support vector machines (SVM) and uniform designs of experiments. The probabilistic approach is applied to two aneurysm geometries to provide a map of probabilities of failure for various design parameter values.

Parametric studies conducted in the course of this research successfully identified intuitive failure regions in the parameter space, and failure probabilities were calculated using both a simplified and more complex aneurysmal geometry.

This research introduces the use of SVM‐based explicit design space decomposition for probabilistic assessment applied to bioengineering problems. This technique allows one to efficiently calculate probabilities of failure. It is particularly suited for problems where outcomes can only be classified as safe or failed (e.g. leak or no leak). Finally, the proposed fluid‐structure interaction simulation accounts for the initiation of Type I endoleak between the graft and the aneurysm due to simultaneous fluid and solid forces.

The development of robust control algorithms for the position, velocity and trajectory control of unmanned underwater vehicles (UUVs) depends on the accuracy of their mathematical models. Accuracy of the model is determined by precise estimation of the UUV hydrodynamic parameters. The purpose of this study is to determine the hydrodynamic forces and moments acting on an underwater vehicle with complex body geometry and moving at low speeds and to achieve the accurate coefficients associated with them.

A three-dimensional (3D) computer-aided design (CAD) model of UUV is designed with one-to-one dimensions. 3D fluid flow simulations are conducted using computational fluid dynamics (CFD) software programme in the solution of Navier Stokes equations for laminar and turbulent flow analysis. The coefficients depending on the hydrodynamic forces and moments are determined by the external flow analysis using the CFD programme. The Flow Simulation k-ε turbulence model is used for the transition from laminar flow to turbulent flow. Hydrodynamic properties such as lift and drag coefficients and roll and yaw moment coefficients are calculated. The parameters are compared with the coefficient values found by experimental methods.

Although the modular type UUV has a complex body geometry, the comparative results of the experiments and simulations confirm that the defined model parameters are accurate and close to the actual experimental values. In the proposed k-ε method, the percentage error in the estimation of drag and lifting coefficients is decreased to 4.2% and 8.39%, respectively.

The model coefficients determined in this study can be used in high-level control simulations which leads to the development of robust real-time controllers for complex-shaped modular UUVs.

The Lucky Fin UUV with 4 degrees of freedom is a specific design and its CAD model is first extracted. Verification of simulation results by experiments is generally less referenced in studies. However, it provides more precise parameter identification of the model. Proposed study offers a simple and low-cost experimental measurement method for verification of the hydrodynamic parameters. The extracted model and coefficients are worthwhile references for the analysis of modular type UUVs.

This paper aims to develop experimentally validated numerical models to accurately characterize the cross-sectional geometry of the deposited beads in a fused filament fabrication (FFF) process under various process conditions.

The presented numerical model is investigated under various fidelity with varying computational complexity. To this end, comparisons between the Newtonian, non-newtonian, isothermal and non-isothermal computational models are presented for the extrusion of polylactic acid material in an FFF process. The computational model is validated through an experimental study on an off-the-shelf FFF printer. Microscope images of experimentally printed FFF bead cross-sections corresponding to various printing conditions are digitally processed for the validation. In the experimental study, common practical printing conditions for an FFF process are tested, and the results are compared to the numerical model.

Microscope image analyses of the cross-sectional geometries of deposited beads show that the numerical model provides a precise characterization of the cross-sectional geometry under varying process parameters in terms of the cross-section outline, bead height and width. The results show that the nozzle-to-table distance has a great effect on the bead shape when compared to the extrusion rate at a given nozzle-to-table distance. Comparison of the various computational models show that the non-Newtonian isothermal model provides the best tradeoff between computational complexity and model accuracy.

The authors provide detailed computational models, including the extruder nozzle geometry for cases ranging from Newtonian isothermal models to non-Newtonian non-isothermal models with experimental validation. The validation study is conducted for practical process parameters that are commonly used in FFF in practice and show that the computational models provide an accurate depiction of the true process outputs. As the developed models can accurately predict process outputs, they can be used in further applications for process planning and parameter tuning.