Freeform Features Research Articles

Evaluation of the Freeform Feature of Solid works Parametric

Evaluation of the Freeform Feature of Solid works Parametric

Versatile computer-aided design of free-form DNA nanostructures and assemblies.

Recent advances in structural DNA nanotechnology have been facilitated by design tools that continue to push the limits of structural complexity while simplifying an often-tedious design process. We recently introduced the software MagicDNA, which enables design of complex 3D DNA assemblies with many components; however, the design of structures with free-form features like vertices or curvature still required iterative design guided by simulation feedback and user intuition. Here, we present an updated design tool, MagicDNA 2.0, that automates the design of free-form 3D geometries, leveraging design models informed by coarse-grained molecular dynamics simulations. Our GUI-based, stepwise design approach integrates a high level of automation with versatile control over assembly and subcomponent design parameters. We experimentally validated this approach by fabricating a range of DNA origami assemblies with complex free-form geometries, including a 3D Nozzle, G-clef, and Hilbert and Trifolium curves, confirming excellent agreement between design input, simulation, and structure formation.

Self-activating metal-polymer composites for the straightforward selective metallization of 3D printed parts by stereolithography

The integration of multifunctional elements directly embedded in three-dimensional (3D) printed parts is the cutting-edge of additive manufacturing (AM) and it is crucial for enlarging as well as for strengthening AM role in industrial applications. Here, a straightforward and low-cost method that synergically combines stereolithography (SLA) and selective electroless metallization (EM) is presented for the fabrication of 3D parts characterized by complex shapes and end-use multifunctionalities (conductive, magnetic, mechanical properties). To this end, a novel photocurable composite based on acrylate resin loaded with nickel (Ni) particles is developed for high-resolution SLA-printing of features with self-catalytic properties for EM. Ni particles are loaded in the resin to trigger metal deposition avoiding time consuming and expensive laser-based surface activation. The effect of Ni content on SLA behavior as well as on the efficiency of EM process is studied. Metallized SLA cured samples show good electrical and magnetic properties as well as improved robustness with respect to their non-loaded counterparts. Then, selective metallization of 3D printed parts is successfully achieved by implementing a multi-material SLA-printing where loaded and non-loaded resins are properly interchanged with strong adhesion at the interface, thus offering a cost-effective approach for rapid prototyping of functional free-form features on 3D structures.

EVALUATION OF 3-AXIS AND 5-AXIS MILLING STRATEGIES WHEN MACHINING FREEFORM SURFACE FEATURES

The article deals with the comparison and evaluation of milling strategies, which are available in CAM systems and are used for the production of components with freeform surfaces. For the purpose of the experiment a test sample with a repeating shape feature was designed. First half of the test sample shape features were machined using 3-Axis milling strategies while second half was performed with strategies available on 5-Axis CNC machining centre. Simulated machining times as well as virtually machined surfaces using color maps with deviation values were evaluated by employed CAM software. Obtained data was used to evaluate the performance of 3-Axis and 5-Axis milling centre both individually and mutually. These results will be used to compare software data with data obtained from real sample production. The main goal is to verify the reliability of the results provided by CAM systems in the production of parts with freeform feature surfaces.

Investigating the Effect of Screw Size on the Stress Level in MERO Joint for Space Frame Structures

Space frame structures satisfy the ever-increasing requirements of societies for providing a variety of structural forms and architectural spaces with special characteristics, such as aesthetic and free-form features, population-wise capacities, and structural performance, among others. Structural behavior of these systems largely depend on the type of joints and their components which are to be considered appropriately in design and analysis. Screws comprise one of the key components of joints in these structures and play a pivotal role in the total cost of the structure, as well as the maximum stress level created in joints. The present study aims to evaluate the effect of screw size on the maximum stress generated in three MERO double-layer ball joints with diameters of 98, 110, and 132 mm as a sample numerical analysis case to pinpoint this fact. Numerical simulations were conducted using ANSYS workbench software. Based on the results, in order to achieve the maximum factor of safety (FOS), the minimum stress, and keeping the total construction cost optimal, it is recommended to use M16, M20, and M24 screws for the ball joints of diameters 98, 110, and 132 mm, respectively.

From regional sensitivity to intra-sensitivity for parametric analysis of free-form shapes: Application to ship design

Robust Parametric Sensitivity Analysis (PSA) is a prerequisite for efficient shape optimisation via parametric modelling. A major challenge PSA has to handle is related to the fact that a parameter can be sensitive in certain local areas of the design space but become insensitive in others. Therefore, setting an applicable space for this analysis becomes a difficult task. In this paper, we introduce the concept of intra-sensitivity to identify parameters whose perturbation has a major impact on the sensitivity index of the remaining parameters. For this purpose, we firstly appeal to Active Subspace Method (ASM) and develop an ASM-based regional sensitivity analysis, which investigates parametric sensitivity in local regions of the design space and aids conducing to parameters’ intra-sensitivity. This regional analysis is applied in conjunction with a Dynamic Propagation Sampling approach, for tackling the computational complexity arising when high-dimensional problems are concerned. Once sensitive and intra-sensitive parameters are identified, then free-form features, correlated to these parameters, are evaluated using a feature saliency map built with the aid of Hausdorff distance. The so resulting methodology has been validated in the area of computer-aided ship design using two parametric modellers: the first one is a Procedural Deformation (PD) modeller which is based on T-splines and involves 24 parameters while the second one is based on Free-Form Deformation (FFD) and involves 104 parameters. The corresponding design spaces have been generated using a parent hull close to the KCS container ship and are analysed against hull’s volume of displacement and total resistance. Finally, the convergence performance of the various components of this approach is compared with state-of-the-art techniques.

An optimization algorithm for automatic structural design

We propose a new algorithm to design lightweight and stiff structures exhibiting free-form features, with the aim of minimizing the compliance under a volume inequality constraint. The procedure is based on the coupling of geometric shape optimization with topology optimization. We start from a full-mass body corresponding to a given material occupying entirely the initial design domain. The first phase of geometric shape optimization acts as an out-of-the-box paradigm. It allows one to modify the initial design domain by acting only on its boundary, keeping the same volume and topology. With respect to the full-mass body, this phase reduces the compliance to a large extent. The successive step of topology optimization does actually change the topology of the structure, e.g., by introducing holes, reduces the volume according to the volume constraint, but does not affect the boundary of the structure, which is fixed by the previous phase. Overall, the combined approach allows us to design a new structure, that is lighter and stiffer with respect to the full-mass body. Additionally, the employment of a structure-tailored computational mesh, via an anisotropic mesh adaptation procedure during topology optimization, yields an intrinsically smooth final layout characterized by free-form features. An extensive numerical assessment corroborates both qualitatively and quantitatively the performances of the proposed optimization algorithm.

Free-Form Feature Classification for Finite Element Meshing based on Shape Descriptors and Machine Learning

Free-Form Feature Classification for Finite Element Meshing based on Shape Descriptors and Machine Learning

Design of a Single-Lens Freeform-Prism-Based Distortion-Free Stereovision System

Stereo vision can be achieved with a single camera aided by a flat-face prism. However, large optical distortions may be caused by irregular refraction. To mitigate this deficiency and minimize distortion, a new freeform prism design is proposed to replace the flat-face prism. All refracting surfaces of the prism are designed for freeform features, which can process object points at a large depth of field. Differential equations are derived to express the freeform surface, and the Runge–Kutta method is used to numerically solve the differential equations.

Topology optimization driven by anisotropic mesh adaptation: Towards a free-form design

We propose the new adaptive algorithm SIMPATY for topology optimization to design lightweight and stiff structures exhibiting free-form features. This is achieved by properly combining the classical SIMP method with an anisotropic mesh adaptation strategy based on a recovery-based a posteriori error estimator. Mesh adaptivity allows us to contain (and, for simple structures, even to eliminate) the filtering usually adopted in a topology optimization context. Thus, the final layout is intrinsically smooth, so that the post-processing phase can be strongly reduced (or even skipped), and the structure can directly move on to the production manufacturing phase. A free-form design is also enhanced by anisotropic mesh adaptivity. An extensive numerical validation supports these remarkable properties.

Rapid and Precise Reverse Engineering of Complex Geometry Through Multi-Sensor Data Fusion

This paper presents an effective multi-sensor approach for improving the accuracy of laser scanner by using a tactile probe to perform rapid and accurate reverse engineering of complex objects. The proposed system is unique in that it includes not only the physical integration of the two digitizers but also their combination at the measurement information level. With the coordinate data acquired using the optical scanner, intelligent data segmentation and feature recognition algorithm are proposed to divide the original point set into geometric elements and free-form surfaces. The tactile probe is guided to re-measure each feature with a small number of sampling points. Then different data fusion algorithms are proposed to compensate the scanned data patches of geometric features and free-form features with the accurate tactile probing data. Finally, the compensated point data can be exploited for accurate reverse engineering of a CAD model. Through the fusion of different sensor’s information, both sensors complement each other with their advantages. Experimental results show that for the measurement of geometric surface, the proposed method can improve the accuracy of optical measurement to the accuracy of contact measurement. For free-form surface measurement, the proposed method reduces the optical measurement error from +0.032/−0.019 mm to ±0.016 mm, and the standard deviation from 0.012 mm to 0.004 mm. The measurement efficiency of proposed method is 4.5 times higher than that of contact measurement alone.

Pattern Design of Freeform Features on Triangular Meshes

Pattern Design of Freeform Features on Triangular Meshes

A novel classification of freeform volumetric features and generative CAPP approach for milling machine selection

Feature recognition is an important function of computer-aided process planning (CAPP) system. The freeform feature recognition works performed so far have resulted in successful classification and recognition of freeform surface-based features, but the works do not classify and recognize freeform volumetric features. The research works like automatic generation of delta volume (DV) for volumetric features, finishing, and roughing process were successful when applied to regular form parts, but generated a complex DV for roughing process when applied to freeform parts. Also, the DV generation works do not generate DV for freeform features. So an effort is made (i) to newly classify freeform volumetric features and develop an algorithm to automatically generate DV for freeform volumetric features; (ii) to automatically recognize freeform volumetric features by a set of conditions and colour coding concept; and (iii) to determine the level of complexity and milling machine selection. The problem of complex DV is overcome by generation of sub-delta volume for transition (SDVT). The algorithm is able to recognize freeform volumetric features and the DV’s quantitative data, exploded view, and labelling will aid the downstream activities of CAPP system. The algorithm validation result shows a percentage error of 0.005% for complex part like impeller.

A Microlens Array with Different Focal Lengths Fabricated by Roll-To-Roll UV Lithography

A simple, highly efficient and low cost roll-to-roll (R2R) UV imprinting lithography facility was achieved for fabricating micro-structures. Firstly, a novel microlens array with focuses distributed on a curved surface was designed and analyzed by an optical software ZEMAX. Then an ultra-precision diamond machine was applied to generate the freeform microlens array features on the master mold, and a belt-type polydimethylsiloxane (PDMS) mold with a microlens array pattern was prepared from the machined master mold. The R2R process was employed to replicate the microlens arrays, followed by an evaluation of their profiles and optical properties. Our experiments demonstrate that the applied method is reliable and efficient for producing the polymeric microlens arrays.

Freeform Machining Feature Recognition with Manufacturability Analysis

As an important information bridge connecting design and manufacturing, feature recognition has been intensively researched. However, most researches focused on regular shaped features. Unlike regular shaped features, freeform features are usually partitioned into faces and regions for the selection of proper machining tools and parameters to meet design specifications and improve machining efficiency. In this paper, a novel recognition method for freeform machining features combining both curvature-based segmentation and manufacturability analysis-based segmentation is developed. A hierarchical representation of freeform machining features is presented. A case study is presented to demonstrate the capability of the proposed method.

Fabrication of freeform progressive addition lenses using a self-developed long stroke fast tool servo

A long stroke fast tool servo (LFTS) system with a maximum stroke range of ±4 mm based on the voice coil actuator was developed and integrated on a diamond turning machine (DTM) for the fabrication of freeform progressive addition lenses (PALs). The LFTS utilized a three-ring cascade control system for the motion trajectory control of a diamond tool. The numerical control codes of the tool path were transferred from the 3D surface data with freeform features. The complete process chain from tool path generation and diamond machining to power measurement was experimentally demonstrated. The obtained surface form accuracy was 6.7 μm (rms), and the measured power of the PAL agreed well with the theoretical design indicating the desirable processing capability of LFTS for the customized freeform spectacle optics.

Comparison of Milling Strategies when Machining Freeform Surfaces

The article deals with comparison and evaluation of the milling strategies that are available in CAM systems and are used to produce components with freeform surfaces. For the purpose of the experiment, sample with freeform features was designed to employ different milling strategies when 3 axis machining. Evaluation of the milling strategies was carried out by surface roughness measurement, comparison of the actual machining time with a simulation time as well as visual control of the sample surface with a surface obtained in simulation. Acquired research results can be utilized within production process of tools with sculptured surfaces, such as tools for metal sheet forming, dies, molds for plastics and many others.

Procedural mesh features applied to subdivision surfaces using graph grammars

A typical industrial design modelling scenario involves defining the overall shape of a product followed by adding detail features. Procedural features are well-established in computer aided design (CAD) involving regular forms, but are less applicable to free-form modelling involving subdivision surfaces. Current approaches do not generate sparse subdivision control meshes as output, which is why free-form features are manually modelled into subdivision control meshes by domain experts. Domain experts change the local topology of the subdivision control mesh to incorporate features into the surface, without increasing the mesh density unnecessarily and carefully avoiding the appearance of artefacts.In this paper we show how to translate this expert knowledge to grammar rules. The rules may then be invoked in an interactive system to automatically apply features to subdivision surfaces.

Transient thermal modeling of laser-based additive manufacturing for 3D freeform structures

Additive layer manufacturing is growing very fast in various industries such as biomedical, aircraft, and aerospace industries. There is a need for developing simulation tools for predicting transient temperature fields in additive layer manufacturing of three-dimensional (3D) complex parts in these industries. Transient temperature fields in additive manufacturing are critical due to the fact that transient temperatures directly affect residual stresses, microstructure, fatigue life, 3D distortions, and deformations of produced parts. Considering this industrial need, this article introduces a new approach to 3D transient thermal analysis for additive manufacturing for 3D complex industrial structures with freeform features in powder bed systems using laser heat source. Incorporating the features of phase changes, porous media, and temperature-dependent thermal material properties in COMSOL Multiphysics, the developed technique is able to simulate instantaneous transient temperature fields in additive layer manufacturing of 3D complex and freeform structures. Temperature model validations are performed on titanium alloy with the experimental temperature measurements available in the literature. It is observed that the predicted model simulation results agree well with the experimental measurements.

Characterization of shape and dimensional accuracy of incrementally formed titanium sheet parts with intermediate curvatures between two feature types

Abstract Single point incremental forming (SPIF) is a relatively new manufacturing process that has been recently used to form medical grade titanium sheets for implant devices. However, one limitation of the SPIF process may be characterized by dimensional inaccuracies of the final part as compared with the original designed part model. Elimination of these inaccuracies is critical to forming medical implants to meet required tolerances. Prior work on accuracy characterization has shown that feature behavior is important in predicting accuracy. In this study, a set of basic geometric shapes consisting of ruled and freeform features were formed using SPIF to characterize the dimensional inaccuracies of grade 1 titanium sheet parts. Response surface functions using multivariate adaptive regression splines (MARS) are then generated to model the deviations at individual vertices of the STL model of the part as a function of geometric shape parameters such as curvature, depth, distance to feature borders, wall angle, etc. The generated response functions are further used to predict dimensional deviations in a specific clinical implant case where the curvatures in the part lie between that of ruled features and freeform features. It is shown that a mixed-MARS response surface model using a weighted average of the ruled and freeform surface models can be used for such a case to improve the mean prediction accuracy within ±0.5 mm. The predicted deviations show a reasonable match with the actual formed shape for the implant case and are used to generate optimized tool paths for minimized shape and dimensional inaccuracy. Further, an implant part is then made using the accuracy characterization functions for improved accuracy. The results show an improvement in shape and dimensional accuracy of incrementally formed titanium medical implants.