Free-form Shapes Research Articles

Automatic control method for freeform surface shapes.

Designing freeform optics with high degrees of freedom can improve their optical performances; however, there are high requirements for controlling the surface shapes of such optics. Optical designers need to add constraints to the optimization process and make repeated adjustments to ensure the manufacturability of these shapes; this process is cumbersome and relies heavily on the experience of the designer. In this study, an automatic control method for freeform surface shapes is proposed. By adding an outer loop to the optimization process, the principal curvature and sag departure of the sampling points are gradually controlled during the optimization cycle based on the system requirements and surface evaluation results. The method was implemented in CODE V and successfully applied to a design example in freeform prism optics.

Low-cost photoreactors for highly photon/energy-efficient solar-driven synthesis

Low-cost photoreactors for highly photon/energy-efficient solar-driven synthesis

A Study of Free-Form Shape Rationalization Using Biomimicry as Inspiration.

Bridging the gap between the material and geometrical aspects of a structure is critical in lightweight construction. Throughout the history of structural development, shape rationalization has been of prime focus for designers and architects, with biological forms being a major source of inspiration. In this work, an attempt is made to integrate different phases of design, construction, and fabrication under a single framework of parametric modeling with the help of visual programming. The idea is to offer a novel free-form shape rationalization process that can be realized with unidirectional materials. Taking inspiration from the growth of a plant, we established a relationship between form and force, which can be translated into different shapes using mathematical operators. Different prototypes of generated shapes were constructed using a combination of existing manufacturing processes to test the validity of the concept in both isotropic and anisotropic material domains. Moreover, for each material/manufacturing combination, generated geometrical shapes were compared with other equivalent and more conventional geometrical constructions, with compressive load-test results being the qualitative measure for each use case. Eventually, a 6-axis robot emulator was integrated with the setup, and corresponding adjustments were made such that a true free-form geometry could be visualized in a 3D space, thus closing the loop of digital fabrication.

Free form shape optimization of three dimensional beams using cross section analysis

We introduce an efficient method for shape optimization of three dimensional beams that is based on free-form design of the beam’s cross section. The cross section boundary of each beam segment is parameterized by a closed, unclamped B-spline curve, whose control points’ coordinates serve as design variables. The response of the beam is evaluated globally as a one-dimensional entity using 3D beam finite elements, while each cross section is modeled locally using cross section analysis following anisotropic beam theory. A fully consistent analytical sensitivity analysis is derived to account for the relation between the control points and the beam cross-sectional properties and design updates are performed using gradient-based optimization. The proposed method is applied to several test cases, aiming at minimization of compliance or maximization of the fundamental frequency. The numerical results and a comparison to other methods for beam optimization show that the method can generate highly competitive designs. A consistent quantitative comparison to high resolution continuum topology optimization shows that a performance which is only slightly inferior can be achieved, for only a small fraction of the computational effort.

Elliptical specularity detection in endoscopy with application to normal reconstruction.

To detect specularities as elliptical blobs in endoscopy. The rationale is that in the endoscopic setting, specularities are generally small and that knowing the ellipse coefficients allows one to reconstruct the surface normal. In contrast, previous works detect specular masks as free-form shapes and consider the specular pixels as nuisance. A pipeline combining deep learning with handcrafted steps for specularity detection. This pipeline is general and accurate in the context of endoscopic applications involving multiple organs and moist tissues. A fully convolutional network produces an initial mask which specifically finds specular pixels, being mainly composed of sparsely distributed blobs. Standard ellipse fitting follows for local segmentation refinement in order to only keep the blobs fulfilling the conditions for successful normal reconstruction. Convincing results in detection and reconstruction on synthetic and real images, showing that the elliptical shape prior improves the detection itself in both colonoscopy and kidney laparoscopy. The pipeline achieved a mean Dice of 84% and 87% respectively in test data for these two use cases, and allows one to exploit the specularities as useful information for inferring sparse surface geometry. The reconstructed normals are in good quantitative agreement with external learning-based depth reconstruction methods manifested, as shown by an average angular discrepancy of [Formula: see text] in colonoscopy. First fully automatic method to exploit specularities in endoscopic 3D reconstruction. Because the design of current reconstruction methods can vary considerably for different applications, our elliptical specularity detection could be of potential interest in clinical practice thanks to its simplicity and generalisability. In particular, the obtained results are promising towards future integration with learning-based depth inference and SfM methods.

A comprehensive study of A357 alloy printability via laser metal deposition

Laser metal deposition (LMD) is one of the most important techniques in additive manufacturing (AM) thanks to the high flexibility of the process, which makes the production of free-form shapes possible. However, working with some materials presents some challenges. This is the case with aluminum alloys due to their reflectivity and their very high thermal conductivity. On the other hand, aluminum and its alloys are quite important in several industrial fields, including aerospace, among others, due to their mechanical properties with low density. In this work, LMD is applied on an A357 aluminum alloy. The techniques are investigated moving from a single-track approach up to multi-pass and multi-layer strategies. Densities, microstructures and mechanical performance are investigated as a function of process parameters. Porosities are reduced, resulting in overall densities of over 97% and microhardness values are in the range of 80–100 HV. Differences in mechanical performance are analysed considering different building directions, showing a dependency on loading direction and the distance from the substrate. Tensile tests reveal a promising performance for further investigation with the LMD technique. The obtained evidence is interesting for future trends where large and light components are required while maintaining the mechanical performance of traditional manufacturing methods. Moreover, a comprehensive study is done for the first time on A357 alloy that is deeply used in the aerospace and automotive fields. The investigation and definition of the best process parameters open the possibility of exploiting LMD technology in the production of wide components or for adding features to already existing components overcoming some limits of other AM technologies.

Mesh modeling of system geometry and anatomy phantoms for realistic GATE simulations and their inclusion in SPECT reconstruction

Objective. Monte-Carlo simulation studies have been essential for advancing various developments in single photon emission computed tomography (SPECT) imaging, such as system design and accurate image reconstruction. Among the simulation software available, Geant4 application for tomographic emission (GATE) is one of the most used simulation toolkits in nuclear medicine, which allows building systems and attenuation phantom geometries based on the combination of idealized volumes. However, these idealized volumes are inadequate for modeling free-form shape components of such geometries. Recent GATE versions alleviate these major limitations by allowing users to import triangulated surface meshes. Approach. In this study, we describe our mesh-based simulations of a next-generation multi-pinhole SPECT system dedicated to clinical brain imaging, called AdaptiSPECT-C. To simulate realistic imaging data, we incorporated in our simulation the XCAT phantom, which provides an advanced anatomical description of the human body. An additional challenge with the AdaptiSPECT-C geometry is that the default voxelized XCAT attenuation phantom was not usable in our simulation due to intersection of objects of dissimilar materials caused by overlap of the air containing regions of the XCAT beyond the surface of the phantom and the components of the imaging system. Main results. We validated our mesh-based modeling against the one constructed by idealized volumes for a simplified single vertex configuration of AdaptiSPECT-C through simulated projection data of 123I-activity distributions. We resolved the overlap conflict by creating and incorporating a mesh-based attenuation phantom following a volume hierarchy. We then evaluated our reconstructions with attenuation and scatter correction for projections obtained from simulation consisting of mesh-based modeling of the system and the attenuation phantom for brain imaging. Our approach demonstrated similar performance as the reference scheme simulated in air for uniform and clinical-like 123I-IMP brain perfusion source distributions. Significance. This work enables the simulation of complex SPECT acquisitions and reconstructions for emulating realistic imaging data close to those of actual patients.

Direct ink writing 3D-printed optical waveguides for multi-layer interconnect.

Low-cost, short-range optical interconnect technology plays an indispensable role in high-speed board-level data communications. In general, 3D printing technology can easily and quickly produce optical components with free-form shapes, while the traditional manufacturing process is complicated and time-consuming. Here, we present a direct ink writing 3D-printing technology to fabricate optical waveguides for optical interconnects. The waveguide core is 3D printed optical polymethylmethacrylate (PMMA) polymer, with propagation loss of 0.21 dB/cm at 980 nm, 0.42 dB/cm at 1310 nm, and 1.08 dB/cm at 1550 nm, respectively. Furthermore, a high-density multilayer waveguide arrays, including a four-layer waveguide arrays with a total of 144 waveguide channels, is demonstrated. Error-free data transmission at 30 Gb/s is achieved for each waveguide channel, indicating that the printing method can produce optical waveguides with excellent optical transmission performance. We believe this simple, low-cost, highly flexible, and environmentally friendly method has great potential for high-speed short-range optical interconnects.

Compensation machining of freeform based on fast tool servo system.

With the advantages of large field of view, low cost and simple structure, the freeform optical system has extensive requirements in space exploration and other fields. However, the current machining methods for freeform are difficult to meet the requirements of optical use. Based on a developed fast servo tool (FTS) device, this paper proposes an error compensation turning method for freeforms. Firstly, the Zernike polynomial fitting method is used to reconstruct the freeform surface shape error obtained from off-line measurement, and the offset compensation is used to correct the tool path. Then, the compensation processing physical system is built to simulate the off-line compensation processing of the workpiece to verify the feasibility of compensation processing. Finally, the turning compensation processing of convex freeform aluminum mirror is carried out, and the surface accuracy of the workpiece meets the requirements of visible band. The research results have important practical significance for realizing the fast response machining of free-form surface mirror.

Embedded 3D Printing of Architected Ceramics via Microwave-Activated Polymerization.

Light- and ink-based 3D printing methods have vastly expanded the design space and geometric complexity of architected ceramics. However, light-based methods are typically confined to a relatively narrow range of preceramic and particle-laden resins, while ink-based methods are limited in geometric complexity due to layerwise assembly. Here, embedded 3D printing is combined with microwave-activated curing to generate architected ceramics with spatially controlled composition in freeform shapes. Aqueous colloidal inks are printed within a support matrix, rapidly cured via microwave-activated polymerization, and subsequently dried and sintered into dense architectures composed of one or more oxide materials. Thisintegrated manufacturing method opens new avenues for the design and fabrication of complex ceramic architectures with programmed composition, density, and form for myriad applications.

Multiple wavelength digital holography for freeform shape measurement and lens alignment.

This paper introduces a technique for freeform optical surface measurements using digital holography with multiple discrete wavelengths or wavelength scans. This experimental arrangement, i.e.,a Mach-Zehnder holographic profiler, is optimized to achieve maximal theoretical precision and is capable of measuring freeform diffuse surfaces. Moreover, the approach can also be used for diagnostics of precise placement of elements within optical systems.

Laser‐Induced Graphene Enabled Additive Manufacturing of Multifunctional 3D Architectures with Freeform Structures (Adv. Sci. 4/2023)

3D Printing In article number 2204990 by Fu Liu, Yan Gao, Sida Luo, and co-workers, a laser-induced graphene based additive manufacturing (LIG-AM) is developed to print bulk 3D graphene with freeform shapes such as variable-section turbine structures. By investigating particle-sintering and graphene-converting dual-mechanism as well as process dependent properties, multifunctional 3D LIG architectures are further demonstrated its potential applications in aerospace and future manufacturing field.

Investigation on Subsurface Damage Patterns in Ultrashort Pulse Laser Machining of Glass using Optical Coherence Tomography

Ultrashort pulse (USP) laser ablation is gaining popularity as a novel manufacturing technique for brittle materials, enabling the creation of complex freeform shapes that are challenging to produce with conventional optics manufacturing techniques. Freeforms have revolutionized optics manufacturing by providing designers with increased degrees of freedom using non-rotational symmetric components. However, this evolution presents new challenges for manufacturing processes, calling for innovative solutions such as USP ablation. To ensure the industrial viability of areal USP laser machining, it is crucial to not only consider material removal rates but also surface quality and subsurface damage (SSD). Especially for optical applications, harsh quality requirements must be met. This study investigates the SSD patterns of fused silica (FS) and borosilicate glass N-BK7 (BK) processed under different laser wavelengths, beam geometries and processing parameters using high-resolution optical coherence tomography (OCT). It is shown that OCT as non-destructive and 3D evaluation method is well-suited for analysing USP processes. The discovered differences in defect morphology between FS and BK emphasize the importance of selecting appropriate processes and process parameters when working with different materials. Compared to previous studies, for the parameter sets analysed here using OCT, much higher defects depths of up to 441 µm were revealed.

Design tools for metal additive manufacturing: a critical and perspective overview

Metal Additive Manufacturing is quite expensive and very different from traditional schemes. The possibility of realizing lightweight products with free-form shapes increases the interest in this technology in the industry. The main limitations of the widespread of Metal Additive Manufacturing concern the high cost of materials and 3D printers, and the necessity of post-processing activities. Additive Manufacturing generally claims different design constraints if compared to traditional manufacturing technologies. The improvements in 3D Metal Printing are increasing the design practices in Additive Manufacturing. The design workflow for Additive Manufacturing includes different tools and methods to manage the design complexity. These tools are CAD/CAE software, numerical simulations, database, etc. They mostly are the updated versions of already existing tools. Therefore, these tools are not directly developed to support the phases of Additive Manufacturing. The paper analyzes the main functionalities of Design for Metal Additive Manufacturing tools. The critical analysis suggests the necessity to improve the interactive practices between users and tools along the design workflow. A more interactive approach to design could reduce the gap between the definition of the part geometry and the parameter settings for the additive process.

Broad Temperature Plateau for High Thermoelectric Properties of n-Type Bi2Te2.7Se0.3 by 3D Printing-Driven Defect Engineering

High-energy-conversion Bi2Te3-based thermoelectric generators (TEGs) are needed to ensure that the assembled material has a high value of average figure of merit (ZTave). However, the inferior ZTave of the n-type leg severely restricts the large-scale applications of Bi2Te3-based TEGs. In this study, we achieved and reported a high peak ZT (1.33) of three-dimensional (3D)-printing n-type Bi2Te2.7Se0.3. In addition, a superior ZTave of 1.23 at a temperature ranging from 300 to 500 K was achieved. The high value of ZTave was obtained by synergistically optimizing the electronic- and phonon-transport properties using the 3D-printing-driven defect engineering. The nonequilibrium solidification mechanism facilitated the multiscale defects formed during the 3D-printed process. Among the defects formed, the nanotwins triggered the energy-filtering effect, thus enhancing the Seebeck coefficient at a temperature range of 300-500 K. The effective scattering of wide-frequency phonons by multiscale defects reduced the lattice thermal conductivity close to the theoretical minimum of ∼0.35 W m-1 k-1. Given the advantages of 3D printing in freeform device shapes, we assembled and measured bionic honeycomb-shaped single-leg TEGs, exhibiting a record-high energy conversion efficiency (10.2%). This work demonstrates the great potential of defect engineering driven by selective laser melting 3D-printing technology for the rational design of advanced n-type Bi2Te2.7Se0.3 thermoelectric material.

Isogeometric neural networks: A new deep learning approach for solving parameterized partial differential equations

We present a new physics-based machine learning approach for solving parameterized partial differential equations (PDEs) over generalized domains. Central to this method is the coupling of isogeometric representation with deep learning. This approach represents both the physical domain and the solution to a PDE as a linear combination of non-uniform rational B-spline (NURBS) basis functions and employs a deep feed-forward neural network to predict NURBS solution coefficients. Trained networks output the coefficients of NURBS to approximate PDE solutions for an entire range of physical and shape variables. Desirable aspects of the NURBS basis, such as its local support, refinement properties, and its capacity to represent freeform shapes compactly, are synergistically integrated with the ability of neural networks to learn hidden and non-linear mappings. Novel features of this isogeometric neural network (IGN) approach include its ability to perform physics-based learning over changing domains and efficient hierarchical learning. In contrast to classical PDE forward-solving techniques such as finite element analysis and isogeometric analysis, the IGN is able to learn PDE solutions for a range of parametric variables. We show empirically that no labeled data is required to obtain high-fidelity approximations to the solutions of parameterized PDEs. To demonstrate the efficacy of the IGN, 1D and 2D problems of various physics are addressed.

Comparison of dimples and grooves based on friction and leakage properties of textured mechanical seals

PurposeThis study aims to obtain a design scheme of the surface texture on mechanical seal with lower friction and leakage by comparing two common texture types: dimples and grooves.Design/methodology/approachAn optimal free-form shape and an optimal circular shape were chosen by multi-objective optimization, and two types of grooves with different directions were chosen by a series of experiments. Then, the optimal free-form dimple, the optimal circular dimple, the groove perpendicular to the direction of movement (hereafter called groove-1) and the groove angled at 60° to the direction of movement (hereafter called groove-2) were compared by experiments under different loads.FindingsThe optimal free-form dimple shows a better performance in terms of a lower coefficient of friction (COF) and a lower leakage than the other shapes, especially for the high speed and low load conditions. The reduction rate of COF is up to 37.5%, and the leakage rate is reduced by about 12.5%. The dimples have a lower leakage than the grooves. The groove angled at 60° to the direction of movement is easier to pump the oil into the interface of the sealing face, leading to a lower friction but a higher leakage.Originality/valueThis study provides a feasible surface texture design scheme for improving the combination performance of mechanical seals.

Cylindrical surface shape measurement method and measurement comparison

Optical elements are used in various fields, in which it is required to measure spherical, aspherical, and free-form surface shapes. We use a nanoprofiler previously developed by our research group to measure a cylindrical surface shape. Unlike spherical or aspherical shapes, the cylindrical surface shape of free-form surface is rotationally asymmetrical and thus difficult to determine the measured position. Therefore, we processed fiducial marks on the measured sample and specified the measurement position by fiducial marks. Then we performed comparative measurements with a Fizeau interferometer using a computer generated hologram (CGH) as a reference plane. The nanoprofiler and interferometer measured to accuracies of 43.7 nm peak-to-valley (PV) and 60.9 nm PV, respectively; the difference between the two was 17.2 nm PV. Furthermore, a spherical shape and an aspherical shape were similarly measured by both devices. The spherical shape had a difference of 8.4 nm PV and that of the aspherical shape was 9.7 nm PV; thus the difference between the measurements of the cylindrical surface shape was larger. Considering that the guaranteed accuracy of CGH for measuring a cylindrical surface shape is ∼30 nm PV, we concluded that this is a reasonable result and fiducial marks are effective to determine the position.

Topology optimization of thermal cloaks in euclidean spaces and manifolds using an extended level set method

Thermal cloaks are devices designed to shield an object against thermal detection, which have attracted growing interest in research. This paper proposes to design thermal cloaks using the level-set-based shape and topology optimization in the context of pure heat conduction. The cloaking effect is achieved by optimizing the distribution of two bulk heat conductive materials to eliminate the temperature disturbance induced by the introduction of the insulator (cloaking region) into a homogeneous thermal conduction medium. The optimized thermal cloaks are free of high anisotropy and nonhomogeneity commonly seen in the popular transformation thermotics or scattering cancellation methods. Due to the clear boundary characteristic of the level set representation, no sophisticated filtering techniques are required to suppress the appearance of ”gray regions” as opposed to the density-based topology optimization methods. Considering the fact that the device components that need to be thermally cloaked, e.g., sensors, can take an arbitrary free-form shape, a conformal thermal cloak on the manifold is also topologically optimized using the extended level set method (X-LSM), which has not been reported in the literature. The structural boundary is evolved by solving the (modified) Hamilton-Jacobi equation. The feasibility and robustness of the proposed method to design thermal meta-devices with cloaking functionality are demonstrated through a number of 2D and 3D (solid and shell) numerical examples with different cloaking regions (circular, human-shaped, spherical, and curved circular). This work may shed light on further exploration of the thermal meta-devices in the heat flux manipulation regime.

Free-Form Shape Optimization of Advanced High-Strength Steel Members

The high yielding strength of advanced high-strength steel (AHSS) provides great opportunities for cold-formed steel (CFS) members with much higher load-carrying capability. However, if manufactured into the traditional cross-section shapes, such as C and Z, the material advantage cannot be fully exploited due to the cross-section instabilities. The purpose of this study was to establish a shape optimization method for cold-formed sections with AHSS and explore the potentially material efficiency that AHSS could provide to these sections in terms of their axial strength. In this study, the insights provided from the elastic buckling analysis and nonlinear finite element (FE) simulations of a set of traditional CFS sections were employed to determine the appropriate section size and length for optimization. Then, the optimization method was established using the particle swarm optimization (PSO) algorithm with the integration of computational analysis through CUFSM and the design approach (i.e., the direct strength method, DSM). The objective function is the maximum axial strength of the CFS sections manufactured with AHSS using the same amount of material (i.e., the same cross-section area). Finally, the optimal sections were simulated and verified by FE analysis, and the characteristics of the optimal cross-sections were analyzed. Overall, the optimization method in this paper achieved good optimization results with greatly improved axial strength capacity from the optimal sections.