Neural-network based approach to optimize THz computer generated holograms

Terahertz (THz) optics often encounters the problem of small f number values (elements have relatively small diameters comparing to focal lengths). The need to redirect the THz beam out of the optical axis or form particular intensity distributions resulted in the application of iterative holographic methods to design THz diffractive elements. Elements working on-axis do not encounter significant improvement while using iterative holographic methods, however, for more complicated distributions the difference becomes meaningful. Here, we propose a totally different approach to design THz holograms, utilizing a neural network based algorithm, suitable also for complicated distributions. Full Text: PDF ReferencesY. Tao, A. Fitzgerald and V. Wallace, "Non-Contact, Non-Destructive Testing in Various Industrial Sectors with Terahertz Technology", Sensors, 20(3), 712 (2020). CrossRef J. O'Hara, S. Ekin, W. Choi and I. Song, "A Perspective on Terahertz Next-Generation Wireless Communications", Technologies, 7(2), 43 (2019). CrossRef L. Yu et al., "The medical application of terahertz technology in non-invasive detection of cells and tissues: opportunities and challenges", RSC Advances, 9(17), 9354 (2019). CrossRef A. Siemion, "The Magic of Optics—An Overview of Recent Advanced Terahertz Diffractive Optical Elements", Sensors, 21(1), 100 (2020). CrossRef A. Siemion, "Terahertz Diffractive Optics—Smart Control over Radiation", J. Infrared Millim. Terahertz Waves, 40(5), 477 (2019). CrossRef M. Surma, I. Ducin, P. Zagrajek and A. Siemion, "Sub-Terahertz Computer Generated Hologram with Two Image Planes", Appl. Sci., 9(4), 659 (2019). CrossRef S. Banerji and B.Sensale-Rodriguez, "A Computational Design Framework for Efficient, Fabrication Error-Tolerant, Planar THz Diffractive Optical Elements", Sci. Rep., 9(1), 5801 (2019). CrossRef J. Sun and F. Hu, "Three-dimensional printing technologies for terahertz applications: A review", Int. J. RF. Microw. C. E., 30(1) (2020). CrossRef E. Castro-Camus, M. Koch and A. I. Hernandez-Serrano, "Additive manufacture of photonic components for the terahertz band", J. Appl. Phys., 127(21), 210901 (2020). CrossRef https://community.wolfram.com/groups/-/m/t/2028026?p_%20479%20p_auth=blBtLb5d DirectLink P. Komorowski, et al., "Three-focal-spot terahertz diffractive optical element-iterative design and neural network approach", Opt. Express, 29(7), 11243-11253 (2021) CrossRef M. Sypek, "Light propagation in the Fresnel region. New numerical approach", Opt. Commun., 116(1-3), 43 (1995). CrossRef

Robotic Spatial Printing For Designers

<p>This research developed a fully-integrated robotic printing system, using new methods of additive manufacture (AM) that enables users to explore spatially printed structures with increased freedom of geometric complexity. Current AM technologies, such as Fusion Deposition Modelling (FDM), can rapidly translate design ideations into solid forms by precisely depositing consecutive layers of material in coordination with the movements of a robotic platform. Using this method, solid objects are digitally deconstructed into linear toolpaths and physically reconstituted with thermoplastic extrusion equipment; the toolpath becomes the form. Spatial printing, using methods such as those demonstrated in this research, offers a new way of building 3D forms. By harnessing the potential of FDM equipment and materials for generating self-supporting structures, the user can create complex free-standing structures unshackled from the layered constraints of typical additive manufacturing processes. Here, the user acts as an informed negotiator between digital form and physical manifestation where movement realises form. A complete spatial printing system was built that harnesses the complexity of robotic movements and responds to the needs of printing materials through a feedback loop that draws from the results of experimentation. Bespoke printing equipment and computational processes strive to improve the craft qualities and printability of input materials with a specific focus on compatibility with co-extrusion biopolymer filaments developed by Scion. This thesis illustrates the development of a versatile spatial printing system and subsequent investigations into the craft qualities and freedom of complexity that this system offers to designers and architects.</p>

Robotic Spatial Printing For Designers

<p>This research developed a fully-integrated robotic printing system, using new methods of additive manufacture (AM) that enables users to explore spatially printed structures with increased freedom of geometric complexity. Current AM technologies, such as Fusion Deposition Modelling (FDM), can rapidly translate design ideations into solid forms by precisely depositing consecutive layers of material in coordination with the movements of a robotic platform. Using this method, solid objects are digitally deconstructed into linear toolpaths and physically reconstituted with thermoplastic extrusion equipment; the toolpath becomes the form. Spatial printing, using methods such as those demonstrated in this research, offers a new way of building 3D forms. By harnessing the potential of FDM equipment and materials for generating self-supporting structures, the user can create complex free-standing structures unshackled from the layered constraints of typical additive manufacturing processes. Here, the user acts as an informed negotiator between digital form and physical manifestation where movement realises form. A complete spatial printing system was built that harnesses the complexity of robotic movements and responds to the needs of printing materials through a feedback loop that draws from the results of experimentation. Bespoke printing equipment and computational processes strive to improve the craft qualities and printability of input materials with a specific focus on compatibility with co-extrusion biopolymer filaments developed by Scion. This thesis illustrates the development of a versatile spatial printing system and subsequent investigations into the craft qualities and freedom of complexity that this system offers to designers and architects.</p>

316L WAAM and pressure machining influence

Wire arc additive manufacture (WAAM) technology has a good development prospect, and can be used to manufacture large metal components with complex shapes in combination with traditional machining equipment. This paper adjusts the parameters from the perspective of heat input and arc control. It is found that the stacking quality of 316L stainless steel is the best when the arc voltage is 40V and the arc current is 360A. It is proposed to obtain the flat layers by pressure machining after every layer is stacked, which can create favorable conditions for manufacturing large-size components. And through the hot rolling experiment, it is proved that pressure machining can improve the density and uniformity of the microstructure, and thus enhance the comprehensive mechanical properties of components built by WAAM.

Topology Optimization and Design for Additive Manufactured Supporting Structure of Vehicle Rudder

The object investigated in this work is a design method for the supporting structure of vehicle rudders, which are the crucial components in flight control system. As a practical application of topology optimization for additive manufacture, the design process was presented in this article. To obtain the optimal material distribution, topology optimization based on SIMP method was applied, with compliance minimization as the optimization objective. A numerical optimization model was built and calculated in Inspire, and the result in an equivalent load scheme of 30 percent point load and 70 percent uniform pressure was adopted to be the initial geometry for the subsequent design. Concentrating on realizing the optimized geometry, this design took a series of technical constrains for additive manufacture and mass requirements into consideration. Notably, the FEM simulation for the supporting structure is necessary, which consist of stress analysis and mode analysis. And the technical feasibility was verified in its practical manufacturing process. Finally, by the experiment about dynamic characteristic, it is verified that the lightweight rudder designed in this work can satisfy all the requirements for flight control.

A data-centric approach to generative modelling for 3D-printed steel

The emergence of additive manufacture (AM) for metallic material enables components of near arbitrary complexity to be produced. This has potential to disrupt traditional engineering approaches. However, metallic AM components exhibit greater levels of variation in their geometric and mechanical properties compared to standard components, which is not yet well understood. This uncertainty poses a fundamental barrier to potential users of the material, since extensive post-manufacture testing is currently required to ensure safety standards are met. Taking an interdisciplinary approach that combines probabilistic mechanics and uncertainty quantification, we demonstrate that intrinsic variation in AM steel can be well described by a generative statistical model that enables the quality of a design to be predicted before manufacture. Specifically, the geometric variation in the material can be described by an anisotropic spatial random field with oscillatory covariance structure, and the mechanical behaviour by a stochastic anisotropic elasto-plastic material model. The fitted generative model is validated on a held-out experimental dataset and our results underscore the need to combine both statistical and physics-based modelling in the characterization of new AM steel products.