scholarly journals Simultaneous optimization of build orientation and topology for self-supported enclosed voids in additive manufacturing

2022 ◽  
Vol 388 ◽  
pp. 114227
Author(s):  
Cunfu Wang
Keyword(s):  
Additive Manufacturing ◽  
Simultaneous Optimization ◽  
Build Orientation ◽  
And Topology

Study on using generative and topology design for feature enrichment in Mars Rovers

2021 ◽  
pp. 87-93
Author(s):  
Abhijith Ram C ◽  
D Ajith
Keyword(s):  
Additive Manufacturing ◽  
Solar System ◽  
Weight Reduction ◽  
Topology Design ◽  
Space Travel ◽  
Design For Additive Manufacturing ◽  
And Topology ◽  
Flexibility Design ◽  
The Origin Of Life ◽  
The Universe

Space travel has always been a crucial task. Exploration and experimenting on Planets in our solar system will help us understand the universe better and also, we could find the origin of life. Rovers play an important role in finding these answers. The problem we have at present is not only with technology to explore the universe but also the ability of our rockets to carry rovers to other rocks. Since a large amount of fuel is required for Space travel, we end with very little cargo that can be sent to explore. As additive manufacturing started to play a vital part in Mechanical Science, we are going to try to use that tool to build a Generative design that helps in parts consolidation, weight reduction, increase flexibility, design optimisation and cost consolidation. Since weight is an important aspect, we could reduce the present rover weight and add additional scientific tools to the rover to increase its scope of search and applications. This project focuses on features enrichment in Rovers by optimizing rover weight and design using Design for Additive Manufacturing concept.

Optimization of profile and damping layer of plates embedded with acoustic black hole indentations for broadband energy dissipation

2022 ◽  
pp. 1045389X2110721
Author(s):  
Wei Huang ◽  
Chongcong Tao ◽  
Hongli Ji ◽  
Jinhao Qiu
Keyword(s):  
Black Hole ◽  
Energy Dissipation ◽  
Vibration Suppression ◽  
Optimal Solution ◽  
Simultaneous Optimization ◽  
Optimal Arrangement ◽  
Focusing Effect ◽  
Upper Limit ◽  
And Topology ◽  
Design Variables

Acoustic Black Hole (ABH) plate structure has shown promising potentials of vibration suppression above a cut on frequency. For energy dissipation below the cut on frequency, however, the ABH is less effective due to the absence of wave focusing effect. This work reports a simultaneous optimization of ABH plates for broadband energy dissipation. Two sets of design variables of ABH plates, that is, geometry of the profile and topology of the damping layer, are optimized in an alternatively nested procedure. A novel objective function, namely the upper limit of kinetic energy, is proposed. Modeling of ABH structures is implemented and dynamic characteristic is solved using finite element method. A rectangular plate embedded with two ABH indentations is presented as a numerical example. Influence of frequency ranges in the calculation and mass ratios of the damping layer on results are discussed. The achieved optimal arrangement of the damping layer is found to cover equally, if not more, above the non-ABH (uniform) part of the plate than the ABH area. This is inconsistent with the conventional believe that damping layers should cover as much of the ABH area as possible. Mechanism of the broadband energy dissipation by the optimal solution is demonstrated.

A statistical method for build orientation determination in additive manufacturing

2019 ◽  
Vol 25 (1) ◽  
pp. 187-207 ◽  
Author(s):  
Yicha Zhang ◽  
Ramy Harik ◽  
Georges Fadel ◽  
Alain Bernard
Keyword(s):  
Additive Manufacturing ◽  
Statistical Method ◽  
Supervised Machine Learning ◽  
Surface Model ◽  
Generic Level ◽  
Content Type ◽  
Build Orientation ◽  
Cad Models ◽  
Feature Based ◽  
Orientation Determination

Purpose For part models with complex shape features or freeform shapes, the existing build orientation determination methods may have issues, such as difficulty in defining features and costly computation. To deal with these issues, this paper aims to introduce a new statistical method to develop fast automatic decision support tools for additive manufacturing build orientation determination. Design/methodology/approach The proposed method applies a non-supervised machine learning method, K-Means Clustering with Davies–Bouldin Criterion cluster measuring, to rapidly decompose a surface model into facet clusters and efficiently generate a set of meaningful alternative build orientations. To evaluate alternative build orientations at a generic level, a statistical approach is defined. Findings A group of illustrative examples and comparative case studies are presented in the paper for method validation. The proposed method can help production engineers solve decision problems related to identifying an optimal build orientation for complex and freeform CAD models, especially models from the medical and aerospace application domains with much efficiency. Originality/value The proposed method avoids the limitations of traditional feature-based methods and pure computation-based methods. It provides engineers a new efficient decision-making tool to rapidly determine the optimal build orientation for complex and freeform CAD models.

Multi-Component Topology Optimization for Powder Bed Additive Manufacturing (MTO-A)

2018 ◽  
Author(s):  
Yuqing Zhou ◽  
Tsuyoshi Nomura ◽  
Kazuhiro Saitou
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Simultaneous Optimization ◽  
Previous Attempt ◽  
Numerical Instability ◽  
Feature Size ◽  
Powder Bed ◽  
Nonlinear Projection ◽  
Gradient Based ◽  
Length Width

This paper presents a gradient-based multi-component topology optimization (MTO) method for structures assembled from components made by powder bed additive manufacturing. It is built upon our previous work on the continuously-relaxed MTO framework utilizing the concept of fractional component membership. The previous attempt on the integration of the relaxed MTO framework with additive manufacturing constraints, however, suffered from numerical instability for larger size problems, limiting its application to 2D low-resolution examples. To overcome this difficulty, this paper proposes an improved MTO formulation based on a design field regularization and a nonlinear projection of component membership variables, with a focus on powder bed additive manufacturing. For each component, constraints on the maximum allowable build volume (i.e., length, width, and height), the elimination of enclosed voids, and the minimum printable feature size are imposed during the simultaneous optimization of the overall base topology and component partitioning. The scalability of the new MTO formulation is demonstrated by a few 2D examples with much higher resolution than previously reported, and the first reported 3D example of MTO.

Algorithm to Reduce Leading and Lagging in Conformal Direct-Print

2018 ◽  
Vol 140 (10) ◽  
Author(s):  
Morteza Vatani ◽  
Faez Alkadi ◽  
Jae-Won Choi
Keyword(s):  
Additive Manufacturing ◽  
3D Printing ◽  
3D Model ◽  
Three Dimensional ◽  
Motion Direction ◽  
B Spline ◽  
And Topology ◽  
Printing System ◽  
3D Printed ◽  
Printed Patterns

A novel additive manufacturing algorithm was developed to increase the consistency of three-dimensional (3D) printed curvilinear or conformal patterns on freeform surfaces. The algorithm dynamically and locally compensates the nozzle location with respect to the pattern geometry, motion direction, and topology of the substrate to minimize lagging or leading during conformal printing. The printing algorithm was implemented in an existing 3D printing system that consists of an extrusion-based dispensing module and an XYZ-stage. A dispensing head is fixed on a Z-axis and moves vertically, while the substrate is installed on an XY-stage and moves in the x–y plane. The printing algorithm approximates the printed pattern using nonuniform rational B-spline (NURBS) curves translated directly from a 3D model. Results showed that the proposed printing algorithm increases the consistency in the width of the printed patterns. It is envisioned that the proposed algorithm can facilitate nonplanar 3D printing using common and commercially available Cartesian-type 3D printing systems.

Additive manufacturing of 316L stainless-steel structures using fused filament fabrication technology: mechanical and geometric properties

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Miguel Ángel Caminero ◽  
Ana Romero ◽  
Jesús Miguel Chacón ◽  
Pedro José Núñez ◽  
Eustaquio García-Plaza ◽  
...  
Keyword(s):  
Stainless Steel ◽  
Additive Manufacturing ◽  
Austenitic Stainless Steel ◽  
Material Properties ◽  
Steel Structures ◽  
Fused Filament Fabrication ◽  
Geometric Properties ◽  
Content Type ◽  
Build Orientation ◽  
Manufacturing Alternatives

Purpose Fused filament fabrication (FFF) technique using metal filled filaments in combination with debinding and sintering steps can be a cost-effective alternative for laser-based powder bed fusion processes. The mechanical behaviour of FFF-metal materials is highly dependent on the processing parameters, filament quality and adjusted post-processing steps. In addition, the microstructural material properties and geometric characteristics are inherent to the manufacturing process. The purpose of this study is to characterize the mechanical and geometric performance of three-dimensional (3-D) printed FFF 316 L metal components manufactured by a low-cost desktop 3-D printer. The debinding and sintering processes are carried out using the BASF catalytic debinding process in combination with the BASF 316LX Ultrafuse filament. Special attention is paid on the effects of build orientation and printing strategy of the FFF-based technology on the tensile and geometric performance of the 3-D printed 316 L metal specimens. Design/methodology/approach This study uses a toolset of experimental analysis techniques [metallography and scanning electron microcope (SEM)] to characterize the effect of microstructure and defects on the material properties under tensile testing. Shrinkage and the resulting porosity of the 3-D printed 316 L stainless steel sintered samples are also analysed. The deformation behaviour is investigated for three different build orientations. The tensile test curves are further correlated with the damage surface using SEM images and metallographic sections to present grain deformation during the loading progress. Mechanical properties are directly compared to other works in the field and similar additive manufacturing (AM) and Metal Injection Moulding (MIM) manufacturing alternatives from the literature. Findings It has been shown that the effect of build orientation was of particular significance on the mechanical and geometric performance of FFF-metal 3-D printed samples. In particular, Flat and On-edge samples showed an average increase in tensile performance of 21.7% for the tensile strength, 65.1% for the tensile stiffness and 118.3% for maximum elongation at fracture compared to the Upright samples. Furthermore, it has been able to manufacture near-dense 316 L austenitic stainless steel components using FFF. These properties are comparable to those obtained by other metal conventional processes such as MIM process. Originality/value 316L austenitic stainless steel components using FFF technology with a porosity lower than 2% were successfully manufactured. The presented study provides more information regarding the dependence of the mechanical, microstructural and geometric properties of FFF 316 L components on the build orientation and printing strategy.

Automated Geometric Correction System for Additive Manufacturing Considering Build Orientation

2021 ◽  
pp. 1-30
Author(s):  
Seyedeh Elaheh Ghiasian ◽  
Kemper Lewis
Keyword(s):  
Additive Manufacturing ◽  
Optimization Model ◽  
Experimental Validation ◽  
Minimal Amount ◽  
Feature Size ◽  
Build Orientation ◽  
Computational Performance ◽  
The Difference ◽  
Processing Effort ◽  
Correction System

Abstract One of the current challenges for the additive manufacturing (AM) industry lies in providing component designs compatible with the AM manufacturability and constraints without compromising the component structural functionalities. To address this challenge, we present an automated correction system that provides geometrically feasible designs for additive processes by applying locally effective modifications while avoiding substantial changes in the current designs. Considering a minimum printable feature size from the process parameters, this system identifies the problematic features in an infeasible part's design using a holistic geometric assessment algorithm. Based on the obtained manufacturability feedback, the system then corrects the detected problematic regions using a set of appropriate redesign solutions through an automated procedure. In addition, to reduce the difference between the current and modified part geometries, a novel optimization model for build orientation is presented. Using this model, one can identify appropriate orientations for obtaining a feasible design with a minimal amount of corrections while also reducing the post-processing effort by minimizing the area of contact with the support structure. The functionalities of the presented correction system and the optimization model are illustrated using a number of case studies with varying geometries. The computational performance of the system and an experimental validation are also presented to demonstrate the effectiveness of the implemented detection and modification approaches.

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