Cited by Avoiding heat source calibration for finite element modeling of the laser powder bed fusion process

A topical review on AI-interlinked biodomain sensors for multi-purpose applications DOI

Rubi Thapa, Sachin Poudel, Katarzyna Krukiewicz

et al.

Measurement, Journal Year: 2024, Volume and Issue: 227, P. 114123 - 114123

Published: Jan. 10, 2024

Language: Английский

Citations

Regularization in space–time topology optimization for additive manufacturing DOI

Weiming Wang, Kai Wu, Fred van Keulen

et al.

Computer Methods in Applied Mechanics and Engineering, Journal Year: 2024, Volume and Issue: 431, P. 117202 - 117202

Published: Aug. 1, 2024

In additive manufacturing, the fabrication sequence has a large influence on quality of manufactured components. While planning is typically performed after component been designed, recent developments have demonstrated possibility and benefits simultaneous optimization both structural layout corresponding sequence. This particularly relevant in multi-axis where rotational motion offers enhanced flexibility compared to planar fabrication. The approach, called space–time topology optimization, introduces pseudo-time field encode manufacturing process order, alongside pseudo-density representing layout. To comply with principles, needs be monotonic, i.e., free local minima. However, explicitly formulated constraints proposed prior work are not always effective, for complex layouts that commonly result from optimization. this paper, we introduce novel method regularize We conceptualize monotonic as virtual heat conduction starting surface upon which constructed layer by layer. temperature field, shall confused actual during serves an analogy encoding new formulation, use conductivity coefficients variables steer and, consequently, inherently minima due physics it resembles. numerically validate effectiveness regularization under process-dependent loads, including gravity thermomechanical loads.

Language: Английский

Citations

Progress in Vat Photopolymerisation Additive Manufacturing of Ceramic Lattice Structures and Applications DOI

Qumail Arshad,

Muhammad Saqib, Muhammad Sajid Arshad

et al.

Thin-Walled Structures, Journal Year: 2025, Volume and Issue: 209, P. 112918 - 112918

Published: Jan. 6, 2025

Language: Английский

Citations

3D forming space and abnormal lamellar microstructures in a Mg-10Gd-Zr alloy fabricated by laser powder bed fusion DOI

Ziyi Liu, Qingchen Deng, Ziyan Li

et al.

Journal of Magnesium and Alloys, Journal Year: 2025, Volume and Issue: unknown

Published: March 1, 2025

Language: Английский

Citations

Manufacturability and mechanical properties of Ti-35Nb-7Zr-5Ta porous titanium alloys produced by laser powder-bed fusion DOI

HH Cheng,

HW Ma,

Lingling Pan

et al.

Additive manufacturing, Journal Year: 2024, Volume and Issue: 86, P. 104190 - 104190

Published: April 1, 2024

Language: Английский

Citations

Advanced deep operator networks to predict multiphysics solution fields in materials processing and additive manufacturing DOI

Shashank Kushwaha, Jaewan Park, Seid Korić

et al.

Additive manufacturing, Journal Year: 2024, Volume and Issue: 88, P. 104266 - 104266

Published: May 1, 2024

Unlike classical artificial neural networks, which require retraining for each new set of parametric inputs, the Deep Operator Network (DeepONet), a lately introduced deep learning framework, approximates linear and nonlinear solution operators by taking functions (infinite-dimensional objects) as inputs mapping them to complete fields. In this paper, two newly devised DeepONet formulations with sequential Residual U-Net (ResUNet) architectures are trained first time simultaneously predict thermal mechanical fields under variable loading, loading histories, process parameters, even geometries. Two real-world applications demonstrated: 1- coupled thermo-mechanical analysis steel continuous casting multiple visco-plastic constitutive laws 2- sequentially direct energy deposition additive manufacturing. Despite highly challenging spatially target distributions, DeepONets can infer reasonably accurate full-field temperature stress solutions several orders magnitude faster than traditional optimized finite-element (FEA), when FEA simulations run on latest high-performance computing platforms. The proposed model's ability provide field predictions almost instantly unseen input parameters opens door future preliminary evaluation design optimization these vital industrial processes.

Language: Английский

Citations

Modelling grain refinement under additive manufacturing solidification conditions using high performance cellular automata DOI

O. Zinovieva, Aleksandr Zinoviev, Mitesh Patel

et al.

Materials & Design, Journal Year: 2024, Volume and Issue: 245, P. 113248 - 113248

Published: Aug. 18, 2024

Despite increasing applications of additively manufactured parts, they still suffer from anisotropic mechanical properties and can experience cracking due to coarse columnar grain structures induced by metal 3D printing. Microstructural control is promising avenue overcome these challenges, but requires deeper understanding factors controlling solidification, particularly regarding refinement. Addressing this gap, study explores refinement in Al-Cu alloys with a process-microstructure linking cellular automata-finite difference (CAFD) approach supported single-track laser surface remelting (LSR) experiments. To enhance the nucleation behaviour under additive manufacturing solidification conditions, research analyses influence parameters on post-LSR microstructures. Additionally, computational dimensions microstructure modelling, testing CA mesh sensitivity effects benchmarking our CAFD models two high-performance computing platforms. The model captures well key microstructural features observed LSR without refiner addition. It shown that maximum density has significant effect final microstructure, resulting different proportions grains epitaxial newly nucleated thin grains, equiaxed grains.

Language: Английский

Citations

Global Length and Overhang Control for Level Set and Density Approaches via Perimeter Minimization DOI

J. Torres, F. Otero, A. Ferrer

et al.

International Journal for Numerical Methods in Engineering, Journal Year: 2025, Volume and Issue: 126(2)

Published: Jan. 20, 2025

ABSTRACT Topology optimization is probably one of the most efficient techniques for structural design. However, running topology without geometry control provides complex designs, which often are manufactured with additive manufacturing methods. Consequently, a fundamental aspect in to consider following constraints: minimal length scale and overhang. The aim this paper propose new numerical method globally such constraints. idea relies on penalizing regularized version perimeter: an isotropic global anisotropic Besides, we show that may be used density level set approaches. Several examples, including compliant mechanisms material design, some bars have been removed, decreasing complexity shape, vertical tendency orientation boundaries generally obtained.

Language: Английский

Citations

Experimental and computational approaches to optimizing the development of NFs reinforced polymer composite: A review of optimization strategies DOI

Olajesu Favor Olanrewaju, Justus Uchenna Anaele, Sodiq Abiodun Kareem

et al.

Sustainable materials and technologies, Journal Year: 2025, Volume and Issue: unknown, P. e01259 - e01259

Published: Jan. 1, 2025

Language: Английский

Citations

The impact of thermocapillary on equiaxed/columnar microstructure evolution in laser powder bed fusion: A high-fidelity ray-tracing based finite volume and cellular automaton study DOI

Heng Gu,

Yanzhao Fu,

Chao Wei

et al.

Journal of Materials Processing Technology, Journal Year: 2024, Volume and Issue: 326, P. 118335 - 118335

Published: Feb. 8, 2024

Language: Английский

Citations