Ness, Kari LovisePaul, ArindamSun, LiZhang, Zhiliang...
13页
查看更多>>摘要：Additive manufacturing (AM) is an emerging manufacturing technology that constructs complex parts through layer-by-layer deposition. The prediction and control of thermal fields during production of AM parts are of crucial importance as the temperature distribution and gradient dictates the microstructures, properties, and performance. Finite element (FE) analyses are commonly conducted to simulate the thermal history of the AM process, but are known to be costly and time-consuming. This paper aims to address the challenge by presenting the essential components of a generic data-driven control framework. The proposed framework utilizes extremely randomized trees and is trained and tested on datasets generated through FE simulations. The datasets contain generic, engineered features constructed based on the physics of the underlying thermal process. The features are transferable between a wide range of cases and have achieved mean absolute percentage errors (MAPE) below 2.5% for predicting nodal temperature profiles. In addition, predictions of entire simulations with machine learning (ML) models trained on datasets from different cases have been conducted with MAPE below 5%. The results demonstrate the transferability of thermal histories between several geometries and significantly reduce the need for expensive FE simulations. We believe that these findings are an important step towards realtime optimization in AM.
查看更多>>摘要：In this work, the hydrostatic pressure-dependency of the distortional plasticity model HAH(20) was implemented using a finite element (FE) code to account for the strength-differential (SD) effect that has been observed in advanced high-strength steel sheets. To this end, a fully-implicit stress update algorithm formulation was introduced for the pressure-dependent plasticity theory. The implementation was validated by comparing the FE prediction of the material behavior during a number of tests with those of a stand-alone code of the constitutive description as well as with experimental data. In order to investigate the SD effect on the springback simulation results, the U-draw bending test was analyzed within this FE framework. Furthermore, in order to assess the effectiveness and stability of the formulation for a large-scale example, forming simulations of an automotive structural part were conducted. In addition to the SD effect, strain path changes and geometrical aspects were also investigated in this example. It was shown that the distortional plasticity-based pressure-dependent yield criterion well describes the asymmetric SD behavior in sheet metal forming simulations.
查看更多>>摘要：This paper provides a quantitative understanding of grain nucleation and growth at the interface of SS316L and IN625 bimetallic structures during directed energy deposition (DED) through multi-physics simulations, including phase-field models and computational fluid dynamics analysis. The main finding is that the flow be-haviors would lead to composition redistribution and the change of liquidus temperature in the mixing zone at the interface, which further influences the solidification sequence and the final grain structure that are different from general single-metal counterparts without the mixing zone. The results show that during depositing IN625 on SS316L, a gradual transition in composition distribution and liquidus temperature in the well-mixing zone caused by simple clockwise flow leads to epitaxial grain growth from the SS316L substrate and the prevalence of columnar grains with a low undercooling ( 1 K) condition. However, when depositing SS316L on IN625, it turns out that initial solidification can occur due to abrupt compositional change at the interface where the well-mixing breaks are caused by two opposite (clockwise and counterclockwise) flow behaviors. Such an abrupt compositional change results in high liquidus temperatures that may trigger the grain nucleation in the middle melt pool due to a high undercooling ( 30 K); thus, a mixed grain microstructure is present.
查看更多>>摘要：Due to the anisotropy characteristic of beta-Sn grain, the microstructure and orientation of Sn-based solder joints are closely related to the reliability of the solder joints. In this paper, the effects of cooling rate and solder ball size on beta-Sn morphology and orientation in Sn-3.0Ag-0.5Cu (SAC305) freestanding solder balls and SAC305/Cu ball grid array (BGA) solder joints were firstly investigated to reveal the process dependence of beta-Sn grain features. Three dominant solidified morphologies, i.e., interlaced & beach ball-like grains with three orientations, multiple twin grains with three orientations and single grain with one orientation, were found in the solder balls/joints. Solder ball size showed more significant impact than cooling rate on the morphologies that interlaced & beach ball-like grains and multiple grains were mainly presented in small sized solder balls/joints (<= 400 mu m) and single grain was mainly presented in large sized solder balls/joints (>= 700 mu m). These three solidified morphologies were nucleated and developed from two nucleus model. That is, the interlaced & beach ball-like grains and multiple twin grains morphologies were attributed to {101} nucleus model, while the single grain morphology was attributed to single grain nucleus model. Regardless of whether the solder balls/joints nucleated and solidified based on the {101} or single grain nucleus model, large theta angle beta-Sn grains were proved to have a formation probability higher than 77 % both theoretically and experimentally, and this formation probability had little relationship with interfacial Cu6Sn5 grains, cooling rate and solder ball size.
查看更多>>摘要：Materials fabricated by laser powder bed fusion (LPBF) are generally characterized with internal defects, inhomogeneous microstructure and rough surface with multiple forms of irregularities in their as-built state. Post-treatments are needed to resolve the issues associated with these imperfections. In this study, the individual and synergistic effects of different post-treatments including heat treatment, shot peening and ultrasonic nanocrystalline surface modification on microstructure, surface morphology, roughness, mechanical, corrosion and tribological properties of LPBF AlSi10Mg specimens have been investigated. Two different sets of parameters were considered for the surface treatments, both with mechanical energy source. Apart from surface characteristics, various properties including microhardness and residual stresses as well as wear and corrosion behavior of post-processed specimens were analyzed and compared with those of the as-built condition. The results indicated that hybrid post-treatments have the highest positive effects on wear and corrosion resistance as their kinetic energy affected multiple physical aspects; these include the microstructure leading to surface grain refinement paired with deep compressive residual stress field and improved surface morphology offering a more regular surface.
NSTL
Elsevier