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Process Chain for Numerical Simulation of IMLS
Additive layer manufacturing methods imply, among other advantages, extensive flexibility
concerning their ability to realize mass customization. Despite various efforts towards process
enhancement, numerous deficiencies concerning part distortion or residual stresses are still
observable. The present work deals with the definition of an efficient process chain for
numerical simulation of indirect metal laser sintering (IMLS), in order to improve
dimensional accuracy. The underlying method is based on investigations of dilatometric behavior of iron based powder, which is integrated into reaction kinetic models and coupled
with a finite element analysis (FEA). Thus, singular process steps, e. g. solid phase sintering,
phase transformations or infiltration, are numerically modelled with adequate accuracy.
Referring to thermomechanical simulation, possibilities for pre-scaling of part geometries are
presented.Mechanical Engineerin
Thermophysical Phenomena in Metal Additive Manufacturing by Selective Laser Melting: Fundamentals, Modeling, Simulation and Experimentation
Among the many additive manufacturing (AM) processes for metallic materials,
selective laser melting (SLM) is arguably the most versatile in terms of its
potential to realize complex geometries along with tailored microstructure.
However, the complexity of the SLM process, and the need for predictive
relation of powder and process parameters to the part properties, demands
further development of computational and experimental methods. This review
addresses the fundamental physical phenomena of SLM, with a special emphasis on
the associated thermal behavior. Simulation and experimental methods are
discussed according to three primary categories. First, macroscopic approaches
aim to answer questions at the component level and consider for example the
determination of residual stresses or dimensional distortion effects prevalent
in SLM. Second, mesoscopic approaches focus on the detection of defects such as
excessive surface roughness, residual porosity or inclusions that occur at the
mesoscopic length scale of individual powder particles. Third, microscopic
approaches investigate the metallurgical microstructure evolution resulting
from the high temperature gradients and extreme heating and cooling rates
induced by the SLM process. Consideration of physical phenomena on all of these
three length scales is mandatory to establish the understanding needed to
realize high part quality in many applications, and to fully exploit the
potential of SLM and related metal AM processes
Numerical modelling of heat transfer and experimental validation in Powder-Bed Fusion with the Virtual Domain Approximation
Among metal additive manufacturing technologies, powder-bed fusion features
very thin layers and rapid solidification rates, leading to long build jobs and
a highly localized process. Many efforts are being devoted to accelerate
simulation times for practical industrial applications. The new approach
suggested here, the virtual domain approximation, is a physics-based rationale
for spatial reduction of the domain in the thermal finite-element analysis at
the part scale. Computational experiments address, among others, validation
against a large physical experiment of 17.5 of deposited
volume in 647 layers. For fast and automatic parameter estimation at such level
of complexity, a high-performance computing framework is employed. It couples
FEMPAR-AM, a specialized parallel finite-element software, with Dakota, for the
parametric exploration. Compared to previous state-of-the-art, this formulation
provides higher accuracy at the same computational cost. This sets the path to
a fully virtualized model, considering an upwards-moving domain covering the
last printed layers
Evolving Material Porosity on an Additive Manufacturing Simulation with the Generalized Method of Cells
The effect of material porosity on final part distortion and residual stresses in a selective laser sintering manufacturing simulation is presented here. A time-dependent thermomechanical model is used with the open-source FEA software CalculiX. Effective homogenized material properties for Inconel 625 are precomputed using NASAs Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC). The evolving porosity of the material is estimated with each pass of the laser beam during simulation runtime. A comparison with a homogenous model and the evolving model shows that the evolving porous model predicts larger distortions with greater residual stresses
A scalable parallel finite element framework for growing geometries. Application to metal additive manufacturing
This work introduces an innovative parallel, fully-distributed finite element
framework for growing geometries and its application to metal additive
manufacturing. It is well-known that virtual part design and qualification in
additive manufacturing requires highly-accurate multiscale and multiphysics
analyses. Only high performance computing tools are able to handle such
complexity in time frames compatible with time-to-market. However, efficiency,
without loss of accuracy, has rarely held the centre stage in the numerical
community. Here, in contrast, the framework is designed to adequately exploit
the resources of high-end distributed-memory machines. It is grounded on three
building blocks: (1) Hierarchical adaptive mesh refinement with octree-based
meshes; (2) a parallel strategy to model the growth of the geometry; (3)
state-of-the-art parallel iterative linear solvers. Computational experiments
consider the heat transfer analysis at the part scale of the printing process
by powder-bed technologies. After verification against a 3D benchmark, a
strong-scaling analysis assesses performance and identifies major sources of
parallel overhead. A third numerical example examines the efficiency and
robustness of (2) in a curved 3D shape. Unprecedented parallelism and
scalability were achieved in this work. Hence, this framework contributes to
take on higher complexity and/or accuracy, not only of part-scale simulations
of metal or polymer additive manufacturing, but also in welding, sedimentation,
atherosclerosis, or any other physical problem where the physical domain of
interest grows in time
Numerical modelling and experimental validation in Selective Laser Melting
In this work a finite-element framework for the numerical simulation of the heat transfer analysis of additive manufacturing processes by powder-bed technologies, such as Selective Laser Melting, is presented. These kind of technologies allow for a layer-by-layer metal deposition process to cost-effectively create, directly from a CAD model, complex functional parts such as turbine blades, fuel injectors, heat exchangers, medical implants, among others. The numerical model proposed accounts for different heat dissipation mechanisms through the surrounding environment and is supplemented by a finite-element activation strategy, based on the born-dead elements technique, to follow the growth of the geometry driven by the metal deposition process, in such a way that the same scanning pattern sent to the numerical control system of the AM machine is used. An experimental campaign has been carried out at the Monash Centre for Additive Manufacturing using an EOSINT-M280 machine where it was possible to fabricate different benchmark geometries, as well as to record the temperature measurements at different thermocouple locations. The experiment consisted in the simultaneous printing of two walls with a total deposition volume of 107 cm3 in 992 layers and about 33,500 s build time. A large number of numerical simulations have been carried out to calibrate the thermal FE framework in terms of the thermophysical properties of both solid and powder materials and suitable boundary conditions. Furthermore, the large size of the experiment motivated the investigation of two different model reduction strategies: exclusion of the powder-bed from the computational domain and simplified scanning strategies. All these methods are analysed in terms of accuracy, computational effort and suitable application
Finite Element Thermal Analysis of Metal Parts Additively Manufactured via Selective Laser Melting
In this chapter, a three-dimensional finite element model is developed to simulate the thermal behavior of the molten pool in selective laser melting (SLM) process. Laser-based additive manufacturing (AM) is a near net shape manufacturing process able to produce 3D objects. They are layer-wise built through selective melting of a metal powder bed. The necessary energy is provided by a laser source. The interaction between laser and material occurs within a few microseconds, hence the transient thermal behavior must be taken into account. A calibration procedure is carried out to fit the numerical solution with the experimental data. Once the calibration has corrected the thermal parameters, a dynamic mesh refinement is applied to reduce the computational cost. The scanning strategy adopted by the laser is simulated by a path simulator built using MatLab®, while numerical analysis is carried out using ANSYS®, a commercial finite element software. To improve the performance of the simulation, the two codes interact each other to solve the analysis. Temperature distribution and geometrical feature of the molten pool under different process conditions are investigated. Results from the FE analysis provide guidance for setting up the optimization of process parameters and develop a base for further residual stress analysis
Modeling and simulation of sintering process across scales
Sintering, as a thermal process at elevated temperature below the melting
point, is widely used to bond contacting particles into engineering products
such as ceramics, metals, polymers, and cemented carbides. Modelling and
simulation as important complement to experiments are essential for
understanding the sintering mechanisms and for the optimization and design of
sintering process. We share in this article a state-to-the-art review on the
major methods and models for the simulation of sintering process at various
length scales. It starts with molecular dynamics simulations deciphering
atomistic diffusion process, and then moves to microstructure-level approaches
such as discrete element method, Monte--Carlo method, and phase-field models,
which can reveal subtle mechanisms like grain coalescence, grain rotation,
densification, grain coarsening, etc. Phenomenological/empirical models on the
macroscopic scales for estimating densification, porosity and average grain
size are also summarized. The features, merits, drawbacks, and applicability of
these models and simulation technologies are expounded. In particular, the
latest progress on the modelling and simulation of selective and direct-metal
laser sintering based additive manufacturing is also reviewed. Finally, a
summary and concluding remarks on the challenges and opportunities are given
for the modelling and simulations of sintering process.Comment: 45 pages, 38 figure
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