Research

Modeling and simulation of SLS-3D printing process

Modeling and simulation of SLS-3D printing process

  Research by: Timo Schmidt More than 50% of the raw materials handled in industry appear in particulate form, which is why an optimal powder might be of interest for industry. However, it is obvious that optimal needs to be defined for each application in a different way. This research project is focused on the SLS-3D printing process, where repeatedly layers of particles are created and sapped by a laser to create the final product. A Discrete Element Method is used to analyze the behavior of the particles in the layer. Moreover, the impact on the density of particles per volume depending on the friction and damping properties of the particles is...

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Smoothed Particle Hydrodynamics for Multiphysics Simulations

Smoothed Particle Hydrodynamics for Multiphysics Simulations

  Research by: Chang Yoon Park Smoothed Particle Hydrodynamics provides a way to approximate field derivatives with a set of unstructured points. Due to its simplicity and ease of implementation, it has gained great traction for solving problems related to free-surface fluid flows. Unfortunately, due to several drawbacks of the conventional/traditional SPH formulations, it was never a massively popular choice for solving solid mechanics problems / non-newtonian fluid flow problems. To overcome the previous difficulties researchers have been facing when using SPH for such problems, I am developing new approaches based on total lagrangian SPH formulations and implicit time stepping schemes. These numerical methods can then be used as a framework simulate various additive-manufacturing situations, such as direct-ink-writing...

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Particle Method for Simulation of Selective Laser Sintering Process

Particle Method for Simulation of Selective Laser Sintering Process

  Research by: Roger Isied Picture from: A coupled discrete element-finite difference model of selective laser sintering–Rishi Ganeriwala and Tarek I. Zohdi Selective Laser Sintering (SLS) and Selective Laser Melting (SLM) are emerging as popular additive manufacturing processes due to their ability to create custom geometries in a vast range of materials such as polymers, composites, and most notably, metals. These processes work by repeatedly depositing a layer of material powder onto a print bed and utilizing a laser to either sinter or melt the layer of particles in a selected region such that it forms the cross-section of the desired geometry. While it provides much functionality, it is currently limited due to large defects that are frequent and inconsistent in even simple geometries. Furthermore, parts fabricated from this process almost always require some form of post processing to address macro and microscope defects and to create features that were not feasible with the SLS/SLM process. Understanding how the controllable parameters of this process can be optimized is essential for the industry to better trust this versatile manufacturing process for a wider scale of applications. This can be done through numerical simulation of these manufacturing processes. This dynamic and multiphysics nature of this process cannot be modeled using standard FEM packages as it would be too computationally expensive. I am focused on discretizing the manufacturing process into each of its physical parameters through the use of meshless particle-based methods such as the Discrete Element Method. In doing so, I can begin modeling this process by implementing a kinematic simulation of the deposition of the particles as well as a thermodynamic simulation of their heating by lasers. Moving forward, I hope to model other aspects of the process such as the laser physics and the effect of geometry on subsequent layer...

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Thermomechanical Simulation for Robotic IR Camera Monitoring of Thermomechanical Surface Processes

Thermomechanical Simulation for Robotic IR Camera Monitoring of Thermomechanical Surface Processes

  Research by: Donghoon Kim, Youngkyu Kim, David Alcantara Many surface treatment processes involve some sort of energy transfer to the treated part. This transfer can cause thermal stresses due to temperature gradients and ultimately deteriorate the treated part. To reduce the effects from energy deposition, it is necessary to monitor the state of the part which is nontrivial due to “hidden” states that cannot be monitored, such as internal temperatures and thermal stresses. The project aims to couple an IR camera reading the part’s surface temperature with thermomechanical simulation to infer the hidden states. Ultimately, the simulation’s output will be used to determine where the camera should be repositioned for more accurate state computation. Thus, the simulation must be performed in real time to keep up with incoming IR camera data. A multitude of simulation methods will be explored, such as the material point method (MPM) and lattice-Boltzmann method (LBM). These solution methods will be coupled with other processes such as machine learning (ML) to speed up the solver and Kalman filters for data assimilation as the computer receives more IR images over...

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Material Point Method

Material Point Method

  Research by: Youngkyu Kim       Solving mechanical problems including large deformation, fracture, and, impact can result in numerical issues. To solve governing equations, a Lagrangian description or an Eulerian description can be used. In Lagrangian methods, the computational mesh deforms with the material. So, in the case of large deformation, fracture, and impact, Lagrangian methods cause mesh distortion leading to mesh entanglement. On the other hand, in Eulerian methods, the governing equations are solved using a fixed grid. Thus, the Eulerian description can handle highly deformed motion. However, tracking material points is difficult to implement, so the Eulerian description has trouble with history dependent constitutive laws. To overcome disadvantages of purely Lagrangian methods and Eulerian methods, a Material Point Method (MPM) is introduced. MPM uses both the Lagrangian description based on a set of material points and the Eulerian description based on the fixed computational grid. In Lagrangian formulation, material points move with the deformation and are used to track the material variables such as position, mass, momentum, stress, and strain. Hence, there is no need to worry about mesh entanglement. In Eulerian formulation, a fixed computational grid is employed to compute a spatial gradient. Furthermore, a convective term in the material time derivative doesn’t have to be considered because a fixed grid performs a role of an Lagrangian frame at every time step. Numerical examples are given to illustrate advantages of MPM.      ...

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A material point method framework for simulation of additive manufacturing processes

A material point method framework for simulation of additive manufacturing processes

  Research by: Erden Yildizdag In this study, we develop a material point method (MPM) framework to simulate additive manufacturing processes. The MPM is one of the extensions of the particle-in-cell (PIC) method which has been used in computational fluid dynamics (CFD) applications since 1960s. The main idea behind the material point method is to take advantages of both Eulerian and Lagrangian descriptions which are two different approaches used in the field of mechanics. In material point method, continuum field is represented with a set of particles (material points). All the physical quantities such as mass, stress, deformation gradient, heat flux, and temperature are stored in particles. The particles flow through a fixed background grid and within each time step, and the data stored in particles is mapped into the background grid to solve the governing equations of the problem (e.g. balance of linear momentum, balance of energy) in a similar manner to the finite element method. Then, the particle data is updated remapping the nodal solution from the background grid. In order to validate our numerical framework, we first considered isothermal droplet impingement problem. The droplet was modeled as an incompressible Newtonian fluid and MPM simulations were validated with COMSOL’s multiphysics solver for two-phase flow modeling with the level set method with different viscosity and surface tension values.   MPM vs....

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Fully Three-Dimensional Process Planning for Additive Manufacturing

Fully Three-Dimensional Process Planning for Additive Manufacturing

  Research by: Maxwell Micali While additive manufacturing and 3D printing have achieved notoriety for their abilities to manufacture complex three-dimensional parts, the state of the art is not truly three-dimensional. Rather, the process plans rely on a stack of discretized two-dimensional layers. Discretization of smooth, freeform features results in printed parts with stair-stepped surfaces, increasing the total volumetric error of the part and potentially diminishing the intended performance of functional surfaces. By performing process planning in a fully three-dimensional domain, as opposed to the 2.5D status quo, the capabilities of additive manufacturing are enhanced and the technologies can be more fully leveraged by designers and...

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Particle method to simulate the flow through marine current turbines

Particle method to simulate the flow through marine current turbines

  Research by: David Fernandez-Gutierrez The Ocean represents a massive energy resource that can be employed for electricity generation. This fact has led to the growing interest ocean-driven energy generation over the last decade. This research project focuses on the development of a novel particle method to simulate the flow through marine current turbines. Ultimately, the goal of the project is to evaluate the probability and potential damage of collisions on the turbine blades from solid elements dragged by currents, and to optimize design modifications to mitigate such events. The proposed numerical method arises from the Smoothed Particle Hydrodynamics (SPH) and Finite Element Method (FEM) philosophies, with emphasis placed on particle-infiltrated...

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Non-invasive repair of piping systems

Non-invasive repair of piping systems

  Research by: Zeyad Zakey The use of piping systems is ubiquitous in several engineering applications, including process plants, factories, and oil refineries. Concerning the latter, it is of priority to maintain structural integrity of all systems to ensure constant operation. However, due to natural wear and tear, corrosion, or other else, piping systems may become damaged during use. In order to repair the system, it must be isolated. This entails stoppage of operation, resulting in loss of operating time and profit. The aim of this project was to propose an alternative method of repair. We hope to investigate a technique where solid particles are inserted into a pipe flow, while an external field is applied to guide the particles to a damage or target site. This is the first step. Secondly, as particles gather at the site, they will be fused in place via some other physical mechanism. Our study involved the first step of the process, accumulation of particles at the site. The problem setup consists of a fully developed laminar flow within a cylindrical pipe. Solid particles are inserted into the flow. The parameters of interest for the problem are the max flow velocity of the flow, the externally applied magnetic field strength, and the particle radii. The video above shows an example for a velocity of 5 m/s with a 1.5 Tesla magnetic field and a particle size of 200 microns. The video is part of a collaborative work done by Mukherjee et. al. (2013). As part of the paper, a non-dimensional scaling was done. Future work entails running the code with several parameter sets while seeing the relationship to a particle accumulation efficiency....

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Multi-scale particle methods for improved heat transfer

Multi-scale particle methods for improved heat transfer

Syd Hashemi email: sydhashemi@berkeley.edu Research description Overview Although computer simulation power has astronomically increased since the beginning of the simulation by computers, and still is increasing, machine performance is still a limiting factor. This primarily restricts the size of the system that can be simulated, for example in the case of molecular dynamics the number of particles that can be handled with the computer, and the number of timesteps that can be calculated during the simulation is part of this restriction. Besides, to capture an important phenomena in the macro scale level, one needs much larger simulation time and extremely large number of particles, but in a conventional MD simulation, a great deal of computing time is used for uninteresting individual particle behavior. As a consequence, there still are problems for which a simulation turns out to be inefficient or even intractable. In this research, I study Dissipative Particle Dynamics (DPD), a method invented for carrying out particle based simulations of hydrodynamic behavior. I tried to use dissipative particle dynamics to address the problem of calculating heat transfer on some applications. In order to do that, the DPD method is used in order to calculate the heat transfer in small scales. Moreover in order to deal with larger scale flow situations a method is developed to couple different scales. Therefore, in combination to the small scale particle model, the continuum model is used to get the higher scale behavior of the flow. The Schematic of domain decomposition is presented in the following figure (top left) The domain decomposition over continuum model in an impinging jet is presented in the top right figure. In the bottom left a particle flow model video is shown for flow in a channel with turbulator and in the bottom right its continuum contour plot is presented http://cmrl.berkeley.edu/wp-content/uploads/part1.mp4 The particle code is used to solve heat transfer problem in some industrial simulation and the result is compared with experiment and CFD simulation. The left figure is heat transfer for flow in a channel with turbulators and right is the heat transfer over a...

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