Pan Michaleris

Measurement of forced surface convection in directed energy deposition additive manufacturing

The accurate modeling of thermal gradients and distortion generated by directed energy deposition additive manufacturing requires a thorough understanding of the underlying physical processes. One area that has the potential to significantly affect the accuracy of thermomechanical simulations is the complex forced convection created by the inert gas jets that are used to deliver metal powder to the melt pool and to shield the laser optics and the molten material. These jets act on part surfaces with higher temperatures than those in similar processes such as welding and consequently have a greater impact on the prevailing heat transfer mechanisms. A methodology is presented here which uses hot-film sensors and constant voltage anemometry to measure the forced convection generated during additive manufacturing processes. This methodology is then demonstrated by characterizing the convection generated by a Precitec® YC50 deposition head under conditions commonly encountered in additive manufacturing. Surface roughness, nozzle configuration, and surface orientation are shown to have the greatest impact on the convection measurements, while the impact from the flow rate is negligible.

Mitigation of distortion in large additive manufacturing parts

Distortion mitigation techniques for large parts constructed by additive manufacturing processes are investigated. Unwanted distortion accumulated during deposition is a common problem encountered in additive manufacturing processes. The proposed strategies include depositing equal material on each side of a substrate to balance the bending moment about the neutral axis of the workpiece and applying heat to straighten the substrate. Simple finite element models are used to predict the effectiveness of the mitigation strategies in order to reduce computation time and to avoid costly experiments. The strategy of adding sacrificial material is shown to be most effective and is then applied to the manufacture of a large electron beam deposited part consisting of several thousand deposition passes. The deposition strategy is shown to reduce the maximum longitudinal bending distortion in the large additive manufacturing part by 91%. It is shown that after the distortion mode of concern is identified, simple finite element models can be used to study distortion accumulation trends relevant to the large part. Experimental observations made here, as well as finite element model results, suggest that the order in which the balancing material is added significantly affects the success of the proposed distortion mitigation strategy.

Modified FETI‐DP Method: FETI‐DP‐RBS‐LNA And Its Applications On Coupled Linear‐Nonlinear Large Scale Welding and Laser Forming Problems

Simulation of large scale problems is a well‐known research topic since it is heavily desired by many science and engineering disciples. However, it also poses many challenges for current available numerical algorithms and computer hardware. In this paper, one domain decomposition (DD) algorithm: the Dual‐Primal Finite Element Tearing and Interconnecting method (FETI‐DP) is carefully investigated, and a reduced back‐substitution (RBS) algorithm is proposed to accelerate the time consuming preconditioned conjugate gradient (PCG) iterations involved in the interface problems. Linear and nonlinear analysis (LNA) is also proposed for large scale welding and laser forming problems. This combined approach is named as the FETI‐DP‐RBS‐LNA algorithm and tested on a 32‐subdomain beam model. The results demonstrate the effectiveness of the proposed computational approach for simulating three dimensional linear‐nonlinear large scale welding and laser forming problems as well as its possible improvement in distributed...

Reduced-order multivariable modeling and nonlinear control of melt-pool geometry and temperature in directed energy deposition

There has been continuing effort in developing analytical, numerical and empirical models of laser-based additive manufacturing (AM) processes in the literature. However, advanced physics-based models that can be directly used for feedback control design, i.e., control-oriented models, are severely lacking. In this paper, we develop a reduced-order (in contrast to finite element models) multivariable model for directed energy deposition. One important difference between our model from the existing work lies in a novel parameterization of the material transfer rate in the deposition as a function of the process operating parameter. Such parameterization allows a more accurate characterization of the steady-state melt-pool geometry compared to the existing lumped-parameter analytical models. Predictions of melt-pool geometry and temperature from our model are validated using experimental data obtained from deposition of Ti-6AL-4V on a laser engineering net shaping (LENS) AM process and finite element analysis. Then based on this reduced-order multivariable model, we design a nonlinear multi-input multi-output (MIMO) control, specifically a feedback linearization control, to track both melt-pool height and temperature reference trajectories using laser power and laser scan speed.

Toward Metamodels for Composable and Reusable Additive Manufacturing Process Models

Though the advanced manufacturing capabilities offered by additive manufacturing (AM) have been known for several decades, industry adoption of AM technologies has been relatively slow. Recent advances in modeling and simulation of AM processes and materials are providing new insights to help overcome some of the barriers that have hindered adoption. However, these models and simulations are often application specific, and few are developed in an easily reusable manner. Variations are compounded because many models are developed as independent or proprietary efforts, and input and output definitions have not been standardized. To further realize the potential benefits of modeling and simulation advancements, including predictive modeling and closed-loop control, more coordinated efforts must be undertaken. In this paper, we advocate a more harmonized approach to model development, through classification and metamodeling that will support model composability, reusability, and integration. We review several types of AM models and use direct metal powder bed fusion characteristics to provide illustrative examples of the proposed classification and metamodel approach. We describe how a coordinated approach can be used to extend modeling capabilities by promoting model composability. As part of future work, a framework is envisioned to realize a more coherent strategy for model development and deployment.Copyright

Applications of the FETI-DP-RBS-LNA Algorithm on Large Scale Problems with Localized Nonlinearities

1 Department of Mechanical and Nuclear Engineering, 307 Reber Building, Pennsylvania State University, University Park, PA 16802, USA. Tel:(814)8650059, Email:junsun@psu.edu 2 Department of Mechanical and Nuclear Engineering, 232 Reber Building, Pennsylvania State University, University Park, PA 16802, USA. Tel:(814)8637273, Fax:(814)8634848, Email:pxm32@psu.edu 3 IBM T. J. Watson Research Center, P. O. Box 218, Yorktown Heights, NY 10598, USA. Tel:(914)9451450, Fax:(914)9453434, Email:anshul@watson.ibm.com 4 Department of Computer Science and Engineering, 343K IST Building, Pennsylvania State University, University Park, PA 16802, USA. Tel:(814)8659233, Fax:(814)8653176, Email:raghavan@cse.psu.edu