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No, Timothy

Publications and source records attributed to No, Timothy.

Fabrication of a Liner Assembly for the MARVEL Microreactor

A liner assembly for an intermediate heat exchanger within the MARVEL microreactor at Idaho National Laboratory has been fabricated using laser-based additive manufacturing. The liner design includes challenging features such as long thin walls, overhangs, and tight geometric tolerances. Two versions of the liner assembly, one full length and the other shortened, were printed from several materials (316L SS, Inconel 625, and Inconel 718) using four powder-based laser printers (AddUp BeAM Modulo 400 DED, EOS 290M LPBF, GE Concept M2, and GE Concept Xline 2000R LPBF) located at the Manufacturing Demonstration Facility of Oak Ridge National Laboratory. Dimensional accuracy, print time, and powder utilization have been evaluated to help assess the feasibility of these AM approaches to liner fabrication. Based on this assessment, a potentially cost-effective pathway for fabrication has been proposed.

36 MATERIALS SCIENCE↗

Hybrid manufacturing by additive friction stir deposition, metrology, CNC machining, and microstructure analysis

Aerospace flight panels must provide high strength with low mass. For aluminum panels, it is common practice to begin with a wrought plate and remove the majority of the material to attain the desired structure, comprising a thinner plate with the desired pattern of reinforcement ribs. As an alternative, this study implements hybrid manufacturing, where aluminum is first deposited on a baseplate only at the rib locations using additive friction stir deposition (AFSD). Structured light scanning is then used to measure the printed geometry. This geometry is finally used as the stock model for computer numerical control (CNC) machining. This paper details the hybrid manufacturing process that consists of: AFSD to print the preform, structured light scanning to generate the stock model and tool path, three-axis CNC machining, and post-process measurements for part geometry and microstructure.

42 ENGINEERING↗

Process planning for hybrid manufacturing using additive friction stir deposition

Additive friction stir deposition (AFSD) provides a solid-state approach to metal deposition that does not rely on local melting and solidification, but rather on kinetic energy and plastic flow. Here, in this study, AFSD is combined with structured light scanning, turning, and milling to produce metal components while considering the unique requirements imposed by the hybrid manufacturing process sequences. Two demonstrations are presented which include: 1) a cylindrical build plate selection to enable coordinate system transfer between deposition and turning of a hollow cone; and 2) intermittent deposition-machining operations with structured light scanning to fabricate a two-sided hexagon-cylinder geometry.

36 MATERIALS SCIENCE↗

Dynamic force and stability prediction for milling using feed rate scheduling software and time-domain simulation

This paper describes: 1) the use of feed rate scheduling software to predict the radial depth of cut variation for three-axis milling toolpaths and; 2) the use of the radial depth profile in a time-domain simulation to predict dynamic cutting forces. The time-domain simulation, which also includes the tool tip frequency response functions and force model (which relates the cutting force components to the chip geometry) as inputs, enables dynamic force profiles to be predicted and parameter combinations that cause chatter to be identified. A ramp geometry is selected that provides constantly varying radial depth and force predictions are completed at multiple axial depths for comparison to measured forces. Both stable and unstable (chatter) milling conditions were observed with good agreement between time-domain simulation and measurement results. The value of combining the feed rate scheduling software and time-domain simulation is demonstrated.

42 ENGINEERING↗

Bayesian optimization for inverse calibration of expensive computer models: A case study for Johnson-Cook model in machining

Inverse model calibration for identifying the constitutive model parameters can be computationally demanding for expensive-to-evaluate simulation models. Here, this paper presents a modified Bayesian optimization (BO) method, denoted as BO-bound, that incorporates theoretical bounds on the quantity of interest. A case study for the inverse calibration of the Johnson Cook (J-C) flow stress model parameters is presented using machining (cutting) force data. The results show fast calibration of the five J-C parameters within 25 simulations. In general, the BO-bound method is applicable for inverse calibration of any expensive simulation models as well as optimization problems with known bounds.

Bayesian optimization↗