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Eliasson, Veronica

Publications and source records attributed to Eliasson, Veronica.

5 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Seal Strength Calculations for Low Mass DDT Vessel

Lawrence Livermore National Laboratory (LLNL) is collaborating with Colorado School of Mines (Mines), to field the first dynamic experiments on the 3-ring flash radiography system (3-ring). One set of experiments for 3-ring concerns the deflagration to detonation transition (DDT), within a sealed column of high-explosives. The high-explosive material is ignited at one end with a BK-80, an igniter made from Boron Potassium-Nitrate (BKNO 3 ). The initial deflagration reaction will increase the pressure in the sealed vessel, resulting in the formation of a dense "plug" of material ahead of the deflagration front. The transition to detonation is thought to be related to the plug formation. Previous experiments have been able to resolve the plug geometry, but only in a two dimensional radio-graph. 3-ring offers a novel diagnostic tool which could provide three dimensional density fields via few-view reconstruction algorithms and computed tomography.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Extrusion parameter control optimization for DIW 3D printing using image analysis techniques

Material extrusion is a well-recognized facet of additive manufacturing that involves the fabrication of parts through the deposition of structural material from an extrusion head from a bulk supply. In the subdivision of Direct Ink Writing (DIW) additive manufacturing, challenges arise when the structural material is flowable, synchronous extrusion control and tool movement becomes critical for achieving high-quality parts with low defect populations. DIW techniques are most used in laboratory settings using expensive custom instruments and may require specialized 3D slicing software. Here, in this study, the fabrication of an inexpensive, consumer-friendly progressive cavity pump dispensing system is detailed, in which can create high-quality parts by executing G-code commands produced from a commercial slicing software. The precision and repeatability of the movement-synchronized material extrusion is demonstrated through a series of optimization schemes, entailing the alteration of various control parameters, which directly affect the extrusion properties demonstrated during a print. In situ diagnostics were implemented to evaluate the results of the established optimization experiment. Using a machine vision technique, images of the optimization prints are processed. Following this, a supervised machine learning model was trained to autonomously judge whether or not the extrusion parameters produced a passing or failing result. The machine learning scheme serves as a preliminary benchmark for future layer-by-layer evaluation of more complex DIW parts. The construction of the printer and development of in situ characterization capabilities demonstrates the ability for this printer to create high-fidelity DIW parts for a fraction of the price of other systems.

42 ENGINEERING↗