Our Python libraries managing TinyUTM’s active parts (load cell, stepper motor, gears, threads) and experiments (with a cam for visual extensometry) seem ok, their mock version simulates the real world showing sound logic, no errors, exceptions handling. This is good to have before hardware connection and its physical limitations, latencies, sensors, networking issues, machine calibration and so on.
Blog
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Prototype: inventory list
Near comprehensive list of items before machining and set up: gears (2x driven gears + 1 driving gear with hub), radial bearings (4x UCF 201 WL), axial bearings (TICFOX 10x F6-12M, 6x12x4.5mm), top and bottom plate (2x 300x300x15mm , Al 6082 T651), columns (6x 3030 Al profile 400mm long) with profile connectors (20x Wall Bracket 90) and helicoils (12x M6 X 1,0 X 3D), antivibration feet (Adam Hall 4907 M8 AH), crosshead (230x100x25mm , Al 6082 T651), load cell (YZC-516C S , 500kg), load cell sensor (DUBEUYEW HX711), stepper motor (RATTMMOTOR Nema 23HS2430) with driver (DRV8825), crosshead’s helicoils (8x M6->M4), Trantorque (2x TTQM1223), Raspberry Pi 4 4GB (Vemico starter kit) with webcam module (Jun-Electronic J2-E327), leadscrews (2x T12x3 500mm long) with bronze nuts (2x T12x3), Emergency stop (Baomain 10A 660V 1NO 1NC), ASTM D638 clampings (2x GAKA M12 yoke, with bolt), ASTM E3205 clampings (custom: punching bar + upper die + lower die, C45 steel) with ZrO2 balls (Quarkzman, 2.5mm diameter, 10x) + screws, bolts, cables, etc.
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TinyUTM’s original reference
Our very first TinyUTM’s prototype in late 2024 was aimed at reproducing the open-source FreeLoader’s work by Amend, McNicoll and Lipson, 2011, University of Colombia, paper reference: “FreeLoader: An Open Source Universal Testing Machine for High-Throughput Experimentation“, ASME IDETC/CIE Conference, Washington, DC, 2011. Other than tensile tests of non-metal and/or additively manufactured specimens, we wanted to try the recent small punch test for metals, all within a 3kN load capacity instead of their 5kN.
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AI steels r&d needing TinyUTM
FOUR INTERESTING MATERIALS FOR LATE 2024
28 August 2024 – The following materials, still at an early or mid technological readiness level, can be prepared and tested in-house for preliminary R&D work or dissemination purposes, employing a metallurgy lab (5kN universal testing machine with small punch test modding + small tube furnace + modified 3D printer for injection molding + standard lab equipment) worth as little as 5k euros:
- Fe-18Cr-8Ni-2Mn-1Cu-0.1N (austenitic stainless steel): automotive applications;
- Fe20Cr20Ni20Mn20Co20 (high entropy alloy): similar to austenitic steel, space applications;
- 70% PLA + 20% PHB + 10% limonene as plasticizer (bioplastic): packaging applications;
- PLA with 2% graphene nanoplatelet (conductive polymer): electronics applications.
There are no non-standard risks associated, so any qualified operator should be able to process the materials and execute the tests by following checklists for safety and for the reliability of results.
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NUMERICAL ANALYSIS OF SMART-SENSING COATINGS IN EXTREME ENVIRONMENTS
15 September 2024 – Multilayer coatings with smart-sensing capabilities for early warning could tentatively protect standard austenitic steels in extreme environments against corrosion, yet their technological readiness level is low. A case study we are interested in is 316L stainless steel with Alumina-forming austenitic steel (Fe-Ni-Cr-Al) top layer for Gen IV European lead-cooled fast reactor.
Preliminary numerical analyses can sustain the r&d process using Windows 10, open-source software packages and dummy yet realistic inputs, in search of criticalities before lab-level experiments:
- LAMMPS for atomic-scale simulations of the layer structure, focusing on radiation effects, diffusion processes and the formation of the layer;
- OpenFOAM to model the liquid lead flow and its interaction with the coating surface, considering heat transfer, oxygen transport and corrosion product dissolution;
- Python with SciPy for corrosion kinetics modeling, electrochemical simulations and sensor response analysis, with a particular focus on the growth and stability of the layer;
- Abaqus free license (< 1000 nodes, non commercial use) for thermal-mechanical stress analysis of the coating under operating conditions, including the effects of the growing oxide layer.
Results from different scales would be integrated using Python for data analysis and visualizazion.