Gypsum-Based 3D Printing Assists in Classifying Geo-Architectural Rock Specimens

Michelle Williams has authored a study (carried out at Sandia National Laboratories and funded by Laboratory Directed Research and Development) for the U.S. Department of Energy, Office of Scientific and Technical Information, outlining recent findings about unique materials for digital fabrication in Geomechanical characterization of Geo-architectural Rock Specimens using Gypsum-based 3D printing.

Because of the natural diversity in rock samples being studied by scientists, there are often challenges in classification. Williams’ study is meant to improve methods for the evaluation of characteristics in natural rock. As with so many other fields too, ranging from automotive to aerospace, medicine and dental, construction, and nearly every industry one can think of, 3D printing offers improvements on previous methods, designs, prototypes and parts, and more.

In relation to rocks, 3D printed models can help scientists have a better understanding of the following:

  • Strength
  • Density
  • Porosity
  • Microstructure
  • Mineralogy
  • Geophysical
  • Mineralogical interactions

Conventional methods for study include microscopy, CT scans, micro-CT scans, and many other techniques, to include rock mass classification; however, issues such as fractures, bedding, inclusions, joints, and more, present challenges during examination. Many benefits arise with the use of 3D printing, from ease in production of models as well as speed, affordability, and the potential for fabrication of complex geometries.

The scientists printed 36 samples in cylinder form, using a powder-based Gypsum 3D ProJet360 printer with an HP11 printhead and VisiJet PXL Clear binder as the material.

Printing direction with respect to horizontal tray. Adapted from SAND2019-14916C.

Direction and location of velocity measurements

The researchers noted velocity and took pictures of each sample before evaluation; they were then baked in a humidity chamber and tested on an MTS 22kip frame.

3D printed sample stack with LVDTs

MTS 22kip load frame used for UCS testing at Sandia National Lab

Stress versus strain curves reflected the greatest strength in samples printed in the H-long direction, with the vertically printed samples coming in second. H-short samples were the weakest.

H-long samples-strongest, stress vs. strain plots

H-short samples-weakest, stress vs. strain plots

Vertical samples-middle strength, stress vs. strain plots

“With varying amount of binder, the larger amount (blue) resulted in the strongest rock during UCS testing,” stated Williams. “Density was also measured to ensure additional binder amount, and the higher density sample is the sample with the larger amount of binder.”

Peak strength vs. varying amount of binder

Density vs. varying binder amount

The environment was responsible for differences in strength. The team noted that baked samples were strongest, while weakest were left in humidity levels of 80 percent.

“Test results of the 3D printed geo-architected rock specimens demonstrated reasonable reproducibility and appear to be a promising path towards increasing the ability to characterize natural rock,” concluded Williams.

“Future work could improve the Python code to also calculate and compare Young’s Modulus from the UCS data versus that from the velocity measurements. Due to the high impact of the 3D printing, advances in the technology appear inevitable. Such advances may help control sample microstructure, which will increase the value of this technology for understanding classification of rock characteristics.”

What do you think of this news? Let us know your thoughts! Join the discussion of this and other 3D printing topics at 3DPrintBoard.com.

[Source / Images: ‘Geomechanical characterization of Geo-architectural Rock Specimens using Gypsum-based 3D printing.’]

The post Gypsum-Based 3D Printing Assists in Classifying Geo-Architectural Rock Specimens appeared first on 3DPrint.com | The Voice of 3D Printing / Additive Manufacturing.