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Weight measurement Weight-O-Meter®

Researchers have developed a technique to quickly determine certain properties of a material, like stress and strain, based on an image of the material showing its internal structure.The image-based approach is especially advantageous for complex composite materials.The researchers used a machine learning technique called a Generative Adversarial Neural Network that was trained with thousands of paired images — one depicting a material's internal microstructure subject to mechanical forces and the other depicting that same material's color-coded stress and strain values.The fully trained network successfully rendered stress and strain values given a series of close-up images of the microstructure of various soft composite materials. The network was even able to capture “singularities” like cracks developing in a material. In these instances, forces and fields change rapidly across tiny distances.

Courtesy: Tech Briefs Vol 46. No. 4 April 2022.

The analyst begins with the well established material science premise that concrete does not withstand tensile stress as effectively as compressive stress, which can be easily verified by observing that a karate chop will result in a slab breaking at the lowest surface and then propagating to the apex.

The design of Weight-O-Meter is based on the fundamental realization that an image based material analysis determines the stress and strain of objects. How much weight can an object sustain is a constant headache. Such paradoxical situations can be addressed with the aid of this electro-optical tool whose primary function is to interrogate the stress/strain profiles of a structure intended to support, be it a delicate electronic instrument or a gazillion ton heavy equipment. A user friendly GUI displays the break-ability factors at the molecular deformation level.


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