Study on Mechanical Properties of crack Healing of low carbon Steel based on cyclic Phase Transformation Heat treatment

With the rapid development of materials, metal materials are used less and less, but at this stage, metal materials are still widely used, and iron and steel materials are the most widely used. Cracks often appear in the process of metal material processing and use, and these cracks will have a certain impact on the use of metal materials. The existence of microcracks will affect the mechanical properties of materials to some extent, but in most cases, the mechanical properties of materials will be greatly reduced, and in serious cases, metal materials will break directly in the process of use or processing. The crack healing process needed after the emergence of cracks can effectively change this situation, but so far, the research on metal crack healing is still not perfect. In this paper, taking the internal crack of low carbon steel as the object, the recovery of mechanical properties of low carbon steel by cyclic phase transformation heat treatment was studied. The results show that with the increase of the healing area, the microhardness of the area after crack healing also increases, and the tensile strength of the specimen also increases after the healing. When the healing area is similar, increasing the healing time and temperature will result in grain coarsening, resulting in the decrease of microhardness and tensile strength in the crack healing zone.

WOOD AND GENERATIVE ALGORITHMS FOR THE COMPARISON BETWEEN MODELS AND REALITY

This study examines the emblematic case of a test room and its relation to digital modelling. This space is the result of a multi-optimization process that has been physically built for the verification of the initial hypotheses. As a result, it is actually a Physical Twin, designed to be transformable by removing a wall. The same space, on the other hand, has become useful for testing the Digital Twin logic by associating a BIM model with a dynamic representation of the data captured by the sensors. The representation is thus placed at the core of this cyclic phase between reality and representation, with the goal of validating the proposed theories through empirical practice, improving digital computational ability, and identifying pathways for monitoring space's interactions with the environment and those who live in it.

Partial Dictionary Based Off-Grid DOA Estimation Using Combined Coprime and Nested Array

A partial dictionary based direction of arrival (DOA) estimation method which addresses the off-grid problem and exploits combined coprime and nested array (CCNA) is proposed. Compared to general coprime array, CCNA yields two sparse coprime subarrays in the coarray domain by adding a third subarray in the physical-array domain. To ensure the DOA estimation performance, the subarray with larger aperture is chosen, and the cyclic phase ambiguity caused by the sparse subarray allows partial dictionary covering arbitrary cycle to represent the whole atoms, and then, the off-grid sparse reconstruction method is developed to amend the grid mismatch. After the sparse recovery and off-grid compensation, ambiguous DOA estimations can be eliminated by substituting the estimations into the whole virtual array. Multiple simulations verify that the proposed algorithm outperforms the other state-of-the-art methods in terms of DOA estimation accuracy and angular resolution.