Dissolution of salts crystallised in building materials using ultrasound: an alternative to NORMAL (1983) standard methodology.
Our aim in the present work is to extract salts from ornamental stone using a faster and less tedious method than the customarily used NORMAL method [NORMAL, Dosaggio dei Sali Solubili, CNR-ICR, Roma, Italy (1983) 13/83]. For extraction in aqueous medium, the latter method requires shaking for 72 h at a temperature of 60 degrees C. Our aim is to attempt to shorten this time to less than 1 h using ultrasound. The results of the present study indicate that there is a good correlation between the amount of salts extracted applying the method described in the NORMAL (1983) normative and the amounts extracted with the method proposed here, subjecting the material to ultrasound (50 KHz) for 45 min.
Salt Weathering Hazard
Peface. Acknowledgements. The Hazard. Case Studies. Nature of Salts Involved in Salt Weathering and Sources of Moisture. Materials' Susceptibility and Experimental Simulations. Mechanisms of Salt Attack. Geomorphological Implications of Salt Weathering. Diagnosing, Solving and Managing Salt weathering Hazards. Referenes. Index.
Research on Fracture Recognition in Well Logging Images: Adversarial Learning with Attention
Semantic recognition of fractures in well logging images is vital for engineers to implement oil and gas exploration. An essential approach to accomplishing the object is to adopt deep learning based on convolutional neural networks. However, due to the lack of annotated labels in well logging images, it is scarcely available to directly train the semantic segmentation network. In this paper, we explore a domain shift model attempting to achieve domain adaptation from one annotated dataset to our target well logging images. This model's core is to utilize adversarial learning, including generator and discriminator, which can prompt the model to generate fracture segmentation similar to the source domain in the target domain. For enhancing the domain adaptive model further, an attention module is introduced, which can suppress redundant noise in semantic segmentation results. We demonstrate that our proposed model performs well by extensive tests and ablation experiments in the ultrasonic well logging images.