The paper presents experimental verification of customized resistive crack propagation sensors as an alternative method for other common structural health monitoring (SHM) techniques. Most of these are sensitive to changes in the sensor network configuration and a baseline dataset must be collected for the analysis of the structure condition. Sensors investigated within the paper are manufactured by the direct-write process with electrically conductive, silver-microparticle-filled paint to prepare a tailored measuring grid on an epoxy or polyurethane coating as a driving/insulating layer. This method is designed to enhance the functionality and usability compared to commercially available crack gauges. By using paint with conductive metal particles, the shape of the sensor measuring grid can be more easily adapted to the structure, while, in the previous approach, only a few grid-fixed sensors are available. A fatigue test on the compact tension (CT) specimen is presented and discussed to evaluate the ability of the developed sensors to detect and monitor fatigue cracks. Additionally, the ARIMA time series algorithm is developed both for monitoring and predicting crack growth, based on the acquired data. The proposed sensors' verification reveal their good performance to detect and monitor fatigue fractures with a relatively low measurement error and ARIMA estimated crack length compared with the crack opening displacement (COD) gauge.
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http://dx.doi.org/10.3390/s21206916 | DOI Listing |
In this paper, we studied the diffusion characteristics and distribution patterns of gas leakage in soil from buried natural gas pipelines. The three-dimensional simulation model of buried natural gas pipeline leakage was established using Fluent software. Monitoring points of gas leakage mole fraction were set up at different locations, and the influence of buried depth and pressure factors on the mole fraction and diffusion of leaked gas was analyzed.
View Article and Find Full Text PDFBrief Bioinform
November 2024
Institute of Medical Information, Chinese Academy of Medical Sciences and Peking Union Medical College, Chaoyang District, Beijing 100020, China.
Drug resistance in Mycobacterium tuberculosis (Mtb) is a significant challenge in the control and treatment of tuberculosis, making efforts to combat the spread of this global health burden more difficult. To accelerate anti-tuberculosis drug discovery, repurposing clinically approved or investigational drugs for the treatment of tuberculosis by computational methods has become an attractive strategy. In this study, we developed a virtual screening workflow that combines multiple machine learning and deep learning models, and 11 576 compounds extracted from the DrugBank database were screened against Mtb.
View Article and Find Full Text PDFBMC Musculoskelet Disord
December 2024
Department of Anatomy, Guangdong Provincial Key Laboratory of Digital Medicine and Biomechanics, Guangdong Engineering Research Center for Translation of Medical 3D Printing Application, National Virtual & Reality Experimental Education Center for Medical Morphology, School of Basic Medical Sciences, Southern Medical University, No.1023, South Shatai Road, Baiyun District, Guangzhou, Guangdong, 510515, China.
Background: This study investigated the impact of higher interfragmentary compression force (IFCF) on the stability of locking plate fixation in lateral tibial plateau fractures.
Methods: Biomechanical experiments and finite element analysis (FEA) were employed to compare the performance of the AO cancellous lag screw (AOCLS) and a newly developed combined cancellous lag screw (CCLS).
Results: The results demonstrated that the CCLS provided a higher IFCF without the risk of over-screwing, significantly improving fixation stability.
Network
December 2024
Department of Electronics and Communication Engineering, Dronacharya Group of Institutions, Greater Noida, UP, India.
Speaker verification in text-dependent scenarios is critical for high-security applications but faces challenges such as voice quality variations, linguistic diversity, and gender-related pitch differences, which affect authentication accuracy. This paper introduces a Gender-Aware Siamese-Triplet Network-Deep Neural Network (ST-DNN) architecture to address these challenges. The Gender-Aware Network utilizes Convolutional 2D layers with ReLU activation for initial feature extraction, followed by multi-fusion dense skip connections and batch normalization to integrate features across different depths, enhancing discrimination between male and female speakers.
View Article and Find Full Text PDFSci Rep
December 2024
Vocational School of Technical Sciences, Akdeniz University, Antalya, Turkey.
This study examined scan speed, hatch distance, and scan rotation angle parameters to determine the effects of the powder bed fusion process on the tensile strength of AlSi10Mg material. The Taguchi L9 experimental design was applied to evaluate the effects of the parameters systematically. The experimental results revealed the importance of the parameters affecting the tensile strength of the AlSi10Mg material.
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