Analysis of the Improvement of Engineering Mechanics Experimental Methods Based on IoT and Machine Learning.

With the rapid development of sensor technology, machine learning, and the Internet of Things, wireless sensor networks have gradually become a research hotspot. In order to improve the data fusion performance of wireless sensor networks and ensure network security in the event of external attacks, this paper proposes a wireless sensor optimization algorithm model, involving wireless sensor networks, the Internet of Things, and other related fields. This paper first analyzes the role of the Internet of Things in wireless sensor networks, studies the localization mechanism and hierarchy of the Internet of Things based on wireless sensor networks, and improves the LE-RLPCCA (Position Estimation Robust Local Retention Criteria Correlation Analysis) localization algorithm model based on sensor grids. This paper discusses the problems of machine learning in wireless sensor networks, constructs a sensor-based machine learning model, and designs a data fusion algorithm for a wireless sensor networks' machine learning model. The application of wireless sensors in engineering mechanics experiments is summarized, and the optimization algorithm model of the wireless sensor in engineering mechanics experiments is proposed. The analysis results show that the average accuracy of the DKFCM-FSVM (Density aware Kernel-based Fuzzy C-means Clustering algorithm Fuzzy Support Vector Machine) algorithm in detecting five behaviors is 0.997, 0.992, 0.904, 0.996, and 0.946, respectively, and the accuracy in detecting different behaviors is the best, 0.005, 0.01, 0.003, and 0.006 respectively. It achieves the lowest false positive rate in the detection of different behaviors, and the average false positive rate is 0.004, 0.003, 0.003, 0.008, and 0.005, respectively, which shows that the DKFCM-FSVM algorithm model of wireless sensor networks in engineering mechanics experiments is the optimal solution. The work of this paper has good reference value for the application of wireless sensor networks and the optimization of engineering mechanics experimental methods and is helpful for further research of sensor technology.

Study of Low-Velocity Impact Behavior of Hybrid Fiber-Reinforced Metal Laminates.

In this paper, the low-velocity impact behavior and damage modes of carbon/glass-hybrid fiber-reinforced magnesium alloy laminates (FMLs-H) and pure carbon-fiber-reinforced magnesium alloy laminates (FMLs-C) are investigated using experimental, theoretical modeling, and numerical simulation methods. Low-velocity impact tests were conducted at incident energies of 20 J, 40 J, and 60 J using a drop-weight impact tester, and the load-displacement curves and energy-time curves of the FMLs were recorded and plotted. The results showed that compared with FMLs-C, the stiffness of FMLs-H was slightly reduced, but the peak load and energy absorption were both greatly improved. Finally, a finite element model based on the Abaqus-VUMAT subroutine was developed to simulate the experimental results, and the damage modes of the metal layer, fiber layer, and interlayer were observed and analyzed. The experimental results are in good agreement with the finite element analysis results. The damage mechanisms of two kinds of FMLs under low-velocity impacts are discussed, providing a reference for the design and application of laminates.

Fire resistance of low alloy Q420d high-strength steel column under high-temperature creep.

The high-temperature mechanical and creep characteristics of Q420D steel are investigated in this essay. To determine the steel's high-temperature yield strength, the high-temperature tensile test of Q420D steel was first performed. In the temperature range of 400°C-800°C, the high-temperature creep test under various pressures was conducted, and the creep strain curve over time was produced. Finite element analysis and comparison were done to examine the impact of creep strain on the Q420D steel column's bearing capacity under high-temperature conditions. The findings demonstrated that: Using Abaqus, a finite element fire resistance analysis of a Q420D steel column, was conducted while taking initial geometrical flaws, residual stress, and creep effect into account. As a result, the critical temperature of a Q420D steel column under various load ratios was determined. The largest deviation from the critical temperature in the standard GB51249-2017 was 2.9% when the creep effect was taken into account under the load ratio R = 0.3. The highest reduction in fire resistance limit time under low load ratio conditions, taking into account the creeping impact of Q420D steel columns, is 35%. The findings demonstrate that the high-temperature creep energy greatly lowers the steel column's fire resistance.

Experimental and Numerical Investigation of the Tensile and Failure Response of Multiple-Hole-Fiber-Reinforced Magnesium Alloy Laminates under Various Temperature Environments.

In this paper, the tensile mechanical behavior and progressive damage morphology of glass-fiber-reinforced magnesium alloy laminate for different numbers of holes in a temperature range of 25-180 °C were investigated. In addition, based on extensive tensile tests, the tensile mechanical behavior and microscopic damage morphology of porous-glass-fiber-reinforced magnesium alloy laminates at different temperatures were observed by finite element simulation and scanning electron microscopy (SEM). Finally, the numerical simulation and experimental results were in good accordance with the prediction of mechanical properties and fracture damage patterns of the laminates, the average difference between the residual strength values of the specimens at ambient temperature was 5.57%, and the stress-strain curves were in good agreement. The experimental and finite element analysis results showed that the damaged area of the bonded layer tended to expand with the increase in the number of holes, which has a lesser effect on the ultimate tensile strength. As the temperature increased, the specimens changed from obvious fiber breakage (pull-out) and the resin matrix damage mode to matrix softening damage and interfacial delamination fracture damage. As the testing temperature of the specimens increased from 25 °C to 180 °C, the tensile strength of the specimens decreased by an average of 51.59%, while the tensile strength of the specimens showed a nonlinear decreasing trend. The damage mechanism of porous-glass-fiber-reinforced magnesium alloy laminates at different temperatures is discussed in this paper, which can provide a reference for engineering applications and design.