Experimental Techniques最新文献

This study presents soft armor design strategies with composite samples produced by impregnating STF into aramid, ultra-high molecular weight polyethylene (UHMWPE) and hybrid fabric types. STF was made by dispersing silica nanoparticles in polyethylene glycol at 40 weight% (wt%). The effects of fabric types and hybrid fabric arrangement sequences on energy absorption were experimentally investigated using a single-stage gas gun system. STF-treated fabrics demonstrated a significant increase in energy absorption compared to non-STF-treated fabrics. The extent of this increase varies depending on the fabric type. STF impregnation was found to be more effective in woven aramid fabric, resulting in a 72.7% increase in energy absorption compared to neat fabric. In contrast, STF impregnation of unidirectional UHMWPE fabric led to only a 3.3% increase. In addition to enhancing energy absorption, STF impregnation also demonstrated that altering the fabric arrangement sequence in hybrid samples influences energy absorption. The H3 hybrid sample, consisting of 15 layers of aramid fabric and 15 layers of UHMWPE fabric, exhibited the highest energy absorption. For practical applications in soft body armor design, the effect of fabric arrangement sequence should be considered.

The study focuses on calibrating a system for inductive heating of samples before performing dynamic compression tests using a Split Hopkinson Pressure Bar (SHPB). In the proposed set-up, the crucial role is played by the pyrometer, which could continuously control the temperature of the specimen during the test. The coupling of the experimental test together with numerical simulations (including thermal and mechanical simulations) is performed to calibrate the considered system. The key outcomes of the coupled experiment and simulation analyses are the shortest heating time required to achieve a uniform temperature in the neck of the sample and the change in the temperature field during cooling (after the heating ends). This procedure will also be used in real experiments to predict the temperature sensitivity of the material under dynamic compression under precisely controlled thermal conditions for a temperature range of 250 °C to 730 °C.

The frequency response function (FRF) is an established way to describe the outcome of experiments in posture control literature. The FRF is an empirical transfer function between an input stimulus and the induced body segment sway profile, represented as a vector of complex values associated with a vector of frequencies. For this reason, testing the components of the FRF independently with Bonferroni correction can result in a too-conservative approach. Performing statistics on scalar values defined on the FRF, e.g., comparing the averages, implies an arbitrary decision by the experimenter. This work proposes bootstrap prediction and confidence bands as general methods to evaluate the outcome of posture control experiments, overcoming the foretold limitations of previously used approaches.

In order to study the deformation and cracking behavior of casing with defects under non-uniform load, different types of defects were prefabricated on the surface of casing samples by building a test system. The cracking and crack propagation process of samples under non-uniform load were observed and analyzed by finite element simulation. The test results show that the defect will significantly reduce the bearing capacity of the casing under non-uniform load, and the defect is a necessary condition for the cracking failure of the material. The defect depth affects the bearing capacity of the sample, and the defect width affects the deformation of the sample. With the increase of the depth of the defect, the maximum load of the sample and the maximum load loading displacement approximate S curve decrease; with the increase of the width of the defect, the deformation of the sample under the same load in the load reduction stage of the sample increases obviously. The variation curve of crack length with loading displacement is obtained, and the finite element model of casing with defects is established, which can analyze and evaluate the stress and deformation distribution of casing. The research results can provide guidance for casing damage evaluation and field detection.

This paper proposes a novel method for calculating damage in fatigue testing of wind turbine blades using machine vision. With the increasing size of wind turbine blades, biaxial fatigue testing has become a significant area of interest in the industry. The traditional damage calculation method, which relies on strain sensors, becomes unreliable when subjected to biaxial load coupling. In the proposed method, machine vision is utilized to obtain the displacement of target points. A static calibration is then performed to establish the relationship between displacement and bending moment, enabling the real-time measurement of bending moment during fatigue testing. The Miner linear fatigue cumulative damage theory is subsequently applied to calculate the equivalent fatigue cumulative damage. To validate the effectiveness of this method, both static and dynamic experiments were conducted. The results demonstrate that this method achieves the required accuracy for detecting damage in wind turbine blade fatigue testing. Moreover, the data obtained through this method exhibits higher accuracy compared to traditional approaches. The proposed method introduces a novel approach to the wind turbine blade testing industry.