This article aims at modeling unified S-N curves based on multifailure modes and stress ratios. Heterogeneous mixture distributions are used to describe life distribution of multifailure modes. Bayes clustering is applied to cluster failure data to avoid convergence to global optima. Derived from regression analysis, failure data are compensated by nonrandom error. The relationship between distribution parameters and stress is established, and the ultimately unified probabilistic S-N curve is modeled. Two assumptions are presented to modify an original S-N curve model with varied stress ratios. The first one is to take into account the effects of low-amplitude load “exercising,” which we call results in the “pseudo-fatigue damage.” The other one is to set up probability density function of fatigue limit considering uncertainty. Combined with material parameters modification, thus a new modified and unified S-N curves model is available for not only researchers, but engineers as well.
BACKGROUND Succinate dehydrogenase inhibitors (SDHIs) play an increasingly important role in controlling plant diseases. However, the similar structures of SDHIs result in rapid development of cross‐resistance development and a clear bottleneck of poor activity against oomycetes, therefore the need to seek new SDHI fungicides with novel structures is urgent. RESULTS Innovative pyrazolyl oxime ethers were designed by replacing amide with oxime ether based on the succinate dehydrogenase (SDH) structure, and 19 pairs of Z‐ and E‐isomers were efficiently prepared for the discovery of SDHI compounds with a novel bridge. Their biological activities against four fungi and two oomycetes were evaluated, and substantial differences were observed between the Z‐ and E‐ isomers of the title compounds. Furthermore, most of these compounds exhibited remarkable activities against Rhizoctonia solani with EC50 values of less than 10 mg L−1 in vitro, and bioassay in vivo further confirmed that E‐I‐6 exhibited good protective efficacy (76.12%) at 200 mg L−1. In addition, Z‐I‐12 provided better activity against the oomycetes Pythium aphanidermatum and Phytophthora capsici (EC50 = 1.56 and 0.93 mg L−1) than those of boscalid. Moreover, E‐I‐12 exhibited excellent SDH inhibition (IC50 = 0.21 mg L−1) thanks to its good binding ability to the SDH by hydrogen‐bonding interactions, π‐cation interaction and hydrophobic interactions. CONCLUSION Novel pyrazolyl oxime ethers have the potential as SDHI compounds for future development, and the strategy of replacing an amide bond with oxime ether may offer an alternative option in SDHI fungicide discovery.
The differential is an important part of a driveline, and differential performance is related to the handling and stability performance of a vehicle. Thus, a differential with sound design structure and reasonable form and size parameters could lead to satisfactory driving performance. In this work, we analyze and evaluate the reliability of the key parts of a differential system. Firstly, each of key parts is regarded as a subsystem of a differential system, so the subsystem reliability models are obtained. A system reliability model is built based on the paths of the forces from the differential system, and system reliability is calculated. Secondly, according to the result of the analysis of system reliability and the use of the six sigma method, 45 steel or 1Cr18Ni9Ti utilized as the material for the worm shaft, system reliability is analyzed and discussed separately. Then, the reliability of the key parts and the overall system reliability increase with the low load strengthening characteristic of the material. Finally, according to the analysis and discussion, the level of system reliability matches that required for differential systems, and the cost is also considerably reduced, as demonstrated using the stress-strength interference and low-load strengthening models. These results provide a theoretical basis for the improvement of the design of Torsen differentials. Similar methods can be used to develop automobile subsystems in the future.
The study discusses how some challenges from a small sample fatigue test can be analysed statistically and resolved. In terms of data dispersion, fatigue data are initially processed by confidence, and then, the fatigue life curve is replaced by the parabolic reliability approximation. Fatigue data under various reliability levels are obtained. Instead of the traditional single S–N curve, the mean value curve and mean square deviation curve of the S–N curve are computed based on the processed fatigue data. The S–N curve with reliability is deduced by applying quantile theory. The S–N curve is improved by considering the effects of low‐amplitude load strengthening. The benefits of the modification are visible in the comparison of the fatigue life before and after low‐amplitude load strengthening. Copyright © 2016 John Wiley & Sons, Ltd.
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