ACCase inhibitor fractionation and glyphosate addition improve perennial sourgrass control

Glyphosate-resistant sourgrass is difficult to control, particularly when perennial, and strategies that improve the control efficiency against this grass and preserve the useful life of graminicides are warranted. Therefore, the present study aimed to answer the following questions: (i) Does fractionating the doses of ACCase inhibitors improve the control of perennial sourgrass? (ii) Does alternating the chemical groups cyclohexanediones (DIMs) and aryloxyphenoxypropanoates (FOPs) improve the control of perennial sourgrass, and does the order of their application affect sourgrass control efficiency? (iii) Does the addition of glyphosate to ACCase inhibitors improve to the control of perennial sourgrass resistant to 5-enol-pyruvyl-shiquime-3-phosphate synthase inhibitors? Two field experiments (I and II) were performed in 2018 and repeated in 2019. In experiment I, the treatments included a single or fractional application clethodim + quizalofop-P-ethyl (216 + 108 g a.i. ha-1), clethodim (216 g a.i. ha-1), and quizalofop-P-tefuryl (108 g a.i. ha-1), applied in the order of clethodim followed by quizalofop-P-tefuryl and vice versa, as well as a control treatment. In experiment II, the treatments included a single or fractional application of clethodim + quizalofop-P-ethyl (216 + 108 g a.i. ha-1) and clethodim (108 g a.i. ha-1), isolated or associated with glyphosate, as well as a control treatment. In both experiments, the interval between the fractional applications was 7 days. Percentage of control, number of tillers per plant, and height of sourgrass plants were determined. Compared with the unfractionated application, the fractionation of clethodim + quizalofop-P-ethyl and clethodim increased control by respectively 20-24 and 25-30%. Fractionated clethodim has greater

A Hybrid Remaining Useful Life Prediction Method for Cutting Tool Considering the Wear State

Accurate cutting tool remaining useful life (RUL) prediction is of significance to guarantee the cutting quality and minimize the production cost. Recently, physics-based and data-driven methods have been widely used in the tool RUL prediction. The physics-based approaches may not accurately describe the time-varying wear process due to a lack of knowledge for underlying physics and simplifications involved in physical models, while the data-driven methods may be easily affected by the quantity and quality of data. To overcome the drawbacks of these two approaches, a hybrid prognostics framework considering tool wear state is developed to achieve an accurate prediction. Firstly, the mapping relationship between the sensor signal and tool wear is established by support vector regression (SVR). Then, the tool wear statuses are recognized by support vector machine (SVM) and the results are put into a Bayesian framework as prior information. Thirdly, based on the constructed Bayesian framework, parameters of the tool wear model are updated iteratively by the sliding time window and particle filter algorithm. Finally, the tool wear state space and RUL can be predicted accordingly using the updating tool wear model. The validity of the proposed method is demonstrated by a high-speed machine tool experiment. The results show that the presented approach can effectively reduce the uncertainty of tool wear state estimation and improve the accuracy of RUL prediction.

Impact of Thermal Dissipation on the Lighting Performance and Useful Life of LED Luminaires Applied to Urban Lighting: A Case Study

Currently, LED technology is an established form of lighting in our cities and homes. Its lighting performance, durability, energy efficiency and light, together with the economic savings that its use implies, are displacing other classic forms of lighting. However, some problems associated with the durability of the equipment related to the problems of thermal dissipation and high temperature have begun to be detected, which end up affecting their luminous intensity and the useful life. There are many studies that show a direct relationship between the low quality of LED lighting and the aging of the equipment or its overheating, observing the depreciation of the intensity of the light and the visual chromaticity performance that can affect the health of users by altering circadian rhythms. On the other hand, the shortened useful life of the luminaires due to thermal stress has a direct impact on the LCA (Life Cycle Analysis) and its environmental impact, which indirectly affects human health. The purpose of this article is to compare the results previously obtained, at different contour temperatures, by theoretical thermal simulation of the 3D model of LED street lighting luminaires through the ANSYS Fluent simulation software. Contrasting these results with the practical results obtained with a thermal imaging camera, the study shows how the phenomenon of thermal dissipation plays a fundamental role in the lighting performance of LED technology. The parameter studied in this work is junction temperature (Tj), and how it can be used to predict the luminous properties in the design phase of luminaires in order to increase their useful life.