Complexity and performance of an Augmented Lagrangian algorithm

Algencan is a well established safeguarded Augmented Lagrangian algorithm introduced in [R. Andreani, E. G. Birgin, J. M. Martínez, and M. L. Schuverdt, On Augmented Lagrangian methods with general lower-level constraints, SIAM J. Optim. 18 (2008), pp. 1286–1309]. Complexity results that report its worst-case behaviour in terms of iterations and evaluations of functions and derivatives that are necessary to obtain suitable stopping criteria are presented in this work. In addition, its computational performance considering all problems from the CUTEst collection is presented, which shows that it is a useful tool for solving large-scale constrained optimization problems.     

Challenges and new methods for designing reliability experiments

Abstract

Engineers use reliability experiments to determine the factors that drive product reliability, build robust products, and predict reliability under use conditions. This article uses recent testing of a howitzer to illustrate the challenges in designing reliability experiments for complex, repairable systems. We review research in complex system reliability models, failure-time experiments, and experimental design principles. We highlight the need for reliability experiments that account for various intended uses and environments. We leverage lessons learned from current research and propose methods for designing an experiment for a complex, repairable system.     

Effects of hydrocarbon impurities,vibrational relaxation,and boundary-layer-induced pressure rise on the ignition of H2–O2‒Ar mixtures behind reflected shock waves

The results of an experimental and theoretical study of the ignition of H₂–O₂?Ar mixtures behind reflected shock waves are reported. The experiments are performed with mixtures containing from 0.15 to 8.0% H₂ and from 0.75 to 2.0% O₂ at temperatures of 980–1800 K and a total gas concentration of (1.0 ± 0.1) × 10^?5 mol/cm³. The progress of the process is monitored by recording the time evolution of the pressure behind the reflected shock wave and the intensity of the chemiluminescence of electronically excited OH1 radicals (λ = 308 ± 2.5 nm). A numerical model capable of predicting the effects of additional factors, such as hydrocarbon impurities, the vibrational relaxation of the test mixture, and boundary-layer-induced pressure rise, is developed and used to simulate our own and published experimental data on the ignition of H₂–O₂?Ar mixtures. It is demonstrated that the best agreement between experimental and theoretical results is achieved when all the additional factors are taken into account. A sensitivity analysis shows that the effects of the vibrational relaxation of the test mixture and the presence of hydrocarbon impurities are significant only for lean mixtures, whereas the influence of the boundary-layer-induced pressure rise is important across a wide range of stoichiometries at long ignition delay times. Additionally, an analytical model is developed, which takes into account the finite time of the chain?propagation reactions O + H₂ and OH + H₂. The predictions of the numerical and analytical models are demonstrated to be in close agreement for a wide range of mixture compositions and experimental conditions.     

Discrete choice experiments in the analysis of consumers’ preferences for finfish products: A systematic literature review

Discrete choice experiments (DCEs) have become an important tool for assessing the preferences of consumers for finfish seafood products. This investigation presents a systematic literature review of studies performed in the last 20 years (2000–2019) that use DCEs to analyse consumers’ preferences for finfish products, with the purpose to identify the main insights of consumer behaviour towards these products, the most used attributes for this type of experiments and to discuss and compare some willingness to pay estimations. We found that origin was the most used attribute for this kind of experiments, while other important factors were the harvest method, a specific certification label and the species or products considered. The WTP estimates evidenced that consumers are willing to pay premiums for domestic products, while similarly, wild products were preferred over farmed products. Also, there were higher WTP estimates for certified products, in which specific certification labels were better options rather than just claiming that the product was certified or not. All claims and labels related to sustainability, nutritional, health and safety information provided premiums that consumers were willing to pay, however, the importance differed depending on the type of label or claim, the country and species. Future research should consider the influence of being or not the main purchaser in the household, as it might affect the WTP values. Also, given the importance, future research extensions using DCEs are needed on the Chinese and Asian finfish market.     

异丙醇铝控制水解制备高纯拟薄水铝石和多孔氧化铝

主要进行异丙醇铝水解制备高纯拟薄水铝石和高纯多孔γ-Al_2O_3的研究。合成路线以异丙醇铝为原料,改变反应过程中水化液组成、水化温度和水化时间,制备一系列拟薄水铝石及其焙烧产物多孔γ-Al_2O_3。结果表明,水化液中异丙醇的存在会抑制无定型氢氧化铝的晶化,但也有助于形成大孔径、高比表面和大孔容的氧化铝;纯水体系下,60℃以下水化会出现三水铝石,60℃以上水化的产物则为拟薄水铝石;γ-Al_2O_3孔结构与前驱体拟薄水铝石的结晶度有关,晶粒越大的拟薄水铝石,焙烧所得氧化铝的孔径和孔容也增大。因此,水化条件的改变可以实现拟薄水铝石结构的控制,进而获得不同结构的多孔氧化铝。为由异丙醇铝水解制备高纯拟薄水铝石和多孔氧化铝的工业化提供相应的研究基础。     

Comparison of fuzzy logic based models for the multi-response surface problems with replicated response measures

A replicated multi-response experiment is a process that includes more than one responses with replications. One of the main objectives in these experiments is to estimate the unknown relationship between responses and input variables simultaneously. In general, classical regression analysis is used for modeling of the responses. However, in most practical problems, the assumptions for regression analysis cannot be satisfied. In this case, alternative modeling methods such as fuzzy logic based modeling approaches can be used. In this study, fuzzy least squares regression (FLSR) and fuzzy clustering based modeling methods, which are switching fuzzy C-regression (SFCR) and Takagi–Sugeno (TS) fuzzy model, are preferred. The novelty of the study is presenting the applicability of SFCR to the multi-response experiment data set with replicated response measures. Three real data set examples are given for application purposes. In order to compare the prediction performance of modeling approaches, root mean square error (RMSE) criteria is used. It is seen from the results that the SFCR gives the better prediction performance among the other fuzzy modeling approaches for the replicated multi-response experimental data sets.     

SiC单晶片切割力建模与自适应控制

Si C单晶因优良的物理和机械性能而大量用于大功率器件和IC行业。但由于材料的高硬度和高脆性,使其加工过程变得很困难。为此,分析了Si C单晶片切割过程,建立切割过程模型,通过F检验法进行系统阶次辨识,采用遗忘因子递推最小二乘算法在线估计模型参数,建立进给量与切割力的差分方程,设计基于最小方差自校正的切割力控制器,并进行实验验证。结果表明:控制器能够很好的跟踪不同信号,具有良好的鲁棒性,提高了Si C单晶片的加工效率和表面质量。