Electrochemical treatment processes can significantly contribute to the protection of the environment through the minimization
of waste and toxic materials in effluents. From a pharmaceutical point of view and due to the existing resemblance between
the electrochemical and biological reactions, it can be assumed that the oxidation mechanisms on the electrode and in the
body share similar principles. In this paper, the application of electrochemical studies in the design of an environmentally
friendly method was delineated for the new hydrocaffeic acid (HCA, 3,4-dihydroxy hydrocinnamic acid) derivatives synthesis
at carbon electrodes in an undivided cell. In this cell, the EC mechanism reaction was involved, comprising two steps alternatively;
(1) electrochemical oxidation and (2) chemical reaction. In particular, the electro-organic reactions of HCA, an important
biological molecule, were studied in a water–acetonitrile (90:10 v/v) mixture in the presence of benzenesulfinic acid (3) and p-toluenesulfinic acid (4). The research included the use of a variety of experimental techniques, such as cyclic voltammetry, controlled-potential
electrolysis and product spectroscopic identification. 相似文献
In this study, analytical modeling of the tensile strength of hot-mix asphalt (HMA) mixtures at low temperatures was developed. To do this, HMA mixtures were treated as a two-phase composite material with aggregates (coarse and fine) dispersed in an asphalt mastic matrix. A two-phase composite model, which was similar to Papanicolaou and Bakos's [J. Reinforced Plast. Compos. 11 (1992) 104] model with a particle embedded in an infinite matrix, was proposed. Unlike Papanicolaou and Bakos's model, an axial stress was introduced to the fiber end to consider the load transferred from the asphalt mastic the aggregate. Efforts were also made to consider the effect of aggregate gradation, asphalt mastic degradation, and interfacial damage between the aggregates and asphalt mastic matrix on the tensile strength of the HMA mixtures. Experimental investigations were conducted to validate the developed theoretical relations. A reasonable agreement was found between the predicted tensile strength and the experimental results at low temperatures. Parameters affecting the tensile strength of asphalt mixtures were discussed based on the calculated results. 相似文献
A study of radiation effects on various types of glasses, dielectric optical coatings, cemented optics and fiber was undertaken with a view to select them for extreme radiation environments. Samples were exposed to different radiation doses in the Pakistan Research Reactor-I (PARR-I) for neutron and Cobalt 60 source for gamma irradiation. Transmissions were measured before and after irradiation. The dielectric coatings were subjected to additional tests (adhesion, abrasion and humidity, etc.) as per MIL-M-13508C and MIL-C-675C. All 15 glasses studied showed varying amounts of transmission loss as expected, with negligible degradation for three types. Recovery of transmissions with time/ageing was also studied, with more or less complete recovery with temperature annealing. A faster bleaching of darkened/brown glasses was achieved by using UV lamps or UV laser. The dielectric coatings (HR, AR) and one of the two commercial optical cements showed excellent resistance to neutrons and gamma radiations, and could be good candidates for the fabrication and utilization of optical components in extreme radiation environments. The data allowed several Chinese glasses to be studied for the first time. 相似文献
This study deals with the neuro-fuzzy (NF) modelling of a real industrial winding process in which the acquired NF model can be exploited to improve control performance and achieve a robust fault-tolerant system. A new simulator model is proposed for a winding process using non-linear identification based on a recurrent local linear neuro-fuzzy (RLLNF) network trained by local linear model tree (LOLIMOT), which is an incremental tree-based learning algorithm. The proposed NF models are compared with other known intelligent identifiers, namely multilayer perceptron (MLP) and radial basis function (RBF). Comparison of our proposed non-linear models and associated models obtained through the least square error (LSE) technique (the optimal modelling method for linear systems) confirms that the winding process is a non-linear system. Experimental results show the effectiveness of our proposed NF modelling approach. 相似文献
Shear connectors play a prominent role in the design of steel-concrete composite systems. The behavior of shear connectors is generally determined through conducting push-out tests. However, these tests are costly and require plenty of time. As an alternative approach, soft computing (SC) can be used to eliminate the need for conducting push-out tests. This study aims to investigate the application of artificial intelligence (AI) techniques, as sub-branches of SC methods, in the behavior prediction of an innovative type of C-shaped shear connectors, called Tilted Angle Connectors. For this purpose, several push-out tests are conducted on these connectors and the required data for the AI models are collected. Then, an adaptive neuro-fuzzy inference system (ANFIS) is developed to identify the most influencing parameters on the shear strength of the tilted angle connectors. Totally, six different models are created based on the ANFIS results. Finally, AI techniques such as an artificial neural network (ANN), an extreme learning machine (ELM), and another ANFIS are employed to predict the shear strength of the connectors in each of the six models. The results of the paper show that slip is the most influential factor in the shear strength of tilted connectors and after that, the inclination angle is the most effective one. Moreover, it is deducted that considering only four parameters in the predictive models is enough to have a very accurate prediction. It is also demonstrated that ELM needs less time and it can reach slightly better performance indices than those of ANN and ANFIS.
Neural Computing and Applications - For the current paper, the technique of feed-forward neural network deep learning controller (FFNNDLC) for the nonlinear systems is proposed. The FFNNDLC... 相似文献