Mechanical properties of tri-arm polyisobutylene based ionomers have been investigated. Number average molecular weights (¯Mn's) of the polymers were varied from 8,300 to 34,000. The ionomer of lowest ¯Mn (8,300) exhibits very low extension at break (~ 150%) while the others with ¯Mn's of 11,000, 14,000 and 34,000 show very high extensions, often exceeding 1,000%, and display relatively low permanent set and low hysteresis behavior. Since the ionic bonding is located exclusively at the chain ends, end-linked pseudo networks are formed due to coulombic attractions.At higher temperatures the coulombic interactions are weakened and the networks can be compression molded (~150°C). 相似文献
This paper presents a method for automatic control of arc length in tungsten inert gas (TIG) welding process using the arc voltage. By using this method, the role of operator in arc length control is played by an automatic control system based on a predefined arc voltage value for any special welding operation. A dynamic model for feed-rate mechanism and the relation between variations of arc length and voltage are described in details. Using a proportional-integral controller, variations of arc length in welding path is compensated with an automatic feed-rate mechanism in a normal direction to the welding path. By keeping the voltage constant during the process, a stable weld with higher quality and better appearance is obtained specially in welding of uneven surfaces. Theoretical and practical investigations show that the suggested method is able to control the TIG welding process successfully. Test results show that an accurate weld is obtained without the interference of the operator, and by comparing the predefined values of arc voltage with what is practically obtained, the welding gap is automatically adjusted. 相似文献
Lactic acid bacteria were isolated from four different sourdough bread cultures previously investigated for antifungal activity. A total of 116 isolates were obtained and screened for antifungal activity against a battery of molds. The most inhibitory isolate obtained was identified by API 50 CHL and 16s ribosomal RNA genotyping and found to be Lactobacillus paracasei ssp. tolerans. This isolate completely inhibited the growth of Fusarium proliferatum M 5689, M 5991 and Fusarium graminearum R 4053 compared to controls in a dual agar plate assay. 相似文献
Important changes occur in egg during storage leading to loss of quality. Prediction of these changes is critical in order
to monitor egg quality and freshness. The aim of this research was to evaluate application of visible (VIS) and near infrared
(NIR) spectroscopy as a rapid and non-destructive technique for egg quality assessment. Three hundred and sixty intact white-shelled
eggs freshly laid by the same flock of hens fed with a standard feed were obtained. They were put under controlled conditions
of temperature and humidity (T = 18 °C and RH = 55%) for 16 days of storage. Forty eggs were analyzed at day 0, 2, 4, 6, 8, 10, 12, 14, and 16. Transmission
spectral data was obtained in the range from 350 to 2,500 nm. The non-destructive spectral data was compared to egg sample’s
Haugh unit (HU) and albumen pH in terms of quality and to the number of storage days in terms of freshness. A partial least
squares predictive model was developed and used to link the destructive assessment methods and the number of storage days
with the spectral data. The correlation coefficient between the measured and predicted values of HU, albumen pH, and number
of storage days were up to 0.94, R2 was up to 0.90 and the root mean square error values for the validation were 5.05, 0.06, and 1.65, respectively. These results
showed that VIS/NIR transmission spectroscopy is a good tool for assessment of egg freshness and albumen pH and can be used
as a non-destructive method for the prediction of HU, albumen pH, and number of storage days. In addition, the relevant information
about these parameters was in the VIS and NIR ranging from 411 to 1,729 nm. 相似文献
To manufacture parts with nano- or micro-scale geometry using laser machining, it is essential to have a thorough understanding of the material removal process in order to control the system behaviour. At present, the operator must use trial-and-error methods to set the process control parameters related to the laser beam, motion system, and work piece material. In addition, dynamic characteristics of the process that cannot be controlled by the operator such as power density fluctuations, intensity distribution within the laser beam, and thermal effects can significantly influence the machining process and the quality of part geometry. This paper describes how a multi-layered neural network can be used to model the nonlinear laser micro-machining process in an effort to predict the level of pulse energy needed to create a dent or crater with the desired depth and diameter. Laser pulses of different energy levels are impinged on the surface of several test materials in order to investigate the effect of pulse energy on the resulting crater geometry and the volume of material removed. The experimentally acquired data is used to train and test the neural network's performance. The key system inputs for the process model are mean depth and mean diameter of the crater, and the system outputs are pulse energy, variance of depth and variance of diameter. This study demonstrates that the proposed neural network approach can predict the behaviour of the material removal process during laser machining to a high degree of accuracy. 相似文献
Metallurgical and Materials Transactions B - An experimental investigation of the reduction of magnetite concentrate particles was conducted in a laboratory-scale flash reactor representing a novel... 相似文献
Engineering with Computers - In this paper, multi-stage continuous belt (MSCB) dryer was used for carrot slices drying. Experiments were performed at three air speeds (1, 1.5, and 2 m/s)... 相似文献
Studies have shown that the major cause of the bridge failures is the local scour around the pier foundations or their abutments. The local scour around the bridge pier is occurred by changing the flow pattern and creating secondary vortices in the front and rear of the bridge piers. Until now, many researchers have proposed empirical equations to estimate the bridge pier scour based on laboratory and field datasets. However, scale impact, laboratory simplification, natural complexity of rivers and the personal judgement are among the main causes of inaccuracy in the empirical equations. Therefore, due to the deficiencies and disadvantages of existing equations and the complex nature of the local scour phenomenon, in this study, the adaptive network-based fuzzy inference system (ANFIS) and teaching–learning-based optimization (TLBO) method were combined and used. The parameters of the ANFIS were optimized by using TLBO optimization method. To develop the model and validate its performance, two datasets were used including laboratory dataset that consisted of experimental results from the current study and previous ones and the field dataset. In total, 27 scaled experiments of different types of pier groups with different cross sections and side slopes were carried out. To evaluate the model ability in prediction of scour depth, results were compared to the standard ANFIS and empirical equations using evaluation functions including Hec-18, Froehlich and Laursen and Toch equations. The results showed that adding TLBO to the standard ANFIS was efficient and can increase the model capability and reliability. Proposed model achieved better results than Laursen and Toch equation which had the best results among empirical relationships. For instance, proposed model in comparison with the Laursen and Toch equation, based on the RMSE function, yielded 50.4% and 71.8% better results in laboratory and field datasets, respectively.