Development of two-phase neural network-genetic algorithm hybrid model in modeling damage evolution in roll forming of aluminum sheet

In this paper a two-phase artificial neural network-genetic algorithm (ANN-GA) hybrid model has been developed for the modeling and prediction of the damage evolution in the roll forming (RF) process of aluminum sheet metal, as a function of process parameters. The multilayer perceptron is used to build the network while the genetic algorithm (GA) is employed to optimize the network structure in the modeling phase. In detail, the number of hidden layer, hidden neurons, weights and biases of the network are optimized by GA to minimize the error between predicted values and actual results. After the modeling phase the optimization of parameters is carried out in the optimization phase to minimize the damage in the aluminum sheet during the forming process. In this work the experimental data used for training and verifying the network is obtained automatically by the integration between CAD-CAE. As a result, the predicted results are validated with the actual values and a good agreement is observed. Moreover, the parametric study also is performed to find the relative influences of process parameters on the damage evolution. It is proven that the hybrid model is the powerful tool for modeling and predicting such a highly nonlinear problem as the damage evolution in RF process. The developed two-phase ANN – GA hybrid model is a new approach that can bring benefits to the forming industry by predicting and preventing the failure at the design stage, as well as improving efficiently the product's quality by optimizing the process parameters.     

Characterization of wines from grape varieties through multivariate statistical analysis of H NMR spectroscopic data

¹H NMR spectroscopic analysis coupled with multivariate statistical data was used to characterize wines vinified from four grape varieties: Muscat Bailey A (Vitis labrusca), Campbell Early (V. labrusca B.), Kyoho (V. labrusca L.) and Meoru (Vitis coignetiae). Pattern recognition methods, such as principal component analysis (PCA) and orthogonal projection to latent structure discriminant analysis (OPLS-DA), showed clear differentiation between wines made from these grape varieties. Metabolites responsible for the differentiation were identified as 2,3-butanediol, glycerol, malate, citrate, tartrate, succinate, lactate, proline, alanine, choline and trigonelline. The PCA score plot of quantitative analysis of targeted profiling data also showed clear separation between the wines. The highest levels of glycerol, 2,3-butanediol, succinate and alcohol were found in Kyoho wines, suggesting higher sugar content in the Kyoho grape berry compared to other grape varieties. Higher contents of citrate and trigonelline in Muscat Bailey A wines, alanine in Campbell Early wines and proline, malate and choline in Meoru wines demonstrated that the metabolites of the wines vary with the grape variety. This study provides insight into the relationship between grape variety and its wine through global and targeted analysis of ¹H NMR spectral data.     

Emission inventory of VOCs from mobile sources in a metropolitan region

Based on methodologies developed by US EPA, European EMEP/CORINAIR, and Australian NPI, and the former emission inventory in Korea, two methods were applied to 151 villages in northeastern Seoul, Korea to estimate emission of VOCs from line and area vehicle sources depending on vehicle types with different fuel types. A discharge coefficient method for the line source on the Eastern main road was calculated by multiplying the emission amounts per unit of mileage, and a fuel exhaust coefficient method for the area vehicle sources on other roads was determined as multiplying the emission rates by the actual consumption of excess fuel. Results indicated the methods could be adequate for estimating the amounts of mobile emissions when limited information on mobile emission is available. The methods can be used to develop the emission model for all VOCs emission sources (point and non-point sources), which provides input data of atmospheric models.     

Application of steel thin film electrical resistance sensor for in situ corrosion monitoring

The corrosion sensor should have high sensitivity enough to measure the corrosion rate in mild corrosive environments and the ability to detect the corrosion mechanism. Therefore, our goal is to develop and apply a steel thin film electrical resistance (TFER) sensor based on the measurement of changes in electrical resistance of the sensing elements in order to follow the corrosion of steel in a wide range of environments. The sensor with a thickness of 600 nm is fabricated by DC magnetron sputter deposition of steel on an Al₂O₃ substrate, followed by silk screen printing to improve the sensitivity of the sensor, especially to measure the corrosion rate in low corrosive environments such as anoxic corrosion in neutral solutions, steel protected by protective measures like a corrosion inhibitor or cathodic protection, and atmospheric corrosion. The sensor also has multiple-line sensing elements to detect the localized corrosion of steel. The TFER sensor is laboratory and field tested. All the studies demonstrate that the newly developed TFER sensor can be a promising and reliable tool for corrosion monitoring of steel exposed to various environments.     

Source voltage sensorless estimation scheme for PWM rectifiers under unbalanced conditions

A source voltage sensorless estimation scheme is proposed for a pulsewidth-modulation (PWM) rectifier in unbalanced circumstances. The negative sequence is accompanied by the unbalance among phases, and acts as an ac disturbance to a normal-mode estimator and controller. Hence, without considering voltage unbalance, a PWM rectifier yields a voltage ripple in the dc-link voltage and large reactive currents. With the proposed sensorless scheme, both positive and negative components are estimated separately by using a full- (or reduced-) order estimator. The feasibility of the proposed sensorless scheme is confirmed through computer simulation and experiment.     

Design of U-shape milled groove conformal cooling channels for plastic injection mold

Besides the solid free-form fabrication technology, milling operation is an alternative applicable method to make complex cooling channels conform to the surface of the mold cavity. This paper presents the U-shape milled groove conformal cooling channels and proposes the design optimization process in order to obtain an optimal cooling channels’ configuration and target mold temperature. The relation between the cycle averaged thermal behavior of the mold cavity and the two-dimensional configuration of cooling channels was first investigated thoroughly by an analytical method. Design of experiment and 2D simulation were done to obtain the mold wall temperature and to check the feasibility of the analytical method. The optimization process of the free-form conformal cooling channels is based on the combination of both analytical method and 3D CAE simulation. The analytical step relies on explicit mathematic formulas, so it can approach the neighboring optimal solution quickly. Subsequently, the three-dimensional heat transfer simulation is applied to fine-tune the optimization results. A case study for a plastic car fender was investigated to verify the feasibility of the proposed method. The results show that conformal cooling channel gives a uniform cooling, reducing the cooling time and increasing the molded part’s quality with less effort of plastic designers and high computational efficiency.     

Excitation of Cy5 in self-assembled lipid bilayers using optical microresonators

Due to their sensitivity and temporal response, optical microresonators are used extensively in the biosensor arena, particularly in the development of label-free diagnostics and measurement of protein kinetics. In the present letter, we investigate using microcavities to probe molecules within biomimetic membranes. Specifically, a method for self-assembling lipid bilayers on spherical microresonators is developed and the bilayer-nature is verified. Subsequently, the microcavity is used to excite a Cy5-conjugated lipid located within the bilayer while the optical performance of the microcavity is characterized. The emission wavelength of the dye and the optical behavior of the microcavity agree with theoretical predictions.     

Loosening mechanism of threaded fastener for complex structures

Journal of Mechanical Science and Technology - Threaded fasteners are widely used in mechanical structures primarily owing to their easy disassembly for maintenance and low cost. However, the...     

Calibration of the plate thermometer for measuring heat flux using a conical heater

Journal of Mechanical Science and Technology - An experimental study was conducted on the calibration method and measurement error for a plate thermometer (PT) that can replace the heat flux gauge...