Scheduling wafer slicing by multi-wire saw manufacturing in photovoltaic industry: a case study

Wafer slicing in photovoltaic industry is mainly done using multi-wire saw machines. The selection of set of bricks (parallelepiped block of crystalline silicon) to be sawn together poses difficult production scheduling decisions. The objective is to maximize the utilization of the available cutting length to improve the process throughput. We address the problem presenting a mathematical formulation and an algorithm that aims to solve it in very short running times while delivering superior solutions. The algorithm employs a reactive greedy randomized adaptive search procedure with some enhancements. Computational experiments proved its effectiveness and efficiency to solve real-world based problems and randomly generated instances. Implementation of an on-line decision system based on this algorithm can help photovoltaic industry to reduce slicing costs making a contribution for its competitiveness against other sources of energy.     

Unified description of martensite microstructure and kinetics

A quantitative metallography method is described to obtain size and number per unit volume of martensite units from linear intercept measurements. The entailed relationship between the number per unit volume of martensite plates and the volume fraction transformed is consistent with the autocatalytic nature of martensite. Application to the athermal and the isothermal martensite reactions allowed development of a unified microstructure-kinetic model. Validation of the model equations was achieved with data pertaining to FeNiC and FeNiMn alloys found in the literature. The apparent activation energy for propagation of isothermal martensite yielded by the transformation curve is compatible with the value obtained from the initial transformation rate. The defect redistribution process austenite/martensite established during the thickening of the plates has a crucial role in autocatalysis.     

Development of method for monitoring of chloride release in the oil refining processes

During oil refining, equipments are constantly exposed to the action of compounds such as salts, leading corrosion problems and to decrease in equipment service life. Soon, the growing search for productivity increasingly demand more strategies to monitor the processes and minimize costs. This article contributes to the methodology development to study the chlorides released during the oil distillation, in a similar process that occurs in refineries, enabling predict and minimize damage. Oils were evaluated with respect to chloride release during each stage of oil heating. Salinity mass balance were obtained as well as their respective chloride release percentage to each oil.     

Prediction via Neural Networks of the Residual Hydrogen Peroxide used in Photo‐Fenton Processes for Effluent Treatment

This communication proposes the use of neural networks in the prediction of residual concentrations of hydrogen peroxide from the treatment of effluents through Advanced Oxidative Processes (AOP's), in particular, the photo‐Fenton process. To verify the efficiency of the oxidative process, the Chemical Oxygen Demand (COD) parameter, the values of which may be modified by the presence of oxidizing agents such as residual hydrogen peroxide, is frequently taken in account. The analysis of the H₂O₂ interference was performed by spectrophotometry at 450 nm wavelength, via the monitoring of the reaction of ammonia with metavanadate. The results of the hydrogen peroxide residual concentration were modeled via a feedforward neural network, with the correlation coefficients between actual and predicted values above 0.96, indicating good prediction capacity.     

Cost-benefit analysis of sustainable drainage systems considering ecosystems services benefits: case study of canal do mangue watershed in Rio de Janeiro city,Brazil

Clean Technologies and Environmental Policy - The increasing demands of humankind contribute to the scarcity of natural resources and foster climate changes. For this reason, sustainable...     

Technical note: Mammary gland ultrasonography to evaluate mammary parenchymal composition in prepubertal heifers

Bovine mammary gland development studies are often terminal or involve invasive biopsy procedures. Therefore, noninvasive means of assessing mammary development should be considered as alternative methods in live animals. The objective was to test if mammary ultrasonography can be used as a noninvasive way to estimate mammary parenchyma (PAR) composition in prepubertal dairy heifers with different average daily body weight gains. In the 84 d preceding, the ultrasound exam heifers were maintained in 1 of 3 treatment groups. Individual heifers were fed a high gain (1 kg/d; n = 6), low gain (0.5 kg/d, n = 6), or maintenance (n = 6) treatment diet. To achieve desired body weight gains, heifers were fed differing amounts of the same silage-based diet. Mammary glands of 18 crossbred heifers Holstein:Gyr underwent a single mammary ultrasound exam immediately before heifer slaughter, which took place when heifers weighed 142.0 ± 8.0 kg and were 200 d old. The 4 mammary glands of each heifer were evaluated using a real-time B-mode ultrasound machine equipped with a 6.5-MHz micro-convex transducer. Digital images (8-bit) of glands were obtained and PAR was identified within gland. Average pixel values per unit of PAR area were determined for each gland and analyzed at the level of heifer. Pixel results were interpreted on the basis that lower average pixel values reflect PAR with relatively high amounts of protein as opposed to fat. To help validate that the pixel value within PAR is associated with composition of PAR, pixel findings were compared with histological [number of adipocytes in PAR (Nad) and epithelial area in PAR (Ep)] and biochemical [percent crude protein in PAR (%CP), percent ether extract in PAR (%EE), PAR weight (WPAR), and mammary fat pad weight (WFAT)] composition of PAR in these same heifers. Within PAR, %EE and WFAT were positively correlated with pixel values, whereas %CP, Ep, and Nad were negatively correlated. Parenchyma weight did not correlate with pixel values. Regression analyses (fixed effect log-pixel value; random effect treatment) were used to estimate Nad, Ep, %CP, %EE, WPAR, and WFAT. Sensitivity analysis of regression equations revealed that accuracy of tested equations ranged from 0.77 to 0.93 and precision ranged from 0.56 to 0.82. Concordance correlation coefficients of the equations ranged from 0.41 to 0.76. In conclusion, ultrasonography of PAR can accurately measure and predict PAR composition in prepubertal dairy heifers growing at various rates of gain.