The effects of different greenhouse covering materials on energy requirement,growth and yield of aubergine

Effects of UV stabilised polyethylene (UV+PE), IR absorbers polyethylene (IR+PE), double layers of polyethylene (D-Poly) and single layer of polyethylene (PE), as greenhouse covers, on aubergine growth, productivity and energy requirement were investigated in a late autumn season (2001). The late and final yields of plants grown in D-Poly houses were higher than those grown in UV+PE, IR+PE and PE. Light transmission was the highest in PE, intermediate in UV+PE and IR+PE, and the lowest in D-Poly houses. Relative humidity was the highest in D-Poly, intermediate in IR+PE and UV+PE, and the lowest in PE houses. The plants in D-Poly houses grew and developed faster (more leaves and flowers) than those in IR+PE, UV+PE and PE houses. Plant growth and development in UV+PE and IR+PE houses was similar. Economic analyses showed that aubergine production was economically viable in D-Poly, UV+PE and IR+PE houses. For aubergine production in climatic conditions similar to Black Sea Region, the D-Poly greenhouse is strongly recommended, because there was a higher productivity and a lower heating requirement in comparison to UV+PE, IR+PE and PE houses.     

Sulfur capture for fluidized-bed combustion of high-sulfur content lignites

Sulfur release and capture behavior of lignites with highly combustible sulfur-contents were investigated by extending a previously-developed comprehensive model to incorporate sulfur retention. The predictive performance of the model was tested by comparing the model predictions with on-line concentration measurements of O₂, CO₂, CO and SO₂. Favorable comparisons are obtained between the predicted and measured concentrations of gaseous species along the combustor. Results show that freeboard sulfur-capture is enhanced significantly with recycling of elutriated sorbent particles as the sulfur release to the freeboard is significant for fuels rich in combustible sulfur.     

An experimental study for determination of the effects of machining parameters on surface roughness in electrical discharge machining (EDM)

Electrical discharge machining (EDM) is a non-traditional production method that has been widely used in the production of dies throughout the world in recent years. The most important performance measure in EDM is the surface roughness; among other measures material removal and tool wear rates could be listed. In this study, experiments were performed to determine parameters effecting surface roughness. The data obtained for performance measures have been analyzed using the design of experiments methods. A considerably profound equation is obtained for the surface roughness using power, pulse time, and spark time parameters. The results are discussed.     

Optimisation of cutting parameters for minimizing carbon emission and maximising cutting quality in turning process

Modern manufacturing systems are faced with the challenge of reducing the carbon emission related to manufacturing technologies. Machining centres consume large amounts of energy and as a consequence; carbon emissions are generated owing to this consumption. This paper presents a design of experiment work related to the optimisation of machining factors in the turning process of aluminium alloys. Carbon emission and surface quality were concurrently optimised. A set of experimental scenarios was set using a Box–Behnken design and the response surface methodology was applied to get the regression model for the carbon emission and surface roughness during turning process. The relationship between factors and the responses (carbon emission and surface quality) was investigated using surface plots. Furthermore, the desirability function method using the Response Optimizer tool in MINITAB and goal programming methodology was used to obtain the values of the parameters that achieved minimum surface roughness and a minimum quantity of carbon emission.     

Backstepping approach for design of PID controller with guaranteed performance for micro-air UAV

Flight controllers for micro-air UAVs are generally designed using proportional-integral-derivative (PID) methods, where the tuning of gains is difficult and time-consuming, and performance is not guaranteed. In this paper, we develop a rigorous method based on the sliding mode analysis and nonlinear backstepping to design a PID controller with guaranteed performance. This technique provides the structure and gains for the PID controller, such that a robust and fast response of the UAV (unmanned aerial vehicle) for trajectory tracking is achieved. First, the second-order sliding variable errors are used in a rigorous nonlinear backstepping design to obtain guaranteed performance for the nonlinear UAV dynamics. Then, using a small angle approximation and rigorous geometric manipulations, this nonlinear design is converted into a PID controller whose structure is naturally determined through the backstepping procedure. PID gains that guarantee robust UAV performance are finally computed from the sliding mode gains and from stabilizing gains for tracking error dynamics. We prove that the desired Euler angles of the inner attitude controller loop are related to the dynamics of the outer backstepping tracker loop by inverse kinematics, which provides a seamless connection with existing built-in UAV attitude controllers. We implement the proposed method on actual UAV, and experimental flight tests prove the validity of these algorithms. It is seen that our PID design procedure yields tighter UAV performance than an existing popular PID control technique.     

Uniform line integral representation of edge-diffracted fields

A uniform line integral representation is derived for edge-diffracted fields by using the modified theory of physical optics and uniform asymptotic evaluation methods. The method is applied to the problem of diffraction of plane waves by a semi-infinite edge, which creates tip-diffracted fields with edge-diffracted waves. The uniform diffracted fields are plotted and examined numerically.     

Remote detection of volatile organic compounds by passive multispectral infrared imaging measurements

Automated pattern recognition methodology is described for the detection of signatures of volatile organic compounds from passive multispectral infrared imaging data collected from an aircraft platform. Data are acquired in an across-track scanning mode with a downward-looking line scanner based on 8 to 16 spectral channels in the 8-14 and 3-5 microm spectral ranges. Two controlled release experiments are performed in which plumes of ethanol are generated and detected from aircraft overflights at altitudes of 2200 to 2800 ft (671 to 853 m). In addition, a methanol release from a chemical manufacturing facility is monitored. Automated classifiers are developed by application of piecewise linear discriminant analysis to the calibrated, registered, and preprocessed radiance data acquired by the line scanner. Preprocessing steps evaluated include contrast enhancement, temperature-emissivity separation, feature selection, and feature extraction/noise reduction by the minimum noise fraction (MNF) transform. Successful classifiers are developed for both compounds and are tested with data not used in the classifier development. Separation of temperature and emissivity by use of the alpha residual calculation is found to reduce false positive detections to a negligible level, and the MNF transform is shown to enhance detection sensitivity.     

Photoinitiated polymerization of ethyl cyanoacrylate by phosphonium salts

The photoinitiated polymerization of ethyl cyanoacrylate (ECA) by benzyl triphenylphosphonium hexafluoroantimonate (BP⁺) and (anthracen-9-ylmethyl)triphenylphosphonium hexafluoroantimonate (MAP⁺) was studied. Zwitterionic and free radical mechanisms which involved homolytic and heterolytic decomposition of the phosphonium salts are discussed. The anthracene-sensitized photopolymerization of ECA was also demonstrated.