127 resultados para column efficiency
Resumo:
Reducing energy consumption is a major challenge for "energy-intensive" industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of "optimized" operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method.
Resumo:
The self-organization of the helical structure of chiral nematic liquid crystals combined with their sensitivity to electric fields makes them particularly interesting for low-threshold, wavelength tunable laser devices. We have studied these organic lasers in detail, ranging from the influence specific macroscopic properties, such as birefringence and order parameter, have on the output characteristics, to practical systems in the form of two-dimensional arrays, double-pass geometries and paintable lasers. Furthermore, even though chiral nematics are responsive to electric fields there is no facile means by which the helix periodicity can be adjusted, thereby allowing laser wavelength tuning, without adversely affecting the optical quality of the resonator. Therefore, in addition to studying the liquid crystal lasers, we have focused on finding a novel method with which to alter the periodicity of a chiral nematic using electric fields without inducing defects and degrading the optical quality factor of the resonator. This paper presents an overview of our research, describing (i) the correlation between laser output and material properties,(ii) the importance of the gain medium,(iii) multicolor laser arrays, and (iv) high slope efficiency (>60%) silicon back-plane devices. Overall we conclude that these materials have great potential for use in versatile organic laser systems.
Resumo:
Just under half of all energy consumption in the UK today takes place indoors, and over a quarter within our homes. The challenges associated with energy security, climate change and sustainable consumption will be overcome or lost in existing buildings. A background analysis, and the scale of the engineering challenge for the next three to four decades, is described in this paper.
Resumo:
Just under half of all energy consumption in the UK today takes place indoors, and over a quarter within our homes. The challenges associated with energy security, climate change and sustainable consumption will be overcome or lost in our existing buildings. A background analysis, and the scale of the engineering challenge for the next three to four decades, is described in this paper.
Resumo:
Reducing energy consumption is a major challenge for energy-intensive industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of optimized operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method. © 2006 IEEE.
Resumo:
The growth techniques which have enabled the realization of InGaN-based multi-quantum-well (MQW) structures with high internal quantum efficiencies (IQE) on 150mm (6-in.) silicon substrates are reviewed. InGaN/GaN MQWs are deposited onto GaN templates on large-area (111) silicon substrates, using AlGaN strain-mediating interlayers to inhibit thermal-induced cracking and wafer-bowing, and using a SiN x interlayer to reduce threading dislocation densities in the active region of the MQW structure. MQWs with high IQE approaching 60% have been demonstrated. Atomic resolution electron microscopy and EELS analysis have been used to study the nature of the important interface between the Si(111) substrate and the AlN nucleation layer. We demonstrate an amorphous SiN x interlayer at the interface about 2nm wide, which does not, however, prevent good epitaxy of the AlN on the Si(111) substrate. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Resumo:
Simultaneous high power (2W), high modulation speed (1Gb/s) and high modulation efficiency (14 W/A) operation of a two-electrode tapered laser is reported. © 2011 IEEE.
Resumo:
Discrete particle simulations of column of an aggregate of identical particles impacting a rigid, fixed target and a rigid, movable target are presented with the aim to understand the interaction of an aggregate of particles upon a structure. In most cases the column of particles is constrained against lateral expansion. The pressure exerted by the particles upon the fixed target (and the momentum transferred) is independent of the co-efficient of restitution and friction co-efficient between the particles but are strongly dependent upon the relative density of the particles in the column. There is a mild dependence on the contact stiffness between the particles which controls the elastic deformation of the densified aggregate of particles. In contrast, the momentum transfer to a movable target is strongly sensitive to the mass ratio of column to target. The impact event can be viewed as an inelastic collision between the sand column and the target with an effective co-efficient of restitution between 0 and 0.35 depending upon the relative density of the column. We present a foam analogy where impact of the aggregate of particles can be modelled by the impact of an equivalent foam projectile. The calculations on the equivalent projectile are significantly less intensive computationally and yet give predictions to within 5% of the full discrete particle calculations. They also suggest that "model" materials can be used to simulate the loading by an aggregate of particles within a laboratory setting. © 2012 Elsevier Ltd. All rights reserved.
Resumo:
Over the last two or three years, the increasing costs of energy and worsening market conditions have focussed even greater attention within paper mills than before, on considering ways to improve efficiency and reduce the energy used in paper making. Arising from a multivariable understanding of paper machine operation, Advanced Process Control (APC) technology enables paper machine behaviour to be controlled in a more coherent way, using all the variables available for control. Furthermore, with the machine under better regulation and with more variables used in control, there is the opportunity to optimise machine operation, usually providing very striking multi-objective performance improvement benefits of a number of kinds. Traditional three term control technology does not offer this capability. The paper presents results from several different paper machine projects we have undertaken around the world. These projects have been aimed at improving machine stability, optimising chemicals usage and reducing energy use. On a brown paperboard machine in Australasia, APC has reduced specific steam usage by 10%, averaged across the grades; the controller has also provided a significant capacity to increase production. On a North American newsprint machine, the APC system has reduced steam usage by more than 10%, and it provides better control of colour and much improved wet end stability. The paper also outlines early results from two other performance improvement projects, each incorporating a different approach to reducing the energy used in paper making. The first of these two projects is focussed on optimising sheet drainage, aiming to present the dryer with a sheet having higher solids content than before. The second project aims to reduce specific steam usage by optimising the operation of the dryer hood.
Resumo:
The automated detection of structural elements (e.g., columns and beams) from visual data can be used to facilitate many construction and maintenance applications. The research in this area is under initial investigation. The existing methods solely rely on color and texture information, which makes them unable to identify each structural element if these elements connect each other and are made of the same material. The paper presents a novel method of automated concrete column detection from visual data. The method overcomes the limitation by combining columns’ boundary information with their color and texture cues. It starts from recognizing long vertical lines in an image/video frame through edge detection and Hough transform. The bounding rectangle for each pair of lines is then constructed. When the rectangle resembles the shape of a column and the color and texture contained in the pair of lines are matched with one of the concrete samples in knowledge base, a concrete column surface is assumed to be located. This way, one concrete column in images/videos is detected. The method was tested using real images/videos. The results are compared with the manual detection ones to indicate the method’s validity.