Data-based robust multiobjective optimization of interconnected processes: energy efficiency case study in papermaking.

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.

Thermal energy minimisation in papermaking via MD control approach

This paper reports the application of Advanced Process Control (APC) techniques for improving the thermal energy efficiency of a paperboard-making process by regulating the Machine Direction (MD) profile of the basis weight and moisture content of the paper-board. A Model Predictive Controller (MPC) is designed so that the sheet moisture and basis weight tracking errors along with variations of the sheet moisture and basis weight are reduced. Also, the drainage is maximised through improved wet-end stability which can facilitate driving the sheet moisture set-point closer to its upper specification limit over time. It is shown that the proposed strategy can result in reducing steam usage by 8-10%. A simulation study based on a UK board machine is presented to show the effectiveness of the proposed technique. © 2011 Intl Journal of Adv Mechatr.

Hybrid model predictive control applied to switching control of burner load for a compact marine boi

This paper discusses the application of hybrid model predictive control to control switching between different burner modes in a novel compact marine boiler design. A further purpose of the present work is to point out problems with finite horizon model predictive control applied to systems for which the optimal solution is a limit cycle. Regarding the marine boiler control the aim is to find an optimal control strategy which minimizes a trade-off between deviations in boiler pressure and water level from their respective setpoints while limiting burner switches.The approach taken is based on the Mixed Logic Dynamical framework. The whole boiler systems is modelled in this framework and a model predictive controller is designed. However to facilitate on-line implementation only a small part of the search tree in the mixed integer optimization is evaluated to find out whether a switch should occur or not. The strategy is verified on a simulation model of the compact marine boiler for control of low/high burner load switches. It is shown that even though performance is adequate for some disturbance levels it becomes deteriorated when the optimal solution is a limit cycle. Copyright © 2007 International Federation of Automatic Control All Rights Reserved.

Data-based robust multiobjective optimization of interconnected processes: Energy efficiency case study in papermaking

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.

The effect of addition of ZrO2 to Fe2O3 for hydrogen production by chemical looping

In this paper, a synthetic mixture of ZrO2 and Fe 2O3 was prepared by coprecipitation for use in chemical looping and hydrogen production. Cycling experiments in a fluidized bed showed that a material composed of 30 mol % ZrO2 and 70 mol % Fe 2O3 was capable of producing hydrogen with a consistent yield of 90 mol % of the stoichiometric amount over 20 cycles of reduction and oxidation at 1123 K. Here, the iron oxide was subjected to cycles consisting of nearly 100% reduction to Fe followed by reoxidation (with steam or CO 2 and then air) to Fe2O3. There was no contamination by CO of the hydrogen produced, at a lower detection limit of 500 ppm, when the conversion of Fe3O4 to Fe was kept below 90 mol %. A preliminary investigation of the reaction kinetics confirmed that the ZrO2 support does not inhibit rates of reaction compared with those observed with iron oxide alone. © 2012 American Chemical Society.

Long range exhaustion-a mathematical model for the axisymmetric air flow of a local exhaust ventilation hood assisted by a turbulent radial jet

Abstract-Mathematical modelling techniques are used to predict the axisymmetric air flow pattern developed by a state-of-the-art Banged exhaust hood which is reinforced by a turbulent radial jet flow. The high Reynolds number modelling techniques adopted allow the complexity of determining the hood's air Bow to be reduced and provide a means of identifying and assessing the various parameters that control the air Bow. The mathematical model is formulated in terms of the Stokes steam function, ψ, and the governing equations of fluid motion are solved using finite-difference techniques. The injection flow of the exhaust hood is modelled as a turbulent radial jet and the entrained Bow is assumed to be an inviscid potential flow. Comparisons made between contours of constant air speed and centre-line air speeds deduced from the model and all the available experimental data show good agreement over a wide range of typical operating conditions. | Mathematical modelling techniques are used to predict the axisymmetric air flow pattern developed by a state-of-the-art flanged exhaust hood which is reinforced by a turbulent radial jet flow. The high Reynolds number modelling techniques adopted allow the complexity of determining the hood's air flow to be reduced and provide a means of identifying and assessing the various parameters that control the air flow. The mathematical model is formulated in terms of the Stokes steam function, Ψ, and the governing equations of fluid motion are solved using finite-difference techniques. The injection flow of the exhaust hood is modelled as a turbulent radial jet and the entrained flow is assumed to be an inviscid potential flow. Comparisons made between contours of constant air speed and centre-line air speeds deduced from the model and all the available experimental data show good agreement over a wide range of typical operating conditions.

Preliminary evaluation of a nuclear scenario involving innovative gas cooled reactors

In order to guarantee a sustainable supply of future energy demand without compromising the environment, some actions for a substantial reduction of CO 2 emissions are nowadays deeply analysed. One of them is the improvement of the nuclear energy use. In this framework, innovative gas-cooled reactors (both thermal and fast) seem to be very attractive from the electricity production point of view and for the potential industrial use along the high temperature processes (e.g., H 2 production by steam reforming or I-S process). This work focuses on a preliminary (and conservative) evaluation of possible advantages that a symbiotic cycle (EPR-PBMR-GCFR) could entail, with special regard to the reduction of the HLW inventory and the optimization of the exploitation of the fuel resources. The comparison between the symbiotic cycle chosen and the reference one (once-through scenario, i.e., EPR-SNF directly disposed) shows a reduction of the time needed to reach a fixed reference level from ∼170000 years to ∼1550 years (comparable with typical human times and for this reason more acceptable by the public opinion). In addition, this cycle enables to have a more efficient use of resources involved: the total electric energy produced becomes equal to ∼630 TWh/year (instead of only ∼530 TWh/year using only EPR) without consuming additional raw materials. © 2009 Barbara Vezzoni et al.

Hierarchically structured nanocarbon electrodes for flexible solid lithium batteries

The ever increasing demand for storage of electrical energy in portable electronic devices and electric vehicles is driving technological improvements in rechargeable batteries. Lithium (Li) batteries have many advantages over other rechargeable battery technologies, including high specific energy and energy density, operation over a wide range of temperatures (-40 to 70. °C) and a low self-discharge rate, which translates into a long shelf-life (~10 years) [1]. However, upon release of the first generation of rechargeable Li batteries, explosions related to the shorting of the circuit through Li dendrites bridging the anode and cathode were observed. As a result, Li metal batteries today are generally relegated to non-rechargeable primary battery applications, because the dendritic growth of Li is associated with the charging and discharging process. However, there still remain significant advantages in realizing rechargeable secondary batteries based on Li metal anodes because they possess superior electrical conductivity, higher specific energy and lower heat generation due to lower internal resistance. One of the most practical solutions is to use a solid polymer electrolyte to act as a physical barrier against dendrite growth. This may enable the use of Li metal once again in rechargeable secondary batteries [2]. Here we report a flexible and solid Li battery using a polymer electrolyte with a hierarchical and highly porous nanocarbon electrode comprising aligned multiwalled carbon nanotubes (CNTs) and carbon nanohorns (CNHs). Electrodes with high specific surface area are realized through the combination of CNHs with CNTs and provide a significant performance enhancement to the solid Li battery performance. © 2013 Elsevier Ltd.

Physicochemical characteristics and droplet impact dynamics of superhydrophobic carbon nanotube arrays.

The physicochemical and droplet impact dynamics of superhydrophobic carbon nanotube arrays are investigated. These superhydrophobic arrays are fabricated simply by exposing the as-grown carbon nanotube arrays to a vacuum annealing treatment at a moderate temperature. This treatment, which allows a significant removal of oxygen adsorbates, leads to a dramatic change in wettability of the arrays, from mildly hydrophobic to superhydrophobic. Such change in wettability is also accompanied by a substantial change in surface charge and electrochemical properties. Here, the droplet impact dynamics are characterized in terms of critical Weber number, coefficient of restitution, spreading factor, and contact time. Based on these characteristics, it is found that superhydrophobic carbon nanotube arrays are among the best water-repellent surfaces ever reported. The results presented herein may pave a way for the utilization of superhydrophobic carbon nanotube arrays in numerous industrial and practical applications, including inkjet printing, direct injection engines, steam turbines, and microelectronic fabrication.