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11.
Shape optimization of truss-stiffened shell structures with variable thickness
Marko Kegl, Boštjan Brank, 2006, original scientific article

Abstract: This paper presents an effective approach to shape optimal design of statically loaded elastic shell-like structures. The shape parametrization is based on a design element technique. The chosen design element is a rational Bézier body, enhanced with a smoothly varying scalar field. A body-like designelement makes possible to unify the shape optimization of both pure shells and truss-stiffened shell structures. The scalar field of the design element is obtained by attaching to each control point a scalar quantity, which is an add-on to the position and weight of the control point. This scalar field is linked to the shell thickness distribution, which can be optimized simultaneously with the shape of the shell. For linear and non-linear analysis of shell structures, a reliable 4-node shell finite element formulation is utilized. The presented optimization approach assumes the employment of a gradient-based optimization algorithm and the use of the discrete method of direct differentiation to perform the sensitivity analysis.Four numerical examples of shell and truss-stiffened shell optimization are presented in detail to illustrate the performance of the proposed approach.
Keywords: mechanics of structures, shape optimization, shells, trusses, Bézier body, numerical methods, optimum design
Published: 30.05.2012; Views: 1120; Downloads: 70
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12.
Energy saving and modifications in the methanol process, using the NLP model optimization
Anita Kovač Kralj, Peter Glavič, 2006, published scientific conference contribution

Abstract: The opportunities for additional profit depend very much on the existing plant and energy system. Heat and power integration can reduce fuel usage in chemical processes. Nonlinear programming contains equations which enable structural and parametric optimization. The NLP model is formulated using an optimum energy target of process integration and electricity generation using a gas turbine with separator. The reactor acts as a combustion chamber of the gas turbine plant, producing a lot of energy. The simultaneous NLP approach can account for capital cost, integration of combined heat and power, process modification and additional production of trade-offs, and can thus yield a better solution. The combined production of electricity, heat and chemical products can lead to better process efficiency. The methanol plant was optimized using a mathematical nonlinear programming model by including an additional flowrate of hydrogen in crude methanol recycle and increasing the methanol production by 2,5%. The electricity can be generated in methanol recycle using a gas turbine. The total additional profit is 2,5 MEUR/a.
Keywords: chemical engineering, methanol production, simultaneous process optimization, nonlinear programming, cogeneration, product increase
Published: 30.05.2012; Views: 1480; Downloads: 14
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13.
Optimization of a gas turbine in the methanol process, using the NLP model
Anita Kovač Kralj, Peter Glavič, 2007, original scientific article

Abstract: Heat and power integration can reduce fuel usage, CO2 and SO2 emissions and, thereby, pollution. In the simultaneous heat and power integration approach and including additional production, the optimization problem is formulated using a simplified process superstructure. Nonlinear programming (NLP) contains equations which enable structural heat and power integration and parametric optimization. In the present work, the NLP model is formulated as an optimum energy target of process integration and electricity generation using a gas turbine with a separator. The reactor acts as a combustion chamber of the gas turbine plant, producing high temperature. The simultaneous NLP approach can account for capital cost, integration of combined heat and power, process modification, and additional production trade-offs accurately, and can thus yield a better solution. It gives better results than non-simultaneous methods. The NLP model does not guarantee a global cost optimum, but it does lead to good, perhaps near optimum designs. This approach is illustrated by an existing, complex methanol production process. The objective function generates a possible increase in annual profit of 1.7 M EUR/a.
Keywords: chemical processes, methanol, simultaneous optimization, NLP, cogeneration, gas turbine
Published: 31.05.2012; Views: 1360; Downloads: 60
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14.
Improvement of engine performance using an optimization procedure
Breda Kegl, Stanislav Pehan, Marko Kegl, 2007, original scientific article

Abstract: This paper presents a simple and effective approach to improve engine performance of a racing car with special requirements. Attention is focused onoptimal design of the intake system, using a gradient-based approximation method of mathematical programming. Since optimization relies on accurate numerical analysis of engine processes, the sub-models and parameters needed in the analysis software are carefully determined by experiment. Subsequently,the influence of different design parameters of intake and exhaust systems on engine performance is investigated numerically. The most influencing parameters are selected to be the design variables in the optimization process. In order to improve engine power at several engine speeds, two different forms of the optimal design problem are proposed, solved, and compared as a means to identify the most appropriate one. Since the analysis software is a black-box program, the optimization procedure is implemented by employing the optimization software as a master (driver) program while the analysis software acts as the slave program. The data exchange between these programs is established by XML data files and suitable wrapper programs. The results obtained confirm the usefulness of the approach presented.
Keywords: internal combustion engines, exhaust system, intake system, optimization
Published: 31.05.2012; Views: 998; Downloads: 46
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15.
CO2 separation from purge gas and flue gas in the methanol process, using NLP model optimization
Anita Kovač Kralj, Peter Glavič, 2007, original scientific article

Abstract: The concentration of CO2 in the atmosphere has to be stabilized, requiring a reduction in current emission rates in existing plants. This will be done by reducing the environmental burden imposed in such areas as materials input andCO2 emission reduction and using cleaner production, resources, and energy recycling. Any opportunities for emission reduction and CO2 reuse largely depend on existing plant and energy systems. CO2 can be separated from the outlet stream (purge gas) and from flue gas by a membrane or absorption system(absorber and regenerator) or adsorption system and reused as a reactantin a reactor system. Therefore, product yield can be increased and CO2emissions reduced, simultaneously. CO2 emissions can be reduced at the source. The authors of this paper studied CO2 reuse in a methanol process, in which electricity can be generated using an open gas turbine, followed by a separator. Simultaneous optimization of a process structure and its parametersusing simplified nonlinear programming (NLP) ensures an additional annual profit, influenced by reusing the flow rate of CO2. The additional electricity cogeneration and additional flow rates of the raw material could generate an additional profit of 2.79 MEUR/a.
Keywords: chemical processing, methanol production, optimization, nonlinear programming, CO2 emissions, CO2 reuse
Published: 31.05.2012; Views: 1234; Downloads: 55
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16.
H2 separation and use in fuel cells and CO2 separation and reuse as a reactant in the existing methanol process
Anita Kovač Kralj, Peter Glavič, 2007, original scientific article

Abstract: Fuel-cell efficiencies yield substantial reductions in the emissions of climate-change gases and promise an end to exclusive reliance on carbon fuels for energy. Fuel cells, CO2 reuse, process heat integration, and open gas turbine electricity cogeneration can be optimized simultaneously, using a nonlinear programming (NLP) algorithm. The simplified NLP model contains equations of structural and parametric optimization. This NLP model is used tooptimize complex and energy-intensive continuous processes. This procedure does not guarantee a global cost optimum, but it does lead to good, perhaps near-optimum, designs. The plant, which produces methanol, has a surplus of hydrogen (H2) and CO2 flow rates in purge gas. H2 is separated from the purge gas by an existing pressure swing adsorption (PSA) column. Pure H2 can be usedas fuel in fuel cells. CO2 can be separated from the outlet stream (purge gas) by a membrane or absorption system (absorber and regenerator) or an adsorption system and reused as a reactant in a reactor system. Therefore, theproduct yield can be increased and CO2 emissions can be reduced, simultaneously. CO2 emissions can then be reduced at the source. The retrofitted process can be operated within existing parameters. Using a methanol process as a case study, the CO2 emission flow rate can be reduced by4800 t/a. The additional electricity cogeneration in the gas turbine and in fuel cells and additional flow rates of the raw material could generate an additional profit of 2.54 MEUR/a.
Keywords: chemical processing, methanol production, optimization, nonlinear programming, CO2 reuse, fuel cells, heat integration, energy cogeneration
Published: 31.05.2012; Views: 1596; Downloads: 49
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17.
Selection of the economic objective function for the optimization of process flow sheets
Zorka Novak-Pintarič, Zdravko Kravanja, 2006, original scientific article

Abstract: This paper highlights the problem of selecting the most suitable economic optimization criteria for mathematical programming approaches to the synthesis, design, and optimization of chemical process flow sheets or their subsystems. Minimization of costs and maximization of profit are the most frequently used economic criteria in technical papers. However, there are manyother financial measures which can lead to different optimal solutions if applied in the objective function. This paper describes the characteristics ofthe optimal solutions obtained with various optimization criteria like the total annual cost, the profit, the payback time, the equivalent annual cost, the net present worth, and the internal rate of return. It was concluded that the maximization of the net present worth (NPW) with a discount rate equal to the minimum acceptable rate of return (MARR) is probably the most appropriate method for the optimization of process flow sheets or their subsystems. Similar or equal solutions can be obtained by simpler criteria of minimum equivalent annual cost or maximum profit if the annual investment cost is calculated by using the MARR instead of the straight-line depreciation method.These criteria represent a thorough compromise between quantitative andqualitative measures, because they consider the absolute terms of future cash flows of investments equally important as profitability through the life cycle of the project. The uncertainty related to the value of the MARR was considered by the generation of Pareto optimal solutions for the NPW and by the stochastic analyses of two design example problems.
Keywords: chemical processing, optimization, mathematical programming, flow sheets
Published: 31.05.2012; Views: 1156; Downloads: 40
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18.
Parameter identification of the Jiles-Atherton hysteresis model using differental evolution
Matej Toman, Gorazd Štumberger, Drago Dolinar, 2008, original scientific article

Abstract: In this paper, parameters of the Jiles-Atherton (J-A) hysteresis model are identified using a stochastic search algorithm called differential evolution (DE). The J-A hysteresis model's parameters are identified by DE in such a way, that best possible agreement is obtained between the measured and model calculated hysteresis loops. This agreement is furthermore increased by improving the J-A hysteresis model. The improvement is achieved by replacing a constant pinning parameter in the J-A hysteresis model with a variable one. Here, the variable pinning parameter is written as a function of a magnetic field. Bz DE identified parameters are used in the J-A hysteresis model, which is included in the dynamic model of a single-phase transformer. The effectiveness of the improved J-A hysteresis model and parameters identification approach is verified with experiments and simulations.
Keywords: Jiles-Atherton model, J-A hysteresis model, magnetic hysteresis, optimization methods, parameters estimation, single-phase transformer
Published: 31.05.2012; Views: 1281; Downloads: 32
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19.
MINLP optimization of a single-storey industrial steel building
Tomaž Žula, Zdravko Kravanja, Stojan Kravanja, 2008, original scientific article

Abstract: The paper presents the topology and standard sizes optimization of a single-storey industrial steel building, made from standard hot rolled I sections. The structure consists of main portal frames, connected with purlins. The structural optimization is performed by the Mixed-Integer Non-linear programming approach (MINLP). The MINLP performs a discrete topology and standard dimension optimization simultaneously with continuous parameters. Since the discrete/continuous optimization problem of the industrial building is non-convex and highly non-linear, the Modified Outer- Approximation/Equality-Relaxation (OA/ER) algorithm has been used for the optimization. Alongside the optimum structure mass, the optimum topology with the optimum number of portal frames and purlins as well as all standard cross-section sizes have been obtained. The paper includes the theoretical basis and a practical example with the results of the optimization.
Keywords: civil engineering, topology optimization, sizing optimization, nonlinear programming, MINLP
Published: 31.05.2012; Views: 1344; Downloads: 30
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20.
Machining process optimization by colony based cooperative search technique
Uroš Župerl, Franc Čuš, 2008, original scientific article

Abstract: Research of economics of multi-pass machining operations has significant practical importance. Non-traditional optimization techniques such genetic algorithms, neural networks and PSO optimization are increasingly used to solve optimization problems. This paper presents a new multi-objective optimization technique, based on ant colony optimization algorithm (ACO), to optimize the machining parameters in turning processes. Three conflicting objectives, production cost, operation time and cutting quality are simultaneously optimized. An objective function based on maximum profit in operation has been used. The proposed approach uses adaptive neuro-fuzzy inference system (ANFIS) system to represent the manufacturer objective function and an ant colony optimization algorithm (ACO) to obtain the optimal objective value. New evolutionary ACO is explained in detail. Also a comprehensive userfriendly software package has been developed to obtain the optimal cutting parameters using the proposed algorithm. An example has been presented to give a clear picture from the application of the system and its efficiency. The results are compared and analysed using methods of other researchers and handbook recommendations. The results indicate that the proposed ant colony paradigm is effective compared to other techniques carried out by other researchers.
Keywords: machining, turning, optimization, cutting parameters
Published: 31.05.2012; Views: 1049; Downloads: 15
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