Design Limits, Basic Parameter Selection and Optimization Methods in Turbomachinery Design

1985 ◽  
pp. 805-828 ◽  
Author(s):  
Ennio Macchi
Keyword(s):  
Basic Parameter ◽  
Optimization Methods ◽  
Parameter Selection ◽  
Turbomachinery Design

scholarly journals Multi-Stage Optimization of Induction Machines Using Methods for Model and Parameter Selection

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5537
Author(s):  
Martin Nell ◽  
Alexander Kubin ◽  
Kay Hameyer
Keyword(s):  
Induction Machine ◽  
Optimization Methods ◽  
Induction Machines ◽  
Parameter Selection ◽  
Pattern Search ◽  
Machine Model ◽  
Multi Stage ◽  
Selection Approach ◽  
Optimization Parameters ◽  
Selection Of

Optimization methods are increasingly used for the design process of electrical machines. The quality of the optimization result and the necessary simulation effort depend on the optimization methods, machine models and optimization parameters used. This paper presents a multi-stage optimization environment for the design optimization of induction machines. It uses the strategies of simulated annealing, evolution strategy and pattern search. Artificial neural networks are used to reduce the solution effort of the optimization. The selection of the electromagnetic machine model is made in each optimization stage using a methodical model selection approach. The selection of the optimization parameters is realized by a methodical parameter selection approach. The optimization environment is applied on the basis of an optimization for the design of an electric traction machine using the example of an induction machine and its suitability for the design of a machine is verified by a comparison with a reference machine.

scholarly journals Balancing Configuration and Refinement in the Design of Two-Spool Multistage Compression Systems

2014 ◽  
Author(s):  
Jerome P. Jarrett ◽  
Tiziano Ghisu
Keyword(s):  
Computational Cost ◽  
Pressure Rise ◽  
Optimization Methods ◽  
Design Parameters ◽  
Overall Design ◽  
Mechanical Constraints ◽  
Surge Margin ◽  
Configuration Selection ◽  
Point Pressure ◽  
Turbomachinery Design

Despite many advances in both optimization methods and computational fluid dynamics, the timely automatic selection and refinement, via physics-based and empirical methods, of “optimal” configurations of compression systems remains challenging. This is due, in part, to the large number of design parameters (with associated high computational cost) operating over wide ranges that can be non-smooth, if not discontinuous (to which many optimization algorithms, developed for smooth problems, are ill-suited). It is further complicated by the phasic nature of turbomachinery design and the associated need to balance the amount of time and computational resource devoted to selecting the most promising configurations with that expended in their refinement. This paper compares a number of combinations of a multi-fidelity approach for configuration selection with a high-fidelity method for design refinement. The system is tested on the aerodynamic design of a complete two-spool core compression system for a generic high bypass ratio turbofan. The resulting designs are obliged to meet familiar constraints for overall design point pressure rise and surge margin together with a number of mechanical constraints including maximum shaft speeds. Through the configuration phase, the number of stages and the duty split between the spools are permitted to change. It is shown that the performance of the design refinement phase is only a weak function of the preceding configuration phase provided that the latter is well into diminishing returns with respect to approaching a converged solution. It is hence shown possible to obtain equally good designs in around half the computational run-time by exploiting this weak dependence by effectively decoupling the configuration and refinement phases and starting the latter before the former has apparently finished. It is also shown that if either configuration or refinement is allowed to dominate the design process, inferior designs result. The best designs are associated with between half and three-quarters of the design effort being devoted to configuration selection.

Static and Modal Topology Optimization of Turbomachinery Components

2016 ◽  
Vol 138 (11) ◽  
Author(s):  
Andrea Rindi ◽  
Enrico Meli ◽  
Enrico Boccini ◽  
Giuseppe Iurisci ◽  
Simone Corbò ◽  
...  
Keyword(s):  
Topology Optimization ◽  
Mechanical Design ◽  
Optimization Methods ◽  
Technical Documentation ◽  
Performance Targets ◽  
New Concepts ◽  
Turbine Component ◽  
Mechanical Optimization ◽  
Turbomachinery Design ◽  
Near Future

The need to be more and more competitive is pushing the complexity of aerodynamic and mechanical design of rotating machines at very high levels. New concepts are required to improve the current machine performances from many points of view: aerodynamics, mechanics, rotordynamics, and manufacturing. Topology optimization is one of the most promising new approaches in the turbomachinery field for mechanical optimization of rotoric and statoric components. It can be a very effective enabler to individuate new paths and strategies, and to go beyond techniques already consolidated in turbomachinery design, such as parametric and shape optimizations. Topology optimization methods improve material distribution within a given design space (for a given set of boundary conditions and loads) to allow the resulting layout to meet a prescribed set of performance targets. Topology optimization allows also to change the topology of the structures (e.g., when a shape splits into two parts or develops holes). This methodology has been applied to a turbine component to reduce the static stress level and the weight of the part and, at the same time, to tune natural frequencies. Thus, the interest of this work is to investigate both static and dynamic/modal aspects of the structural optimization. These objectives can be applied alone or in combination, performing a single analysis or a multiple analysis optimization. It has been possible to improve existing components and to design new concepts with higher performances compared to the traditional ones. This approach could be also applied to other generic components. The research paper has been developed in collaboration with Nuovo Pignone General Electric S.p.A. that has provided all the technical documentation. The developed geometries of the prototypes will be manufactured in the near future with the help of an industrial partner.

Optimization Methods in Finance

2018 ◽  
Author(s):  
Gérard Cornuéjols ◽  
Javier Peña ◽  
Reha Tütüncü
Keyword(s):  
Optimization Methods

Optimization Methods in Finance

2006 ◽  
Author(s):  
Gerard Cornuejols ◽  
Reha Tutuncu
Keyword(s):  
Optimization Methods

Applied Optimization Methods for Wireless Networks

2009 ◽  
Author(s):  
Y. Thomas Hou ◽  
Yi Shi ◽  
Hanif D. Sherali
Keyword(s):  
Wireless Networks ◽  
Optimization Methods ◽  
Applied Optimization

Economics of coated paper production made from deinked pulp

TAPPI Journal ◽  
2013 ◽  
Vol 12 (4) ◽  
pp. 19-27
Author(s):  
PATRICK HUBER ◽  
LAURENT LYANNAZ ◽  
BRUNO CARRÉ
Keyword(s):  
Mechanical Properties ◽  
Optimization Methods ◽  
Coating Process ◽  
Coated Paper ◽  
Paper Production ◽  
Base Paper

The fraction of deinked pulp for coated paper production is continually increasing, with some mills using 100% deinked pulp for the base paper. The brightness of the coated paper made from deinked pulp may be reached through a combination of more or less extensive deinking, compensated by appropriate coating, to optimize costs overall. The authors proposed general optimization methods combined with Kubelka-Munk multilayer calculations to find the most economical combination of deinking and coating process that would produce a coated paper made from DIP, at a given target brightness, while maintaining mechanical properties.

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