Full Design of a Highly Loaded and Compact Contra-Rotating Fan Using Multidisciplinary Evolutionary Optimization

2013 ◽  
Author(s):  
Michael Joly ◽  
Tom Verstraete ◽  
Guillermo Paniagua
Keyword(s):  
High Speed ◽  
Flow Model ◽  
Safety Margin ◽  
Rocket Engines ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Through Flow ◽  
Computational Structural Mechanics ◽  
Full Design ◽  
Highly Loaded

Contra-rotation enables one to produce low-weight and high-load fans suitable for high-speed propulsion systems, such as Air Turbo Rocket engines. This paper presents a Multidisciplinary Design Optimization (MDO) methodology to achieve the full-design of highly-loaded and compact contra-rotating fans. It utilizes a multi-objective optimization at every step of the design. Performances of the two-stage machine is first evaluated by a through-flow model to determine an optimal flow path configuration. A novel parameterization based on span-wise distributions is used to smooth the transition between the preliminary design phase and the detailed three-dimensional shape optimization. High-fidelity aero-mechanical performances are then considered to generate the detailed design of the rotors, including the section profiles along the span, as well as lean and sweep. The multi-objective optimization algorithm treats simultaneously Computational Fluid Dynamics (CFD) and Computational Structural Mechanics (CSM) performances of both rotors. The designed rotors satisfy a 20% safety margin to the yielding strength of titanium. A pressure ratio of 3.07 is achieved with an overall efficiency of 72.4%. A comparison between the through-flow model and the CFD-based optimized shape is made, illustrating a very close match in velocity distributions and losses. It shows that the through-flow code is able to identify an optimal configuration for highly-loaded turbomachines and only needs a small refinement in the subsequent CFD-based optimization. The developed methodology allows to produce innovative configurations at a reduced time-to-market cost compared to traditional designs.

Full Design of a Highly Loaded Fan by Multi-Objective Optimization of Through-Flow and High-Fidelity Aero-Mechanical Performances

2012 ◽  
Author(s):  
Michael Joly ◽  
Tom Verstraete ◽  
Guillermo Paniagua
Keyword(s):  
Structural Integrity ◽  
Pressure Ratio ◽  
Optimization Techniques ◽  
High Fidelity ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Through Flow ◽  
Computational Structural Mechanics ◽  
Full Design ◽  
Highly Loaded

An innovative design methodology for axial flow compressors is developed utilizing a multi-objective optimization. The full design of a highly-loaded fan is considered, including through-flow and high-fidelity performance evaluations. To augment the explored design space and smoothen the whole process, optimization techniques are integrated into the different steps in the design. As an alternative to the traditional parametric studies performed for the flow path design, an optimization of the through-flow configuration is performed to initiate the aerodynamic design of the fan. To bypass two-dimensional sub-optimal results, the detailed design of the fan rotor geometry is then directly processed with a three-dimensional optimization, including several section profiles along the span, as well as lean and sweep. The multi-objective algorithm enables one to consider fluid and structure performances simultaneously. High-fidelity CFD (Computational Fluid Dynamics) and CSM (Computational Structural Mechanics) methods are used to guarantee the flow efficiency and the structural integrity of the finalized design. This methodology is applied to the design of a transonic fan achieving a pressure ratio of 2.1.

Multi-Objective Pricing Optimization for a High-Speed Rail Network Under Competition

2019 ◽  
Vol 2673 (7) ◽  
pp. 215-226 ◽  
Author(s):  
Huizhuo Cao ◽  
Xuemei Li ◽  
Vikrant Vaze ◽  
Xueyan Li
Keyword(s):  
High Speed ◽  
Programming Model ◽  
Pareto Frontier ◽  
Multiple Objectives ◽  
Multi Objective Optimization ◽  
High Speed Rail ◽  
Multi Objective ◽  
Trade Offs ◽  
Conflicting Objectives ◽  
Single Objective

Multi-objective pricing of high-speed rail (HSR) passenger fares becomes a challenge when the HSR operator needs to deal with multiple conflicting objectives. Although many studies have tackled the challenge of calculating the optimal fares over railway networks, none of them focused on characterizing the trade-offs between multiple objectives under multi-modal competition. We formulate the multi-objective HSR fare optimization problem over a linear network by introducing the epsilon-constraint method within a bi-level programming model and develop an iterative algorithm to solve this model. This is the first HSR pricing study to use an epsilon-constraint methodology. We obtain two single-objective solutions and four multi-objective solutions and compare them on a variety of metrics. We also derive the Pareto frontier between the objectives of profit and passenger welfare to enable the operator to choose the best trade-off. Our results based on computational experiments with Beijing–Shanghai regional network provide several new insights. First, we find that small changes in fares can lead to a significant improvement in passenger welfare with no reduction in profitability under multi-objective optimization. Second, multi-objective optimization solutions show considerable improvements over the single-objective optimization solutions. Third, Pareto frontier enables decision-makers to make more informed decisions about choosing the best trade-offs. Overall, the explicit modeling of multiple objectives leads to better pricing solutions, which have the potential to guide pricing decisions for the HSR operators.

Design-Optimization Approach to Multistage Axial Contra-Rotating Turbines

2013 ◽  
Author(s):  
Ernesto Sozio ◽  
Tom Verstraete ◽  
Guillermo Paniagua
Keyword(s):  
High Speed ◽  
Differential Evolution Algorithm ◽  
Design Procedure ◽  
Second Step ◽  
Optimization Approach ◽  
Rocket Engines ◽  
Multi Stage ◽  
Through Flow ◽  
Evolution Algorithm ◽  
Turbine Airfoils

Air Turbo Rocket engines, suitable for high-speed propulsion, require compact turbomachinery. This paper presents the design of an innovative multi-stage turbine mounted at the hub of a counter-rotating fan. Hence, the turbine airfoils are required to deliver high torque at low peripheral speeds. The design methodology specifically developed for this fourteen-stage turbine relies on two successive optimization cycles. The first one is based on a through-flow 1D code. This optimization cycle explores a vast set of possible design solutions. In a second step, an optimization using a 3D high fidelity RANS defines the 3D airfoil geometry. In order to accelerate the entire design procedure, a special routine was developed to morph the 1D results into the required info for the 3D optimization. Both the 1D and 3D optimizations are based on differential evolution algorithm.

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