Progresses in application of computational ?uid dynamic methods to large scale wind turbine aerodynamics?

The computational ?uid dynamics (CFD) methods are applied to aerody-namic problems for large scale wind turbines. The progresses including the aerodynamic analyses of wind turbine pro?les, numerical ?ow simulation of wind turbine blades, evalu-ation of aerodynamic performance, and multi-objective blade optimization are discussed. Based on the CFD methods, signi?cant improvements are obtained to predict two/three-dimensional aerodynamic characteristics of wind turbine airfoils and blades, and the vorti-cal structure in their wake ?ows is accurately captured. Combining with a multi-objective genetic algorithm, a 1.5 MW NH-1500 optimized blade is designed with high e?ciency in wind energy conversion.     

Framework for efficient feature selection in genetic algorithm based data mining

We present the design of more effective and efficient genetic algorithm based data mining techniques that use the concepts of feature selection. Explicit feature selection is traditionally done as a wrapper approach where every candidate feature subset is evaluated by executing the data mining algorithm on that subset. In this article we present a GA for doing both the tasks of mining and feature selection simultaneously by evolving a binary code along side the chromosome structure used for evolving the rules. We then present a wrapper approach to feature selection based on Hausdorff distance measure. Results from applying the above techniques to a real world data mining problem show that combining both the feature selection methods provides the best performance in terms of prediction accuracy and computational efficiency.     

气动、结构、载荷相协调的大型风电叶片自主研发进展

从叶片设计的3个关键环节（气动设计、结构设计和载荷评估）出发,对叶片自主研发进展进行了总结分析．在气动设计方面,概述了计算流体动力学（computational fluid dynamics, CFD）方法、涡方法和叶素动量（blade element momentum, BEM）方法,并依据工程中广泛应用的BEM方法,指出了低风速区风电叶片的解决思路;在结构设计方面,简要概述了基于梁模型的传统设计分析方法,分析了其在大型复合材料叶片薄壳结构上的不足,并对有限元方法（finite element method, FEM）在叶片结构分析中的应用进展进行了介绍;在载荷评估方面,介绍了其对叶片和整机其它部件的影响,阐述了载荷预估方面的工作进展．然后,通过分析3个关键环节之间的相互关系,得到如下结论:建立气动、结构和载荷相协调的叶片优化设计体系,才能真正满足高效低成本的需要．最后,指明了需要进一步研究的主要方向,即高效低载翼型研究,结构非线性有限元分析,气动-结构耦合研究,设计标准制定．最终目标是建立适合中国风资源特点的叶片研发体系,推动我国风电产业发展.     

Discrete boundary smoothing using control node parameterisation for aerodynamic shape optimisation

This paper presents an automated aerodynamic optimisation algorithm using a novel method of parameterising the search domain and geometry by employing user–defined control nodes. The displacement of the control nodes is coupled to the shape boundary movement via a ‘discrete boundary smoothing’. This is initiated by a linear deformation followed by a discrete smoothing step to act on the boundary during the mesh movement based on the change in its second derivative. Implementing the discrete boundary smoothing allows both linear and non-linear shape deformation along the same boundary dependent on the preference of the user. The domain mesh movement is coupled to the shape boundary movement via a Delaunay graph mapping. An optimisation algorithm called Modified Cuckoo Search (MCS) is used acting within the prescribed design space defined by the allowed range of control node displacement. In order to obtain the aerodynamic design fitness a finite volume compressible Navier-Stokes solver is utilized. The resulting coupled algorithm is applied to a range of case studies in two dimensional space including the optimisation of a RAE2822 aerofoil and the optimisation of an intake duct under subsonic, transonic and supersonic flow conditions. The discrete mesh–based optimisation approach outlined is shown to be effective in terms of its generalised applicability, intuitiveness and design space definition.     

Quantile-based robust optimization of a supersonic nozzle for organic rankine cycle turbines

Organic Rankine Cycle (ORC) turbines usually operate in thermodynamic regions characterized by high-pressure ratios and strong non-ideal gas effects, complicating the aerodynamic design significantly. Systematic optimization methods accounting for multiple uncertainties due to variable operating conditions, referred to as Robust Optimization may benefit to ORC turbines aerodynamic design. This study presents an original and fast robust shape optimization approach to overcome the limitation of a deterministic optimization that neglects operating conditions variability, applied to a well-known supersonic turbine nozzle for ORC applications. The flow around the blade is assumed inviscid and adiabatic and it is reconstructed using the open-source SU2 code. The non-ideal gasdynamics is modeled through the Peng-Robinson-Stryjek-Vera equation of state. We propose here a mono-objective formulation which consists in minimizing the α-quantile of the targeted Quantity of Interest (QoI) under a probabilistic constraint, at a low computational cost. This problem is solved by using an efficient robust optimization approach, coupling a state-of-the-art quantile estimation and a classical Bayesian optimization method. First, the advantages of a quantile-based formulation are illustrated with respect to a conventional mean-based robust optimization. Secondly, we demonstrate the effectiveness of applying this robust optimization framework with a low-fidelity inviscid solver by comparing the resulting optimal design with the ones obtained with a deterministic optimization using a fully turbulent solver.     

Research status and trend of wind turbine aerodynamic noise?

The main components of the wind turbine aerodynamic noise are introduced. A detailed review is given on the theoretical prediction, experimental measurement, and numerical simulation methods of wind turbine noise, with speci?c attention to appli-cations. Furthermore, suppression techniques of wind turbine aerodynamic noise are discussed. The perspective of future research on the wind turbine aerodynamic noise is presented.     

RBF Neural Network Based Prediction on Blade Surface Pressure Fields in Compressors北大核心CSCD

The airflow characteristics of the internal flow path of an aero-engine compressor are complex, and the vortex flow field around the blade is characterized by high pressure, high speed, rotation, and unsteadiness. Therefore, there is an urgent need to calculate and predict the aerodynamic characteristics of the complex flow field around the compressor blade efficiently and accurately. The computational fluid dynamics (CFD) method was used to generate the aerodynamic load distribution on the blade surface under different operating conditions for the study of the complex flow fields around aero-engine blades. The radial based function (RBF) neural network was applied to establish the pressure surface aerodynamic load prediction model, and the neural network modeling method was combined with the flow field calculation. The neural network method can learn and train the CFD-based data set to properly compensate the errors from the CFD, which provides a reference for the effective prediction of the complex flow fields around aero-engine compressor blades. © 2023 Editorial Office of Applied Mathematics and Mechanics. All rights reserved.     

Fast reconstruction of aerodynamic shapes using evolutionary algorithms and virtual nash strategies in a CFD design environment

This paper compares the performances of two different optimisation techniques for solving inverse problems; the first one deals with the Hierarchical Asynchronous Parallel Evolutionary Algorithms software (HAPEA) and the second is implemented with a game strategy named Nash-EA. The HAPEA software is based on a hierarchical topology and asynchronous parallel computation. The Nash-EA methodology is introduced as a distributed virtual game and consists of splitting the wing design variables-aerofoil sections-supervised by players optimising their own strategy. The HAPEA and Nash-EA software methodologies are applied to a single objective aerodynamic ONERA M6 wing reconstruction. Numerical results from the two approaches are compared in terms of the quality of model and computational expense and demonstrate the superiority of the distributed Nash-EA methodology in a parallel environment for a similar design quality.     

Stall-delay modelling of wind turbine blades

Most aerodynamic design tools for horizontal-axial wind turbines are based on the blade-element momentum theory (BEM). Due to the nature of this theory, the design tools need 2-D steady sectional lift and drag curves as an input. In practice, flow over a wind turbine rotor blade is neither two-dimensional nor steady, and is affected by rotation. Pioneering experiments have identified a consequence: at inboard rotor blade sections stall is delayed. This so-called Himmelskamp effect [1] gives a larger lift than predicted and, as a result, a higher power and loading than expected. Consequently, an aerodynamic model is needed to explain and predict sectional lift and drag under rotating conditions. (© 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

风力机气动噪声研究现状与发展趋势

首先介绍风力机气动噪声源的基本组成,然后对风力机气动噪声理论预测、实验测试和数值模拟方法进行阐述,重点论述这3类方法在风力机气动噪声研究中的应用现状,并讨论风力机气动噪声抑制技术,最后简要展望风力机气动噪声研究的发展趋势     

Investigation of horizontal-axis wind turbine (HAWT) blade three-dimensional rotational e?ect based on ?eld experiments?

Field experiments are performed on a two-bladed 33 kW horizontal-axis wind turbine (HAWT). The pressures are measured with 191 pressure sensors positioned around the surfaces of seven spanwise section airfoils on one of the two blades. Three-dimensional (3D) and two-dimensional (2D) numerical simulations are performed, respectively, on the rotor and the seven airfoils of the blade. The results are compared with the experimental results of the pressure distribution on the seven airfoils and the lift coe?cients. The 3D rotational e?ect on the blade aerodynamic characteristics is then studied with a numerical approach. Finally, some conclusions are drawn as follows. From the tip to the root of the blade, the experimental di?erential pressure of the blade section airfoil increases at ?rst and then decreases gradually. The calculated 3D result of the pressure distribution on the blade surface is closer to that of the experiment than the 2D result. The 3D rotational e?ect has a signi?cant impact on the blade surface ?ow and the aerodynamic load, leading to an increase of the di?erential pressure on the airfoils and their lift coe?cient than that with the 2D one because of the stall delay. The in?uence of the 3D rotational e?ect on the wind turbine blade especially takes place on the sections with ?ow separation.     

Optimisation of gravity-fed water distribution network design: A critical review

This paper surveys the literature on the optimisation of water distribution network design. The water distribution network design (WDND) optimisation problem entails finding the material and diameter of each pipe in the network so that the total cost of the network is minimised without violating any hydraulic constraints. This is a difficult combinatorial optimisation problem, in which decision variables are discrete and both cost function and constraints are non-linear. Over the past 30 years, a large number of methods, especially in the field of (meta) heuristics, have been developed to solve this problem, most of which obtain good results on the available benchmark networks. In addition to outlining the basic features of each method, a detailed computational comparison is presented. Based on this comparison, some issues with the current state of the art in this domain are discussed, and some future research directions are suggested. Additionally, the need for an adequate set of benchmark instances is motivated, and the minimal requirements for an instance set generator are discussed.     

Modular global optimisation in chemical engineering

Chemical Engineering design and analysis is dominated by the use of modular computational systems restricting the use of rigorous global optimisation techniques. Other engineering domains also exploit modularity in order to break down complex tasks to allow the use of legacy codes, to protect intellectual property, and to allow large teams to work on problems. By casting modules in a generic form such systems could be recast to incorporate interval based methods. In this paper we explore the use of five interval contraction methods to improve the performance of interval based optimization of modular process design systems: consistency methods, constraint propagation, Interval Gaussian elimination, Interval Newton and Linear Programming. It is shown that the Linear Programming contractor provides the greatest value in contracting the intervals and that constraint propagation and Interval Gaussian elimination (as implemented here) provides less of an impact. Other contractors do provide value and the LP contractor will be of less value as the problem size increases so it is necessary to include a number of contractors which can be done at small computational cost. A number of challenges are outlined which need to be addressed before there can be routine use of interval global optimization in modular systems.     

风力机叶型增升及叶尖流动控制研究

研究了两种改善风力机叶型气动性能的流动控制技术,分别对风力机专用S809翼型和较大升阻比的FX 60-100翼型进行应用研究．首先,通过在叶型前缘加装流动偏转器,研究流动偏转器对叶型流动分离的控制效果．并采用多岛基因算法,对流动偏转器进行多参数优化．结果表明:流动偏转器可以有效控制叶型的失速特性,推迟失速攻角和增加升力;基因优化算法能更大地提升流动偏转器的控制效果．其次,基于对风力机叶尖旋涡和尾涡特征以及叶片表面压力分布的分析,在叶片尖部加装不同倾斜角的旋涡扩散器控制叶尖涡．结果表明:涡扩散器能够提高叶尖涡涡核的总压,削弱其旋涡强度,使风力机尾流旋涡耗散更快,从而可以减小噪声,提高叶片效率．     

A comparison of parallel large-scale knowledge acquisition using rough set theory on different MapReduce runtime systems

Nowadays, with the volume of data growing at an unprecedented rate, large-scale data mining and knowledge discovery have become a new challenge. Rough set theory for knowledge acquisition has been successfully applied in data mining. The recently introduced MapReduce technique has received much attention from both scientific community and industry for its applicability in big data analysis. To mine knowledge from big data, we present parallel large-scale rough set based methods for knowledge acquisition using MapReduce in this paper. We implemented them on several representative MapReduce runtime systems: Hadoop, Phoenix and Twister. Performance comparisons on these runtime systems are reported in this paper. The experimental results show that (1) The computational time is mostly minimum on Twister while employing the same cores; (2) Hadoop has the best speedup for larger data sets; (3) Phoenix has the best speedup for smaller data sets. The excellent speedups also demonstrate that the proposed parallel methods can effectively process very large data on different runtime systems. Pitfalls and advantages of these runtime systems are also illustrated through our experiments, which are helpful for users to decide which runtime system should be used in their applications.     

大型近海水平轴风力机转轮的空气动力学性能优化判据

以近海风能工程为研究目标,对具有不同特性参数（设计风速、叶尖线速度和转轮实度）的大容量（1～10 MW）风力机转轮的气动性能与几何特性进行分析与研究．首先提出大型机组转轮气动性能优化判据:在其直径最小的前提下具有尽可能高的年可用风能特性因数以及与之相关的风能利用系数,因而可捕获最多风能,使年发电量最大．接着给出影响它的几个主要气动参数,如转轮设计风速、叶尖线速度以及转轮实度,并分析风力机在近海气象条件下运转时上述两个气动指标随这些参数变化的规律．提供的气动分析方法及结果可作为大型近海风力机转轮气动性能的评价基础．     

An efficient strategy for reliability-based multidisciplinary design optimization of twin-web disk with non-probabilistic model

The twin-web disk holds big promise for increasing efficiency of the aircraft engine. Its reliability-based multidisciplinary design optimization involves several disciplines including fluid mechanics, heat transfer, structural strength, and vibration. The solution to this optimization problem requires three-loop calculations including loops for optimization, reliability, and interdisciplinary consistence often making its computational cost unacceptably high. The lack of sufficient amount of probabilistic data, especially for this brand-new turbine disk, makes matters worse. In this paper, the non-probabilistic uncertain variables are described by an evidence theory-based fuzzy set method, which we extend to general structure of uncertain data. We also propose two modifications of the active learning kriging model: one of them for the purpose of optimization with respect to the distance from the optimum point and another one for the purpose of assessing reliability by introducing the importance concept. Applications of these two modifications are demonstrated in this paper. Finally, a multi-adaptive learning kriging strategy for non-probabilistic reliability-based multidisciplinary design optimization of twin-web disk is proposed to improve its power efficiency and reliability in a computationally effective way.     

A coupled blade element momentum – Computational fluid dynamics model for evaluating tidal stream turbine performance

A modelling approach based on blade element momentum theory is developed for the prediction of tidal stream turbine performance in the ocean environment. Through the coupling of the blade element momentum method with computational fluid dynamics, the influence of upstream hydrodynamics on rotor performance is accounted for. Incoming flow onto the rotor can vary in speed and direction compared to free-stream conditions due to the presence of obstructions to the flow in the upstream, due to other devices for example, or due to the complexity of natural bathymetries. The relative simplicity of the model leads to short run times and a lower demand on computational resources making it a useful tool for considering more complex engineering problems consisting of multiple tidal stream turbines. Results from the model compare well against both measured data from flume experiments and results obtained using the classical blade element momentum model. A discussion considering the advantages and disadvantages of these different approaches is included.     

An optimization procedure for the design of prop-rotors in high speed cruise including the coupling of performance,aeroelastic stability,and structures

An optimization procedure is developed to address the complex problem of designing prop-rotors in high speed cruise. The objectives are maximization of the aerodynamic efficiency in high speed cruise and minimization of the total rotor weight. Constraints are imposed on aeroelastic stability in cruise and rotor thrust. An isotropic box beam is used to model the principal load carrying member in the blade. Design variables include blade sweep and twist distributions, rotational velocity in cruise, and the box beam wall thickness. Since the optimization problem is associated with multiple design objectives, the problem is formulated using a multiobjective formulation technique known as the Kreisselmeier-Steinhauser function approach. The optimization algorithm is based on the method of feasible directions. A hybrid approximate analysis technique is used to reduce the computational expense of using exact analyses for every function evaluation within the optimizer. The results are compared to two reference rotors, unswept and swept. The optimum result shows significant improvements in the propulsive efficiency in cruise and reductions in the rotor weight without loss of aeroelastic stability or thrust, when compared to the reference unswept rotor. The swept reference rotor is initially unstable and the optimization procedure has been successful in producing a blade design which is fully stable with significant improvements in efficiency and blade weight. Off-design studies performed indicate that the optimum rotor maintains high propulsive efficiency over a wide range of operating conditions.