空氣壓縮機設計外文翻譯

1、<p>　　畢業(yè)設計外文資料翻譯</p><p>　　學 院： 機械電子工程學院 </p><p>　　專 業(yè)： 過程裝備與控制工程 </p><p>　　姓 名： 崔紅飛 </p><p>　　學 號：

2、 080503105 </p><p>　　外文出處： Applied Energy 85 (2008)</p><p>　　625—633 </p><p>　　附 件： 1.外文資料翻譯譯文；2.外文原文。 </p><p>　　附件1：外文資料翻譯譯文<

3、/p><p>　　一維多級軸流壓縮機性能的解析優(yōu)化</p><p>　　Lingen Chen Jun Luo Fengrui Sun Chih Wu</p><p>　　摘要 對多級壓縮機的優(yōu)化設計模型，本文假設固定的流道形狀以入口和出口的動葉絕對角度，靜葉的絕對角度和靜葉及每一級的入口和出口的相對氣體密度作為設計變量，得到壓縮機基元級的基本方程和多級

4、壓縮機的解析關系。用數(shù)值實例來說明多級壓縮機的各種參數(shù)對最優(yōu)性能的影響。</p><p>　　關鍵詞 軸流壓縮機 效率 分析關系 優(yōu)化 </p><p><b>　　1 引言</b></p><p>　　軸流式壓縮機的設計是工藝技術的一部分，如果缺乏準確的預測將影響設計過程。至今還沒有公認的方法可使新的設計參數(shù)達到一個足夠精確的值，通

5、過應用一些已經取得新進展的數(shù)值優(yōu)化技術，以完成單級和多級軸流式壓縮機的設計。計算流體動力學（CFD）和許多更準確的方法特別是發(fā)展計算的CFD技術，已經應用到許多軸流式壓縮機的平面和三維優(yōu)化設計。它仍然是使用一維流體力學理論用數(shù)值實例來計算壓縮機的最佳設計。Boiko通過以下假設提出了詳細的數(shù)學模型用以優(yōu)化設計單級和多級軸流渦輪：（1）固定的軸向均勻速度分布（2）固定流動路徑的形狀分布，并獲得了理想的優(yōu)化結果。陳林根等人也采用了類似的想法

6、，通過假設一個固定的軸向速度分布的優(yōu)化設計提出了設計單級軸流式壓縮機一種數(shù)學模型。在本文中為優(yōu)化設計多級軸流壓縮機的模型，提出了假設一個固定的流道形狀，以入口和出口的動葉絕對角度，靜葉的絕對角度和靜葉及每一級的入口和出口的相對氣體密度作為設計變量，分析壓縮機的每個階段之間的關系，用數(shù)值實例來說明多級壓縮機的各種參數(shù)對最優(yōu)性能的影響。</p><p>　　2 基元級的基本方程</p><p&g

7、t;　　考慮圖1所示由n級組成的軸流壓縮機, 其某一壓縮過程焓熵圖和中間級的速度三角形見圖2和圖3，相應的中間級的具體焓熵圖如圖4，按一維理論作級的性能計算。按一般情況列出軸流壓縮機中氣體流動的能量方程和連續(xù)方程,工作流體和葉輪的速度。在不同級的軸向流速不為常數(shù)，即考慮, () 時的能量和流量方程。在下列假定下分析軸流壓縮機的工作: </p><p>　　·相對于穩(wěn)定回轉的動葉、靜葉和導向葉片機構, 氣

8、體流動是穩(wěn)定的； </p><p>　　·流體是可壓縮、無黏性和不導熱的； </p><p>　　·通過級的流體質量流量為定值；</p><p>　　·在實際工質的情況下, 壓縮過程是均勻的；</p><p>　　·本級出口絕對氣流角為下一級進口角絕對氣流角；</p><p>　

9、　·忽略進出口管道的影響。 </p><p>　　在每一級的具體焓如下：</p><p><b>　?。?）</b></p><p><b>　?。?）</b></p><p>　　第階段的動葉和靜葉的焓值損失總額計算如下：</p><p><b>　　

10、（3）</b></p><p><b>　?。?）</b></p><p>　　其中是第階段動葉葉片輪廓總損失系數(shù)，是第階段靜葉葉片輪廓總損</p><p><b>　　失的系數(shù)。</b></p><p>　　圖1 n級軸流式壓縮機的流量路徑。</p><p>

11、　　葉片輪廓損失系數(shù)和是工作流體和葉片的幾何功能參數(shù)。它們可以使用各種方法及視作常量來計算。當和看做工作流體和葉片的幾何功能參數(shù)時，可以使用Ref迭代的方法來計算損失系數(shù)。使用迭代方法解決計算損失系數(shù)：（1）選擇和初始值，然后計算各級的參數(shù)。（2）計算的，值，重復第一步，直到計算值和原值之間的差異足夠小。</p><p>　　第階段理論所需計算得：</p><p><b>　

12、?。?）</b></p><p>　　第階段實際所需計算得：</p><p>　　圖2 n級壓縮機的焓熵圖</p><p>　　圖3 中間級的速度三角形</p><p>　　圖4 中間級的焓熵圖</p><p><b>　?。?）</b></p><p>　　

13、基元級反應度定義為。因此有：</p><p><b>　?。?）</b></p><p>　　在這里，視作速度系數(shù),它們的計算為:</p><p><b>　　和 </b></p><p><b>　?。?）</b></p><p><b>

14、　?。?）</b></p><p>　　3 級組的數(shù)學模型</p><p>　　壓縮機各級的比壓縮功為則總的比耗功為， 各級的滯止等熵能量頭為，則級組各級滯止等熵比壓縮功總和為，級組等熵比壓縮功為, 則為壓縮機的重熱系數(shù)。根據(jù)定義,多級壓縮機通流部分滯止等熵效率為： </p><p>　　求解確定各級能量頭的分配：</p><p&g

15、t;<b>　?。?1）</b></p><p>　　方程式（11）同樣可以寫作：</p><p><b>　　….</b></p><p><b>　　(12)</b></p><p>　　出于方便，一些參數(shù)簡化約束計算做了如下定義：</p><p>

16、<b>　?。?3）</b></p><p><b>　?。?4）</b></p><p><b>　　（15）</b></p><p><b>　?。?6）</b></p><p>　　這里 是氣動力函數(shù)，在這里的是滯止聲速相對應的，且 是相對面積，是相

17、對密度，是葉片高 是流量系數(shù)。</p><p>　　通過Boiko的論文引入等熵線系數(shù)，一個是：</p><p><b>　?。?7）</b></p><p>　　這里 （18）</p><p>　　因此約束條件也可寫作<

18、/p><p><b>　?。?9）</b></p><p><b>　　（20）</b></p><p><b>　?。?1）</b></p><p>　　在這里多級軸流式壓縮機滯止等熵線的效率計算如下：</p><p><b>　　（22）<

19、;/b></p><p>　　這里是多級壓縮機的等熵工作系數(shù)，每一級的等熵工作系數(shù)是。</p><p>　　現(xiàn)在的優(yōu)化問題是尋找和的最佳值，來找出在方程（19~21)約束下的目標函數(shù)的最大值。</p><p><b>　　4 結論</b></p><p>　　一旦這些系統(tǒng)和定義的常數(shù)按目標實現(xiàn)自己系統(tǒng)功能，在他最

20、理想的環(huán)境下達到預計函數(shù)最大的程度。其呈現(xiàn)的并非是一個線性的而是一階梯函數(shù)。本優(yōu)化模型是（2n +1）約束功能和一個n級軸流壓縮機（4n + 1）變量的非線性規(guī)劃程序。例如改善外部法或SUMT法，對于這樣的問題Powell采用在無約束極小化技術與一維最小的拋物線插值方法。人們已經發(fā)現(xiàn)是非常有作用的。</p><p><b>　　表1 各級相對面積</b></p><p&g

21、t;　　表2 原始數(shù)據(jù)和設計計劃</p><p><b>　　5 數(shù)值計算例子</b></p><p>　　在計算中，做，，，，，,則為0.04, 為0.025和為0.02的設置。表1列出了在每個級的相對面積。應當指出會有一些優(yōu)化目標的關系與這些量綱的影響是工作流體參數(shù)的功能和流動路徑的幾何參數(shù)設置。然而，得到的關系不會改變流體性質。對于3級壓縮機中，有13個設計變

22、量和7個約束條件。此外，較低上限約束的13個設計變量的值也應考慮在計算中。優(yōu)化變量的上限和下限，原來的設計方案中優(yōu)化不同流量系數(shù)和工作系數(shù)的結果列于表2。由此可以看出，優(yōu)化程序是有效和實用的。</p><p>　　計算結果表明，最佳停滯等熵效率是隨工作系數(shù)和流量系數(shù)的遞減而遞減的函數(shù)。工作系數(shù)影響最佳停滯等熵效率的作用大于流量系數(shù)。各值流量系數(shù)和工作系數(shù)，最優(yōu)的最后一級輸出絕對角度總是接近。</p>

23、<p><b>　　6 結論</b></p><p>　　在本文中在研究固定流形的多級軸流壓縮機的效率優(yōu)化中使用一維流體理論研究。根據(jù)壓縮機普遍特性和特征間關系。由展示的數(shù)值量其結果可以為多級壓縮機的性能分析和優(yōu)化提供一些指導。這是一個初步的研究將其不可避免的使用多目標數(shù)值優(yōu)化技術和人工神經網(wǎng)絡算法用于分析壓縮機優(yōu)化。</p><p><b>

24、　　參考文獻（見原文）</b></p><p><b>　　術語</b></p><p>　　附件2：外文原文（復印件）</p><p>　　Design efficiency optimization of one-dimensional multi-stage axial-flow compressor</p>&

25、lt;p>　　Lingen Chen , Jun Luo , Fengrui Sun , Chih Wu</p><p>　　Postgraduate School, Naval University of Engineering, Wuhan, 430033, PR China</p><p>　　Mechanical Engineering Department, US Nava

26、l Academy, Annapolis MN21402, USA</p><p>　　Available online 28 November 2007</p><p><b>　　Abstract</b></p><p>　　A model for the optimal design of a multi-stage compressor

27、, assuming a fixed configuration of the flow-path, is presented.The absolute inlet and exit angles of the rotor, the absolute exit angle of the stator, and the relative gas densities at the inlet and exit stations of th

28、e stator, of every stage, are taken as the design variables. Analytical relations of the compressor elemental stage and the multi-stage compressor are obtained. Numerical examples are provided to illustrate the effects o

29、f </p><p>　　Keywords: Multi-stage axial-flow compressor; Efficiency; Analytical relation; Optimization</p><p>　　1. Introduction</p><p>　　The design of the axial-flow compressor is p

30、artially an art. The lack of accurate prediction influences the design process. Until today, there are no methods currently available that permit the prediction of the values of these quantities to a sufficient accuracy

31、for a new design. Some progresses has been achieved via the application of numerical optimization techniques to single- and multi-stage axial-flow compressor design [1–22].Especially with the development of computational

32、 fluid-dynamics </p><p>　　? The working fluid flows stably relative to the vanes, stators and rotors, which rotate at a fixed speed.</p><p>　　? The working fluid is compressible, non-viscous and

33、 adiabatic.</p><p>　　? The mass-flow rate of the working fluid is constant.</p><p>　　? The compression process is homogeneous in the working fluid.</p><p>　　? The absolute outlet an

34、gle of the working fluid, in jth stage, is equal to the absolute inlet angle of the working fluid in (j+1)th stage.</p><p>　　? The effects of intake and outlet piping are neglected.</p><p>　　The

35、 specific enthalpies at every station are as follows</p><p><b>　?。?）</b></p><p><b>　?。?）</b></p><p>　　The total profile losses of the jth stage rotor and the

36、 stator are calculated as follows:</p><p><b>　?。?）</b></p><p><b>　　（4）</b></p><p>　　Whereis the total profile loss coefficient of jth stage rotor-blade and i

37、s that of jth stage-stator blade.</p><p>　　Fig. 1. Flow-path of a n-stage axial-flow compressor</p><p>　　Fig. 2. Enthalpy–entropy diagram of a n-stage compressor</p><p>　　Fig. 3. Ve

38、locity triangle of an intermediate stage</p><p>　　Fig. 4. Enthalpy–entropy diagram of an intermediate stage.</p><p>　　The blade profile loss-coefficients and are functions of parameters of the

39、 working fluid and blade geometry. They can be calculated using various methods and are considered to be constants. When and are functions of the parameters of the working fluid and blade geometry, the loss coefficients

40、 can be calculated using the method of Ref. [24], which was employed and described in Ref. [21]. The optimization problem can be solved using the iterative method:</p><p>　　(1) First, select the original val

41、ues of and and then calculate the parameters of the stage.</p><p>　　(2) Secondly, calculate the values of and , and repeat the first step until the differences between the calculated values and the original

42、 ones are small enough.</p><p>　　The work required by the jth stage is</p><p><b>　?。?）</b></p><p>　　The work required by the jth rotor is:</p><p><b>　

43、　（6）</b></p><p>　　The degree of reaction of the jth stage compressor is defined as . Hence, one has</p><p><b>　?。?）</b></p><p>　　Where， are the velocity coefficien

44、ts, and they are defined as: andThe constraint conditions can be obtained from the energy-balance equation for the one-dimensional flow</p><p><b>　?。?）</b></p><p><b>　?。?）</

45、b></p><p>　　3. Mathematical model for the behaviour of the multi-stage compressor</p><p>　　The compression work required by each stage is. The total compression work required by the multi-sta

46、ge compressor is . The stagnation isentropic enthalpy rise of every stage is . The sum of the stagnation isentropic enthalpy rise of each stage is, while the stagnation isentropic enthalpy rise of the multi-stage compres

47、sor is . One has,The stagnation isentropic efficiency of the multi-stage axial-flow compressor is</p><p><b>　?。?0）</b></p><p>　　The total energy-balance of a n-stage compressor gives

48、:</p><p><b>　　（11）</b></p><p>　　Eq. (11) can be rewritten as</p><p><b>　　….</b></p><p><b>　　(12)</b></p><p>　　For conve

49、nience, in order to make the constraints dimensionless, some parameters are defined:</p><p><b>　　（13）</b></p><p><b>　?。?4）</b></p><p><b>　?。?5）</b&g

50、t;</p><p><b>　?。?6）</b></p><p>　　Where are the aerodynamic functions, and , where is the stagnation sound velocity and ，is the relative area, is the relative density, where l is t

51、he height of the blade, and is flow coefficient. Introducing the isentropic coefficient used by Boiko [23], one has</p><p><b>　?。?7）</b></p><p>　　Where

52、 （18）</p><p>　　Therefore, the constraint conditions can be rewritten as：</p><p><b>　　（19）</b></p><p><b>　?。?0）</b></p><p><b

53、>　　（21）</b></p><p>　　and the stagnation isentropic efficiency of the multi-stage axial-flow compressor can be rewritten as</p><p><b>　?。?2）</b></p><p>　　Where i

54、s isentropic work coefficient of the multi-stage. The isentropic work coefficient of each stage is defined as .Now the optimization problem is to search the optimal values of and for finding the maximum value of the obj

55、ective function under the constraints of Eqs. (19)~(21).</p><p>　　4. Solution procedure</p><p>　　Once the system variables, the objective function, and the constraints are defined, a suitable m

56、ethod has to be adopted to determine the values of the design variables that maximize the objective function while satisfying the given constraints. The present optimization model is a non-linear programming procedure wi

57、th</p><p>　　Table 1Relative areas for the stations</p><p>　　Table 2Original and optimal design plans</p><p>　　5. Numerical example</p><p>　　In the calculations, ,, , ,

58、n = 3, R = 286.96 J/(kg·K), , and are set. The relative areas at every station are listed in Table 1. It should be pointed out that there will be some influence on the relation of the optimization objective with th

59、ese dimensionless parameters if are functions of the working fluid parameters and geometry parameters of the flow-path configuration. However, the relation obtained will not change qualitatively. For a 3-stage compressor

60、, there are 13 design variables and 7</p><p>　　6. Conclusion</p><p>　　In this paper, the efficiency optimization of a multi-stage axial-flow compressor for a fixed flow shape has been studied us

61、ing one-dimensional flow-theory. The universal characteristic relation of the compressor be haviour is obtained. Numerical examples are presented. The results can provide some guidance as to the performance analysis and

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83、 optimal</p><p>　　twist at the outlet of blade. Int J Pow Energy Syst 1998;18(1):16–20.</p><p>　　[28] Chen L, Zhang J, Wu C, Blank D, Sun F. Analysis of multi-objective decision-making for marin

84、e steam turbine. Int J Pow Energy</p><p>　　Syst 1998;18(2):96–101.</p><p>　　[29] Chen L, Zhou S, Wu C, Sun F. Preliminary design optimization of a steam generator. Energy Convers Manage 2002;43(

85、13):1651–61.</p><p>　　[30] Lin BJ, Hung CI, Tang EJ. An optimal design of axial-flow fan blades by the machining method and an artificial neural-network.</p><p>　　Proc Inst Mech Eng 2002;216(C3)

86、:367–76.</p><p>　　[31] Qin X, Chen L, Sun F, Wu C. Efficiency optimization for an axial-flow steam-turbine stage using genetic algorithm. Appl Therm Eng</p><p>　　2003;23(18):2307–16.</p>