Design and Optimization of Thermal Systems Episode 3 Part 1 pot

... constant Δ G y (b) x 4.0 3. 0 2.0 1. 0 4. 03. 0 3 2 1 2. 01. 00.0 U = x + y = 4 U*= 2 G = xy – 1 = 0 474 Design and Optimization of Thermal Systems seek the global extremum, which is usually unique and represents ... . ) . 35 14 14 8 22 49 04 32  mm 04 32 32 56 0 .  Therefore,  m  ¤ ¦ ¥ ³ µ ´  32 56 49 1 692 13 6 . . . /. The second derivative is...

Ngày tải lên: 06/08/2014, 15:21

... stage, of thermal energy, 39 V Validation, 2 83 example, 1 63 16 5 of mathematical models, 12 8, 16 0 1 63 of numerical models for systems, 252–2 53 three strategies for, 16 1 16 2 Valve types, 35 4, 35 5 Vapor ... 465 vs. optimal design, 18 Working models, communicating design through, 91 Worth as function of time, 38 4, 38 5, 39 0 future worth, 39 1 39 3...

Ngày tải lên: 06/08/2014, 15:21

... methods. 502 Design and Optimization of Thermal Systems Fxx x U x G x G nm 112 1 1 1 1 1 2 2 (, , , , , , )##LL L L t t  t t  t tt  t t   t t x G x Fxx x U m m nm 11 212 1 0$ ## L LL(, ... This leads to the equation 20 41 67 29 1 1 208 22 . (. / )  VV or 2.9 V  1  (9. 816 ) 1/ 2  3. 13 3 Therefore, V *  1. 425 m 3 . Then, A *  26. 536 m 2 and...

Ngày tải lên: 06/08/2014, 15:21

... given in the following table: rxyxyU 0 .3 2 .15 3. 86 8 .30 28.55 0.5 2 .33 4.20 9.79 31 .86 1. 0 2 .39 4.58 10 .96 34 .32 10 .0 2.46 4.84 11 .90 36 .29 10 0.0 2.48 4. 83 11 .99 36 .48 Different subinterval sizes ... 2.266 29 .36 4 0 Increment 1. 524 2.466 27. 614 10 . 935 Return 1. 524 2.470 27. 637 0 Increment 1 .35 2 2.670 26.668 –6.275 Return 1 .35 2 2.675 26.690 0 Incr...

Ngày tải lên: 06/08/2014, 15:21

... Design and Optimization of Thermal Systems with w 1  w 2  1 and 1. 4w 1  2.2w 2  0 From these equations, w 1  0. 611 and w 2  0 .38 9. Therefore, C *  (3. 5/0. 611 ) 0. 611 (14 .8/0 .38 9) 0 .38 9  11 .965 Then, ... gives w 1  10 /3, w 2  1, and w 3  –4 /3. Therefore, U * / . / . /  ¤ ¦ ¥ ³ µ ´   ¤ ¦ ¥ ³ µ ´    10 5 10 3 12 1 015 43...

Ngày tải lên: 06/08/2014, 15:21

... of the form au au au a u au nn 11 1 12 2 13 3 1 1 1 21 1 0 *** , * *     ! aau au a u au au nn nn 22 2 23 3 2 1 1 11 2 2 0 ** , * *     ! " *** , *    au a u nnnn 33 1 ... w ww w * .  ¤ ¦ ¥ ³ µ ´ ¤ ¦ ¥ ³ µ ´ ¤ ¦ ¥ ³ µ ´ ¤ ¦ 12 202 12 3 4 12 3 ¥¥ ³ µ ´  ¤ ¦ ¥ ³ µ ´ ¤ ¦ ¥ ³ µ ´ ¤ ¦ ¥ ³ pw 4 1 13 2 13 2 13 13 13 /// // µµ ´ ¤ ¦ ¥ ³...

Ngày tải lên: 06/08/2014, 15:21

... locations given as A 1 A–2 A 3 A–4 1 D 2–D 3 D 4–D 10 14 12 15 16 12 10 8 and 1 1 1–2 1 3 1 4 2 1 2–2 2 3 2–4 16 20 14 17 12 14 15 6 3 1 3 2 3 3 3–4 4 1 4–2 4 3 4–4 10 11 13 18 8 11 14 22 Determine ... Geometric, Linear, and Dynamic Programming 597 and for the others 1 1 1–2 1 3 2 1 2–2 2 3 3 1 3 2 3 3 12 15 19 15 13 17 18 18 16...

Ngày tải lên: 06/08/2014, 15:21

... data % x= [1 234 56]; y= [10 6.4 57.79 32 .9 19 .52 12 . 03 7.67]’; % % Form Matrix for exact fit % c1=[x (1) ^5 x (1) ^4 x (1) ^3 x (1) ^2 x (1) ^1 1]; c2=[x(2)^5 x(2)^4 x(2) ^3 x(2)^2 x(2) ^1 1]; c3=[x (3) ^5 x (3) ^4 x (3) ^3 ... 2.5 and 3. 6 % x1=2.5; y1=a (1) *x1^5+a(2)*x1^4+a (3) *x1 ^3+ a(4)*x1^2+a(5)*x1+a(6) x2 =3. 6; y2=a (1) *x2^5+a(2)*x2^4+a (3) *x2 ^3+ a(4)*x2^2+a(5)*...

Ngày tải lên: 06/08/2014, 15:21

... 1. 006 1. 4 015 18 .70 26. 63 0.707 30 5 .3 350.2 31 0 36 .85 98 1. 13 9 1. 007 1. 40 13 18 . 93 27. 01 0.705 31 0 .3 3 53. 1 31 5 41. 85 10 7 1. 1 21 1.007 1. 4 010 19 .15 27.40 0.704 31 5 .3 355.8 32 0 46.85 11 6 1. 1 03 1. 007 1. 4008 ... 12 9.0 227.6 14 0 – 13 3 .15 –208 2.540 1. 012 1. 411 9 9.646 12 .84 0.7 61 13 9 .1 236 .4 15 0 1 23. 15 19...

Ngày tải lên: 06/08/2014, 15:21

... 3. 8554E- 01 6 .14 46E 00 1. 6275E- 01 11 2.8 5 31 E 00 3. 5049E- 01 6.4951E 00 1. 539 6E- 01 12 3. 13 8 4E 00 3. 18 63E- 01 6.8 13 7 E 00 1. 4676E- 01 13 3.4523E 00 2.8966E- 01 7 .1 034 E 00 1. 4078E- 01 14 3. 7975E 00 2. 633 3E- 01 ... 4 .33 09E- 01 13 1. 1699E 00 2 .15 90E 01 5.2594E- 01 4 .10 95E- 01 14 1. 1 4 31 E 00 2 .32 17 E 01 5.0789E- 01 3. 9054E- 01...

Ngày tải lên: 06/08/2014, 15:21