The applications of the non-linear equations systems algorithms for the heat transfer processes

Size: px
Start display at page:

Download "The applications of the non-linear equations systems algorithms for the heat transfer processes"

Transcription

1 MHEMICL MEHODS, COMPUIONL ECHNIQUES, INELLIGEN SYSEMS he applatos o the o-lear equatos systems algorthms or the heat traser proesses CRISIN PRSCIOIU, CRISIN MRINOIU Cotrol ad Computer Departmet Iormats Departmet Petroleum Gas Uversty o Ploest Ploest, 39 Bd. Buurest, ROMNI patrasouu@upg-ploest.ro marou_@yahoo.om bstrat: he paper presets the author s researhes the heat traser mathematal models ad the mplemetato o the umerally algorthms or solvg the o-lear equatos systems. he artle has three parts. I the rst part s preseted the mathematally model o the heat exhager. he seod part s dedated to study o the umerally algorthms or solvg the o-lear equatos systems. he authors have studed three algorthms: the Newto-Raphso algorthm based o aalytally expressos o the Jaobea matrx, the Newto-Raphso algorthm based o umerally values o the Jaobea matrx ad the Broyde algorthm. he last part otas a aalyss o the perormaes o theses algorthms rapport o alulus eort ad alulus preso rtera. Key-Words: o-lear equatos system, Newto-Raphso algorthm, Broyde algorthm, mathematal modelg, heat exhager, umerally aalyze Itroduto he mathematal modellg o the hemal proesses represets a mportat problem or the proess desg ad or the hemal proess operatg. lass o the hemal proesses s represeted by the heat traser proesses. he authors have studed the heaters proess ad they have modeled the radato seto o the tubular heater []. he researhes have permtted or the authors to buldg the statally haratersts o the tubular heater there ad have otrbuted to developed the optmal ombusto otrol struture []. I the last years, the authors have studed the modelg o the heat exhager, or desg the otrol systems whh otaed heat exhagers [3]. O mportat problem o the heat exhagers modelg s the mathematal algorthm used to solve the model. Beause the mathematal model o these proesses s a equatos system, the authors have studed the algorthms used to solve the model. he struture ad the mathematal model o the heat traser proess most mportat lass o the heat traser proesses s deed by the heat exhagers. he authors have studed, modeled ad smulated the shell ad tube heat exhager havg luxes outer low. I gure s preseted a seto o the shell ad tube heat exhager [3]. Fg. he shell ad tube heat exhager seto he heat exhager s haraterzed by our let ad two outlet varables, gure. he let varables are: h, Q hot the put hot temperature ad the hot low rate, l, Q old the put old temperature ad the low rate o old lud. he outlet varables are: h - the outlet temperature o the hot lud, the outlet temperature o the old lud. ISSN: ISBN:

2 MHEMICL MEHODS, COMPUIONL ECHNIQUES, INELLIGEN SYSEMS Fg. he shell ad tube heat exhager struture Mathematal model o heat exhager ossts to heat balae equato assoated wth the hot low ad the old low ad the Delaware model o the heat exhager [4]. he ompat orm o the mathematal model o the exhager s a o-lear equato system wth two equatos ad two varables h,, h. he o lear utos o the equatos system are the ext orm: Q = Q ; hot p,hot h h old p,old h h h = Qhot p,hot h h k. 3 h l 3 he algorthms used to solvg the o-lear equato systems Let the o-lear equato system x,x, Kx x,x, Kx x,x, Kx respetvely X, 4 F, 5 where the X vetor represets the o-lear equato system varables [ x,x, K,x ] X =. 6 he vetor F otas the utos deed to o-lear equato system 4 [,, K, ] F =. 7 he equato system soluto may be approxmated usg the suessve alulatos, started at tal estmato [ ] X = x,x, K,x. 8 he soluto o the o-lear system s determated usg the Newto method [5]. hs method s based o the aylor lear approxmato ormula = X + 0 x. 9 X X = 0 X I wll geeralzed the aylor lear approxmato o the all utos o the system 4 wll be obtaed 0 X + 0 x, =, K, X. 0 x X X = = Usg the matreal ompoets deed to relatos 6 ad 7, the relato 0 wll have a ew orm F 0 X = F X he X 0 + J X X. J represets the Jaobea matrx assoated to o-lear equato system 4 L L J X =. L L L L L he applatos o the Newto method are the Newto Raphso algorthm ad the Broyde algorthm. ISSN: ISBN:

3 MHEMICL MEHODS, COMPUIONL ECHNIQUES, INELLIGEN SYSEMS 3. he Newto - Raphso algorthm he Newto-Raphso algorthm ossts to ew approxmato o the soluto o the o-lear equato system, approxmato deed by relato + X = X + X. 3 he orreto vetor X s obtaed usg the F X =, respetvely equato, where 0 J k X X = F X. 4 I the Jaobea matrx J X s a o-sgular matrx, the soluto o the lear system 4 has the orm h =Q hot p,hot k X =J X F X. 5 he umeral values o the soluto 5 are obtaed by usg the Gauss algorthm. he overgee odtos o the array 0 { K X, X,, X,K} o the system soluto estmatos are preseted [5]. he stop rtera o the Newto-Raphso algorthm s ormulated by the relatos X ε, =, K,. 6 he Jaobea matrx assoated to o-lear equatos system has the ollowg ompoets: ; 7 =Q old p,old ; 8 h =Q hot p,hot k ed l h h l h h h h h + ; 9 =k ed l h h l h h h h h +. 0 he most mportat dsadvatage o the Newto- Raphso method ossts to alulatg eort to evaluate the elemets o the Jaobea matrx J X ad the utos o the vetor F X [7]. 3. he umeral evaluato o the Jaobea matrx he authors have studed the estmato o the partally dervates o the utos,, K, o the olear system 4. For the urret pot X have bee deed the small varatos h. 000 x, =, K,. For evaluato o the Jaobea matrx the pot X, the authors have used the geeral relato or the evaluato o the elemet o the Jaobea matrx x, K, x + h, K, x X =, k h =, K,; =, K,. 3.3 he Broyde algorthm he Broyde algorthm redues the Jaobea elemets alulus eort usg the approxmato o the Newto-Raphso Jaobea matrx: ISSN: ISBN:

4 MHEMICL MEHODS, COMPUIONL ECHNIQUES, INELLIGEN SYSEMS F X = + X, 3 X where relato 0 0 = J X ad F s deed by k F = F X F X 4 ad X = X X. he matrx most to satsy the propertes: a o veryg the equato J X X = F X ; b o mmzg the deree m. heses two propertes o the matrx have demostrated [6]. he stop rtera o the Broyde algorthm are smlarly to the stop rtera o the Newto-Raphso algorthm. he steps o the Broyde algorthm are desrbed below [7]: Step. Varables talzato k, X 0 0 = J, X 0 0 F = F. Step. Italzato usg the Newto-Raphso algorthm X F = X. Step 3. Whle the stop rtero has alse value does: k = k+ ; F = F X ; F X = + X X ; + k X = X F. Step 4. Stop he maor dsadvatage o the Broyde algorthm s represeted by the evaluato o the verse matrx or eah terato k. better soluto o ths problem has bee deed by Sherma-Morrso [7]. he orgal orm o the Sherma-Morrso ormula s uv + uv =, 5 + v u where s a osgular matrx ; v ad u are dmesoal vetors wth the property v u. he authors have osdered the ollowg expressos or the u ad v varables: F X u= ; 6 X =. 7 v X Usg the ew varables u ad v, the relato 3 wll have the orm = + u v. 8 Usg 5 to 8 ormula s obtaed a ew orm o the verse o the matrx k = + u v = = uv v + u. 9 Wth ths result, the thrd step o the Broyde algorthm s trasormed a ew orm: Step 3. Whle the stop rtero has alse value does: k = k+ ; F = F X ; F X u= ; X v = X ; = uv v + u k ; + k X = X F. ll the modatos have otrbuted to rease the perormaes o the Broyde algorthm. ISSN: ISBN:

5 MHEMICL MEHODS, COMPUIONL ECHNIQUES, INELLIGEN SYSEMS 4 he results o the smulato o the heat traser proess he authors have elaborated the umeral programs dested to smulato o the shell ad tube heat exhager. he programs have a modular struture whh otaed: a the sub-algorthms or readg the put data le the geometrally heat exhager data, the propertes ad the operatg parameters o the heat ad old lud; b the sub-algorthm or solvg the o-lear equato system; the ma module the put data readg ad the heat traser algorthm. he authors have elaborated three umeral programs, deretated by the sub-algorthm used to solve the o-lear equato systems. Frst program uses the Newto-Raphso algorthm wth the aalytally expressos o the Jaobea matrx. he seod program mplemeted the Newto- Raphso algorthm wth the umerally expressos o the Jaobea matrx. he last program s based o the Broyde algorthm. ll the sub-algorthms used to solvg the o-lear equato system are made by the authors [8]. he shell ad tube heat exhager used by the authors s desrbed [3, 9]. For the struture showed gure, the heat exhager s haraterzed by the ext put data: Q = kg/h; h Q = kg/h; h = 80 C; 3 C. For all the algorthms the stop rtera parameter 6 has the value ε 0 5 =, =, kj/h, ad the 0 tal soluto has the ompoets: x = 60 C, 0 x = 30 C. For the Newto Raphso algorthm whh uses the umerally expressos or evaluato o the Jeaobea matrx, the values o the small varato 4 are h = 0 4 x C. he results obtaed wth the three umeral programs are preseted table. able. Comparatve results to solver the o-lear equato system o the heat exhager lgorthm he Newto-Raphso algorthm based o aalytally expressos o the Jaobea matrx he Newto-Raphso algorthm based o umerally values o the Jaobea matrx he Broyde algorthm Iterato 9 6 he varable o the system x 0 [ C] [kj/h] E E E E E E+03 he soluto o the o-lear equatos system preseted [9] s x = 40 C ad x = 8 C. For the tal soluto assumed by the authors ad or the stop rtero preseted allow, the soluto o the o-lear equato system s obtaed varous teratos depedg o the algorthm. he program based o the Newto-Raphso algorthm determes the most exatly soluto the bgger terato umber. For the system, the Newto- Raphso algorthm based o umerally values o the Jaobea matrx s the most qukly. ll the obtaed solutos are oetrated aroud the pot h = 39 C ad = 8 C. he luee o the stop rtera parameter to the preso o the soluto o the o-lear equato system s preseted table. he olusos o umeral aalyss are ollowg: a he derease o the stop rtera value wll rease the alulus preso; wll derease the values o the utos ad ad wll rease the umber o terato. ISSN: ISBN:

6 MHEMICL MEHODS, COMPUIONL ECHNIQUES, INELLIGEN SYSEMS b lthough the umeral values o the utos ad derease at oe by the stop rtera value, the modato o the soluto o the o-lear equatos system s very small, that the supplemetary alulus eort s ot usted. able. he luee o the stop rtera value o the soluto o the o-lear equatos system solved by the Newto-Raphso algorthm Stop rtera value [kj/h] Equato o the system x 0 [ C] [kj/h] Iterato umber E E E E E E E E Beause the errors betwee the values o the solutos obtaed by usg the three algorthms ad the orgal soluto are very small, the authors osder that the mathematal model o the heat exhager, the algorthms or the solvg the olear equatos systems ad the umeral programs are valdated. 4 Coluso he artle presets the author s researhes o the applatos o the umeral algorthm or heat proesses. For the heat exhager, the mathematal model s represeted by a o-lear equatos system. For solvg the mathematal model, the authors have studed three algorthms: the Newto- Raphso algorthm based o aalytally expressos o the Jaobea matrx, the Newto- Raphso algorthm based o umerally values o the Jaobea matrx ad the Broyde algorthm. he authors have aalyzed the perormaes o theses algorthms rapport o alulus eort ad alulus preso rtera. Reerees: [] Pătrăşou C., Marou V., dvaed Cotrol System or the tubular heaters o the vauum ad rude ut - I. Mathemat Modellg o the Combusto ad Heat raser, Revsta de hme r.4, 997 Romaa. [] Pătrăşou C., Marou V., Modellg ad Optmal Cotrol o a Idustral Furae - DYCOPS-5, 5 th IFC Symposum o Dyams ad Cotrol o Proess Systems, Coru, Greee, Jue 8-0, 998. [3] Patrasou C., he Steady-State Modelgad Smulatoo a Heat Exheger, Petroleum-Gas Uversty o Ploest Bullet, ehal Seres, Vol LXI, No [4] Serth, De R. W., Proess heat traser: prples ad applatos, ISBN , Elsever Ltd, p.89-95, 007. [5] Demdovh B. P., Maro I.,., Computatoal mathemats, Mr Publshers, Mosow, 98. [6] 58.pd [7] emethodmod.html [8] Patrasou C., Numeral methods appled hemal egeerg PSCL applatos, MatrxRom, Buurest, p.7-4, 005 Romaa. [9] Dobresu D., Heat traser proesees ad spe deves, Edtura Ddata s Pedagga, Buurest, p , 983 Romaa. ISSN: ISBN:

Analyzing Control Structures

Analyzing Control Structures Aalyzg Cotrol Strutures sequeg P, P : two fragmets of a algo. t, t : the tme they tae the tme requred to ompute P ;P s t t Θmaxt,t For loops for to m do P t: the tme requred to ompute P total tme requred

More information

A Mean- maximum Deviation Portfolio Optimization Model

A Mean- maximum Deviation Portfolio Optimization Model A Mea- mamum Devato Portfolo Optmzato Model Wu Jwe Shool of Eoom ad Maagemet, South Cha Normal Uversty Guagzhou 56, Cha Tel: 86-8-99-6 E-mal: wujwe@9om Abstrat The essay maes a thorough ad systemat study

More information

Proceeding of the 5th International Conference on Inverse Problems in Engineering: Theory and Practice, Cambridge, UK, th July 2005

Proceeding of the 5th International Conference on Inverse Problems in Engineering: Theory and Practice, Cambridge, UK, th July 2005 A Proeedg o the th Iteratoal Coeree o Iverse Problems Egeerg: Theory ad Prate, Cambrdge, UK, - th July SIMULTAEOUS ESTIMATIO OF TWO BOUDARY CODITIOS I A TWO-DIMESIOAL HEAT CODUCTIO PROBLEM S. ABBOUDI ad

More information

Cubic Nonpolynomial Spline Approach to the Solution of a Second Order Two-Point Boundary Value Problem

Cubic Nonpolynomial Spline Approach to the Solution of a Second Order Two-Point Boundary Value Problem Joural of Amerca Scece ;6( Cubc Nopolyomal Sple Approach to the Soluto of a Secod Order Two-Pot Boudary Value Problem W.K. Zahra, F.A. Abd El-Salam, A.A. El-Sabbagh ad Z.A. ZAk * Departmet of Egeerg athematcs

More information

BERNSTEIN COLLOCATION METHOD FOR SOLVING NONLINEAR DIFFERENTIAL EQUATIONS. Aysegul Akyuz Dascioglu and Nese Isler

BERNSTEIN COLLOCATION METHOD FOR SOLVING NONLINEAR DIFFERENTIAL EQUATIONS. Aysegul Akyuz Dascioglu and Nese Isler Mathematcal ad Computatoal Applcatos, Vol. 8, No. 3, pp. 293-300, 203 BERNSTEIN COLLOCATION METHOD FOR SOLVING NONLINEAR DIFFERENTIAL EQUATIONS Aysegul Ayuz Dascoglu ad Nese Isler Departmet of Mathematcs,

More information

Comparison of Four Methods for Estimating. the Weibull Distribution Parameters

Comparison of Four Methods for Estimating. the Weibull Distribution Parameters Appled Mathematal Sees, Vol. 8, 14, o. 83, 4137-4149 HIKARI Ltd, www.m-hkar.om http://dx.do.org/1.1988/ams.14.45389 Comparso of Four Methods for Estmatg the Webull Dstrbuto Parameters Ivaa Pobočíková ad

More information

Ulam stability for fractional differential equations in the sense of Caputo operator

Ulam stability for fractional differential equations in the sense of Caputo operator Sogklaakar J. S. Tehol. 4 (6) 71-75 Nov. - De. 212 http://www.sjst.psu.a.th Orgal Artle Ulam stablty for fratoal dfferetal equatos the sese of Caputo operator Rabha W. Ibrahm* Isttute of Mathematal Sees

More information

(This summarizes what you basically need to know about joint distributions in this course.)

(This summarizes what you basically need to know about joint distributions in this course.) HG Ot. ECON 430 H Extra exerses for o-semar week 4 (Solutos wll be put o the et at the ed of the week) Itroduto: Revew of multdmesoal dstrbutos (Ths summarzes what you basally eed to kow about jot dstrbutos

More information

2006 Jamie Trahan, Autar Kaw, Kevin Martin University of South Florida United States of America

2006 Jamie Trahan, Autar Kaw, Kevin Martin University of South Florida United States of America SOLUTION OF SYSTEMS OF SIMULTANEOUS LINEAR EQUATIONS Gauss-Sedel Method 006 Jame Traha, Autar Kaw, Kev Mart Uversty of South Florda Uted States of Amerca kaw@eg.usf.edu Itroducto Ths worksheet demostrates

More information

Derivation of 3-Point Block Method Formula for Solving First Order Stiff Ordinary Differential Equations

Derivation of 3-Point Block Method Formula for Solving First Order Stiff Ordinary Differential Equations Dervato of -Pot Block Method Formula for Solvg Frst Order Stff Ordary Dfferetal Equatos Kharul Hamd Kharul Auar, Kharl Iskadar Othma, Zara Bb Ibrahm Abstract Dervato of pot block method formula wth costat

More information

Ruin Probability-Based Initial Capital of the Discrete-Time Surplus Process

Ruin Probability-Based Initial Capital of the Discrete-Time Surplus Process Ru Probablty-Based Ital Captal of the Dsrete-Tme Surplus Proess by Parote Sattayatham, Kat Sagaroo, ad Wathar Klogdee AbSTRACT Ths paper studes a surae model uder the regulato that the surae ompay has

More information

G S Power Flow Solution

G S Power Flow Solution G S Power Flow Soluto P Q I y y * 0 1, Y y Y 0 y Y Y 1, P Q ( k) ( k) * ( k 1) 1, Y Y PQ buses * 1 P Q Y ( k1) *( k) ( k) Q Im[ Y ] 1 P buses & Slack bus ( k 1) *( k) ( k) Y 1 P Re[ ] Slack bus 17 Calculato

More information

Numerical Simulations of the Complex Modied Korteweg-de Vries Equation. Thiab R. Taha. The University of Georgia. Abstract

Numerical Simulations of the Complex Modied Korteweg-de Vries Equation. Thiab R. Taha. The University of Georgia. Abstract Numercal Smulatos of the Complex Moded Korteweg-de Vres Equato Thab R. Taha Computer Scece Departmet The Uversty of Georga Athes, GA 002 USA Tel 0-542-2911 e-mal thab@cs.uga.edu Abstract I ths paper mplemetatos

More information

On the Nonlinear Difference Equation

On the Nonlinear Difference Equation Joural of Appled Mathemats ad Phss 6 4-9 Pulshed Ole Jauar 6 SRes http://wwwsrporg/joural/jamp http://ddoorg/436/jamp644 O the Nolear Dfferee Equato Elmetwall M Elaas Adulmuhaem A El-Bat Departmet of Mathemats

More information

Spring Ammar Abu-Hudrouss Islamic University Gaza

Spring Ammar Abu-Hudrouss Islamic University Gaza ١ ١ Chapter Chapter 4 Cyl Blo Cyl Blo Codes Codes Ammar Abu-Hudrouss Islam Uversty Gaza Spr 9 Slde ٢ Chael Cod Theory Cyl Blo Codes A yl ode s haraterzed as a lear blo ode B( d wth the addtoal property

More information

Comparing Different Estimators of three Parameters for Transmuted Weibull Distribution

Comparing Different Estimators of three Parameters for Transmuted Weibull Distribution Global Joural of Pure ad Appled Mathematcs. ISSN 0973-768 Volume 3, Number 9 (207), pp. 55-528 Research Ida Publcatos http://www.rpublcato.com Comparg Dfferet Estmators of three Parameters for Trasmuted

More information

The acoustic wave propagation equation in a turbulent combusting flow

The acoustic wave propagation equation in a turbulent combusting flow Aousts 8 Pars The aoust wave propagato equato a turbulet ombustg low J. B. W. Kok Uversty o Twete, P.O. Box 17, 75 AE Eshede, Netherlads.b.w.kok@utwete.l 761 Aousts 8 Pars Abstrat Soud geerato by turbulet

More information

r 1,2 = a 1 (a 2 2 4a 2 a 0 )

r 1,2 = a 1 (a 2 2 4a 2 a 0 ) Fall emester- 6 Numeral Methods Mehaal Egeerg - ME Dr. aeed J. Almalow, smalow@taahu.edu.sa CHAPTER. Roots of Equatos, Lear ystems ad Algera ystems.. Roots of Polyomal The polyomal equato s: f( ) = a +

More information

LOAD-FLOW CALCULATIONS IN MESHED SYSTEMS Node voltage method A system part with the node k and its direct neighbour m

LOAD-FLOW CALCULATIONS IN MESHED SYSTEMS Node voltage method A system part with the node k and its direct neighbour m LOAD-FLOW CALCLATIONS IN MESHED SYSTEMS Node oltage method A system part wth the ode ad ts dret eghbor m Î Îm Î m m Crrets Î m m m Î Î m m m m Î m m m m m m m Let s dee the ode sel-admttae (adm. matr dagoal

More information

Newton s Power Flow algorithm

Newton s Power Flow algorithm Power Egeerg - Egll Beedt Hresso ewto s Power Flow algorthm Power Egeerg - Egll Beedt Hresso The ewto s Method of Power Flow 2 Calculatos. For the referece bus #, we set : V = p.u. ad δ = 0 For all other

More information

Chapter 5. Curve fitting

Chapter 5. Curve fitting Chapter 5 Curve ttg Assgmet please use ecell Gve the data elow use least squares regresso to t a a straght le a power equato c a saturato-growthrate equato ad d a paraola. Fd the r value ad justy whch

More information

Adaptive Input-Output Linearization Control of ph Processes

Adaptive Input-Output Linearization Control of ph Processes Ira. J. Chem. Chem. Eg. ol. 7, No., Adaptve Iput-Output earzato Cotrol o Proesses Nejat, Al Departmet o Chemal Egeerg, Isaha Uversty o Tehology, Isaha, I.R. IRAN Shahrokh, Mohammad* Departmet o Chemal

More information

Probabilistic Load Flow Solution of Radial Distribution Networks Including Wind Power Generation

Probabilistic Load Flow Solution of Radial Distribution Networks Including Wind Power Generation Iteratoal Joural o Power Egeerg ad Eergy (IJPEE) Vol. (9) No. () ISSN Prt ( 8) ad Ole ( X) Jauary 8 Probablst Load Flow Soluto of Radal Dstrbuto Networks Iludg Wd Power Geerato Walaa Hamdy, Salah Kamel,

More information

Open Access Design for Networked Control Systems Based on Multi-Rate Technique

Open Access Design for Networked Control Systems Based on Multi-Rate Technique Sed Orders or Reprts to reprts@betamsee.ae 68 e Ope utomato ad Cotrol Systems Joural 5 7 68-73 Ope ess Desg or Networked Cotrol Systems Based o Mult-Rate eque Guotao Hu * Wawe L ad Ygu Wag College o Iormato

More information

Identification of Contact Conditions from Contaminated Data of Contact Force and Moment

Identification of Contact Conditions from Contaminated Data of Contact Force and Moment Proeedgs o the IEEE Iteratoal Coeree o Robots & Automato eoul, Korea May -6, Idetato o Cotat Codtos rom Cotamated Data o Cotat Fore ad Momet etsuya MOURI *, aayosh YAMADA **, Ayao IWAI **, Nobuharu MIMURA

More information

Numerical Analysis Formulae Booklet

Numerical Analysis Formulae Booklet Numercal Aalyss Formulae Booklet. Iteratve Scemes for Systems of Lear Algebrac Equatos:.... Taylor Seres... 3. Fte Dfferece Approxmatos... 3 4. Egevalues ad Egevectors of Matrces.... 3 5. Vector ad Matrx

More information

A NEW NUMERICAL APPROACH FOR SOLVING HIGH-ORDER LINEAR AND NON-LINEAR DIFFERANTIAL EQUATIONS

A NEW NUMERICAL APPROACH FOR SOLVING HIGH-ORDER LINEAR AND NON-LINEAR DIFFERANTIAL EQUATIONS Secer, A., et al.: A New Numerıcal Approach for Solvıg Hıgh-Order Lıear ad No-Lıear... HERMAL SCIENCE: Year 8, Vol., Suppl., pp. S67-S77 S67 A NEW NUMERICAL APPROACH FOR SOLVING HIGH-ORDER LINEAR AND NON-LINEAR

More information

Estimation of Stress- Strength Reliability model using finite mixture of exponential distributions

Estimation of Stress- Strength Reliability model using finite mixture of exponential distributions Iteratoal Joural of Computatoal Egeerg Research Vol, 0 Issue, Estmato of Stress- Stregth Relablty model usg fte mxture of expoetal dstrbutos K.Sadhya, T.S.Umamaheswar Departmet of Mathematcs, Lal Bhadur

More information

Using Fuzzy Integral to Model Case-Base Competence

Using Fuzzy Integral to Model Case-Base Competence Usg Fuzzy Itegral to Model Case-Base Competee Smo C. K. Shu, Ya L, X Z. Wag Departmet o Computg Hog Kog Polyteh Uversty Hug Hom, Kowloo, Hog Kog {skshu, syl, sxzwag}@omp.polyu.edu.hk Abstrat Modelg ase-base

More information

Beam Warming Second-Order Upwind Method

Beam Warming Second-Order Upwind Method Beam Warmg Secod-Order Upwd Method Petr Valeta Jauary 6, 015 Ths documet s a part of the assessmet work for the subject 1DRP Dfferetal Equatos o Computer lectured o FNSPE CTU Prague. Abstract Ths documet

More information

A Class of Deformed Hyperbolic Secant Distributions Using Two Parametric Functions. S. A. El-Shehawy

A Class of Deformed Hyperbolic Secant Distributions Using Two Parametric Functions. S. A. El-Shehawy A Class o Deormed Hyperbolc Secat Dstrbutos Usg Two Parametrc Fuctos S. A. El-Shehawy Departmet o Mathematcs Faculty o Scece Meoua Uversty Sheb El-om Egypt shshehawy6@yahoo.com Abstract: Ths paper presets

More information

We have already referred to a certain reaction, which takes place at high temperature after rich combustion.

We have already referred to a certain reaction, which takes place at high temperature after rich combustion. ME 41 Day 13 Topcs Chemcal Equlbrum - Theory Chemcal Equlbrum Example #1 Equlbrum Costats Chemcal Equlbrum Example #2 Chemcal Equlbrum of Hot Bured Gas 1. Chemcal Equlbrum We have already referred to a

More information

0/1 INTEGER PROGRAMMING AND SEMIDEFINTE PROGRAMMING

0/1 INTEGER PROGRAMMING AND SEMIDEFINTE PROGRAMMING CONVEX OPIMIZAION AND INERIOR POIN MEHODS FINAL PROJEC / INEGER PROGRAMMING AND SEMIDEFINE PROGRAMMING b Luca Buch ad Natala Vktorova CONENS:.Itroducto.Formulato.Applcato to Kapsack Problem 4.Cuttg Plaes

More information

APPLYING TRANSFORMATION CHARACTERISTICS TO SOLVE THE MULTI OBJECTIVE LINEAR FRACTIONAL PROGRAMMING PROBLEMS

APPLYING TRANSFORMATION CHARACTERISTICS TO SOLVE THE MULTI OBJECTIVE LINEAR FRACTIONAL PROGRAMMING PROBLEMS Iteratoal Joural of Computer See & Iformato eholog IJCSI Vol 9, No, Aprl 07 APPLYING RANSFORMAION CHARACERISICS O SOLVE HE MULI OBJECIVE LINEAR FRACIONAL PROGRAMMING PROBLEMS We Pe Departmet of Busess

More information

Dynamic Analysis of Axially Beam on Visco - Elastic Foundation with Elastic Supports under Moving Load

Dynamic Analysis of Axially Beam on Visco - Elastic Foundation with Elastic Supports under Moving Load Dyamc Aalyss of Axally Beam o Vsco - Elastc Foudato wth Elastc Supports uder Movg oad Saeed Mohammadzadeh, Seyed Al Mosayeb * Abstract: For dyamc aalyses of ralway track structures, the algorthm of soluto

More information

Optimization design of wind turbine drive train based on Matlab genetic algorithm toolbox

Optimization design of wind turbine drive train based on Matlab genetic algorithm toolbox IOP Coferee Seres: Materals See ad Egeerg OPEN ACCESS Optmzato desg of wd ture drve tra ased o Matla geet algorthm toolox o te ths artle: R N L et al 2013 IOP Cof. Ser.: Mater. S. Eg. 52 052013 Vew the

More information

Feature Selection: Part 2. 1 Greedy Algorithms (continued from the last lecture)

Feature Selection: Part 2. 1 Greedy Algorithms (continued from the last lecture) CSE 546: Mache Learg Lecture 6 Feature Selecto: Part 2 Istructor: Sham Kakade Greedy Algorthms (cotued from the last lecture) There are varety of greedy algorthms ad umerous amg covetos for these algorthms.

More information

Generalization of the Dissimilarity Measure of Fuzzy Sets

Generalization of the Dissimilarity Measure of Fuzzy Sets Iteratoal Mathematcal Forum 2 2007 o. 68 3395-3400 Geeralzato of the Dssmlarty Measure of Fuzzy Sets Faramarz Faghh Boformatcs Laboratory Naobotechology Research Ceter vesa Research Isttute CECR Tehra

More information

4. Standard Regression Model and Spatial Dependence Tests

4. Standard Regression Model and Spatial Dependence Tests 4. Stadard Regresso Model ad Spatal Depedece Tests Stadard regresso aalss fals the presece of spatal effects. I case of spatal depedeces ad/or spatal heterogeet a stadard regresso model wll be msspecfed.

More information

A Missing Inflated Power Series Model for regression analysis of the British Household Panel Survey (BHPS) data

A Missing Inflated Power Series Model for regression analysis of the British Household Panel Survey (BHPS) data Australa Joural of Bas ad Appled Sees, 5(7): 325-33, 20 ISSN 99-878 A Mssg Iflated Power Seres for regresso aalyss of the Brtsh Household Pael Survey (BHPS) data E. Bahram Sama Departmet of Statsts, Faulty

More information

( ) Using the SAS System to Fit the Burr XII Distribution to Lifetime Data. A J Watkins, University of Wales Swansea. Introduction

( ) Using the SAS System to Fit the Burr XII Distribution to Lifetime Data. A J Watkins, University of Wales Swansea. Introduction Usg the SAS System to Ft the Burr II Dstrbuto to Lfetme Data A J Watks Uversty of Wales Swasea Itroduto Ths paper s oered wth varous pratal ad theoretal aspets of usg the Burr II dstrbuto to model lfetme

More information

Multi-Step Methods Applied to Nonlinear Equations of Power Networks

Multi-Step Methods Applied to Nonlinear Equations of Power Networks Electrcal ad Electroc Egeerg 03, 3(5): 8-3 DOI: 0.593/j.eee.030305.0 Mult-Step s Appled to olear Equatos of Power etworks Rubé llafuerte D.,*, Rubé A. llafuerte S., Jesús Meda C. 3, Edgar Meja S. 3 Departmet

More information

Suboptimal Filter for Multisensor Linear Discrete-Time Systems with Observation Uncertainties

Suboptimal Filter for Multisensor Linear Discrete-Time Systems with Observation Uncertainties roeedgs of the World Cogress o Egeerg 7 Vol I WCE 7 Jul - 7 odo U.K. Submal Flter for Multsesor ear Dsrete-me Sstems wth Obserato Uertates ag Deepa Vladmr Sh Abstrat-he fous of ths paper s the problem

More information

Assignment 7/MATH 247/Winter, 2010 Due: Friday, March 19. Powers of a square matrix

Assignment 7/MATH 247/Winter, 2010 Due: Friday, March 19. Powers of a square matrix Assgmet 7/MATH 47/Wter, 00 Due: Frday, March 9 Powers o a square matrx Gve a square matrx A, ts powers A or large, or eve arbtrary, teger expoets ca be calculated by dagoalzg A -- that s possble (!) Namely,

More information

A Mixture Model for Longitudinal Trajectories with Covariates

A Mixture Model for Longitudinal Trajectories with Covariates Amera Joural of Mathemats ad Statsts 05, 5(5: 93-305 DOI: 0.593/j.ajms.050505.0 A Mxture Model for Lotudal rajetores wth Covarates Vtor Mooto Nawa Departmet of Mathemats ad Statsts, Uversty of Zamba, Lusaka,

More information

A Method for Damping Estimation Based On Least Square Fit

A Method for Damping Estimation Based On Least Square Fit Amerca Joural of Egeerg Research (AJER) 5 Amerca Joural of Egeerg Research (AJER) e-issn: 3-847 p-issn : 3-936 Volume-4, Issue-7, pp-5-9 www.ajer.org Research Paper Ope Access A Method for Dampg Estmato

More information

ECON 5360 Class Notes GMM

ECON 5360 Class Notes GMM ECON 560 Class Notes GMM Geeralzed Method of Momets (GMM) I beg by outlg the classcal method of momets techque (Fsher, 95) ad the proceed to geeralzed method of momets (Hase, 98).. radtoal Method of Momets

More information

Solution of General Dual Fuzzy Linear Systems. Using ABS Algorithm

Solution of General Dual Fuzzy Linear Systems. Using ABS Algorithm Appled Mathematcal Sceces, Vol 6, 0, o 4, 63-7 Soluto of Geeral Dual Fuzzy Lear Systems Usg ABS Algorthm M A Farborz Aragh * ad M M ossezadeh Departmet of Mathematcs, Islamc Azad Uversty Cetral ehra Brach,

More information

Application of Legendre Bernstein basis transformations to degree elevation and degree reduction

Application of Legendre Bernstein basis transformations to degree elevation and degree reduction Computer Aded Geometrc Desg 9 79 78 www.elsever.com/locate/cagd Applcato of Legedre Berste bass trasformatos to degree elevato ad degree reducto Byug-Gook Lee a Yubeom Park b Jaechl Yoo c a Dvso of Iteret

More information

Bayesian Analysis of Scale Parameter of the Generalized Inverse Rayleigh Model Using Different Loss Functions

Bayesian Analysis of Scale Parameter of the Generalized Inverse Rayleigh Model Using Different Loss Functions Artle Iteratoal Joural o Moder Mathematal Sees 4 :5-6 Iteratoal Joural o Moder Mathematal Sees Joural homepae:www.modersetpress.om/jourals/jmms.asp ISSN:66-86X Florda USA Bayesa Aalyss o Sale Parameter

More information

Chapter 2 - Free Vibration of Multi-Degree-of-Freedom Systems - II

Chapter 2 - Free Vibration of Multi-Degree-of-Freedom Systems - II CEE49b Chapter - Free Vbrato of Mult-Degree-of-Freedom Systems - II We ca obta a approxmate soluto to the fudametal atural frequecy through a approxmate formula developed usg eergy prcples by Lord Raylegh

More information

CH E 374 Computational Methods in Engineering Fall 2007

CH E 374 Computational Methods in Engineering Fall 2007 CH E 7 Computatoal Methods Egeerg Fall 007 Sample Soluto 5. The data o the varato of the rato of stagato pressure to statc pressure (r ) wth Mach umber ( M ) for the flow through a duct are as follows:

More information

2. Higher Order Consensus

2. Higher Order Consensus Prepared by F.L. Lews Updated: Wedesday, February 3, 0. Hgher Order Cosesus I Seto we dsussed ooperatve otrol o graphs for dyamal systems that have frstorder dyams, that s, a sgle tegrator or shft regster

More information

L5 Polynomial / Spline Curves

L5 Polynomial / Spline Curves L5 Polyomal / Sple Curves Cotets Coc sectos Polyomal Curves Hermte Curves Bezer Curves B-Sples No-Uform Ratoal B-Sples (NURBS) Mapulato ad Represetato of Curves Types of Curve Equatos Implct: Descrbe a

More information

LINEARLY CONSTRAINED MINIMIZATION BY USING NEWTON S METHOD

LINEARLY CONSTRAINED MINIMIZATION BY USING NEWTON S METHOD Jural Karya Asl Loreka Ahl Matematk Vol 8 o 205 Page 084-088 Jural Karya Asl Loreka Ahl Matematk LIEARLY COSTRAIED MIIMIZATIO BY USIG EWTO S METHOD Yosza B Dasrl, a Ismal B Moh 2 Faculty Electrocs a Computer

More information

STA 108 Applied Linear Models: Regression Analysis Spring Solution for Homework #1

STA 108 Applied Linear Models: Regression Analysis Spring Solution for Homework #1 STA 08 Appled Lear Models: Regresso Aalyss Sprg 0 Soluto for Homework #. Let Y the dollar cost per year, X the umber of vsts per year. The the mathematcal relato betwee X ad Y s: Y 300 + X. Ths s a fuctoal

More information

Bezier curve and its application

Bezier curve and its application , 49-55 Receved: 2014-11-12 Accepted: 2015-02-06 Ole publshed: 2015-11-16 DOI: http://dx.do.org/10.15414/meraa.2015.01.02.49-55 Orgal paper Bezer curve ad ts applcato Duša Páleš, Jozef Rédl Slovak Uversty

More information

Modeling of dark characteristics for longwavelength

Modeling of dark characteristics for longwavelength Modelg of dark haratersts for logwaelegth HgCdTe photodode Z. J. Qua, X. S. Che, W. Lu atoal Laboratory for Ifrared Physs Shagha Isttute of Tehal Physs Chese Aademy of Sees Outle Itroduto Carrer desty

More information

MOLECULAR VIBRATIONS

MOLECULAR VIBRATIONS MOLECULAR VIBRATIONS Here we wsh to vestgate molecular vbratos ad draw a smlarty betwee the theory of molecular vbratos ad Hückel theory. 1. Smple Harmoc Oscllator Recall that the eergy of a oe-dmesoal

More information

THE UNITARY THEORY OF THE ELECTRIC POWERS. Gheorghe MIHAI

THE UNITARY THEORY OF THE ELECTRIC POWERS. Gheorghe MIHAI Aals of the versty of Craova, Eletral Egeerg seres, No. 3, 6 HE NARY HEORY O HE EECRC OWERS Gheorghe MHA versty of Craova, aulty of Eletrotehs, 7 eebal Blvd. E-al: gha@elth.uv.ro Abstrat Geeral physs approah

More information

Decomposition of Hadamard Matrices

Decomposition of Hadamard Matrices Chapter 7 Decomposto of Hadamard Matrces We hae see Chapter that Hadamard s orgal costructo of Hadamard matrces states that the Kroecer product of Hadamard matrces of orders m ad s a Hadamard matrx of

More information

Design maintenanceand reliability of engineering systems: a probability based approach

Design maintenanceand reliability of engineering systems: a probability based approach Desg mateaead relablty of egeerg systems: a probablty based approah CHPTER 2. BSIC SET THEORY 2.1 Bas deftos Sets are the bass o whh moder probablty theory s defed. set s a well-defed olleto of objets.

More information

Multivariate Transformation of Variables and Maximum Likelihood Estimation

Multivariate Transformation of Variables and Maximum Likelihood Estimation Marquette Uversty Multvarate Trasformato of Varables ad Maxmum Lkelhood Estmato Dael B. Rowe, Ph.D. Assocate Professor Departmet of Mathematcs, Statstcs, ad Computer Scece Copyrght 03 by Marquette Uversty

More information

On the convergence of derivatives of Bernstein approximation

On the convergence of derivatives of Bernstein approximation O the covergece of dervatves of Berste approxmato Mchael S. Floater Abstract: By dfferetatg a remader formula of Stacu, we derve both a error boud ad a asymptotc formula for the dervatves of Berste approxmato.

More information

{ }{ ( )} (, ) = ( ) ( ) ( ) Chapter 14 Exercises in Sampling Theory. Exercise 1 (Simple random sampling): Solution:

{ }{ ( )} (, ) = ( ) ( ) ( ) Chapter 14 Exercises in Sampling Theory. Exercise 1 (Simple random sampling): Solution: Chapter 4 Exercses Samplg Theory Exercse (Smple radom samplg: Let there be two correlated radom varables X ad A sample of sze s draw from a populato by smple radom samplg wthout replacemet The observed

More information

Math 10 Discrete Mathematics

Math 10 Discrete Mathematics Math 0 Dsrete Mathemats T. Heso REVIEW EXERCISES FOR EXM II Whle these problems are represetatve of the types of problems that I mght put o a exam, they are ot lusve. You should be prepared to work ay

More information

Functions of Random Variables

Functions of Random Variables Fuctos of Radom Varables Chapter Fve Fuctos of Radom Varables 5. Itroducto A geeral egeerg aalyss model s show Fg. 5.. The model output (respose) cotas the performaces of a system or product, such as weght,

More information

Introduction to local (nonparametric) density estimation. methods

Introduction to local (nonparametric) density estimation. methods Itroducto to local (oparametrc) desty estmato methods A slecture by Yu Lu for ECE 66 Sprg 014 1. Itroducto Ths slecture troduces two local desty estmato methods whch are Parze desty estmato ad k-earest

More information

Solving Constrained Flow-Shop Scheduling. Problems with Three Machines

Solving Constrained Flow-Shop Scheduling. Problems with Three Machines It J Cotemp Math Sceces, Vol 5, 2010, o 19, 921-929 Solvg Costraed Flow-Shop Schedulg Problems wth Three Maches P Pada ad P Rajedra Departmet of Mathematcs, School of Advaced Sceces, VIT Uversty, Vellore-632

More information

Ordinary Least Squares Regression. Simple Regression. Algebra and Assumptions.

Ordinary Least Squares Regression. Simple Regression. Algebra and Assumptions. Ordary Least Squares egresso. Smple egresso. Algebra ad Assumptos. I ths part of the course we are gog to study a techque for aalysg the lear relatoshp betwee two varables Y ad X. We have pars of observatos

More information

The number of observed cases The number of parameters. ith case of the dichotomous dependent variable. the ith case of the jth parameter

The number of observed cases The number of parameters. ith case of the dichotomous dependent variable. the ith case of the jth parameter LOGISTIC REGRESSION Notato Model Logstc regresso regresses a dchotomous depedet varable o a set of depedet varables. Several methods are mplemeted for selectg the depedet varables. The followg otato s

More information

Homework. Homework 1. are as follows

Homework. Homework 1. are as follows Homework Homework M D Computg desrbes the use o Baes theorem ad the use o odtoal probablt medal dagoss Pror probabltes o dseases are based o the phsa s assessmet o suh thgs as geographal loato seasoal

More information

Simulation Output Analysis

Simulation Output Analysis Smulato Output Aalyss Summary Examples Parameter Estmato Sample Mea ad Varace Pot ad Iterval Estmato ermatg ad o-ermatg Smulato Mea Square Errors Example: Sgle Server Queueg System x(t) S 4 S 4 S 3 S 5

More information

Lecture Notes 2. The ability to manipulate matrices is critical in economics.

Lecture Notes 2. The ability to manipulate matrices is critical in economics. Lecture Notes. Revew of Matrces he ablt to mapulate matrces s crtcal ecoomcs.. Matr a rectagular arra of umbers, parameters, or varables placed rows ad colums. Matrces are assocated wth lear equatos. lemets

More information

Equivalent linearization approach to probabilistic response evaluation for base-isolated buildings

Equivalent linearization approach to probabilistic response evaluation for base-isolated buildings Equvalet learzato approah to probablst respose evaluato for base-solated bulds T. Naa & A. Nshta Dept. of Arhteture, Waseda Uversty Keywords: equvalet learzato, base solato, probablst dstrbuto, vsous damp

More information

Section 2:00 ~ 2:50 pm Thursday in Maryland 202 Sep. 29, 2005

Section 2:00 ~ 2:50 pm Thursday in Maryland 202 Sep. 29, 2005 Seto 2:00 ~ 2:50 pm Thursday Marylad 202 Sep. 29, 2005. Homework assgmets set ad 2 revews: Set : P. A box otas 3 marbles, red, gree, ad blue. Cosder a expermet that ossts of takg marble from the box, the

More information

Journal of Chemical and Pharmaceutical Research, 2014, 6(5): Research Article

Journal of Chemical and Pharmaceutical Research, 2014, 6(5): Research Article Avalable ole www.opr.o Joural of Cheal a Pharaeutal Researh, 04, 6(5:743-749 Researh Artle ISSN : 0975-7384 CODEN(USA : JCPRC5 Stuy o swar optzato lusterg algorth Zuo Yg Lu a Xa We Southwest Uversty Chogqg,

More information

General Method for Calculating Chemical Equilibrium Composition

General Method for Calculating Chemical Equilibrium Composition AE 6766/Setzma Sprg 004 Geeral Metod for Calculatg Cemcal Equlbrum Composto For gve tal codtos (e.g., for gve reactats, coose te speces to be cluded te products. As a example, for combusto of ydroge wt

More information

An Evaluation of Implicit Time Integration Schemes for Discontinuous High Order Methods

An Evaluation of Implicit Time Integration Schemes for Discontinuous High Order Methods 21st AIAA Computatoal Flud Dyams Coeree Jue 24-27, 2013, Sa Dego, CA AIAA 2013-2688 A Evaluato o Implt Tme Itegrato Shemes or Dsotuous Hgh Order Methods Cheg Zhou 1 ( ) ad Z. J. Wag 2 Uversty o Kasas,

More information

Interval Valued Fuzzy Neutrosophic Soft Structure Spaces

Interval Valued Fuzzy Neutrosophic Soft Structure Spaces Neutrosop Sets ad Systems Vol 5 0 6 Iterval Valued Fuzzy Neutrosop Sot Struture Spaes Iroara & IRSumat Nrmala College or Wome Combatore- 608 Tamladu Ida E-mal: sumat_rama005@yaooo bstrat I ts paper we

More information

Adaptive Fuzzy Control Design

Adaptive Fuzzy Control Design Ata Polyteha Huara Vol. 6, No. 4, 009 Adaptve uzzy Cotrol Des Mart Kratmüller SIEMENS PSE sro Slovaa Dúbravsá esta 4, 845 37 Bratslava, Slova Republ E-mal: mart.ratmueller@semes.om Abstrat: A applato o

More information

Spreadsheet Problem Solving

Spreadsheet Problem Solving 1550 1500 CO Emmssos for the US, 1989 000 Class meetg #6 Moday, Sept 14 th CO Emssos (MMT Carbo) y = 1.3x 41090.17 1450 1400 1350 1300 1989 1990 1991 199 1993 1994 1995 1996 1997 1998 1999 000 Year GEEN

More information

Progress Report on. Advanced Detection and Classification Algorithms for Acoustic-Color-Based Sonar Systems N C-0026.

Progress Report on. Advanced Detection and Classification Algorithms for Acoustic-Color-Based Sonar Systems N C-0026. CDRL A00 Cotrat o. 0004-06-C006 Progress Report o Advaed Deteto ad Classato Algorthms or Aoust-Color-Based Soar Systems 0004-06-C-006 Submtted by Laree Car Sgal Iovatos Group 009 Slater Rd., Sute 00 Durham,

More information

Line Fitting and Regression

Line Fitting and Regression Marquette Uverst MSCS6 Le Fttg ad Regresso Dael B. Rowe, Ph.D. Professor Departmet of Mathematcs, Statstcs, ad Computer Scece Coprght 8 b Marquette Uverst Least Squares Regresso MSCS6 For LSR we have pots

More information

A Fast Algorithm for Multiphase Image Segmentation: The Split-Bregman-Projection Algorithm

A Fast Algorithm for Multiphase Image Segmentation: The Split-Bregman-Projection Algorithm A Fast Algorthm for Multphase Image Segmetato: The Splt-Bregma-Projeto Algorthm Culag Lu, Yogguo Zheg, Zhekua Pa, ad Guodog Wag Abstrat I ths paper, we propose a varatoal model of multphase mage segmetato

More information

C-1: Aerodynamics of Airfoils 1 C-2: Aerodynamics of Airfoils 2 C-3: Panel Methods C-4: Thin Airfoil Theory

C-1: Aerodynamics of Airfoils 1 C-2: Aerodynamics of Airfoils 2 C-3: Panel Methods C-4: Thin Airfoil Theory ROAD MAP... AE301 Aerodyamcs I UNIT C: 2-D Arfols C-1: Aerodyamcs of Arfols 1 C-2: Aerodyamcs of Arfols 2 C-3: Pael Methods C-4: Th Arfol Theory AE301 Aerodyamcs I Ut C-3: Lst of Subects Problem Solutos?

More information

A Method to Establish the Dynamic Models of Multibody System Based on Kane s Equations

A Method to Establish the Dynamic Models of Multibody System Based on Kane s Equations d Iteratoal Coferee o Modellg, Idetfato ad Cotrol (MIC 05) A Method to Establsh the Dyam Models of Multbody System Based o Kae s Equatos Yagwe Zhog Shool of Eergy & Power Egeerg, NJUST, Nag, Cha zyw_60@6.om

More information

Introduction to Matrices and Matrix Approach to Simple Linear Regression

Introduction to Matrices and Matrix Approach to Simple Linear Regression Itroducto to Matrces ad Matrx Approach to Smple Lear Regresso Matrces Defto: A matrx s a rectagular array of umbers or symbolc elemets I may applcatos, the rows of a matrx wll represet dvduals cases (people,

More information

Chapter Gauss-Seidel Method

Chapter Gauss-Seidel Method Chpter 04.08 Guss-Sedel Method After redg ths hpter, you should be ble to:. solve set of equtos usg the Guss-Sedel method,. reogze the dvtges d ptflls of the Guss-Sedel method, d. determe uder wht odtos

More information

A CLASS OF SINGULAR PERTURBATED BILOCAL LINEAR PROBLEMS

A CLASS OF SINGULAR PERTURBATED BILOCAL LINEAR PROBLEMS Proeegs of the Iteratoal Coferee o Theor a Applatos of Matheats a Iforats ICTAMI 3 Alba Iula A CLASS OF SINGULAR PERTURBATED BILOCAL LINEAR PROBLEMS b Mhaela Jaraat a Teoor Groşa Abstrat. Ths paper presets

More information

ON THE LAWS OF LARGE NUMBERS FOR DEPENDENT RANDOM VARIABLES

ON THE LAWS OF LARGE NUMBERS FOR DEPENDENT RANDOM VARIABLES Joural of Sees Islam Republ of Ira 4(3): 7-75 (003) Uversty of Tehra ISSN 06-04 ON THE LAWS OF LARGE NUMBERS FOR DEPENDENT RANDOM VARIABLES HR Nl Sa * ad A Bozorga Departmet of Mathemats Brjad Uversty

More information

THE ACOUSTIC WAVE PROPAGATION EQUATION IN A TURBULENT COMBUSTING FLOW

THE ACOUSTIC WAVE PROPAGATION EQUATION IN A TURBULENT COMBUSTING FLOW ICSV14 Cars Australa 9-1 July, 7 THE ACOUSTIC WAVE PROPAGATION EQUATION IN A TURBULENT COMBUSTING FLOW Jm B.W. Kok ad Bram de Jager Uversty of Twete Dept. of Meh Eg. PO Box 17, 75 AE Eshede The Netherlads.b.w.kok@utwete.l

More information

1 0, x? x x. 1 Root finding. 1.1 Introduction. Solve[x^2-1 0,x] {{x -1},{x 1}} Plot[x^2-1,{x,-2,2}] 3

1 0, x? x x. 1 Root finding. 1.1 Introduction. Solve[x^2-1 0,x] {{x -1},{x 1}} Plot[x^2-1,{x,-2,2}] 3 Adrew Powuk - http://www.powuk.com- Math 49 (Numercal Aalyss) Root fdg. Itroducto f ( ),?,? Solve[^-,] {{-},{}} Plot[^-,{,-,}] Cubc equato https://e.wkpeda.org/wk/cubc_fucto Quartc equato https://e.wkpeda.org/wk/quartc_fucto

More information

02/15/04 INTERESTING FINITE AND INFINITE PRODUCTS FROM SIMPLE ALGEBRAIC IDENTITIES

02/15/04 INTERESTING FINITE AND INFINITE PRODUCTS FROM SIMPLE ALGEBRAIC IDENTITIES 0/5/04 ITERESTIG FIITE AD IFIITE PRODUCTS FROM SIMPLE ALGEBRAIC IDETITIES Thomas J Osler Mathematcs Departmet Rowa Uversty Glassboro J 0808 Osler@rowaedu Itroducto The dfferece of two squares, y = + y

More information

A unified matrix representation for degree reduction of Bézier curves

A unified matrix representation for degree reduction of Bézier curves Computer Aded Geometrc Desg 21 2004 151 164 wwwelsevercom/locate/cagd A ufed matrx represetato for degree reducto of Bézer curves Hask Suwoo a,,1, Namyog Lee b a Departmet of Mathematcs, Kokuk Uversty,

More information

Some Different Perspectives on Linear Least Squares

Some Different Perspectives on Linear Least Squares Soe Dfferet Perspectves o Lear Least Squares A stadard proble statstcs s to easure a respose or depedet varable, y, at fed values of oe or ore depedet varables. Soetes there ests a deterstc odel y f (,,

More information

ECE 595, Section 10 Numerical Simulations Lecture 19: FEM for Electronic Transport. Prof. Peter Bermel February 22, 2013

ECE 595, Section 10 Numerical Simulations Lecture 19: FEM for Electronic Transport. Prof. Peter Bermel February 22, 2013 ECE 595, Secto 0 Numercal Smulatos Lecture 9: FEM for Electroc Trasport Prof. Peter Bermel February, 03 Outle Recap from Wedesday Physcs-based devce modelg Electroc trasport theory FEM electroc trasport

More information

Nonlinear Interval Finite Elements for Structural Mechanics Problems

Nonlinear Interval Finite Elements for Structural Mechanics Problems Nolear Iterval te Elemets for Strutural Mehas Problems Raf L. Muhaa, Robert L. Mulle, a M. V. Rama Rao Shool of Cvl a Evrometal Egeerg, Georga Isttute of Tehology tlata, G 0-0 US, raf.muhaa@gtsav.gateh.eu

More information

Iterative Threshold Decoding of Majority Logic Decodable Codes on Rayleigh Fading Channels

Iterative Threshold Decoding of Majority Logic Decodable Codes on Rayleigh Fading Channels SETIT 7 4 th Iteratoal Coferee: Sees of Eletro, Tehologes of Iformato ad Teleommuatos Marh 5-9, 7 TUISIA Iteratve Threshold Deodg of Maorty og Deodable Codes o Raylegh Fadg Chaels Mohamed ahmer, Mostafa

More information

Development of the Couple Stress Relationships for the Power Law Fluid and the Solution of Flow in Ceramic Tape Casting Process

Development of the Couple Stress Relationships for the Power Law Fluid and the Solution of Flow in Ceramic Tape Casting Process Joural of Appled Flud Mehas, Vol., No. 5, pp. 39-46, 8. Avalable ole at www.jafmole.et, ISSN 735-357, EISSN 735-3645. DOI:.95/jafm..5.85 Developmet of the Couple Stress Relatoshps for the Power aw Flud

More information