Elements of Heat Transfer Analysis

Size: px
Start display at page:

Download "Elements of Heat Transfer Analysis"

Transcription

1 !H-ref,mmc,rev/5/0prt/5/0 Elements of Heat ransfer Analyss (A Bref Introducton to Heat ransfer) Mchael M. Chen Unversty of Mchgan. Introducton A. General dscussons hese lectures consttute a compact presentaton of elementary heat transfer analyss, ntended to accompany the study of thermodynamcs n a frst course on thermal scences n mechancal engneerng. Students wth a good understandng of these pages and wllng to use some deductve reasonng should e ale to perform effectve analyses of heat transfer for many engneerng purposes. Occasonal reference to more extensve property tales, charts and formulas n a dedcated textook on heat transfer or handook may e helpful for some prolems [Incropera & DeWtt 996, Mlls 99, Ozsk 985]. Most of the methodologes llustrated here are algerac. Calculus and dfferental equatons are used sparngly, prmarly to help students gan famlarty and eneft from the clarty and physcal nsght they rng to analyss, and to ndcate what more advanced analyss mght ental. Heat transfer s concerned wth the study of the transport of energy due to temperature dfferences. As engneers, we are more nterested n the rate of heat transfer, denoted n these notes y Q & [unt watts, or W, whch s J/s], rather than n the amount of heat energy transferred 3. In addton, we wll also fnd t convenent to work wth the heat transfer rate per unt area q&, [W/m ], whch we wll call the heat flux. Heat flux s clearly a vector, snce t has a magntude and a drecton. For many purposes the drecton s ovous y context, so we wll fnd t adequate to work wth the scalar verson of heat flux, denoted y q&. Student should make an effort to dstngush these from the amount of heat transfer Q [J] and heat transfer per unt mass q [J/kg] used n the thermodynamc dscussons of ths course. Heat transfer takes place n one of three modes: conducton, convecton and radaton. We wll refly dscuss each of these modes n ths secton. Practcal prolems of heat transfer frequently nvolve more than one component and more than one mode. he asc sklls for dealng wth mult-component, mult-mode heat transfer wll e dscussed n Secton. More detaled dscussons for asc calculatons for each of the three modes wll e dscussed n the Square rackets[ ] wth name(s) and year are keys to lst of references. Otherwse [ ] are used ndcate unts and dmensons, as ndcated n the next footnote. Another arevated ntroducton to heat transfer, wth dfferent emphass, can also e found n Chapter of Sonntag and Borgnakke, Introducton to Engneerng hermodyancs, Wley, 00, the current textook for ME30. 3 In some heat transfer ooks Q s used to denote the heat transfer rate [W] and q s used to denote heat flux [W/m ].

2 !H-ref,mmc,rev/5/0prt/5/0 next three sectons, to e followed y other sectons that wll develop our sklls further and ntroduce a few addtonal concepts. B. Conducton Heat ransfer Conducton s heat transfer due to temperature non-unformtes n a contnuous sustance, ether statonary or n moton. Consder the plane sla shown n Fg.. Oservatons supplemented y common sense reasonng suggest that the heat transfer rate Q & [W] must e proportonal to the temperature dfference [K], cross-sectonal area A [m ], and the nverse of the thckness B [m]. Q& = Ak () B Area = A Q & B Fg. Heat conducton through a plane sla he coeffcent of proportonalty k s a materal property, called the thermal conductvty. Unt consstency requres that the unt of k e [W/mK]. More careful analyss would ndcate that a more general way to wrte ths equaton s q& = k () cond where denotes the temperature gradent. hs s a vector whose drecton and magntude are the drecton and magntude of the steepest slope of temperature ncrease. he negatve sgn s necessary snce heat transfer only proceed from n the drecton of decreasng temperature. he x- component of oth sdes of Eq. () s q& x = k (3) x Smlar equatons can e otaned for the y- and z- components. Eq. () s known as the Fourer s Law of Heat Conducton. he algerac form, Eq. () can e used as an approxmaton for heat transfer through plane layers or thn non-planar layers n steady state f k s relatvely unform n the layer.

3 !H-ref,mmc,rev/5/0prt/5/0 3 Snce n general k s a materal property 4, t s a functon of and p. In most cases, however, the pressure dependence s small and k depends prmarly on temperature. ypcal thermal conductvtes for several classes of materal are shown n ale. It s advsale for students to e famlar wth the relatve magntudes of thermal conductvtes of dfferent classes of materal or representatve values, to facltate quck decsons n analyses or desgn. Other propertes n n ale wll e dscussed n later sectons. Materal, at temperature(s) Damond, at 300, 400K Alumnum oxde, at 300, 600 K Metals Pure copper, at 300 K Brass, a copper alloy, at 300, 600 Alumnum alloy 04-6, at 300, 600 K Caron steel, AISI 00, at 300, 000 K Stanless steel, AISI 30, at 300, 000 K Common Non-metallc Materals Plate glass, at 300 K Plastcs akelte, at 300 K Plastcs eflon, at 300 K Wood, common types, at 300 K Glass fer nsulaton, at 300 K Urethane foam nsulaton, at 300 K Lquds Water, at 300, 400 K Engne ol at 300 K Gases Helum, at 300, 600 K Ar, at 300, 600 K ale Selected hermal Propertes s shown W/mK 300, , , 49 77, , , , , , K 0 6 J/m α k/ρc 300 K 0 6 m /s If etter sources are not avalale, approxmate conductvtes at ntermedate temperatures for solds and lquds can e otaned y lnear nterpolaton. Interpolaton, and modest extrapolaton, for gas conductvtes can est e done y assumng logk-versus-log as lnear. Note that k s for common engneerng metals vary etween 5 00 W/mK, wth stanless steel near the ottom and alumnum alloys near the top. Pure metals have much hgher conductvtes than ther own alloys, ut are of no engneerng sgnfcance. Example Basc Conducton 4 he exceptons are very dlute gases or very thn (nanometer scale) layers, for whch molecular-scale effects ecome mportant.

4 !H-ref,mmc,rev/5/0prt/5/0 4 A hot water heater has an exposed surface area of.8 m. After t s nsulated wth nch of ferglass nsulaton, t s found that the nsde surface of the nsulaton s at 0 F, and outsde surface s at 90 F. Determne the heat loss through the nsulaton. Soluton: = 0 F 90 F = 30 F = 30*5/9=6.67 K A =.8 m B = n = *0.054=0.054 m k = W/mK (est nformaton convenently avalale, from ale ) Hence Q & = Ak /B =.8*0.046*6.67/0.054 [m ][W/mK][K/m] = W Students are strongly recommended to pay attenton to the followng n dong homework:. All quanttes not n SI unts are frst converted to SI unts to nsure unt consstency.. Arthmetc expresson s frst wrtten n symolc form, as n the case of = Ak to assst gradng and future checkng, and to nsure partal credt ncase of numercal error. hs s then followed y numercal susttutons n the same order so the grader can determne the value used for each parameter. 3. he numercal susttutons s accompaned y a unt consstency check n wrtten form, as n [m ][W/mK][K/m]. hs can e great help n spottng errors. hs may e omtted as you gan expertse and confdence, or when the prolem s smple and ovous. C. Convecton and the Convectve Heat ransfer Coeffcent he word convecton refers to the conveyance of energy y movng materal, usually a flud. he detaled study of convecton would nclude the study of the flow feld and ts effect on temperature dstruton. It s a suject of nterest not only to mechancal engneers ut also to other professons, for example chemcal and aeronautcal engneers and atmospherc scentsts. In elementary heat transfer analyses, however, the study of convecton prmarly refers to the calculaton of rate of heat transfer etween a sold surface and a ody of flud, due to the comned effects of flow and conducton. he consequence of the comned effects of flow and conducton n the flud s to concentrate the temperature varatons n the flud to a small layer adjacent to the surface, as llustrated y the shaded regons n Fg.. hs evokes the mage that the flud at large s well mxed, wth nearly unform temperature, and there exsts a ncreasngly stagnant flm near the wall whch consttutes the prmary resstance to heat transfer. hs s the thermal oundary layer, also called conducton oundary layer.

5 !H-ref,mmc,rev/5/0prt/5/0 5 For quanttatve calculatons, t s convenent to defne the convectve heat transfer coeffcent 5 h, attruted to Issac Newton: q& = h ; where w flud (4) As was the case n Eq. (), s customarly employed as a postve numer. he user should keep track of the drecton of heat transfer y oservng the sense of the temperature drop. he suscrpt w (wall) refers to the sold-flud nterface. As mght e expected, h vares wth the flow confguraton, the flud velocty, the dmenson of the mmersed oject or contanng vessel, and the flud propertes. It should e recognzed that ths s not a fundamental equaton, ut s merely a defnton of h for convenent computaton of the convectve heat flux. he actual value of h must e provded separately y detaled analyss or emprcal correlatons ased on accumulaton of data. Furthermore, there s also an amguty n assgnng flud. By conventon, for external flows, llustrated n Fg. a and c, flud s taken to e the undstured flud temperature away from the wall, usually denoted as. For nternal flows, llustrated n Fg., flud vares wth axal poston and s taken to e the average temperature over the cross secton wth the flow rate as the weghtng factor. hs wll e dscussed n greater detal n a later secton. f = w V V w V a w f = ave c Fg. Common confguratons of convecton. a. External flow Forced Convecton,. Internal flow Forced Convecton, c. Free or Natural Convecton 5 he heat transfer coeffcent s almost unversally denoted y h, the same symol used for specfc enthalpy. Students should e alert to dstngush the two y context.

6 !H-ref,mmc,rev/5/0prt/5/0 6 Forced convecton refers to convecton due to an mposed velocty, as shown n a and of Fg., whereas natural or free convecton refers to flows generated naturally y the uoyancy of heated ar, as shown n c of Fg.. As an example for forced convecton, consder a crcular rod or ppe wth surface temperature w, sujected to a cross wnd of ar at velocty U and temperature. hs s an external flow, forced convecton prolem, for whch s computed as w. For ranges of condtons shown y the nequaltes, an approxmate formula wth aout 5% accuracy s V h For ar, 80 K < 30 K, 0.5 VD mf < < <. D ( h n W/m K, V n m/s, D n m) (5) hs formula has een derved from a more elaorate and more general formula (see Secton 4) y usng propertes of ar at 300 K. If the mean flm temperature mf ( w + ) / strays too far from 300 K, the assumed propertes wll no longer e vald, and results wll not e accurate. As an example for free convecton, consder a heated horzontal ppe located n stll ar. In ths case uoyancy would nduce a local ar flow just around the ppes, n the manner of Fg. c. For ranges of condtons shown, an approxmate formula wth aout 5% accuracy s h =. 55 ( ) D For ar, 0.00 < D 80 K < 3 mf < 00, < 30 K, < 60, ( h n W/m K, n K, D n m) Both of these formulas are approxmatons of the more elaorate and more general formulas to e dscussed n Secton 4. Note that these specalzed formulas constructed for restrcted applcatons must e used wth the specfed set of unts, and must e converted carefully when parameters n other unts are nvolved. In contrast, fundamental physcal laws and asc defntons, such as Eqs. (), (3) and (4), are general and can e used wth any set of selfconsstent unts. he exponents n these formulas are emprcal and wll change wth condtons. Wthn the specfed range of valdty, the exponents gve a concse ndcaton of the dependence of h on parameters U and D. For example, t can e shown from Eq. (5) that for ths forced convecton confguraton, a one percent ncrease of U wll lead to a 0.65% ncrease n h, and each percent ncrease of D wll lead to a 0.35% decrease n h. Smlarly, Eq. (6) tells us that h for free convecton s approxmately proportonal to /3-power of the temperature dfference, and nversely proportonal to the one-tenth power of D. hs type of understandng of the trends s very valuale n engneerng desgn and analyss. Representatve values of h are gven n ale. he forgong dscusson clearly shows that the convecton heat transfer coeffcent represents a form of conducton modfed y flud moton. Hence we cannot smultaneously (6)

7 !H-ref,mmc,rev/5/0prt/5/0 7 consder the conducton and convecton through the same ody of flud, or doule countng would result. ale. ypcal Values of Heat ransfer Coeffcents (n W/m K) (From varous sources) Free Convecton Gases 5 0 (Some dependence) Lquds Forced Convecton Gases 5 50 (Weak dependence) Lquds 50 0,000 Bolng and Condensaton (Strong-Weak dependence) h for radaton near room temperature h for radaton around 600 K,500 00, ~50 Example. Forced Convecton An ar heater conssts of electrc heatng elements, 0.5 n dameter and 3 ft long, each dsspatng 00 W. A fan lows ar, at 5 C across the heaters at 5000 ft/mn. Determne the heat transfer coeffcent and the surface temperature of the heater. Soluton: From Eq. (4), and the defnton of, the total heat transfer rate s ( ) Q& = Ah w whch can e solved to yeld w + Q& / Ah = V = 5000**0.054/60=5.4 m/s D = 0.5*0.054 = 0.07 m h = 4.68*5.4^0.65/0.07^0.035 = 44.6 W/m K A = 3**0.054*p()*0.07= m (End surfaces neglected) w = Q& + / Ah = 5+00/(44.6* ) [W]/[m ][W/m K] = 7.8 C A retrospectve check shows that the computed mean flm temperature would e aout 76 C, consderaly aove the allowed lmt. hs means that the results are lkely to e qute naccurate, wth errors greater than 5%, whch corresponds to a error n greater than 5 K. If more accurate results are desred, the more elaorate formulas of Secton 4, or a dedcated text ook on heat transfer, should e consulted.

8 !H-ref,mmc,rev/5/0prt/5/0 8 Comments on Accuracy Although the result of the last example s not very accurate, t nevertheless can serve very useful engneerng functons. For example, an estmated temperature of 8 C s proaly suffcent to show that the surface s unlkely to start a fre f t s n contact wth a pece of wood or paper. On the other hand, t s proaly hot enough to present a urn hazard to humans and pets, and should e desgned wth safeguards to prevent drect contact. Example 3 Free Convecton A horzontal heatng element, 0.5 dameter and 3 feet long, s located n a room wth stll ar at 0 C. he surface temperature of the heatng element s mantaned at 40 C. Determne the free convecton heat transfer coeffcent and the total heat transfer rate. Soluton hs rod has the same dmensons as the rod n Example. From Eq. (6), wth = 50 0 = 30 K, ( ) 0. 3 h =. 55 =.55*30^0.3/0.07^0.= W/m K 0. D Q& fr c = Ah = *6.504*30 [m ][W/m K][K] = 7.8 W D. Radaton Heat ransfer It s apparent to most oservers that very hot surfaces such as stoves and freplaces, as well as the sun, can transmt heat wthout the help of an ntervenng materal, and that the heat can e asored y ojects whch are n lne-of-sght of such hot ojects. hs s thermal radaton, emtted y all ojects not at asolute zero temperature. We now know that thermal radaton s a form of electromagnetc wave. All electromagnetc waves carry energy, and represent transmtted power. ypcal thermal radaton dffers from waves ntended for sgnal transmsson n that t s spread over a wde wavelength range (or equvalently, frequency range). he sun s radaton s thermal radaton wth the ulk of ts power spread over a wavelength range of µm. Evoluton has made our eyes adapt to ths ountful source of radaton. So we now call ths range the vsle lght range. Ojects at lower temperatures generally emt at longer wavelengths. Most earthound radaton heat transfer occurs n the nfrared range, wth wavelengths aove µm. hermal radaton has essentally the same propertes as lght, travelng n straght lnes n unform, transparent meda and can e transmtted, asored, or reflected from surfaces. Ar at moderate temperatures s essentally transparent to nfrared radaton, whereas most lquds and solds are not. Hence an mportant class of radatve heat transfer prolems s concerned wth heat exchange among surfaces, ether n vacuum or mmersed n ar. he general prncples and methodology of such analyses wll e ntroduced n later sectons. o provde an example for the relatve magntude and mathematcs of radatve heat transfer, we wll cte wthout dervaton one smple formula for an mportance case of radatve transfer. hs s the case when a small ody s completely enclosed y a larger enclosure e, as shown n Fg. 3a. We wll later show that as long as e s at least two- or three-fold as large as,

9 !H-ref,mmc,rev/5/0prt/5/0 9 essentally all of the radaton emtted from wll e asored y e after ether sngle or multple reflecton n the cavty. On the other hand, most of the radaton emtted y e, n whchever drecton, s lkely to e reflected y other parts of e and n the process joned y addtonal emssons, so that when t fnally reaches t wll nearly equal the deal theoretcal ntensty correspondng to e s surface temperature, ndependent of the surface propertes. Under such condtons the net radatve heat transfer etween and e can e satsfactorly calculaton y the approxmate expresson r, e 4 4 ( ) Q& = A ε σ (7) e In the aove equaton, σ s a unversal physcal constant called the Stephan-Boltzmann constant, equal to 5.67(0) 8 W/m K 4. ε s a dmensonless surface property called the emssvty []. Note that heat transfer s proportonal to the dfference of the 4 th power of temperatures 6, ut depends only on the surface area and emssvty ε of ody, and not on those of e. More detaled explanaton for ths apparent asymmetry n the formula wll e dscussed later. he emssvty s the rato of the emssve power of a surface compared to that of a perfect emtter, called a lack ody. For all ut hghly polshed metals, the emssvty s typcally etween 0.7 and. Sample emssvtes for selected surface are shown n ale 3. e a Fg. 3 a. A small ody completely enclosed n a larger ody.. A wndow pane wth one sde exchangng heat radatvely wth nteror walls, furnture and occupants, and another sde exchangng heat wth the exteror radatve envronment, ncludng ground, trees, clouds, mst and mosture n the atmosphere, and deep space. he aove equaton can e generalzed to apply to the radatve exchange etween any small surface exchangng heat radatvely wth a comnaton of odes whch enclose t optcally. Examples nclude the nsde surface of the wndow pane shown n Fg. 3, exchangng heat radatvely wth a comnaton of surfaces whch completely occupy ts vew, ncludng all the nteror walls and the furnture. Note that common glass s opaque to nfrared radaton. he 6 For essentally lnear processes such as convecton and conducton, t s mmateral whether temperature s Celsus or Kelvn. For a non-lnear process such as radaton, t s essental to use the asolute temperature.

10 !H-ref,mmc,rev/5/0prt/5/0 0 nsde surface of the glass therefore cannot communcate radatvely wth the outsde. hermal radaton nsde the room does not pass through the wndow. Smlarly, the exteror surface of the wndowpane exchanges heat radatvely wth the outsde ground, the trees, cloud, droplet-laden atmosphere, and the deep space ackground. In ether case e n the aove equaton s replaced, a sutaly defned mean radatve envronment temperature: y mre r, e 4 4 ( ) Q& = A ε σ (8) mre For certan calculatons t s more convenent to recast these results n terms the more famlar heat transfer coeffcent. We may then defne a radaton heat transfer coeffcent n a manner smlar to the convectve heat transfer coeffcent: r, e r ( ) Q & A h (9) mre Solvng for h from these two equatons, we have, after re-arrangement 3 3 hr = 4ε σ ave + 4 ave f 0. 3 ave ε σ (0) ave where ave ( + mre ) /, mre. he approxmate form s usually adequate snce rarely s greater than 0. 3ave. ypcal values of the radatve heat transfer coeffcent are also lsted n ale, for comparson wth convectve coeffcents. ale 3 Sample Ranges of Emssvtes and Asorptvtes Clean, hghly polshed metals Common metal surfaces Oxdzed metal surfaces Clean Al O 3 (whte), at room temperature 0.7 At C Most surfaces at room temperature, ncludng some apparently whte surfaces Example 4 Radatve Heat ransfer and Comned Radaton and Convecton For the prolem of Example 3, f the mean radatve envronment temperature s also 0 C, determne the radatve heat loss and the total heat loss due to radaton and convecton. Assume the emssvty of heatng element to e 0.9. Soluton

11 !H-ref,mmc,rev/5/0prt/5/0 It s mportant to convert all s to Kelvn: = = =33.5 K, Smlarly, mre =83.5 K, ave =98.5 K. Q& r, e = A ε σ 4 4 ( ) mre w = *0.9*5.67E-8*(33.5^4-83.5^4) [m ][][W/m K 4 ][K 4 ] = W We can next try to solve the prolem usng the radatve heat transfer coeffcent, and see f we get essentally the same result. Snce the nequalty s satsfed, we may use the smple approxmate equaton for h: h Q& r r, e 3 4εσave A h r = 4*0.9*5.67E-8*98.5^3 [] [W/m K 4 ][K 3 ]= 5.40 W/m K ( ) mre a = *5.40*30 [m ][W/m K][K]= 5.9 W he dfference etween ths and the prevous result of W s small. Ar s transparent. Hence convecton and radaton can proceed ndependently and smultaneously. Hence the total heat transfer rate s the sum of the two, or Q & = Q& + Q& = = 3.05 W total free c rad In ths prolem, the ament condtons for oth convecton and radaton are oth equal to 0 C. herefore we can also comne the two heat transfer coeffcents and use a total heat transfer coeffcent equal to =.94 W/m K. Usng ths value Q& total ( + h ) = A hfr c rad = *.94*30 [m ][W/m K][K]= 3.04 W Example 5 Comned Radaton and Convecton -- Inverse Prolem If the heatng element of Examples 3 and 4 s known to dsspate 0 W y convecton and radaton, what s s the surface temperature? Comments: Comnng radaton and convectve heat transfer, we have Q& total 4 4 ( ) + Ah( ) = Aε w σ w mre w o solve for the unknown w nvolves a messy, hghly non-lnear algerac prolem. he dffculty s not allevated y usng the radatve heat transfer coeffcent formulaton, snce wthout a known surface temperature, the radatve heat transfer coeffcent cannot e determned. Hence such a prolem must e solved usng one of the teraton methods. hs example wll e completed n Secton.F.

12 !H-ref,mmc,rev/5/0prt/5/0. Formulaton and Soluton Methodologes A. Conservaton Laws Heat transfer analyss usually requres two types of equatons. he relatonshps dscussed aove, relatng the conductve, convectve and radatve heat fluxes to varous forms of temperature non-unformtes, are called consttutve relatonshps. he second type of equatons are the conservaton laws. he prmary conservaton law used n heat transfer s the conservaton of energy, though sometmes t s supplemented y the conservaton of mass and conservaton of momentum. Beyond the smplest of prolems, at least some of the varales of nterest, ncludng temperature, heat flux, etc., are unknown. he conservaton of energy s then used to te them together n algerac and/or dfferental equatons, whch are then solved to permt calculaton of the desred quanttes. Examples wll e gven n su-secton C elow and n later sectons. In tme-dependent heat transfer prolems and n convecton prolems, changes n nternal energy and enthalpy are often expressed n a per-volume ass as ρ d and ρc p d respectvely. he specfc heats c v and c p always appear n comnaton wth ρ, never can thus e vewed as a sngle property Sample values are shown n ale. It s alone. ρcp useful to note that for solds and lquds, ther values cluster around.5(0) 6 J/m 3 K, and s almost always wthn the range.7 4.(0) 6 J/m 3 K. hs means crude ut relale estmates can often e made wthout detaled knowledge of the two separate propertes ρ and c p. he alty to do ths can e of consderale value n analyss and desgn when precse property values are not avalale. B. Unt and Dmensons Unts play mportant roles n heat transfer analyss. hs s partcularly true n the present transton perod etween tradtonal Amercan unts and the new standard, SI. Whle SI unts are self-consstent, so that no converson s necessary etween work unt [N-m] and the unt of thermal energy [J], ths s not true for the tradtonal Amercan unts. Careless use of nconsstent unts s a frequent cause of errors. Mathematcal expressons ased on physcal laws must also have unt consstency each term n the expresson must e reducle to the same unts. hs s a valuale tool for checkng the correctness of dervatons and calculatons for correctness. Students should develop the hat of checkng unts constantly as he/she s performng the analyss. Once the hat s developed, t can e effortless and s not tme-consumng, ut can often save a lot of the tme wasted on erroneous computatons. Self-consstent unts are derved from just a few asc quanttes, called dmensons. For example, the SI unt of force, N, s really [kg-m/s ], derved through the equaton F = ma. Hence the dmenson for force s [ML/ ], where M, L and denote the dmensons of mass, length and tme. he checkng of dmensonal consstency s clearly a requste for unt consstency. A smple and effectve way to nsure dmensonal consstency s to render equatons dmensonless y makng all varales and parameters n the equaton dmensonless. Examples of such an approach can e found n Secton 4. c v

13 !H-ref,mmc,rev/5/0prt/5/0 3 Another common source of error s the careless treatment of prefxes k, M, m (klo, mega, mll), etc. Whle kg s part of the asc, self-consstent SI system, other unts, such as kj, mm, are not. For example, to determne the velocty correspondng to a gven knetc energy, usng kj n the equaton K.E. = mv / would lead to erroneous answers. If energy s gven n kj, t s necessary to convert t to J efore usng ths equaton to calculate the velocty. C. Resstances, Conductances and Comnaton Rules o hghlght the value of the concepts to e dscussed elow, we shall egn y consderng a smple composte wall consstng of two layers of dfferent materals onded together, an nner layer of thckness B a wth conductvty k a, and a outer layer of thckness B wth conductvty k. he nsde and outsde temperatures are, 3 respectvely. What s the heat transfer rate per unt area? he soluton to ths prolem s not straghtforward, ecause the temperature at the nterface etween the two layers s not known. he concept of resstance wll greatly smplfy the analyss of ths type of prolems. he conducton and convecton expressons, and the approxmate expresson for radaton dscussed n Secton all show the heat transfer rates to e proportonal to the temperature dfference. hs s analogous to the flow of electrc current, whch s proportonal to the voltage dfference across a component. he analogy permts us the defne the heat transfer resstance, denoted y R, as the rato of the temperature dfference and the heat transfer rate, wth unt [K/W]: R [K/W], or Q& () Q& R For example, the conducton resstance for the plane sla, the convectve resstance for an area A wth coeffcent h, and radatve resstance for a small oject n a large enclosure, accordng to Eqs. ()(4) and (0) respectvely, are B Rk, sla = ; Rv = ; Rr, a = = () Ak Ah Ah 4Aε σ where the suscrpts k, v, r denote conducton, convecton, and radaton respectvely. he great eneft of orrowng the resstance concept from electrcal crcutry s that the well-estalshed comnaton rules for electrcal resstances also apply here for heat transfer resstances. hese rules are for the calculaton of the equvalent resultant resstance for comnatons of the ndvdual resstances, accordng to whether they are n seres or parallel: For Seres Resstances: Equvalent resstance equals to sum of ndvdual resstances n R e = R = r a 3 ave for seres resstances (3) For Parallel Resstances: Inverse of equvalent resstance equals sum of nverses of ndvdual resstances

14 !H-ref,mmc,rev/5/0prt/5/0 4 n = R e R = for parallel resstances (4a) An alternatve statement for Eq. (4) s to make use of the concept of conductance, whch s just the nverse of the resstance G (5) R he comnaton rule for parallel resstance can now e stated as Equvalent Conductance s equal to the sum of conductances: n R e = R = for parallel resstances (4) Shown on the rght of the equatons are standard schematc representatons for resstance networks, whch we have also orrowed. hs can e very valuale for constructng schematcs to ad n vsualzng the relatonshp etween dfferent heat transfer components n an overall system. Dervaton of the comnaton rules he orgn of the comnaton rules s the conservaton of energy. he comnaton rule for parallel resstances smply states that the total heat transfer s equal to the sum of heat transfer through all resstances. hs s ecause for each resstance, Q & = / R. Snce s the same for all parallel resstances, the total heat transfer s smply the product of and the sum of all (/R) s. o derve the comnaton rule for seres resstances, we consder the composte wall of two slas, descred n the lead paragraph of ths secton. he prolem conssts of two components (slas), a and, n seres, wth known overall = 3. he temperature of the medan nterface s not known. o solve ths prolem, we oserve that n steady state, conservaton of energy requres oth slas to have the same heat transfer rate Q &. Referrng to the defnton of resstance, we can wrte, for layers a and : a : : 3 = R Q& a = R Q& We have two equatons for the two unknowns Q & and. he algera of elmnatng the s partcularly easy -- we smply add oth sdes of the equatons. he result s a formula for Q & n terms of the overall and ( R + R ), whch s clearly the equvalent resstance: = ( R + R )Q & 3 a hs proves the comnaton rule for two resstances n seres. he proof can e easly extended to any numer of resstances n seres.

15 !H-ref,mmc,rev/5/0prt/5/0 5 Applcaton of the Comnaton Rules he comnaton rules can e used systematcally to reduce a complex system wth multple components to a smple system wth only one equvalent resstance or conductance. hs s llustrated y the followng example. Example 6 An ndustral oven, wth nsde surface temperature at 0 C, conssts of a 0. m thck ceramc wall of conductvty k =.6 W/mK, covered y a layer of nsulaton 0. m thck wth k = 0.05 W/mK. he outsde wall s exposed to ar at 5 C wth a convectve heat transfer coeffcent of 30 W/m K and to a mean radatve envronment at 5 C, wth a radatve heat transfer coeffcent of 7 W/m K. (a) Determne the heat loss per m of the wall. () Determne the nterface temperature f and the surface temperature s. Soluton: he crcut representaton for ths prolem s shown n Rcer Rns Rconv out Rrad We shall frst comne the two parallel components -- the convectve and radatve heat transfer coeffcents. We may use ether Eq. (4a) or (4), though latter s much smpler and smply states that radaton and convecton n ar can proceed ndependently and are addtve. Hence the equvalent resstance R vr for comned convecton and radaton s R vr = = A h =/(30+7) = K/W, for m ( + h ) conv rad hs reduced the prolem to three resstances n seres. he total resstance, for m of area, s hence Bcer Bns R tot = Rcer + Rns + Rvr = + + R Ak Ak cer = 0./ / = =.490 K/W (a) For heat transfer rate Q& = = (0 5)/.490 = 38.5 W per m. R tot tot? f? s () o determne the temperatures, we make use of the relatonshp etween temperature dfference and resstance. Frst, for the ceramc wall ns vr

16 !H-ref,mmc,rev/5/0prt/5/0 6 Q& = R f cer cer n n f =. Hence R cer cer = Q& R = *0.065 = = 7.6 C. Next, for the comned convecton/radaton coeffcents Q& = R s vr vr out = s R vr out vr. Hence = + Q& R = * = = 6.3 C. Unt Area Resstance and the R-Value In Example 6, we computed the heat transfer rate Q & and resstance R for unt area of the wall, ut retaned the unts for the overall heat transfer and resstance, [W] and [K/W] respectvely. If we desre, we can also express the results n terms of unt-area symols and unts. For heat transfer per unt area, ths s the heat flux q& [W/m ]. Snce resstance s nversely proportonal to the area, the unt s [m K/W]. Note that we can not call ths the resstance per unt area or per m ecause of recprocal relatonshp. We shall refer to t as the unt area resstance. he R-value often cted n connecton wth uldng products n the US s the unt area resstance n [ft hr F/Btu]. For example, consder a 3.5 thck layer of ferglass nsulaton. Wth k = W/mK, the unt area resstance value would e B / k = 3.5*.054/0.04 =. m K/W. Converted to tradtonal Amercan unts, we have R-Value =.*3.808^*.8/3.43 =.6 ft hr F/Btu. hs s close to, ut not necessarly equal to the marked R-value of roll nsulaton eng sold n uldng materal stores ecause of varatons of product and manufacturng processes. D. Domnant and Non-domnant Components Most real-lfe prolems n engneerng nvolve more than one component. In these prolems t mmensely mportant to have an apprecaton for what s domnant and what s not. Knowng what s domnant s valuale n desgn teratons, as well as n allocatng tme and effort for analyss. Clearly effort expended n detaled, accurate analyss of a domnant component pays far greater dvdends than effort expended on an unmportant component. For most people the alty and hat to assess quckly what s domnant does not come naturally, ut s developed after repeated practce. Consder the prolem of Example 6. For ths prolem, the overall resstance, for m of area, was found to e.49 K/W. Of ths, the nsulaton accounts for.4 K/W, or aout 96% of total. hs s clearly the domnant resstance. In contrast, the ceramc wall accounts for aout.5%, and the comnaton of convecton and radaton coeffcents accounts for only.%. Suppose some one ponts out that the accuracy of the convecton heat transfer coeffcent s very low, only 30%. Is t worthwhle for us to re-evaluate these coeffcents? Proaly not. hs s ecause a 30% error of.% of the total resstance s only 0.33%, whch s clearly too low to

17 !H-ref,mmc,rev/5/0prt/5/0 7 e of concern. If we wsh to mprove the accuracy of the overall computaton, we must focus on the thckness of the nsulaton and the accuracy of the value of thermal conductvty. Smlar consderatons may also suggest that we smply neglect the radatve contruton to heat transfer. Snce t s much smaller than convecton, and snce even convecton s not too mportant, the neglect of radaton would not ntroduce sgnfcant errors n ths case. Suppose we wsh to reduce the total heat loss. Clearly ncreasng the thckness of the ceramc wall s not cost-effectve, snce t accounts for only.5% of the total resstance. A small ncrease of the thckness of the nsulaton would accomplsh the goal much more economcally. Conversely, we may desre to change the desgn to ncrease the effcency of heat transfer, n order to reduce the nsde surface temperature for the same heat transfer rate. Clearly ncreasng the ar coolng would not e effectve, snce convecton only accounts for a neglgle fracton of the resstance. Decreasng the thckness of nsulaton s the most effectve measure for ths purpose. E. General Method for Lnear Networks Not all networks can e smplfed y comnaton rules. For example, the smple network n Fg. 4. s a non-comnale network. Fortunately, there s a general method for solvng all lnear resstance networks. We wll frst descre the method for the smple network shown n Fg. 4.. Afterwards the general procedure wll e descred. Let and and all the fve resstances e known. We wsh to determne the total heat transfer from node to node 4, along wth the temperatures at nodes and 3. Conservaton of energy requres that n steady state, the total heat transfer toward any node must vansh. Applyng ths prncple to nodes and 3, we have R a R R c R c R + 4 d R e 3 = 0 = 0 hs consttute a set of two lnear algerac equatons, wth two unknowns and. hese of course can e solved n a straghtforward manner, y any of the many methods for lnear algerac equatons. Once and are known, the heat transfer can e otaned. (6) (7) R 3 Re Rc 4 Ra Rd Fg. 4. Example of a non-comnale resstance network

18 !H-ref,mmc,rev/5/0prt/5/0 8 hs procedure can e extended to any network wth any numer of unknown nodal temperatures. Invokng the conservaton of energy wll usually lead to one equaton for each node wth an unknown temperature. Soluton of these equatons y Gaussan elmnaton or other matrx nverson schemes s straghtforward. Iteraton methods may also e used. Once the unknown temperatures have een found, the computaton of heat transfer rates follows drectly. F. emperature-dependent Coeffcents, Non-lneartes here s a potental catch- stuaton that occur frequently n heat transfer analyss. Most resstances and conductances are temperature-dependent. he temperature-dependence of the coeffcents for free convecton and radaton s qute ovous. Even conducton and forced convecton are at least somewhat temperature-dependent, ecause the conductvty and other physcal propertes are temperature dependent. When we egn to solve a heat transfer prolem, the temperature dstruton s frequently not known. How can we proceed? he dffculty s a symptom of the non-lnearty of the prolem. Wth temperaturedependent resstances and conductances, nether the resstance-comnaton method nor the smultaneous equaton method descred n su-sectons C and E apples. he answer to ths dffculty s teraton. Rather than attemptng to solve the prolem drectly, many teraton methods are far more effcent n ths type of stuatons. For example, the Newton-Raphson method would e qute effectve. For most heat transfer prolem, however, a specal form of the successve susttuton method s oth effcent and ntutvely easy to understand. For smple prolems, the method can e easly mplemented wth a programmale computer. For ether smple or complex prolems, t can also e easly mplemented wth a spreadsheet program such as Excel. o start the teraton process, reasonale guesses (these are called frst terates ) are frst assumed for each of the unknown temperatures requred for the evaluaton of the coeffcents. hese wll permt the resstances to e determned. Wth known tentatve resstances, the crcut can e constructed and solved, as f t were a lnear prolem. he temperatures from ths soluton are often mprovements over the frst terates, and can e used to as second terates to evaluate mproved coeffcents and resstances. he processes can e repeated untl the temperatures no longer change. he valty of the method depends on the fact that frequently, the coeffcents are only weakly dependent on temperature. hus a gven relatve error n temperature would lead to a smaller relatve error n the coeffcents. When these coeffcents are used to compute new temperatures, the relatve error would e smaller than those orgnally assumed. As n all teraton methods, occasonally condtons are such that succeedng terates do not represent mproved values, ut may ether oscllate or contnue to change wthout settlng down to a converged value. In ths case the teraton s sad to dverge and another teraton method must e found. Fortunately, the successve susttuton method descred here wll converge for most heat transfer prolems. We wll llustrate ths method y completng the soluton of Example 5. Example 5 (contnued from Secton.D)

19 !H-ref,mmc,rev/5/0prt/5/0 9 hs s the same prolem as Example 4, except that the surface temperature s unknown and that the heatng element s dsspatng 0 W. Wth mre = ( )( h h ) Q & + = A s fc r D = 0.07 m, A = m (Prevously computed. End surfaces neglected) For frst terate, assume surface temperature to e 33.5 K (40 C). he free convecton and radaton heat transfer coeffcents would then e W/m K and 5.40 W/m K respectvely. R = s ( + ) A h fc h r = /( *( )) =.30 K/W = + Q& R = *.30=39.7 K total Wth ths surface temperature, we can re-evaluate the free convecton and radaton heat transfer coeffcents h fr c =. 55 ( ) D ( + )/ =.55*( )^0.3/0.07^0.= W/m K ave = s = ( )/ = K h ra 3 4ε a σave = 4*0.9*5.67E-8*306.6^3 = W/m K hese can the used to calculate R, s n turn, startng a new cycle of teraton. In sx teratons 7, the converged value for the surface temperature s found to e 35.3 K. Iteraton numer s Assumed hfr-c ave hr (Exact) R s Computed * It s nterestng to note that should the gven power of the heatng element e 400 W or hgher nstead of 0 W, the teraton process descred here would dverge. hs s ecause at the hgh temperatures correspondng to these hgh power levels, radaton domnates. he radaton heat transfer coeffcent at thse hgh temperatures s very strongly temperature-dependent.

20 !H-ref,mmc,rev/5/0prt/5/ *Iteraton can stop at ths pont wth less than 0.3% error. 3. Steady Conducton through Non-planer Geometres A. he Dfferental Equaton for Heat Conducton for Constant Densty Meda (hs susecton s for your enrchment only. horough understandng not requred.) Consder a sold or a statonary flud wth non-unform ut steady temperature ( x, y, z). We wll see that ( x, y, z) oeys a dfferental equaton that can e otaned from the conservaton of energy. he dfferental equaton can then e solved to determne the heat transfer ehavor of complex ody shapes. We wll conser the conservaton of energy for a very small volume element dxdydz center at locaton (x,y,z). Snce qx denotes the heat flux n the x-drecton, ( dx)( qx / x) denotes the dfference etween the heat flux on the rght surface and that on the left surface. Hence the net rate of outward heat transfer due to q x for ths element s qx ( dydz) dx x where the product n the parenthess represents the cross-sectonal area. Smlarly, the net rate of outward heat transfer due to qy and q z for ths element are q y qz ( dzdx) dy, ( dxdy) dz y z he sum of these three terms s the total rate of outward heat transfer for the element dxdydz. Conservaton of energy states that, n the asence of volume change (whch leads to work), the total rate of outward heat transfer must e equal to the rate of decrease of nternal energy, equal to the mass ( dxdydz )ρ tmes the rate of decrease of specfc nternal energy ( u / t). Puttng these together, we have u t q x q x y ( dxdydz) = ( dydz) dx + ( dzdx) dy + ( dxdy) y q dz z Recognzng that ( u / t) = c( / t), and makng use of Eq. (3) and ts counterparts n y- and z- drectons, the dfferental equaton for heat conducton ecomes ρ c = k + k + k (8) t x x y y z z z

21 !H-ref,mmc,rev/5/0prt/5/0 Frequently smpler forms of ths equaton are satsfactory. For example, for constant thermal conductvty, k can e moved n front of the dfferentaton sgn and wth ρc to form α = k/ρc: = α + + (9) t x y z In cylndrcal coordnates wth ax-symmetry (.e., ndependent of θ ), the same equaton takes the form = α r + r (0) t r r z For -D ax-symmetrc prolems n polar coordnates, the z-dervatve term s omtted. For steady state prolems, the tme dervatves vansh, the reduced equatons just consst of contents of the parentheses set equal to zero. B. Steady Conducton through a Cylndrcal Shell We now consder a cylndrcal shell of length L, and nner and outer rad R and R o, at temperatures and o respectvely. Although ths prolem can e solved from the more general partal dfferental equaton dscussed n the last secton, the smple geometry permts a straghtforward formulaton n ordnary dfferental equatons, whch wll e llustrated here. he cross secton of the shell s shown n Fg. 5. he total heat transfer rate Q at any radus r s gven y Eq. (3) to e Q d = () () r L( πr) dr In ths case we expect the heat flux qr to decrease as r ncreases, ecause the same total heat transfer s spread over a larger cylndrcal area. So the dfferental equaton requred s otaned y requred Q to e constant and unchangng: d d d Q() r = 0 or r = 0 f k = unform 8 () dr dr dr he oundary condtons are ( R ) = ( Ro ) o, = (3) r 8 hs equaton can also e otaned from Eq. (0) y settng the tme and z-dervatves equal to zero. R R o

22 !H-ref,mmc,rev/5/0prt/5/0 Fg. 5. he Cross-secton of a cylndrcal shell hs system can e solved easly y two successve ntegratons and evaluatng the constants wth the help of oundary condtons. he results s πl Q = R ln R o k C. More Complex Shapes, Conducton Shape Factors For more complex ody shapes than the plane sla and the cylndrcal shell, the prncple of the method of analyss s the same. he only dfference s that n most cases the conservaton of energy leads to a partal dfferental equaton 9 + x y = 0 wth oundary condtons gven at all exteror surfaces. Methods for solvng such equatons are eyond the scope of ths ref ntroducton. hey can e found n mathematcal texts, especally those on numercal methods. For frequently encountered ody shapes, however, such solutons have already een otaned y engneers and taulated n reference sources. We wll refly descre the use of such a resource. It can e shown from dmensonal consderatons that all solutons of steady heat condton prolems wth an mposed are n the followng format: Q = Sk (6) he factor S, called the Conducton Shape factor, contans all the mportant nformaton on the shape and sze of the ody. It has the dmenson [L], whch s a consequence of the fact that heat transfer rate s proportonal to the cross secton area, of dmenson [L ], and nversely proportonal to the length of the heat conducton path, of dmenson [L]. aulatons of the conducton shape factor can e found n many heat transfer reference sources, ncludng most (4) (5) 9 hs can e otaned from Eq. (9) y settng the parenthess = 0 and omttng the z-dervatve term.

23 !H-ref,mmc,rev/5/0prt/5/0 3 text ooks. An arevated lst of some of the most useful shape factors s shown n ale 4. for llustratve purposes and to provde for smple calculatons. D. emperature-dependent Conductvty and the Average Conductvty hermal conductvtes are strong functons of temperature. For prolems spannng a small enough temperature range, ths varaton may e nconsequental. Assumng the conductvty to e constant and equal to any representatve value wthn the range would lead to lttle error. On the other hand, f the varaton of conductvty s large, one may ask f there s a technque to avod the complcatons of solvng non-lnear equatons? he answer s yes, at least for steady state conducton prolems. For steady conducton prolems, t can e shown that the average thermal conductvty defned n the usual sense wll yeld the correct heat transfer calculatons: k kd (7) ale 4. A Short Lst of Selected Conducton Shape Factors S Q Sk Descrpton Schematc Condtons Shape Factor Eccentrc cylndrcal shell of length L, dameters D & D o, and eccentrcty e. Rectangular shell of length L, wth square cross sectons of sdes D & D o. Addtve correcton for edge of ntersectng walls, when walls have een computed usng plane sla formula Cylnder, of dam. D & length L, surface at, ured n semnfnte medum normal to plane D o B L e D o D o > D and L >> D Do + D 4e o cosh DoD D o / D <.4 D o / D >.4 π L π L ln D o D ( / ) π L 0. 93ln D o D L / B > L ( / ) π L L >> D ln( 4L / D)

24 !H-ref,mmc,rev/5/0prt/5/0 4 surface, at Example 7. Determne the heat transfer rate per meter for a.5 cm dam. ppe at 00 C, nsulated wth cm of ferglass nsulaton wth the outer surface temperature equal to 30 C. Soluton: We wll solve ths prolem wth two methods and compare the results. Method. We wll use Eq. (4) for the cylndrcal shell. πl Q = R ln R o k =*π*l*k*(00 30)/ln(4.5/.5) =*π**0.046*70/ln(4.5/.5)=34.4 W Method, We wll use the entry for eccentrc cylnders n the shape factor tale, and settng the eccentrcty equal to zero. π L π L Q = Sk = k = k cosh Do + D e cosh + * 4. 5 *. 5 DoD π L π L π = k = k = * 70 = W cosh (. 777) 4. Convecton Heat ransfer Coeffcents A. Correlatons of h n terms of Nusselt Numers We have prevously ntroduced the heat transfer coeffcent h for the computaton of convectve heat transfer: q& = h ; where w flud (8) Only two sample formulas for determnng h were gven. We shall now dscuss how to determne h for wde ranges of condtons. In prncple, h can e evaluated from solutons of the partal dfferental equatons of heat transfer and flud flow. hs can e qute nvolved and s the concern of more advanced studes of convecton. For smple and frequently encountered flow confguratons, use can made of complatons of formulas and correlatons already estalshed y analyss and experments. hese can e found for n handooks and textooks of elementary heat transfer. hese formulas are typcally gven n the form of a dmensonless parameter called Nusselt numer, defned as hl/k, where L s a characterstc length, ether length, heght or dameter as s approprate for the prolem. For forced convecton when the velocty s mposed, the Nusselt numer s represented as a functon of the Reynolds numer Re UL/ν, a dmensonless velocty for vscous flow, and the Prandtl numer Pr ν /α, a flud property equal to the rato of momentum

25 !H-ref,mmc,rev/5/0prt/5/0 5 and heat dffusvtes. ν denotes the knematc vscosty [m /s], equal to µ /ρ, the dynamc vscosty [N-s/m or kg/s-m] dvded y densty [kg/m 3 ]. One physcal nterpretaton of ν s the dffusvty for momentum. α s the heat dffusvty [m /s], k/ρcp. For free convecton, when convecton s due to uoyancy assocated wth the temperature dstruton, the velocty s unknown. In ths case the Nusselt numer s typcally gven as a functon of the Raylegh numer Ra gβ L 3 /να. o avod amguty n the choce of the length parameter, frequently Nu, Re and Ra are wrtten wth the proper length parameter as a suscrpt. For example, Nu D, Re D, Ra D use the dameter D for the length parameter L n ther defntons. As a general rule, flud propertes can vary sgnfcantly etween the surface and the flud nteror. A short lst of the most mportant correlatons are gven elow as examples and for the convenence of students. More complete lsts can e found n dedcated textooks. hese are often dvded nto groups or chapters for nternal forced convecton, external forced convecton, and free convecton. Sample flud propertes requred for these calculatons are gven n ale 5. a. urulent Flow nsde Crcular ues hs s an example of nternal forced convecton. A frequently cted correlaton s Nu D = 0.03 ReD. Pr / for ReD > 0, L / D > 0, 0.7 < Pr < 60 (9) In ths equaton, the Nusselt and Reynolds numers are ased on the nternal ppe dameter, and the velocty n the Reynolds numer s the average flud velocty (suscrpt af) over the cross-sectonal area of the ppe. hd UaveD Nu D ; ReD (30) k ν U af c A c 4 Volumetrc flow rate Mass flow rate uda = = (3) A A ρa c he defnton of the heat transfer coeffcent, and the computaton of heat transfer, also make use of the average flud (suscrpt af) temperature: q w af ( ) h (3) U w A af c af A c uda For many prolems the flud propertes may change sgnfcantly etween the wall temperature and the flud temperature. Some correlatons gve specfc remedes to account for ths change. A general procedure, sutale for modest varatons of property or when etter nformaton s not avalale, s to evaluate the propertes at the flm temperature, taken to e the md-pont etween the wall temperature and the flud temperature: c (33)

Principles of Food and Bioprocess Engineering (FS 231) Solutions to Example Problems on Heat Transfer

Principles of Food and Bioprocess Engineering (FS 231) Solutions to Example Problems on Heat Transfer Prncples of Food and Boprocess Engneerng (FS 31) Solutons to Example Problems on Heat Transfer 1. We start wth Fourer s law of heat conducton: Q = k A ( T/ x) Rearrangng, we get: Q/A = k ( T/ x) Here,

More information

Thermal-Fluids I. Chapter 18 Transient heat conduction. Dr. Primal Fernando Ph: (850)

Thermal-Fluids I. Chapter 18 Transient heat conduction. Dr. Primal Fernando Ph: (850) hermal-fluds I Chapter 18 ransent heat conducton Dr. Prmal Fernando prmal@eng.fsu.edu Ph: (850) 410-6323 1 ransent heat conducton In general, he temperature of a body vares wth tme as well as poston. In

More information

Numerical Transient Heat Conduction Experiment

Numerical Transient Heat Conduction Experiment Numercal ransent Heat Conducton Experment OBJECIVE 1. o demonstrate the basc prncples of conducton heat transfer.. o show how the thermal conductvty of a sold can be measured. 3. o demonstrate the use

More information

Week 9 Chapter 10 Section 1-5

Week 9 Chapter 10 Section 1-5 Week 9 Chapter 10 Secton 1-5 Rotaton Rgd Object A rgd object s one that s nondeformable The relatve locatons of all partcles makng up the object reman constant All real objects are deformable to some extent,

More information

Lab 2e Thermal System Response and Effective Heat Transfer Coefficient

Lab 2e Thermal System Response and Effective Heat Transfer Coefficient 58:080 Expermental Engneerng 1 OBJECTIVE Lab 2e Thermal System Response and Effectve Heat Transfer Coeffcent Warnng: though the experment has educatonal objectves (to learn about bolng heat transfer, etc.),

More information

Numerical Heat and Mass Transfer

Numerical Heat and Mass Transfer Master degree n Mechancal Engneerng Numercal Heat and Mass Transfer 06-Fnte-Dfference Method (One-dmensonal, steady state heat conducton) Fausto Arpno f.arpno@uncas.t Introducton Why we use models and

More information

Introduction to Vapor/Liquid Equilibrium, part 2. Raoult s Law:

Introduction to Vapor/Liquid Equilibrium, part 2. Raoult s Law: CE304, Sprng 2004 Lecture 4 Introducton to Vapor/Lqud Equlbrum, part 2 Raoult s Law: The smplest model that allows us do VLE calculatons s obtaned when we assume that the vapor phase s an deal gas, and

More information

x yi In chapter 14, we want to perform inference (i.e. calculate confidence intervals and perform tests of significance) in this setting.

x yi In chapter 14, we want to perform inference (i.e. calculate confidence intervals and perform tests of significance) in this setting. The Practce of Statstcs, nd ed. Chapter 14 Inference for Regresson Introducton In chapter 3 we used a least-squares regresson lne (LSRL) to represent a lnear relatonshp etween two quanttatve explanator

More information

Module 1 : The equation of continuity. Lecture 1: Equation of Continuity

Module 1 : The equation of continuity. Lecture 1: Equation of Continuity 1 Module 1 : The equaton of contnuty Lecture 1: Equaton of Contnuty 2 Advanced Heat and Mass Transfer: Modules 1. THE EQUATION OF CONTINUITY : Lectures 1-6 () () () (v) (v) Overall Mass Balance Momentum

More information

Supplementary Notes for Chapter 9 Mixture Thermodynamics

Supplementary Notes for Chapter 9 Mixture Thermodynamics Supplementary Notes for Chapter 9 Mxture Thermodynamcs Key ponts Nne major topcs of Chapter 9 are revewed below: 1. Notaton and operatonal equatons for mxtures 2. PVTN EOSs for mxtures 3. General effects

More information

Section 8.3 Polar Form of Complex Numbers

Section 8.3 Polar Form of Complex Numbers 80 Chapter 8 Secton 8 Polar Form of Complex Numbers From prevous classes, you may have encountered magnary numbers the square roots of negatve numbers and, more generally, complex numbers whch are the

More information

DUE: WEDS FEB 21ST 2018

DUE: WEDS FEB 21ST 2018 HOMEWORK # 1: FINITE DIFFERENCES IN ONE DIMENSION DUE: WEDS FEB 21ST 2018 1. Theory Beam bendng s a classcal engneerng analyss. The tradtonal soluton technque makes smplfyng assumptons such as a constant

More information

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems Numercal Analyss by Dr. Anta Pal Assstant Professor Department of Mathematcs Natonal Insttute of Technology Durgapur Durgapur-713209 emal: anta.bue@gmal.com 1 . Chapter 5 Soluton of System of Lnear Equatons

More information

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X Statstcs 1: Probablty Theory II 37 3 EPECTATION OF SEVERAL RANDOM VARIABLES As n Probablty Theory I, the nterest n most stuatons les not on the actual dstrbuton of a random vector, but rather on a number

More information

Week3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity

Week3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity Week3, Chapter 4 Moton n Two Dmensons Lecture Quz A partcle confned to moton along the x axs moves wth constant acceleraton from x =.0 m to x = 8.0 m durng a 1-s tme nterval. The velocty of the partcle

More information

CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE

CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE Analytcal soluton s usually not possble when exctaton vares arbtrarly wth tme or f the system s nonlnear. Such problems can be solved by numercal tmesteppng

More information

Lecture 12: Discrete Laplacian

Lecture 12: Discrete Laplacian Lecture 12: Dscrete Laplacan Scrbe: Tanye Lu Our goal s to come up wth a dscrete verson of Laplacan operator for trangulated surfaces, so that we can use t n practce to solve related problems We are mostly

More information

ONE DIMENSIONAL TRIANGULAR FIN EXPERIMENT. Technical Advisor: Dr. D.C. Look, Jr. Version: 11/03/00

ONE DIMENSIONAL TRIANGULAR FIN EXPERIMENT. Technical Advisor: Dr. D.C. Look, Jr. Version: 11/03/00 ONE IMENSIONAL TRIANGULAR FIN EXPERIMENT Techncal Advsor: r..c. Look, Jr. Verson: /3/ 7. GENERAL OJECTIVES a) To understand a one-dmensonal epermental appromaton. b) To understand the art of epermental

More information

MATH 5630: Discrete Time-Space Model Hung Phan, UMass Lowell March 1, 2018

MATH 5630: Discrete Time-Space Model Hung Phan, UMass Lowell March 1, 2018 MATH 5630: Dscrete Tme-Space Model Hung Phan, UMass Lowell March, 08 Newton s Law of Coolng Consder the coolng of a well strred coffee so that the temperature does not depend on space Newton s law of collng

More information

Open Systems: Chemical Potential and Partial Molar Quantities Chemical Potential

Open Systems: Chemical Potential and Partial Molar Quantities Chemical Potential Open Systems: Chemcal Potental and Partal Molar Quanttes Chemcal Potental For closed systems, we have derved the followng relatonshps: du = TdS pdv dh = TdS + Vdp da = SdT pdv dg = VdP SdT For open systems,

More information

Global Sensitivity. Tuesday 20 th February, 2018

Global Sensitivity. Tuesday 20 th February, 2018 Global Senstvty Tuesday 2 th February, 28 ) Local Senstvty Most senstvty analyses [] are based on local estmates of senstvty, typcally by expandng the response n a Taylor seres about some specfc values

More information

ELASTIC WAVE PROPAGATION IN A CONTINUOUS MEDIUM

ELASTIC WAVE PROPAGATION IN A CONTINUOUS MEDIUM ELASTIC WAVE PROPAGATION IN A CONTINUOUS MEDIUM An elastc wave s a deformaton of the body that travels throughout the body n all drectons. We can examne the deformaton over a perod of tme by fxng our look

More information

Structure and Drive Paul A. Jensen Copyright July 20, 2003

Structure and Drive Paul A. Jensen Copyright July 20, 2003 Structure and Drve Paul A. Jensen Copyrght July 20, 2003 A system s made up of several operatons wth flow passng between them. The structure of the system descrbes the flow paths from nputs to outputs.

More information

NUMERICAL DIFFERENTIATION

NUMERICAL DIFFERENTIATION NUMERICAL DIFFERENTIATION 1 Introducton Dfferentaton s a method to compute the rate at whch a dependent output y changes wth respect to the change n the ndependent nput x. Ths rate of change s called the

More information

where I = (n x n) diagonal identity matrix with diagonal elements = 1 and off-diagonal elements = 0; and σ 2 e = variance of (Y X).

where I = (n x n) diagonal identity matrix with diagonal elements = 1 and off-diagonal elements = 0; and σ 2 e = variance of (Y X). 11.4.1 Estmaton of Multple Regresson Coeffcents In multple lnear regresson, we essentally solve n equatons for the p unnown parameters. hus n must e equal to or greater than p and n practce n should e

More information

More metrics on cartesian products

More metrics on cartesian products More metrcs on cartesan products If (X, d ) are metrc spaces for 1 n, then n Secton II4 of the lecture notes we defned three metrcs on X whose underlyng topologes are the product topology The purpose of

More information

Foundations of Arithmetic

Foundations of Arithmetic Foundatons of Arthmetc Notaton We shall denote the sum and product of numbers n the usual notaton as a 2 + a 2 + a 3 + + a = a, a 1 a 2 a 3 a = a The notaton a b means a dvdes b,.e. ac = b where c s an

More information

Implicit Integration Henyey Method

Implicit Integration Henyey Method Implct Integraton Henyey Method In realstc stellar evoluton codes nstead of a drect ntegraton usng for example the Runge-Kutta method one employs an teratve mplct technque. Ths s because the structure

More information

Solution Thermodynamics

Solution Thermodynamics Soluton hermodynamcs usng Wagner Notaton by Stanley. Howard Department of aterals and etallurgcal Engneerng South Dakota School of nes and echnology Rapd Cty, SD 57701 January 7, 001 Soluton hermodynamcs

More information

Physics 5153 Classical Mechanics. D Alembert s Principle and The Lagrangian-1

Physics 5153 Classical Mechanics. D Alembert s Principle and The Lagrangian-1 P. Guterrez Physcs 5153 Classcal Mechancs D Alembert s Prncple and The Lagrangan 1 Introducton The prncple of vrtual work provdes a method of solvng problems of statc equlbrum wthout havng to consder the

More information

Transfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system

Transfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system Transfer Functons Convenent representaton of a lnear, dynamc model. A transfer functon (TF) relates one nput and one output: x t X s y t system Y s The followng termnology s used: x y nput output forcng

More information

χ x B E (c) Figure 2.1.1: (a) a material particle in a body, (b) a place in space, (c) a configuration of the body

χ x B E (c) Figure 2.1.1: (a) a material particle in a body, (b) a place in space, (c) a configuration of the body Secton.. Moton.. The Materal Body and Moton hyscal materals n the real world are modeled usng an abstract mathematcal entty called a body. Ths body conssts of an nfnte number of materal partcles. Shown

More information

Thermodynamics General

Thermodynamics General Thermodynamcs General Lecture 1 Lecture 1 s devoted to establshng buldng blocks for dscussng thermodynamcs. In addton, the equaton of state wll be establshed. I. Buldng blocks for thermodynamcs A. Dmensons,

More information

One-sided finite-difference approximations suitable for use with Richardson extrapolation

One-sided finite-difference approximations suitable for use with Richardson extrapolation Journal of Computatonal Physcs 219 (2006) 13 20 Short note One-sded fnte-dfference approxmatons sutable for use wth Rchardson extrapolaton Kumar Rahul, S.N. Bhattacharyya * Department of Mechancal Engneerng,

More information

Temperature. Chapter Heat Engine

Temperature. Chapter Heat Engine Chapter 3 Temperature In prevous chapters of these notes we ntroduced the Prncple of Maxmum ntropy as a technque for estmatng probablty dstrbutons consstent wth constrants. In Chapter 9 we dscussed the

More information

The Finite Element Method

The Finite Element Method The Fnte Element Method GENERAL INTRODUCTION Read: Chapters 1 and 2 CONTENTS Engneerng and analyss Smulaton of a physcal process Examples mathematcal model development Approxmate solutons and methods of

More information

Inductance Calculation for Conductors of Arbitrary Shape

Inductance Calculation for Conductors of Arbitrary Shape CRYO/02/028 Aprl 5, 2002 Inductance Calculaton for Conductors of Arbtrary Shape L. Bottura Dstrbuton: Internal Summary In ths note we descrbe a method for the numercal calculaton of nductances among conductors

More information

Chapter 11: Simple Linear Regression and Correlation

Chapter 11: Simple Linear Regression and Correlation Chapter 11: Smple Lnear Regresson and Correlaton 11-1 Emprcal Models 11-2 Smple Lnear Regresson 11-3 Propertes of the Least Squares Estmators 11-4 Hypothess Test n Smple Lnear Regresson 11-4.1 Use of t-tests

More information

FREQUENCY DISTRIBUTIONS Page 1 of The idea of a frequency distribution for sets of observations will be introduced,

FREQUENCY DISTRIBUTIONS Page 1 of The idea of a frequency distribution for sets of observations will be introduced, FREQUENCY DISTRIBUTIONS Page 1 of 6 I. Introducton 1. The dea of a frequency dstrbuton for sets of observatons wll be ntroduced, together wth some of the mechancs for constructng dstrbutons of data. Then

More information

Mathematical Preparations

Mathematical Preparations 1 Introducton Mathematcal Preparatons The theory of relatvty was developed to explan experments whch studed the propagaton of electromagnetc radaton n movng coordnate systems. Wthn expermental error the

More information

Physics 3 (PHYF144) Chap 2: Heat and the First Law of Thermodynamics System. Quantity Positive Negative

Physics 3 (PHYF144) Chap 2: Heat and the First Law of Thermodynamics System. Quantity Positive Negative Physcs (PHYF hap : Heat and the Frst aw of hermodynamcs -. Work and Heat n hermodynamc Processes A thermodynamc system s a system that may exchange energy wth ts surroundngs by means of heat and work.

More information

MMA and GCMMA two methods for nonlinear optimization

MMA and GCMMA two methods for nonlinear optimization MMA and GCMMA two methods for nonlnear optmzaton Krster Svanberg Optmzaton and Systems Theory, KTH, Stockholm, Sweden. krlle@math.kth.se Ths note descrbes the algorthms used n the author s 2007 mplementatons

More information

STAT 309: MATHEMATICAL COMPUTATIONS I FALL 2018 LECTURE 16

STAT 309: MATHEMATICAL COMPUTATIONS I FALL 2018 LECTURE 16 STAT 39: MATHEMATICAL COMPUTATIONS I FALL 218 LECTURE 16 1 why teratve methods f we have a lnear system Ax = b where A s very, very large but s ether sparse or structured (eg, banded, Toepltz, banded plus

More information

DETERMINATION OF TEMPERATURE DISTRIBUTION FOR ANNULAR FINS WITH TEMPERATURE DEPENDENT THERMAL CONDUCTIVITY BY HPM

DETERMINATION OF TEMPERATURE DISTRIBUTION FOR ANNULAR FINS WITH TEMPERATURE DEPENDENT THERMAL CONDUCTIVITY BY HPM Ganj, Z. Z., et al.: Determnaton of Temperature Dstrbuton for S111 DETERMINATION OF TEMPERATURE DISTRIBUTION FOR ANNULAR FINS WITH TEMPERATURE DEPENDENT THERMAL CONDUCTIVITY BY HPM by Davood Domr GANJI

More information

CHAPTER 14 GENERAL PERTURBATION THEORY

CHAPTER 14 GENERAL PERTURBATION THEORY CHAPTER 4 GENERAL PERTURBATION THEORY 4 Introducton A partcle n orbt around a pont mass or a sphercally symmetrc mass dstrbuton s movng n a gravtatonal potental of the form GM / r In ths potental t moves

More information

Module 3: Element Properties Lecture 1: Natural Coordinates

Module 3: Element Properties Lecture 1: Natural Coordinates Module 3: Element Propertes Lecture : Natural Coordnates Natural coordnate system s bascally a local coordnate system whch allows the specfcaton of a pont wthn the element by a set of dmensonless numbers

More information

PHYS 705: Classical Mechanics. Calculus of Variations II

PHYS 705: Classical Mechanics. Calculus of Variations II 1 PHYS 705: Classcal Mechancs Calculus of Varatons II 2 Calculus of Varatons: Generalzaton (no constrant yet) Suppose now that F depends on several dependent varables : We need to fnd such that has a statonary

More information

Physics 53. Rotational Motion 3. Sir, I have found you an argument, but I am not obliged to find you an understanding.

Physics 53. Rotational Motion 3. Sir, I have found you an argument, but I am not obliged to find you an understanding. Physcs 53 Rotatonal Moton 3 Sr, I have found you an argument, but I am not oblged to fnd you an understandng. Samuel Johnson Angular momentum Wth respect to rotatonal moton of a body, moment of nerta plays

More information

Some Comments on Accelerating Convergence of Iterative Sequences Using Direct Inversion of the Iterative Subspace (DIIS)

Some Comments on Accelerating Convergence of Iterative Sequences Using Direct Inversion of the Iterative Subspace (DIIS) Some Comments on Acceleratng Convergence of Iteratve Sequences Usng Drect Inverson of the Iteratve Subspace (DIIS) C. Davd Sherrll School of Chemstry and Bochemstry Georga Insttute of Technology May 1998

More information

n α j x j = 0 j=1 has a nontrivial solution. Here A is the n k matrix whose jth column is the vector for all t j=0

n α j x j = 0 j=1 has a nontrivial solution. Here A is the n k matrix whose jth column is the vector for all t j=0 MODULE 2 Topcs: Lnear ndependence, bass and dmenson We have seen that f n a set of vectors one vector s a lnear combnaton of the remanng vectors n the set then the span of the set s unchanged f that vector

More information

Difference Equations

Difference Equations Dfference Equatons c Jan Vrbk 1 Bascs Suppose a sequence of numbers, say a 0,a 1,a,a 3,... s defned by a certan general relatonshp between, say, three consecutve values of the sequence, e.g. a + +3a +1

More information

Module 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur

Module 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur Module 3 LOSSY IMAGE COMPRESSION SYSTEMS Verson ECE IIT, Kharagpur Lesson 6 Theory of Quantzaton Verson ECE IIT, Kharagpur Instructonal Objectves At the end of ths lesson, the students should be able to:

More information

THE SMOOTH INDENTATION OF A CYLINDRICAL INDENTOR AND ANGLE-PLY LAMINATES

THE SMOOTH INDENTATION OF A CYLINDRICAL INDENTOR AND ANGLE-PLY LAMINATES THE SMOOTH INDENTATION OF A CYLINDRICAL INDENTOR AND ANGLE-PLY LAMINATES W. C. Lao Department of Cvl Engneerng, Feng Cha Unverst 00 Wen Hwa Rd, Tachung, Tawan SUMMARY: The ndentaton etween clndrcal ndentor

More information

Inner Product. Euclidean Space. Orthonormal Basis. Orthogonal

Inner Product. Euclidean Space. Orthonormal Basis. Orthogonal Inner Product Defnton 1 () A Eucldean space s a fnte-dmensonal vector space over the reals R, wth an nner product,. Defnton 2 (Inner Product) An nner product, on a real vector space X s a symmetrc, blnear,

More information

Lecture 5.8 Flux Vector Splitting

Lecture 5.8 Flux Vector Splitting Lecture 5.8 Flux Vector Splttng 1 Flux Vector Splttng The vector E n (5.7.) can be rewrtten as E = AU (5.8.1) (wth A as gven n (5.7.4) or (5.7.6) ) whenever, the equaton of state s of the separable form

More information

Lecture Note 3. Eshelby s Inclusion II

Lecture Note 3. Eshelby s Inclusion II ME340B Elastcty of Mcroscopc Structures Stanford Unversty Wnter 004 Lecture Note 3. Eshelby s Incluson II Chrs Wenberger and We Ca c All rghts reserved January 6, 004 Contents 1 Incluson energy n an nfnte

More information

Robert Eisberg Second edition CH 09 Multielectron atoms ground states and x-ray excitations

Robert Eisberg Second edition CH 09 Multielectron atoms ground states and x-ray excitations Quantum Physcs 量 理 Robert Esberg Second edton CH 09 Multelectron atoms ground states and x-ray exctatons 9-01 By gong through the procedure ndcated n the text, develop the tme-ndependent Schroednger equaton

More information

NON-CENTRAL 7-POINT FORMULA IN THE METHOD OF LINES FOR PARABOLIC AND BURGERS' EQUATIONS

NON-CENTRAL 7-POINT FORMULA IN THE METHOD OF LINES FOR PARABOLIC AND BURGERS' EQUATIONS IJRRAS 8 (3 September 011 www.arpapress.com/volumes/vol8issue3/ijrras_8_3_08.pdf NON-CENTRAL 7-POINT FORMULA IN THE METHOD OF LINES FOR PARABOLIC AND BURGERS' EQUATIONS H.O. Bakodah Dept. of Mathematc

More information

Econ107 Applied Econometrics Topic 3: Classical Model (Studenmund, Chapter 4)

Econ107 Applied Econometrics Topic 3: Classical Model (Studenmund, Chapter 4) I. Classcal Assumptons Econ7 Appled Econometrcs Topc 3: Classcal Model (Studenmund, Chapter 4) We have defned OLS and studed some algebrac propertes of OLS. In ths topc we wll study statstcal propertes

More information

Note 10. Modeling and Simulation of Dynamic Systems

Note 10. Modeling and Simulation of Dynamic Systems Lecture Notes of ME 475: Introducton to Mechatroncs Note 0 Modelng and Smulaton of Dynamc Systems Department of Mechancal Engneerng, Unversty Of Saskatchewan, 57 Campus Drve, Saskatoon, SK S7N 5A9, Canada

More information

LINEAR REGRESSION ANALYSIS. MODULE IX Lecture Multicollinearity

LINEAR REGRESSION ANALYSIS. MODULE IX Lecture Multicollinearity LINEAR REGRESSION ANALYSIS MODULE IX Lecture - 30 Multcollnearty Dr. Shalabh Department of Mathematcs and Statstcs Indan Insttute of Technology Kanpur 2 Remedes for multcollnearty Varous technques have

More information

Electrical double layer: revisit based on boundary conditions

Electrical double layer: revisit based on boundary conditions Electrcal double layer: revst based on boundary condtons Jong U. Km Department of Electrcal and Computer Engneerng, Texas A&M Unversty College Staton, TX 77843-318, USA Abstract The electrcal double layer

More information

Experiment 1 Mass, volume and density

Experiment 1 Mass, volume and density Experment 1 Mass, volume and densty Purpose 1. Famlarze wth basc measurement tools such as verner calper, mcrometer, and laboratory balance. 2. Learn how to use the concepts of sgnfcant fgures, expermental

More information

Physics 181. Particle Systems

Physics 181. Particle Systems Physcs 181 Partcle Systems Overvew In these notes we dscuss the varables approprate to the descrpton of systems of partcles, ther defntons, ther relatons, and ther conservatons laws. We consder a system

More information

Lectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix

Lectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix Lectures - Week 4 Matrx norms, Condtonng, Vector Spaces, Lnear Independence, Spannng sets and Bass, Null space and Range of a Matrx Matrx Norms Now we turn to assocatng a number to each matrx. We could

More information

Comparison of Regression Lines

Comparison of Regression Lines STATGRAPHICS Rev. 9/13/2013 Comparson of Regresson Lnes Summary... 1 Data Input... 3 Analyss Summary... 4 Plot of Ftted Model... 6 Condtonal Sums of Squares... 6 Analyss Optons... 7 Forecasts... 8 Confdence

More information

Linear Approximation with Regularization and Moving Least Squares

Linear Approximation with Regularization and Moving Least Squares Lnear Approxmaton wth Regularzaton and Movng Least Squares Igor Grešovn May 007 Revson 4.6 (Revson : March 004). 5 4 3 0.5 3 3.5 4 Contents: Lnear Fttng...4. Weghted Least Squares n Functon Approxmaton...

More information

HEAT TRANSFER THROUGH ANNULAR COMPOSITE FINS

HEAT TRANSFER THROUGH ANNULAR COMPOSITE FINS Journal of Mechancal Engneerng and Technology (JMET) Volume 4, Issue 1, Jan-June 2016, pp. 01-10, Artcle ID: JMET_04_01_001 Avalable onlne at http://www.aeme.com/jmet/ssues.asp?jtype=jmet&vtype=4&itype=1

More information

COMPOSITE BEAM WITH WEAK SHEAR CONNECTION SUBJECTED TO THERMAL LOAD

COMPOSITE BEAM WITH WEAK SHEAR CONNECTION SUBJECTED TO THERMAL LOAD COMPOSITE BEAM WITH WEAK SHEAR CONNECTION SUBJECTED TO THERMAL LOAD Ákos Jósef Lengyel, István Ecsed Assstant Lecturer, Professor of Mechancs, Insttute of Appled Mechancs, Unversty of Mskolc, Mskolc-Egyetemváros,

More information

Psychology 282 Lecture #24 Outline Regression Diagnostics: Outliers

Psychology 282 Lecture #24 Outline Regression Diagnostics: Outliers Psychology 282 Lecture #24 Outlne Regresson Dagnostcs: Outlers In an earler lecture we studed the statstcal assumptons underlyng the regresson model, ncludng the followng ponts: Formal statement of assumptons.

More information

ECEN 5005 Crystals, Nanocrystals and Device Applications Class 19 Group Theory For Crystals

ECEN 5005 Crystals, Nanocrystals and Device Applications Class 19 Group Theory For Crystals ECEN 5005 Crystals, Nanocrystals and Devce Applcatons Class 9 Group Theory For Crystals Dee Dagram Radatve Transton Probablty Wgner-Ecart Theorem Selecton Rule Dee Dagram Expermentally determned energy

More information

THE SUMMATION NOTATION Ʃ

THE SUMMATION NOTATION Ʃ Sngle Subscrpt otaton THE SUMMATIO OTATIO Ʃ Most of the calculatons we perform n statstcs are repettve operatons on lsts of numbers. For example, we compute the sum of a set of numbers, or the sum of the

More information

Finite Element Modelling of truss/cable structures

Finite Element Modelling of truss/cable structures Pet Schreurs Endhoven Unversty of echnology Department of Mechancal Engneerng Materals echnology November 3, 214 Fnte Element Modellng of truss/cable structures 1 Fnte Element Analyss of prestressed structures

More information

A PROCEDURE FOR SIMULATING THE NONLINEAR CONDUCTION HEAT TRANSFER IN A BODY WITH TEMPERATURE DEPENDENT THERMAL CONDUCTIVITY.

A PROCEDURE FOR SIMULATING THE NONLINEAR CONDUCTION HEAT TRANSFER IN A BODY WITH TEMPERATURE DEPENDENT THERMAL CONDUCTIVITY. Proceedngs of the th Brazlan Congress of Thermal Scences and Engneerng -- ENCIT 006 Braz. Soc. of Mechancal Scences and Engneerng -- ABCM, Curtba, Brazl,- Dec. 5-8, 006 A PROCEDURE FOR SIMULATING THE NONLINEAR

More information

Integrals and Invariants of Euler-Lagrange Equations

Integrals and Invariants of Euler-Lagrange Equations Lecture 16 Integrals and Invarants of Euler-Lagrange Equatons ME 256 at the Indan Insttute of Scence, Bengaluru Varatonal Methods and Structural Optmzaton G. K. Ananthasuresh Professor, Mechancal Engneerng,

More information

Moments of Inertia. and reminds us of the analogous equation for linear momentum p= mv, which is of the form. The kinetic energy of the body is.

Moments of Inertia. and reminds us of the analogous equation for linear momentum p= mv, which is of the form. The kinetic energy of the body is. Moments of Inerta Suppose a body s movng on a crcular path wth constant speed Let s consder two quanttes: the body s angular momentum L about the center of the crcle, and ts knetc energy T How are these

More information

Errors for Linear Systems

Errors for Linear Systems Errors for Lnear Systems When we solve a lnear system Ax b we often do not know A and b exactly, but have only approxmatons  and ˆb avalable. Then the best thng we can do s to solve ˆx ˆb exactly whch

More information

1 GSW Iterative Techniques for y = Ax

1 GSW Iterative Techniques for y = Ax 1 for y = A I m gong to cheat here. here are a lot of teratve technques that can be used to solve the general case of a set of smultaneous equatons (wrtten n the matr form as y = A), but ths chapter sn

More information

Formal solvers of the RT equation

Formal solvers of the RT equation Formal solvers of the RT equaton Formal RT solvers Runge- Kutta (reference solver) Pskunov N.: 979, Master Thess Long characterstcs (Feautrer scheme) Cannon C.J.: 970, ApJ 6, 55 Short characterstcs (Hermtan

More information

2016 Wiley. Study Session 2: Ethical and Professional Standards Application

2016 Wiley. Study Session 2: Ethical and Professional Standards Application 6 Wley Study Sesson : Ethcal and Professonal Standards Applcaton LESSON : CORRECTION ANALYSIS Readng 9: Correlaton and Regresson LOS 9a: Calculate and nterpret a sample covarance and a sample correlaton

More information

Linear Regression Analysis: Terminology and Notation

Linear Regression Analysis: Terminology and Notation ECON 35* -- Secton : Basc Concepts of Regresson Analyss (Page ) Lnear Regresson Analyss: Termnology and Notaton Consder the generc verson of the smple (two-varable) lnear regresson model. It s represented

More information

Workshop: Approximating energies and wave functions Quantum aspects of physical chemistry

Workshop: Approximating energies and wave functions Quantum aspects of physical chemistry Workshop: Approxmatng energes and wave functons Quantum aspects of physcal chemstry http://quantum.bu.edu/pltl/6/6.pdf Last updated Thursday, November 7, 25 7:9:5-5: Copyrght 25 Dan Dll (dan@bu.edu) Department

More information

Formulas for the Determinant

Formulas for the Determinant page 224 224 CHAPTER 3 Determnants e t te t e 2t 38 A = e t 2te t e 2t e t te t 2e 2t 39 If 123 A = 345, 456 compute the matrx product A adj(a) What can you conclude about det(a)? For Problems 40 43, use

More information

Kernel Methods and SVMs Extension

Kernel Methods and SVMs Extension Kernel Methods and SVMs Extenson The purpose of ths document s to revew materal covered n Machne Learnng 1 Supervsed Learnng regardng support vector machnes (SVMs). Ths document also provdes a general

More information

Chapter Newton s Method

Chapter Newton s Method Chapter 9. Newton s Method After readng ths chapter, you should be able to:. Understand how Newton s method s dfferent from the Golden Secton Search method. Understand how Newton s method works 3. Solve

More information

Advanced Circuits Topics - Part 1 by Dr. Colton (Fall 2017)

Advanced Circuits Topics - Part 1 by Dr. Colton (Fall 2017) Advanced rcuts Topcs - Part by Dr. olton (Fall 07) Part : Some thngs you should already know from Physcs 0 and 45 These are all thngs that you should have learned n Physcs 0 and/or 45. Ths secton s organzed

More information

Fundamental loop-current method using virtual voltage sources technique for special cases

Fundamental loop-current method using virtual voltage sources technique for special cases Fundamental loop-current method usng vrtual voltage sources technque for specal cases George E. Chatzaraks, 1 Marna D. Tortorel 1 and Anastasos D. Tzolas 1 Electrcal and Electroncs Engneerng Departments,

More information

The Geometry of Logit and Probit

The Geometry of Logit and Probit The Geometry of Logt and Probt Ths short note s meant as a supplement to Chapters and 3 of Spatal Models of Parlamentary Votng and the notaton and reference to fgures n the text below s to those two chapters.

More information

Prof. Dr. I. Nasser Phys 630, T Aug-15 One_dimensional_Ising_Model

Prof. Dr. I. Nasser Phys 630, T Aug-15 One_dimensional_Ising_Model EXACT OE-DIMESIOAL ISIG MODEL The one-dmensonal Isng model conssts of a chan of spns, each spn nteractng only wth ts two nearest neghbors. The smple Isng problem n one dmenson can be solved drectly n several

More information

Indeterminate pin-jointed frames (trusses)

Indeterminate pin-jointed frames (trusses) Indetermnate pn-jonted frames (trusses) Calculaton of member forces usng force method I. Statcal determnacy. The degree of freedom of any truss can be derved as: w= k d a =, where k s the number of all

More information

PHYS 705: Classical Mechanics. Newtonian Mechanics

PHYS 705: Classical Mechanics. Newtonian Mechanics 1 PHYS 705: Classcal Mechancs Newtonan Mechancs Quck Revew of Newtonan Mechancs Basc Descrpton: -An dealzed pont partcle or a system of pont partcles n an nertal reference frame [Rgd bodes (ch. 5 later)]

More information

MODULE 2: Worked-out Problems

MODULE 2: Worked-out Problems MODUE : Worked-out Problems Problem : he steady-state temperature dstrbuton n a one dmensonal wall of thermal conductvty 5W/m and thckness 5 mm s observed to be ( C) abx, where a C, B- c/ m, and x n meters

More information

Negative Binomial Regression

Negative Binomial Regression STATGRAPHICS Rev. 9/16/2013 Negatve Bnomal Regresson Summary... 1 Data Input... 3 Statstcal Model... 3 Analyss Summary... 4 Analyss Optons... 7 Plot of Ftted Model... 8 Observed Versus Predcted... 10 Predctons...

More information

Module 2. Random Processes. Version 2 ECE IIT, Kharagpur

Module 2. Random Processes. Version 2 ECE IIT, Kharagpur Module Random Processes Lesson 6 Functons of Random Varables After readng ths lesson, ou wll learn about cdf of functon of a random varable. Formula for determnng the pdf of a random varable. Let, X be

More information

A Hybrid Variational Iteration Method for Blasius Equation

A Hybrid Variational Iteration Method for Blasius Equation Avalable at http://pvamu.edu/aam Appl. Appl. Math. ISSN: 1932-9466 Vol. 10, Issue 1 (June 2015), pp. 223-229 Applcatons and Appled Mathematcs: An Internatonal Journal (AAM) A Hybrd Varatonal Iteraton Method

More information

CSci 6974 and ECSE 6966 Math. Tech. for Vision, Graphics and Robotics Lecture 21, April 17, 2006 Estimating A Plane Homography

CSci 6974 and ECSE 6966 Math. Tech. for Vision, Graphics and Robotics Lecture 21, April 17, 2006 Estimating A Plane Homography CSc 6974 and ECSE 6966 Math. Tech. for Vson, Graphcs and Robotcs Lecture 21, Aprl 17, 2006 Estmatng A Plane Homography Overvew We contnue wth a dscusson of the major ssues, usng estmaton of plane projectve

More information

Buckingham s pi-theorem

Buckingham s pi-theorem TMA495 Mathematcal modellng 2004 Buckngham s p-theorem Harald Hanche-Olsen hanche@math.ntnu.no Theory Ths note s about physcal quanttes R,...,R n. We lke to measure them n a consstent system of unts, such

More information

AP Physics 1 & 2 Summer Assignment

AP Physics 1 & 2 Summer Assignment AP Physcs 1 & 2 Summer Assgnment AP Physcs 1 requres an exceptonal profcency n algebra, trgonometry, and geometry. It was desgned by a select group of college professors and hgh school scence teachers

More information

Research Article Green s Theorem for Sign Data

Research Article Green s Theorem for Sign Data Internatonal Scholarly Research Network ISRN Appled Mathematcs Volume 2012, Artcle ID 539359, 10 pages do:10.5402/2012/539359 Research Artcle Green s Theorem for Sgn Data Lous M. Houston The Unversty of

More information

EXAMPLES of THEORETICAL PROBLEMS in the COURSE MMV031 HEAT TRANSFER, version 2017

EXAMPLES of THEORETICAL PROBLEMS in the COURSE MMV031 HEAT TRANSFER, version 2017 EXAMPLES of THEORETICAL PROBLEMS n the COURSE MMV03 HEAT TRANSFER, verson 207 a) What s eant by sotropc ateral? b) What s eant by hoogeneous ateral? 2 Defne the theral dffusvty and gve the unts for the

More information