Numerical simulation and experimental study on thermal properties of trailer house composite envelope with vacuum insulation panels

Size: px
Start display at page:

Download "Numerical simulation and experimental study on thermal properties of trailer house composite envelope with vacuum insulation panels"

Transcription

1 Bulgara Chemcal Commucatos, Volume 48, pecal Issue D (pp. 6) 6 Numercal smulato ad permetal study o thermal propertes of traler house composte evelope wth vacuum sulato paels Haju Lou, Akag Ka *, Zhpeg Guo Merchat Mare College, hagha Martme Uversty, hagha, 6, P.R.Cha Receved Jue 5, 6, Revsed eptember 6, 6 Due to dstgushed thermal performace of vacuum sulato paels (VIPs),.e. the thermal coductvty s approxmately 5- tmes lower tha that of tradtoal thermal sulato materal, t has bee wdely appled for eergy coservato purpose, especally as buldg evelope. To research the thermal characterstc of VIPs composte evelope for traler house, the VIPs are employed, based o the clmate characterstcs of the cold zoe, ad three typcal models, amely, the teror adabatc, sadwch ad teror adabatc models are costructed. The physcal ad mathematc models are developed ad the umercal comparatve aalyss of the thermal performace s made uder the lager temperature dfferece codto. Compared amog those costructos wth the same cotuous temperature waves, the dampg factor, the delay tme, the temperature vbrato of teror wall surface, heat trasfer flux ad the thermal brdge are theoretcally aalyzed. The results of the smulato mply that, teror adabatc model of the VIPs composte evelope s the best for the eergy coservato, especally thermal brdge rego, reducto the rage of the teror temperature fluctuato, radato thermal cool sesato ad mprovemet thermal comfort d. The work provdes the theoretcal foudato for the VIPs developmet ad applcato buldg cotracture. Key words: Vacuum sulato paels, Traler house, Composte evelope costructo, Thermal performace, Eergy coservato. INTRODUCTION The developmet of cold regos s mportat for regoal ecoomc, mltary sgfcace ad research value. The traler house ca be the temporary workg ad lvg place for researchers or staff. As the specal outdoor clmate wter, that s, the temperature dfferece betwee teror ad teror ca be up to 6, thermal performace of the buldg evelope s vtal for eergy coservato ad persoal thermal comfort. Excellet adabatc performace of evelope costructo, ot oly ca reduce eergy cosumpto, mprove door thermal comfort, but also ca avod mosture codesato problems of er wall surface []. Due to the dstgushed low thermal coductvty,.e. approxmately 5- tmes lower tha tradtoal thermal sulato materals [--4], Vacuum sulato paels (VIPs), has sgfcat advatages as the adabatc compoet for traler house evelope. The VIPs are already troduced to the market large-scale producto, such as reefer cotaers, cvl buldg evelopes, refrgerato storage room, ce boxes ad so o[5]. ome theoretcal calculatos have bee proposed ad amout of study has bee carred out o the possbltes of VIPs sulated systems. But the To whom all correspodece should be set: E-mal: akag57@6.com reports for the VIPs stallato ad thermal operato system are rare. The objectve of ths paper was to aalyse theoretcally the thermal sulato models, the teral terface temperature, delay tme, thermal erta d, etc., model the traler houses wall structure wth VIPs ad compare the models combed wth the teror temperature varato cold regos [5]. THERMAL PERFORMANCE OF TRAILER HOUE ENVELOPE The evelopes of traler house, cludg oe door pael, three sde paels, oe roof pael, ad oe floor pael, maly used to reduce the heat leakage ad mata the room temperature. Accordg to the thermal comfort d, teror wall surface temperature closed to the door evromet temperature meas the comfortable feelg [6]. However, the teror surface wall temperature maly depeds o the door ar temperature ad the thermal resstace of the wall. Accordg to some relevat provsos, heat trasfer coeffcet of traler house evelope cold rego must be: k.4 W/(m.K), ad temperature dfferece betwee teror surface ad desg ambet temperature must be: t 4.K [7-9]. Too thck wall meas hgh tal vestmet 6 Bulgara Academy of ceces, Uo of Chemsts Bulgara

2 H.J. Lou, et al. : Numercal smulato ad permetal study o thermal propertes... ad trasportato costs, whle too th wall meas eergy cosumpto ad eve mosture codesato. Optmal costructo of the traler house evelope ca ot oly provde comfortable lvg evromet, but ca also reduce eergy cosumpto. I addto, traler house belogs to reusable buldg, whch s beefcal to evrometal protecto, ecoomc. Mmum thckess of traler house evelope costructo The mmum heat trasfer resstace of buldg evelope cold rego should meet the requremets of the GB576-99, Ca be calculated by Eq.(): ( t t ) R m R () [ t] where: R,m s mmum heat trasfer resstace of the evelope, m K/W; t s door desg temperature of the traler house wter, K; t s outdoor desg temperature of the traler house wter, K ; s temperature dfferece correcto factor, =.; s teral surface heat trasfer resstace; R =. m K/W; Δt meas allow error betwee door ar ad teror wall surface, Δt =.5 K. o, R,m =.99 m K/W. Accordg to the desg Code [8], ts heat trasfer resstace should be: R 7.4m K/W.4 () k VIPs ad polyurethae (PU) as traler house evelope costructo of fllg materals, ad the thckess of PU layer ca be calculated by Eq. (): 4 f vp R R R R () R Where: R s the desg teror surface heat trasfer resstace, R =.4 m K/W; f s thermal coductvty of PU, f =. W/(m K); vp s thermal coductvty of VIPs, vp =.7 W/(m K); vp s thckess of VIPs, vp =. m. The teror protectve layers of the traler house evelope are made of steel plate ad galvazed sheet ad the teror protectve layer s made of staless steel plate. All the protectve layers are very th ad the cellet thermal coductors. R ad R are gored the calculato. Combed wth the Eqs. () ad (), the PU layer thckess s mm. I fact, PU layer thckess s 5 mm ths research. f vp The thermal characterstc parameters of traler house evelope costructo VIPs caot be used aloe as the evelope of the traler house, but form of composte paels wth other thermal sulatg materals. The followg parameters should be cofed before the study. () The dampg factor. The dampg factor refers to the teror ar temperature stablty of the traler house evelope, the teror evelope effect by outdoor tegrated temperature or outdoor ar temperature harmoc. The dampg factor s the rato of outdoor tegrated temperature or outdoor ar temperature harmoc ampltude to teror surface temperature harmoc ampltude. For the multlayer evelope, the dampg factor ca be calculated by the Eq. (4) [8]: D Y Y Y v.9e (4) Y Y Y where: ν s the dampg factor of the multlayer evelope; D s thermal erta d of the layer ; h s teror surface thermal covectve coeffcet of the traler house, W/(m K); h s teror surface thermal covectve coeffcet, W/(m K);,,, are heat storage coeffcets of each layer materals from sde to outsde, W/(m K); Y, Y,,Y s surface heat storage coeffcet of each layer materals from sde to outsde, W/(m K). ()The delay tme. The delay tme s the tme dfferece betwee the momet that hghest (or lowest) teror surface temperature harmoc appears ad the momet that the hghest (or lowest) outdoor tegrated temperature or the hghest (or lowest) outdoor ar temperature harmoc appears. It ca be calculated by Eq. (5) (GB576-99): Y (4.5 D arcta arcta ) 5 Y Y (5) where: s the delay tme, h; Y s the heat storage coeffcet of teror surface evelope, W/(m K); Y s heat storage coeffcet of outer surface evelope, W/(m K). () Thermal erta d. Thermal erta d D s a dmesoless d to characterze ts resstace ablty of temperature fluctuatos ad thermal flux fluctuatos. The greater the D value s, the better thermal stablty of evelope s. The D of a sgle materal layer evelope ca be calculated by Eq. (6)[8] : C p D R (6) T

3 H.J. Lou, et al. : Numercal smulato ad permetal study o thermal propertes... Where: R s thermal resstace, m /W; s thermal storage coeffcet, W/(m K); δ s thckess, m; C p s specfc heat at costat pressure, J/(kg.K); ρ s desty, ; s heat coductvty coeffcet, ; T s perod of fluctuatos, s. For multlayer composte layers evelope, the D value ca be calculated by Eq. (7) [8]: W/(mK) kg/m D R (7) (4)The thermal storage coeffcet. The thermal storage coeffcet s the rato of the heat flux ampltude through the layer surface to the surface temperature ampltude. It ca characterze the merts of the materal thermal stablty. The greater the thermal storage coeffcet s, the better thermal stablty s. It's ca be calculated by the Eq. (8)[8]. Aq C p (8) At T where: A q s heat flux wave-ampltude of layer surface; A t s temperature wave-ampltude of layer surface. The types of composte evelope As the thermal coductvty of VIPs s much less tha that of tradtoal thermal sulated materals, the composte evelope of traler house, accordg to VIPs layer locato posto, ca be dvded to three types, that s, teror adabatc (Fgure a), sadwch (Fgure b) ad teror adabatc (Fgure c ). (a) (b) (c) Fg.. The adabatc types of the composte evelope: (a) teror adabatc, (b) sadwch ad(c) teror adabatc. ()- teral staless steel plate; () - VIPs layer; () - H-shaped fxed pece; (4) - PU layer; (5) - teral steel plate. VIPs COMPOITE ENVELOPE CONTRUCTION MODEL Heat trasfer through traler house evelope uder large temperature dfferece cold rego s a complcated usteady process, whch s ot oly affected by the outdoor ar temperature, solar radato, wd speed ad so o, but also relates to thermal coductvty, thermal storage coeffcet, specfc heat at costat pressure, desty ad thermal performace of evelope materal. As the drect calculato for the heat trasfer process traler house evelope s very complcated, the followg ecessary assumptos should be made advace. ()No clearace st betwee each layer; () Physcal parameters of each layer materal does ot chage wth temperature;()igore the fluece of ''H-shape coectg pece" ad heat trasfers oe dmeso way;(4) No teral heat source ad mass trasfer. Physcal model Iteral staless steel plate ad teral steel plate are gored to smplfy the models ad the physcal models are llumated Fgure. The types of composte evelope maly deped o the locato of the VIPs layer. I ths physcal model, the thckess δ vp of VIPs layer s a costat value, ad total thckess δ + δ for polyurethae layer s also a costat value. Whe δ =, the type s teror adabatc. Whle δ =, the type s teror adabatc. Whle δ = δ, the type s sadwch. Fg.. The sketch of traler house VIPs composte evelope. Outdoor temperature The outdoor temperature s a key varable to calculate the heat flux that trasfers from teror to teror. However, the outdoor temperature chages wth tme. I a perod of tme (for ample wth a

4 H.J. Lou, et al. : Numercal smulato ad permetal study o thermal propertes... moth), the dural varato of the temperature ca be thought as a cyclcal fluctuato 4 hours. e (or cose) fucto seres are always take to smplfy temperature fluctuato for calculato practce. The real outdoor temperature fluctuato a certa Chese cold rego oe day of the coldest moth s collected by the atoal meteorologcal stato, ad the fttg curve s show Fgure. Fg.. Actual temperature ad fttg curve the cold rego. Outdoor comprehesve temperature fttg fucto s: T, 47 6.cos( ( 5)) (9) 4 where: T, s the correspodg outdoor temperatures at the momet, K. Mathematcal model As the dmeso of heght ad wdth s much larger tha that of thckess of traler house evelope, o heat source sts ad materals of every layer s uform dvdually, the thermal coducto of the evelope ca be cosdered as oe dmesoal way. Based o Fourer's law, a correspodg usteady dfferetal equato () ca be establshed. T T () C x Where, s tme; x s fte-thckess. Accordg to the cold rego clmate characterstcs, h = 8.7 W/(m K), h = 9. W/(m K). The desg door temperature wter s o C, relatve humdty %. That boudary codto s: T x T x x xl h ( T T ) p T T T 47 6.cos( ( 5)) 4 () Lear fte elemet equato of usteady thermal coducto fucto ca be derved by varable separato method. upposed that door ar temperature s costat, the heat flux, trasferrg through the teror surface s maly used for heat storage at the begg. A perod later, the heat trasfers from the teror surface to the teror surface. Whle the thermal equlbrum s establshed, the teror surface temperature reaches ts maxmum value. For the usteady-state heat trasfer of the evelope, t's teror surface thermal trasfer stregth s: q h( T T( )) () Where: s thermal flux desty through q evelope teral surface, ; s temperature of evelope teror surface, K. the thermal flux desty s made up of two parts, that s, thermal coducto stregth of evelope materal q evelope materal. T ( ) T5 ( ) q q / W/m T ( ) ad thermal storage stregth of q h ( T ( ) T 5 Where: ( )) () dt( ) q Cp (4) d ( ) s average temperature chage dt d K / s amout per ut tme of the materal, Accordg to q q q, Eq.(5) ca be obtaed. h h hh R h R ht ht hht R ( h RD ) T () ( e ) h h hh R h R Where: D D ; R /. (5) Types ad thermal parameters of VIPs composte evelope The three evelopes are costructed accordg to the Fgure. As the thermal resstaces of staless steel plate ad steel plate are much smaller tha that of thermal sulated materals, the staless steel plate ad steel plate are gored the smplfed models ad the followg smulato. The core materal of VIPs s super-fe glass fbre. Ad thermal propertes parameters of thermal sulated materals are show Table.

5 Bulgara Chemcal Commucatos, Volume 48, pecal Issue D (pp. 6) 6 Table. VIPs composte evelope structure. NO. Models Composto (from sde to outsde) Iteror taless steel plate ad teral decorato +CUFF pael + VIPsmm+ PU5mm+steel adabatc plate, galvazed plate ad outer decorato taless steel plate ad teral decorato + PU 75mm+ VIPsmm+ PU 75mm+ steel plate, adwch galvazed plate ad outer decorato Exteror taless steel plate ad teral decorato + PU5mm+ VIPs mm +CUFF pael+ steel adabatc plate, galvazed plate ad outer decorato Table. Thermal propertes parameters of sulated materals. Materals Heat coductvty coeffcet/ W/(mK) Desty/ kg/m pecfc heat capacty / J/(kgK) Heat storage coeffcet 4h / W/(m K) PU / VIPs REULT AND DICUION Comparso of the dampg factor ad the delay tme As metoed above, the dampg factor ad the delay tme of a buldg evelope are all mportat parameters to characterze the teror surface temperature stablty. The dampg factor ad the delay tme of the three kd traler house evelopes are collected Table. Table. The dampg factor ad the delay tme of three traler house evelopes. Thermal The dampg The delay NO. Models erta d factor tme / h D Iteror adabatc adwch Exteror adabatc The cocluso ca be easly made from Table that, the dampg factor of model s the largest oe, followed by that of model, ad that of model s the smallest oe. The chage treds of delay tme are the same wth that of the dampg factor. Uder the same outdoor evromet wave fluctuato codto, the bgger the dampg factor s, the loger the delay tme s, ad the smaller the teral surface temperature fluctuato s, that meas the cellet at terferece ablty of outdoor evromet temperature ad good thermal stablty. o the teror adabatc model, amely Thermal erta d/ the VIPs layer s closed to the teror the evelope structure, s good for the teral surface temperature stablty. Iteror surface temperature fluctuato The teror surface temperature of traler house evelope s oe of the mportat factors of door thermal comfort study. It s also a vtal factor of the mosture codesato o the surface of buldg teral wall surface, especally cold rego. The teral wall surface temperature fluctuatos of three models uder the same codto were umercally aalyzed, ad the smulato curves are posed Fgure 4. Fg. 4. mulato curves of three teral wall surface temperatures. All the teral wall surface temperatures kept pace wth the teral evromet chage ad 6 Bulgara Academy of ceces, Uo of Chemsts Bulgara D

6 H.J. Lou, et al. : Numercal smulato ad permetal study o thermal propertes... appeared maer of se waves, whle the teror temperature was costat. As the thermal erta d s the bggest of the three, the model has the logest delay tme ad the smallest wave ampltude. The wave trough of the model, that s, 9.5K, appeared at about 4: Bejg tme. The wave troughs of models ad are all a lttle lower that that of model, respectvely 9.89K ad 9.5K, eve the dfferece wth teror ar temperature s ot over 4K. Obvously, the teral wall surface of model wll easly mosture codese whle the relatve humdty s up to the dew pot. Takg the door thermal comfort for cosderato, the mea teral wall surface temperature of model, a lttle hgh tha that of models ad, s much closer to the teror costat temperature ad ca reduce the cold feelg of wall radato. Heat trasfer capacty For the usteady thermal process of the traler house evelopes, the tal put heat capacty Q L Q R s always ot equal to the output heat capacty. As the heat storage capacty of the evelopes, resultg the delay trasfer of heat, ad the fluctuato effect of teral temperature, ad Q R Q R > Q L caot be equal to each other all the tme, eve Q L at some momet. But for a cycle terval, the total put heat capacty should be approxmate equal to the output oe, that s, 4 Q d 4 QRd.The relate fucto ca be L pressed as: 4 4 T 4 QL d h h T T d ( ( )) (6) x Total heat trasfer capactes 4 hours of three evelopes are summarzed Table 4. Table 4. Heat trasfer capacty of three evelopes. NO.Models Heat trasfer quatty /4h / kj/m Iteror adabatc adwch 9.6 Exteror adabatc 44. The cocluso ca be made from Table 4 that, eergy trasmsso, that s, output heat capacty of model s the smallest, followed by that of model, ad the last s that of model. o, teror adabatc structure s the best oe for eergy coservato. Local thermal brdge effect I order to ehace the traler house evelopes stregth, the steel compoets, such as beams, reforcg rbs, crutches, etc. are always volved. But they ca chage the temperature dstrbuto at ther locato, causg so called local thermal brdge. Uder the cold rego codto, the local teral surface temperature s much lower tha that of ma teral surface temperature, resultg mosture codesato, eve frost at the local space, reducg thermal comfort ad causg potetal dager. Although the area of the thermal brdge space s small, the heat loss s huge. As thermal brdge spots ad types are varous, the typcal thermal brdge at the beam s selected ths research to smulato ad dscusso. Three dfferet cofguratos dagrams are show Fg. 5a, whch sold le meas model, dotted le, model, dash le dot, model, ad upper left corer area meas door room boudary. Combed wth the thrd boudary codto, smulatos for three models were posed the temperature dstrbuto ad thermal brdge effect. Ad the results were show Fgure 5b,c,d. Wth the posto of VIPs evelopes shftg from the sde to the outsde, the thermal brdge of the beam s becomg more ad more sgfcat. Isothermal treds of model Fgure 5 (b) s getle, ad the local teral surface temperature, the mmum value 9.5K, eve a lttle lower tha the ma teral surface temperature, s ot beyod 4K dfferece wth the teror temperature, that the code requres. Isothermal treds of model (show Fgure 5(c)) ad model (show Fgure 5 (d)) are dstorted, mplyg the thermal brdge effects are obvously. The lowest temperatures of model ad model, respectvely, are 9.6K ad 9.86K, all beyod 4K dfferece. o, uder the large temperature dfferece codto, the teror adabatc type of VIPs traler house evelope s deal for the reducto of eergy loss ad mprovemet of the teror thermal comfort. Takg the temperature dstrbuto charts for cosderato, the mea temperatures of the VIPs layers are also dfferet. For a cycle perod, the mea temperature of model s 87K, s hgher tha that of model, 75K, also hgher tha that of model, 55K. However, VIPs' servce lfe s flueced by ambet temperature. It s helpful to ted the servce lfe f the surroudg temperature s close to the room temperature. o, the model s deal for the traler house evelope. 5

7 H.J. Lou, et al. : Numercal smulato ad permetal study o thermal propertes... (a) Three dfferet evelopes cofguratos. (b) Temperature dstrbuto of model. CONCLUION Three typcal composte evelopes models for traler house, by usg VIPs, that s, teror adabatc, sadwch, teror adabatc, are structured. Ad the thermal characterstcs of the evelopes are theoretcally compared uder the cold rego temperature codto. () Combg wth the three types ad thermal performace cold rego, the dampg factor, the delay tme, the teral wall surface temperature vbrato, ad heat trasfer flux are theoretcally aalyzed. Iteror adabatc model s superor to the others eergy coservato ad door thermal comfort. () The thermal brdge effects of three VIPs composte evelopes are smulated ad theoretcally aalyzed uder the usteady codto. The cocluso ca be gaed that, the teror adabatc type s cellet for eergy coservato o thermal brdge regos ad temperature dfferece decreasg betwee the teral wall surface temperature ad door ar temperature. Meawhle, the teror adabatc evelope ca reduce radato cold feelg, avod local mosture codesato ad mprove thermal comfort d. Ackowledgemet: Ths research s facally supported by the Natural ceces Foudato of hagha, Cha (5ZR499). The authors would also lke to reder thakfuless to Mr. Yag Baotog from Yagzhou Toglee Reefer Cotaer Co., Ltd. for the kd help. (c) Temperature dstrbuto of model. (d) Temperature dstrbuto of model. Fg. 5. Three dfferet evelopes cofgurato ad temperature dstrbuto dagram. REFERENCE. H.H. Wag, Y.Y. Zhua, Togj Uversty(Natural ceces), 8, 64 ().. R. Baetes, B.P. Jelle, J.V. Thue, Eergy ad Buldgs, 4, 47 ().. M. Alam, H. gh, Appled Eergy, 88, 59 ( ) 4. J. Frcke, U. Heema, H.P. Ebert, Vacuum, 8, 68 (8). 5. J. Zhag, Z.L. Huag, Harb Egeerg Uversty,, 56 (9). 6. H.M. L, W.L. J, J. Buldg truct., 5, 9 (4). 7. GB589-5, Desg stadard for eergy effcecy of publc buldgs, Cha Buldg Idustry Press, Bejg, GB576-99, Code for thermal desg of cvl buldgs, Cha Buldg Idustry Press, Bejg, CAN/CA-Z4..-99, Caada tadards Assocato tadards, tructure Requremets for Moble Homes, Caada ( press), 99. 6

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

Block-Based Compact Thermal Modeling of Semiconductor Integrated Circuits

Block-Based Compact Thermal Modeling of Semiconductor Integrated Circuits Block-Based Compact hermal Modelg of Semcoductor Itegrated Crcuts Master s hess Defese Caddate: Jg Ba Commttee Members: Dr. Mg-Cheg Cheg Dr. Daqg Hou Dr. Robert Schllg July 27, 2009 Outle Itroducto Backgroud

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

best estimate (mean) for X uncertainty or error in the measurement (systematic, random or statistical) best

best estimate (mean) for X uncertainty or error in the measurement (systematic, random or statistical) best Error Aalyss Preamble Wheever a measuremet s made, the result followg from that measuremet s always subject to ucertaty The ucertaty ca be reduced by makg several measuremets of the same quatty or by mprovg

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

Lecture 2 - What are component and system reliability and how it can be improved?

Lecture 2 - What are component and system reliability and how it can be improved? Lecture 2 - What are compoet ad system relablty ad how t ca be mproved? Relablty s a measure of the qualty of the product over the log ru. The cocept of relablty s a exteded tme perod over whch the expected

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

MEASURES OF DISPERSION

MEASURES OF DISPERSION MEASURES OF DISPERSION Measure of Cetral Tedecy: Measures of Cetral Tedecy ad Dsperso ) Mathematcal Average: a) Arthmetc mea (A.M.) b) Geometrc mea (G.M.) c) Harmoc mea (H.M.) ) Averages of Posto: a) Meda

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

Lecture 07: Poles and Zeros

Lecture 07: Poles and Zeros Lecture 07: Poles ad Zeros Defto of poles ad zeros The trasfer fucto provdes a bass for determg mportat system respose characterstcs wthout solvg the complete dfferetal equato. As defed, the trasfer fucto

More information

2C09 Design for seismic and climate changes

2C09 Design for seismic and climate changes 2C09 Desg for sesmc ad clmate chages Lecture 08: Sesmc aalyss of elastc MDOF systems Aurel Strata, Poltehca Uversty of Tmsoara 06/04/2017 Europea Erasmus Mudus Master Course Sustaable Costructos uder atural

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

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

Analysis of Variance with Weibull Data

Analysis of Variance with Weibull Data Aalyss of Varace wth Webull Data Lahaa Watthaacheewaul Abstract I statstcal data aalyss by aalyss of varace, the usual basc assumptos are that the model s addtve ad the errors are radomly, depedetly, ad

More information

A NEW LOG-NORMAL DISTRIBUTION

A NEW LOG-NORMAL DISTRIBUTION Joural of Statstcs: Advaces Theory ad Applcatos Volume 6, Number, 06, Pages 93-04 Avalable at http://scetfcadvaces.co. DOI: http://dx.do.org/0.864/jsata_700705 A NEW LOG-NORMAL DISTRIBUTION Departmet of

More information

A New Family of Transformations for Lifetime Data

A New Family of Transformations for Lifetime Data Proceedgs of the World Cogress o Egeerg 4 Vol I, WCE 4, July - 4, 4, Lodo, U.K. A New Famly of Trasformatos for Lfetme Data Lakhaa Watthaacheewakul Abstract A famly of trasformatos s the oe of several

More information

The Mathematical Appendix

The Mathematical Appendix The Mathematcal Appedx Defto A: If ( Λ, Ω, where ( λ λ λ whch the probablty dstrbutos,,..., Defto A. uppose that ( Λ,,..., s a expermet type, the σ-algebra o λ λ λ are defed s deoted by ( (,,...,, σ Ω.

More information

Module 7: Probability and Statistics

Module 7: Probability and Statistics Lecture 4: Goodess of ft tests. Itroducto Module 7: Probablty ad Statstcs I the prevous two lectures, the cocepts, steps ad applcatos of Hypotheses testg were dscussed. Hypotheses testg may be used to

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

The E vs k diagrams are in general a function of the k -space direction in a crystal

The E vs k diagrams are in general a function of the k -space direction in a crystal vs dagram p m m he parameter s called the crystal mometum ad s a parameter that results from applyg Schrödger wave equato to a sgle-crystal lattce. lectros travelg dfferet drectos ecouter dfferet potetal

More information

Summary of the lecture in Biostatistics

Summary of the lecture in Biostatistics Summary of the lecture Bostatstcs Probablty Desty Fucto For a cotuos radom varable, a probablty desty fucto s a fucto such that: 0 dx a b) b a dx A probablty desty fucto provdes a smple descrpto of the

More information

Journal of Chemical and Pharmaceutical Research, 2014, 6(7): Research Article

Journal of Chemical and Pharmaceutical Research, 2014, 6(7): Research Article Avalable ole www.jocpr.com Joural of Chemcal ad Pharmaceutcal Research, 04, 6(7):4-47 Research Artcle ISSN : 0975-7384 CODEN(USA) : JCPRC5 Predcto of CNG automoble owershp by usg the combed model Ku Huag,

More information

Heat-Integrated Distillation Columns -Analysis and Modellingwith. Advanced Distillation as Supporting Subject

Heat-Integrated Distillation Columns -Analysis and Modellingwith. Advanced Distillation as Supporting Subject Norwega Uversty Of Scece ad Techology Faculty of Egeerg ad Techology Uversty of Belgrade Faculty of Mechacal Egeerg Isttute for Eergy Techology The log-term co-operatve project Master Degree Program: Sustaable

More information

FINITE DIFFERENCE METHOD FOR THERMAL ANALYSIS OF PASSIVE SOLAR SYSTEM WITH MASSIVE WALL

FINITE DIFFERENCE METHOD FOR THERMAL ANALYSIS OF PASSIVE SOLAR SYSTEM WITH MASSIVE WALL FINIE DIFFERENCE MEHOD FOR HERMAL ANALYSIS OF PASSIVE SOLAR SYSEM WIH MASSIVE WALL Stako Vl. Shtrakov South - West Uversty Neoft Rlsk, Dept for Computer s systems ad techology, 66 Iva Mhalov Str., 700

More information

A Helmholtz energy equation of state for calculating the thermodynamic properties of fluid mixtures

A Helmholtz energy equation of state for calculating the thermodynamic properties of fluid mixtures A Helmholtz eergy equato of state for calculatg the thermodyamc propertes of flud mxtures Erc W. Lemmo, Reer Tller-Roth Abstract New Approach based o hghly accurate EOS for the pure compoets combed at

More information

Analysis of a Repairable (n-1)-out-of-n: G System with Failure and Repair Times Arbitrarily Distributed

Analysis of a Repairable (n-1)-out-of-n: G System with Failure and Repair Times Arbitrarily Distributed Amerca Joural of Mathematcs ad Statstcs. ; (: -8 DOI:.593/j.ajms.. Aalyss of a Reparable (--out-of-: G System wth Falure ad Repar Tmes Arbtrarly Dstrbuted M. Gherda, M. Boushaba, Departmet of Mathematcs,

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

CHAPTER VI Statistical Analysis of Experimental Data

CHAPTER VI Statistical Analysis of Experimental Data Chapter VI Statstcal Aalyss of Expermetal Data CHAPTER VI Statstcal Aalyss of Expermetal Data Measuremets do ot lead to a uque value. Ths s a result of the multtude of errors (maly radom errors) that ca

More information

f f... f 1 n n (ii) Median : It is the value of the middle-most observation(s).

f f... f 1 n n (ii) Median : It is the value of the middle-most observation(s). CHAPTER STATISTICS Pots to Remember :. Facts or fgures, collected wth a defte pupose, are called Data.. Statstcs s the area of study dealg wth the collecto, presetato, aalyss ad terpretato of data.. The

More information

hp calculators HP 30S Statistics Averages and Standard Deviations Average and Standard Deviation Practice Finding Averages and Standard Deviations

hp calculators HP 30S Statistics Averages and Standard Deviations Average and Standard Deviation Practice Finding Averages and Standard Deviations HP 30S Statstcs Averages ad Stadard Devatos Average ad Stadard Devato Practce Fdg Averages ad Stadard Devatos HP 30S Statstcs Averages ad Stadard Devatos Average ad stadard devato The HP 30S provdes several

More information

UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS

UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS Postpoed exam: ECON430 Statstcs Date of exam: Jauary 0, 0 Tme for exam: 09:00 a.m. :00 oo The problem set covers 5 pages Resources allowed: All wrtte ad prted

More information

Chapter 8. Inferences about More Than Two Population Central Values

Chapter 8. Inferences about More Than Two Population Central Values Chapter 8. Ifereces about More Tha Two Populato Cetral Values Case tudy: Effect of Tmg of the Treatmet of Port-We tas wth Lasers ) To vestgate whether treatmet at a youg age would yeld better results tha

More information

Some Notes on the Probability Space of Statistical Surveys

Some Notes on the Probability Space of Statistical Surveys Metodološk zvezk, Vol. 7, No., 200, 7-2 ome Notes o the Probablty pace of tatstcal urveys George Petrakos Abstract Ths paper troduces a formal presetato of samplg process usg prcples ad cocepts from Probablty

More information

FINITE DIFFERENCE METHOD FOR THERMAL ANALYSIS OF PASSIVE SOLAR SYSTEM WITH MASSIVE WALL

FINITE DIFFERENCE METHOD FOR THERMAL ANALYSIS OF PASSIVE SOLAR SYSTEM WITH MASSIVE WALL FINIE DIFFERENCE MEHOD FOR HERMAL ANALYSIS OF PASSIVE SOLAR SYSEM WIH MASSIVE WALL Stako Vl. Shtrakov, Ato Stolov South - West Uversty Neoft Rlsk, Dept for Computer s systems ad techology, 66 Iva Mhalov

More information

Risk management of hazardous material transportation

Risk management of hazardous material transportation Maagemet of atural Resources, Sustaable Developmet ad Ecologcal azards 393 Rs maagemet of hazardous materal trasportato J. Auguts, E. Uspuras & V. Matuzas Lthuaa Eergy Isttute, Lthuaa Abstract I recet

More information

d dt d d dt dt Also recall that by Taylor series, / 2 (enables use of sin instead of cos-see p.27 of A&F) dsin

d dt d d dt dt Also recall that by Taylor series, / 2 (enables use of sin instead of cos-see p.27 of A&F) dsin Learzato of the Swg Equato We wll cover sectos.5.-.6 ad begg of Secto 3.3 these otes. 1. Sgle mache-fte bus case Cosder a sgle mache coected to a fte bus, as show Fg. 1 below. E y1 V=1./_ Fg. 1 The admttace

More information

Research on SVM Prediction Model Based on Chaos Theory

Research on SVM Prediction Model Based on Chaos Theory Advaced Scece ad Techology Letters Vol.3 (SoftTech 06, pp.59-63 http://dx.do.org/0.457/astl.06.3.3 Research o SVM Predcto Model Based o Chaos Theory Sog Lagog, Wu Hux, Zhag Zezhog 3, College of Iformato

More information

Bounds on the expected entropy and KL-divergence of sampled multinomial distributions. Brandon C. Roy

Bounds on the expected entropy and KL-divergence of sampled multinomial distributions. Brandon C. Roy Bouds o the expected etropy ad KL-dvergece of sampled multomal dstrbutos Brado C. Roy bcroy@meda.mt.edu Orgal: May 18, 2011 Revsed: Jue 6, 2011 Abstract Iformato theoretc quattes calculated from a sampled

More information

Absorption in Solar Atmosphere

Absorption in Solar Atmosphere Absorpto Solar Atmosphere A black body spectrum emtted from solar surface causes exctato processes o atoms the solar atmosphere. Ths tur causes absorpto of characterstc wavelegths correspodg to those atoms

More information

DYNAMIC ANALYSIS OF CONCRETE RECTANGULAR LIQUID STORAGE TANKS

DYNAMIC ANALYSIS OF CONCRETE RECTANGULAR LIQUID STORAGE TANKS The 4 th World Coferece o Earthquake Egeerg October 2-7, 28, Bejg, Cha DYNAMIC ANAYSIS OF CONCRETE RECTANGUAR IQUID STORAGE TANKS J.Z. Che, A.R. Ghaemmagham 2 ad M.R. Kaoush 3 Structural Egeer, C2M I Caada,

More information

Objectives of Multiple Regression

Objectives of Multiple Regression Obectves of Multple Regresso Establsh the lear equato that best predcts values of a depedet varable Y usg more tha oe eplaator varable from a large set of potetal predctors {,,... k }. Fd that subset of

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

Lecture Notes Types of economic variables

Lecture Notes Types of economic variables Lecture Notes 3 1. Types of ecoomc varables () Cotuous varable takes o a cotuum the sample space, such as all pots o a le or all real umbers Example: GDP, Polluto cocetrato, etc. () Dscrete varables fte

More information

ANALYSIS ON THE NATURE OF THE BASIC EQUATIONS IN SYNERGETIC INTER-REPRESENTATION NETWORK

ANALYSIS ON THE NATURE OF THE BASIC EQUATIONS IN SYNERGETIC INTER-REPRESENTATION NETWORK Far East Joural of Appled Mathematcs Volume, Number, 2008, Pages Ths paper s avalable ole at http://www.pphm.com 2008 Pushpa Publshg House ANALYSIS ON THE NATURE OF THE ASI EQUATIONS IN SYNERGETI INTER-REPRESENTATION

More information

Multi Objective Fuzzy Inventory Model with. Demand Dependent Unit Cost and Lead Time. Constraints A Karush Kuhn Tucker Conditions.

Multi Objective Fuzzy Inventory Model with. Demand Dependent Unit Cost and Lead Time. Constraints A Karush Kuhn Tucker Conditions. It. Joural of Math. Aalyss, Vol. 8, 204, o. 4, 87-93 HIKARI Ltd, www.m-hkar.com http://dx.do.org/0.2988/jma.204.30252 Mult Objectve Fuzzy Ivetory Model wth Demad Depedet Ut Cost ad Lead Tme Costrats A

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

Point Estimation: definition of estimators

Point Estimation: definition of estimators Pot Estmato: defto of estmators Pot estmator: ay fucto W (X,..., X ) of a data sample. The exercse of pot estmato s to use partcular fuctos of the data order to estmate certa ukow populato parameters.

More information

Chapter 14 Logistic Regression Models

Chapter 14 Logistic Regression Models Chapter 4 Logstc Regresso Models I the lear regresso model X β + ε, there are two types of varables explaatory varables X, X,, X k ad study varable y These varables ca be measured o a cotuous scale as

More information

is the score of the 1 st student, x

is the score of the 1 st student, x 8 Chapter Collectg, Dsplayg, ad Aalyzg your Data. Descrptve Statstcs Sectos explaed how to choose a sample, how to collect ad orgaze data from the sample, ad how to dsplay your data. I ths secto, you wll

More information

Lecture 7. Confidence Intervals and Hypothesis Tests in the Simple CLR Model

Lecture 7. Confidence Intervals and Hypothesis Tests in the Simple CLR Model Lecture 7. Cofdece Itervals ad Hypothess Tests the Smple CLR Model I lecture 6 we troduced the Classcal Lear Regresso (CLR) model that s the radom expermet of whch the data Y,,, K, are the outcomes. The

More information

2.28 The Wall Street Journal is probably referring to the average number of cubes used per glass measured for some population that they have chosen.

2.28 The Wall Street Journal is probably referring to the average number of cubes used per glass measured for some population that they have chosen. .5 x 54.5 a. x 7. 786 7 b. The raked observatos are: 7.4, 7.5, 7.7, 7.8, 7.9, 8.0, 8.. Sce the sample sze 7 s odd, the meda s the (+)/ 4 th raked observato, or meda 7.8 c. The cosumer would more lkely

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

Module 1 : The equation of continuity. Lecture 5: Conservation of Mass for each species. & Fick s Law

Module 1 : The equation of continuity. Lecture 5: Conservation of Mass for each species. & Fick s Law Module : The equato of cotuty Lecture 5: Coservato of Mass for each speces & Fck s Law NPTEL, IIT Kharagpur, Prof. Sakat Chakraborty, Departmet of Chemcal Egeerg 2 Basc Deftos I Mass Trasfer, we usually

More information

Department of Agricultural Economics. PhD Qualifier Examination. August 2011

Department of Agricultural Economics. PhD Qualifier Examination. August 2011 Departmet of Agrcultural Ecoomcs PhD Qualfer Examato August 0 Istructos: The exam cossts of sx questos You must aswer all questos If you eed a assumpto to complete a questo, state the assumpto clearly

More information

6.4.5 MOS capacitance-voltage analysis

6.4.5 MOS capacitance-voltage analysis 6.4.5 MOS capactace-voltage aalyss arous parameters of a MOS devce ca be determed from the - characterstcs.. Type of substrate dopg. Isulator capactace = /d sulator thckess d 3. The mmum depleto capactace

More information

RESEARCH ON THE RADIANT CEILING COOLING SYSTEM

RESEARCH ON THE RADIANT CEILING COOLING SYSTEM RESEARCH ON THE RADIANT CEILING COOLING SYSTEM Y Ya,*, ZX 2 a W Wag 3 Departmet o Urba Costructo Egeerg, Bejg Isttute o Cvl Egeerg a Archtecture Bejg 00044, Cha 2 Cha Natoal Real Developmet Group Ne Techology

More information

ENGI 3423 Simple Linear Regression Page 12-01

ENGI 3423 Simple Linear Regression Page 12-01 ENGI 343 mple Lear Regresso Page - mple Lear Regresso ometmes a expermet s set up where the expermeter has cotrol over the values of oe or more varables X ad measures the resultg values of aother varable

More information

MODELING AND OPTIMIZATION OF TWO-LAYER POROUS ASPHALT ROADS ABSTRACT 1- INTRODUCTION

MODELING AND OPTIMIZATION OF TWO-LAYER POROUS ASPHALT ROADS ABSTRACT 1- INTRODUCTION 143.DOC/1 MODELING AND OPTIMIZATION OF TWO-LAYER POROUS ASPHALT ROADS A. KUIJPERS, G. VAN BLOKLAND M+P Nose & Vbrato Cosultats, Brustesgel 3, NL-531 AD's, Hertogebosch, Netherlads Tél.: +31 73 648851 /

More information

EECE 301 Signals & Systems

EECE 301 Signals & Systems EECE 01 Sgals & Systems Prof. Mark Fowler Note Set #9 Computg D-T Covoluto Readg Assgmet: Secto. of Kame ad Heck 1/ Course Flow Dagram The arrows here show coceptual flow betwee deas. Note the parallel

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

Analysis of Lagrange Interpolation Formula

Analysis of Lagrange Interpolation Formula P IJISET - Iteratoal Joural of Iovatve Scece, Egeerg & Techology, Vol. Issue, December 4. www.jset.com ISS 348 7968 Aalyss of Lagrage Iterpolato Formula Vjay Dahya PDepartmet of MathematcsMaharaja Surajmal

More information

STA302/1001-Fall 2008 Midterm Test October 21, 2008

STA302/1001-Fall 2008 Midterm Test October 21, 2008 STA3/-Fall 8 Mdterm Test October, 8 Last Name: Frst Name: Studet Number: Erolled (Crcle oe) STA3 STA INSTRUCTIONS Tme allowed: hour 45 mutes Ads allowed: A o-programmable calculator A table of values from

More information

LECTURE - 4 SIMPLE RANDOM SAMPLING DR. SHALABH DEPARTMENT OF MATHEMATICS AND STATISTICS INDIAN INSTITUTE OF TECHNOLOGY KANPUR

LECTURE - 4 SIMPLE RANDOM SAMPLING DR. SHALABH DEPARTMENT OF MATHEMATICS AND STATISTICS INDIAN INSTITUTE OF TECHNOLOGY KANPUR amplg Theory MODULE II LECTURE - 4 IMPLE RADOM AMPLIG DR. HALABH DEPARTMET OF MATHEMATIC AD TATITIC IDIA ITITUTE OF TECHOLOGY KAPUR Estmato of populato mea ad populato varace Oe of the ma objectves after

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

A Study of the Reproducibility of Measurements with HUR Leg Extension/Curl Research Line

A Study of the Reproducibility of Measurements with HUR Leg Extension/Curl Research Line HUR Techcal Report 000--9 verso.05 / Frak Borg (borgbros@ett.f) A Study of the Reproducblty of Measuremets wth HUR Leg Eteso/Curl Research Le A mportat property of measuremets s that the results should

More information

Bayes Estimator for Exponential Distribution with Extension of Jeffery Prior Information

Bayes Estimator for Exponential Distribution with Extension of Jeffery Prior Information Malaysa Joural of Mathematcal Sceces (): 97- (9) Bayes Estmator for Expoetal Dstrbuto wth Exteso of Jeffery Pror Iformato Hadeel Salm Al-Kutub ad Noor Akma Ibrahm Isttute for Mathematcal Research, Uverst

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

Centroids & Moments of Inertia of Beam Sections

Centroids & Moments of Inertia of Beam Sections RCH 614 Note Set 8 S017ab Cetrods & Momets of erta of Beam Sectos Notato: b C d d d Fz h c Jo L O Q Q = ame for area = ame for a (base) wdth = desgato for chael secto = ame for cetrod = calculus smbol

More information

A Robust Total Least Mean Square Algorithm For Nonlinear Adaptive Filter

A Robust Total Least Mean Square Algorithm For Nonlinear Adaptive Filter A Robust otal east Mea Square Algorthm For Nolear Adaptve Flter Ruxua We School of Electroc ad Iformato Egeerg X'a Jaotog Uversty X'a 70049, P.R. Cha rxwe@chare.com Chogzhao Ha, azhe u School of Electroc

More information

Mean is only appropriate for interval or ratio scales, not ordinal or nominal.

Mean is only appropriate for interval or ratio scales, not ordinal or nominal. Mea Same as ordary average Sum all the data values ad dvde by the sample sze. x = ( x + x +... + x Usg summato otato, we wrte ths as x = x = x = = ) x Mea s oly approprate for terval or rato scales, ot

More information

Comparison of Analytical and Numerical Results in Modal Analysis of Multispan Continuous Beams with LS-DYNA

Comparison of Analytical and Numerical Results in Modal Analysis of Multispan Continuous Beams with LS-DYNA th Iteratoal S-N Users oferece Smulato Techology omparso of alytcal ad Numercal Results Modal alyss of Multspa otuous eams wth S-N bht Mahapatra ad vk hatteree etral Mechacal Egeerg Research Isttute, urgapur

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

PROJECTION PROBLEM FOR REGULAR POLYGONS

PROJECTION PROBLEM FOR REGULAR POLYGONS Joural of Mathematcal Sceces: Advaces ad Applcatos Volume, Number, 008, Pages 95-50 PROJECTION PROBLEM FOR REGULAR POLYGONS College of Scece Bejg Forestry Uversty Bejg 0008 P. R. Cha e-mal: sl@bjfu.edu.c

More information

Statistics MINITAB - Lab 5

Statistics MINITAB - Lab 5 Statstcs 10010 MINITAB - Lab 5 PART I: The Correlato Coeffcet Qute ofte statstcs we are preseted wth data that suggests that a lear relatoshp exsts betwee two varables. For example the plot below s of

More information

Long blade vibration model for turbine-generator shafts torsional vibration analysis

Long blade vibration model for turbine-generator shafts torsional vibration analysis Avalable ole www.ocpr.co Joural of Checal ad Pharaceutcal Research, 05, 7(3):39-333 Research Artcle ISSN : 0975-7384 CODEN(USA) : JCPRC5 Log blade vbrato odel for turbe-geerator shafts torsoal vbrato aalyss

More information

Analysis of System Performance IN2072 Chapter 5 Analysis of Non Markov Systems

Analysis of System Performance IN2072 Chapter 5 Analysis of Non Markov Systems Char for Network Archtectures ad Servces Prof. Carle Departmet of Computer Scece U Müche Aalyss of System Performace IN2072 Chapter 5 Aalyss of No Markov Systems Dr. Alexader Kle Prof. Dr.-Ig. Georg Carle

More information

Laboratory I.10 It All Adds Up

Laboratory I.10 It All Adds Up Laboratory I. It All Adds Up Goals The studet wll work wth Rema sums ad evaluate them usg Derve. The studet wll see applcatos of tegrals as accumulatos of chages. The studet wll revew curve fttg sklls.

More information

A New Method for Decision Making Based on Soft Matrix Theory

A New Method for Decision Making Based on Soft Matrix Theory Joural of Scetfc esearch & eports 3(5): 0-7, 04; rtcle o. JS.04.5.00 SCIENCEDOMIN teratoal www.scecedoma.org New Method for Decso Mag Based o Soft Matrx Theory Zhmg Zhag * College of Mathematcs ad Computer

More information

Chapter 4 (Part 1): Non-Parametric Classification (Sections ) Pattern Classification 4.3) Announcements

Chapter 4 (Part 1): Non-Parametric Classification (Sections ) Pattern Classification 4.3) Announcements Aoucemets No-Parametrc Desty Estmato Techques HW assged Most of ths lecture was o the blacboard. These sldes cover the same materal as preseted DHS Bometrcs CSE 90-a Lecture 7 CSE90a Fall 06 CSE90a Fall

More information

Lecture 3. Sampling, sampling distributions, and parameter estimation

Lecture 3. Sampling, sampling distributions, and parameter estimation Lecture 3 Samplg, samplg dstrbutos, ad parameter estmato Samplg Defto Populato s defed as the collecto of all the possble observatos of terest. The collecto of observatos we take from the populato s called

More information

Simple Linear Regression

Simple Linear Regression Statstcal Methods I (EST 75) Page 139 Smple Lear Regresso Smple regresso applcatos are used to ft a model descrbg a lear relatoshp betwee two varables. The aspects of least squares regresso ad correlato

More information

ENGI 4421 Propagation of Error Page 8-01

ENGI 4421 Propagation of Error Page 8-01 ENGI 441 Propagato of Error Page 8-01 Propagato of Error [Navd Chapter 3; ot Devore] Ay realstc measuremet procedure cotas error. Ay calculatos based o that measuremet wll therefore also cota a error.

More information

Chapter 9 Jordan Block Matrices

Chapter 9 Jordan Block Matrices Chapter 9 Jorda Block atrces I ths chapter we wll solve the followg problem. Gve a lear operator T fd a bass R of F such that the matrx R (T) s as smple as possble. f course smple s a matter of taste.

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

Evaluation of uncertainty in measurements

Evaluation of uncertainty in measurements Evaluato of ucertaty measuremets Laboratory of Physcs I Faculty of Physcs Warsaw Uversty of Techology Warszawa, 05 Itroducto The am of the measuremet s to determe the measured value. Thus, the measuremet

More information

Chapter Business Statistics: A First Course Fifth Edition. Learning Objectives. Correlation vs. Regression. In this chapter, you learn:

Chapter Business Statistics: A First Course Fifth Edition. Learning Objectives. Correlation vs. Regression. In this chapter, you learn: Chapter 3 3- Busess Statstcs: A Frst Course Ffth Edto Chapter 2 Correlato ad Smple Lear Regresso Busess Statstcs: A Frst Course, 5e 29 Pretce-Hall, Ic. Chap 2- Learg Objectves I ths chapter, you lear:

More information

FREQUENCY ANALYSIS OF A DOUBLE-WALLED NANOTUBES SYSTEM

FREQUENCY ANALYSIS OF A DOUBLE-WALLED NANOTUBES SYSTEM Joural of Appled Matematcs ad Computatoal Mecacs 04, 3(4), 7-34 FREQUENCY ANALYSIS OF A DOUBLE-WALLED NANOTUBES SYSTEM Ata Cekot, Stasław Kukla Isttute of Matematcs, Czestocowa Uversty of Tecology Częstocowa,

More information

Generalized Convex Functions on Fractal Sets and Two Related Inequalities

Generalized Convex Functions on Fractal Sets and Two Related Inequalities Geeralzed Covex Fuctos o Fractal Sets ad Two Related Iequaltes Huxa Mo, X Su ad Dogya Yu 3,,3School of Scece, Bejg Uversty of Posts ad Telecommucatos, Bejg,00876, Cha, Correspodece should be addressed

More information

Productivity Evaluation Method of Horizontal Well Volume Fracturing in Tight Oil Reservoir

Productivity Evaluation Method of Horizontal Well Volume Fracturing in Tight Oil Reservoir Advaces Petroleum Explorato ad Developmet Vol. 11, No. 1, 2016, pp. 18-23 DOI:10.3968/7966 ISSN 1925-542X [Prt] ISSN 1925-5438 [Ole] www.cscaada.et www.cscaada.org Productvty Evaluato Method of Horzotal

More information

DATE: 21 September, 1999 TO: Jim Russell FROM: Peter Tkacik RE: Analysis of wide ply tube winding as compared to Konva Kore CC: Larry McMillan

DATE: 21 September, 1999 TO: Jim Russell FROM: Peter Tkacik RE: Analysis of wide ply tube winding as compared to Konva Kore CC: Larry McMillan M E M O R A N D U M DATE: 1 September, 1999 TO: Jm Russell FROM: Peter Tkack RE: Aalyss of wde ply tube wdg as compared to Kova Kore CC: Larry McMlla The goal of ths report s to aalyze the spral tube wdg

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

n -dimensional vectors follow naturally from the one

n -dimensional vectors follow naturally from the one B. Vectors ad sets B. Vectors Ecoomsts study ecoomc pheomea by buldg hghly stylzed models. Uderstadg ad makg use of almost all such models requres a hgh comfort level wth some key mathematcal sklls. I

More information

ECE606: Solid State Devices Lecture 13 Solutions of the Continuity Eqs. Analytical & Numerical

ECE606: Solid State Devices Lecture 13 Solutions of the Continuity Eqs. Analytical & Numerical ECE66: Sold State Devces Lecture 13 Solutos of the Cotuty Eqs. Aalytcal & Numercal Gerhard Klmeck gekco@purdue.edu Outle Aalytcal Solutos to the Cotuty Equatos 1) Example problems ) Summary Numercal Solutos

More information

ESS Line Fitting

ESS Line Fitting ESS 5 014 17. Le Fttg A very commo problem data aalyss s lookg for relatoshpetwee dfferet parameters ad fttg les or surfaces to data. The smplest example s fttg a straght le ad we wll dscuss that here

More information

Bootstrap Method for Testing of Equality of Several Coefficients of Variation

Bootstrap Method for Testing of Equality of Several Coefficients of Variation Cloud Publcatos Iteratoal Joural of Advaced Mathematcs ad Statstcs Volume, pp. -6, Artcle ID Sc- Research Artcle Ope Access Bootstrap Method for Testg of Equalty of Several Coeffcets of Varato Dr. Navee

More information

Manipulator Dynamics. Amirkabir University of Technology Computer Engineering & Information Technology Department

Manipulator Dynamics. Amirkabir University of Technology Computer Engineering & Information Technology Department Mapulator Dyamcs mrkabr Uversty of echology omputer Egeerg formato echology Departmet troducto obot arm dyamcs deals wth the mathematcal formulatos of the equatos of robot arm moto. hey are useful as:

More information

Outline. Point Pattern Analysis Part I. Revisit IRP/CSR

Outline. Point Pattern Analysis Part I. Revisit IRP/CSR Pot Patter Aalyss Part I Outle Revst IRP/CSR, frst- ad secod order effects What s pot patter aalyss (PPA)? Desty-based pot patter measures Dstace-based pot patter measures Revst IRP/CSR Equal probablty:

More information

Notes on the proof of direct sum for linear subspace

Notes on the proof of direct sum for linear subspace Notes o the proof of drect sum for lear subspace Da u, Qa Guo, Huzhou Xag, B uo, Zhoghua Ta, Jgbo Xa* College of scece, Huazhog Agrcultural Uversty, Wuha, Hube, Cha * Correspodece should be addressed to

More information

C.11 Bang-bang Control

C.11 Bang-bang Control Itroucto to Cotrol heory Iclug Optmal Cotrol Nguye a e -.5 C. Bag-bag Cotrol. Itroucto hs chapter eals wth the cotrol wth restrctos: s boue a mght well be possble to have scotutes. o llustrate some of

More information

Integral Equation Methods. Jacob White. Thanks to Deepak Ramaswamy, Michal Rewienski, Xin Wang and Karen Veroy

Integral Equation Methods. Jacob White. Thanks to Deepak Ramaswamy, Michal Rewienski, Xin Wang and Karen Veroy Itroducto to Smulato - Lecture 22 Itegral Equato ethods Jacob Whte Thaks to Deepak Ramaswamy, chal Rewesk, X Wag ad Kare Veroy Outle Itegral Equato ethods Exteror versus teror problems Start wth usg pot

More information