ESTIMATION METHODS FOR THERMOPHYSICAL PROPERTIES OF CAMELINA SATIVA CRUDE OIL

Size: px
Start display at page:

Download "ESTIMATION METHODS FOR THERMOPHYSICAL PROPERTIES OF CAMELINA SATIVA CRUDE OIL"

Transcription

1 U.P.B. Sc. Bull., Seres B, Vol. 78, Iss. 1, 2016 ISSN ESTIMATION METHODS FOR THERMOPHYSICAL PROPERTIES OF CAMELINA SATIVA CRUDE OIL Andreea Crstna PETCU 1, Valentn PLEŞU 2, Cornelu BERBENTE 3 Camelna s one of the most promsng sources of renewable fuels. The crude ol obtaned from ths plant can be chemcally treated and converted nto bo-desel or bo-kerosene. To study straght camelna ol combuston process s very mportant to know as many of ts propertes as possble. In ths artcle, estmaton methods of several thermophyscal propertes, such as: crtcal propertes, densty, thermal conductvty, and specfc heat are presented. Where t was possble, the estmated values have been compared wth expermental measurements, thus valdatng the used method. Keywords: camelna ol, estmaton methods, thermophyscal propertes 1. Introducton Camelna ol s a new, promsng feedstock for second generaton bofuels. The bo-kerosene obtaned from camelna ol meets all the performance and safety requrements so that t can be used n avaton. Blends of classc avaton fuel / bo-kerosene obtaned from camelna ol have been successfully tested on fghtng planes and passenger planes [1]. Accordng to European drectves 2003/30/CE and 2009/28/CE, crude vegetable ols are also consdered bofuels. In the specalzed lterature, there s scarce nformaton regardng the combuston process of crude vegetable ols, n partcular camelna ol. The possblty of usng straght camelna ol as fuel for terrestral applcatons has been taken n consderaton because the process of obtanng the vegetable ol s cheaper and less tme consumng then obtanng bofuels from vegetable ols. To understand better the combuston process of the crude camelna ol, s very mportant to know as many of ts propertes as possble. In ths paper, estmaton methods for several thermophyscal propertes are presented and appled for the partcular case of crude vegetable camelna ol. To valdate the used methods, the estmated values have been compared wth expermental 1 PhD. student, Romanan Research & Development Insttute for Gas Turbnes COMOTI Bucharest, Romana, e-mal: andreea.petcu@comot.ro 2 Prof., Faculty of Appled Chemstry and Materals Scence, Unversty POLITEHNICA of Bucharest, Romana, e-mal: v_plesu@chm.upb.ro 3 Prof., Faculty of Aerospace Engneerng, Unversty POLITEHNICA of Bucharest, Romana, e- mal: berbente@yahoo.com

2 60 Andreea Crstna Petcu, Valentn Pleşu, Cornelu Berbente measurements, where such data were avalable. A detaled presentaton of the expermental procedure used for obtanng the expermental data whch wll be presented n ths paper, can be found n reference [2]. 2. Camelna ol molar weght estmaton The calculatons presented n ths artcle are based on the fatty acds camelna ol chemcal composton, gven n Table 1. The camelna ol fatty acds composton has been analyzed at the Dangerous substances, waste and resdual water testng laboratory from the Natonal Research and Development Insttute for Chemstry and Petrochemstry. Table 1 Camelna ol fatty acds composton Fatty acd Molar fracton Molar weght MW (g/mol) 1 Palmtc acd(c16) Stearc acd (C18) Olec acd (C18:1) Lnolec acd (C18:2) Lnolenc acd (C18:3) Ecosanoc acd (C20:1) Behenc acd (C22) Erucc acd (C22:1) The fatty acds composton of the camelna ol cultvated n Romana, and presented n Table 1, s smlar, but not the same as those reported for ols obtaned from camelna seeds cultvated n Span [3] and n Slovena [4]. The dfferences n the composton may be due to dfferent cultvaton regons and dfferent growng condtons. These fatty acds are found n the camelna ol n the form of trglycerdes. The mathematcal methods presented n ths artcle estmate the termophyscal propertes of these trglycerdes. The camelna ol thermophyscal propertes are calculated startng from these values and consderng that the molar fracton of these trglycerdes s equal wth the molar fracton of the fatty acd n ther composton. The camelna ol molar weght has been calculated usng the followng relaton [5]: MW = 3 x MW ol + (1) where x represents the molar fracton of the fatty acd n the ol's composton, and MW s the molar weght of the respectve fatty acd. Accordng to equaton (1), n order to estmate the molar weght of camelna ol s necessary to calculate frst the weght average molecular weght of all the fatty acds components of the compound, based on ther ndvdual molecular weghts and mole fractons. Ths

3 Estmaton methods for thermophyscal propertes of camelna satva crude ol 61 s multpled by 3 to take nto account the 3 dentcal fatty acd chans found n the fatty acd correspondng trglycerde. In addton, one also needs to take nto account the glycerol part of the trglycerde, whch s composed of 3 carbon atoms and 5 hydrogen atoms (-CH 2- CH-CH 2 -), as well as the dfference of 3 hydrogen atoms between the fatty acds and the fatty acd chans n the composton of the trglycerde. The sum of these contrbutons, calculated usng equaton (2) [5], leads to the obtanng of the second term on the rght-hand sde of equaton (1): 3 MWCarbon + 5 MWHdrogen 3 MWHdrogen = (2) By applyng equaton (1) the molar weght of the camelna ol has been estmated to g/mol. 3. Crtcal propertes estmaton methods To determne the thermophyscal propertes of a substance, estmaton methods use as nput data the characterstc constants of the respectve compound, defned n the followng: normal bolng pont, crtcal temperature, crtcal pressure, crtcal volume and acentrc factor. To determne expermentally these constants s very dffcult, because the majorty of substances chemcally decompose before reachng the crtcal pont. The crtcal temperature represents the temperature value above whch the substance can no longer be lquefed, no matter how much pressure s appled. The crtcal pressure s the pressure of the substance's vapor pressure at the crtcal temperature. The crtcal volume s the volume occuped by 1 mole of substance at ts crtcal temperature and pressure. The normal bolng pont represents the temperature value at whch the compound's vapor pressure s equal to the atmospherc pressure [6]. The acentrc factor s a measure of the sphercty of the molecule [7]. The used estmaton methods are presented n Table 2. Table 2 Crtcal propertes estmaton methods Method Equaton Joback [7] T b [ K] = 198+ x ΔT b (3) 2 1 Tc [ K] = T b x ΔTc ( x ΔTc) (4) P [ bar] ( n x P ) 2 c = + A Δ c (5) 3 Vc [ cm / mol] = xδvc (6) Constantnou & Gan [8] T b [ K ] = ln( x Δ T b1 + y ΔT b2 ) (7) T c[ K ] = ln( x Δ T c 1 + x Δ T c2 ) (8)

4 62 Andreea Crstna Petcu, Valentn Pleşu, Cornelu Berbente 2 Pc [ bar] = ( x Δ P c 1 + y Δ P c ) (9) V 3 c[ cm / ] = ( x Δ V c 1 + y Δ V c2 ) (10) Fedor [6,9] Tc [ K] = 535 log 10 ( x ΔTc) (11) 3 Vc [ cm / mol] = x ΔV c (12) Marrero & Gan [10] T b [ ] ln( x T b1 y b2 ) (13) Tc [ K] = ln( x Δ T c 1 + x ΔT c2 ) (14) 2 Pc [ bar] = ( x Δ P c 1 + y Δ P c ) (15) 3 Vc [ cm / mol] = ( x Δ V c 1 + y ΔV c2 ) (16) Nannoolal [11] x ΔT T [ ] b b K = n (17) Banks [12] log 10 T b [ ] = / M (18) Burnop [12] log 10 T b [ ] x b M 8 / M (19) The results obtaned usng the above estmaton methods are summarzed n Tables 3-6. Table 3 Estmaton of normal bolng pont T b Constantnou Gan & T b [K] Joback Nannoolal Banks Burnop & Gan Marrero Trpalmtn 1, Trstearn 1, Trolen 1, , Trlnolen 1, , Trlnolenn 1, , Trecosanon 1, Trbehenn 1, , Trerucn 1, , Camelna ol 1,710,95 828,65 852,33 1, Table 4 Estmaton of crtcal temperature T c [K] Joback Constantnou & Gan Gan & Marrero Fedor Trpalmtn 3, , , Trstearn 4, , , Trolen 4, , , Trlnolen 3, , , Trlnolenn 3, , , Trecosanon 8, , ,062.49

5 Estmaton methods for thermophyscal propertes of camelna satva crude ol 63 Trbehenn 94, , , , Trerucn 23, , , , Camelna ol 4, , , Table 5 Estmaton of crtcal pressure P c [bar] Joback Constantnou & Gan Gan & Marrero Trpalmtn Trstearn Trolen Trlnolen Trlnolenn Trecosanon Trbehenn Trerucn Camelna ol Table 6 Estmaton of crtcal volume V c [cm 3 Constantnou & Gan & /mol] Joback Gan Marrero Fedor Trpalmtn 2, , , , Trstearn 3, , , , Trolen 3, , , , Trlnolen 3, , , , Trlnolenn 3, , , , Trecosanon 3, , , , Trbehenn 3, , , , Trerucn 3, , , , Camelna ol 3, , , , There are no expermental data or nformaton n the specalzed lterature regardng these propertes for the camelna ol. In Table 7, values of the crtcal propertes of smlar vegetable ols and of trglycerdes found n the composton of the camelna ol, avalable n the specalzed lterature, are presented. Table 7 Crtcal propertes values found n the lterature Substance T b [K] T c [K] P c [bar] V c [cm3/mol] Rapeseed ol 584 [13] 765 [13] - - Jatropha ol [14] [14] - - Trpalmtn [15] 675 [16] Trolen [15] 953 [17] 977 [18] [17] 3.34 [18] 3090 [17] 3250 [18] Trstearn 682 [14] - - -

6 64 Andreea Crstna Petcu, Valentn Pleşu, Cornelu Berbente Comparng the lterature data wth the calculated data, t has been concluded that the best result for the normal bolng pont has been obtaned usng the Banks method [12], whle for the crtcal propertes the best results have been obtaned usng the Constantnou & Gan method [8]. A method to verfy the consstency of the crtcal propertes values s to calculate the crtc compressblty factor, gven by the relaton (20) [6]: Pc Vc Zc = (20) R Tc Ths factor s value should be smaller than [7]. In our case ths factor has the value of Another mportant materal constant whch s used as nput data n other estmaton methods s the acentrc factor. Ths factor s calculated usng the relaton (21) [7]: Zc = ω (21) For the camelna ol, the value of 1.96 has been obtaned. 4. Densty estmaton methods To estmate the densty of camelna ol, two methods have been used: the Ihmels method [5] and the Zong method [5]. The calculaton formula proposed by the Ihmels method s: MW MW ρ = = (22) V nδν where MW represents the molar weght and V the molar volume. The molar volume s calculated by summng up the volume group contrbutons Δν multpled by the number of group's appearances n the compound, n. Δν s calculated usng the followng temperature dependng polynomal functon [5]: 2 Δ ν = A + BT + CT (23) The values of the structural group specfc coeffcents A, B and C are presented n reference [5]. The calculaton formula proposed by the Zong method s [5]: MW MW ρ = = (24) V N frag, A VA( T) where N frag. A represents the number of fragment A present n the compound, and VA ( T) represents the molar volume of the respectve fragment. VA ( T ) s gven by the followng relaton [5]:

7 Estmaton methods for thermophyscal propertes of camelna satva crude ol 65 V ( T) A 1+ B T 2, A = (25) B1, A The values of coeffcents B 1,A and B 2,A are presented n reference [5]. The results obtaned by usng the estmaton methods presented above are summarzed n Table 8. Table 8 Camelna ol densty ρ [kg/m 3 ] T[K] Expermental data Ihmels method Error Zong method Error % % % % % % % % % % % % % % % % % % % % Both methods have a good accuracy n estmatng the camelna ol's densty, as t can been observed from the data presented n Table 8. Comparng the two methods, the values obtaned wth the Zong method are n a very good agreement to the expermental data, havng an error under 1%. By extrapolatng the obtaned data on a larger temperature range than the one for whch expermental data are avalable, t can be observed n Fg. 1 that the results obtaned wth the Zong method are very closed to the those obtaned by extrapolatng the expermental data, whle the results obtaned usng the Ihmels method tend to dverge, startng from the temperature of 450 K. Fg. 1 Camelna ol densty ρ (kg/m 3 )

8 66 Andreea Crstna Petcu, Valentn Pleşu, Cornelu Berbente 5. Specfc heat estmaton methods To estmate the camelna ol specfc heat at constant pressure two methods have been used: the Ceran method [5] and the Zong method [5]. The calculaton formula proposed by the Ceran method s: Cp = Nk ( Ak + Bk T) (26) where N k represents the number of structural groups k present n the substance, and A k and B k are the method s coeffcents specfc to each structural group. The values of parameters A k and B k used n the calculatons are presented n [5]. The calculaton formula proposed by the Zong method s: Cp = N frag. A CpA, ( T) (27) where N frag. A represents the number of fragment A present n the substance, and CpA, ( T ) represents the specfc heat of fragment A. CpA, ( T) s calculated usng the lnear equaton below: CpA, ( T) = A1, A+ A2, A( T) (28) The values of parameters A 1,A and A 2,A, specfc to each fragment, used n the calculatons are presented n [5]. The results obtaned by usng the estmaton methods presented above are summarzed n Table 9. Table 9 Camelna ol specfc heat c p [J/(kg K)] T[K] Expermental data Ceran method Error Zong method Error 293 2,053 1, % 2, % 294 2,043 1, % 2, % 295 2,056 1, % 2, % 296 2,070 1, % 2, % 297 2,059 1, % 2, % 298 2,072 1, % 2, % 299 2,062 1, % 2, % 300 2,075 1, % 2, % 301 2,089 1, % 2, % 302 2,078 1, % 2, % 303 2,092 1, % 2, % From the results presented above, t can be observed that, for the temperature range for whch expermental data are avalable, the values obtaned usng both estmaton methods are comparable. Comparng them wth the expermental data, the error n the case of the Ceran method s around 7%, whle n the case of the Zong method the error s smaller, beng around 2%.

9 Estmaton methods for thermophyscal propertes of camelna satva crude ol 67 Extrapolatng the results on a larger temperature nterval, t can be observed from Fg. 2 that the results obtaned usng the Ceran method follow the trend of the expermental data, whle the results obtaned usng the Zong method get farther away wth the ncrease of the temperature. Fg. 2 Specfc heat of camelna ol [J/(kmol K)] 6. Thermal conductvty estmaton methods To estmate camelna ol thermal conductvty, two methods have been used: the Sastr-Rao method [6] and the Baroncn method [6]. The calculaton formula proposed by the Sastr-Rao method s: k = k b α β (29) kb = nδk (30) where: γ 1 T r β = 1 (31) 1 T br where n represents the number of group n the compound, Δk s the coeffcent specfc to each group, T r s the reduced temperature and Tbr represents the rato of the normal bolng pont and the crtcal temperature. The constants α and γ have the followng values: 0.16, respectvely 0.2. The values of the Δk coeffcents used n the calculatons are gven n reference [6]. The calculaton formula proposed by the Baroncn method s: 0.38 α β γ (1 Tr ) b c 1/6 Tr k = A T M T (32)

10 68 Andreea Crstna Petcu, Valentn Pleşu, Cornelu Berbente where M represents the molar mass (g/mol), T b s the normal bolng pont, T c s the crtcal temperature, T r s the reduced temperature, and A, α, β andγ are constants specfc to the method. In the case of esters, these constants have the followng values: A=0.0415, α=1.2, β=1 andγ =0.167 [6]. In the case of camelna ol thermal conductvty, expermental data are avalable only for the temperature of 298 K. Comparng ths value wth the ones obtaned by applyng the estmaton methods the followng errors have resulted. Table 10 Thermal conductvty of camelna ol k [W/(m K)] T[K] Expermental data Sastr-Rao Error Baroncn Error method method % % From the results presented above, t can be concluded that the Sastr-Rao method s better suted for estmatng the thermal conductvty of camelna ol at the temperature of 298 K. Snce no expermental data are avalable for other temperatures, the accuracy of the method cannot be assessed for other temperature values. 7. Conclusons Fg. 3 Thermal conductvty of camelna ol [W/(m K)] In ths paper thermophyscal propertes estmaton methods for the partcular case of camelna crude ol have been presented. The lterature data regardng these propertes for the camelna ol s very scarce. Some of the camelna ols propertes have been determned expermentally, but not on a very large temperature nterval. Beng mportant to know as many as possble

11 Estmaton methods for thermophyscal propertes of camelna satva crude ol 69 propertes of camelna ol to better understand ts combuston process, mathematcal methods have been employed to estmate some of these propertes. In the case of the crtcal propertes of the camelna ol, t has been concluded that the normal bolng pont s estmated wth the best accuracy by the Banks method, whle the crtcal temperature, pressure and volume are estmated wth the best accuracy by the Constantnou & Gan method. In the case of densty, although on the temperature nterval for whch expermental data s avalable both presented methods have good accuracy, on a larger temperature range the Zong method s the most accurate. In the case of the specfc heat at constant pressure, on the temperature range for whch expermental data s avalable both methods have comparable errors: the Zong method 12-13%, and the Ceran method 17-18%. Extrapolatng on a larger temperature nterval, the results obtaned wth the Ceran method follow the trend gven by the expermental data, whle the results obtaned usng the Zong method become dvergent above a certan temperature. In the case of the thermal conductvty, data for only one temperature value, 298 K, s avalable. Two methods have been used to estmate the thermal conductvty correspondng to ths temperature value. The best result has been obtaned by the Sastr-Rao method, wth an error under 2%. Other expermental data not beng avalable, t cannot be sad f the results obtaned wth ths estmaton method on larger temperature ntervals wll have the same good accuracy. The values of the camelna ol thermophyscal propertes presented n ths artcle are very smlar wth those of varous vegetable ols [13, 19, 20], ols from whch bofuels can be obtaned. Thus, for the future t s consdered to carry out straght camelna ol combuston tests on a heatng plant s burner. R E F E R E N C E S [1]. D.R. Shonnard, L. Wllams, T.N. Kalnes, Camelna-Derved Jet Fuel and Desel: Sustanable Advanced Bofuels, Envronmental Progress & Sustanable Energy, vol. 29, no. 3, p , 2010 [2]. A.C. Petcu, R. Carlanescu, C. Berbente, Straght and Blended Camelna Ol Propertes, Recent Advances n Mechancal Engneerng Seres, vol. 11, p , 2014 [3]. C. Cubota-Rose, J.R. Ruz, M.J. Ramos, A. Perez, Bodesel from Camelna satva: A comprehensve charactersaton, Fuel, vol. 105, p , 2013 [4]. H. Abramovc, V. Abram, Physco-Chemcal Propertes, Composton and Oxdatve Stablty of Camelna satva Ol, Food Technology and Botechnology, vol. 43, p.63-70, 2005 [5]. Y.C. Su, Y.A. Lu, "Selecton of predcton methods for thermophyscal propertes for process modelng and product desgn of bodesel manufacturng", Journal of Industral and Engneerng Chemstry Research, vol. 50, p , 2011 [6]. D.W. Green, R.H. Perry, "Perry s Chemcal Engneers Handbook", 8 th edton, McGraw Hll, 2008

12 70 Andreea Crstna Petcu, Valentn Pleşu, Cornelu Berbente [7]. B.E. Polng, J.M. Prausntz, J.P. O Connell, "The propertes of gases and lquds", 5 th edton, McGraw Hll, 2004 [8] L. Constantnou, R. Gan, "New group contrbuton method for estmatng propertes of pure compounds", AlChE Journal, vol. 40, p , 1994 [9]. K.M. Klncewcz, "Predcton of crtcal temperatures, pressures and volumes of organc compounds from molecular structure", Master of Scence Thess, Massachusetts Insttute of Technology, 1982 [10]. J. Marrero, R. Gan, "Group-contrbuton based estmaton of pure component propertes", Flud Phase Equlbra, vol. 183, p , 2001 [11]. Y. Nannoolal, "Development and crtcal evaluaton of group contrbuton methods for the estmaton of crtcal propertes, lqud vapour pressure and lqud vscosty of organc compounds", PhD. Thess, Unversty of Kwazulu-Natal, 2006 [12]. R.S. Boethlng, D. Mackay, "Handbook of Property Estmaton Methods for Chemcals: envronmental and health scences", Lews Publshers, 2000 [13]. J. Parrlla, C. Cortes, "Modellng of droplet burnng for rapeseed ol as lqud fuel", Proceedngs of Internatonal Conference on Renewable Energes and Power Qualty ICREPQ 07, Sevlla, Spana, 2007 [14]. E.G. Lma Neto, G.P. Slva, G.F. Slva, Evaluaton of group-contrbuton methods to estmate vegetable ols and bodesel propertes, Internatonal Journal of Engneerng & Technology, vol. 2, p , 2012 [15]. C.M. Santander, S.M. Rueda, N. da Slva, C.L.de Camargo, T.G. Keckbusch, M.R. Macel, Measurements of normal bolng ponts of fatty acd ethyl esters and tracylglycerols by thermogravmetrc analyss, Fuel, vol. 92, p , 2012 [16]. D.C. Cruz-Forero, O.A. Gonzalez-Ruz, L.J. Lopez-Graldo, "Calculaton of thermophyscal propertes of ols and tracylglycerols usng an extended consttuent fragment approach", Journal Cenca, Tecnologa y Futuro, vol. 5, p , 2012 [17]. Z. Tang, Z. Du, E. Mn, L. Gao, T. Jang, B. Han, "Phase equlbra of methanol-trolen system at elevated temperature and pressure", Flud Phase Equlbra, vol. 239, p. 8-11, 2006 [18]. S. Glsc, D. Skala, "The predcton of crtcal parameters for trolen, dolen, monolen and methyl esters", 9th Internatonal Symposum on SuperCrtcal Fluds, Archon, France, 2009 [19]. O.O. Fasna, Z. Colley, Vscosty and specfc heat of vegetable ols as a functon of temperature: 35 C to 180 C, Internatonal Journal of Food Propertes, vol. 11, p , 2008 [20]. F. Lujaj, A. Bereczky, L. Janos, Cetane number and thermal propertes of vegetable ol, bodesel, 1-butanol and desel blends, Journal of Thermal Analyss and Calormetry, vol. 102, p , 2010

LNG CARGO TRANSFER CALCULATION METHODS AND ROUNDING-OFFS

LNG CARGO TRANSFER CALCULATION METHODS AND ROUNDING-OFFS CARGO TRANSFER CALCULATION METHODS AND ROUNDING-OFFS CONTENTS 1. Method for determnng transferred energy durng cargo transfer. Calculatng the transferred energy.1 Calculatng the gross transferred energy.1.1

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

Chapter 13: Multiple Regression

Chapter 13: Multiple Regression Chapter 13: Multple Regresson 13.1 Developng the multple-regresson Model The general model can be descrbed as: It smplfes for two ndependent varables: The sample ft parameter b 0, b 1, and b are used to

More information

Energy, Entropy, and Availability Balances Phase Equilibria. Nonideal Thermodynamic Property Models. Selecting an Appropriate Model

Energy, Entropy, and Availability Balances Phase Equilibria. Nonideal Thermodynamic Property Models. Selecting an Appropriate Model Lecture 4. Thermodynamcs [Ch. 2] Energy, Entropy, and Avalablty Balances Phase Equlbra - Fugactes and actvty coeffcents -K-values Nondeal Thermodynamc Property Models - P-v-T equaton-of-state models -

More information

Estimation of the composition of the liquid and vapor streams exiting a flash unit with a supercritical component

Estimation of the composition of the liquid and vapor streams exiting a flash unit with a supercritical component Department of Energ oltecnco d Mlano Va Lambruschn - 05 MILANO Eercses of Fundamentals of Chemcal rocesses rof. Ganpero Gropp Eercse 8 Estmaton of the composton of the lqud and vapor streams etng a unt

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

Calculating the Quasi-static Pressures of Confined Explosions Considering Chemical Reactions under the Constant Entropy Assumption

Calculating the Quasi-static Pressures of Confined Explosions Considering Chemical Reactions under the Constant Entropy Assumption Appled Mechancs and Materals Onlne: 202-04-20 ISS: 662-7482, ol. 64, pp 396-400 do:0.4028/www.scentfc.net/amm.64.396 202 Trans Tech Publcatons, Swtzerland Calculatng the Quas-statc Pressures of Confned

More information

Assignment 4. Adsorption Isotherms

Assignment 4. Adsorption Isotherms Insttute of Process Engneerng Assgnment 4. Adsorpton Isotherms Part A: Compettve adsorpton of methane and ethane In large scale adsorpton processes, more than one compound from a mxture of gases get adsorbed,

More information

Simulated Power of the Discrete Cramér-von Mises Goodness-of-Fit Tests

Simulated Power of the Discrete Cramér-von Mises Goodness-of-Fit Tests Smulated of the Cramér-von Mses Goodness-of-Ft Tests Steele, M., Chaselng, J. and 3 Hurst, C. School of Mathematcal and Physcal Scences, James Cook Unversty, Australan School of Envronmental Studes, Grffth

More information

Adiabatic Sorption of Ammonia-Water System and Depicting in p-t-x Diagram

Adiabatic Sorption of Ammonia-Water System and Depicting in p-t-x Diagram Adabatc Sorpton of Ammona-Water System and Depctng n p-t-x Dagram J. POSPISIL, Z. SKALA Faculty of Mechancal Engneerng Brno Unversty of Technology Techncka 2, Brno 61669 CZECH REPUBLIC Abstract: - Absorpton

More information

Uncertainty in measurements of power and energy on power networks

Uncertainty in measurements of power and energy on power networks Uncertanty n measurements of power and energy on power networks E. Manov, N. Kolev Department of Measurement and Instrumentaton, Techncal Unversty Sofa, bul. Klment Ohrdsk No8, bl., 000 Sofa, Bulgara Tel./fax:

More information

DETERMINATION OF CO 2 MINIMUM MISCIBILITY PRESSURE USING SOLUBILITY PARAMETER

DETERMINATION OF CO 2 MINIMUM MISCIBILITY PRESSURE USING SOLUBILITY PARAMETER DETERMINATION OF CO 2 MINIMUM MISCIBILITY PRESSURE USING SOLUBILITY PARAMETER Rocha, P. S. 1, Rbero, A. L. C. 2, Menezes, P. R. F. 2, Costa, P. U. O. 2, Rodrgues, E. A. 2, Costa, G. M. N. 2 *, glora.costa@unfacs.br,

More information

I wish to publish my paper on The International Journal of Thermophysics. A Practical Method to Calculate Partial Properties from Equation of State

I wish to publish my paper on The International Journal of Thermophysics. A Practical Method to Calculate Partial Properties from Equation of State I wsh to publsh my paper on The Internatonal Journal of Thermophyscs. Ttle: A Practcal Method to Calculate Partal Propertes from Equaton of State Authors: Ryo Akasaka (correspondng author) 1 and Takehro

More information

OFF-AXIS MECHANICAL PROPERTIES OF FRP COMPOSITES

OFF-AXIS MECHANICAL PROPERTIES OF FRP COMPOSITES ICAMS 204 5 th Internatonal Conference on Advanced Materals and Systems OFF-AXIS MECHANICAL PROPERTIES OF FRP COMPOSITES VLAD LUPĂŞTEANU, NICOLAE ŢĂRANU, RALUCA HOHAN, PAUL CIOBANU Gh. Asach Techncal Unversty

More information

A Self-Consistent Gibbs Excess Mixing Rule for Cubic Equations of State: derivation and fugacity coefficients

A Self-Consistent Gibbs Excess Mixing Rule for Cubic Equations of State: derivation and fugacity coefficients A Self-Consstent Gbbs Excess Mxng Rule for Cubc Equatons of State: dervaton and fugacty coeffcents Paula B. Staudt, Rafael de P. Soares Departamento de Engenhara Químca, Escola de Engenhara, Unversdade

More information

MODELING THE HIGH-PRESSURE BEHAVIOR OF BINARY MIXTURES OF CARBON DIOXIDE+ALKANOLS USING AN EXCESS FREE ENERGY MIXING RULE

MODELING THE HIGH-PRESSURE BEHAVIOR OF BINARY MIXTURES OF CARBON DIOXIDE+ALKANOLS USING AN EXCESS FREE ENERGY MIXING RULE Brazlan Journal of Chemcal Engneerng ISSN 0104-6632 Prnted n Brazl Vol. 21, No. 04, pp. 659-666, October - December 04 MODELING THE HIGH-PRESSURE BEHAVIOR OF BINARY MIXTURES OF CARBON DIOXIDE+ALKANOLS

More information

Lecture. Polymer Thermodynamics 0331 L Chemical Potential

Lecture. Polymer Thermodynamics 0331 L Chemical Potential Prof. Dr. rer. nat. habl. S. Enders Faculty III for Process Scence Insttute of Chemcal Engneerng Department of Thermodynamcs Lecture Polymer Thermodynamcs 033 L 337 3. Chemcal Potental Polymer Thermodynamcs

More information

is the calculated value of the dependent variable at point i. The best parameters have values that minimize the squares of the errors

is the calculated value of the dependent variable at point i. The best parameters have values that minimize the squares of the errors Multple Lnear and Polynomal Regresson wth Statstcal Analyss Gven a set of data of measured (or observed) values of a dependent varable: y versus n ndependent varables x 1, x, x n, multple lnear regresson

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

A Robust Method for Calculating the Correlation Coefficient

A Robust Method for Calculating the Correlation Coefficient A Robust Method for Calculatng the Correlaton Coeffcent E.B. Nven and C. V. Deutsch Relatonshps between prmary and secondary data are frequently quantfed usng the correlaton coeffcent; however, the tradtonal

More information

ON A DETERMINATION OF THE INITIAL FUNCTIONS FROM THE OBSERVED VALUES OF THE BOUNDARY FUNCTIONS FOR THE SECOND-ORDER HYPERBOLIC EQUATION

ON A DETERMINATION OF THE INITIAL FUNCTIONS FROM THE OBSERVED VALUES OF THE BOUNDARY FUNCTIONS FOR THE SECOND-ORDER HYPERBOLIC EQUATION Advanced Mathematcal Models & Applcatons Vol.3, No.3, 2018, pp.215-222 ON A DETERMINATION OF THE INITIAL FUNCTIONS FROM THE OBSERVED VALUES OF THE BOUNDARY FUNCTIONS FOR THE SECOND-ORDER HYPERBOLIC EUATION

More information

Three-Phase Distillation in Packed Towers: Short-Cut Modelling and Parameter Tuning

Three-Phase Distillation in Packed Towers: Short-Cut Modelling and Parameter Tuning European Symposum on Computer Arded Aded Process Engneerng 15 L. Pugjaner and A. Espuña (Edtors) 2005 Elsever Scence B.V. All rghts reserved. Three-Phase Dstllaton n Packed Towers: Short-Cut Modellng and

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

Module 3: The Whole-Process Perspective for Thermochemical Hydrogen

Module 3: The Whole-Process Perspective for Thermochemical Hydrogen "Thermodynamc Analyss of Processes for Hydrogen Generaton by Decomposton of Water" by John P. O'Connell Department of Chemcal Engneerng Unversty of Vrgna Charlottesvlle, VA 2294-4741 A Set of Energy Educaton

More information

Prediction of the flash point of ternary ideal mixtures

Prediction of the flash point of ternary ideal mixtures Electronc Journal of New Materals, Energy and Envronment Volume No. (25), -5 url: http://ejnmee.eu/ eissn: 2367-6868 redcton of the flash pont of ternary deal mxtures M. Hrstova Unversty of Chemcal Technology

More information

Prediction of Ultrasonic Velocity in Binary Mixtures of a Nuclear Extractant and Monocarboxylic Acids using Several Theoretical Models

Prediction of Ultrasonic Velocity in Binary Mixtures of a Nuclear Extractant and Monocarboxylic Acids using Several Theoretical Models Predcton of ltrasonc Velocty n Bnary Mxtures of a Nuclear Extractant and Monocarboxylc Acds usng Several Theoretcal Models R. K. Mshra 1, B. Dala 1*, N. Swan 2 and S.K. Dash 3 1 BSH, Gandh Insttute of

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

COEFFICIENT DIAGRAM: A NOVEL TOOL IN POLYNOMIAL CONTROLLER DESIGN

COEFFICIENT DIAGRAM: A NOVEL TOOL IN POLYNOMIAL CONTROLLER DESIGN Int. J. Chem. Sc.: (4), 04, 645654 ISSN 097768X www.sadgurupublcatons.com COEFFICIENT DIAGRAM: A NOVEL TOOL IN POLYNOMIAL CONTROLLER DESIGN R. GOVINDARASU a, R. PARTHIBAN a and P. K. BHABA b* a Department

More information

LINEAR REGRESSION ANALYSIS. MODULE IX Lecture Multicollinearity

LINEAR REGRESSION ANALYSIS. MODULE IX Lecture Multicollinearity LINEAR REGRESSION ANALYSIS MODULE IX Lecture - 31 Multcollnearty Dr. Shalabh Department of Mathematcs and Statstcs Indan Insttute of Technology Kanpur 6. Rdge regresson The OLSE s the best lnear unbased

More information

Randić Energy and Randić Estrada Index of a Graph

Randić Energy and Randić Estrada Index of a Graph EUROPEAN JOURNAL OF PURE AND APPLIED MATHEMATICS Vol. 5, No., 202, 88-96 ISSN 307-5543 www.ejpam.com SPECIAL ISSUE FOR THE INTERNATIONAL CONFERENCE ON APPLIED ANALYSIS AND ALGEBRA 29 JUNE -02JULY 20, ISTANBUL

More information

CHEMICAL ENGINEERING

CHEMICAL ENGINEERING Postal Correspondence GATE & PSUs -MT To Buy Postal Correspondence Packages call at 0-9990657855 1 TABLE OF CONTENT S. No. Ttle Page no. 1. Introducton 3 2. Dffuson 10 3. Dryng and Humdfcaton 24 4. Absorpton

More information

Modeling of Phase and Chemical Equilibria for Systems Involved in Biodiesel Production

Modeling of Phase and Chemical Equilibria for Systems Involved in Biodiesel Production 855 A publcaton of CHEMICAL ENGINEERING TRANSACTIONS VOL. 43, 205 Chef Edtors: Sauro Perucc, Jří J. Klemeš Copyrght 205, AIDIC Servz S.r.l., ISBN 978-88-95608-34-; ISSN 2283-926 The Italan Assocaton of

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 EFFECT OF TORSIONAL RIGIDITY BETWEEN ELEMENTS ON FREE VIBRATIONS OF A TELESCOPIC HYDRAULIC CYLINDER SUBJECTED TO EULER S LOAD

THE EFFECT OF TORSIONAL RIGIDITY BETWEEN ELEMENTS ON FREE VIBRATIONS OF A TELESCOPIC HYDRAULIC CYLINDER SUBJECTED TO EULER S LOAD Journal of Appled Mathematcs and Computatonal Mechancs 7, 6(3), 7- www.amcm.pcz.pl p-issn 99-9965 DOI:.75/jamcm.7.3. e-issn 353-588 THE EFFECT OF TORSIONAL RIGIDITY BETWEEN ELEMENTS ON FREE VIBRATIONS

More information

Equation of State Modeling of Phase Equilibrium in the Low-Density Polyethylene Process

Equation of State Modeling of Phase Equilibrium in the Low-Density Polyethylene Process Equaton of State Modelng of Phase Equlbrum n the Low-Densty Polyethylene Process H. Orbey, C. P. Boks, and C. C. Chen Ind. Eng. Chem. Res. 1998, 37, 4481-4491 Yong Soo Km Thermodynamcs & Propertes Lab.

More information

Chapter 9: Statistical Inference and the Relationship between Two Variables

Chapter 9: Statistical Inference and the Relationship between Two Variables Chapter 9: Statstcal Inference and the Relatonshp between Two Varables Key Words The Regresson Model The Sample Regresson Equaton The Pearson Correlaton Coeffcent Learnng Outcomes After studyng ths chapter,

More information

Multicomponent Vaporization Modeling of Petroleum-Biofuel Mixture at High-Pressure Conditions

Multicomponent Vaporization Modeling of Petroleum-Biofuel Mixture at High-Pressure Conditions ILASS Amercas, 3 rd Annual Conference on Lqud Atomzaton and Spray Systems, Ventura, CA, May 011 Multcomponent Vaporzaton Modelng of Petroleum-Bofuel Mxture at Hgh-Pressure Condtons L. Zhang and Song-Charng

More information

Color Rendering Uncertainty

Color Rendering Uncertainty Australan Journal of Basc and Appled Scences 4(10): 4601-4608 010 ISSN 1991-8178 Color Renderng Uncertanty 1 A.el Bally M.M. El-Ganany 3 A. Al-amel 1 Physcs Department Photometry department- NIS Abstract:

More information

Grand canonical Monte Carlo simulations of bulk electrolytes and calcium channels

Grand canonical Monte Carlo simulations of bulk electrolytes and calcium channels Grand canoncal Monte Carlo smulatons of bulk electrolytes and calcum channels Thess of Ph.D. dssertaton Prepared by: Attla Malascs M.Sc. n Chemstry Supervsor: Dr. Dezső Boda Unversty of Pannona Insttute

More information

Parameter Estimation for Dynamic System using Unscented Kalman filter

Parameter Estimation for Dynamic System using Unscented Kalman filter Parameter Estmaton for Dynamc System usng Unscented Kalman flter Jhoon Seung 1,a, Amr Atya F. 2,b, Alexander G.Parlos 3,c, and Klto Chong 1,4,d* 1 Dvson of Electroncs Engneerng, Chonbuk Natonal Unversty,

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

Chapter 3 Thermochemistry of Fuel Air Mixtures

Chapter 3 Thermochemistry of Fuel Air Mixtures Chapter 3 Thermochemstry of Fuel Ar Mxtures 3-1 Thermochemstry 3- Ideal Gas Model 3-3 Composton of Ar and Fuels 3-4 Combuston Stochometry t 3-5 The1 st Law of Thermodynamcs and Combuston 3-6 Thermal converson

More information

x = , so that calculated

x = , so that calculated Stat 4, secton Sngle Factor ANOVA notes by Tm Plachowsk n chapter 8 we conducted hypothess tests n whch we compared a sngle sample s mean or proporton to some hypotheszed value Chapter 9 expanded ths to

More information

Exercises of Fundamentals of Chemical Processes

Exercises of Fundamentals of Chemical Processes Department of Energ Poltecnco d Mlano a Lambruschn 4 2056 MILANO Exercses of undamentals of Chemcal Processes Prof. Ganpero Gropp Exercse 7 ) Estmaton of the composton of the streams at the ext of an sothermal

More information

Determination of Structure and Formation Conditions of Gas Hydrate by Using TPD Method and Flash Calculations

Determination of Structure and Formation Conditions of Gas Hydrate by Using TPD Method and Flash Calculations nd atonal Iranan Conference on Gas Hydrate (ICGH) Semnan Unersty Determnaton of Structure and Formaton Condtons of Gas Hydrate by Usng TPD Method and Flash Calculatons H. Behat Rad, F. Varamnan* Department

More information

Uncertainty and auto-correlation in. Measurement

Uncertainty and auto-correlation in. Measurement Uncertanty and auto-correlaton n arxv:1707.03276v2 [physcs.data-an] 30 Dec 2017 Measurement Markus Schebl Federal Offce of Metrology and Surveyng (BEV), 1160 Venna, Austra E-mal: markus.schebl@bev.gv.at

More information

Air Age Equation Parameterized by Ventilation Grouped Time WU Wen-zhong

Air Age Equation Parameterized by Ventilation Grouped Time WU Wen-zhong Appled Mechancs and Materals Submtted: 2014-05-07 ISSN: 1662-7482, Vols. 587-589, pp 449-452 Accepted: 2014-05-10 do:10.4028/www.scentfc.net/amm.587-589.449 Onlne: 2014-07-04 2014 Trans Tech Publcatons,

More information

Comparison of the Population Variance Estimators. of 2-Parameter Exponential Distribution Based on. Multiple Criteria Decision Making Method

Comparison of the Population Variance Estimators. of 2-Parameter Exponential Distribution Based on. Multiple Criteria Decision Making Method Appled Mathematcal Scences, Vol. 7, 0, no. 47, 07-0 HIARI Ltd, www.m-hkar.com Comparson of the Populaton Varance Estmators of -Parameter Exponental Dstrbuton Based on Multple Crtera Decson Makng Method

More information

NAME and Section No. it is found that 0.6 mol of O

NAME and Section No. it is found that 0.6 mol of O NAME and Secton No. Chemstry 391 Fall 7 Exam III KEY 1. (3 Ponts) ***Do 5 out of 6***(If 6 are done only the frst 5 wll be graded)*** a). In the reacton 3O O3 t s found that.6 mol of O are consumed. Fnd

More information

Number Average Molar Mass. Mass Average Molar Mass. Z-Average Molar Mass

Number Average Molar Mass. Mass Average Molar Mass. Z-Average Molar Mass 17 Molar mass: There are dfferent ways to report a molar mass lke (a) Number average molar mass, (b) mass average molar mass, (c) Vscosty average molar mass, (d) Z- Average molar mass Number Average Molar

More information

Property Estimation of Commercial Ecological Gasoline

Property Estimation of Commercial Ecological Gasoline 247 A publcaton of CHEMICAL ENGINEERINGTRANSACTIONS VOL. 43, 205 Chef Edtors:Sauro Perucc, JříJ. Klemeš Copyrght 205, AIDIC Servz S.r.l., ISBN 978-88-95608-34-; ISSN 2283-926 The Italan Assocaton of Chemcal

More information

Applied Mathematics Letters

Applied Mathematics Letters Appled Matheatcs Letters 2 (2) 46 5 Contents lsts avalable at ScenceDrect Appled Matheatcs Letters journal hoepage: wwwelseverco/locate/al Calculaton of coeffcents of a cardnal B-splne Gradr V Mlovanovć

More information

Credit Card Pricing and Impact of Adverse Selection

Credit Card Pricing and Impact of Adverse Selection Credt Card Prcng and Impact of Adverse Selecton Bo Huang and Lyn C. Thomas Unversty of Southampton Contents Background Aucton model of credt card solctaton - Errors n probablty of beng Good - Errors n

More information

PORE STRUCTURE AND THERMAL CONDUCTIVITY OF BURNT CLAY BRICKS INTRODUCTION

PORE STRUCTURE AND THERMAL CONDUCTIVITY OF BURNT CLAY BRICKS INTRODUCTION PORE STRUCTURE AND THERMAL CONDUCTIVITY OF BURNT CLAY BRICKS Olga Koronthalyova, Peter Matasovsky Insttute of Constructon and Archtecture, Slovak Academy of Scences, Dubravska 9, 845 43 Bratslava, Slovaka.

More information

Using T.O.M to Estimate Parameter of distributions that have not Single Exponential Family

Using T.O.M to Estimate Parameter of distributions that have not Single Exponential Family IOSR Journal of Mathematcs IOSR-JM) ISSN: 2278-5728. Volume 3, Issue 3 Sep-Oct. 202), PP 44-48 www.osrjournals.org Usng T.O.M to Estmate Parameter of dstrbutons that have not Sngle Exponental Famly Jubran

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

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

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

Statistics II Final Exam 26/6/18

Statistics II Final Exam 26/6/18 Statstcs II Fnal Exam 26/6/18 Academc Year 2017/18 Solutons Exam duraton: 2 h 30 mn 1. (3 ponts) A town hall s conductng a study to determne the amount of leftover food produced by the restaurants n the

More information

A Note on Bound for Jensen-Shannon Divergence by Jeffreys

A Note on Bound for Jensen-Shannon Divergence by Jeffreys OPEN ACCESS Conference Proceedngs Paper Entropy www.scforum.net/conference/ecea- A Note on Bound for Jensen-Shannon Dvergence by Jeffreys Takuya Yamano, * Department of Mathematcs and Physcs, Faculty of

More information

System in Weibull Distribution

System in Weibull Distribution Internatonal Matheatcal Foru 4 9 no. 9 94-95 Relablty Equvalence Factors of a Seres-Parallel Syste n Webull Dstrbuton M. A. El-Dacese Matheatcs Departent Faculty of Scence Tanta Unversty Tanta Egypt eldacese@yahoo.co

More information

A new Approach for Solving Linear Ordinary Differential Equations

A new Approach for Solving Linear Ordinary Differential Equations , ISSN 974-57X (Onlne), ISSN 974-5718 (Prnt), Vol. ; Issue No. 1; Year 14, Copyrght 13-14 by CESER PUBLICATIONS A new Approach for Solvng Lnear Ordnary Dfferental Equatons Fawz Abdelwahd Department of

More information

Non-Ideality Through Fugacity and Activity

Non-Ideality Through Fugacity and Activity Non-Idealty Through Fugacty and Actvty S. Patel Deartment of Chemstry and Bochemstry, Unversty of Delaware, Newark, Delaware 19716, USA Corresondng author. E-mal: saatel@udel.edu 1 I. FUGACITY In ths dscusson,

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

The Jacobsthal and Jacobsthal-Lucas Numbers via Square Roots of Matrices

The Jacobsthal and Jacobsthal-Lucas Numbers via Square Roots of Matrices Internatonal Mathematcal Forum, Vol 11, 2016, no 11, 513-520 HIKARI Ltd, wwwm-hkarcom http://dxdoorg/1012988/mf20166442 The Jacobsthal and Jacobsthal-Lucas Numbers va Square Roots of Matrces Saadet Arslan

More information

Comparative Studies of Law of Conservation of Energy. and Law Clusters of Conservation of Generalized Energy

Comparative Studies of Law of Conservation of Energy. and Law Clusters of Conservation of Generalized Energy Comparatve Studes of Law of Conservaton of Energy and Law Clusters of Conservaton of Generalzed Energy No.3 of Comparatve Physcs Seres Papers Fu Yuhua (CNOOC Research Insttute, E-mal:fuyh1945@sna.com)

More information

If two volatile and miscible liquids are combined to form a solution, Raoult s law is not obeyed. Use the experimental data in Table 9.

If two volatile and miscible liquids are combined to form a solution, Raoult s law is not obeyed. Use the experimental data in Table 9. 9.9 Real Solutons Exhbt Devatons from Raoult s Law If two volatle and mscble lquds are combned to form a soluton, Raoult s law s not obeyed. Use the expermental data n Table 9.3: Physcal Chemstry 00 Pearson

More information

Pop-Click Noise Detection Using Inter-Frame Correlation for Improved Portable Auditory Sensing

Pop-Click Noise Detection Using Inter-Frame Correlation for Improved Portable Auditory Sensing Advanced Scence and Technology Letters, pp.164-168 http://dx.do.org/10.14257/astl.2013 Pop-Clc Nose Detecton Usng Inter-Frame Correlaton for Improved Portable Audtory Sensng Dong Yun Lee, Kwang Myung Jeon,

More information

Chapter 6. Supplemental Text Material

Chapter 6. Supplemental Text Material Chapter 6. Supplemental Text Materal S6-. actor Effect Estmates are Least Squares Estmates We have gven heurstc or ntutve explanatons of how the estmates of the factor effects are obtaned n the textboo.

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

COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS

COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS Avalable onlne at http://sck.org J. Math. Comput. Sc. 3 (3), No., 6-3 ISSN: 97-537 COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS

More information

Orientation Model of Elite Education and Mass Education

Orientation Model of Elite Education and Mass Education Proceedngs of the 8th Internatonal Conference on Innovaton & Management 723 Orentaton Model of Elte Educaton and Mass Educaton Ye Peng Huanggang Normal Unversty, Huanggang, P.R.Chna, 438 (E-mal: yepeng@hgnc.edu.cn)

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

y i x P vap 10 A T SOLUTION TO HOMEWORK #7 #Problem

y i x P vap 10 A T SOLUTION TO HOMEWORK #7 #Problem SOLUTION TO HOMEWORK #7 #roblem 1 10.1-1 a. In order to solve ths problem, we need to know what happens at the bubble pont; at ths pont, the frst bubble s formed, so we can assume that all of the number

More information

Lecture 16 Statistical Analysis in Biomaterials Research (Part II)

Lecture 16 Statistical Analysis in Biomaterials Research (Part II) 3.051J/0.340J 1 Lecture 16 Statstcal Analyss n Bomaterals Research (Part II) C. F Dstrbuton Allows comparson of varablty of behavor between populatons usng test of hypothess: σ x = σ x amed for Brtsh statstcan

More information

Neryškioji dichotominių testo klausimų ir socialinių rodiklių diferencijavimo savybių klasifikacija

Neryškioji dichotominių testo klausimų ir socialinių rodiklių diferencijavimo savybių klasifikacija Neryškoj dchotomnų testo klausmų r socalnų rodklų dferencjavmo savybų klasfkacja Aleksandras KRYLOVAS, Natalja KOSAREVA, Julja KARALIŪNAITĖ Technologcal and Economc Development of Economy Receved 9 May

More information

Binomial transforms of the modified k-fibonacci-like sequence

Binomial transforms of the modified k-fibonacci-like sequence Internatonal Journal of Mathematcs and Computer Scence, 14(2019, no. 1, 47 59 M CS Bnomal transforms of the modfed k-fbonacc-lke sequence Youngwoo Kwon Department of mathematcs Korea Unversty Seoul, Republc

More information

DERIVATION OF THE PROBABILITY PLOT CORRELATION COEFFICIENT TEST STATISTICS FOR THE GENERALIZED LOGISTIC DISTRIBUTION

DERIVATION OF THE PROBABILITY PLOT CORRELATION COEFFICIENT TEST STATISTICS FOR THE GENERALIZED LOGISTIC DISTRIBUTION Internatonal Worshop ADVANCES IN STATISTICAL HYDROLOGY May 3-5, Taormna, Italy DERIVATION OF THE PROBABILITY PLOT CORRELATION COEFFICIENT TEST STATISTICS FOR THE GENERALIZED LOGISTIC DISTRIBUTION by Sooyoung

More information

ARTICLE IN PRESS. Fluid Phase Equilibria 275 (2008) Contents lists available at ScienceDirect. Fluid Phase Equilibria

ARTICLE IN PRESS. Fluid Phase Equilibria 275 (2008) Contents lists available at ScienceDirect. Fluid Phase Equilibria Flud Phase Equlbra 275 (2008) 33 38 Contents lsts avalable at ScenceDrect Flud Phase Equlbra journal homepage: www.elsever.com/locate/flud Solubltes of cnnamc acd, phenoxyacetc acd and 4-methoxyphenylacetc

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

Non-Commercial Use Only

Non-Commercial Use Only Plottng P-x-y dagram for bnary system Acetone/water at temperatures 25,100,and 200 C usng UNIFAC method and comparng t wth expermental results. Unfac Method: The UNIFAC method s based on the UNIQUAC equaton,

More information

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

and Statistical Mechanics Material Properties

and Statistical Mechanics Material Properties Statstcal Mechancs and Materal Propertes By Kuno TAKAHASHI Tokyo Insttute of Technology, Tokyo 15-855, JAPA Phone/Fax +81-3-5734-3915 takahak@de.ttech.ac.jp http://www.de.ttech.ac.jp/~kt-lab/ Only for

More information

Statistics Chapter 4

Statistics Chapter 4 Statstcs Chapter 4 "There are three knds of les: les, damned les, and statstcs." Benjamn Dsrael, 1895 (Brtsh statesman) Gaussan Dstrbuton, 4-1 If a measurement s repeated many tmes a statstcal treatment

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

A novel mathematical model of formulation design of emulsion explosive

A novel mathematical model of formulation design of emulsion explosive J. Iran. Chem. Res. 1 (008) 33-40 Journal of the Iranan Chemcal Research IAU-ARAK www.au-jcr.com A novel mathematcal model of formulaton desgn of emulson explosve Mng Lu *, Qfa Lu Chemcal Engneerng College,

More information

Thermodynamic Modeling and Simulation of Biodiesel Systems at Supercritical Conditions

Thermodynamic Modeling and Simulation of Biodiesel Systems at Supercritical Conditions Cte Ths: pubs.acs.org/iecr Thermodynamc Modelng and Smulaton of Bodesel Systems at Supercrtcal Condtons Pedro F. Arce,* Nan F. Vera, and Edson M. S. Igarash Chemcal Engneerng Department, Engneerng School

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

Convexity preserving interpolation by splines of arbitrary degree

Convexity preserving interpolation by splines of arbitrary degree Computer Scence Journal of Moldova, vol.18, no.1(52), 2010 Convexty preservng nterpolaton by splnes of arbtrary degree Igor Verlan Abstract In the present paper an algorthm of C 2 nterpolaton of dscrete

More information

PART I: MULTIPLE CHOICE (32 questions, each multiple choice question has a 2-point value, 64 points total).

PART I: MULTIPLE CHOICE (32 questions, each multiple choice question has a 2-point value, 64 points total). CHEMISTRY 123-07 Mdterm #2 answer key November 04, 2010 Statstcs: Average: 68 p (68%); Hghest: 91 p (91%); Lowest: 37 p (37%) Number of students performng at or above average: 58 (53%) Number of students

More information

Economics 130. Lecture 4 Simple Linear Regression Continued

Economics 130. Lecture 4 Simple Linear Regression Continued Economcs 130 Lecture 4 Contnued Readngs for Week 4 Text, Chapter and 3. We contnue wth addressng our second ssue + add n how we evaluate these relatonshps: Where do we get data to do ths analyss? How do

More information

The Two-scale Finite Element Errors Analysis for One Class of Thermoelastic Problem in Periodic Composites

The Two-scale Finite Element Errors Analysis for One Class of Thermoelastic Problem in Periodic Composites 7 Asa-Pacfc Engneerng Technology Conference (APETC 7) ISBN: 978--6595-443- The Two-scale Fnte Element Errors Analyss for One Class of Thermoelastc Problem n Perodc Compostes Xaoun Deng Mngxang Deng ABSTRACT

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

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

ALGORITHM FOR THE CALCULATION OF THE TWO VARIABLES CUBIC SPLINE FUNCTION

ALGORITHM FOR THE CALCULATION OF THE TWO VARIABLES CUBIC SPLINE FUNCTION ANALELE ŞTIINŢIFICE ALE UNIVERSITĂŢII AL.I. CUZA DIN IAŞI (S.N.) MATEMATICĂ, Tomul LIX, 013, f.1 DOI: 10.478/v10157-01-00-y ALGORITHM FOR THE CALCULATION OF THE TWO VARIABLES CUBIC SPLINE FUNCTION BY ION

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

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

CALCULATION OF ACID GAS DENSITY IN THE VAPOR, LIQUID, AND DENSE-PHASE REGIONS

CALCULATION OF ACID GAS DENSITY IN THE VAPOR, LIQUID, AND DENSE-PHASE REGIONS CALCULATION OF ACID GAS DENSITY IN THE VAPOR, LIQUID, AND DENSE-PHASE REGIONS Tm B. Boyle PanCanadan Petroleum Ltd. 150-9 Avenue SW Calgary, Alberta TP 1S John J. Carroll Gas Lquds Engneerng Ltd. #300,

More information

Statistics for Economics & Business

Statistics for Economics & Business Statstcs for Economcs & Busness Smple Lnear Regresson Learnng Objectves In ths chapter, you learn: How to use regresson analyss to predct the value of a dependent varable based on an ndependent varable

More information

Heuristic Algorithm for Finding Sensitivity Analysis in Interval Solid Transportation Problems

Heuristic Algorithm for Finding Sensitivity Analysis in Interval Solid Transportation Problems Internatonal Journal of Innovatve Research n Advanced Engneerng (IJIRAE) ISSN: 349-63 Volume Issue 6 (July 04) http://rae.com Heurstc Algorm for Fndng Senstvty Analyss n Interval Sold Transportaton Problems

More information