The thermodynamics of alcohols-hydrocarbons mixtures

Size: px
Start display at page:

Download "The thermodynamics of alcohols-hydrocarbons mixtures"

Transcription

1 MATEC Web of Conferences 3, (2013) DOI: / matecconf/ C Owned by the authors, publshed by EDP Scences, 2013 The thermodynamcs of alcohols-hydrocarbons mxtures R. Prvat 1, J.-N. Jaubert 1, and M. Molère 2 1 Laboratore Réactons et Géne des Procédés (LRGP), Unversté de Lorrane, Nancy 54000, France 2 GE Energy Products Europe, 20 Avenue du Maréchal Jun, BP 379, Belfort Cedex, France Alcohols/hydrocarbons blends represent mportant products n the ndustry and remarkable systems from the thermodynamc standpont, especally n presence of traces of water. In automotve applcatons, ethanol s ncorporated n ncreasng proportons nto car fuel formulatons for envronmental and economc reasons. From a thermodynamc vewpont, the strongly polar nature of ethanol versus the rather apolar character of hydrocarbons makes the study of such blends partcularly nterestng n terms of vapor pressure and mscblty behavor. A long term collaboraton between GE Energy- Europe (Belfort, France) and the Thermodynamcs Team of the LRGP laboratory (Nancy, France) has been conducted to mprove the knowledge of these systems, usng the UNIFAC thermodynamc theory. Frst, blends of anhydrous ethanol and naphtha class hydrocarbons have been studed n terms of volatlty: a strong lqud/vapor non-dealty effect has been put n evdence and numercally characterzed. In a further step, blends of hydrated ethanol and hydrocarbons featurng dverse compostons have been the matter of a thermodynamc modelng that confrmed the paramount role played by the mosture content of ethanol on the mscblty, usng the Maxmum Mscblty Temperature ( TMM ) concept; ths study also ponted out the non-neglgble nfluence of the PONA data and sulfur speces of the hydrocarbon cut. Later on, other alcohols namely methanol, sopropanol and n-butanol, that may play an mportant role n future green fuel formulatons, were ncluded n ths study that showed an nterestng chan length effect. Recently, the team has started a study of the effect of bodesel addtons on the TMM of hydrated alcoholhydrocarbon mxtures. Ths paper summarzes the methodology and the results of the mult-step, collaboratve modelng study developed n the feld of ethanol/hydrocarbon thermodynamcs. hydrocarbon car fuels and ncrease ther octane number (RON) whle mprovng vehcle emssons. Industral alcohols often contan a non-neglgble amount of water (that can reach 10 % n mass). From a thermodynamc pont of vew, the addton of an ndustral alcohol (even n small quanttes) to a gasolne or a gasol strongly mpacts on all phase equlbra. GE and the thermodynamc team of the LRGP are conductng a collaboratve, mult-year program amed at studyng these systems wth a specal emphass placed on the vapor pressure and the mscblty behavour. In 2009, the team carred out a frst study devoted to the change n vapor pressure caused by the ncorporaton of anhydrous ethanol nto a naphtha cut taken as surrogate for a commercal gasolne. In 2010, the thematc of the alcohols/gasol mscblty was tackled and led to study the nfluence of the type of alcohol and ts water content on ts mscblty wth selected gasol cuts featurng varous compostons (paraffn/ aromatcs/ naphthenes dstrbuton; sulphur compounds). Snce the openlterature contans very few expermental data n ths area, the strategy has been n favor of a theoretcal approach. Four ndustral alcohols (methanol, ethanol, sopropanol or 1-butanol) featurng varous water contents and four commercal gasol wth defned hydrocarbon dstrbutons were ncluded n ths study. 2 Vapor pressure of ethanol-naphtha blends The theoretcal approach s based on the 1978 verson of the Peng and Robnson equaton of state [1], noted PR78 n ths paper. More nformaton on the theoretcal model s avalable n [2]. Fgure 1 shows a plot of the vapour pressure data computed for blends contanng varable proportons of anhydrous ethanol and a naphtha consstng n 18% n- hexane and 82% n-heptane by weght. 1 Introducton In recent years, the quest for sustanable prmary energes has ncreased the potental nterest of bogenc/fossl fuels mxes. In ths context, lght alcohols are often used as gasolne extenders to both partly substtute for Ths s an Open Access artcle dstrbuted under the terms of the Creatve Commons Attrbuton Lcense 2. 0, whch permts unrestrcted use, dstrbuton, and reproducton n any medum, provded the orgnal work s properly cted. Artcle avalable at or

2 MATEC Web of Conferences Ths fgure demonstrates the hghly non-deal behavor of these blends: for nstance, for a blend contanng 17% ethanol, a calculaton assumng an deal behavour (Raoult s law) would lead to undervalue the vapour pressure by 51% (table 1). These results are very mportant from a safety standpont snce the Lower and Upper Flammablty Lmts depend on the vapour pressure; they are also relevant for the selecton of the rght naphtha cuts when one wshes to prepare ethanol/gasolnes blends havng sutable volatlty for cars (e.g. E10 ). Fgure 1. Vapor pressure devaton from dealty for a naphtha/ethanol blend. Table 1. Vapor pressure of tanks contanng () naphtha, () ethanol and () a gven naptha-ethanol blend (27 C, 70 % full tank). Lqud (% mass) () Naphtha: (18 %C %C 7 ) () 100% EtOH () 83 % napththa + 17 % EtOH Real (computed) Idealty hypothess Relatve dfference Vapor pressure (mbar) % 3 Alcohol-gasol mscblty study In ths paper, we wll use a pseudo-bnary system made by the hydrocarbon mxture consttutng the gasol, on one hand, and the alcohol/water mxture (also called hydrated alcohol or ndustral alcohol ), on another hand. To characterze the mscblty behavour of such gasol/alcohol/water systems, t s convenent to access to the so-called Mnmum Mscblty Temperature ( MMT ) whch s the lowest temperature at whch the fluds are fully mscble, regardless of the proporton of ndustral alcohol. For any temperature below the MMT, addton of ndustral alcohol to the gasol may gve rse to two lqud phases n equlbrum whle, for any temperature above the MMT, the mxture cannot unmx anymore, as llustrated n fgure 2. lqud phase s stable the lqud phase may unmx for a range of x values 1 lqud phase 1 lqud phase 2 lqud phases T/K MMT Mole fracton of ndustral alcohol x 1 The sketch of fgure 2 has large commonaltes wth classcal lqud-lqud phase dagrams of bnary systems n whch () the maxmum of the saturaton curve s actually a lqud-lqud crtcal pont (and s called UCST for upper crtcal soluton temperature, nstead of MMT) and () t s possble to draw a horzontal te-lne at a gven temperature. However, snce the pseudo-bnary gasol/ndustral alcohol systems nvolve many compounds, t s no longer possble to draw horzontal te-lnes; n addton, the maxmum of the saturaton curve s not a crtcal pont anymore (a crtcal pont may exst anywhere on the saturaton curve). The openlterature s very poor n MMT data for gasol/ndustral alcohols systems. For ths reason, we decded to use an effcent predctve thermodynamc model, called UNIFAC for representng the behavor of the fluds of nterest. Ths model reles on the group-contrbuton concept and s able to account for the effects of: () the nature of the alcohol and () addtons of small amounts of water n the alcohol. In studyng four gasols (noted GO1, GO2, GO3 and GO4) havng dfferent compostons, t s possble to nvestgate the nfluence of the paraffnc, aromatc, naphthenc and sulphur contents. The rough compostons of these four gasols are gven table 1. As we wll work wth condensed lqud phases, the pressure effect wll be neglected throughout ths study. 0.0 Fgure 2. Pseudo-bnary phase dagram for a mxture of gasol and ndustral alcohol. The bell s the boundary between the sngle lqud and the two-lqud felds (saturaton curve). MMT s the summt of the saturaton curve p.2

3 39 th JEEP 19 th - 21 st March 2013 Nancy Table 2. Compostons of the four studed gasols Compounds GO1 GO2 GO3 GO4 Paraffnc 16 % 10.5 % 84 % 90 % Aromatc 84 % 82 % 16 % 8 % Naphthenc % Sulphur % The Group-Contrbuton concept 4.1 General aspects The group-contrbuton (GC) approach s a relatvely recent concept [1-17] whch orgnally amed at predctng the physcal propertes of pure molecules startng from ther chemcal structures. The applcaton of the GC concept to mxtures s actually an extenson of the GC concept for sngle molecules [3, 18]. The basc dea of any group-contrbuton method s that, whereas there are thousands of chemcal molecules, the number of functonal groups that consttute them s very lmted. Assumng that a physcal property of a flud s the sum of contrbutons made by the molecule s functonal groups, one can use a GC method to correlate the propertes of a very large number of fluds based on a much smaller number of parameters. These GC parameters characterze the contrbutons of ndvdual groups n the propertes. In ths paper, a predctve thermodynamc model based on the GC concept, named UNIFAC, s used for calculatng lqud-lqud phase equlbra of complex gasol/alcohol/water mxtures. 4.2 Outlnes of the UNIFAC method Ths model enables the estmaton of the complete sets of actvty coeffcents of all the components n a mxture, wthout fttng any model parameter from lqud-lqud expermental data. The mere knowledge of the chemcal structure of all the compounds n the mxture s enough to predct phase equlbra. Based on the mathematcal formulaton of the non-predctve UNIQUAC model, the UNIFAC model can be seen as a predctve verson of ths last model. The UNIQUAC equaton often gves good representatons of vapor-lqud and lqud-lqud equlbra for bnary and multcomponent mxtures contanng a varety of non-electrolytes, such as for nstance hydrocarbons and alcohols. The molecular actvty coeffcent s break down nto two parts: one part provdes the contrbuton due to dfferences n molecular sze and shape ( the combnatoral part ), and the other provdes the contrbuton due to molecular nteractons ( the resdual part ). In a multcomponent mxture, the UNIFAC equaton for the actvty coeffcent of component wrtes: comb res ln ln ln (1) res The calculaton of ln requres the knowledge of energy group-nteracton parameters a mn, the values of whch were estmated from phase equlbrum data regresson by Fredenslund et al. [18]. Note however that some amn values were reftted by ths team n prevous works (GT and GT ) for selected chemcal groups nvolved n gasol/alcohol mxtures; more detals about the UNIFAC model are avalable n these references. 5 Lqud-lqud phase dagrams for multcomponent systems Due to the hgh number of compounds contaned n gasol/ndustral alcohol mxtures (between 30 and 50 n the present case), the calculaton of the saturaton curve s a much more complcated and tme-consumng task than for actual bnary systems. Ths secton s thus devoted to explan the optons used to perform fast and relable calculatons of saturaton curves n a reasonable tme. 5.1 Drect calculaton of the saturaton curve In ths secton, the gasol composton s assumed to be known. Let us defne a system resultng from the mxng of a gven amount of ndustral alcohol (fully defned n terms of composton) wth a gven amount of gasol. The overall mole fracton vector z of such a system s thus completely characterzed; let us also denote z alcohol, the overall composton of the ndustral alcohol. The system s a sngle, stable lqud phase at hgh temperature and gves rse to a lqud-lqud equlbrum at low temperature. The saturaton pont s defned as the transton state between the sngle-lqud state and the lqud-lqud equlbrum state. Let us denote T* the saturaton temperature. The calculaton of a saturaton pont (.e. a pont of the saturaton curve) s llustrated n fgure 3. Fgure 3. Drect calculaton of the saturaton pont at a fxed overall composton z p.3

4 MATEC Web of Conferences A saturaton pont corresponds to two lqud phases n equlbrum, the frst one havng a known composton z and the second one havng an unknown composton x. The unknown varables T* and x can be determned by solvng the followng set of equatons: N 1 * * z a (T, ) a (T, x), for all 1;...; N x 1 (2) where a s the actvty of component calculated from the UNIFAC model and N s the total number of compounds contaned n the mxture. The frst lne of the equaton set (2) s obtaned by equatng the chemcal potental of component n the two lqud phases, whch expresses the lqud-lqud equlbrum condton). The second lne expresses the normalzaton of the molar fractons. To facltate the resoluton of the equaton set (2), one can rewrte t as an optmzaton problem, e.g.: * T, x * * z Mn a (T, ) - a (T, x) under the constrant x = 1 N =1 2 (3) Dong so, classcal optmzaton procedures (such as e.g. quas-newton methods) can be appled to determne T* and x. In the present case, the SLSQP (Sequental Least Squares Quadratc Programmng), optmzaton algorthm was used and led generally to satsfactorly results. Of course, when drawng the complete saturaton lne, the calculaton of a gven saturaton pont can be easly ntalzed from varables T* and x of the prevous saturaton pont. However, the ntalzaton procedure of the frst calculated saturaton pont remans an entre problem. Despte generally satsfactory results, t was observed that the resoluton of eq. (3) usng the SLSQP procedure was lkely to fal when: - the saturaton pont to be calculated s very close to a lqud-lqud crtcal pont (such that the two lqud phases n equlbrum have the same composton,.e. x = z) - several lqud-lqud equlbra exst at a gven overall composton z; when ths stuaton occurs, one lqud-lqud equlbra s declared stable (the one assocated to the lowest Gbbs energy value) and the other ones are declared non-stable. Each tme a drect calculaton of a saturaton pont faled, another procedure based on a flash algorthm calculaton was run. Such a combnaton of these two procedures allowed us to successfully plot the saturaton curves of all the consdered gasol/ndustral alcohol systems wthn a reasonable tme (less than 1 mnute for each curve contanng 150 ponts). Note that the flash algorthm can also be used to ntalze the frst calculated pont of the saturaton curve. 5.2 Indrect calculaton of the saturaton curve usng a flash-calculaton based procedure A lqud-lqud flash calculaton s a classcal algorthm amed at determnng whether a multcomponent lqud mxture gves rse to a lqud-lqud equlbrum at a gven temperature and overall composton z. If so, the flash calculaton provdes the composton of the phases as well as ther proportons. As llustrated n fgure 4, t s possble to use ths knd of calculaton to determne the saturaton temperature T*. Fgure 4. Indrect calculaton of the saturaton pont at a fxed overall composton z. To do so, t s necessary to perform a seres of flash calculatons n order to determne two temperatures T (1) and T (2) such that: T (2) < T* < T (1) where T (1) s a temperature at whch the system conssts of a sngle lqud phase and T (2) s a temperature at whch the system conssts of two lqud phases n equlbrum. The saturaton temperature T*, whch s the transton temperature between a 2-phase and a 1-phase system, can be accurately calculated usng, for nstance, a dchotomc procedure. 5.3 Flash calculaton Let us consder an N-component system havng an overall composton z and gvng rse to a lqud-lqud equlbrum (the two lqud phases n equlbrum are denoted and β). To perform a flash calculaton, a set of (2N + 2) equatons has to be solved: a (T, x ) a (T, x ), 1;...;N,, N 1 N 1,, α z x x, 1;...;N x 1 x 1 β (4) p.4

5 39 th JEEP 19 th - 21 st March 2013 Nancy where and are the proportons of the lqud phases and β and the compostons of these two lqud phases are noted x and x β. To solve the set of equatons (4), the well-known Rce-Rachford procedure can be appled. 6 nfluence of the alcohol and the water content on the MMT In ths study, four real commercal gasols (GO1, GO2, GO3 and GO4) were selected; ther detaled compostons are gven n table 3. These types of gasols were taken because they contan dfferent amounts of paraffnc, aromatc, naphthenc and sulphur compounds. The frst gasol (GO1) contans 84 % of aromatc compounds, 16 % of paraffnc compounds and no sulphur speces. GO2 s smlar to GO1 but contans 7.5 % of sulphur compounds. On the contrary, GO3 and GO4 contan large amounts of paraffnc compounds (more than 80 %), and small quanttes of aromatcs. GO4 has the partcularty to contan a small amount of naphthenc hydrocarbons. It s thus possble to evaluate how these chemcal famles mpact on the MMT value of gasol/ndustral alcohol mxtures. The frst task s the calculaton of the lqud-lqud phase dagram usng the UNIFAC model. 6.1 Addton of four dfferent ndustral alcohols n gasol GO1 The hghest temperature at whch the phase splt occurs.e. the MMT has been calculated. The correspondng phase dagrams are shown n fgure 5 and the correspondng MMT are gven n table 4. Table 4. MMT values for gasol GO1 mxed wth the four alcohols havng varous H2O contents. % H 2 O (mass) methanol ethanol sopropanol butanol Fgure 5. Phase dagrams for GO1 mxed wth 4 alcohols contanng from 1 to 10 % water (n abscssa: mole fracton of hydrated alcohol). For any alcohol content, one observes that: - the MMT systematcally ncreases wth the proporton of water n the alcohol - the heaver the alcohol, the stronger ths ncrease; thus, when the water percent goes from 1 to 10 %, the MMT (n K) s multpled by: 1.3 for the methanol; 2.1 for the ethanol; 2.7 for the sopropanol and for 1- butanol. The changes of MMT wth the alcohol mass water contents are represented n fgure 6. As t can be observed, the smallest MMT values are obtaned wth heavy alcohols havng small water contents p.5

6 MATEC Web of Conferences Table 3. Specated analyses of the four gasols. Components GO1 GO2 GO3 GO4 1,4-dmethyl benzene (para-xylene) ethyl-3-methyl benzene ,2,3-trmethyl benzene benzocyclopentane (ndane) methyl-1-propyl benzene ethyl-1,2-dmethyl benzene ,2,4,5-tetramethyl benzene methyl-4-(2-propenyl) benzene methyl-1-butyl Benzene Naphthalene ,3-dhydro-1,2-dmethyl 1H-ndene methyl naphthalene ethyl naphthalene 2.9 1,2-dmethyl naphthalene ,4-dhydro-1,4-methano naphthalene ,3,6-trmethyl naphthalene 15.7 n-pentadecane fluorene methyl-1-ethyl naphthalene methyl bphenyle n-hexadecane ethyl-1,4-dethyl azulene ,2-dmethyl bphenyle n-heptadecane phenanthrene n-octadecane methyl phenanthrene n-nonadecane ,10-dmethyl anthracene n-ecosane n-henecosane n-docosane n-trcosane n-tetracosane (n-pentacosane) (0.3) 0.9 2,3-dhydro-1-methyl ndene 0.6 para-dsopropyl benzene 0.5 n-octane 6.25 n-nonane n-decane n-undecane n-dodecane (n-trdecane) 9.8 (8.6) n-tetradecane n-hexacosane (n-heptacosane) 0.3 (0.3) 1-methylethyl cyclohexane 0.6 octyl cyclohexane 0.6 decyl cyclohexane 0.5 benzothophene 0.5 methyl benzothophene 0.9 dmethyl benzothophene 3.0 dbenzo thophene 0.9 thoxanthene p.6

7 39 th JEEP 19 th - 21 st March 2013 Nancy As prevously, for any alcohol content, one observes that: - the MMT ncreases wth the proporton of water n the alcohol, - the heaver the alcohol, the hgher ths ncrease; thus, when the water percentage goes from 1 to 10 %, the MMT (n K) s multpled by: 1.2 for methanol; 2.0 for ethanol; 2.5 for sopropanol and 2.7 for the 1- butanol. The change of MMT wth mass water contents the varous alcohol s represented n fgure 8. Fgure 6. Change of the MMT of the four GO1/alcohols wth the water content of the alcohol. 6.2 Addton of four dfferent ndustral alcohols n gasol GO2 The MMT data are gven n table 5 and the correspondng phase dagrams can be seen n fgure 7. Table 5. MMT values for gasol GO2 mxed wth the four alcohols havng varous H 2 O contents. % H 2 O (mass) methanol ethanol sopropanol butanol Fgure 8. Change of the MMT of the four GO 2/alcohols systems wth the water content of the alcohol. Here, the conclusons are exactly the same as wth gasol GO1. Due to the dfferent compostons of the gasol, the MMT values are however hgher than wth gasol GO1. Fgure 7. Phase dagrams for GO2 mxed wth 4 alcohols contanng from 1 to 10 % water (n abscssa: mole fracton of hydrated alcohol) p.7

8 MATEC Web of Conferences 6.3 Addton of four dfferent ndustral alcohols n gasol GO3 The phase dagrams can be seen n fgures 9 and 10 and the correspondng MMT are gven n table 6. Table 6. MMT values for gasol GO3 mxed wth the four alcohols havng varous H2O contents. % H 2 O (mass) methanol ethanol sopropanol 1-butanol Conclusons are the same as wth GO1 and GO2. When the water percent goes from 1 to 10 %, the MMT (n K) s multpled by: 1.5 for methanol; 2.6 for the ethanol; 3.3 for sopropanol and 3.4 for 1-butanol. Fgure 10. Change of the MMT of the four GO 3/alcohols systems wth the water content of the alcohol. Fgure 9. Phase dagrams for GO3 mxed wth 4 alcohols contanng from 1 to 10 % water (n abscssa: mole fracton of hydrated alcohol). 6.4 Addton of dfferent ndustral alcohols n gasol GO4 Phase dagrams can be seen n fgures 11 and 12 and the correspondng MMT are gven n table 7. Conclusons are the same as wth GO1, GO2 and GO3. When the water percent goes from 1 to 10 %, the MMT (n K) s multpled by: 1.6 for methanol; 2.7 for ethanol; 3.6 for sopropanol and 4.9 for 1-butanol p.8

9 39 th JEEP 19 th - 21 st March 2013 Nancy Fgure 11. Phase dagrams for GO4 mxed wth 4 alcohols contanng from 1 to 10 % water (n abscssa: mole fracton of hydrated alcohol). 7 nfluence of gasol composton on the MMT From the results above, t s possble to draw the nfluence of gasol compostons on the MMT, for a gven alcohol. It s remembered that these compostons are summarzed n tables 1 and 2. Results are syntheszed n fgure 13 and are dscussed n the concluson. Fgure 12. Change of the MMT of the four GO 4/alcohols systems wth the water content of the alcohol. Table 7. MMT values for gasol GO4 mxed wth the four alcohols havng varous H2O contents. % H 2 O (mass) methanol ethanol sopropanol Butanol Fgure 13. Results summary; Legend: PAR: paraffns; Aro: aromatcs; Nap: naphthenes; S: sulphur; Uppercases: major compounds; n parentheses: mnor compounds p.9

10 MATEC Web of Conferences 8 Concluson Ths collaboratve, multstep study was ntended to progress n the thermodynamc descrpton of alcoholhydrocarbons mxtures n presence or absence of water. In a frst step, we have ponted out the strongly non-deal behavor of ethanol-naphtha blends n terms of vapor pressure. The second step was devoted to provdng general gudelnes for preparng mxtures of gasols wth ndustral alcohols dsplayng low Mnmum Mscblty Temperature (MMT) data. It must be stressed that the MMT values computed n the present paper are sometmes qute hgh and above the stablty temperature of the related alcohols; ths ponts out the essentally theoretcal reach of the present study, whch owes ts man nterest to the man trends observed: 1- wth slghtly hydrated alcohols: t s preferable to use heavy alcohols. As the alcohol molecules gets close, n sze, to the hydrocarbons contaned n the gasols, they are better solublzed. It s also preferable to use a gasol featurng a hghly aromatc character and substantal sulphur content n order to prevent any lqud-lqud phase splt. Naphthenc compounds should be dscarded. The mxtures of 1-butanol wth GO4 llustrate well these nferences. 2- wth strongly hydrated alcohols: ths tme, t s preferable to select lght alcohols (methanol or ethanol) n order the alcohol molecule sze becomes closer to that of the water molecule. Then, water gets more easly solublzed n the alcohol. Here agan, t s preferable to take gasols havng substantal aromatc contents and some sulphur contanng molecules havng more affnty wth polar speces (water and ethanol) than paraffnc compounds. Once agan, naphthenc compounds have to be dscarded. The mxtures of ethanol wth GO1 llustrate well these nferences. As next steps, ths study wll be followed by () an expermental work devoted to the verfcaton of these man theoretcal results and () a further study of the effect of ntroducng alkyl esters n the gasols/hydrated alcohols blends. 2. L. Constantnou, R. Gan, AIChE J. 40(10) 1697 (1994) 3. J.N. Jaubert, F. Mutelet, Flud Phase Equlbra (2004) 4. J.N. Jaubert, S. Vtu, F. Mutelet, J.P. Corrou, Flud Phase Equlbra (2005) 5. S. Vtu, J.N. Jaubert, F. Mutelet, Flud Phase Equlbra (2006) 6. S. Vtu, R. Prvat, J.N. Jaubert, F. Mutelet, Journal of Supercrtcal Fluds 45 1 (2008) 7. R. Prvat, J.N. Jaubert, F. Mutelet, Industral & Engneerng Chemstry Research (2008) 8. R. Prvat, J.N. Jaubert, F. Mutelet, Industral & Engneerng Chemstry Research (2008) 9. R. Prvat, J.N. Jaubert, F. Mutelet, Journal of Chemcal Thermodynamcs (2008) 10. R. Prvat, F. Mutelet, J.N. Jaubert, Industral & Engneerng Chemstry Research (2008) 11. J.N. Jaubert, R. Prvat, F. Mutelet, AIChE Journal (2010) 12. R. Prvat, J.N. Jaubert, F. Garca, M. Molere, Journal of Engneerng for Gas Turbnes and Power 132 art. no (2010) 13. J.N. Jaubert, L. Conglo, F. Denet, Industral & Engneerng Chemstry Research (1999) 14. J.N. Jaubert, L. Conglo, Industral & Engneerng Chemstry Research (1999) 15. J.N. Jaubert, P. Borg, L. Conglo, D. Barth, Journal of Supercrtcal Fluds (2001) 16. R. Gan, P. M. Harper, M. Hostrup, Industral & Engneerng Chemstry Research (2005) 17. R. Prvat, J.N. Jaubert, Global Journal of Physcal Chemstry (2010) 18. A. Fredenslund, R. L. Jones, J.M. Prausntz, AIChE Journal (1975) Nomenclature GO: gasol MMT: mnmum mscblty temperature. x : mole fracton of component n a gven phase. z : overall mole fracton of component. : actvty coeffcent of component. comb : combnatoral part of the actvty coeffcent. res : resdual part of the actvty coeffcent. k : molar proporton of lqud phase k. References 1. B.E. Polng, J.M. Prausntz, J.P. O'Connell, The propertes of gases and lquds, 5th edton, Mc Graw Hll, p.10

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

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

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

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

UNIFAC. Documentation. DDBSP Dortmund Data Bank Software Package

UNIFAC. Documentation. DDBSP Dortmund Data Bank Software Package UNIFAC Documentaton DDBSP Dortmund Data Ban Software Pacage DDBST Dortmund Data Ban Software & Separaton Technology GmbH Mare-Cure-Straße 10 D-26129 Oldenburg Tel.: +49 441 361819 0 Fax: +49 441 361819

More information

Solution Thermodynamics

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

More information

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

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

Prediction of steady state input multiplicities for the reactive flash separation using reactioninvariant composition variables

Prediction of steady state input multiplicities for the reactive flash separation using reactioninvariant composition variables Insttuto Tecnologco de Aguascalentes From the SelectedWorks of Adran Bonlla-Petrcolet 2 Predcton of steady state nput multplctes for the reactve flash separaton usng reactonnvarant composton varables Jose

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

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

INTRODUCTION TO CHEMICAL PROCESS SIMULATORS

INTRODUCTION TO CHEMICAL PROCESS SIMULATORS INTRODUCTION TO CHEMICAL PROCESS SIMULATORS DWSIM Chemcal Process Smulator A. Carrero, N. Qurante, J. Javaloyes October 2016 Introducton to Chemcal Process Smulators Contents Monday, October 3 rd 2016

More information

10.34 Numerical Methods Applied to Chemical Engineering Fall Homework #3: Systems of Nonlinear Equations and Optimization

10.34 Numerical Methods Applied to Chemical Engineering Fall Homework #3: Systems of Nonlinear Equations and Optimization 10.34 Numercal Methods Appled to Chemcal Engneerng Fall 2015 Homework #3: Systems of Nonlnear Equatons and Optmzaton Problem 1 (30 ponts). A (homogeneous) azeotrope s a composton of a multcomponent mxture

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

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

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

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

Kernel Methods and SVMs Extension

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

More information

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

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

Psychology 282 Lecture #24 Outline Regression Diagnostics: Outliers

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

More information

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

( ) 1/ 2. ( P SO2 )( P O2 ) 1/ 2.

( ) 1/ 2. ( P SO2 )( P O2 ) 1/ 2. Chemstry 360 Dr. Jean M. Standard Problem Set 9 Solutons. The followng chemcal reacton converts sulfur doxde to sulfur troxde. SO ( g) + O ( g) SO 3 ( l). (a.) Wrte the expresson for K eq for ths reacton.

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

Negative Binomial Regression

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

More information

3. Be able to derive the chemical equilibrium constants from statistical mechanics.

3. Be able to derive the chemical equilibrium constants from statistical mechanics. Lecture #17 1 Lecture 17 Objectves: 1. Notaton of chemcal reactons 2. General equlbrum 3. Be able to derve the chemcal equlbrum constants from statstcal mechancs. 4. Identfy how nondeal behavor can be

More information

Linear Regression Analysis: Terminology and Notation

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

More information

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

The Exact Formulation of the Inverse of the Tridiagonal Matrix for Solving the 1D Poisson Equation with the Finite Difference Method

The Exact Formulation of the Inverse of the Tridiagonal Matrix for Solving the 1D Poisson Equation with the Finite Difference Method Journal of Electromagnetc Analyss and Applcatons, 04, 6, 0-08 Publshed Onlne September 04 n ScRes. http://www.scrp.org/journal/jemaa http://dx.do.org/0.46/jemaa.04.6000 The Exact Formulaton of the Inverse

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

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

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

Lecture 7: Boltzmann distribution & Thermodynamics of mixing

Lecture 7: Boltzmann distribution & Thermodynamics of mixing Prof. Tbbtt Lecture 7 etworks & Gels Lecture 7: Boltzmann dstrbuton & Thermodynamcs of mxng 1 Suggested readng Prof. Mark W. Tbbtt ETH Zürch 13 März 018 Molecular Drvng Forces Dll and Bromberg: Chapters

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

(1) The saturation vapor pressure as a function of temperature, often given by the Antoine equation:

(1) The saturation vapor pressure as a function of temperature, often given by the Antoine equation: CE304, Sprng 2004 Lecture 22 Lecture 22: Topcs n Phase Equlbra, part : For the remander of the course, we wll return to the subject of vapor/lqud equlbrum and ntroduce other phase equlbrum calculatons

More information

University of Washington Department of Chemistry Chemistry 452/456 Summer Quarter 2014

University of Washington Department of Chemistry Chemistry 452/456 Summer Quarter 2014 Lecture 16 8/4/14 Unversty o Washngton Department o Chemstry Chemstry 452/456 Summer Quarter 214. Real Vapors and Fugacty Henry s Law accounts or the propertes o extremely dlute soluton. s shown n Fgure

More information

General Thermodynamics for Process Simulation. Dr. Jungho Cho, Professor Department of Chemical Engineering Dong Yang University

General Thermodynamics for Process Simulation. Dr. Jungho Cho, Professor Department of Chemical Engineering Dong Yang University General Thermodynamcs for Process Smulaton Dr. Jungho Cho, Professor Department of Chemcal Engneerng Dong Yang Unversty Four Crtera for Equlbra μ = μ v Stuaton α T = T β α β P = P l μ = μ l1 l 2 Thermal

More information

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

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

More information

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

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

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

More information

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

Name: SID: Discussion Session:

Name: SID: Discussion Session: Name: SID: Dscusson Sesson: Chemcal Engneerng Thermodynamcs 141 -- Fall 007 Thursday, November 15, 007 Mdterm II SOLUTIONS - 70 mnutes 110 Ponts Total Closed Book and Notes (0 ponts) 1. Evaluate whether

More information

An identification algorithm of model kinetic parameters of the interfacial layer growth in fiber composites

An identification algorithm of model kinetic parameters of the interfacial layer growth in fiber composites IOP Conference Seres: Materals Scence and Engneerng PAPER OPE ACCESS An dentfcaton algorthm of model knetc parameters of the nterfacal layer growth n fber compostes o cte ths artcle: V Zubov et al 216

More information

The optimal delay of the second test is therefore approximately 210 hours earlier than =2.

The optimal delay of the second test is therefore approximately 210 hours earlier than =2. THE IEC 61508 FORMULAS 223 The optmal delay of the second test s therefore approxmately 210 hours earler than =2. 8.4 The IEC 61508 Formulas IEC 61508-6 provdes approxmaton formulas for the PF for smple

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

Problem Set 9 Solutions

Problem Set 9 Solutions Desgn and Analyss of Algorthms May 4, 2015 Massachusetts Insttute of Technology 6.046J/18.410J Profs. Erk Demane, Srn Devadas, and Nancy Lynch Problem Set 9 Solutons Problem Set 9 Solutons Ths problem

More information

modeling of equilibrium and dynamic multi-component adsorption in a two-layered fixed bed for purification of hydrogen from methane reforming products

modeling of equilibrium and dynamic multi-component adsorption in a two-layered fixed bed for purification of hydrogen from methane reforming products modelng of equlbrum and dynamc mult-component adsorpton n a two-layered fxed bed for purfcaton of hydrogen from methane reformng products Mohammad A. Ebrahm, Mahmood R. G. Arsalan, Shohreh Fatem * Laboratory

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

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

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

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

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

Gasometric Determination of NaHCO 3 in a Mixture

Gasometric Determination of NaHCO 3 in a Mixture 60 50 40 0 0 5 15 25 35 40 Temperature ( o C) 9/28/16 Gasometrc Determnaton of NaHCO 3 n a Mxture apor Pressure (mm Hg) apor Pressure of Water 1 NaHCO 3 (s) + H + (aq) Na + (aq) + H 2 O (l) + CO 2 (g)

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

Inductance Calculation for Conductors of Arbitrary Shape

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

More information

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

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

More information

The ChemSep Book. Harry A. Kooijman Consultant. Ross Taylor Clarkson University, Potsdam, New York University of Twente, Enschede, The Netherlands

The ChemSep Book. Harry A. Kooijman Consultant. Ross Taylor Clarkson University, Potsdam, New York University of Twente, Enschede, The Netherlands The ChemSep Book Harry A. Koojman Consultant Ross Taylor Clarkson Unversty, Potsdam, New York Unversty of Twente, Enschede, The Netherlands Lbr Books on Demand www.bod.de Copyrght c 2000 by H.A. Koojman

More information

Asymptotics of the Solution of a Boundary Value. Problem for One-Characteristic Differential. Equation Degenerating into a Parabolic Equation

Asymptotics of the Solution of a Boundary Value. Problem for One-Characteristic Differential. Equation Degenerating into a Parabolic Equation Nonl. Analyss and Dfferental Equatons, ol., 4, no., 5 - HIKARI Ltd, www.m-har.com http://dx.do.org/.988/nade.4.456 Asymptotcs of the Soluton of a Boundary alue Problem for One-Characterstc Dfferental Equaton

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

CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE

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

More information

The influence of non-ideal vapor-liquid-equilibrium on vaporization of multicomponent hydrocarbon fuels

The influence of non-ideal vapor-liquid-equilibrium on vaporization of multicomponent hydrocarbon fuels ICLASS 202, 2 th Trennal Internatonal Conference on Lqud Atomzaton and Spray Systems, Hedelberg, Germany, September 2-6, 202 The nfluence of non-deal vapor-lqud-equlbrum on vaporzaton of multcomponent

More information

x i1 =1 for all i (the constant ).

x i1 =1 for all i (the constant ). Chapter 5 The Multple Regresson Model Consder an economc model where the dependent varable s a functon of K explanatory varables. The economc model has the form: y = f ( x,x,..., ) xk Approxmate ths by

More information

Influence Of Operating Conditions To The Effectiveness Of Extractive Distillation Columns

Influence Of Operating Conditions To The Effectiveness Of Extractive Distillation Columns Influence Of Operatng Condtons To The Effectveness Of Extractve Dstllaton Columns N.A. Vyazmna Moscov State Unversty Of Envrnmental Engneerng, Department Of Chemcal Engneerng Ul. Staraya Basmannaya 21/4,

More information

Assessing the use of NMR chemical shifts for prediction of VLE in nonideal binary liquid mixtures

Assessing the use of NMR chemical shifts for prediction of VLE in nonideal binary liquid mixtures Assessng the use of NMR chemcal shfts for predcton of VLE n nondeal bnary lqud mtures Q. Zhu, G. D. Moggrdge, T. Dalton, J. Cooper, M.D. Mantle, L. F. Gladden, C. D Agostno* *Correspondng Author: Dr Carmne

More information

4 Analysis of Variance (ANOVA) 5 ANOVA. 5.1 Introduction. 5.2 Fixed Effects ANOVA

4 Analysis of Variance (ANOVA) 5 ANOVA. 5.1 Introduction. 5.2 Fixed Effects ANOVA 4 Analyss of Varance (ANOVA) 5 ANOVA 51 Introducton ANOVA ANOVA s a way to estmate and test the means of multple populatons We wll start wth one-way ANOVA If the populatons ncluded n the study are selected

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

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

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

The Order Relation and Trace Inequalities for. Hermitian Operators

The Order Relation and Trace Inequalities for. Hermitian Operators Internatonal Mathematcal Forum, Vol 3, 08, no, 507-57 HIKARI Ltd, wwwm-hkarcom https://doorg/0988/mf088055 The Order Relaton and Trace Inequaltes for Hermtan Operators Y Huang School of Informaton Scence

More information

International Journal of Engineering Research and Modern Education (IJERME) Impact Factor: 7.018, ISSN (Online): (

International Journal of Engineering Research and Modern Education (IJERME) Impact Factor: 7.018, ISSN (Online): ( CONSTRUCTION AND SELECTION OF CHAIN SAMPLING PLAN WITH ZERO INFLATED POISSON DISTRIBUTION A. Palansamy* & M. Latha** * Research Scholar, Department of Statstcs, Government Arts College, Udumalpet, Tamlnadu

More information

Entropy generation in a chemical reaction

Entropy generation in a chemical reaction Entropy generaton n a chemcal reacton E Mranda Área de Cencas Exactas COICET CCT Mendoza 5500 Mendoza, rgentna and Departamento de Físca Unversdad aconal de San Lus 5700 San Lus, rgentna bstract: Entropy

More information

( ) Phase equilibrium Some basic principles for phase calculations

( ) Phase equilibrium Some basic principles for phase calculations Chapter From Fundamentals to Propertes 6 Table. Total propertes from an excess approach V U H A G S Pure component Real mxture Ideal mxture Mxng contrbuton Excess property = * v + 0 + * v v (.0) = * u

More information

Lecture 14: Forces and Stresses

Lecture 14: Forces and Stresses The Nuts and Bolts of Frst-Prncples Smulaton Lecture 14: Forces and Stresses Durham, 6th-13th December 2001 CASTEP Developers Group wth support from the ESF ψ k Network Overvew of Lecture Why bother? Theoretcal

More information

Section 8.3 Polar Form of Complex Numbers

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

More information

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

A LINEAR PROGRAM TO COMPARE MULTIPLE GROSS CREDIT LOSS FORECASTS. Dr. Derald E. Wentzien, Wesley College, (302) ,

A LINEAR PROGRAM TO COMPARE MULTIPLE GROSS CREDIT LOSS FORECASTS. Dr. Derald E. Wentzien, Wesley College, (302) , A LINEAR PROGRAM TO COMPARE MULTIPLE GROSS CREDIT LOSS FORECASTS Dr. Derald E. Wentzen, Wesley College, (302) 736-2574, wentzde@wesley.edu ABSTRACT A lnear programmng model s developed and used to compare

More information

See Book Chapter 11 2 nd Edition (Chapter 10 1 st Edition)

See Book Chapter 11 2 nd Edition (Chapter 10 1 st Edition) Count Data Models See Book Chapter 11 2 nd Edton (Chapter 10 1 st Edton) Count data consst of non-negatve nteger values Examples: number of drver route changes per week, the number of trp departure changes

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

Lecture Notes on Linear Regression

Lecture Notes on Linear Regression Lecture Notes on Lnear Regresson Feng L fl@sdueducn Shandong Unversty, Chna Lnear Regresson Problem In regresson problem, we am at predct a contnuous target value gven an nput feature vector We assume

More information

Errors for Linear Systems

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

More information

Chapter 11: Simple Linear Regression and Correlation

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

More information

Parametric fractional imputation for missing data analysis. Jae Kwang Kim Survey Working Group Seminar March 29, 2010

Parametric fractional imputation for missing data analysis. Jae Kwang Kim Survey Working Group Seminar March 29, 2010 Parametrc fractonal mputaton for mssng data analyss Jae Kwang Km Survey Workng Group Semnar March 29, 2010 1 Outlne Introducton Proposed method Fractonal mputaton Approxmaton Varance estmaton Multple mputaton

More information

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

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

More information

Correlation and Regression. Correlation 9.1. Correlation. Chapter 9

Correlation and Regression. Correlation 9.1. Correlation. Chapter 9 Chapter 9 Correlaton and Regresson 9. Correlaton Correlaton A correlaton s a relatonshp between two varables. The data can be represented b the ordered pars (, ) where s the ndependent (or eplanator) varable,

More information

Assortment Optimization under MNL

Assortment Optimization under MNL Assortment Optmzaton under MNL Haotan Song Aprl 30, 2017 1 Introducton The assortment optmzaton problem ams to fnd the revenue-maxmzng assortment of products to offer when the prces of products are fxed.

More information

University of Washington Department of Chemistry Chemistry 453 Winter Quarter 2015

University of Washington Department of Chemistry Chemistry 453 Winter Quarter 2015 Lecture 2. 1/07/15-1/09/15 Unversty of Washngton Department of Chemstry Chemstry 453 Wnter Quarter 2015 We are not talkng about truth. We are talkng about somethng that seems lke truth. The truth we want

More information

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

Generalized Linear Methods

Generalized Linear Methods Generalzed Lnear Methods 1 Introducton In the Ensemble Methods the general dea s that usng a combnaton of several weak learner one could make a better learner. More formally, assume that we have a set

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

Solution Thermodynamics

Solution Thermodynamics CH2351 Chemcal Engneerng Thermodynamcs II Unt I, II www.msubbu.n Soluton Thermodynamcs www.msubbu.n Dr. M. Subramanan Assocate Professor Department of Chemcal Engneerng Sr Svasubramanya Nadar College of

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

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

Chapter - 2. Distribution System Power Flow Analysis

Chapter - 2. Distribution System Power Flow Analysis Chapter - 2 Dstrbuton System Power Flow Analyss CHAPTER - 2 Radal Dstrbuton System Load Flow 2.1 Introducton Load flow s an mportant tool [66] for analyzng electrcal power system network performance. Load

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

This column is a continuation of our previous column

This column is a continuation of our previous column Comparson of Goodness of Ft Statstcs for Lnear Regresson, Part II The authors contnue ther dscusson of the correlaton coeffcent n developng a calbraton for quanttatve analyss. Jerome Workman Jr. and Howard

More information

Markov Chain Monte Carlo Lecture 6

Markov Chain Monte Carlo Lecture 6 where (x 1,..., x N ) X N, N s called the populaton sze, f(x) f (x) for at least one {1, 2,..., N}, and those dfferent from f(x) are called the tral dstrbutons n terms of mportance samplng. Dfferent ways

More information

The Minimum Universal Cost Flow in an Infeasible Flow Network

The Minimum Universal Cost Flow in an Infeasible Flow Network Journal of Scences, Islamc Republc of Iran 17(2): 175-180 (2006) Unversty of Tehran, ISSN 1016-1104 http://jscencesutacr The Mnmum Unversal Cost Flow n an Infeasble Flow Network H Saleh Fathabad * M Bagheran

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

Numerical Solution of Ordinary Differential Equations

Numerical Solution of Ordinary Differential Equations Numercal Methods (CENG 00) CHAPTER-VI Numercal Soluton of Ordnar Dfferental Equatons 6 Introducton Dfferental equatons are equatons composed of an unknown functon and ts dervatves The followng are examples

More information

JAB Chain. Long-tail claims development. ASTIN - September 2005 B.Verdier A. Klinger

JAB Chain. Long-tail claims development. ASTIN - September 2005 B.Verdier A. Klinger JAB Chan Long-tal clams development ASTIN - September 2005 B.Verder A. Klnger Outlne Chan Ladder : comments A frst soluton: Munch Chan Ladder JAB Chan Chan Ladder: Comments Black lne: average pad to ncurred

More information