Modified method of a determination in the 1/E 1+a epithermal neutron spectrum of reactor

Size: px
Start display at page:

Download "Modified method of a determination in the 1/E 1+a epithermal neutron spectrum of reactor"

Transcription

1 J Rdionl Nucl Chem (2010) 285: DOI /s x Modified method of determintion in the 1/E 1+ epitherml neutron spectrum of rector Trn Vn Hung Received: 19 Februry 2010 / Published online: 7 April 2010 Ó The Author(s) This rticle is published with open ccess t Springerlink.com Abstrct A modified method hs been developed for the determintion in the 1/E 1? epitherml neutron spectrum of rector. It is bsed on the Cd-covered nd without Cdcovered irrditions of two monitors. This method ws pplied to determine the vlue in the chnnels of Dlt rector nd the results were compred with those obtined by the other methods. It ppered tht the results of the modified method were in quite good greement with those of other methods. It lso showed tht the modified method ws simple in prcticl uses nd good ppliction in the experiment of determintion in the rector irrdition chnnels. Keywords Introduction Vlue Dlt rector Modified method As reported by Schumnn nd Albert [1] nd by Ryves [2], the epitherml neutron flux in rector irrdition chnnels is not proportionl to 1/E, but rther 1/E 1?, where is smll positive or negtive constnt nd mesure of the epitherml neutron flux devition from the idel distribution 1/E, nd E is the neutron energy. The vlues re smller thn unity in bsolute vlue, nd vry between the irrdition chnnels in the sme rector. T. Vn Hung (&) Reserch nd Development Center for Rdition Technology, 202A, Street 11, Linh Xun Wrd, Thu Duc District, HoChiMinh City, Vietnm e-mil: trnhungkeiko@yhoo.com In the idel cse, the resonnce integrl for 1/E epitherml neutron spectrum is written s: I 0 ¼ Z 1 E Cd rðeþ E de ð1þ with: E Cd is the effective Cd cut-off energy (=0.55 ev). The resonnce integrls, defined ccording to Eq. 1 nd tbled in litertures, re not vlid in non-idel cse. In the non-idel cse, the resonnce integrl for 1/E 1? epitherml neutron spectrum is defined s: I 0 ðþ ¼ Z 1 E Cd rðeþ:1 ev E 1þ de: ð2þ It indictes tht the resonnce integrls for prcticl uses re function of nd thus of the irrdition position. Thus, in the (n, c)-ctivtion nlysis with rector neutrons (NAA) using comprtor method, should be known to preserve the ccurcy of the nlysis results. The vlue should be determined either by experiment or by clcultion. In experiment, severl techniques hve been developed by De Corte et l. [3 5], nmely the Cd-covered multi-monitor method, the Cd-rtio for multi-monitor method, the bre multi-monitor method. However, in these methods, the vlues re found from implicit functions by the itertive method on computer. Consequently, they re merely pproximte methods. In this work, modified method for the determintion of prmeters in rector irrdition chnnels is to be presented. In tht, the prmeter is written s n explicit formul. The results of the determintion in irrdition chnnels of Dlt rector using the modified method re lso being reported.

2 332 T. Vn Hung Bse of modified method From Eq. 2, the resonnce integrl of isotope i in the nonidel cse should be written s:! I 0i ðþ ¼ I 0i 0:426r 0i 0:426r 0i þ E ri ð2 þ 1ÞðE Cd Þ 1eV ð3þ where r 0i 2,200 m s -1 cross-section of nuclide i, E ri effective resonnce energy (ev) of nuclide i. Note tht Eq. 3 is only vlid when E Cd = 0.55 ev, since = 2(E 0 /E Cd ) 1/2 with E 0 = ev nd E Cd = 0.55 ev. Accordingly, Q 0 () = I 0 ()/r 0 cn be written (in ev unit) s below:! Q 0i ðþ ¼ Q 0i 0:426 0:426 þ ð2 þ 1ÞðE Cd Þ : ð4þ E ri We know tht, vlue is much smller thn unity in bsolute vlue. In prctice, in rector irrdition chnnels, the bsolute vlue is less thn 0.2 (in most cses, \ 0.1 nd this condition is stisfctory in rector core). We suggest substitution Q 0i () from Eq. 4 by the following pproximte formul: Q 0i ðþ ¼Q 0i expð i ðln E ri ÞÞ ð5þ where i is constnt for ech nuclide nd determined by fitting the vlues of Q 0i (), which re clculted from Eq. 4 in the rnge of B 0.2, ccording to the fitting function (5). Note tht, i for ech nuclide is dependent on the sign of. In this work, i vlues re determined by fitting Q 0i () using Kleigrph progrm. The vlues of i, correltion nd coefficient r of fitting function, nd the relevnt nucler dt for nuclides chosen s -monitors re given in Tble 1. As the comprison of Q 0i () between formul (4) nd (5), the results of clculting Q 0i () for 197 Au(n, c) 198 Au, 64 Zn(n, c) 65 Zn nd 94 Zr(n, c) 95 Zr for negtive nd positive re respectively shown in Tbles 2 nd 3. It indictes tht, when vlues re negtive nd less thn 0.2 in bsolute vlue, the differences of Q 0i () clculted from these formul re less thn 0.08% for 197 Au(n, c) 198 Au, 0.8% for 94 Zr(n, c) 95 Zr, nd bout 2% for 64 Zn(n, c) 65 Zn. In the cse of positive vlues, Q 0i () vlues for 197 Au(n, c) 198 Au mtch ech other very well with the differences less thn 0.04%, while Q 0i () vlues for 94 Zr(n, c) 95 Zr nd 64 Zn(n, c) 65 Zn re in good greement with \ When vlues re more thn 0.16, the differences of Q 0i () vlues clculted from these formul cn be more thn 2% for 94 Zr(n, c) 95 Zr nd 64 Zn(n, c) 65 Zn. However, in most cses, jj\ 0:1 nd this condition is stisfctory in rector Tble 1 Nucler dt nd i fctor for the nuclides chosen s -monitors, correltion coefficient r of fitting function Nuclide E ri ðevþ Q 0i i r \ 0 [ Au(n, c) 198 Au ± ± Zr(n, c) 95 Zr ± ± Zn(n, c) 65 Zn ± ± Dt for Au nd Zn were tken from De Corte [6] nd Zr dt from Simonits [7] Tble 2 The vlues Q 0i () for monitors clculted from formul (4) nd (5) with in intervl [0,-0.2] 197 Au(n, c) 198 Au 64 Zn(n, c) 65 Zn 94 Zr(n, c) 95 Zr Q 0i () from (4) Q 0i () from (5) Q 0i () from (4) Q 0i () from (5) Q 0i () from (4) Q 0i () from (5)

3 Modified method of determintion 333 Tble 3 The vlues Q 0i () for monitors clculted from formul (4) nd (5) with in intervl [0,0.2] 197 Au(n, c) 198 Au 64 Zn(n, c) 65 Zn 94 Zr(n, c) 95 Zr Q 0i () from (4) Q 0i () from (5) Q 0i () from (4) Q 0i () from (5) Q 0i () from (4) Q 0i () from (5) core; s for chnnel R4V4 of the DR-3 rector (Ri/, Denmrk), = ± [8], Eq. 5 cn be good use to replce Eq. 4 in -prctice. It cn be seen lter in the discussion bout the error estimtion of the method. Thus, in the two-detector method of Ryves using Cd-rtio modified by De Corte et l. [4], cn be found s the root of the eqution: I 01 ðr Cd2 1Þ ðr Cd1 1Þ ¼ r 01 0:426 E r1 þ 0:426 ð2þ1 I 02 r 02 0:426 E r2 þ 0:426 Note tht: Q 0i ðþ ¼ Q 0i 0:426 0:426 E ri þ ð2 þ 1Þ:0:55 : Eqution 6 cn be written s: ÞE Cd ð2þ1þe Cd : ð6þ ðr Cd2 1Þ ðr Cd1 1Þ ¼ Q 01ðÞ ð7þ Q 02 ðþ Where i is denotes the ith monitor nd R Cdi is Cd rtio of ith monitor. Substituting Eq. 5 into Eq. 7, it cn be written: ðr Cd2 1Þ ðr Cd1 1Þ ¼ Q 01ðÞ Q 02 ðþ ¼ Q 01 expð 1 ðln E r1 Þ ð8þ Q 02 expð 2 ðln E r2 Þ nd thus, prmeter cn be written: 1 ¼ ð 2 ln E r2 1 ln E r1 Þ ln ðr Cd2 1ÞQ 02 : ð9þ ðr Cd1 1ÞQ 01 In the cse of Cd-covered co-irrdition of two-detector, from bse ctivtion eqution, is esily written: 1 ¼ ð 2 ln E r2 1 ln E r1 Þ ln A sp1k 0Auð1Þ e 2 Q 02 ð10þ A sp2 k 0Auð2Þ e 2 Q 01 A spi ¼ A pi wsdc where A pi mesured verge ctivity of the full-energy pek, A pi = N pi /t m with N pi net number of counts under the full-energy pek collected during mesuring time t m ; w weight of the irrdited element; S ¼ 1 e kt irr ; k = decy constnt, t irr = irrdition time; D ¼ e kt d ; t d = decy time; C ¼ 1 e ktm kt m k 0Au(i) is k 0 -fctor of ith isotope to gold (see Ref. [3]) nd e i is full-energy pek detection efficiency of energy E i. Thus, in experiment using pirs of 197 Au 94 Zr nd 197 Au 64 Zn, we only need the determintion of R Cdi rtios (Cdrtio method) or A spi (Cd-covered irrdition only) of monitors. Then will be clculted using Eqs. 9 or 10, respectively. Error estimtion of the method Errors of the method should be estimted in two kinds: systemtic nd sttisticl errors. In this report, the errors due to pproximtion of Eq. 5 re considered s systemtic errors, while the errors of the vribles in Eqs. 9 nd 10 using clcultion of re sttisticl errors. The 197 Au 94 Zr nd 197 Au 64 Zn pirs were pplied. The choice of 197 Au 94 Zr nd 197 Au 64 Zn monitor pirs is very suitble for the experiment of the -determintion. The reson is the E ri effective resonnt energies of these isotopes re in wide region (E 197 r ð AuÞ ¼ 5:65 ev; E 64 r Zn ¼ 2; 560 ev; E 94 r ð ZrÞ¼6; 260 evþ nd nucler prmeters re suitble for rector irrdition. Moreover, the smple preprtion is prticulrly esy, the product nucleus hve simple decy scheme nd their cross-section hve been determined in detil nd with high ccurcy. Error estimtion due to pproximtion of Eq. 5 Reviewing Tbles 2 nd 3, we see tht the Q 0i ()-vlues of 197 Au(n, c) 198 Au clculted from Eqs. 4 nd 5 re in very

4 334 T. Vn Hung Reltive error (%) Monitor Zn-64 Monitor Zr-94 α Fig. 1 Survey of f -vlues on when \ 0 Reltive error (%) α 0.25 Fig. 2 Survey of f -vlues on when [ 0 Monitor Zn-64 Monitor Zr-94 good greement with the difference of less thn 0.08% in the rnge of B 0.2. We cn think tht they re quite coincident. The uncertinty of the -vlues depends only on the differences of the Q 0i ()-vlues of 94 Zr(n, c) 95 Zr nd 64 Zn(n, c) 65 Zn clculted from Eqs. 4 nd 5, respectively. From Eq. 5, it cn be written s: ¼ðlnQ 0 ðþ lnq 0 Þ=ln E r : ð11þ From the error propgtion eqution, the percentile error or uncertinty due to pproximtion of Eq. 5 cn be written s: f ¼ r ¼ 1 : 1 DQ 0 ðþ ð12þ ln E r Q 0 ðþ where r is bsolute uncertinty of ; DQ 0 ()is the difference of the Q 0i ()-vlues clculted from Eqs. 4 nd 5. From Eq. 5, f is dependent upon ech isotope chosen s monitor nd inverse proportion to -vlue. The survey of f -vlues on, in which \ 0.2, for 94 Zr nd 65 Zn were crried out in Figs. 1 nd 2. From Figs. 1 nd 2, the systemtic uncertinty (f )of the 197 Au 94 Zr pir is lower thn tht of 197 Au 64 Zn one. It is obvious tht Q 0 of 94 Zr (Q 0 = 5.306) is bigger thn one of 64 Zn (Q 0 = 1.908). Furthermore, DQ 0 ()of 64 Zn clculted from Eqs. 4 nd 5 is bigger thn one of 94 Zr nd the effective resonnce energy of 94 Zr E ri ¼ 6; 260 ev is lso bigger thn the one of 64 Zn E ri ¼ 2; 560 ev : Sttisticl errors This error cn be estimted from the errors of the vribles in Eqs. 9 or 10. The bsolute uncertinty in cn be clculted from the uncertinties of the vribles (denoted x j ) which determine in Eqs. 9 or 10: vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi X u r ¼ r 2 o 2 t x j ox j j ð13þ where q/qx j nd rx j re the corresponding prtil derivtives nd the uncertinties of x j -vribles, respectively. According to the customry error propgtion theory, the error propgtion functions cn be written s: Z ðx j Þ¼ o. oxj x ¼ o x j j ox j : ð14þ And reltive error: s ðx j Þ¼Z ðx j Þ Dx j : x j ð15þ Applying the bove formul Eqs. 14 9, we get: 1 Z ðe r1 Þ¼ 2 ln E r2 1 ln E r1 ð16þ 2 Z ðe r2 Þ¼ 2 ln E r2 1 ln E r1 ð17þ 1 ln E r1 Z ð 1 Þ¼ 2 ln E r2 1 ln E r1 ð18þ 2 Z ð 2 Þ¼ 2 ln E r2 1 ln E r1 ð19þ Z ðq 01 Þ¼Z ðq 02 Þ¼ ln E r2 1 ln E r1 ð20þ Z ðr Cd1 Þ¼ 1 R Cd1 ðr Cd1 1Þð 2 ln E r2 1 ln E r1 Þ ð21þ Z ðr Cd2 Þ¼ 1 R Cd2 ðr Cd2 1Þð 2 ln E r2 1 ln E r1 Þ : ð22þ In the cse of Cd-covered co-irrdition of two-detector, the vlue is clculted using Eq. 10, nd we obtin Eqs for the error propgtion functions of E ri nd i. The other vribles cn be clculted s following: Z ða sp1 Þ¼Z ða sp2 Þ¼Z ðk 0Auð1Þ Þ¼Z ðk 0Auð2Þ Þ ¼ Z ðe 1 Þ¼Z ðe 2 Þ¼ 1 1 ð 2 ln E r2 1 ln E r1 Þ : ð23þ

5 Modified method of determintion 335 Fig. 3 Ground pln of Dlt rector Experimentl As the first check, in this work, the 197 Au 94 Zr pir ws pplied. The E ri effective resonnt energies of these isotopes re in wide region (E 197 r ð AuÞ ¼ 5:65 ev; E 96 r Zr ¼ 248 ev; 94 Er ð ZrÞ ¼ 6; 260 evþ nd nucler prmeters re suitble for rector irrdition. Moreover, the irrdition of these monitor foils with bre nd Cdcover, we cn simultneously determine the vlue by bre multi-monitor method s presented in [3], s comprison. The experiment of the -determintion ws crried out in the chnnels 7-1, 1-4 nd neutron trp of Dlt rector. These irrdition positions re situted in rector core (Fig. 3). As stndrd mterils, % Au Al wire (dim. 1 mm) nd high-purity Zr foils of mm thickness were used. In this cse, the monitor foils of Au nd Zr with bre nd Cd-covered were simultneously irrdited in the mentioned rector chnnels. The irrdition durtions were 20 min nd 1 h, respectively. In both cses, decying nd mesuring time were h nd 30 min. The counting ws performed with 70 cm 3 coxil GeHP detector pired to 4096 chnnels nlyzer. The results which were summrized in Tble 4, were compred with those obtined by the three-detector method without Cd [3] nd by -determintion method using neutron spectrum clculted by MCNP code [9]. As n exmple for the error estimtion of, we crried out the results of the error estimtion of in 7-1 chnnel of Dlt rector using R Cd method (Eq. 9). Indeed, with = 0.044, the uncertinty of R Cd in the experiment bout 1%, the uncertinties Q oi nd E ri from report [6, 7], we

6 336 T. Vn Hung Tble 4 -Vlues in irrdition chnnels of Dlt rector Chnnels 197 Au 94 Zr (Eq. 9), (10-2 ) 197 Au 94 Zr (Eq. 10), (10-2 ) Three-detector method with Cd, (10-2 ) Clculted (10-2 )[9] Neutron trp -3.1 ± ± ± ± Chnnel -3.6 ± ± ± ± Chnnel -4.4 ± ± ± ± 0.4 used Eqs nd obtined: s ðe rzr Þ1:4%; s ðe rau Þ 1:4%; s ð Au Þ0:03%; s ð Zr Þ0:13%; s ðq 0Au Þ 6:5%; s ðq 0Zr Þ7%; s ðr CdAu Þ5:2%; s ðr CdZr Þ 7:6%: The uncertinty of in totl ws bout 13% (with f & 2%). Similrly, in the cse using the method of Cdcovered co-irrdition of two-detectors ( = 0.045), the uncertinty of estimted from Eqs nd Eq. 23 ws bout 15%, wheres using of the three-detector method without Cd, the uncertinty of ws bout 30%. The comprison of the vlues in Tble 4 shows tht the vlues clculted from Eqs. 9 or 10 re in good greement with ech other. Moreover, they gree well with -determintion method using neutron spectrum clculted by MCNP code [9] nd the three-detector method without Cd. Conclusion From Tble 4, it is obvious tht the modified method presented in this report is suitble for rpid -determintion in experiment. This is in complete greement with the results of the other methods. Moreover, the results from studying on the error due to pproximtion of Eq. 5 suggest tht in cse bsolute vlue is less thn 0.25 (this condition is stisfctory in irrdition chnnels locted in the rector core), the using of this method is quite possible with resonble errors. Open Access This rticle is distributed under the terms of the Cretive Commons Attribution Noncommercil License which permits ny noncommercil use, distribution, nd reproduction in ny medium, provided the originl uthor(s) nd source re credited. References 1. Schumnn P, Albert D (1965) Kernenergie 2:88 2. Ryvers TB (1969) Metrologi 5: de Corte F, Moens L, Simonits A, de Wispelere A, Hoste J (1979) J Rdionl Chem 52: de Corte F, Moens L, Sordo-El Hmmmi K, Simonits A, Hoste J (1979) J Rdionl Chem 52: de Corte F, Sordo-El Hmmmi K, Moens L, Simonits A, de Wispelere A, Hoste J (1981) J Rdionl Chem 62: de Corte F, Simonits A (1989) J Rdionl Nucl Chem 133:43 7. Simonits A, de Corte F, Vn Lierde S, Pomme S, Robouch P, Eguskiz M (2000) J Rdionl Nucl Chem 245: de Corte F, Moens L, Jovnovic S, Simonits A, de Wispelere A (1986) J Rdionl Nucl Chem 102:37 9. Hung TV (2010) J Rdionl Nucl Chem 283:719

New Expansion and Infinite Series

New Expansion and Infinite Series Interntionl Mthemticl Forum, Vol. 9, 204, no. 22, 06-073 HIKARI Ltd, www.m-hikri.com http://dx.doi.org/0.2988/imf.204.4502 New Expnsion nd Infinite Series Diyun Zhng College of Computer Nnjing University

More information

Driving Cycle Construction of City Road for Hybrid Bus Based on Markov Process Deng Pan1, a, Fengchun Sun1,b*, Hongwen He1, c, Jiankun Peng1, d

Driving Cycle Construction of City Road for Hybrid Bus Based on Markov Process Deng Pan1, a, Fengchun Sun1,b*, Hongwen He1, c, Jiankun Peng1, d Interntionl Industril Informtics nd Computer Engineering Conference (IIICEC 15) Driving Cycle Construction of City Rod for Hybrid Bus Bsed on Mrkov Process Deng Pn1,, Fengchun Sun1,b*, Hongwen He1, c,

More information

NUMERICAL INTEGRATION. The inverse process to differentiation in calculus is integration. Mathematically, integration is represented by.

NUMERICAL INTEGRATION. The inverse process to differentiation in calculus is integration. Mathematically, integration is represented by. NUMERICAL INTEGRATION 1 Introduction The inverse process to differentition in clculus is integrtion. Mthemticlly, integrtion is represented by f(x) dx which stnds for the integrl of the function f(x) with

More information

Unit #9 : Definite Integral Properties; Fundamental Theorem of Calculus

Unit #9 : Definite Integral Properties; Fundamental Theorem of Calculus Unit #9 : Definite Integrl Properties; Fundmentl Theorem of Clculus Gols: Identify properties of definite integrls Define odd nd even functions, nd reltionship to integrl vlues Introduce the Fundmentl

More information

63. Representation of functions as power series Consider a power series. ( 1) n x 2n for all 1 < x < 1

63. Representation of functions as power series Consider a power series. ( 1) n x 2n for all 1 < x < 1 3 9. SEQUENCES AND SERIES 63. Representtion of functions s power series Consider power series x 2 + x 4 x 6 + x 8 + = ( ) n x 2n It is geometric series with q = x 2 nd therefore it converges for ll q =

More information

THERMAL EXPANSION COEFFICIENT OF WATER FOR VOLUMETRIC CALIBRATION

THERMAL EXPANSION COEFFICIENT OF WATER FOR VOLUMETRIC CALIBRATION XX IMEKO World Congress Metrology for Green Growth September 9,, Busn, Republic of Kore THERMAL EXPANSION COEFFICIENT OF WATER FOR OLUMETRIC CALIBRATION Nieves Medin Hed of Mss Division, CEM, Spin, mnmedin@mityc.es

More information

The International Association for the Properties of Water and Steam. Release on the Ionization Constant of H 2 O

The International Association for the Properties of Water and Steam. Release on the Ionization Constant of H 2 O IAPWS R-7 The Interntionl Assocition for the Properties of Wter nd Stem Lucerne, Sitzerlnd August 7 Relese on the Ioniztion Constnt of H O 7 The Interntionl Assocition for the Properties of Wter nd Stem

More information

Chapter 0. What is the Lebesgue integral about?

Chapter 0. What is the Lebesgue integral about? Chpter 0. Wht is the Lebesgue integrl bout? The pln is to hve tutoril sheet ech week, most often on Fridy, (to be done during the clss) where you will try to get used to the ides introduced in the previous

More information

APPROXIMATE INTEGRATION

APPROXIMATE INTEGRATION APPROXIMATE INTEGRATION. Introduction We hve seen tht there re functions whose nti-derivtives cnnot be expressed in closed form. For these resons ny definite integrl involving these integrnds cnnot be

More information

Predict Global Earth Temperature using Linier Regression

Predict Global Earth Temperature using Linier Regression Predict Globl Erth Temperture using Linier Regression Edwin Swndi Sijbt (23516012) Progrm Studi Mgister Informtik Sekolh Teknik Elektro dn Informtik ITB Jl. Gnesh 10 Bndung 40132, Indonesi 23516012@std.stei.itb.c.id

More information

A REVIEW OF CALCULUS CONCEPTS FOR JDEP 384H. Thomas Shores Department of Mathematics University of Nebraska Spring 2007

A REVIEW OF CALCULUS CONCEPTS FOR JDEP 384H. Thomas Shores Department of Mathematics University of Nebraska Spring 2007 A REVIEW OF CALCULUS CONCEPTS FOR JDEP 384H Thoms Shores Deprtment of Mthemtics University of Nebrsk Spring 2007 Contents Rtes of Chnge nd Derivtives 1 Dierentils 4 Are nd Integrls 5 Multivrite Clculus

More information

Math 113 Exam 2 Practice

Math 113 Exam 2 Practice Mth 3 Exm Prctice Februry 8, 03 Exm will cover 7.4, 7.5, 7.7, 7.8, 8.-3 nd 8.5. Plese note tht integrtion skills lerned in erlier sections will still be needed for the mteril in 7.5, 7.8 nd chpter 8. This

More information

Problem Set 3 Solutions

Problem Set 3 Solutions Chemistry 36 Dr Jen M Stndrd Problem Set 3 Solutions 1 Verify for the prticle in one-dimensionl box by explicit integrtion tht the wvefunction ψ ( x) π x is normlized To verify tht ψ ( x) is normlized,

More information

5.7 Improper Integrals

5.7 Improper Integrals 458 pplictions of definite integrls 5.7 Improper Integrls In Section 5.4, we computed the work required to lift pylod of mss m from the surfce of moon of mss nd rdius R to height H bove the surfce of the

More information

Properties of Integrals, Indefinite Integrals. Goals: Definition of the Definite Integral Integral Calculations using Antiderivatives

Properties of Integrals, Indefinite Integrals. Goals: Definition of the Definite Integral Integral Calculations using Antiderivatives Block #6: Properties of Integrls, Indefinite Integrls Gols: Definition of the Definite Integrl Integrl Clcultions using Antiderivtives Properties of Integrls The Indefinite Integrl 1 Riemnn Sums - 1 Riemnn

More information

Strategy: Use the Gibbs phase rule (Equation 5.3). How many components are present?

Strategy: Use the Gibbs phase rule (Equation 5.3). How many components are present? University Chemistry Quiz 4 2014/12/11 1. (5%) Wht is the dimensionlity of the three-phse coexistence region in mixture of Al, Ni, nd Cu? Wht type of geometricl region dose this define? Strtegy: Use the

More information

Numerical Analysis: Trapezoidal and Simpson s Rule

Numerical Analysis: Trapezoidal and Simpson s Rule nd Simpson s Mthemticl question we re interested in numericlly nswering How to we evlute I = f (x) dx? Clculus tells us tht if F(x) is the ntiderivtive of function f (x) on the intervl [, b], then I =

More information

Chapter 6 Notes, Larson/Hostetler 3e

Chapter 6 Notes, Larson/Hostetler 3e Contents 6. Antiderivtives nd the Rules of Integrtion.......................... 6. Are nd the Definite Integrl.................................. 6.. Are............................................ 6. Reimnn

More information

n f(x i ) x. i=1 In section 4.2, we defined the definite integral of f from x = a to x = b as n f(x i ) x; f(x) dx = lim i=1

n f(x i ) x. i=1 In section 4.2, we defined the definite integral of f from x = a to x = b as n f(x i ) x; f(x) dx = lim i=1 The Fundmentl Theorem of Clculus As we continue to study the re problem, let s think bck to wht we know bout computing res of regions enclosed by curves. If we wnt to find the re of the region below the

More information

Review of Calculus, cont d

Review of Calculus, cont d Jim Lmbers MAT 460 Fll Semester 2009-10 Lecture 3 Notes These notes correspond to Section 1.1 in the text. Review of Clculus, cont d Riemnn Sums nd the Definite Integrl There re mny cses in which some

More information

Lecture 20: Numerical Integration III

Lecture 20: Numerical Integration III cs4: introduction to numericl nlysis /8/0 Lecture 0: Numericl Integrtion III Instructor: Professor Amos Ron Scribes: Mrk Cowlishw, Yunpeng Li, Nthnel Fillmore For the lst few lectures we hve discussed

More information

NUMERICAL INTEGRATION

NUMERICAL INTEGRATION NUMERICAL INTEGRATION How do we evlute I = f (x) dx By the fundmentl theorem of clculus, if F (x) is n ntiderivtive of f (x), then I = f (x) dx = F (x) b = F (b) F () However, in prctice most integrls

More information

Math 8 Winter 2015 Applications of Integration

Math 8 Winter 2015 Applications of Integration Mth 8 Winter 205 Applictions of Integrtion Here re few importnt pplictions of integrtion. The pplictions you my see on n exm in this course include only the Net Chnge Theorem (which is relly just the Fundmentl

More information

UNIT 1 FUNCTIONS AND THEIR INVERSES Lesson 1.4: Logarithmic Functions as Inverses Instruction

UNIT 1 FUNCTIONS AND THEIR INVERSES Lesson 1.4: Logarithmic Functions as Inverses Instruction Lesson : Logrithmic Functions s Inverses Prerequisite Skills This lesson requires the use of the following skills: determining the dependent nd independent vribles in n exponentil function bsed on dt from

More information

Math& 152 Section Integration by Parts

Math& 152 Section Integration by Parts Mth& 5 Section 7. - Integrtion by Prts Integrtion by prts is rule tht trnsforms the integrl of the product of two functions into other (idelly simpler) integrls. Recll from Clculus I tht given two differentible

More information

New data structures to reduce data size and search time

New data structures to reduce data size and search time New dt structures to reduce dt size nd serch time Tsuneo Kuwbr Deprtment of Informtion Sciences, Fculty of Science, Kngw University, Hirtsuk-shi, Jpn FIT2018 1D-1, No2, pp1-4 Copyright (c)2018 by The Institute

More information

Lecture 21: Order statistics

Lecture 21: Order statistics Lecture : Order sttistics Suppose we hve N mesurements of sclr, x i =, N Tke ll mesurements nd sort them into scending order x x x 3 x N Define the mesured running integrl S N (x) = 0 for x < x = i/n for

More information

P 3 (x) = f(0) + f (0)x + f (0) 2. x 2 + f (0) . In the problem set, you are asked to show, in general, the n th order term is a n = f (n) (0)

P 3 (x) = f(0) + f (0)x + f (0) 2. x 2 + f (0) . In the problem set, you are asked to show, in general, the n th order term is a n = f (n) (0) 1 Tylor polynomils In Section 3.5, we discussed how to pproximte function f(x) round point in terms of its first derivtive f (x) evluted t, tht is using the liner pproximtion f() + f ()(x ). We clled this

More information

Math 1B, lecture 4: Error bounds for numerical methods

Math 1B, lecture 4: Error bounds for numerical methods Mth B, lecture 4: Error bounds for numericl methods Nthn Pflueger 4 September 0 Introduction The five numericl methods descried in the previous lecture ll operte by the sme principle: they pproximte the

More information

MIXED MODELS (Sections ) I) In the unrestricted model, interactions are treated as in the random effects model:

MIXED MODELS (Sections ) I) In the unrestricted model, interactions are treated as in the random effects model: 1 2 MIXED MODELS (Sections 17.7 17.8) Exmple: Suppose tht in the fiber breking strength exmple, the four mchines used were the only ones of interest, but the interest ws over wide rnge of opertors, nd

More information

Numerical Integration

Numerical Integration Chpter 1 Numericl Integrtion Numericl differentition methods compute pproximtions to the derivtive of function from known vlues of the function. Numericl integrtion uses the sme informtion to compute numericl

More information

Construction of Gauss Quadrature Rules

Construction of Gauss Quadrature Rules Jim Lmbers MAT 772 Fll Semester 2010-11 Lecture 15 Notes These notes correspond to Sections 10.2 nd 10.3 in the text. Construction of Guss Qudrture Rules Previously, we lerned tht Newton-Cotes qudrture

More information

The Velocity Factor of an Insulated Two-Wire Transmission Line

The Velocity Factor of an Insulated Two-Wire Transmission Line The Velocity Fctor of n Insulted Two-Wire Trnsmission Line Problem Kirk T. McDonld Joseph Henry Lbortories, Princeton University, Princeton, NJ 08544 Mrch 7, 008 Estimte the velocity fctor F = v/c nd the

More information

Math 31S. Rumbos Fall Solutions to Assignment #16

Math 31S. Rumbos Fall Solutions to Assignment #16 Mth 31S. Rumbos Fll 2016 1 Solutions to Assignment #16 1. Logistic Growth 1. Suppose tht the growth of certin niml popultion is governed by the differentil eqution 1000 dn N dt = 100 N, (1) where N(t)

More information

CHM Physical Chemistry I Chapter 1 - Supplementary Material

CHM Physical Chemistry I Chapter 1 - Supplementary Material CHM 3410 - Physicl Chemistry I Chpter 1 - Supplementry Mteril For review of some bsic concepts in mth, see Atkins "Mthemticl Bckground 1 (pp 59-6), nd "Mthemticl Bckground " (pp 109-111). 1. Derivtion

More information

On the Uncertainty of Sensors Based on Magnetic Effects. E. Hristoforou, E. Kayafas, A. Ktena, DM Kepaptsoglou

On the Uncertainty of Sensors Based on Magnetic Effects. E. Hristoforou, E. Kayafas, A. Ktena, DM Kepaptsoglou On the Uncertinty of Sensors Bsed on Mgnetic Effects E. ristoforou, E. Kyfs, A. Kten, DM Kepptsoglou Ntionl Technicl University of Athens, Zogrfou Cmpus, Athens 1578, Greece Tel: +3177178, Fx: +3177119,

More information

Space Curves. Recall the parametric equations of a curve in xy-plane and compare them with parametric equations of a curve in space.

Space Curves. Recall the parametric equations of a curve in xy-plane and compare them with parametric equations of a curve in space. Clculus 3 Li Vs Spce Curves Recll the prmetric equtions of curve in xy-plne nd compre them with prmetric equtions of curve in spce. Prmetric curve in plne x = x(t) y = y(t) Prmetric curve in spce x = x(t)

More information

Tests for the Ratio of Two Poisson Rates

Tests for the Ratio of Two Poisson Rates Chpter 437 Tests for the Rtio of Two Poisson Rtes Introduction The Poisson probbility lw gives the probbility distribution of the number of events occurring in specified intervl of time or spce. The Poisson

More information

Physics 116C Solution of inhomogeneous ordinary differential equations using Green s functions

Physics 116C Solution of inhomogeneous ordinary differential equations using Green s functions Physics 6C Solution of inhomogeneous ordinry differentil equtions using Green s functions Peter Young November 5, 29 Homogeneous Equtions We hve studied, especilly in long HW problem, second order liner

More information

CONTRIBUTION TO THE EXTENDED DYNAMIC PLANE SOURCE METHOD

CONTRIBUTION TO THE EXTENDED DYNAMIC PLANE SOURCE METHOD CONTRIBUTION TO THE EXTENDED DYNAMIC PLANE SOURCE METHOD Svetozár Mlinrič Deprtment of Physics, Fculty of Nturl Sciences, Constntine the Philosopher University, Tr. A. Hlinku, SK-949 74 Nitr, Slovki Emil:

More information

Chapter 9: Inferences based on Two samples: Confidence intervals and tests of hypotheses

Chapter 9: Inferences based on Two samples: Confidence intervals and tests of hypotheses Chpter 9: Inferences bsed on Two smples: Confidence intervls nd tests of hypotheses 9.1 The trget prmeter : difference between two popultion mens : difference between two popultion proportions : rtio of

More information

Fig. 1. Open-Loop and Closed-Loop Systems with Plant Variations

Fig. 1. Open-Loop and Closed-Loop Systems with Plant Variations ME 3600 Control ystems Chrcteristics of Open-Loop nd Closed-Loop ystems Importnt Control ystem Chrcteristics o ensitivity of system response to prmetric vritions cn be reduced o rnsient nd stedy-stte responses

More information

Arithmetic Mean Derivative Based Midpoint Rule

Arithmetic Mean Derivative Based Midpoint Rule Applied Mthemticl Sciences, Vol. 1, 018, no. 13, 65-633 HIKARI Ltd www.m-hikri.com https://doi.org/10.1988/ms.018.858 Arithmetic Men Derivtive Bsed Midpoint Rule Rike Mrjulis 1, M. Imrn, Symsudhuh Numericl

More information

Continuous Random Variables

Continuous Random Variables STAT/MATH 395 A - PROBABILITY II UW Winter Qurter 217 Néhémy Lim Continuous Rndom Vribles Nottion. The indictor function of set S is rel-vlued function defined by : { 1 if x S 1 S (x) if x S Suppose tht

More information

THE EXISTENCE-UNIQUENESS THEOREM FOR FIRST-ORDER DIFFERENTIAL EQUATIONS.

THE EXISTENCE-UNIQUENESS THEOREM FOR FIRST-ORDER DIFFERENTIAL EQUATIONS. THE EXISTENCE-UNIQUENESS THEOREM FOR FIRST-ORDER DIFFERENTIAL EQUATIONS RADON ROSBOROUGH https://intuitiveexplntionscom/picrd-lindelof-theorem/ This document is proof of the existence-uniqueness theorem

More information

Chapter 1. Basic Concepts

Chapter 1. Basic Concepts Socrtes Dilecticl Process: The Þrst step is the seprtion of subject into its elements. After this, by deþning nd discovering more bout its prts, one better comprehends the entire subject Socrtes (469-399)

More information

Math 113 Fall Final Exam Review. 2. Applications of Integration Chapter 6 including sections and section 6.8

Math 113 Fall Final Exam Review. 2. Applications of Integration Chapter 6 including sections and section 6.8 Mth 3 Fll 0 The scope of the finl exm will include: Finl Exm Review. Integrls Chpter 5 including sections 5. 5.7, 5.0. Applictions of Integrtion Chpter 6 including sections 6. 6.5 nd section 6.8 3. Infinite

More information

Chapter 3 Solving Nonlinear Equations

Chapter 3 Solving Nonlinear Equations Chpter 3 Solving Nonliner Equtions 3.1 Introduction The nonliner function of unknown vrible x is in the form of where n could be non-integer. Root is the numericl vlue of x tht stisfies f ( x) 0. Grphiclly,

More information

Calculus - Activity 1 Rate of change of a function at a point.

Calculus - Activity 1 Rate of change of a function at a point. Nme: Clss: p 77 Mths Helper Plus Resource Set. Copright 00 Bruce A. Vughn, Techers Choice Softwre Clculus - Activit Rte of chnge of function t point. ) Strt Mths Helper Plus, then lod the file: Clculus

More information

Euler, Ioachimescu and the trapezium rule. G.J.O. Jameson (Math. Gazette 96 (2012), )

Euler, Ioachimescu and the trapezium rule. G.J.O. Jameson (Math. Gazette 96 (2012), ) Euler, Iochimescu nd the trpezium rule G.J.O. Jmeson (Mth. Gzette 96 (0), 36 4) The following results were estblished in recent Gzette rticle [, Theorems, 3, 4]. Given > 0 nd 0 < s

More information

Numerical integration

Numerical integration 2 Numericl integrtion This is pge i Printer: Opque this 2. Introduction Numericl integrtion is problem tht is prt of mny problems in the economics nd econometrics literture. The orgniztion of this chpter

More information

ADVANCEMENT OF THE CLOSELY COUPLED PROBES POTENTIAL DROP TECHNIQUE FOR NDE OF SURFACE CRACKS

ADVANCEMENT OF THE CLOSELY COUPLED PROBES POTENTIAL DROP TECHNIQUE FOR NDE OF SURFACE CRACKS ADVANCEMENT OF THE CLOSELY COUPLED PROBES POTENTIAL DROP TECHNIQUE FOR NDE OF SURFACE CRACKS F. Tkeo 1 nd M. Sk 1 Hchinohe Ntionl College of Technology, Hchinohe, Jpn; Tohoku University, Sendi, Jpn Abstrct:

More information

( dg. ) 2 dt. + dt. dt j + dh. + dt. r(t) dt. Comparing this equation with the one listed above for the length of see that

( dg. ) 2 dt. + dt. dt j + dh. + dt. r(t) dt. Comparing this equation with the one listed above for the length of see that Arc Length of Curves in Three Dimensionl Spce If the vector function r(t) f(t) i + g(t) j + h(t) k trces out the curve C s t vries, we cn mesure distnces long C using formul nerly identicl to one tht we

More information

Terminal Velocity and Raindrop Growth

Terminal Velocity and Raindrop Growth Terminl Velocity nd Rindrop Growth Terminl velocity for rindrop represents blnce in which weight mss times grvity is equl to drg force. F 3 π3 ρ L g in which is drop rdius, g is grvittionl ccelertion,

More information

13: Diffusion in 2 Energy Groups

13: Diffusion in 2 Energy Groups 3: Diffusion in Energy Groups B. Rouben McMster University Course EP 4D3/6D3 Nucler Rector Anlysis (Rector Physics) 5 Sept.-Dec. 5 September Contents We study the diffusion eqution in two energy groups

More information

Numerical Integration

Numerical Integration Chpter 5 Numericl Integrtion Numericl integrtion is the study of how the numericl vlue of n integrl cn be found. Methods of function pproximtion discussed in Chpter??, i.e., function pproximtion vi the

More information

AQA Further Pure 2. Hyperbolic Functions. Section 2: The inverse hyperbolic functions

AQA Further Pure 2. Hyperbolic Functions. Section 2: The inverse hyperbolic functions Hperbolic Functions Section : The inverse hperbolic functions Notes nd Emples These notes contin subsections on The inverse hperbolic functions Integrtion using the inverse hperbolic functions Logrithmic

More information

1B40 Practical Skills

1B40 Practical Skills B40 Prcticl Skills Comining uncertinties from severl quntities error propgtion We usully encounter situtions where the result of n experiment is given in terms of two (or more) quntities. We then need

More information

The Regulated and Riemann Integrals

The Regulated and Riemann Integrals Chpter 1 The Regulted nd Riemnn Integrls 1.1 Introduction We will consider severl different pproches to defining the definite integrl f(x) dx of function f(x). These definitions will ll ssign the sme vlue

More information

Higher Checklist (Unit 3) Higher Checklist (Unit 3) Vectors

Higher Checklist (Unit 3) Higher Checklist (Unit 3) Vectors Vectors Skill Achieved? Know tht sclr is quntity tht hs only size (no direction) Identify rel-life exmples of sclrs such s, temperture, mss, distnce, time, speed, energy nd electric chrge Know tht vector

More information

Lecture 3 Gaussian Probability Distribution

Lecture 3 Gaussian Probability Distribution Introduction Lecture 3 Gussin Probbility Distribution Gussin probbility distribution is perhps the most used distribution in ll of science. lso clled bell shped curve or norml distribution Unlike the binomil

More information

Estimation of Global Solar Radiation at Onitsha with Regression Analysis and Artificial Neural Network Models

Estimation of Global Solar Radiation at Onitsha with Regression Analysis and Artificial Neural Network Models eserch Journl of ecent Sciences ISSN 77-5 es.j.ecent Sci. Estimtion of Globl Solr dition t Onitsh with egression Anlysis nd Artificil Neurl Network Models Abstrct Agbo G.A., Ibeh G.F. *nd Ekpe J.E. Fculty

More information

1.2. Linear Variable Coefficient Equations. y + b "! = a y + b " Remark: The case b = 0 and a non-constant can be solved with the same idea as above.

1.2. Linear Variable Coefficient Equations. y + b ! = a y + b  Remark: The case b = 0 and a non-constant can be solved with the same idea as above. 1 12 Liner Vrible Coefficient Equtions Section Objective(s): Review: Constnt Coefficient Equtions Solving Vrible Coefficient Equtions The Integrting Fctor Method The Bernoulli Eqution 121 Review: Constnt

More information

We partition C into n small arcs by forming a partition of [a, b] by picking s i as follows: a = s 0 < s 1 < < s n = b.

We partition C into n small arcs by forming a partition of [a, b] by picking s i as follows: a = s 0 < s 1 < < s n = b. Mth 255 - Vector lculus II Notes 4.2 Pth nd Line Integrls We begin with discussion of pth integrls (the book clls them sclr line integrls). We will do this for function of two vribles, but these ides cn

More information

Measuring Electron Work Function in Metal

Measuring Electron Work Function in Metal n experiment of the Electron topic Mesuring Electron Work Function in Metl Instructor: 梁生 Office: 7-318 Emil: shling@bjtu.edu.cn Purposes 1. To understnd the concept of electron work function in metl nd

More information

Vyacheslav Telnin. Search for New Numbers.

Vyacheslav Telnin. Search for New Numbers. Vycheslv Telnin Serch for New Numbers. 1 CHAPTER I 2 I.1 Introduction. In 1984, in the first issue for tht yer of the Science nd Life mgzine, I red the rticle "Non-Stndrd Anlysis" by V. Uspensky, in which

More information

Entropy ISSN

Entropy ISSN Entropy 006, 8[], 50-6 50 Entropy ISSN 099-4300 www.mdpi.org/entropy/ ENTROPY GENERATION IN PRESSURE GRADIENT ASSISTED COUETTE FLOW WITH DIFFERENT THERMAL BOUNDARY CONDITIONS Abdul Aziz Deprtment of Mechnicl

More information

potentials A z, F z TE z Modes We use the e j z z =0 we can simply say that the x dependence of E y (1)

potentials A z, F z TE z Modes We use the e j z z =0 we can simply say that the x dependence of E y (1) 3e. Introduction Lecture 3e Rectngulr wveguide So fr in rectngulr coordintes we hve delt with plne wves propgting in simple nd inhomogeneous medi. The power density of plne wve extends over ll spce. Therefore

More information

1 Error Analysis of Simple Rules for Numerical Integration

1 Error Analysis of Simple Rules for Numerical Integration cs41: introduction to numericl nlysis 11/16/10 Lecture 19: Numericl Integrtion II Instructor: Professor Amos Ron Scries: Mrk Cowlishw, Nthnel Fillmore 1 Error Anlysis of Simple Rules for Numericl Integrtion

More information

4 7x =250; 5 3x =500; Read section 3.3, 3.4 Announcements: Bell Ringer: Use your calculator to solve

4 7x =250; 5 3x =500; Read section 3.3, 3.4 Announcements: Bell Ringer: Use your calculator to solve Dte: 3/14/13 Objective: SWBAT pply properties of exponentil functions nd will pply properties of rithms. Bell Ringer: Use your clcultor to solve 4 7x =250; 5 3x =500; HW Requests: Properties of Log Equtions

More information

7/19/2011. Models of Solution Chemistry- III Acids and Bases

7/19/2011. Models of Solution Chemistry- III Acids and Bases Models of Solution Chemistry- III Acids nd Bses Ionic Atmosphere Model : Revisiting Ionic Strength Ionic strength - mesure of totl concentrtion of ions in the solution Chpter 8 1 2 i μ ( ) 2 c i z c concentrtion

More information

Sufficient condition on noise correlations for scalable quantum computing

Sufficient condition on noise correlations for scalable quantum computing Sufficient condition on noise correltions for sclble quntum computing John Presill, 2 Februry 202 Is quntum computing sclble? The ccurcy threshold theorem for quntum computtion estblishes tht sclbility

More information

6.5 Numerical Approximations of Definite Integrals

6.5 Numerical Approximations of Definite Integrals Arknss Tech University MATH 94: Clculus II Dr. Mrcel B. Finn 6.5 Numericl Approximtions of Definite Integrls Sometimes the integrl of function cnnot be expressed with elementry functions, i.e., polynomil,

More information

SOLUTION OF QUADRATIC NONLINEAR PROBLEMS WITH MULTIPLE SCALES LINDSTEDT-POINCARE METHOD. Mehmet Pakdemirli and Gözde Sarı

SOLUTION OF QUADRATIC NONLINEAR PROBLEMS WITH MULTIPLE SCALES LINDSTEDT-POINCARE METHOD. Mehmet Pakdemirli and Gözde Sarı Mthemticl nd Computtionl Applictions, Vol., No., pp. 37-5, 5 http://dx.doi.org/.99/mc-5- SOLUTION OF QUADRATIC NONLINEAR PROBLEMS WITH MULTIPLE SCALES LINDSTEDT-POINCARE METHOD Mehmet Pkdemirli nd Gözde

More information

Testing categorized bivariate normality with two-stage. polychoric correlation estimates

Testing categorized bivariate normality with two-stage. polychoric correlation estimates Testing ctegorized bivrite normlity with two-stge polychoric correltion estimtes Albert Mydeu-Olivres Dept. of Psychology University of Brcelon Address correspondence to: Albert Mydeu-Olivres. Fculty of

More information

Module 2: Rate Law & Stoichiomtery (Chapter 3, Fogler)

Module 2: Rate Law & Stoichiomtery (Chapter 3, Fogler) CHE 309: Chemicl Rection Engineering Lecture-8 Module 2: Rte Lw & Stoichiomtery (Chpter 3, Fogler) Topics to be covered in tody s lecture Thermodynmics nd Kinetics Rection rtes for reversible rections

More information

Credibility Hypothesis Testing of Fuzzy Triangular Distributions

Credibility Hypothesis Testing of Fuzzy Triangular Distributions 666663 Journl of Uncertin Systems Vol.9, No., pp.6-74, 5 Online t: www.jus.org.uk Credibility Hypothesis Testing of Fuzzy Tringulr Distributions S. Smpth, B. Rmy Received April 3; Revised 4 April 4 Abstrct

More information

Polynomial Approximations for the Natural Logarithm and Arctangent Functions. Math 230

Polynomial Approximations for the Natural Logarithm and Arctangent Functions. Math 230 Polynomil Approimtions for the Nturl Logrithm nd Arctngent Functions Mth 23 You recll from first semester clculus how one cn use the derivtive to find n eqution for the tngent line to function t given

More information

An approximation to the arithmetic-geometric mean. G.J.O. Jameson, Math. Gazette 98 (2014), 85 95

An approximation to the arithmetic-geometric mean. G.J.O. Jameson, Math. Gazette 98 (2014), 85 95 An pproximtion to the rithmetic-geometric men G.J.O. Jmeson, Mth. Gzette 98 (4), 85 95 Given positive numbers > b, consider the itertion given by =, b = b nd n+ = ( n + b n ), b n+ = ( n b n ) /. At ech

More information

Estimation of the particle concentration in hydraulic liquid by the in-line automatic particle counter based on the CMOS image sensor

Estimation of the particle concentration in hydraulic liquid by the in-line automatic particle counter based on the CMOS image sensor Glyndŵr University Reserch Online Conference Presenttion Estimtion of the prticle concentrtion in hydrulic liquid by the in-line utomtic prticle counter bsed on the CMOS imge sensor Kornilin, D.V., Kudryvtsev,

More information

The steps of the hypothesis test

The steps of the hypothesis test ttisticl Methods I (EXT 7005) Pge 78 Mosquito species Time of dy A B C Mid morning 0.0088 5.4900 5.5000 Mid Afternoon.3400 0.0300 0.8700 Dusk 0.600 5.400 3.000 The Chi squre test sttistic is the sum of

More information

The Predom module. Predom calculates and plots isothermal 1-, 2- and 3-metal predominance area diagrams. Predom accesses only compound databases.

The Predom module. Predom calculates and plots isothermal 1-, 2- and 3-metal predominance area diagrams. Predom accesses only compound databases. Section 1 Section 2 The module clcultes nd plots isotherml 1-, 2- nd 3-metl predominnce re digrms. ccesses only compound dtbses. Tble of Contents Tble of Contents Opening the module Section 3 Stoichiometric

More information

Discrete Least-squares Approximations

Discrete Least-squares Approximations Discrete Lest-squres Approximtions Given set of dt points (x, y ), (x, y ),, (x m, y m ), norml nd useful prctice in mny pplictions in sttistics, engineering nd other pplied sciences is to construct curve

More information

AP Calculus Multiple Choice: BC Edition Solutions

AP Calculus Multiple Choice: BC Edition Solutions AP Clculus Multiple Choice: BC Edition Solutions J. Slon Mrch 8, 04 ) 0 dx ( x) is A) B) C) D) E) Divergent This function inside the integrl hs verticl symptotes t x =, nd the integrl bounds contin this

More information

1.9 C 2 inner variations

1.9 C 2 inner variations 46 CHAPTER 1. INDIRECT METHODS 1.9 C 2 inner vritions So fr, we hve restricted ttention to liner vritions. These re vritions of the form vx; ǫ = ux + ǫφx where φ is in some liner perturbtion clss P, for

More information

Conservation Law. Chapter Goal. 5.2 Theory

Conservation Law. Chapter Goal. 5.2 Theory Chpter 5 Conservtion Lw 5.1 Gol Our long term gol is to understnd how mny mthemticl models re derived. We study how certin quntity chnges with time in given region (sptil domin). We first derive the very

More information

Chapter 5 : Continuous Random Variables

Chapter 5 : Continuous Random Variables STAT/MATH 395 A - PROBABILITY II UW Winter Qurter 216 Néhémy Lim Chpter 5 : Continuous Rndom Vribles Nottions. N {, 1, 2,...}, set of nturl numbers (i.e. ll nonnegtive integers); N {1, 2,...}, set of ll

More information

Math Calculus with Analytic Geometry II

Math Calculus with Analytic Geometry II orem of definite Mth 5.0 with Anlytic Geometry II Jnury 4, 0 orem of definite If < b then b f (x) dx = ( under f bove x-xis) ( bove f under x-xis) Exmple 8 0 3 9 x dx = π 3 4 = 9π 4 orem of definite Problem

More information

1 The Riemann Integral

1 The Riemann Integral The Riemnn Integrl. An exmple leding to the notion of integrl (res) We know how to find (i.e. define) the re of rectngle (bse height), tringle ( (sum of res of tringles). But how do we find/define n re

More information

The Fundamental Theorem of Calculus. The Total Change Theorem and the Area Under a Curve.

The Fundamental Theorem of Calculus. The Total Change Theorem and the Area Under a Curve. Clculus Li Vs The Fundmentl Theorem of Clculus. The Totl Chnge Theorem nd the Are Under Curve. Recll the following fct from Clculus course. If continuous function f(x) represents the rte of chnge of F

More information

Estimation of Binomial Distribution in the Light of Future Data

Estimation of Binomial Distribution in the Light of Future Data British Journl of Mthemtics & Computer Science 102: 1-7, 2015, Article no.bjmcs.19191 ISSN: 2231-0851 SCIENCEDOMAIN interntionl www.sciencedomin.org Estimtion of Binomil Distribution in the Light of Future

More information

Improper Integrals. Type I Improper Integrals How do we evaluate an integral such as

Improper Integrals. Type I Improper Integrals How do we evaluate an integral such as Improper Integrls Two different types of integrls cn qulify s improper. The first type of improper integrl (which we will refer to s Type I) involves evluting n integrl over n infinite region. In the grph

More information

A027 Uncertainties in Local Anisotropy Estimation from Multi-offset VSP Data

A027 Uncertainties in Local Anisotropy Estimation from Multi-offset VSP Data A07 Uncertinties in Locl Anisotropy Estimtion from Multi-offset VSP Dt M. Asghrzdeh* (Curtin University), A. Bon (Curtin University), R. Pevzner (Curtin University), M. Urosevic (Curtin University) & B.

More information

S. S. Dragomir. 2, we have the inequality. b a

S. S. Dragomir. 2, we have the inequality. b a Bull Koren Mth Soc 005 No pp 3 30 SOME COMPANIONS OF OSTROWSKI S INEQUALITY FOR ABSOLUTELY CONTINUOUS FUNCTIONS AND APPLICATIONS S S Drgomir Abstrct Compnions of Ostrowski s integrl ineulity for bsolutely

More information

The Wave Equation I. MA 436 Kurt Bryan

The Wave Equation I. MA 436 Kurt Bryan 1 Introduction The Wve Eqution I MA 436 Kurt Bryn Consider string stretching long the x xis, of indeterminte (or even infinite!) length. We wnt to derive n eqution which models the motion of the string

More information

Math 32B Discussion Session Session 7 Notes August 28, 2018

Math 32B Discussion Session Session 7 Notes August 28, 2018 Mth 32B iscussion ession ession 7 Notes August 28, 28 In tody s discussion we ll tlk bout surfce integrls both of sclr functions nd of vector fields nd we ll try to relte these to the mny other integrls

More information

SUMMER KNOWHOW STUDY AND LEARNING CENTRE

SUMMER KNOWHOW STUDY AND LEARNING CENTRE SUMMER KNOWHOW STUDY AND LEARNING CENTRE Indices & Logrithms 2 Contents Indices.2 Frctionl Indices.4 Logrithms 6 Exponentil equtions. Simplifying Surds 13 Opertions on Surds..16 Scientific Nottion..18

More information

Student Activity 3: Single Factor ANOVA

Student Activity 3: Single Factor ANOVA MATH 40 Student Activity 3: Single Fctor ANOVA Some Bsic Concepts In designed experiment, two or more tretments, or combintions of tretments, is pplied to experimentl units The number of tretments, whether

More information

#6A&B Magnetic Field Mapping

#6A&B Magnetic Field Mapping #6A& Mgnetic Field Mpping Gol y performing this lb experiment, you will: 1. use mgnetic field mesurement technique bsed on Frdy s Lw (see the previous experiment),. study the mgnetic fields generted by

More information

Definite integral. Mathematics FRDIS MENDELU

Definite integral. Mathematics FRDIS MENDELU Definite integrl Mthemtics FRDIS MENDELU Simon Fišnrová Brno 1 Motivtion - re under curve Suppose, for simplicity, tht y = f(x) is nonnegtive nd continuous function defined on [, b]. Wht is the re of the

More information