ENV05: METROLOGY FOR OCEAN SALINITY AND ACIDITY

Size: px
Start display at page:

Download "ENV05: METROLOGY FOR OCEAN SALINITY AND ACIDITY"

Transcription

1 Kck-off meetng EMRP ENV5 Ocean Metrology - Setember, PB Berln ENV5: MEROLOGY FOR OCEAN SALINIY AND ACIDIY WP: Extenson of measurement range for thermohyscal arameters (INRM, PB) ISIUO MEROLOGICA Smona Lago INRM Steffen Rudtsch PB

2 Labour Resources: - PB - INRIM 3- IPQ 4- JRC 5- LNE 6- SYKE 7- MKEH WP NPL 9- SMU - U - UoP OAL Start month: Setember, End month: August 4 he man ams of the WP are: accurate exermental seed of sound measurements n seawater as functon of temerature ( C u to 4 C), ressures u to 7 MPa and salnty between 4 and 4 n-stu measurements of temerature and seed of sound hese nformaton are needed for further mrovements of the Equaton of State of seawater and to resolve exermental dscreances of hgh ressure seed of sound data. Dfferently from now avalable thermohyscal roertes data, those obtaned n ths WP wll refer to 8 dfferent Practcal Salnty values reared n WP (ask. - D..). ISIUO MEROLOGICA

3 Summary of Delverables for WP ask.: Start month Setember, End month Arl 4 Seed of sound measurements for metrologcal characterzaton of seawater (INRM, PB) Delverable number D.. D.. Delverable descrton Exermental devce comatblty wth chemcal characterstcs of SW tested estng of the exermental setu for the hase comarson method fnshed D..3 SoS results ( C < t < C, < < 7 MPa) D..4 SoS results ( C < t < 4 C, < < 7 MPa), D..5 D..6 Paer about SoS data as a functon of, and S submtted to a eer-revewed ournal Reort on methodology for nstu SoS determnatons submtted to a trade ournal Lead Partcant Other Partcants Delverable tye Delvery date INRM - Reort October PB - Reort October 3 INRM PB Data set December 3 INRM PB Data set February 4 INRM PB Publcaton Arl 4 PB INRM Reort Arl 4 ISIUO MEROLOGICA

4 Summary of Delverables for WP ask.: Start month Arl 3, End month August 4 Determnaton of thermohyscal roertes of Seawater (INRM) Delverable number D.. D.. Delverable descrton Comarson data between the seed of sound results obtaned by INRM and PB and nowadays avalable Equaton of state obtaned Paer about thermohyscal roertes of seawater obtaned from exermental measurements submtted to a eer-revewed ournal Lead Partcant Other Partcants Delverable tye Delvery date INRM - Data set, reort March 4 INRM - Publcaton August 4 ISIUO MEROLOGICA

5 Summary of Delverables for WP ask.3: Start month: Setember, End month: August 4 Imroved n-stu measurements of temerature and seed of sound (PB, INRM) Delverable number D.3. Delverable descrton Calbraton setu for drect nstu SoS sensor s buld Lead Partcant Other Partcants Delverable tye Delvery date PB - Reort October D.3. D.3.3 D.3.4 D.3.5 D.3.6 ISIUO MEROLOGICA Sensor for drect n-stu SoS measurements s tested Determnaton of uncertanty contrbutons of n-stu measurements of electrcal conductvty, temerature, and densty (CD) of ocean water erformed Metrologcal analyss of the uncertanty of drect SoS measurements, keeng nto account all the contrbutng arameters done Paer about self calbratng temerature sensors submtted to a eer-revewed ournal Gude for mroved n-stu measurements of oceanc temeratures done PB - Reort February 3 PB - Reort Arl 4 INRM PB Reort Arl 4 PB - Publcaton August 4 PB INRM Good Practce Gude August 4

6 ask.: Seed of sound measurements for metrologcal characterzaton of seawater (INRM, PB) he am of ths task are measurement results of seed of sound n seawater n a wde range of temerature ( C u to 4 C), ressures u to 7 MPa and salnty between 4 and 4 by means of an ultrasonc double-reflector ulseecho technque. Because of the large mact of accurate seed of sound data, the results wll be comared, at secfc temeratures and salntes, wth those obtaned at ambent ressure by a hase-comarson method. hs task wll enable to obtan accurate seed of sound values as a functon of the salnty, wth an uncertanty of about. % over the ranges secfed above. ISIUO MEROLOGICA

7 Measurement technque : Pulse-Echo method FUNCION GENERAOR (snusodal burst) 5 MHz L L PZ u t t t OSCILLOSCOPE L eco eco 3 eco 4 eco Frst Pulse L = w L = w(t - ) L = wt Second Pulse L = w L = w(t - ) L = wt w ex ( L L) L ( t t ) w ex = exermental seed of sound = delay between the two echoes L = dfference between the acoustc ath-lengths ISIUO MEROLOGICA

8 Ambent ressure lqud vessel Needle valve Pressure amlfers Mechancal manometer Vacuum um connector Pressure transducer Exermental Aaratus Ch Ch Lqud bath thermostat Hgh ressure lqud vessel 4 Ultrasonc cell 3 5 P I D Seral GPIB ISIUO MEROLOGICA

9 Ambent ressure lqud vessel Resstance brdge Osclloscoe Functon generator Exermental Aaratus Dewar Pressure amlfer Vacuum um ISIUO MEROLOGICA

10 u, m s- Seed of sound measurements n ure Water u, m s - emerature, K a b K 7 36 u, m s c em eratu re, K P res su re, M P a d ressure, MPa. MPa 9 MPa 74 K K 89 K 34 K 39 K 334 K 349 K 364 K 379 K 394 K ISIUO MEROLOGICA ressure, M Pa em erature, K. MPa MPa MPa 3 MPa 4 MPa 5 MPa 6 MPa 7 MPa 8 MPa 9 MPa

11 Estmated Uncertanty for ure Water w w L,,, meas w L w w meas w meas L wmeas wmeas Uncertanty Source Relatve Magntude Determnaton of the acoustc ath L L.6 % Determnaton of temoral delay. % emerature measurements Pressure measurements w w w w.3 %.3 % Estmated Overall Uncertanty <.5 % ISIUO MEROLOGICA

12 Devatons of w ex from w IAPWS-95 for ure Water IAPWS-95 4 (u ex - u IAPW S-95 )/ u IAPW S IAPWS K 89 K 34 K 39 K 334 K 349 K 364 K 379 K 394 K ressure, MPa ISIUO MEROLOGICA

13 Very relmnary SoS measurements n Standard Seawater (s = 35 ): Problem!!! After strrng ISIUO MEROLOGICA

14 Estmated Uncertanty for Standard Seawater (s = 35 ) wex w L,,,, s Uncertanty Source Relatve Magntude Determnaton of the acoustc ath L L.4 % Determnaton of temoral delay emerature measurements Pressure measurements Salnty/Comoston. % u u u.3 % u. % S S.3 % Estmated Overall Uncertanty.5 % ISIUO MEROLOGICA

15 Devatons of w INRM from w EOS- [] for Seawater EOS- uncertanty (.5%) ISIUO MEROLOGICA [] IAPWS Formulaton 8 for the hermodynamc Proertes of Seawater (SIA Lbrary)

16 ISIUO MEROLOGICA

17 ask.: Determnaton of thermohyscal roertes of Seawater (INRM) Defnng the Equaton of State of seawater s fundamental for many actvtes concerned wth observng the hyscal state of the oceans and reresentng ocean rocesses n numercal models. he characterzaton of seawater can rovde a metrologcal suort to the analyss and redcton of global clmate change. he thermodynamc quanttes measured wll be merged together wth the am to calculate those roertes that are not drectly accessble by exermental measurements, but that can lay a fundamental role n the modellng comlex systems nvolvng seawater. INRM wll mlement an emrcal Equaton of State of Seawater, as a functon of temerature, densty and salnty, based on analytcal thermodynamc relatonshs, and lmted to the lqud hase. ISIUO MEROLOGICA

18 ISIUO MEROLOGICA = densty c = sobarc secfc heat caacty = thermal exanson coeff. S = entroy w c c In a flud, there are quanttes that are very useful both for mlementng and for checkng the redctons of ts equaton of state (EoS). In artcular, asde from densty and vaor ressure, seed of sound s the next most mortant roerty for develong excellent equatons of state (more accurate the SoS data are, more accurate the EoS wll be). S w, Seed of sound as thermodynamcal quantty Intal condtons: ), ( );, ( c Among dfferent ways to obtan the thermodynamc roertes (and EoS) of a flud n lqud hase, there s the ossblty to solve a system of two dfferental equatons, where densty and secfc heat caacty are the unknown varables, exressed as functons of temerature and ressure.

19 hermodynamc roertes from seed of sound measurements Advantages of ths aroach: few ntal condtons ermt to determne ndrectly the thermodynamc roertes n a wde range of temerature and ressure, wth a good accuracy (comarable wth that obtaned by drect measurements), usng the seed of sound data as control onts for the algorthm of mlementaton. n lquds, drect accurate measurements of quanttes lke densty or, esecally, secfc heat caacty become extremely dffcult n condtons of hgh ressure, as consequence ths method results artcularly attractve. Moreover, wth a comlete knowledge of densty and sobarc heat caacty as a functon of temerature and ressure, all other observable thermodynamc roertes can then be calculated, ncludng: ISIUO MEROLOGICA Adabatc comressblty, S hermal exanson coeffcent, Isothermal comressblty, Isochorc heat caacty, c v w S w c c v c

20 Recursve Equaton Method he REM method s based on the resoluton of recursve equatons, by means of (,,s) and c (,,s) known at reference ressure, as a functon of the temerature, consderng known the seed of sound functon w(,,s), at least over a temerature and ressure range. Usng a mxed ntegraton method, analytc and numercal, t s ossble to determne the felds (,,s) and c (,,s) over the same doman of w(,,s). he am s to mrove the accuracy of the determnatons of the unknown functons values, n artcular those ones near the boundary of the ntegraton range and to make a detaled statstcal analyss of the arameters obtaned by fttng and to evaluate the consequent uncertanty roagaton on the calculated coeffcents. B-dmensonal Polynomal Functon N M L w(,, s) w ( ) ( ) ( s s ), l l,, l where N = olynomal degree, M = olynomal degree, L = s olynomal degree, w,,l = unknown arameters Alyng the seed of sound olynomal functon w(,,s) to our exermental row data N M L w u(,, s ) w ( ) ( ) ( s s ) l k k k k,, l k k k l Least-Squares Regresson Method Lookng for the best arameters w,,k that mnmze the ( ) functon n order to obtan a contnuous w(,,s) functon w,, k ISIUO MEROLOGICA

21 Recursve Equaton Method Dfferently from the most wdesread algorthm, the recursve equaton method exects that the mathematcs form of the solutons s establshed a ror and t has been chosen to make use, also for and c, of a bvarate olynomal functon he necessary frst and second dervates have been calculated: N M (, ) a, ( ) ( ), N M (, ) ( ) a, ( ) ( ), N M c (, ) b ( ) ( ), N M w(, ) w ( ) ( ), N M, (, ) a ( ) ( ),, N M, c (, ) b ( ) ( ) Rewrtng the revous equatons system: c w w c, c 3 and the coeffcents regardng the ntal condtons (one-dmensonal olynomal ft): ISIUO MEROLOGICA M (, ) a ( ),, M, c (, ) b ( ) a we obtan the solutons of the recursve equatons for the unknown arameters a, and b, of the system as a functon of the terms a,, b, and w,, : a,, w, b, a, e b, a,, 3, a a a,

22 ISIUO MEROLOGICA REM - Isobarc secfc heat caacty determnaton Usng REM, sobarc secfc heat caacty c (,) can be calculated n a wde - range also startng only by means of seed of sound w(,) and densty (,), as nut data. w c c ), ( w c calculated usng: M a ) ( ) ( N b ) ( ) ( calculated usng: M a ) ( N b ) ( N M w w ) ( ) ( ), (, N M a ) ( ) ( ), (,,, ), ( w b a a c REM allows a detaled statstcal analyss of the arameters and the consequent evaluaton of the uncertanty roagaton on the calculated coeffcents

23 Results of sobarc secfc heat caacty for ure water: Comarson wth the dedcated EoS [] NIS uncertanty 3 K 3 K 3 K 33 K 34 K 35 K (c NIS -c INRIM )/c NIS / MPa ISIUO MEROLOGICA [] NIS Reference Flud hermodynamc and ransort Proertes Database (REFPROP): Verson 9.

24 ask.3: Imroved n-stu measurements of temerature and seed of sound (PB, INRM) Currently the n-stu determnaton of the seed of sound of ocean water s mostly carred out ndrectly. Seed of sound s calculated from measurements of electrcal conductvty, temerature and densty (CD). he am s to comare ths methodology wth drect seed of sound measurements on the bass of a comlete uncertanty analyss. - PB wll determne the uncertanty contrbutons of n stu measurements of electrcal conductvty, temerature and densty of ocean water; wll delver a self calbratng scheme for temerature sensors; wll mrove the n-stu determnaton of temerature and seed of sound by CD measurements and wll test a sensor for n-stu seed of sound measurements. - INRM wll carry on a detaled metrologcal analyss of the uncertanty of drect seed of sound measurements obtaned n ask. keeng nto account all contrbutng arameters and wll suort the uncertanty comarson between CD seed of sound values. ISIUO MEROLOGICA

25 ISIUO MEROLOGICA

26 ISIUO MEROLOGICA

27 Conclusons wo dfferent exermental aaratuses (ulse-echo and hase comarson) wll be set-u n order to obtan a metrologcal themodynamc characterzaton (EoS) of seawater, by means of accurate exermental seed of sound w(,,s) measurements, over an extended regon of s sace. A new method for the determnaton of the thermodynamcal roertes of fluds, based on the combnaton between exermental acoustc measurements and seres ntegraton methods, has been descrbed. he Recursve Equatons Method s based on the resoluton of recursve equatons, for the determnaton of the densty (,,s) and sobarc secfc heat caacty c (,,s) functons, usng the w(,,s) exermental values and the ntal values of densty (,,s) and sobarc secfc heat caacty c (,,s) known at reference ressure, as a functon of temerature. Moreover, an alcaton of REM method has been resented. It ermts an accurate themodynamcal characterzaton of lquds (EoS), by means of only seed of sound w(,,s) and densty (,,s) nut data, as a functon of temerature, ressure and salnty. Develoment of a methodology for mroved temerature measurements, by mroved sensor annealng and more accurate and traceable calbratons. Develoment of a measurement set-u for the calbraton of n-stu seed of sound sensors. ISIUO MEROLOGICA

28 ISIUO MEROLOGICA hank you for your knd attenton!

Hans-Joachim Kretzschmar and Katja Knobloch

Hans-Joachim Kretzschmar and Katja Knobloch Sulementary Backward Equatons for the Industral Formulaton IAPWS-IF of Water and Steam for Fast Calculatons of Heat Cycles, Bolers, and Steam Turbnes Hans-Joachm Kretzschmar and Katja Knobloch Deartment

More information

Speed of sound measurements in liquid Methane at cryogenic temperature and for pressure up to 10 MPa

Speed of sound measurements in liquid Methane at cryogenic temperature and for pressure up to 10 MPa LNGII - raining Day Delft, August 07 Seed of sound measurements in liquid Methane at cryogenic temerature and for ressure u to 0 MPa Simona Lago*, P. Alberto Giuliano Albo INRiM Istituto Nazionale di Ricerca

More information

Evaluating Thermodynamic Properties in LAMMPS

Evaluating Thermodynamic Properties in LAMMPS D. Keffer ME 64 Det. of Materals cence & Engneerng Unversty of ennessee Knoxvlle Evaluatng hermodynamc Proertes n LAMMP Davd Keffer Deartment of Materals cence & Engneerng Unversty of ennessee Knoxvlle

More information

ME 440 Aerospace Engineering Fundamentals

ME 440 Aerospace Engineering Fundamentals Fall 006 ME 440 Aerosace Engneerng Fundamentals roulson hrust Jet Engne F m( & Rocket Engne F m & F ρ A - n ) ρ A he basc rncle nsde the engne s to convert the ressure and thermal energy of the workng

More information

Priority Queuing with Finite Buffer Size and Randomized Push-out Mechanism

Priority Queuing with Finite Buffer Size and Randomized Push-out Mechanism ICN 00 Prorty Queung wth Fnte Buffer Sze and Randomzed Push-out Mechansm Vladmr Zaborovsy, Oleg Zayats, Vladmr Muluha Polytechncal Unversty, Sant-Petersburg, Russa Arl 4, 00 Content I. Introducton II.

More information

Lecture # 02: Pressure measurements and Measurement Uncertainties

Lecture # 02: Pressure measurements and Measurement Uncertainties AerE 3L & AerE343L Lecture Notes Lecture # 0: Pressure measurements and Measurement Uncertantes Dr. Hu H Hu Deartment of Aerosace Engneerng Iowa State Unversty Ames, Iowa 500, U.S.A Mechancal Pressure

More information

A Quadratic Cumulative Production Model for the Material Balance of Abnormally-Pressured Gas Reservoirs F.E. Gonzalez M.S.

A Quadratic Cumulative Production Model for the Material Balance of Abnormally-Pressured Gas Reservoirs F.E. Gonzalez M.S. Formaton Evaluaton and the Analyss of Reservor Performance A Quadratc Cumulatve Producton Model for the Materal Balance of Abnormally-Pressured as Reservors F.E. onale M.S. Thess (2003) T.A. Blasngame,

More information

A Quadratic Cumulative Production Model for the Material Balance of Abnormally-Pressured Gas Reservoirs F.E. Gonzalez M.S.

A Quadratic Cumulative Production Model for the Material Balance of Abnormally-Pressured Gas Reservoirs F.E. Gonzalez M.S. Natural as Engneerng A Quadratc Cumulatve Producton Model for the Materal Balance of Abnormally-Pressured as Reservors F.E. onale M.S. Thess (2003) T.A. Blasngame, Texas A&M U. Deartment of Petroleum Engneerng

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

EURAMET.M.D-S2 Final Report Final report

EURAMET.M.D-S2 Final Report Final report Fnal report on ERAMET blateral comparson on volume of mass standards Project number: 1356 (ERAMET.M.D-S2) Volume of mass standards of 10g, 20 g, 200 g, 1 kg Zoltan Zelenka 1 ; Stuart Davdson 2 ; Cslla

More information

6. Hamilton s Equations

6. Hamilton s Equations 6. Hamlton s Equatons Mchael Fowler A Dynamcal System s Path n Confguraton Sace and n State Sace The story so far: For a mechancal system wth n degrees of freedom, the satal confguraton at some nstant

More information

Uncertainty in measurements of power and energy on power networks

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

More information

[O5A.1] Ethanol pervaporation through high-silica MFI zeolite membrane T. Leppäjärvi*, I. Malinen, J. Tanskanen University of Oulu, Finland

[O5A.1] Ethanol pervaporation through high-silica MFI zeolite membrane T. Leppäjärvi*, I. Malinen, J. Tanskanen University of Oulu, Finland Introducton [OA.] Ethanol ervaoraton through hgh-slca MFI zeolte membrane. Leäjärv I. Malnen. anskanen Unversty o Oulu Fnland he exact transort and searaton mechansms n ervaoraton are not ully understood

More information

Dr. Shalabh Department of Mathematics and Statistics Indian Institute of Technology Kanpur

Dr. Shalabh Department of Mathematics and Statistics Indian Institute of Technology Kanpur Analyss of Varance and Desgn of Exerments-I MODULE III LECTURE - 2 EXPERIMENTAL DESIGN MODELS Dr. Shalabh Deartment of Mathematcs and Statstcs Indan Insttute of Technology Kanur 2 We consder the models

More information

Digital PI Controller Equations

Digital PI Controller Equations Ver. 4, 9 th March 7 Dgtal PI Controller Equatons Probably the most common tye of controller n ndustral ower electroncs s the PI (Proortonal - Integral) controller. In feld orented motor control, PI controllers

More information

Methodological Aspects of the Calculation of the Adiabatic Combustion Temperature of Carbon

Methodological Aspects of the Calculation of the Adiabatic Combustion Temperature of Carbon World Aled Scences Journal 24 (): 483-488, 203 ISSN 88-4952 IDOSI Publcatons, 203 DOI: 0.5829/dos.wasj.203.24..703 Methodologcal Asects of the Calculaton of the Adabatc Combuston emerature of Carbon Alexander

More information

THERMODYNAMICS. Temperature

THERMODYNAMICS. Temperature HERMODYNMICS hermodynamcs s the henomenologcal scence whch descrbes the behavor of macroscoc objects n terms of a small number of macroscoc arameters. s an examle, to descrbe a gas n terms of volume ressure

More information

Machine Learning. Classification. Theory of Classification and Nonparametric Classifier. Representing data: Hypothesis (classifier) Eric Xing

Machine Learning. Classification. Theory of Classification and Nonparametric Classifier. Representing data: Hypothesis (classifier) Eric Xing Machne Learnng 0-70/5 70/5-78, 78, Fall 008 Theory of Classfcaton and Nonarametrc Classfer Erc ng Lecture, Setember 0, 008 Readng: Cha.,5 CB and handouts Classfcaton Reresentng data: M K Hyothess classfer

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

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

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

More information

EP523 Introduction to QFT I

EP523 Introduction to QFT I EP523 Introducton to QFT I Toc 0 INTRODUCTION TO COURSE Deartment of Engneerng Physcs Unversty of Gazante Setember 2011 Sayfa 1 Content Introducton Revew of SR, QM, RQM and EMT Lagrangan Feld Theory An

More information

Adsorption: A gas or gases from a mixture of gases or a liquid (or liquids) from a mixture of liquids is bound physically to the surface of a solid.

Adsorption: A gas or gases from a mixture of gases or a liquid (or liquids) from a mixture of liquids is bound physically to the surface of a solid. Searatons n Chemcal Engneerng Searatons (gas from a mxture of gases, lquds from a mxture of lquds, solds from a soluton of solds n lquds, dssolved gases from lquds, solvents from gases artally/comletely

More information

A quote of the week (or camel of the week): There is no expedience to which a man will not go to avoid the labor of thinking. Thomas A.

A quote of the week (or camel of the week): There is no expedience to which a man will not go to avoid the labor of thinking. Thomas A. A quote of the week (or camel of the week): here s no expedence to whch a man wll not go to avod the labor of thnkng. homas A. Edson Hess law. Algorthm S Select a reacton, possbly contanng specfc compounds

More information

Topology optimization of plate structures subject to initial excitations for minimum dynamic performance index

Topology optimization of plate structures subject to initial excitations for minimum dynamic performance index th World Congress on Structural and Multdsclnary Otmsaton 7 th -2 th, June 25, Sydney Australa oology otmzaton of late structures subject to ntal exctatons for mnmum dynamc erformance ndex Kun Yan, Gengdong

More information

1.72, Groundwater Hydrology Prof. Charles Harvey Lecture Packet #3: Hydraulic Head and Fluid Potential. p o. p o + p

1.72, Groundwater Hydrology Prof. Charles Harvey Lecture Packet #3: Hydraulic Head and Fluid Potential. p o. p o + p 1.7, Groundwater Hydrology Prof. Charles Harvey Lecture Packet #3: Hydraulc Head and Flud Potental What makes water flow? Consder ressure Water Level o A Water Level C o o + B Pressure at A atmosherc (

More information

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

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

More information

Mathematical Modeling of a Lithium Ion Battery

Mathematical Modeling of a Lithium Ion Battery Ecert from the Proceedngs of the COMSOL Conference 9 Boston Mathematcal Modelng of a Lthum Ion Battery Long Ca and Ralh E. Whte * Deartment of Chemcal Engneerng Unversty of South Carolna *Corresondng author:

More information

A family of multivariate distributions with prefixed marginals

A family of multivariate distributions with prefixed marginals A famly of multvarate dstrbutons wth refxed margnals Isdro R. Cruz_Medna, F. Garca_Paez and J. R. Pablos_Tavares. Recursos Naturales, Insttuto Tecnológco de Sonora Cnco de Febrero 88, Cd. Obregón Son.

More information

Confidence intervals for weighted polynomial calibrations

Confidence intervals for weighted polynomial calibrations Confdence ntervals for weghted olynomal calbratons Sergey Maltsev, Amersand Ltd., Moscow, Russa; ur Kalambet, Amersand Internatonal, Inc., Beachwood, OH e-mal: kalambet@amersand-ntl.com htt://www.chromandsec.com

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

Linear Approximation with Regularization and Moving Least Squares

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

More information

Complete Variance Decomposition Methods. Cédric J. Sallaberry

Complete Variance Decomposition Methods. Cédric J. Sallaberry Comlete Varance Decomoston Methods Cédrc J. allaberry enstvty Analyss y y [,,, ] [ y, y,, ] y ny s a vector o uncertan nuts s a vector o results s a comle uncton successon o derent codes, systems o de,

More information

Conservative Surrogate Model using Weighted Kriging Variance for Sampling-based RBDO

Conservative Surrogate Model using Weighted Kriging Variance for Sampling-based RBDO 9 th World Congress on Structural and Multdsclnary Otmzaton June 13-17, 011, Shzuoka, Jaan Conservatve Surrogate Model usng Weghted Krgng Varance for Samlng-based RBDO Lang Zhao 1, K.K. Cho, Ikn Lee 3,

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

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

Lecture 3 Examples and Problems

Lecture 3 Examples and Problems Lecture 3 Examles and Problems Mechancs & thermodynamcs Equartton Frst Law of Thermodynamcs Ideal gases Isothermal and adabatc rocesses Readng: Elements Ch. 1-3 Lecture 3, 1 Wllam Thomson (1824 1907) a.k.a.

More information

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

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

More information

Statistical tools to perform Sensitivity Analysis in the Context of the Evaluation of Measurement Uncertainty

Statistical tools to perform Sensitivity Analysis in the Context of the Evaluation of Measurement Uncertainty Statstcal tools to perform Senstvty Analyss n the Contet of the Evaluaton of Measurement Uncertanty N. Fscher, A. Allard Laboratore natonal de métrologe et d essas (LNE) MATHMET PTB Berln nd June Outlne

More information

Chapter 8 Balances on Nonreactive Processes 8.1 Elements of Energy Balances Calculations 8.1a Reference States A Review

Chapter 8 Balances on Nonreactive Processes 8.1 Elements of Energy Balances Calculations 8.1a Reference States A Review Chater 8 Balances on Nonreactve Processes 8.1 Elements of Energy Balances Calculatons 8.1a Reference States A Revew We can never know the absolute values of U and H for a seces at a gven state. t Fortunately,

More information

PID Controller Design Based on Second Order Model Approximation by Using Stability Boundary Locus Fitting

PID Controller Design Based on Second Order Model Approximation by Using Stability Boundary Locus Fitting PID Controller Desgn Based on Second Order Model Aroxmaton by Usng Stablty Boundary Locus Fttng Furkan Nur Denz, Bars Baykant Alagoz and Nusret Tan Inonu Unversty, Deartment of Electrcal and Electroncs

More information

Power-sum problem, Bernoulli Numbers and Bernoulli Polynomials.

Power-sum problem, Bernoulli Numbers and Bernoulli Polynomials. Power-sum roblem, Bernoull Numbers and Bernoull Polynomals. Arady M. Alt Defnton 1 Power um Problem Fnd the sum n : 1... n where, n N or, usng sum notaton, n n n closed form. Recurrence for n Exercse Usng

More information

Answers Problem Set 2 Chem 314A Williamsen Spring 2000

Answers Problem Set 2 Chem 314A Williamsen Spring 2000 Answers Problem Set Chem 314A Wllamsen Sprng 000 1) Gve me the followng crtcal values from the statstcal tables. a) z-statstc,-sded test, 99.7% confdence lmt ±3 b) t-statstc (Case I), 1-sded test, 95%

More information

Final Report on Bilateral Supplementary Comparison APMP.M.P-S5 in Hydraulic Gauge Pressure from 1 MPa to 10 MPa

Final Report on Bilateral Supplementary Comparison APMP.M.P-S5 in Hydraulic Gauge Pressure from 1 MPa to 10 MPa ASIA-PACIFIC METROLOGY PROGRAMME 10 MPa HYDRAULIC GAUGE PRESSURE BILATERAL SUPPLEMENTARY COMPARISON Comarson Identfer: APMP.M.P-S5 Fnal Reort on Blateral Sulementary Comarson APMP.M.P-S5 n Hydraulc Gauge

More information

Advanced Topics in Optimization. Piecewise Linear Approximation of a Nonlinear Function

Advanced Topics in Optimization. Piecewise Linear Approximation of a Nonlinear Function Advanced Tocs n Otmzaton Pecewse Lnear Aroxmaton of a Nonlnear Functon Otmzaton Methods: M8L Introducton and Objectves Introducton There exsts no general algorthm for nonlnear rogrammng due to ts rregular

More information

DETERMINATION OF UNCERTAINTY ASSOCIATED WITH QUANTIZATION ERRORS USING THE BAYESIAN APPROACH

DETERMINATION OF UNCERTAINTY ASSOCIATED WITH QUANTIZATION ERRORS USING THE BAYESIAN APPROACH Proceedngs, XVII IMEKO World Congress, June 7, 3, Dubrovn, Croata Proceedngs, XVII IMEKO World Congress, June 7, 3, Dubrovn, Croata TC XVII IMEKO World Congress Metrology n the 3rd Mllennum June 7, 3,

More information

BIPM comparison BIPM.RI(II)-K1.Eu-155 of the activity measurements of the radionuclide 155 Eu. G. Ratel and C. Michotte BIPM

BIPM comparison BIPM.RI(II)-K1.Eu-155 of the activity measurements of the radionuclide 155 Eu. G. Ratel and C. Michotte BIPM BIPM comparson BIPM.RI(II)-K1.Eu-155 of the actvty measurements of the radonuclde 155 Eu G. Ratel and C. Mchotte BIPM Abstract In 1993, a natonal metrology nsttute, the NPL (UK), submtted a sample of known

More information

Linear system of the Schrödinger equation Notes on Quantum Mechanics

Linear system of the Schrödinger equation Notes on Quantum Mechanics Lnear sstem of the Schrödnger equaton Notes on Quantum Mechancs htt://quantum.bu.edu/notes/quantummechancs/lnearsstems.df Last udated Wednesda, October 9, 003 :0:08 Corght 003 Dan Dll (dan@bu.edu) Deartment

More information

A total variation approach

A total variation approach Denosng n dgtal radograhy: A total varaton aroach I. Froso M. Lucchese. A. Borghese htt://as-lab.ds.unm.t / 46 I. Froso, M. Lucchese,. A. Borghese Images are corruted by nose ) When measurement of some

More information

Toward a virtual laboratory for the design of acoustic imaging systems

Toward a virtual laboratory for the design of acoustic imaging systems Toward a vrtual laboratory for the desgn of acoustc magng systems PACS Reference : 43.3.Jx Ballandras Sylvan 1 ; Wlm Mkaël 1 ; Laude Vncent 1 ; Danau Wllam 1 ; Dogesche Karm 1 Pastureaud Thomas ; Lardat

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

Outline. Unit Eight Calculations with Entropy. The Second Law. Second Law Notes. Uses of Entropy. Entropy is a Property.

Outline. Unit Eight Calculations with Entropy. The Second Law. Second Law Notes. Uses of Entropy. Entropy is a Property. Unt Eght Calculatons wth Entropy Mechancal Engneerng 370 Thermodynamcs Larry Caretto October 6, 010 Outlne Quz Seven Solutons Second law revew Goals for unt eght Usng entropy to calculate the maxmum work

More information

Polynomial Regression Models

Polynomial Regression Models LINEAR REGRESSION ANALYSIS MODULE XII Lecture - 6 Polynomal Regresson Models Dr. Shalabh Department of Mathematcs and Statstcs Indan Insttute of Technology Kanpur Test of sgnfcance To test the sgnfcance

More information

A Hybrid Variational Iteration Method for Blasius Equation

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

More information

Statistics Chapter 4

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

More information

Uncertainty as the Overlap of Alternate Conditional Distributions

Uncertainty as the Overlap of Alternate Conditional Distributions Uncertanty as the Overlap of Alternate Condtonal Dstrbutons Olena Babak and Clayton V. Deutsch Centre for Computatonal Geostatstcs Department of Cvl & Envronmental Engneerng Unversty of Alberta An mportant

More information

829. An adaptive method for inertia force identification in cantilever under moving mass

829. An adaptive method for inertia force identification in cantilever under moving mass 89. An adaptve method for nerta force dentfcaton n cantlever under movng mass Qang Chen 1, Mnzhuo Wang, Hao Yan 3, Haonan Ye 4, Guola Yang 5 1,, 3, 4 Department of Control and System Engneerng, Nanng Unversty,

More information

Uncertainty and auto-correlation in. Measurement

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

More information

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

PATH INTEGRALS FOR QUADRATIC LAGRANGIANS IN TWO AND MORE DIMENSIONS

PATH INTEGRALS FOR QUADRATIC LAGRANGIANS IN TWO AND MORE DIMENSIONS PATH INTEGRAL FOR QUADRATIC LAGRANGIAN IN TWO AND MORE DIMENION G.. DJORDJEVIC and LJ. NEIC Deartment of Physcs, Faculty of cences, P.O. Box 4, 8 Ns,, Ns, erba, gorandj@juns.n.ac.yu ABTRACT A general form

More information

SMALL AREA ESTIMATES FROM THE AMERICAN COMMUNITY SURVEY USING A HOUSING UNIT MODEL

SMALL AREA ESTIMATES FROM THE AMERICAN COMMUNITY SURVEY USING A HOUSING UNIT MODEL SMALL AREA ESTIMATES FROM THE AMERICAN COMMUNITY SURVEY USING A HOUSING UNIT MODEL Nanak Chand and Donald Malec U.S. Bureau of the Census Abstract The Amercan Communty Survey (ACS) s desgned to, ultmately,

More information

Fuzzy approach to solve multi-objective capacitated transportation problem

Fuzzy approach to solve multi-objective capacitated transportation problem Internatonal Journal of Bonformatcs Research, ISSN: 0975 087, Volume, Issue, 00, -0-4 Fuzzy aroach to solve mult-objectve caactated transortaton roblem Lohgaonkar M. H. and Bajaj V. H.* * Deartment of

More information

Using Genetic Algorithms in System Identification

Using Genetic Algorithms in System Identification Usng Genetc Algorthms n System Identfcaton Ecaterna Vladu Deartment of Electrcal Engneerng and Informaton Technology, Unversty of Oradea, Unverstat, 410087 Oradea, Româna Phone: +40259408435, Fax: +40259408408,

More information

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

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

More information

Analytical Gradient Evaluation of Cost Functions in. General Field Solvers: A Novel Approach for. Optimization of Microwave Structures

Analytical Gradient Evaluation of Cost Functions in. General Field Solvers: A Novel Approach for. Optimization of Microwave Structures IMS 2 Workshop Analytcal Gradent Evaluaton of Cost Functons n General Feld Solvers: A Novel Approach for Optmzaton of Mcrowave Structures P. Harscher, S. Amar* and R. Vahldeck and J. Bornemann* Swss Federal

More information

Numerical studies of space filling designs: optimization algorithms and subprojection properties

Numerical studies of space filling designs: optimization algorithms and subprojection properties umercal studes of sace fllng desgns: otmzaton algorthms and subroecton roertes Bertrand Iooss wth Gullaume Dambln & Matheu Coulet CEMRACS 03 July, 30th, 03 Motvatng eamle: Uncertantes management n smulaton

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

Probabilistic Variation Mode and Effect Analysis: A Case Study of an Air Engine Component

Probabilistic Variation Mode and Effect Analysis: A Case Study of an Air Engine Component Probablstc Varaton Mode and Effect Analyss: A Case Study of an Ar Engne Comonent Pär Johannesson Fraunhofer-Chalmers Research Centre for Industral Mathematcs, Sweden; Par.Johannesson@fcc.chalmers.se Thomas

More information

The International Association for the Properties of Water and Steam

The International Association for the Properties of Water and Steam IAPWS G11-15 The Internatonal Assocaton for the Propertes of Water and Steam Stockholm, Sweden July 015 Gudelne on a Vral Equaton for the Fugacty of HO n Humd Ar 015 Internatonal Assocaton for the Propertes

More information

Bayesian Decision Theory

Bayesian Decision Theory No.4 Bayesan Decson Theory Hu Jang Deartment of Electrcal Engneerng and Comuter Scence Lassonde School of Engneerng York Unversty, Toronto, Canada Outlne attern Classfcaton roblems Bayesan Decson Theory

More information

Lesson 16: Basic Control Modes

Lesson 16: Basic Control Modes 0/8/05 Lesson 6: Basc Control Modes ET 438a Automatc Control Systems Technology lesson6et438a.tx Learnng Objectves Ater ths resentaton you wll be able to: Descrbe the common control modes used n analog

More information

ABSTRACT. 1. Introduction. propagation of. with respect to. Method. dered in. terms of the velocity Cartesin. waves in the. the Atmosphere. D one.

ABSTRACT. 1. Introduction. propagation of. with respect to. Method. dered in. terms of the velocity Cartesin. waves in the. the Atmosphere. D one. Journal of Aled Mathematcs and Physcs,, 13, 1, 1-17 htt://dx.do.org/1.436/jam..13.143 Publshed Onlne October 13 (htt://www.scr.org/journal/jam) Numercal Smulaton of Acoustc-Gravty Waves Proagaton n a Heterogeneous

More information

The Ordinary Least Squares (OLS) Estimator

The Ordinary Least Squares (OLS) Estimator The Ordnary Least Squares (OLS) Estmator 1 Regresson Analyss Regresson Analyss: a statstcal technque for nvestgatng and modelng the relatonshp between varables. Applcatons: Engneerng, the physcal and chemcal

More information

Numerical Methods. ME Mechanical Lab I. Mechanical Engineering ME Lab I

Numerical Methods. ME Mechanical Lab I. Mechanical Engineering ME Lab I 5 9 Mechancal Engneerng -.30 ME Lab I ME.30 Mechancal Lab I Numercal Methods Volt Sne Seres.5 0.5 SIN(X) 0 3 7 5 9 33 37 4 45 49 53 57 6 65 69 73 77 8 85 89 93 97 0-0.5 Normalzed Squared Functon - 0.07

More information

Statistical Material Balance Analysis of Water Drive Reservoirs

Statistical Material Balance Analysis of Water Drive Reservoirs Abstract Research Journal of Chemcal Scences E-ISSN 2231-606X Res. J. Chem. Sc. Statstcal ateral Balance Analyss of Water Drve Reservors Adeloye Olalean chael 1*, Ejofor Chnonso Declan 2 and Abu Robn Nyemenm

More information

Statistics for Business and Economics

Statistics for Business and Economics Statstcs for Busness and Economcs Chapter 11 Smple Regresson Copyrght 010 Pearson Educaton, Inc. Publshng as Prentce Hall Ch. 11-1 11.1 Overvew of Lnear Models n An equaton can be ft to show the best lnear

More information

Application of artificial intelligence in earthquake forecasting

Application of artificial intelligence in earthquake forecasting Alcaton of artfcal ntellgence n earthquae forecastng Zhou Shengu, Wang Chengmn and Ma L Center for Analyss and Predcton of CSB, 63 Fuxng Road, Bejng 00036 P.R.Chna (e-mal zhou@ca.ac.cn; hone: 86 0 6827

More information

A Mathematical Theory of Communication. Claude Shannon s paper presented by Kate Jenkins 2/19/00

A Mathematical Theory of Communication. Claude Shannon s paper presented by Kate Jenkins 2/19/00 A Mathematcal Theory of Communcaton Claude hannon s aer resented by Kate Jenkns 2/19/00 Publshed n two arts, July 1948 and October 1948 n the Bell ystem Techncal Journal Foundng aer of Informaton Theory

More information

CFD simulation of a stratified flow at the inlet of a compact plate heat exchanger

CFD simulation of a stratified flow at the inlet of a compact plate heat exchanger Comutatonal Methods n Multhase Flow I 5 CFD smulaton of a stratfed flow at the nlet of a comact late heat exchanger M. Ahmad, J. F. Fourmgue, P. Mercer & G. Berthoud Commssarat à l Energe Atomue, Grenoble,

More information

Quasi-Static transient Thermal Stresses in a Robin's thin Rectangular plate with internal moving heat source

Quasi-Static transient Thermal Stresses in a Robin's thin Rectangular plate with internal moving heat source 31-7871 Weely Scence Research Journal Orgnal Artcle Vol-1, Issue-44, May 014 Quas-Statc transent Theral Stresses n a Robn's n Rectangular late w nternal ovng heat source D. T. Solane and M.. Durge ABSTRACT

More information

MACHINE APPLIED MACHINE LEARNING LEARNING. Gaussian Mixture Regression

MACHINE APPLIED MACHINE LEARNING LEARNING. Gaussian Mixture Regression 11 MACHINE APPLIED MACHINE LEARNING LEARNING MACHINE LEARNING Gaussan Mture Regresson 22 MACHINE APPLIED MACHINE LEARNING LEARNING Bref summary of last week s lecture 33 MACHINE APPLIED MACHINE LEARNING

More information

COMPOSITE BEAM WITH WEAK SHEAR CONNECTION SUBJECTED TO THERMAL LOAD

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

More information

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

Convection Heat Transfer. Textbook: Convection Heat Transfer. Reference: Convective Heat and Mass Transfer. Convection Heat Transfer

Convection Heat Transfer. Textbook: Convection Heat Transfer. Reference: Convective Heat and Mass Transfer. Convection Heat Transfer Convecton Heat Transfer Tetbook: Convecton Heat Transfer Adran Bean, John Wley & Sons Reference: Convectve Heat and Mass Transfer Kays, Crawford, and Wegand, McGraw-Hll Convecton Heat Transfer Vedat S.

More information

Solutions for Euler and Navier-Stokes Equations in Powers of Time

Solutions for Euler and Navier-Stokes Equations in Powers of Time Solutons for Euler and Naver-Stokes Equatons n Powers of Tme Valdr Montero dos Santos Godo valdr.msgodo@gmal.com Abstract We present a soluton for the Euler and Naver-Stokes equatons for ncompressble case

More information

Review of Thermodynamics

Review of Thermodynamics Revew of hermodynamcs from Statstcal Physcs usng Mathematca James J. Kelly, 1996-2002 We revew the laws of thermodynamcs and some of the technques for dervaton of thermodynamc relatonshs. Introducton Equlbrum

More information

CHAPTER 7 ENERGY BALANCES SYSTEM SYSTEM. * What is energy? * Forms of Energy. - Kinetic energy (KE) - Potential energy (PE) PE = mgz

CHAPTER 7 ENERGY BALANCES SYSTEM SYSTEM. * What is energy? * Forms of Energy. - Kinetic energy (KE) - Potential energy (PE) PE = mgz SYSTM CHAPTR 7 NRGY BALANCS 1 7.1-7. SYSTM nergy & 1st Law of Thermodynamcs * What s energy? * Forms of nergy - Knetc energy (K) K 1 mv - Potental energy (P) P mgz - Internal energy (U) * Total nergy,

More information

Mechanics Physics 151

Mechanics Physics 151 Mechancs hyscs 151 Lecture Canoncal Transformatons (Chater 9) What We Dd Last Tme Drect Condtons Q j Q j = = j, Q, j, Q, Necessary and suffcent j j for Canoncal Transf. = = j Q, Q, j Q, Q, Infntesmal CT

More information

A new Approach for Solving Linear Ordinary Differential Equations

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

More information

Introduction to Regression

Introduction to Regression Introducton to Regresson Dr Tom Ilvento Department of Food and Resource Economcs Overvew The last part of the course wll focus on Regresson Analyss Ths s one of the more powerful statstcal technques Provdes

More information

FUZZY FINITE ELEMENT METHOD

FUZZY FINITE ELEMENT METHOD FUZZY FINITE ELEMENT METHOD RELIABILITY TRUCTURE ANALYI UING PROBABILITY 3.. Maxmum Normal tress Internal force s the shear force, V has a magntude equal to the load P and bendng moment, M. Bendng moments

More information

Segmentation Method of MRI Using Fuzzy Gaussian Basis Neural Network

Segmentation Method of MRI Using Fuzzy Gaussian Basis Neural Network Neural Informaton Processng - Letters and Revews Vol.8, No., August 005 LETTER Segmentaton Method of MRI Usng Fuzzy Gaussan Bass Neural Networ We Sun College of Electrcal and Informaton Engneerng, Hunan

More information

Constitutive Modelling of Superplastic AA-5083

Constitutive Modelling of Superplastic AA-5083 TECHNISCHE MECHANIK, 3, -5, (01, 1-6 submtted: September 19, 011 Consttutve Modellng of Superplastc AA-5083 G. Gulano In ths study a fast procedure for determnng the constants of superplastc 5083 Al alloy

More information

Digital Speech Processing Lecture 14. Linear Predictive Coding (LPC)-Lattice Methods, Applications

Digital Speech Processing Lecture 14. Linear Predictive Coding (LPC)-Lattice Methods, Applications Dgtal Seech Processng Lecture 14 Lnear Predctve Codng (LPC)-Lattce Methods, Alcatons 1 Predcton Error Sgnal 1. Seech Producton Model sn ( ) = asn ( k) + Gun ( ) 2. LPC Model: k = 1 Sz ( ) Hz ( ) = = Uz

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

Role of Tundish Argon Diffuser in Steelmaking Tundish to Improve Inclusion Flotation with CFD and Water Modelling Studies

Role of Tundish Argon Diffuser in Steelmaking Tundish to Improve Inclusion Flotation with CFD and Water Modelling Studies Role of Tundsh Argon Dffuser n Steelmang Tundsh to Imrove Incluson Flotaton wth CFD and Water Modellng Studes Suata Dev, Raeev Kumar Sngh, &Amtava Paul RDCIS, SAIL, Ranch-834002 Abstract - Investgaton

More information

Lecture #06 Hotwire anemometry: Fundamentals and instrumentation

Lecture #06 Hotwire anemometry: Fundamentals and instrumentation AerE 344 Lecture otes Lecture #06 Hotwre anemometry: Fundamentals and nstrumentaton Dr. Hu Hu Department of Aerospace Engneerng Iowa State Unversty Ames, Iowa 500, U.S.A Thermal anemometers: Techncal Fundamentals

More information

Digital Signal Processing

Digital Signal Processing Dgtal Sgnal Processng Dscrete-tme System Analyss Manar Mohasen Offce: F8 Emal: manar.subh@ut.ac.r School of IT Engneerng Revew of Precedent Class Contnuous Sgnal The value of the sgnal s avalable over

More information

Combining Iterative Heuristic Optimization and Uncertainty Analysis methods for Robust Parameter Design

Combining Iterative Heuristic Optimization and Uncertainty Analysis methods for Robust Parameter Design Ths s a rernt of an artcle submtted for consderaton to the ournal Engneerng Otmzaton. It has been acceted and the revsed verson wll be avalable onlne at: htt://ournalsonlne.tandf.co.uk/ Combnng Iteratve

More information

Turbulence classification of load data by the frequency and severity of wind gusts. Oscar Moñux, DEWI GmbH Kevin Bleibler, DEWI GmbH

Turbulence classification of load data by the frequency and severity of wind gusts. Oscar Moñux, DEWI GmbH Kevin Bleibler, DEWI GmbH Turbulence classfcaton of load data by the frequency and severty of wnd gusts Introducton Oscar Moñux, DEWI GmbH Kevn Blebler, DEWI GmbH Durng the wnd turbne developng process, one of the most mportant

More information

Key component in Operational Amplifiers

Key component in Operational Amplifiers Key component n Operatonal Amplfers Objectve of Lecture Descrbe how dependent voltage and current sources functon. Chapter.6 Electrcal Engneerng: Prncples and Applcatons Chapter.6 Fundamentals of Electrc

More information