Lawrence Livermore National Laboratory, Livermore, CA, 94550

Size: px
Start display at page:

Download "Lawrence Livermore National Laboratory, Livermore, CA, 94550"

Transcription

1 4.9 TURBULENCE KINETIC ENERGY BUDGETS AND DISSIPATION RATES IN DISTURBED STABLE BOUNDARY LAYERS Jule K. Lundqust* 1, Mark Pper 2, and Branko Kosov 1 1 Atmospherc Scence Dvson Lawrence Lvermore Natonal Laboratory, Lvermore, CA, Program n Atmospherc and Oceanc Scence, Unversty of Colorado at Boulder 1. INTRODUCTION An mportant parameter n the numercal smulaton of atmospherc boundary layers s the dsspaton length scale, l ε. It s especally mportant n weakly to moderately stable condtons, n whch a tenuous balance between shear producton of turbulence, buoyant destructon of turbulence, and turbulent dsspaton s mantaned. In large-scale models, the dsspaton rate s often parameterzed usng a dagnostc equaton based on the producton of turbulent knetc energy (TKE) and an estmate of the dsspaton length scale. Proper parameterzaton of the dsspaton length scale from expermental data requres accurate estmaton of the rate of dsspaton of TKE from expermental data. Usng data from the MICROFRONTS and CASES-99 feld programs, we evaluate turbulent knetc energy (TKE), TKE dsspaton rate ε, and dsspaton length l ε over a range of stablty regmes represented by a stable boundary layer (SBL), a destablzng ntruson (by frst a cold front and second a densty current) and recovery. These data may be utlzed to test recent parameterzatons of dsspaton rate ε and l ε n order to determne the sutablty of these models for ncluson n mesoscale models for numercal weather predcton or polluton dsperson predcton. 2. DATA SOURCES Data from the MICROFRONTS and CASES-99 feld programs are used n ths study. The data from each experment are descrbed n the subsectons below. 2.1 MICROFRONTS (The cold front) The MICROFRONTS feld experment was conducted from 1 March 1995 through 30 March 1995 at a ste approxmately 75~km northeast of Wchta, near De Graff, Kansas. The feld ste was stuated n gently rollng farmland n eastern Kansas, wth a homogeneous fetch to the northwest. The ASTER faclty, operated by the Natonal Center for Atmospherc Research (NCAR) Atmospherc Technology Dvson, was deployed to collect turbulence data. The ASTER sonc anemometers were used to compute turbulence statstcs for the three velocty components and used to estmate dsspaton rate. A dry Arctc cold front passed the MICROFRONTS ste at approxmately 0237 UTC (2037 LST) 20 March 1995, two hours after local sunset at 1839 LST. Tme seres spannng the perod UTC are shown n Fgure 1.The 6-hr tme perod was chosen because t allows tme for the front to completely pass the nstrumented tower, wth tme on ether sde to vew the state of the surface layer. The top two panels show wnd speed and wnd drecton from the 10m south tower sonc anemometer, at a rate of 10 samples s -1. The next panel shows dry bulb temperature from the 10m south tower platnum resstance thermometer, also at 10 samples s -1. The last panel shows two surface layer scalng parameters, the local frcton velocty u* and the Monn-Obukhov scalng parameter ζ = z/l, where L s a local Obukhov length. Both u* and ζ are calculated from fluxes from the sonc anemometer at the 3m level. These scalng parameters are calculated usng 900-s averagng ntervals, centered on the tme of the frontal passage. The dotted lnes n Fgure 1 delmt the frontal zone. Note, vsually, the sharp ncrease n wnd speed varance wth the passng of the front. After the front passes, the wnd speed and speed varance decay to near prefrontal values. The wnd has a southwesterly component n the prefrontal perod. The temperature trace n panel 3 shows that there was a 2 o C rse n temperature startng at 0200 UTC, possbly due to advecton of warmer ar from the southwest or ncreased mxng n the surface layer. After the frontal passage, temperature decreased steadly due to radatonal coolng and cold ar advecton. The wnd shft and temperature drop were not concdent n ths front, wth the

2 temperature drop at 10m laggng the wnd shft by about 180s. Ths s also observed n Taylor et al. (1993) and Shapro et al. (1985), suggestng that ths front may have an elevated head, lke a densty current. Fgure 1: Tme seres from the 10m south tower nstruments on 20 Mar (A) Wnd speed from the sonc anemometer. (B) Wnd drecton from the sonc anemometer. (C) Temperature from the platnum resstance thermometer. (D) The frcton velocty u* (.) and the Monn-Obukhov scalng parameter ζ (squares). The dotted lnes gve the extent of the frontal zone. 2.2 CASES-99: the densty current The CASES-99 feld experment was conducted from 1 October 1999 through 30 October 1999 east of Wchta, near Leon, Kansas. An extensve array of nstrumentaton ncludng a 60m tower, the HRDL ldar, boundary-layer wnd proflers, radosondes, a tethered lftng system, and two arcraft probed the nocturnal boundary layer throughout the feld program (Poulos et al. 2002a). Local orographc relef dd not exceed 30m, and yet several densty currents were observed durng early evenngs throughout the feld campagn. A densty current passed the CASES-99 man tower at approxmately 0215 UTC (2115 LDT) 20 October 1999, two hours after local sunset at 1900 CDT and four hours after surface heat flux became negatve. Fgure 2 shows an 10 hour tme seres of wnd speed, wnd drecton, vrtual temperature T v, u*, and heat flux from the sonc anemometer located at the 10m level. In addton to the 0215 UTC ntal passage of the densty current, another mxng event occurs at 0315 UTC. The later event s not accompaned by coolng and lkely ndcates the tal end of the densty current. The top two panels show wnd speed and wnd drecton at a rate of 10 samples sec -1. The next panel shows vrtual temperature measured by the sonc anemometer, also at 10 samples sec -1. The bottom panel shows the frcton velocty u* and heat flux, also calculated wth sonc anemometer data. The fluxes are calculated as covarances of perturbatons from 720s mean values. The 0215 UTC densty current caused temperatures at 10m to drop from 10 o to 6 o C for a perod of about fve mnutes. Ths pool of cooler ar was confned to the regon between the surface and 20m; hgher levels (not shown) exhbted gradual coolng rather than an mpulse of cold ar. Whle the cold front was accompaned by a sharp ncrease n wnd speed, the densty current suppressed wnds: wnd speed decreases almost to zero momentarly, and the varance of wnd speed s reduced followng the passage of the densty current. The passage of the densty current s accompaned by an uplft-downdraft couplet (Blumen et al. 1999), as evdent n the local maxma of heat flux. The vertcal lnes on Fgure 2 mark the begnnng and the end of the densty current as defned by the temperature decrease and concurrent wnd shft at the 5m level. The 10m data, presented here, lag the 5m data, ndcatng that the head of the densty current s tlted. Ths tlted structure s also evdent n tme-heght cross sectons of temperature, as shown n Poulos et al. (2002b). 3. DISSIPATION RATE CALCULATIONS As descrbed, for example, n Champagne et al. (1977), f u ( f ) s the frequency spectrum of S velocty component u n the nertal range and α s the Kolmogorov constant for the velocty component, the dsspaton rate s gven by 2π f = U 5/3 S u ( f ) α 3/ 2 ε. Ths technque can be used by any hgh-frequency sensor that can measure veloctes n the nertal range (Oncley et al. 1996). Ths method s compared wth other methods of estmatng ε durng the MICROFRONTS experment n paper 7.5 ( Surface-layer turbulence durng a frontal passage, by Pper and Lundqust) of ths volume and n Pper and Lundqust (2004). Only the

3 streamwse component s used for the calculatons shown here. Values of ε are calculated n 300s ntervals, whereas 60s ntervals are presented n Pper and Lundqust (2004). The longer tme seres both smooths out small-scale fluctuatons and ncreases the confdence n the calculatons (Pper, 2001). Fgure 3 shows a tme seres of dsspaton rate at 10m calculated for the 6 hour nterval depcted n Fgure 1. At the tme of the frontal passage, dsspaton rates ncrease to a maxmum value of ~0.4 m 2 s -3, compared to prefrontal values of ~0.05 m 2 s -3. Dsspaton rate levels reman hgh even after the passage of the frontal zone. Note that the maxmum value here, at 10m heght usng 300s ntervals, s one-thrd of the maxmum value calculated usng data from 3m heght at 60s ntervals, presented n Pper & Lundqust (2004). The ncreased dsspaton rate n the frontal zone reflects the ncreased producton of TKE due to mxng n the frontal zone. Prevous work (Blumen et al. 1999) has suggested that the head of a densty current also nduces turbulent mxng. Fgure 4 depcts a tme seres of dsspaton rate at 10m calculated for the 10 hour nterval presented n Fgure 2. Pre-densty current values are ~ 0.1 m 2 s -3, twce those observed before the frontal passage n MICROFRONTS. Even more strkng, the passage of the densty current head s not marked by ncreased dsspaton, as seen n Blumen et al. (1999), and would be expected from the peak n momentum and heat flux seen n Fgure 2, but rather by a suppresson of dsspaton. Dsspaton rates are less than 0.01 m 2 s -3 from the tme of the passage of the head through untl ts end. Ths unque response could be a functon of the relatvely long nterval (300s) used for calculatng ε compared to the tme requred for the head of the densty current to pass; ths behavor wll be nvestgated n future work. 4. COMPARISONS OF OBSERVED DISSIPATION LENGTH WITH PROPOSED MODELS The calculatons presented above, as well as those from dfferent levels durng the same tme perods wll be compared wth several proposed models for dsspaton length. Dsspaton length l ε s typcally proposed to be a related to local stablty, ether through a gradent Rchardson number, a flux Rchardson number, or a local Froude number. The parameterzatons offered by Cheng & Canuto (1994) and Freedman and Jacobson (2003) wll be consdered. Fgure 2: Tme seres from the sonc anemometer mounted at 10m on the man 60m CASES-99 tower on 20 Oct (A) Wnd speed. (B) Wnd drecton. (C) Vrtual temperature. (D) Frcton velocty u* and heat flux wt. Dotted lnes mark the passage of the densty current as defned by the temperature shft at the 5m level; note that the 10m level (shown here) slghtly lags the 5m level, ndcatng a tlted structure to the head of the densty current. 5. SUMMARY Observatons of turbulent knetc energy dsspaton rate n dsturbed stable boundary layers exhbt great varablty. In the 20 March 1995 frontal passage, the dsspaton rate s found to ncrease by nearly an order of magntude to a maxmum value of ~0.4 m 2 s -3, compared to prefrontal values of ~0.05 m 2 s -3. Dsspaton rate levels reman hgh even after the passage of the frontal zone. In the 20 October 1999 densty current, the densty current suppresses TKE dsspaton, from pre-densty current values ~ 0.1 m 2 s -3 to less than 0.01 m 2 s -3. The broad range of

4 stablty condtons offered by these two cases creates an deal testbed for parameterzatons of TKE dsspaton and TKE dsspaton length l ε. Acknowledgements Support for MP has been provded by the Ar Force Offce of Scentfc Research under Grant F and under AASERT Grant F Support for MP and JKL at the Unversty of Colorado has been provded by the Atmospherc Scences Dvson, Mesoscale Dynamcs Program of the Natonal Scence Foundaton under Grant ATM MP also thanks Research Systems, Inc. for allowng a leave of absence. Ths work was performed under the auspces of the U.S. Department of Energy by the Unversty of Calforna, Lawrence Lvermore Natonal Laboratory under contract No. W-7405-Eng-48. References Blumen, W., R.L. Grossman, and M. Pper, 1999: Analyss of heat budget, dsspaton and frontogeness n a shallow densty current. Bound.-Layer Meteorol., 91, Fgure 3: Inertal dsspaton rate calculatons from the 10m sonc anemometer for the 20 Mar 1995 front. Values of ε are calculated n 300s ntervals. Error bars denote 95% confdence ntervals on the means. Champagne, F.H., C.A. Frehe, J.C. LaRue, and J.C. Wyngaard, 1977: Flux measurements, flux estmaton technques, and fne-scale turbulence measurements n the unstable surface layer over land. J. Atmos. Sc., 34, Cheng, Y. and V.M. Canuto, 1994: Stably stratfed shear turbulence: A new model for the energy dsspaton length scale. J. Atmos. Sc., 51, Freedman, F. R. and M. Z. Jacobson. 2003: Modfcaton of the standard ε-equaton for the stable ABL through enforced consstency wth Monn-Obukhov smlarty theory. Bound.-Layer Meteorol., 106, Oncley, S.P., C.A. Frehe, J.A. Busnger, E.C. Itswere, J. C. LaRue and S.S. Chang, 1996: Surface-layer fluxes, profles, and turbulence measurements over unform terran under near-neutral condtons. J. Atmos. Sc., 53, Fgure 4:. Inertal dsspaton rate calculatons from the 10m sonc anemometer for the 20 Oct 1999 densty current. Values of ε are calculated n 300s ntervals. Error bars denote 95% confdence ntervals on the means. Note the expanded ordnate, n comparson to that n Fgure 3.

5 Pper, M., 2001: The Effects of a Frontal Passage on Fne-Scale Nocturnal Boundary Layer Turbulence. Ph.D. dssertaton, Unversty of Colorado at Boulder, Dept. of Astrophyscal, Planetary, and Atmospherc Scences, 217 pp. Pper, M., and J. K. Lundqust, 2004: Surface- Layer Turbulence Measurements durng a Frontal Passage. J. Atmos. Sc., to appear. Poulos, G.S., and co-authors, 2002a: CASES-99: A comprehensve nvestgaton of the stable nocturnal boundary layer. Bull. Amer. Meteor. Soc., 83, Poulos, G.S., J.K. Lundqust, W. Blumen, and S. Neuvlle, 2002b: Shallow Slope Densty Currents durng CASES-99: Observatons and Modelng. 15 th Symposum on Boundary Layers and Turbulence, Wagenngen, The Netherlands, pp

FEATURES OF TURBULENT TRANSPORT OF MOMENTUM AND HEAT IN STABLY STRATIFIED BOUNDARY LAYERS AND THEIR REPRODUCTION IN ATMOSPHERIC MESOSCALE MODELS

FEATURES OF TURBULENT TRANSPORT OF MOMENTUM AND HEAT IN STABLY STRATIFIED BOUNDARY LAYERS AND THEIR REPRODUCTION IN ATMOSPHERIC MESOSCALE MODELS C I T E S 009_ Krasnoyarsk 009 FEATURES OF TURBULENT TRANSPORT OF MOMENTUM AND HEAT IN STABLY STRATIFIED BOUNDARY LAYERS AND THEIR REPRODUCTION IN ATMOSPHERIC MESOSCALE MODELS A. F. Kurbatsky Insttute

More information

Week3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity

Week3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity Week3, Chapter 4 Moton n Two Dmensons Lecture Quz A partcle confned to moton along the x axs moves wth constant acceleraton from x =.0 m to x = 8.0 m durng a 1-s tme nterval. The velocty of the partcle

More information

1. Governing Equations

1. Governing Equations 1. Governng Equatons 1a. Governng Equatons for Mean Varables The governng equatons descrbe the varaton n space and tme of the zonal, merdonal and vertcal wnd components, densty, temperature, specfc humdty

More information

LINEAR REGRESSION ANALYSIS. MODULE IX Lecture Multicollinearity

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

More information

Turbulence. Lecture 21. Non-linear Dynamics. 30 s & 40 s Taylor s work on homogeneous turbulence Kolmogorov.

Turbulence. Lecture 21. Non-linear Dynamics. 30 s & 40 s Taylor s work on homogeneous turbulence Kolmogorov. Turbulence Lecture 1 Non-lnear Dynamcs Strong non-lnearty s a key feature of turbulence. 1. Unstable, chaotc behavor.. Strongly vortcal (vortex stretchng) 3 s & 4 s Taylor s work on homogeneous turbulence

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

First Law: A body at rest remains at rest, a body in motion continues to move at constant velocity, unless acted upon by an external force.

First Law: A body at rest remains at rest, a body in motion continues to move at constant velocity, unless acted upon by an external force. Secton 1. Dynamcs (Newton s Laws of Moton) Two approaches: 1) Gven all the forces actng on a body, predct the subsequent (changes n) moton. 2) Gven the (changes n) moton of a body, nfer what forces act

More information

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

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

More information

AP Physics 1 & 2 Summer Assignment

AP Physics 1 & 2 Summer Assignment AP Physcs 1 & 2 Summer Assgnment AP Physcs 1 requres an exceptonal profcency n algebra, trgonometry, and geometry. It was desgned by a select group of college professors and hgh school scence teachers

More information

Comparison of Regression Lines

Comparison of Regression Lines STATGRAPHICS Rev. 9/13/2013 Comparson of Regresson Lnes Summary... 1 Data Input... 3 Analyss Summary... 4 Plot of Ftted Model... 6 Condtonal Sums of Squares... 6 Analyss Optons... 7 Forecasts... 8 Confdence

More information

Publication 2006/01. Transport Equations in Incompressible. Lars Davidson

Publication 2006/01. Transport Equations in Incompressible. Lars Davidson Publcaton 2006/01 Transport Equatons n Incompressble URANS and LES Lars Davdson Dvson of Flud Dynamcs Department of Appled Mechancs Chalmers Unversty of Technology Göteborg, Sweden, May 2006 Transport

More information

Lab 2e Thermal System Response and Effective Heat Transfer Coefficient

Lab 2e Thermal System Response and Effective Heat Transfer Coefficient 58:080 Expermental Engneerng 1 OBJECTIVE Lab 2e Thermal System Response and Effectve Heat Transfer Coeffcent Warnng: though the experment has educatonal objectves (to learn about bolng heat transfer, etc.),

More information

CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE

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

More information

Chapter Newton s Method

Chapter Newton s Method Chapter 9. Newton s Method After readng ths chapter, you should be able to:. Understand how Newton s method s dfferent from the Golden Secton Search method. Understand how Newton s method works 3. Solve

More information

A strong wind prediction model for the railway operation based on the onsite measurement and the numerical simulation

A strong wind prediction model for the railway operation based on the onsite measurement and the numerical simulation A strong wnd predcton for the ralway operaton based on the onste measurement and the numercal smulaton Yayo Msu a, Atsush Yamaguch b, and Takesh Ishhara c a Dsaster Preventon Research Laboratory, East

More information

The equation of motion of a dynamical system is given by a set of differential equations. That is (1)

The equation of motion of a dynamical system is given by a set of differential equations. That is (1) Dynamcal Systems Many engneerng and natural systems are dynamcal systems. For example a pendulum s a dynamcal system. State l The state of the dynamcal system specfes t condtons. For a pendulum n the absence

More information

Numerical Transient Heat Conduction Experiment

Numerical Transient Heat Conduction Experiment Numercal ransent Heat Conducton Experment OBJECIVE 1. o demonstrate the basc prncples of conducton heat transfer.. o show how the thermal conductvty of a sold can be measured. 3. o demonstrate the use

More information

THE CURRENT BALANCE Physics 258/259

THE CURRENT BALANCE Physics 258/259 DSH 1988, 005 THE CURRENT BALANCE Physcs 58/59 The tme average force between two parallel conductors carryng an alternatng current s measured by balancng ths force aganst the gravtatonal force on a set

More information

Negative Binomial Regression

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

More information

Transfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system

Transfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system Transfer Functons Convenent representaton of a lnear, dynamc model. A transfer functon (TF) relates one nput and one output: x t X s y t system Y s The followng termnology s used: x y nput output forcng

More information

EN40: Dynamics and Vibrations. Homework 4: Work, Energy and Linear Momentum Due Friday March 1 st

EN40: Dynamics and Vibrations. Homework 4: Work, Energy and Linear Momentum Due Friday March 1 st EN40: Dynamcs and bratons Homework 4: Work, Energy and Lnear Momentum Due Frday March 1 st School of Engneerng Brown Unversty 1. The fgure (from ths publcaton) shows the energy per unt area requred to

More information

Chapter 11: Simple Linear Regression and Correlation

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

More information

Section 8.1 Exercises

Section 8.1 Exercises Secton 8.1 Non-rght Trangles: Law of Snes and Cosnes 519 Secton 8.1 Exercses Solve for the unknown sdes and angles of the trangles shown. 10 70 50 1.. 18 40 110 45 5 6 3. 10 4. 75 15 5 6 90 70 65 5. 6.

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

NUMERICAL DIFFERENTIATION

NUMERICAL DIFFERENTIATION NUMERICAL DIFFERENTIATION 1 Introducton Dfferentaton s a method to compute the rate at whch a dependent output y changes wth respect to the change n the ndependent nput x. Ths rate of change s called the

More information

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems Numercal Analyss by Dr. Anta Pal Assstant Professor Department of Mathematcs Natonal Insttute of Technology Durgapur Durgapur-713209 emal: anta.bue@gmal.com 1 . Chapter 5 Soluton of System of Lnear Equatons

More information

This column is a continuation of our previous column

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

More information

CFD VALIDATION OF STRATIFIED TWO-PHASE FLOWS IN A HORIZONTAL CHANNEL

CFD VALIDATION OF STRATIFIED TWO-PHASE FLOWS IN A HORIZONTAL CHANNEL CFD VALIDATION OF STRATIFIED TWO-PHASE FLOWS IN A HORIZONTAL CHANNEL 1. Introducton Chrstophe Vallée and Thomas Höhne In dfferent scenaros of small break Loss of Coolant Accdent (SB-LOCA), stratfed twophase

More information

ONE-DIMENSIONAL COLLISIONS

ONE-DIMENSIONAL COLLISIONS Purpose Theory ONE-DIMENSIONAL COLLISIONS a. To very the law o conservaton o lnear momentum n one-dmensonal collsons. b. To study conservaton o energy and lnear momentum n both elastc and nelastc onedmensonal

More information

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

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

More information

PHYSICS - CLUTCH CH 28: INDUCTION AND INDUCTANCE.

PHYSICS - CLUTCH CH 28: INDUCTION AND INDUCTANCE. !! www.clutchprep.com CONCEPT: ELECTROMAGNETIC INDUCTION A col of wre wth a VOLTAGE across each end wll have a current n t - Wre doesn t HAVE to have voltage source, voltage can be INDUCED V Common ways

More information

Aerosols, Dust and High Spectral Resolution Remote Sensing

Aerosols, Dust and High Spectral Resolution Remote Sensing Aerosols, Dust and Hgh Spectral Resoluton Remote Sensng Irna N. Sokolk Program n Atmospherc and Oceanc Scences (PAOS) Unversty of Colorado at Boulder rna.sokolk@colorado.edu Goals and challenges MAIN GOALS:

More information

Mathematical Preparations

Mathematical Preparations 1 Introducton Mathematcal Preparatons The theory of relatvty was developed to explan experments whch studed the propagaton of electromagnetc radaton n movng coordnate systems. Wthn expermental error the

More information

Effect of loading frequency on the settlement of granular layer

Effect of loading frequency on the settlement of granular layer Effect of loadng frequency on the settlement of granular layer Akko KONO Ralway Techncal Research Insttute, Japan Takash Matsushma Tsukuba Unversty, Japan ABSTRACT: Cyclc loadng tests were performed both

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

= 1.23 m/s 2 [W] Required: t. Solution:!t = = 17 m/s [W]! m/s [W] (two extra digits carried) = 2.1 m/s [W]

= 1.23 m/s 2 [W] Required: t. Solution:!t = = 17 m/s [W]! m/s [W] (two extra digits carried) = 2.1 m/s [W] Secton 1.3: Acceleraton Tutoral 1 Practce, page 24 1. Gven: 0 m/s; 15.0 m/s [S]; t 12.5 s Requred: Analyss: a av v t v f v t a v av f v t 15.0 m/s [S] 0 m/s 12.5 s 15.0 m/s [S] 12.5 s 1.20 m/s 2 [S] Statement:

More information

High resolution entropy stable scheme for shallow water equations

High resolution entropy stable scheme for shallow water equations Internatonal Symposum on Computers & Informatcs (ISCI 05) Hgh resoluton entropy stable scheme for shallow water equatons Xaohan Cheng,a, Yufeng Ne,b, Department of Appled Mathematcs, Northwestern Polytechncal

More information

2016 Wiley. Study Session 2: Ethical and Professional Standards Application

2016 Wiley. Study Session 2: Ethical and Professional Standards Application 6 Wley Study Sesson : Ethcal and Professonal Standards Applcaton LESSON : CORRECTION ANALYSIS Readng 9: Correlaton and Regresson LOS 9a: Calculate and nterpret a sample covarance and a sample correlaton

More information

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

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

More information

A Numerical Study of Heat Transfer and Fluid Flow past Single Tube

A Numerical Study of Heat Transfer and Fluid Flow past Single Tube A Numercal Study of Heat ransfer and Flud Flow past Sngle ube ZEINAB SAYED ABDEL-REHIM Mechancal Engneerng Natonal Research Center El-Bohos Street, Dokk, Gza EGYP abdelrehmz@yahoo.com Abstract: - A numercal

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

Chapter 3 Describing Data Using Numerical Measures

Chapter 3 Describing Data Using Numerical Measures Chapter 3 Student Lecture Notes 3-1 Chapter 3 Descrbng Data Usng Numercal Measures Fall 2006 Fundamentals of Busness Statstcs 1 Chapter Goals To establsh the usefulness of summary measures of data. The

More information

Chapter 4. Velocity analysis

Chapter 4. Velocity analysis 1 Chapter 4 Velocty analyss Introducton The objectve of velocty analyss s to determne the sesmc veloctes of layers n the subsurface. Sesmc veloctes are used n many processng and nterpretaton stages such

More information

Physics 207 Lecture 6

Physics 207 Lecture 6 Physcs 207 Lecture 6 Agenda: Physcs 207, Lecture 6, Sept. 25 Chapter 4 Frames of reference Chapter 5 ewton s Law Mass Inerta s (contact and non-contact) Frcton (a external force that opposes moton) Free

More information

Testing for seasonal unit roots in heterogeneous panels

Testing for seasonal unit roots in heterogeneous panels Testng for seasonal unt roots n heterogeneous panels Jesus Otero * Facultad de Economía Unversdad del Rosaro, Colomba Jeremy Smth Department of Economcs Unversty of arwck Monca Gulett Aston Busness School

More information

STUDY ON TWO PHASE FLOW IN MICRO CHANNEL BASED ON EXPERI- MENTS AND NUMERICAL EXAMINATIONS

STUDY ON TWO PHASE FLOW IN MICRO CHANNEL BASED ON EXPERI- MENTS AND NUMERICAL EXAMINATIONS Blucher Mechancal Engneerng Proceedngs May 0, vol., num. www.proceedngs.blucher.com.br/evento/0wccm STUDY ON TWO PHASE FLOW IN MICRO CHANNEL BASED ON EXPERI- MENTS AND NUMERICAL EXAMINATIONS Takahko Kurahash,

More information

A large scale tsunami run-up simulation and numerical evaluation of fluid force during tsunami by using a particle method

A large scale tsunami run-up simulation and numerical evaluation of fluid force during tsunami by using a particle method A large scale tsunam run-up smulaton and numercal evaluaton of flud force durng tsunam by usng a partcle method *Mtsuteru Asa 1), Shoch Tanabe 2) and Masaharu Isshk 3) 1), 2) Department of Cvl Engneerng,

More information

One-sided finite-difference approximations suitable for use with Richardson extrapolation

One-sided finite-difference approximations suitable for use with Richardson extrapolation Journal of Computatonal Physcs 219 (2006) 13 20 Short note One-sded fnte-dfference approxmatons sutable for use wth Rchardson extrapolaton Kumar Rahul, S.N. Bhattacharyya * Department of Mechancal Engneerng,

More information

Thermodynamics General

Thermodynamics General Thermodynamcs General Lecture 1 Lecture 1 s devoted to establshng buldng blocks for dscussng thermodynamcs. In addton, the equaton of state wll be establshed. I. Buldng blocks for thermodynamcs A. Dmensons,

More information

Amplification and Relaxation of Electron Spin Polarization in Semiconductor Devices

Amplification and Relaxation of Electron Spin Polarization in Semiconductor Devices Amplfcaton and Relaxaton of Electron Spn Polarzaton n Semconductor Devces Yury V. Pershn and Vladmr Prvman Center for Quantum Devce Technology, Clarkson Unversty, Potsdam, New York 13699-570, USA Spn Relaxaton

More information

PHYSICS - CLUTCH 1E CH 28: INDUCTION AND INDUCTANCE.

PHYSICS - CLUTCH 1E CH 28: INDUCTION AND INDUCTANCE. !! www.clutchprep.com CONCEPT: ELECTROMAGNETIC INDUCTION A col of wre wth a VOLTAGE across each end wll have a current n t - Wre doesn t HAVE to have voltage source, voltage can be INDUCED V Common ways

More information

Computation of Higher Order Moments from Two Multinomial Overdispersion Likelihood Models

Computation of Higher Order Moments from Two Multinomial Overdispersion Likelihood Models Computaton of Hgher Order Moments from Two Multnomal Overdsperson Lkelhood Models BY J. T. NEWCOMER, N. K. NEERCHAL Department of Mathematcs and Statstcs, Unversty of Maryland, Baltmore County, Baltmore,

More information

MATH 5630: Discrete Time-Space Model Hung Phan, UMass Lowell March 1, 2018

MATH 5630: Discrete Time-Space Model Hung Phan, UMass Lowell March 1, 2018 MATH 5630: Dscrete Tme-Space Model Hung Phan, UMass Lowell March, 08 Newton s Law of Coolng Consder the coolng of a well strred coffee so that the temperature does not depend on space Newton s law of collng

More information

Thermal-Fluids I. Chapter 18 Transient heat conduction. Dr. Primal Fernando Ph: (850)

Thermal-Fluids I. Chapter 18 Transient heat conduction. Dr. Primal Fernando Ph: (850) hermal-fluds I Chapter 18 ransent heat conducton Dr. Prmal Fernando prmal@eng.fsu.edu Ph: (850) 410-6323 1 ransent heat conducton In general, he temperature of a body vares wth tme as well as poston. In

More information

2 Finite difference basics

2 Finite difference basics Numersche Methoden 1, WS 11/12 B.J.P. Kaus 2 Fnte dfference bascs Consder the one- The bascs of the fnte dfference method are best understood wth an example. dmensonal transent heat conducton equaton T

More information

( ) = ( ) + ( 0) ) ( )

( ) = ( ) + ( 0) ) ( ) EETOMAGNETI OMPATIBIITY HANDBOOK 1 hapter 9: Transent Behavor n the Tme Doman 9.1 Desgn a crcut usng reasonable values for the components that s capable of provdng a tme delay of 100 ms to a dgtal sgnal.

More information

SIMULATION OF SOUND WAVE PROPAGATION IN TURBULENT FLOWS USING A LATTICE-BOLTZMANN SCHEME. Abstract

SIMULATION OF SOUND WAVE PROPAGATION IN TURBULENT FLOWS USING A LATTICE-BOLTZMANN SCHEME. Abstract SIMULATION OF SOUND WAVE PROPAGATION IN TURBULENT FLOWS USING A LATTICE-BOLTZMANN SCHEME PACS REFERENCE: 43.20.Mv Andreas Wlde Fraunhofer Insttut für Integrerte Schaltungen, Außenstelle EAS Zeunerstr.

More information

Physics 2A Chapter 3 HW Solutions

Physics 2A Chapter 3 HW Solutions Phscs A Chapter 3 HW Solutons Chapter 3 Conceptual Queston: 4, 6, 8, Problems: 5,, 8, 7, 3, 44, 46, 69, 70, 73 Q3.4. Reason: (a) C = A+ B onl A and B are n the same drecton. Sze does not matter. (b) C

More information

Gravitational Acceleration: A case of constant acceleration (approx. 2 hr.) (6/7/11)

Gravitational Acceleration: A case of constant acceleration (approx. 2 hr.) (6/7/11) Gravtatonal Acceleraton: A case of constant acceleraton (approx. hr.) (6/7/11) Introducton The gravtatonal force s one of the fundamental forces of nature. Under the nfluence of ths force all objects havng

More information

Here is the rationale: If X and y have a strong positive relationship to one another, then ( x x) will tend to be positive when ( y y)

Here is the rationale: If X and y have a strong positive relationship to one another, then ( x x) will tend to be positive when ( y y) Secton 1.5 Correlaton In the prevous sectons, we looked at regresson and the value r was a measurement of how much of the varaton n y can be attrbuted to the lnear relatonshp between y and x. In ths secton,

More information

4DVAR, according to the name, is a four-dimensional variational method.

4DVAR, according to the name, is a four-dimensional variational method. 4D-Varatonal Data Assmlaton (4D-Var) 4DVAR, accordng to the name, s a four-dmensonal varatonal method. 4D-Var s actually a drect generalzaton of 3D-Var to handle observatons that are dstrbuted n tme. The

More information

Operating conditions of a mine fan under conditions of variable resistance

Operating conditions of a mine fan under conditions of variable resistance Paper No. 11 ISMS 216 Operatng condtons of a mne fan under condtons of varable resstance Zhang Ynghua a, Chen L a, b, Huang Zhan a, *, Gao Yukun a a State Key Laboratory of Hgh-Effcent Mnng and Safety

More information

Supplemental Material: Causal Entropic Forces

Supplemental Material: Causal Entropic Forces Supplemental Materal: Causal Entropc Forces A. D. Wssner-Gross 1, 2, and C. E. Freer 3 1 Insttute for Appled Computatonal Scence, Harvard Unversty, Cambrdge, Massachusetts 02138, USA 2 The Meda Laboratory,

More information

11. Dynamics in Rotating Frames of Reference

11. Dynamics in Rotating Frames of Reference Unversty of Rhode Island DgtalCommons@URI Classcal Dynamcs Physcs Course Materals 2015 11. Dynamcs n Rotatng Frames of Reference Gerhard Müller Unversty of Rhode Island, gmuller@ur.edu Creatve Commons

More information

Chapter 3. Estimation of Earthquake Load Effects

Chapter 3. Estimation of Earthquake Load Effects Chapter 3. Estmaton of Earthquake Load Effects 3.1 Introducton Sesmc acton on chmneys forms an addtonal source of natural loads on the chmney. Sesmc acton or the earthquake s a short and strong upheaval

More information

STAT 511 FINAL EXAM NAME Spring 2001

STAT 511 FINAL EXAM NAME Spring 2001 STAT 5 FINAL EXAM NAME Sprng Instructons: Ths s a closed book exam. No notes or books are allowed. ou may use a calculator but you are not allowed to store notes or formulas n the calculator. Please wrte

More information

EVALUATION OF THE VISCO-ELASTIC PROPERTIES IN ASPHALT RUBBER AND CONVENTIONAL MIXES

EVALUATION OF THE VISCO-ELASTIC PROPERTIES IN ASPHALT RUBBER AND CONVENTIONAL MIXES EVALUATION OF THE VISCO-ELASTIC PROPERTIES IN ASPHALT RUBBER AND CONVENTIONAL MIXES Manuel J. C. Mnhoto Polytechnc Insttute of Bragança, Bragança, Portugal E-mal: mnhoto@pb.pt Paulo A. A. Perera and Jorge

More information

CONTRAST ENHANCEMENT FOR MIMIMUM MEAN BRIGHTNESS ERROR FROM HISTOGRAM PARTITIONING INTRODUCTION

CONTRAST ENHANCEMENT FOR MIMIMUM MEAN BRIGHTNESS ERROR FROM HISTOGRAM PARTITIONING INTRODUCTION CONTRAST ENHANCEMENT FOR MIMIMUM MEAN BRIGHTNESS ERROR FROM HISTOGRAM PARTITIONING N. Phanthuna 1,2, F. Cheevasuvt 2 and S. Chtwong 2 1 Department of Electrcal Engneerng, Faculty of Engneerng Rajamangala

More information

9.2 Seismic Loads Using ASCE Standard 7-93

9.2 Seismic Loads Using ASCE Standard 7-93 CHAPER 9: Wnd and Sesmc Loads on Buldngs 9.2 Sesmc Loads Usng ASCE Standard 7-93 Descrpton A major porton of the Unted States s beleved to be subject to sesmc actvty suffcent to cause sgnfcant structural

More information

Department of Quantitative Methods & Information Systems. Time Series and Their Components QMIS 320. Chapter 6

Department of Quantitative Methods & Information Systems. Time Series and Their Components QMIS 320. Chapter 6 Department of Quanttatve Methods & Informaton Systems Tme Seres and Ther Components QMIS 30 Chapter 6 Fall 00 Dr. Mohammad Zanal These sldes were modfed from ther orgnal source for educatonal purpose only.

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

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

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 Experment-I MODULE VIII LECTURE - 34 ANALYSIS OF VARIANCE IN RANDOM-EFFECTS MODEL AND MIXED-EFFECTS EFFECTS MODEL Dr Shalabh Department of Mathematcs and Statstcs Indan

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

Experiment 1 Mass, volume and density

Experiment 1 Mass, volume and density Experment 1 Mass, volume and densty Purpose 1. Famlarze wth basc measurement tools such as verner calper, mcrometer, and laboratory balance. 2. Learn how to use the concepts of sgnfcant fgures, expermental

More information

Energy configuration optimization of submerged propeller in oxidation ditch based on CFD

Energy configuration optimization of submerged propeller in oxidation ditch based on CFD IOP Conference Seres: Earth and Envronmental Scence Energy confguraton optmzaton of submerged propeller n oxdaton dtch based on CFD To cte ths artcle: S Y Wu et al 01 IOP Conf. Ser.: Earth Envron. Sc.

More information

LOW BIAS INTEGRATED PATH ESTIMATORS. James M. Calvin

LOW BIAS INTEGRATED PATH ESTIMATORS. James M. Calvin Proceedngs of the 007 Wnter Smulaton Conference S G Henderson, B Bller, M-H Hseh, J Shortle, J D Tew, and R R Barton, eds LOW BIAS INTEGRATED PATH ESTIMATORS James M Calvn Department of Computer Scence

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

Research & Reviews: Journal of Engineering and Technology

Research & Reviews: Journal of Engineering and Technology Research & Revews: Journal of Engneerng and Technology Case Study to Smulate Convectve Flows and Heat Transfer n Arcondtoned Spaces Hussen JA 1 *, Mazlan AW 1 and Hasanen MH 2 1 Department of Mechancal

More information

GAUTENG DEPARTMENT OF EDUCATION SENIOR SECONDARY INTERVENTION PROGRAMME PHYSICAL SCIENCES GRADE 12 SESSION 1 (LEARNER NOTES)

GAUTENG DEPARTMENT OF EDUCATION SENIOR SECONDARY INTERVENTION PROGRAMME PHYSICAL SCIENCES GRADE 12 SESSION 1 (LEARNER NOTES) PHYSICAL SCIENCES GRADE 1 SESSION 1 (LEARNER NOTES) TOPIC 1: MECHANICS PROJECTILE MOTION Learner Note: Always draw a dagram of the stuaton and enter all the numercal alues onto your dagram. Remember to

More information

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X Statstcs 1: Probablty Theory II 37 3 EPECTATION OF SEVERAL RANDOM VARIABLES As n Probablty Theory I, the nterest n most stuatons les not on the actual dstrbuton of a random vector, but rather on a number

More information

A particle in a state of uniform motion remain in that state of motion unless acted upon by external force.

A particle in a state of uniform motion remain in that state of motion unless acted upon by external force. The fundamental prncples of classcal mechancs were lad down by Galleo and Newton n the 16th and 17th centures. In 1686, Newton wrote the Prncpa where he gave us three laws of moton, one law of gravty,

More information

Appendix B. The Finite Difference Scheme

Appendix B. The Finite Difference Scheme 140 APPENDIXES Appendx B. The Fnte Dfference Scheme In ths appendx we present numercal technques whch are used to approxmate solutons of system 3.1 3.3. A comprehensve treatment of theoretcal and mplementaton

More information

AS-Level Maths: Statistics 1 for Edexcel

AS-Level Maths: Statistics 1 for Edexcel 1 of 6 AS-Level Maths: Statstcs 1 for Edecel S1. Calculatng means and standard devatons Ths con ndcates the slde contans actvtes created n Flash. These actvtes are not edtable. For more detaled nstructons,

More information

Airflow and Contaminant Simulation with CONTAM

Airflow and Contaminant Simulation with CONTAM Arflow and Contamnant Smulaton wth CONTAM George Walton, NIST CHAMPS Developers Workshop Syracuse Unversty June 19, 2006 Network Analogy Electrc Ppe, Duct & Ar Wre Ppe, Duct, or Openng Juncton Juncton

More information

Stateof the art of urbanmesoscale modelling and possible use of the Helsinki testbed data

Stateof the art of urbanmesoscale modelling and possible use of the Helsinki testbed data Stateof the art of urbanmesoscale modellng and possble use of the Helsnk testbed data Alberto Martll CIEMAT, Madrd, Span alberto.martll@cemat.es Snce the orgn of mesoscale meteorologcal modelng, urban

More information

Predictive Analytics : QM901.1x Prof U Dinesh Kumar, IIMB. All Rights Reserved, Indian Institute of Management Bangalore

Predictive Analytics : QM901.1x Prof U Dinesh Kumar, IIMB. All Rights Reserved, Indian Institute of Management Bangalore Sesson Outlne Introducton to classfcaton problems and dscrete choce models. Introducton to Logstcs Regresson. Logstc functon and Logt functon. Maxmum Lkelhood Estmator (MLE) for estmaton of LR parameters.

More information

Flow equations To simulate the flow, the Navier-Stokes system that includes continuity and momentum equations is solved

Flow equations To simulate the flow, the Navier-Stokes system that includes continuity and momentum equations is solved Smulaton of nose generaton and propagaton caused by the turbulent flow around bluff bodes Zamotn Krll e-mal: krart@gmal.com, cq: 958886 Summary Accurate predctons of nose generaton and spread n turbulent

More information

Electrical double layer: revisit based on boundary conditions

Electrical double layer: revisit based on boundary conditions Electrcal double layer: revst based on boundary condtons Jong U. Km Department of Electrcal and Computer Engneerng, Texas A&M Unversty College Staton, TX 77843-318, USA Abstract The electrcal double layer

More information

U1- > 1.2, (1) Use of conventional stability parameters during swell. Anna Rutgersson, Ann-Soft Smedman, and Ulf H6gstr6m

U1- > 1.2, (1) Use of conventional stability parameters during swell. Anna Rutgersson, Ann-Soft Smedman, and Ulf H6gstr6m JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 106, NO. Cll, PAGES 27,117-27,134, NOVEMBER 15, 2001 Use of conventonal stablty parameters durng swell Anna Rutgersson, Ann-Soft Smedman, and Ulf H6gstr6m Department

More information

Chapter 3. r r. Position, Velocity, and Acceleration Revisited

Chapter 3. r r. Position, Velocity, and Acceleration Revisited Chapter 3 Poston, Velocty, and Acceleraton Revsted The poston vector of a partcle s a vector drawn from the orgn to the locaton of the partcle. In two dmensons: r = x ˆ+ yj ˆ (1) The dsplacement vector

More information

3) Surrogate Responses

3) Surrogate Responses 1) Introducton Vsual neurophysology has benefted greatly for many years through the use of smple, controlled stmul lke bars and gratngs. One common characterzaton of the responses elcted by these stmul

More information

Parameter Estimation for Dynamic System using Unscented Kalman filter

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

More information

Prof. Dr. I. Nasser Phys 630, T Aug-15 One_dimensional_Ising_Model

Prof. Dr. I. Nasser Phys 630, T Aug-15 One_dimensional_Ising_Model EXACT OE-DIMESIOAL ISIG MODEL The one-dmensonal Isng model conssts of a chan of spns, each spn nteractng only wth ts two nearest neghbors. The smple Isng problem n one dmenson can be solved drectly n several

More information

CHAPTER IV RESEARCH FINDING AND ANALYSIS

CHAPTER IV RESEARCH FINDING AND ANALYSIS CHAPTER IV REEARCH FINDING AND ANALYI A. Descrpton of Research Fndngs To fnd out the dfference between the students who were taught by usng Mme Game and the students who were not taught by usng Mme Game

More information

Abstract. 1 Introduction

Abstract. 1 Introduction Numercal models for unsteady flow n ppe dvdng systems R. Klasnc," H. Knoblauch," R. Mader* ^ Department of Hydraulc Structures and Water Resources Management, Graz Unversty of Technology, A-8010, Graz,

More information

Physics 207: Lecture 20. Today s Agenda Homework for Monday

Physics 207: Lecture 20. Today s Agenda Homework for Monday Physcs 207: Lecture 20 Today s Agenda Homework for Monday Recap: Systems of Partcles Center of mass Velocty and acceleraton of the center of mass Dynamcs of the center of mass Lnear Momentum Example problems

More information

Copyright 2017 by Taylor Enterprises, Inc., All Rights Reserved. Adjusted Control Limits for P Charts. Dr. Wayne A. Taylor

Copyright 2017 by Taylor Enterprises, Inc., All Rights Reserved. Adjusted Control Limits for P Charts. Dr. Wayne A. Taylor Taylor Enterprses, Inc. Control Lmts for P Charts Copyrght 2017 by Taylor Enterprses, Inc., All Rghts Reserved. Control Lmts for P Charts Dr. Wayne A. Taylor Abstract: P charts are used for count data

More information

Corresponding author: Tsubasa Okaze,

Corresponding author: Tsubasa Okaze, Academc Artcle Journal of Heat Island Insttute Internatonal Vol. - (7) Large-Eddy Smulaton of on-isothermal Flow around a Buldng Usng Artfcally Generated Inflow Turbulent Fluctuatons of Wnd Velocty and

More information

A Simple Inventory System

A Simple Inventory System A Smple Inventory System Lawrence M. Leems and Stephen K. Park, Dscrete-Event Smulaton: A Frst Course, Prentce Hall, 2006 Hu Chen Computer Scence Vrgna State Unversty Petersburg, Vrgna February 8, 2017

More information