AQUIFER DRAWDOWN AND VARIABLE-STAGE STREAM DEPLETION INDUCED BY A NEARBY PUMPING WELL

Size: px
Start display at page:

Download "AQUIFER DRAWDOWN AND VARIABLE-STAGE STREAM DEPLETION INDUCED BY A NEARBY PUMPING WELL"

Transcription

1 Pocing of h 1 h Innaional Confnc on Enionmnal cinc an chnolog Rho Gc 3-5 pmb 15 AUIFER DRAWDOWN AND VARIABE-AGE REAM DEPEION INDUCED BY A NEARBY PUMPING WE BAAOUHA H.M. aa Enionmn & Eng Rach Iniu EERI PO Bo: 55 Doha aa Baalouha@wb. ABRAC A am plion phnomnon ha bn ui fo man ca an iffn analical mol w lop o fin h ffc of a pumping wll on a nab am. Mo lop mol coni a conan am ag o nglc h aiaion in am ag. hi i no h ca in ali wh h am flow an ll coninuoul a o im. In hi pap a nw analical mol wa lop coniing aiaion in am flow i.. am ag. h lop mol coni h cion of am flow an i impac on am plion an awown. Compaion bwn h lop oluion an h iing on how a ignifican icpanc whn h am flow ai. Kwo: am plion am cion analical oluion awown. 1. Inoucion Numou ui w conuc o unan h phnomnon of h am plion uling fom a pumping wll. hi 191 wa h fi o u h ffc of a pumping wll on a flowing am poucing a impl oluion which wa la lop b Glo an Balm 195. h la mol wa fuh lop b Hanuh 196 o accoun fo amb conucanc. Hun 1999 moifi h Hanuh oluion o b pn h ffc of paiall clogg amb on am plion an awown. Baalouha 1 i h am oluion of Hun 1999 ba on a uppoiion appoach an coniing a am of a fini wih. In all oluion lop o fa i wa aum h am ll i.. ag i conan all h im. How hi conaic h ali ha am flow an ag a coninuoul. hi pap lop a oluion ha accoun fo am ll aiaion o im an incopoa hi aiaion in anali of am plion an awown.. Mahmaical Dlopmn.1. Dawown Baalouha 1 i h awown in auif uling fom a pumping wll na a am ba on uppoiion of a pumping wll w an a loing am. Coniing a cooina m a h cn of a am h wll awown w a an poin an a an im i gin b hi Euaion: w Ei wh i h pumping a i h auif oaii i h ianc bwn a pumping wll an h am i im inc pumping a an i h auif anmiii. Ei i h ponnial ingal alo known a wll funcion. h awown uling fom h am alon i gin b Hun 1999 Baalouha 1: 1 CE15_6

2 CE15_6 Ei / Wh i h amb conucanc [m /]. Euaion i ba on h aumpion of a conan am ll a i h ca in all lop analical oluion. Auming i h funcion of am ll aiaion o im hn i gin uing h conoluion ingal Calaw an Jag 1959: 3 Wh i h auif awown uling fom a aiabl ag am lakag. Fom an 3: / Ingaing Euaion wih pc o il: fc / 5 If h am ag i conan hn accoing o aumpion of piou oluion gin in Euaion =1. hi i bcau i wa aum in Hun 1999 oluion ha h ppumping gounwa ll an h i a a h am ll. In hi ca Euaion an bcom inical... am Dplion Ba on Dac aw an following h am appoach of Baalouha 1 oal am plion i gin b: 6 Euaion 6 i mulipli b bcau am plion occu a boh i of h am. Euaion 6 can b fuh implifi a: 7 Bcau h funcion i mmic a boh i of -ai i.. o no chang whn ign chang a hown in Euaion 5 an i a funcion of onl. Ba on Euaion 5 h flow gain a h g of h am can b win a: fc 5 / / 16 Fom 7 an h am plion i:

3 CE15_6 fc 9.3. Eampl An ampl i u o mona h ffc of pumping on awown an am plion whn h ag ai o im. hi ampl aum an ponnial chang of am ll which i conin wih a pical cion cu allakn 1995 ob 196. In hi ca h am ag funcion i: a 1 Wh i h iniial am ll a i a conan an i im. Uing Euaion 5 an 1 h awown i: fc a / 11 Ba on Euaion 9 an 1 h am plion i: fc a a 1 I i aum ha a pumping wll i loca a a ianc =3 m fom h am cnlin. h am wih i 1 m an h pumping a i 1 ma. oaii an anmiii w aum o b. an m /a pcil an h ical haulic conucii of h i b i.1. Figu 1 how h oal awown o im uling fom am lakag fo boh ca of aiabl-ag am an conan-ag am. h oal awown i h um of goun wa ll i u o am lakag an op u o pumping. I i gin b: Ei fc a / 13 Boh conan an aiabl ag ha imila awown in h al im bu hn h aiabl ag how high awown i.. l lakag u o clining ag o im a gin b Euaion 1.

4 Figu 1: Dawown a h g of h am fo boh conan an aiabl ag. h imnionl am plion / uling fom h pumping wll i hown in Figu. h aiabl-ag am how a coniabl l plion i.. flow o auif compa o h conan-ag am. hi i bcau h ag of h am ca o im a fa a of clining wa abl b pumping. A a conunc h ha iffnc bwn h am an h auif uc which uc am plion. Figu : am plion fo boh conan an aiabl ag. 3. Concluion A nw oluion ha bn i in hi u o calcula h awown an am plion uling fom a nab pumping wll. hi oluion i mo gnali han iing oluion CE15_6

5 in h liau a i coni aiaion in am ag. A hown in hi u chang in am ag ignificanl affc boh awown an am plion. I i foun ha boh awown an am plion ca o im a a ul of ag cion. h oluion pn can b u wih an funcion o conan pning h chang in am ag o im. I alo can b u wih uppoiion in ca h ag funcion chang o im. REFERENCE 1. Baalouha H.M. 1 Dawown an am plion inuc b a nab pumping wll. Jounal of Holog DOI: 1.116/j.jhol Calaw H.. an Jag J.C Conucion of ha in oli. Ofo Unii P. 51p. 3. Glo R.E. Balm G.G. 195 Ri plion uling fom pumping a wll na a i. an. Am. Goph. Union Hanuh M Wll na am wih mipiou b. J. Goph. R Hun B Una am plion fom goun wa pumping. Goun Wa allakn.m A iw of baflow cion anali. Jounal of Holog 165 pp hi C. 191 h ffc of a wll on h flow of a nab am. an. Am. Goph. Union ob Conli an ang D. D. 196 On cion cu. i - Rcion uaion. Jounal of holog Nw Zalan 3 no. pp -1 CE15_6

Instructors Solution for Assignment 3 Chapter 3: Time Domain Analysis of LTIC Systems

Instructors Solution for Assignment 3 Chapter 3: Time Domain Analysis of LTIC Systems Inrucor Soluion for Aignmn Chapr : Tim Domain Anali of LTIC Sm Problm i a 8 x x wih x u,, an Zro-inpu rpon of h m: Th characriic quaion of h LTIC m i i 8, which ha roo a ± j Th zro-inpu rpon i givn b zi

More information

T h e C S E T I P r o j e c t

T h e C S E T I P r o j e c t T h e P r o j e c t T H E P R O J E C T T A B L E O F C O N T E N T S A r t i c l e P a g e C o m p r e h e n s i v e A s s es s m e n t o f t h e U F O / E T I P h e n o m e n o n M a y 1 9 9 1 1 E T

More information

European and American options with a single payment of dividends. (About formula Roll, Geske & Whaley) Mark Ioffe. Abstract

European and American options with a single payment of dividends. (About formula Roll, Geske & Whaley) Mark Ioffe. Abstract 866 Uni Naions Plaza i 566 Nw Yo NY 7 Phon: + 3 355 Fa: + 4 668 info@gach.com www.gach.com Eoan an Amican oions wih a singl amn of ivins Abo fomla Roll Gs & Whal Ma Ioff Absac Th aicl ovis a ivaion of

More information

Performance Comparison of LCMV-based Space-time 2D Array and Ambiguity Problem

Performance Comparison of LCMV-based Space-time 2D Array and Ambiguity Problem Inernaional journal of cience Commerce and umaniie Volume No 2 No 3 April 204 Performance Comparion of LCMV-baed pace-ime 2D Arra and Ambigui Problem 2 o uan Chang and Jin hinghia Deparmen of Communicaion

More information

A L A BA M A L A W R E V IE W

A L A BA M A L A W R E V IE W A L A BA M A L A W R E V IE W Volume 52 Fall 2000 Number 1 B E F O R E D I S A B I L I T Y C I V I L R I G HT S : C I V I L W A R P E N S I O N S A N D TH E P O L I T I C S O F D I S A B I L I T Y I N

More information

DEPARTMENT OF ELECTRICAL &ELECTRONICS ENGINEERING SIGNALS AND SYSTEMS. Assoc. Prof. Dr. Burak Kelleci. Spring 2018

DEPARTMENT OF ELECTRICAL &ELECTRONICS ENGINEERING SIGNALS AND SYSTEMS. Assoc. Prof. Dr. Burak Kelleci. Spring 2018 DEPARTMENT OF ELECTRICAL &ELECTRONICS ENGINEERING SIGNALS AND SYSTEMS Aoc. Prof. Dr. Burak Kllci Spring 08 OUTLINE Th Laplac Tranform Rgion of convrgnc for Laplac ranform Invr Laplac ranform Gomric valuaion

More information

Faraday s Law. To be able to find. motional emf transformer and motional emf. Motional emf

Faraday s Law. To be able to find. motional emf transformer and motional emf. Motional emf Objecie F s w Tnsfome Moionl To be ble o fin nsfome. moionl nsfome n moionl. 331 1 331 Mwell s quion: ic Fiel D: Guss lw :KV : Guss lw H: Ampee s w Poin Fom Inegl Fom D D Q sufce loop H sufce H I enclose

More information

Partial Fraction Expansion

Partial Fraction Expansion Paial Facion Expanion Whn ying o find h inv Laplac anfom o inv z anfom i i hlpfl o b abl o bak a complicad aio of wo polynomial ino fom ha a on h Laplac Tanfom o z anfom abl. W will illa h ing Laplac anfom.

More information

University of Toledo REU Program Summer 2002

University of Toledo REU Program Summer 2002 Univiy of Toldo REU Pogam Summ 2002 Th Effc of Shadowing in 2-D Polycyallin Gowh Jff Du Advio: D. Jacqu Ama Dpamn of Phyic, Univiy of Toldo, Toldo, Ohio Abac Th ffc of hadowing in 2-D hin film gowh w udid

More information

CS4445/9544 Analysis of Algorithms II Solution for Assignment 1

CS4445/9544 Analysis of Algorithms II Solution for Assignment 1 Conider he following flow nework CS444/944 Analyi of Algorihm II Soluion for Aignmen (0 mark) In he following nework a minimum cu ha capaciy 0 Eiher prove ha hi aemen i rue, or how ha i i fale Uing he

More information

P a g e 5 1 of R e p o r t P B 4 / 0 9

P a g e 5 1 of R e p o r t P B 4 / 0 9 P a g e 5 1 of R e p o r t P B 4 / 0 9 J A R T a l s o c o n c l u d e d t h a t a l t h o u g h t h e i n t e n t o f N e l s o n s r e h a b i l i t a t i o n p l a n i s t o e n h a n c e c o n n e

More information

Final Exam : Solutions

Final Exam : Solutions Comp : Algorihm and Daa Srucur Final Exam : Soluion. Rcuriv Algorihm. (a) To bgin ind h mdian o {x, x,... x n }. Sinc vry numbr xcp on in h inrval [0, n] appar xacly onc in h li, w hav ha h mdian mu b

More information

Drill Bit Hydraulics

Drill Bit Hydraulics Drill i yraulic Aumpion ) Change of preure ue o elevaion i negligible. ) Velociy upream i negligible compare o nozzle. 3) reure ue o fricion i negligible. Δ Δ 8.075 4 E ρvn 0 reure rop acro bi, vn nozzle

More information

Chapter 4 Circular and Curvilinear Motions

Chapter 4 Circular and Curvilinear Motions Chp 4 Cicul n Cuilin Moions H w consi picls moing no long sigh lin h cuilin moion. W fis su h cicul moion, spcil cs of cuilin moion. Anoh mpl w h l sui li is h pojcil..1 Cicul Moion Unifom Cicul Moion

More information

, the. L and the L. x x. max. i n. It is easy to show that these two norms satisfy the following relation: x x n x = (17.3) max

, the. L and the L. x x. max. i n. It is easy to show that these two norms satisfy the following relation: x x n x = (17.3) max ecure 8 7. Sabiliy Analyi For an n dimenional vecor R n, he and he vecor norm are defined a: = T = i n i (7.) I i eay o how ha hee wo norm aify he following relaion: n (7.) If a vecor i ime-dependen, hen

More information

Molecular Evolution and Phylogeny. Based on: Durbin et al Chapter 8

Molecular Evolution and Phylogeny. Based on: Durbin et al Chapter 8 Molecula Evoluion and hylogeny Baed on: Dubin e al Chape 8. hylogeneic Tee umpion banch inenal node leaf Topology T : bifucaing Leave - N Inenal node N+ N- Lengh { i } fo each banch hylogeneic ee Topology

More information

Introduction to SLE Lecture Notes

Introduction to SLE Lecture Notes Inroducion o SLE Lecure Noe May 13, 16 - The goal of hi ecion i o find a ufficien condiion of λ for he hull K o be generaed by a imple cure. I urn ou if λ 1 < 4 hen K i generaed by a imple curve. We will

More information

The Moúõ. ExplÉüers. Fun Facts. WÉüd Proèô. Parts oì Sp. Zoú Animal Roêks

The Moúõ. ExplÉüers. Fun Facts. WÉüd Proèô. Parts oì Sp. Zoú Animal Roêks onn C f o l b Ta 4 5 õ Inoåucio Pacic 8 L LoËíca c i c 3 a P L Uppca 35 k W h Day oì 38 a Y h Moõh oì WÉüld 44 o nd h a y a d h Bi 47 u g 3-D Fi 54 Zoú Animal 58 Éüm Landf 62 Roêk 68 Th Moúõ õ o 74 l k

More information

DSP-First, 2/e. This Lecture: LECTURE #3 Complex Exponentials & Complex Numbers. Introduce more tools for manipulating complex numbers

DSP-First, 2/e. This Lecture: LECTURE #3 Complex Exponentials & Complex Numbers. Introduce more tools for manipulating complex numbers DSP-Fis, / LECTURE #3 Compl Eponnials & Compl umbs READIG ASSIGMETS This Lcu: Chap, Scs. -3 o -5 Appndi A: Compl umbs Appndi B: MATLAB Lcu: Compl Eponnials Aug 016 003-016, JH McClllan & RW Schaf 3 LECTURE

More information

Elementary Differential Equations and Boundary Value Problems

Elementary Differential Equations and Boundary Value Problems Elmnar Diffrnial Equaions and Boundar Valu Problms Boc. & DiPrima 9 h Ediion Chapr : Firs Ordr Diffrnial Equaions 00600 คณ ตศาสตร ว ศวกรรม สาขาว ชาว ศวกรรมคอมพ วเตอร ป การศ กษา /55 ผศ.ดร.อร ญญา ผศ.ดร.สมศ

More information

ESCI 341 Atmospheric Thermodynamics Lesson 16 Pseudoadiabatic Processes Dr. DeCaria

ESCI 341 Atmospheric Thermodynamics Lesson 16 Pseudoadiabatic Processes Dr. DeCaria ESCI 34 Atmohi hmoynami on 6 Puoaiabati Po D DCaia fn: Man, A an FE obitaill, 97: A omaion of th uialnt otntial tmatu an th tati ngy, J Atmo Si, 7, 37-39 Btt, AK, 974: Futh ommnt on A omaion of th uialnt

More information

2. VECTORS. R Vectors are denoted by bold-face characters such as R, V, etc. The magnitude of a vector, such as R, is denoted as R, R, V

2. VECTORS. R Vectors are denoted by bold-face characters such as R, V, etc. The magnitude of a vector, such as R, is denoted as R, R, V ME 352 VETS 2. VETS Vecor algebra form he mahemaical foundaion for kinemaic and dnamic. Geomer of moion i a he hear of boh he kinemaic and dnamic of mechanical em. Vecor anali i he imehonored ool for decribing

More information

P a g e 3 6 of R e p o r t P B 4 / 0 9

P a g e 3 6 of R e p o r t P B 4 / 0 9 P a g e 3 6 of R e p o r t P B 4 / 0 9 p r o t e c t h um a n h e a l t h a n d p r o p e r t y fr om t h e d a n g e rs i n h e r e n t i n m i n i n g o p e r a t i o n s s u c h a s a q u a r r y. J

More information

The Australian Society for Operations Research

The Australian Society for Operations Research h Asalian Sociy fo Opaions sach www.aso.og.a ASO Bllin Vol 33 ss 4 Pags 4-48 A Coninos viw nvnoy Mol fo Dioaing s wih Sochasic Dan an Pic Discon on Backos Manisha Pal an Sjan Chana Dpan of Saisics Univsiy

More information

Algorithmic Discrete Mathematics 6. Exercise Sheet

Algorithmic Discrete Mathematics 6. Exercise Sheet Algorihmic Dicree Mahemaic. Exercie Shee Deparmen of Mahemaic SS 0 PD Dr. Ulf Lorenz 7. and 8. Juni 0 Dipl.-Mah. David Meffer Verion of June, 0 Groupwork Exercie G (Heap-Sor) Ue Heap-Sor wih a min-heap

More information

Exponential Sawtooth

Exponential Sawtooth ECPE 36 HOMEWORK 3: PROPERTIES OF THE FOURIER TRANSFORM SOLUTION. Exponenial Sawooh: The eaie way o do hi problem i o look a he Fourier ranform of a ingle exponenial funcion, () = exp( )u(). From he able

More information

C 2.21 EDGEWATER HEIGHTS CITY OF MUSKEGO, WI INTERIM GRADING PLAN SEE SHEET C 2.0 LEGEND EDGEWATER COURT NORTHEAST BASIN #1 20 PHASE 1

C 2.21 EDGEWATER HEIGHTS CITY OF MUSKEGO, WI INTERIM GRADING PLAN SEE SHEET C 2.0 LEGEND EDGEWATER COURT NORTHEAST BASIN #1 20 PHASE 1 AIN NOS: S OL NON- AIN SHON SHOUL B CONSI INIM AN PSNS H AS HA H CONACO SHOUL LAV H SI HN AIN IS FINISH INIM AIN ON LOS SHALL NSU POSIIV AINA O H BASINS ACCUACY OF ALL SPO LVAIONS SHALL B O: SCON O, CLASS

More information

CHAPTER 7: SECOND-ORDER CIRCUITS

CHAPTER 7: SECOND-ORDER CIRCUITS EEE5: CI RCUI T THEORY CHAPTER 7: SECOND-ORDER CIRCUITS 7. Inroducion Thi chaper conider circui wih wo orage elemen. Known a econd-order circui becaue heir repone are decribed by differenial equaion ha

More information

f(x) dx with An integral having either an infinite limit of integration or an unbounded integrand is called improper. Here are two examples dx x x 2

f(x) dx with An integral having either an infinite limit of integration or an unbounded integrand is called improper. Here are two examples dx x x 2 Impope Inegls To his poin we hve only consideed inegls f() wih he is of inegion nd b finie nd he inegnd f() bounded (nd in fc coninuous ecep possibly fo finiely mny jump disconinuiies) An inegl hving eihe

More information

The far field calculation: Approximate and exact solutions. Persa Kyritsi November 10th, 2005 B2-109

The far field calculation: Approximate and exact solutions. Persa Kyritsi November 10th, 2005 B2-109 Th fa fl calculao: Appoa a ac oluo Pa K Novb 0h 005 B-09 Oul Novb 0h 005 Pa K Iouco Appoa oluo flco fo h gou ac oluo Cocluo Pla wav fo Ic fl: pla wav k ( ) jk H ( ) λ λ ( ) Polaao fo η 0 0 Hooal polaao

More information

To become more mathematically correct, Circuit equations are Algebraic Differential equations. from KVL, KCL from the constitutive relationship

To become more mathematically correct, Circuit equations are Algebraic Differential equations. from KVL, KCL from the constitutive relationship Laplace Tranform (Lin & DeCarlo: Ch 3) ENSC30 Elecric Circui II The Laplace ranform i an inegral ranformaion. I ranform: f ( ) F( ) ime variable complex variable From Euler > Lagrange > Laplace. Hence,

More information

Double Slits in Space and Time

Double Slits in Space and Time Doubl Slis in Sac an Tim Gorg Jons As has bn ror rcnly in h mia, a am l by Grhar Paulus has monsra an inrsing chniqu for ionizing argon aoms by using ulra-shor lasr ulss. Each lasr uls is ffcivly on an

More information

Course II. Lesson 7 Applications to Physics. 7A Velocity and Acceleration of a Particle

Course II. Lesson 7 Applications to Physics. 7A Velocity and Acceleration of a Particle Course II Lesson 7 Applicaions o Physics 7A Velociy and Acceleraion of a Paricle Moion in a Sraigh Line : Velociy O Aerage elociy Moion in he -ais + Δ + Δ 0 0 Δ Δ Insananeous elociy d d Δ Δ Δ 0 lim [ m/s

More information

Trade Patterns, Production networks, and Trade and employment in the Asia-US region

Trade Patterns, Production networks, and Trade and employment in the Asia-US region Trade Patterns, Production networks, and Trade and employment in the Asia-U region atoshi Inomata Institute of Developing Economies ETRO Development of cross-national production linkages, 1985-2005 1985

More information

English Made Easy: Foundation Book 1 Notes for parents

English Made Easy: Foundation Book 1 Notes for parents a nh Ma ay: Fnan 1 pan h b n hp y ch an ay an by cn n h n n ach h n h aphab. h h achn an ca phnc. h nan, achn an wn ac w nca y ch an h na ach, a w a h n n ach a an hw wn n h pa. y cpn h pa h b, y ch w

More information

Derivation of the differential equation of motion

Derivation of the differential equation of motion Divion of h iffnil quion of oion Fis h noions fin h will us fo h ivion of h iffnil quion of oion. Rollo is hough o -insionl isk. xnl ius of h ll isnc cn of ll (O) - IDU s cn of gviy (M) θ ngl of inclinion

More information

Laplace Transform. Inverse Laplace Transform. e st f(t)dt. (2)

Laplace Transform. Inverse Laplace Transform. e st f(t)dt. (2) Laplace Tranform Maoud Malek The Laplace ranform i an inegral ranform named in honor of mahemaician and aronomer Pierre-Simon Laplace, who ued he ranform in hi work on probabiliy heory. I i a powerful

More information

Lecture 2: Bayesian inference - Discrete probability models

Lecture 2: Bayesian inference - Discrete probability models cu : Baysian infnc - Disc obabiliy modls Many hings abou Baysian infnc fo disc obabiliy modls a simila o fqunis infnc Disc obabiliy modls: Binomial samling Samling a fix numb of ials fom a Bnoulli ocss

More information

Randomized Perfect Bipartite Matching

Randomized Perfect Bipartite Matching Inenive Algorihm Lecure 24 Randomized Perfec Biparie Maching Lecurer: Daniel A. Spielman April 9, 208 24. Inroducion We explain a randomized algorihm by Ahih Goel, Michael Kapralov and Sanjeev Khanna for

More information

What is maximum Likelihood? History Features of ML method Tools used Advantages Disadvantages Evolutionary models

What is maximum Likelihood? History Features of ML method Tools used Advantages Disadvantages Evolutionary models Wha i maximum Likelihood? Hiory Feaure of ML mehod Tool ued Advanage Diadvanage Evoluionary model Maximum likelihood mehod creae all he poible ree conaining he e of organim conidered, and hen ue he aiic

More information

PERIODICAL SOLUTION OF SOME DIFFERENTIAL EQUATIONS UDC 517.9(045)=20. Julka Knežević-Miljanović

PERIODICAL SOLUTION OF SOME DIFFERENTIAL EQUATIONS UDC 517.9(045)=20. Julka Knežević-Miljanović FCT UNIVESITTIS Sri: chanic uomaic Conrol and oboic Vol. N o 7 5. 87-9 PEIODICL SOLUTION OF SOE DIFFEENTIL EQUTIONS UDC 57.95= Julka Knžvić-iljanović Facul o ahmaic Univri o lgrad E-mail: knzvic@oincar.ma.bg.ac.u

More information

REPETITION before the exam PART 2, Transform Methods. Laplace transforms: τ dτ. L1. Derive the formulas : L2. Find the Laplace transform F(s) if.

REPETITION before the exam PART 2, Transform Methods. Laplace transforms: τ dτ. L1. Derive the formulas : L2. Find the Laplace transform F(s) if. Tranform Mhod and Calculu of Svral Variabl H7, p Lcurr: Armin Halilovic KTH, Campu Haning E-mail: armin@dkh, wwwdkh/armin REPETITION bfor h am PART, Tranform Mhod Laplac ranform: L Driv h formula : a L[

More information

CATAVASII LA NAȘTEREA DOMNULUI DUMNEZEU ȘI MÂNTUITORULUI NOSTRU, IISUS HRISTOS. CÂNTAREA I-A. Ήχος Πα. to os se e e na aș te e e slă ă ă vi i i i i

CATAVASII LA NAȘTEREA DOMNULUI DUMNEZEU ȘI MÂNTUITORULUI NOSTRU, IISUS HRISTOS. CÂNTAREA I-A. Ήχος Πα. to os se e e na aș te e e slă ă ă vi i i i i CATAVASII LA NAȘTEREA DOMNULUI DUMNEZEU ȘI MÂNTUITORULUI NOSTRU, IISUS HRISTOS. CÂNTAREA I-A Ήχος α H ris to os s n ș t slă ă ă vi i i i i ți'l Hris to o os di in c ru u uri, în tâm pi i n ți i'l Hris

More information

Journal of Contemporary Issues in Business Research USING THE COST-OF-CARRY FORMULA TO DETERMINE FUTURES PRICES: HOW WRONG CAN YOU BE?

Journal of Contemporary Issues in Business Research USING THE COST-OF-CARRY FORMULA TO DETERMINE FUTURES PRICES: HOW WRONG CAN YOU BE? Jonal o Conmpoay I in in Rach ING HE CO-OF-CARRY FORLA O DEERINE FRE PRICE: HO RONG CAN YO E? NORRE LINDE Nowgian niiy o cinc an chnology Dp o Economic Dagoll 749 onhim Noway ARAC In hi no w analyz h picing

More information

Network Flows: Introduction & Maximum Flow

Network Flows: Introduction & Maximum Flow CSC 373 - lgorihm Deign, nalyi, and Complexiy Summer 2016 Lalla Mouaadid Nework Flow: Inroducion & Maximum Flow We now urn our aenion o anoher powerful algorihmic echnique: Local Search. In a local earch

More information

Analysis of Boundedness for Unknown Functions by a Delay Integral Inequality on Time Scales

Analysis of Boundedness for Unknown Functions by a Delay Integral Inequality on Time Scales Inernaional Conference on Image, Viion and Comuing (ICIVC ) IPCSIT vol. 5 () () IACSIT Pre, Singaore DOI:.7763/IPCSIT..V5.45 Anali of Boundedne for Unknown Funcion b a Dela Inegral Ineuali on Time Scale

More information

Physics 240: Worksheet 16 Name

Physics 240: Worksheet 16 Name Phyic 4: Workhee 16 Nae Non-unifor circular oion Each of hee proble involve non-unifor circular oion wih a conan α. (1) Obain each of he equaion of oion for non-unifor circular oion under a conan acceleraion,

More information

14.02 Principles of Macroeconomics Fall 2005 Quiz 3 Solutions

14.02 Principles of Macroeconomics Fall 2005 Quiz 3 Solutions 4.0 rincipl of Macroconomic Fall 005 Quiz 3 Soluion Shor Quion (30/00 poin la a whhr h following amn ar TRUE or FALSE wih a hor xplanaion (3 or 4 lin. Each quion coun 5/00 poin.. An incra in ax oday alway

More information

The Exile Began. Family Journal Page. God Called Jeremiah Jeremiah 1. Preschool. below. Tell. them too. Kids. Ke Passage: Ezekiel 37:27

The Exile Began. Family Journal Page. God Called Jeremiah Jeremiah 1. Preschool. below. Tell. them too. Kids. Ke Passage: Ezekiel 37:27 Faily Jo Pag Th Exil Bg io hy u c prof b jo ou Shar ab ou job ab ar h o ay u Yo ra u ar u r a i A h ) ar par ( grp hav h y y b jo i crib blo Tll ri ir r a r gro up Allo big u r a i Rvi h b of ha u ha a

More information

Flow networks. Flow Networks. A flow on a network. Flow networks. The maximum-flow problem. Introduction to Algorithms, Lecture 22 December 5, 2001

Flow networks. Flow Networks. A flow on a network. Flow networks. The maximum-flow problem. Introduction to Algorithms, Lecture 22 December 5, 2001 CS 545 Flow Nework lon Efra Slide courey of Charle Leieron wih mall change by Carola Wenk Flow nework Definiion. flow nework i a direced graph G = (V, E) wih wo diinguihed verice: a ource and a ink. Each

More information

Motion In One Dimension. Graphing Constant Speed

Motion In One Dimension. Graphing Constant Speed Moion In One Dimenion PLATO AND ARISTOTLE GALILEO GALILEI LEANING TOWER OF PISA Graphing Conan Speed Diance v. Time for Toy Car (0-5 ec.) be-fi line (from TI calculaor) d = 207.7 12.6 Diance (cm) 1000

More information

Anouncements. Conjugate Gradients. Steepest Descent. Outline. Steepest Descent. Steepest Descent

Anouncements. Conjugate Gradients. Steepest Descent. Outline. Steepest Descent. Steepest Descent oucms Couga Gas Mchal Kazha (6.657) Ifomao abou h Sma (6.757) hav b pos ol: hp://www.cs.hu.u/~msha Tch Spcs: o M o Tusay afoo. o Two paps scuss ach w. o Vos fo w s caa paps u by Thusay vg. Oul Rvw of Sps

More information

The angle between L and the z-axis is found from

The angle between L and the z-axis is found from Poblm 6 This is not a ifficult poblm but it is a al pain to tansf it fom pap into Mathca I won't giv it to you on th quiz, but know how to o it fo th xam Poblm 6 S Figu 6 Th magnitu of L is L an th z-componnt

More information

Representing Knowledge. CS 188: Artificial Intelligence Fall Properties of BNs. Independence? Reachability (the Bayes Ball) Example

Representing Knowledge. CS 188: Artificial Intelligence Fall Properties of BNs. Independence? Reachability (the Bayes Ball) Example C 188: Aificial Inelligence Fall 2007 epesening Knowledge ecue 17: ayes Nes III 10/25/2007 an Klein UC ekeley Popeies of Ns Independence? ayes nes: pecify complex join disibuions using simple local condiional

More information

UT Austin, ECE Department VLSI Design 5. CMOS Gate Characteristics

UT Austin, ECE Department VLSI Design 5. CMOS Gate Characteristics La moule: CMOS Tranior heory Thi moule: DC epone Logic Level an Noie Margin Tranien epone Delay Eimaion Tranior ehavior 1) If he wih of a ranior increae, he curren will ) If he lengh of a ranior increae,

More information

THE COST-OF-CARRY FORMULA TO DETERMINE FUTURES PRICES: HOW WRONG CAN YOU BE? *

THE COST-OF-CARRY FORMULA TO DETERMINE FUTURES PRICES: HOW WRONG CAN YOU BE? * Jonal o Conmpoay I in in Rach Volm I No 03 Jonal o Conmpoay I in in Rach IN 305-877 Onlin 03 Vol No 39-43 Copyigh o h Acamic Jonal JCIR All igh HE CO-OF-CARRY FORLA O DEERINE FRE PRICE: HO RONG CAN YO

More information

Math 266, Practice Midterm Exam 2

Math 266, Practice Midterm Exam 2 Mh 66, Prcic Midrm Exm Nm: Ground Rul. Clculor i NOT llowd.. Show your work for vry problm unl ohrwi d (pril crdi r vilbl). 3. You my u on 4-by-6 indx crd, boh id. 4. Th bl of Lplc rnform i vilbl h l pg.

More information

Transfer function and the Laplace transformation

Transfer function and the Laplace transformation Lab No PH-35 Porland Sa Univriy A. La Roa Tranfr funcion and h Laplac ranformaion. INTRODUTION. THE LAPLAE TRANSFORMATION L 3. TRANSFER FUNTIONS 4. ELETRIAL SYSTEMS Analyi of h hr baic paiv lmn R, and

More information

Control Volume Derivation

Control Volume Derivation School of eospace Engineeing Conol Volume -1 Copyigh 1 by Jey M. Seizman. ll ighs esee. Conol Volume Deiaion How o cone ou elaionships fo a close sysem (conol mass) o an open sysem (conol olume) Fo mass

More information

Reinforcement learning

Reinforcement learning CS 75 Mchine Lening Lecue b einfocemen lening Milos Huskech milos@cs.pi.edu 539 Senno Sque einfocemen lening We wn o len conol policy: : X A We see emples of bu oupus e no given Insed of we ge feedbck

More information

Neutrosophic Hyperideals of Semihyperrings

Neutrosophic Hyperideals of Semihyperrings Nuooph m Vol. 06 05 Uv o Nw Mo Nuooph Hpl o mhpg D Ml Dpm o Mhm j P Moh Collg Up Hooghl-758 mljumh@gml.om A. h pp w hv ou uooph hpl o mhpg o om opo o hm o u oo pop. Kwo: C Pou Compoo l o Nuooph mhpmg.

More information

THIS PAGE DECLASSIFIED IAW EO 12958

THIS PAGE DECLASSIFIED IAW EO 12958 L " ^ \ : / 4 a " G E G + : C 4 w i V T / J ` { } ( : f c : < J ; G L ( Y e < + a : v! { : [ y v : ; a G : : : S 4 ; l J / \ l " ` : 5 L " 7 F } ` " x l } l i > G < Y / : 7 7 \ a? / c = l L i L l / c f

More information

Physics 180A Fall 2008 Test points. Provide the best answer to the following questions and problems. Watch your sig figs.

Physics 180A Fall 2008 Test points. Provide the best answer to the following questions and problems. Watch your sig figs. Physics 180A Fall 2008 Tes 1-120 poins Name Provide he bes answer o he following quesions and problems. Wach your sig figs. 1) The number of meaningful digis in a number is called he number of. When numbers

More information

3.1.3 INTRODUCTION TO DYNAMIC OPTIMIZATION: DISCRETE TIME PROBLEMS. A. The Hamiltonian and First-Order Conditions in a Finite Time Horizon

3.1.3 INTRODUCTION TO DYNAMIC OPTIMIZATION: DISCRETE TIME PROBLEMS. A. The Hamiltonian and First-Order Conditions in a Finite Time Horizon 3..3 INRODUCION O DYNAMIC OPIMIZAION: DISCREE IME PROBLEMS A. he Hamilonian and Firs-Order Condiions in a Finie ime Horizon Define a new funcion, he Hamilonian funcion, H. H he change in he oal value of

More information

PHYS GENERAL RELATIVITY AND COSMOLOGY PROBLEM SET 7 - SOLUTIONS

PHYS GENERAL RELATIVITY AND COSMOLOGY PROBLEM SET 7 - SOLUTIONS PHYS 54 - GENERAL RELATIVITY AND COSMOLOGY - 07 - PROBLEM SET 7 - SOLUTIONS TA: Jeome Quinin Mach, 07 Noe ha houghou hee oluion, we wok in uni whee c, and we chooe he meic ignaue (,,, ) a ou convenion..

More information

6.8 Laplace Transform: General Formulas

6.8 Laplace Transform: General Formulas 48 HAP. 6 Laplace Tranform 6.8 Laplace Tranform: General Formula Formula Name, ommen Sec. F() l{ f ()} e f () d f () l {F()} Definiion of Tranform Invere Tranform 6. l{af () bg()} al{f ()} bl{g()} Lineariy

More information

PFC Predictive Functional Control

PFC Predictive Functional Control PFC Prdiciv Funcional Conrol Prof. Car d Prada D. of Sm Enginring and Auomaic Conrol Univri of Valladolid, Sain rada@auom.uva. Oulin A iml a oibl Moivaion PFC main ida An inroducor xaml Moivaion Prdiciv

More information

Optimal Dynamic Asset Allocation with Capital Gains Taxes and Stochastic Volatility

Optimal Dynamic Asset Allocation with Capital Gains Taxes and Stochastic Volatility Opimal Dynamic A Allocaion wih Capial Gain Tax and ochaic olailiy Yuan-Hung Huku * Dpamn of Financial Opaion Naional Kaohiung Fi Uniiy of cinc and Tchnoy ABTRACT Thi pap appli h opion in h ax law o iniga

More information

Algorithms and Data Structures 2011/12 Week 9 Solutions (Tues 15th - Fri 18th Nov)

Algorithms and Data Structures 2011/12 Week 9 Solutions (Tues 15th - Fri 18th Nov) Algorihm and Daa Srucure 2011/ Week Soluion (Tue 15h - Fri 18h No) 1. Queion: e are gien 11/16 / 15/20 8/13 0/ 1/ / 11/1 / / To queion: (a) Find a pair of ube X, Y V uch ha f(x, Y) = f(v X, Y). (b) Find

More information

Math 2214 Solution Test 1 B Spring 2016

Math 2214 Solution Test 1 B Spring 2016 Mah 14 Soluion Te 1 B Spring 016 Problem 1: Ue eparaion of ariable o ole he Iniial alue DE Soluion (14p) e =, (0) = 0 d = e e d e d = o = ln e d uing u-du b leing u = e 1 e = + where C = for he iniial

More information

Chapter 12 Introduction To The Laplace Transform

Chapter 12 Introduction To The Laplace Transform Chapr Inroducion To Th aplac Tranorm Diniion o h aplac Tranorm - Th Sp & Impul uncion aplac Tranorm o pciic uncion 5 Opraional Tranorm Applying h aplac Tranorm 7 Invr Tranorm o Raional uncion 8 Pol and

More information

H STO RY OF TH E SA NT

H STO RY OF TH E SA NT O RY OF E N G L R R VER ritten for the entennial of th e Foundin g of t lair oun t y on ay 8 82 Y EEL N E JEN K RP O N! R ENJ F ] jun E 3 1 92! Ph in t ed b y h e t l a i r R ep u b l i c a n O 4 1922

More information

2. The Laplace Transform

2. The Laplace Transform Th aac Tranorm Inroucion Th aac ranorm i a unamna an vry uu oo or uying many nginring robm To in h aac ranorm w conir a comx variab σ, whr σ i h ra ar an i h imaginary ar or ix vau o σ an w viw a a oin

More information

Sections 3.1 and 3.4 Exponential Functions (Growth and Decay)

Sections 3.1 and 3.4 Exponential Functions (Growth and Decay) Secions 3.1 and 3.4 Eponenial Funcions (Gowh and Decay) Chape 3. Secions 1 and 4 Page 1 of 5 Wha Would You Rahe Have... $1million, o double you money evey day fo 31 days saing wih 1cen? Day Cens Day Cens

More information

Sharif University of Technology - CEDRA By: Professor Ali Meghdari

Sharif University of Technology - CEDRA By: Professor Ali Meghdari Shaif Univesiy of echnology - CEDRA By: Pofesso Ali Meghai Pupose: o exen he Enegy appoach in eiving euaions of oion i.e. Lagange s Meho fo Mechanical Syses. opics: Genealize Cooinaes Lagangian Euaion

More information

Discussion Session 2 Constant Acceleration/Relative Motion Week 03

Discussion Session 2 Constant Acceleration/Relative Motion Week 03 PHYS 100 Dicuion Seion Conan Acceleraion/Relaive Moion Week 03 The Plan Today you will work wih your group explore he idea of reference frame (i.e. relaive moion) and moion wih conan acceleraion. You ll

More information

Linearization Variance Estimators for Survey Data: Some Recent Work

Linearization Variance Estimators for Survey Data: Some Recent Work Pa n a h ICES-III Jun 8-7 Monal Qubc Canaa Linaiaion Vaianc Eiao fo Suvy Daa: So Rcn Wo A. Dnai an J.. K. Rao A. Dnai Social Suvy Mho Diviion Saiic Canaa Oawa Canaa J.. K. Rao School of Mahaic an Saiic

More information

Math 2214 Solution Test 1B Fall 2017

Math 2214 Solution Test 1B Fall 2017 Mah 14 Soluion Tes 1B Fall 017 Problem 1: A ank has a capaci for 500 gallons and conains 0 gallons of waer wih lbs of sal iniiall. A soluion conaining of 8 lbsgal of sal is pumped ino he ank a 10 galsmin.

More information

Introduction to Congestion Games

Introduction to Congestion Games Algorihmic Game Theory, Summer 2017 Inroducion o Congeion Game Lecure 1 (5 page) Inrucor: Thoma Keelheim In hi lecure, we ge o know congeion game, which will be our running example for many concep in game

More information

176 5 t h Fl oo r. 337 P o ly me r Ma te ri al s

176 5 t h Fl oo r. 337 P o ly me r Ma te ri al s A g la di ou s F. L. 462 E l ec tr on ic D ev el op me nt A i ng er A.W.S. 371 C. A. M. A l ex an de r 236 A d mi ni st ra ti on R. H. (M rs ) A n dr ew s P. V. 326 O p ti ca l Tr an sm is si on A p ps

More information

Kinematics Vocabulary. Kinematics and One Dimensional Motion. Position. Coordinate System in One Dimension. Kinema means movement 8.

Kinematics Vocabulary. Kinematics and One Dimensional Motion. Position. Coordinate System in One Dimension. Kinema means movement 8. Kinemaics Vocabulary Kinemaics and One Dimensional Moion 8.1 WD1 Kinema means movemen Mahemaical descripion of moion Posiion Time Inerval Displacemen Velociy; absolue value: speed Acceleraion Averages

More information

where: u: input y: output x: state vector A, B, C, D are const matrices

where: u: input y: output x: state vector A, B, C, D are const matrices Sa pac modl: linar: y or in om : Sa q : f, u Oupu q : y h, u u Du F Gu y H Ju whr: u: inpu y: oupu : a vcor,,, D ar con maric Eampl " $ & ' " $ & 'u y " & * * * * [ ],, D H D I " $ " & $ ' " & $ ' " &

More information

MA 214 Calculus IV (Spring 2016) Section 2. Homework Assignment 1 Solutions

MA 214 Calculus IV (Spring 2016) Section 2. Homework Assignment 1 Solutions MA 14 Calculus IV (Spring 016) Secion Homework Assignmen 1 Soluions 1 Boyce and DiPrima, p 40, Problem 10 (c) Soluion: In sandard form he given firs-order linear ODE is: An inegraing facor is given by

More information

A Simple Method for Determining the Manoeuvring Indices K and T from Zigzag Trial Data

A Simple Method for Determining the Manoeuvring Indices K and T from Zigzag Trial Data Rind 8-- Wbsi: wwwshimoionsnl Ro 67, Jun 97, Dlf Univsiy of chnoloy, Shi Hydomchnics Lbooy, Mklw, 68 CD Dlf, h Nhlnds A Siml Mhod fo Dminin h Mnouvin Indics K nd fom Ziz il D JMJ Jouné Dlf Univsiy of chnoloy

More information

Kinematics in two dimensions

Kinematics in two dimensions Lecure 5 Phsics I 9.18.13 Kinemaics in wo dimensions Course websie: hp://facul.uml.edu/andri_danlo/teaching/phsicsi Lecure Capure: hp://echo36.uml.edu/danlo13/phsics1fall.hml 95.141, Fall 13, Lecure 5

More information

e t dt e t dt = lim e t dt T (1 e T ) = 1

e t dt e t dt = lim e t dt T (1 e T ) = 1 Improper Inegrls There re wo ypes of improper inegrls - hose wih infinie limis of inegrion, nd hose wih inegrnds h pproch some poin wihin he limis of inegrion. Firs we will consider inegrls wih infinie

More information

T ansmission Line Theory Smith Chart

T ansmission Line Theory Smith Chart Tranmiion Thory Smih har Tranmiion Thory Wir conncion Anao / Diia circui: No voa rop on wir conncion Tranmiion Microwav circui: wav on ranmiion Fi anayi: E H EM wav Tranmiion Thory Fiur. p. 5 oa an currn

More information

Identification of the Solution of the Burgers. Equation on a Finite Interval via the Solution of an. Appropriate Stochastic Control Problem

Identification of the Solution of the Burgers. Equation on a Finite Interval via the Solution of an. Appropriate Stochastic Control Problem Ad. heor. Al. Mech. Vol. 3 no. 37-44 Idenificaion of he oluion of he Burger Equaion on a Finie Ineral ia he oluion of an Aroriae ochaic Conrol roblem Arjuna I. Ranainghe Dearmen of Mahemaic Alabama A &

More information

Network Flow. Data Structures and Algorithms Andrei Bulatov

Network Flow. Data Structures and Algorithms Andrei Bulatov Nework Flow Daa Srucure and Algorihm Andrei Bulao Algorihm Nework Flow 24-2 Flow Nework Think of a graph a yem of pipe We ue hi yem o pump waer from he ource o ink Eery pipe/edge ha limied capaciy Flow

More information

Graphs III - Network Flow

Graphs III - Network Flow Graph III - Nework Flow Flow nework eup graph G=(V,E) edge capaciy w(u,v) 0 - if edge doe no exi, hen w(u,v)=0 pecial verice: ource verex ; ink verex - no edge ino and no edge ou of Aume every verex v

More information

y z P 3 P T P1 P 2. Werner Purgathofer. b a

y z P 3 P T P1 P 2. Werner Purgathofer. b a Einführung in Viual Compuing Einführung in Viual Compuing 86.822 in co T P 3 P co in T P P 2 co in Geomeric Tranformaion Geomeric Tranformaion W P h f Werner Purgahofer b a Tranformaion in he Rendering

More information

EECE 301 Signals & Systems Prof. Mark Fowler

EECE 301 Signals & Systems Prof. Mark Fowler EECE 30 Signal & Syem Prof. ark Fowler oe Se #34 C-T Tranfer Funcion and Frequency Repone /4 Finding he Tranfer Funcion from Differenial Eq. Recall: we found a DT yem Tranfer Funcion Hz y aking he ZT of

More information

CONTROL SYSTEMS. Chapter 10 : State Space Response

CONTROL SYSTEMS. Chapter 10 : State Space Response CONTROL SYSTEMS Chaper : Sae Space Repone GATE Objecive & Numerical Type Soluion Queion 5 [GATE EE 99 IIT-Bombay : Mark] Conider a econd order yem whoe ae pace repreenaion i of he form A Bu. If () (),

More information

5.2 GRAPHICAL VELOCITY ANALYSIS Polygon Method

5.2 GRAPHICAL VELOCITY ANALYSIS Polygon Method ME 352 GRHICL VELCITY NLYSIS 52 GRHICL VELCITY NLYSIS olygon Mehod Velociy analyi form he hear of kinemaic and dynamic of mechanical yem Velociy analyi i uually performed following a poiion analyi; ie,

More information

A Theoretical Model of a Voltage Controlled Oscillator

A Theoretical Model of a Voltage Controlled Oscillator A Theoreical Model of a Volage Conrolled Ocillaor Yenming Chen Advior: Dr. Rober Scholz Communicaion Science Iniue Univeriy of Souhern California UWB Workhop, April 11-1, 6 Inroducion Moivaion The volage

More information

4/12/12. Applications of the Maxflow Problem 7.5 Bipartite Matching. Bipartite Matching. Bipartite Matching. Bipartite matching: the flow network

4/12/12. Applications of the Maxflow Problem 7.5 Bipartite Matching. Bipartite Matching. Bipartite Matching. Bipartite matching: the flow network // Applicaion of he Maxflow Problem. Biparie Maching Biparie Maching Biparie maching. Inpu: undireced, biparie graph = (, E). M E i a maching if each node appear in a mo one edge in M. Max maching: find

More information

Differential Kinematics

Differential Kinematics Lctu Diffntia Kinmatic Acknowgmnt : Pof. Ouama Khatib, Robotic Laboato, tanfo Univit, UA Pof. Ha Aaa, AI Laboato, MIT, UA Guiing Qution In obotic appication, not on th poition an ointation, but th vocit

More information

Mathcad Lecture #4 In-class Worksheet Vectors and Matrices 1 (Basics)

Mathcad Lecture #4 In-class Worksheet Vectors and Matrices 1 (Basics) Mh Lr # In-l Workh Vor n Mri (Bi) h n o hi lr, o hol l o: r mri n or in Mh i mri prorm i mri mh oprion ol m o linr qion ing mri mh. Cring Mri Thr r rl o r mri. Th "Inr Mri" Wino (M) B K Poin Rr o

More information

Table of C on t en t s Global Campus 21 in N umbe r s R e g ional Capac it y D e v e lopme nt in E-L e ar ning Structure a n d C o m p o n en ts R ea

Table of C on t en t s Global Campus 21 in N umbe r s R e g ional Capac it y D e v e lopme nt in E-L e ar ning Structure a n d C o m p o n en ts R ea G Blended L ea r ni ng P r o g r a m R eg i o na l C a p a c i t y D ev elo p m ent i n E -L ea r ni ng H R K C r o s s o r d e r u c a t i o n a n d v e l o p m e n t C o p e r a t i o n 3 0 6 0 7 0 5

More information

WEEK-3 Recitation PHYS 131. of the projectile s velocity remains constant throughout the motion, since the acceleration a x

WEEK-3 Recitation PHYS 131. of the projectile s velocity remains constant throughout the motion, since the acceleration a x WEEK-3 Reciaion PHYS 131 Ch. 3: FOC 1, 3, 4, 6, 14. Problems 9, 37, 41 & 71 and Ch. 4: FOC 1, 3, 5, 8. Problems 3, 5 & 16. Feb 8, 018 Ch. 3: FOC 1, 3, 4, 6, 14. 1. (a) The horizonal componen of he projecile

More information