Roughness Coefficients for Selected Residue Materials

Size: px
Start display at page:

Download "Roughness Coefficients for Selected Residue Materials"

Transcription

1 University of Nersk - Linoln DigitlCommons@University of Nersk - Linoln Biologil Systems Engineering: Ppers nd Pulitions Biologil Systems Engineering Roughness Coeffiients for Seleted Residue Mterils John E. Gilley University of Nersk-Linoln, john.gilley@rs.usd.gov Eugene R. Kottwitz University of Nersk-Linoln Gry A. Wiemn University of Nersk-Linoln Follow this nd dditionl works t: Prt of the Biologil Engineering Commons Gilley, John E.; Kottwitz, Eugene R.; nd Wiemn, Gry A., "Roughness Coeffiients for Seleted Residue Mterils" (1991). Biologil Systems Engineering: Ppers nd Pulitions This Artile is rought to you for free nd open ess y the Biologil Systems Engineering t DigitlCommons@University of Nersk - Linoln. It hs een epted for inlusion in Biologil Systems Engineering: Ppers nd Pulitions y n uthorized dministrtor of DigitlCommons@University of Nersk - Linoln.

2 ROUGHNESS COEFFICIENTS FOR SELECTED RESIDUE MATERIALS By John E. Gilley, 1 Eugene R. Kottwitz, 2 nd Gry A. Wiemn 3 ABSTRACT: Anlysis of surfe runoff on uplnd res requires identifition of roughness oeffiients. A lortory study is onduted to mesure Dry-Weish nd Mnning roughness oeffiients for orn, otton, penut, pine needles, sorghum, soyens, sunflower, nd whet residue. Vrying rtes of flow re introdued into flume in whih seleted mounts of residue re seurely tthed. Roughness oeffiients re lulted from mesurements of dishrge rte nd flow veloity. The lortory dt re used to derive regression equtions for relting roughness oeffiients to Reynolds numer nd either perent residue over or residue rte. Seprte equtions re developed for Reynolds numer vlues from 500 to 20,000, nd from 20,000 to 110,000. Generlized equtions re presented for estimting roughness oeffiients for other residue mterils not used in this investigtion. Aurte predition of roughness oeffiients for residue mterils will improve our ility to understnd nd properly model uplnd flow hydrulis. INTRODUCTION Anlysis of surfe runoff on uplnd res requires identifition of hydruli roughness oeffiients. Roughness oeffiients re used in the lultion of flow veloity nd the routing of runoff hydrogrphs. The ility to understnd nd properly model uplnd flow hydrulis is lso essentil in the development of proess-sed erosion models. On griulturl res, resistne to flow my e used y fritionl drg over the soil surfe, stnding vegettive mteril, residue over nd roks lying on the surfe, rindrop impt, nd other ftors. Eh of these elements my ontriute to totl hydruli resistne. Conservtion tillge systems hve een developed tht rely hevily on surfe rop residues s primry mens of ontrolling runoff nd soil erosion. The effets of rindrop impt on flow resistne over smooth surfe were exmined y Shen nd Li (1973). A set of regression equtions were presented to desrie vritions in Dry-Weish frition ftors with rinfll intensity nd Reynolds numer. Gilley et l. (1990) mesured hydruli hrteristis of rills t 11 sites loted throughout the estern United Sttes. Regression equtions were developed tht relted Dry-Weish nd Mnning roughness oeffiients to Reynolds numer. A omprehensive desription of previous studies involving roughness oeffiients on griulturl nd nturl res ws provided y Engmn (1986). Hydruli roughness oeffiients were developed from runoff plot dt originlly olleted for erosion studies. Frition ftors were presented in tulr formt with desription of vrious surfes nd lnd uses. 'Agri. Engr., USDA-ARS, Univ. of Nersk, Linoln, NE Res. Engr., Dept. of Biologil Systems Engrg., Univ. of Nersk, Linoln, NE. 3 Res. Engr., Dept. of Biologil Systems Engrg., Univ. of Nersk, Linoln, NE. Note. Disussion open until Jnury 1, To extend the losing dte one month, written request must e filed with the ASCE Mnger of Journls. The mnusript for this pper ws sumitted for review nd possile pulition on August 9, This pper is prt of the Journl of Irrigtion nd Dringe Engineering, Vol. 117, No. 4, July/August, ASCE, ISSN /91/ /$ $.15 per pge. Pper No

3 Liong et l. (1989) developed simple method for ssigning Mnning roughness oeffiients to overlnd flow segments in kinemti wve models. The proposed method ws found to work well on gged sin. This proedure my e useful in estimting hydrogrphs for ungged wtersheds. Lortory mesurements of roughness oeffiients on surfes overed with snd or grvel were onduted y Woo nd Brter (1961), Emmett (1970), Phelps (1975), nd Svt (1980). Similr tests were performed under field onditions on nturl lndspes y Dunne nd Dietrih (1980), Roels (1984), nd Arhms et l. (1986). In most of these studies, roughness oeffiients deresed with inresing Reynolds numer. One roughness elements re sumerged, their ility to retrd overlnd flow is redued s the depth of overlnd flow eomes greter. A similr redution in roughness oeffiients with inresing Reynolds numer would e expeted for residue mterils. The quntity of rop mteril found on the soil surfe is usully gretest following hrvest. After hrvest, residue mteril is sujeted to deomposition. Tillge serves to inorporte the residue mteril into the soil nd thus redues surfe over. Proedures re ville for estimting the redution in surfe over used y tillge (Colvin et l. 1986). Crop residues found on the soil surfe re usully identified on perentover or residue-rte sis. Surfe over n e rpidly nd urtely mesured in the field. Crop growth models typilly provide estimtes of vegettive dry mtter prodution. Residue rte my lso e mesured y removing nd drying the vegettive mteril olleted from representtive re. The ojetive of this investigtion ws to develop regression equtions for estimting roughness oeffiients for seleted residue mterils. Reltionships re identified for prediting oth Dry-Weish nd Mnning roughness oeffiients. These equtions use Reynolds numer nd either perent over or residue rte s independent vriles. HYDRAULIC EQUATIONS The Dry-Weish nd Mnning equtions hve een widely used to desrie flow hrteristis. Both of these reltions ontin roughness oeffiient. Under uniform flow onditions, the Dry-Weish roughness oeffiient, /, is given s (Chow 1959) 8gRS f ^ (1) where g elertion due to grvity; S verge slope; V flow veloity; nd hydruli rdius, R, is defined s A R ~ p») where A ross-setionl flow re; nd P wetted perimeter. For retngulr flume with flow width y R + 2y 504

4 where y flow depth. For overlnd flow onditions where flow width is muh greter thn flow depth, hydruli rdius n e ssumed to e pproximtely equl to flow depth. The Mnning roughness oeffiient, n, is given s R 2/3 S 1/2 n V Mnning nd Dry-Weish roughness oeffiients n e relted using the following eqution 1/2 Reynolds numer is lso used to desrie flow hrteristis. Reynolds numer, R, is given s VR R (6) v where v kinemti visosity, whih n e determined diretly from wter temperture. The ontinuity eqution for flow is defined s Q VA (7) where Q flow rte. For retngulr flume, wter depth is given s Q y (8) V In this study, wter depth ws determined indiretly using (8), nd mesurements of Q, V, nd. EXPERIMENTAL PROCEDURES The types of residue used in this study inluded orn, otton, penut, pine needles, sorghum, soyens, sunflower, nd whet. Needles produed y ponderos pine were inluded to otin n estimte of roughness oeffiients on forested res. After the residue mterils hd een removed from the field, they were pled in n oven nd dried. For eh residue type, 10 seprte residue elements were seleted for mesurement of residue dimensions. Men residue dimeter nd length re shown in Tle 1. A mesured mss of residue mteril ws glued in rndom orienttion onto setion of reinfored fierglss sheeting. For eh residue type, five residue rtes were seleted. All of the residue mterils exept pine needles nd whet were pplied t rtes equivlent to 2, 4, 6, 8, nd 10 metri tons/ h. Rtes equivlent to 0.75, 2, 4, 6, nd 8 metri tons/h were used for pine needles, while whet strw ws pplied t rtes equivlent to 0.25, 0.50, 1, 2, nd 4 metri tons/h. Sine pine needle nd whet residue elements hd smller dimeters thn the other residue mterils, they furnished greter surfe over t given residue rte. The perentge of surfe over provided t given residue rte ws o- 505

5 TABLE 1. Dimeter, Length, Residue Rts, nd Surfe Cover of Vegettive Mterils Residue type (D Com Dimeter (m) Length (m) Residue rte (metri tons/h) Surfe over (%) ; ' tined using photogrphi grid proedure (Lflen et l. 1978). Residue overs on the fierglss sheets were photogrphed using 35-mm olor slide film. The slides were projeted onto sreen on whih grid hd een superimposed. The numer of grid intersetions over residue mteril ws determined visully from the projeted slides nd surfe over ws then lulted. For eh residue rte, six mesurements of surfe over were otined. The rnge in surfe over vlues for eh residue type is shown in Tle 1. The fierglss sheets with the tthed residue were pled in flume 0.91-m wide, 7.31-m long, nd m deep. The slope grdient of the flume ws mintined t 1.35%. Wter ws supplied to the flume using onstnt hed tnk. Two replited tests were run t 15 flow rtes rnging from 5.24 X 10~ 4 to 1.01 X 10-1 m 3 /s. Flow rte ws determined immeditely efore nd fter eh test to ensure stedy stte onditions. Wter temperture ws mesured following flow rte determintions. Reynolds numer vlues vried from pproximtely 500 to 110,000. It ws diffiult to mintin uniform flow onditions on the residue overed surfes for Reynolds numers less thn pproximtely 500. The flow pity of the flume would hve een exeeded for Reynolds numer vlues signifintly greter thn 110,000. One stedy stte runoff onditions hd eome estlished, line soures of fluoresent dye were injeted ross the flume t downslope distnes of 0.91 m nd 7.01 m. A fluorometer ws used to determine time of trvel of the dye onentrtion peks. Men flow veloity ws identified y dividing the distne etween the two line soures of dye (6.10 m) y the differene in trvel time etween the two dye onentrtion peks. Pek onentrtion ws used euse the dye onentrtion time urves were symmetri. For eh test sequene, three mesurements of flow veloity were mde. Roughness oeffiients for the fierglss sheets on whih the residue mterils were pled were lso identified. The experimentl proedures used to mesure roughness oeffiients for the fierglss sheets with nd without residue were identil. Roughness oeffiients indued y the re fierglss sheets t given Reynolds numer were sutrted from mesurements otined with tthed residue to determine hydruli resistne used y the residue mterils lone. 506

6 RESULTS AND ANALYSIS Surfe-over-residue-rte reltionships otined using regression nlysis re given herein. Equtions for estimting Dry-Weish nd Mnning roughness oeffiients for the residue mterils re lso provided. Finlly, proedures for prediting roughness oeffiients for residue mterils not inluded in this study re presented. Surfe Cover Residue Rte Conversion Both surfe over nd residue rte re used to hrterize the mount of vegettive mteril found on the soil surfe. It my sometimes e neessry to mke onversions etween surfe over nd residue rte for prtiulr vegettive mteril. Regression equtions for mking these onversions re shown in Tle 2. Surfe over nd residue rte vlues used to derive the regression equtions re presented in Tle 1. The rnge in surfe over nd residue rte vlues vried onsiderly etween residue mterils. The regression reltionships shown in Tle 2 should not e used for vlues of surfe over or residue rte outside of the rnge for whih they were derived. Dry-Weish Roughness Coeffiients Dry-Weish roughness oeffiients t vrying Reynolds numers for seleted rtes of whet residue re shown in Fig. 1. The trends presented in Fig. 1 re hrteristi not only of whet residue ut lso the other vegettive mterils used in this investigtion. It n e seen in Fig. 1 tht for given residue rte, the Dry-Weish frition ftor onsistently deresed s Reynolds numer inresed for Reynolds numers less thn pproximtely 20,000. Other investigtors hve otined similr results for sndovered surfes. The vrition in Dry-Weish roughness oeffiient with Reynolds numer ws muh less pronouned for Reynolds numers greter thn 20,000. Surfe over vlues of pproximtely 70%, 79%, nd 99% were provided y whet residue t rtes of 1, 2, nd 4 metri tons/h, respetively. These three whet residue rtes produed similr roughness oeffiients for Reynolds numers greter thn 20,000. TABLE 2. Regression Equtions for Surfe Cover versus Residue Rte Residue type (1) Regression oeffiient," Coeffiient of determintion, r "Regression oeffiient is used in eqution: surfe over 100 (1 e res,du,i ""), where surfe over is given s perentge nd residue rte is in metri tons per hetre. 507

7 CD 'g is CD O,0 CO o CD x: D) g 1 EC % CO U 4.00 Vh B B 2.00 l/h A A 1.00 Mi e e o.so wi l/h CO Q ,000 10,000 Reynolds Numer 100,000 FIG. 1. Dry-Weish Roughness Coeffiients s Funtion of Reynolds Numer for Seleted Rtes of Residue When developing regression reltionships for the dt presented in Fig. 1, seprte equtions were derived for Reynolds numers less thn nd greter thn 20,000. Regression equtions for Dry-Weish roughness oeffiient versus perent over nd Reynolds numer re presented in Tles 3 nd 4 for Reynolds numers less thn nd greter thn 20,000, respetively. For Reynolds numers less thn 20,000 (Tle 3), generlized eqution ws omputed using dt from ll of the residue types. Regression equtions for Dry-Weish roughness oeffiient versus TABLE 3. Regression Equtions for Dry-Weish Roughness Coeffiient versus Perent Cover nd Reynolds Numer for Reynolds Numer Less thn 20,000 Residue type (1) All residue types omined 6.30 x 10" x 1CT x 10" x 1(T x x 10' x 10 _1 Reg ession Coeffiients x 10~' x 10" x 10" x KT x 10" x KT x 10" x 10" x 10~' 3.88 x 10~' Coeffiient of determintion, r "Regression oeffiients,, nd <; used in eqution: / (perent over) /(Reynolds numer)'. 508

8 TABLE 4. Regression Equtions for Dry-Weish Roughness Coeffiient versus Perent Cover nd Reynolds Numer for Reynolds Numer Greter thn 20,000 Residue type 0) 1.23 x 10~ x 10" x 10" x 1CT x 10" x 10" x 1CT x 10" 4 Regression Coeffiients' x 10~' x 10~' 1.44 x 10" x 10" x 10 _ x 10" X 10" x 10~' 1.45 x 10"' Coeffiient of determintion, r "Regression oeffiients,, nd used in eqution:/ (Perent over) 6 /(Reynolds numer)'. residue rte nd Reynolds numer re reported in Tles 5 nd 6 for Reynolds numers less thn nd greter thn 20,000, respetively. Mesurements otined from the vrious residue mterils were omined (Tle 6) to develop generlized eqution for use with vlues of Reynolds numer greter thn 20,000. In the generlized eqution, the Dry-Weish roughness oeffiient n e seen to vry with residue rte in nerly liner fshion. Mnning Roughness Coeffiients Fig. 2 presents Mnning roughness oeffiients s funtion of Reynolds numer for seleted rtes of whet residue. As required y, the shpes of the urves shown in Figs. 1 nd 2 re very similr. The hrteristi redution in roughness oeffiient with inresing Reynolds numer for Reynolds numer vlues less thn 20,000 is evident in Fig. 2. TABLE 5. Regression Equtions for Dry-Weish Roughness Coeffiient versus Residue Rte nd Reynolds Numer for Reynolds Numer Less thn 20,000 Residue type (1) 4.60 x x 10 _l 1.01 x x x x x x Regression Coeffiients" x 10~' X 10"' x 10"' 9.91 x x 10"' 7.89 x 10~ x 10"' 7.10 x 10"' 5.60 x 10"' x 10"' 6.80 x 10"' Coeffiient of determintion, r "Regression oeffiients, >, nd used in eqution: / (residue rte)v(reynolds numer)' where residue rte is in metri tons per hetre. 509

9 TABLE 6. Regression Equtions for Dry-Wsish Roughness Coeffiient versus Residue Rte nd Reynolds Numer for Reynolds Numer Greter thn 20,000 Residue type (1) All residue types omined 1.80 x ,62 x 10"' x 10-' x 10~' 2.84 Regression Coeffiients" x 10' x 10' 'Regression oeffiients,, nd used in eqution: / : numer)" where residue rte is in metri tons per hetre X 10 ' 1.39 X 10"' 2.33 X 10"' 2.89 X 10"' 5.30 X 10" X X 10"' 3.35 x 10~ x 10~ x Coeffiient of determintion; r (residue rte)v(reynolds Seprte equtions for estimting Mnning roughness oeffiients were developed for Reynolds numers less thn nd greter thn 20,000. Tles 7 nd 8 present equtions used for prediting Mnning roughness oeffiients using perent over nd Reynolds numer s independent vriles. Using dt from ll of the residue types, generlized eqution ws derived for estimting roughness oeffiients for Reynolds numers less thn 20,000 (Tle 7). 0) o it <D O o 0) 0) 0) s: O) o e D) C ' to Mi G D 2.00 t/h A A 1.00t/h o s 0.50 t/h 0.25 t/h 1,000 10,000 Reynolds Numer 100,000 FIG. 2. Mnning Roughness Coeffiients s Funtion of Reynolds Numer for Seleted Rtes of Residue 510

10 TABLE 7. Regression Equtions for Mnning Roughness Coeffiient versus Perent Cover nd Reynolds Numer for Reynolds Numer Less thn 20,000 Residue type (1) All residue types omined 4.96 x x 10" x 10-' 5.39 x 10" x 10-' 4.51 x 10"' 4.13 x 10"' 2.07 x 10-' 1.89 x 10' Reg ession Coeffiients" 8.92 x 10-' 6.78 x 10~' 7.03 X 10-' X 10-' 9.13 x 10"' 4.39 X 10-' x 10-' 3.11 X 10" x x 10"' 1.92 X 10-' 1.98 x 10-' 3.58 X 10"' 8.93 x 10' 3.02 x 10"' 1.42 x 10"' Coeffiient of determintion, r' "Regression oeffiients,, nd used in eqution: n (perent over) 6 /(Reynolds numer) 0. As n e seen in Fig. 2, very little hnge in Mnning roughness oeffiients ourred for Reynolds numer vlues greter thn 20,000. For some of the residue mterils, smll inrese in hydruli resistne ourred with inresing Reynolds numer for Reynolds numers ove 20,000. This is further demonstrted y the negtive oeffiients shown for seleted residue mterils in Tle 8. The phenomenon of greter roughness oeffiient with inresing Reynolds numer for very rough surfes ws disussed y Morris (1963). Mnning roughness oeffiients n e estimted from vlues of residue rte for Reynolds numers less thn nd greter thn 20,000 using Tles 9 nd 10, respetively. Agin, s evidened y the negtive oeffiients in Tle 10, smll inreses in roughness oeffiients s Reynolds numer eme lrger were found for some residue mterils t Reynolds numers TABLE 8. Regression Equtions for Mnning Roughness Coeffiient versus Perent Cover nd Reynolds Numer for Reynolds Numer Greter thn 20,000 Residue type (1) Com 5.19 x 10" X 10" X X IO" X 10" x 'X 10" X 10" 4 Regression Coeffiients x 10"' 4.11 x 10"' x 10"' 9.61 x 10"' 8.58 x 10-' x x x 3.11 x 1.89 x 5.10 x 3.30 x x 10"' io-' 10"' 10" 3 io-' 10" 2 10"' 10' Coeffiient of determintion, r "Regression oeffiients,, nd used in eqution: n (perent over) k /(Reynolds numer)". 511

11 Wl TABLE 9. Regression Equtions for Mnning Roughness Coeffiient versus Residue Rte nd Reynolds Numer for Reynolds Numer Less thn 20,000 Residue type (D Com 5.18 x IO x 10~ x 10-' 2.00 x 10"' 2.60 x 10"' 7.25 x 10-' 1.24 x 10"' 1.13 Regression Coeffiients x 10' 6.26 x 10~' 6.83 x 10~' 5.02 x 10 M 4.22 x 10~' 5.97 x KT x 10-' 4.96 x 10-' 2.37 X 10~ X 10~ X 10-' 1.83 X 10"' 1.98 X 10"' 3.59 X 10-' 1.02 X 10"' 3.36 X 10-' Coeffiient of determintion, r 2 ; "Regression oeffiients,, nd used in eqution: n (residue rte)*/(reynolds numer) where residue rte is in metri tons per hetre. ove 20,000. For Reynolds numers greter thn 20,000, generlized eqution ws otined for estimting Mnning roughness oeffiients (Tle 10). Use of Regression Equtions If roughness oeffiients re required for other vegettive mterils, the residue type used in this study most similr to the mteril under onsidertion should e identified. Estimtes of resistne ftors n then e mde using the previously identified equtions. The generlized reltionships n lso e used to predit roughness oeffiients for other vegettive mterils. When using the generlized reltionships, the physil hrteristis of the mteril under onsidertion should e similr to those used in this investigtion (Tle 1). TABLE 10. Regression Equtions for Mnning Roughness Coeffiient versus Residue Rte nd Reynolds Numer for Reynolds Numer Greter thn 20,000 Residue type (D All residue types omined 1.21 x 10"' 1.61 X 10"" x 10" x IO' x 10-' 3.00 x IO' x x X KT 2 Reg ression Coeffiients x 10-' 6.61 x 10"' 4.87 x 10-' 5.72 x 10"' 6.81 x 10-' 5.92 x 10"' 7.37 x 10-' 4.57 x 10"' 5.73 X 10"' 1.74 x x x 6.27 x 1.90 x 4.55 x 1.17 x x 6.44 x io-' 10" 2 io- 3 10" 2 io-' 10" 2 io-' IO" 3 IO" 2 Coeffiient of determintion, r "Regression oeffiients,, nd used in eqution: n (residue rte)''/(reynolds numer)" where residue rte is in metri tons per hetre. 512

12 Residue mterils used in this study were glued in ple during the experimentl tests. Under nturl onditions, the residue mterils my move t higher flow rtes using sustntil hnges in flow resistne. At present, the sher stress required to initite movement of residue mterils is not well defined. SUMMARY AND CONCLUSIONS Anlysis of surfe runoff on uplnd res requires identifition of hydruli roughness oeffiients. Totl hydruli resistne t site my e omposite of roughness omponents used y severl ftors. In this investigtion, roughness oeffiients were identified for seleted residue mterils. Experimentl vriles used in this study inluded residue type, residue rte, nd flow rte. Seleted rtes of orn, otton, penut, pine needles, sorghum, soyens, sunflower, nd whet residue were glued in rndom orienttion on setions of reinfored fierglss sheeting. Mesurements of residue surfe over were mde, nd the fierglss sheets were pled in flume. Stedy uniform flow onditions were then estlished for wide rnge of dishrge rtes. Dry-Weish nd Mnning roughness oeffiients were lulted from mesurements of dishrge rte nd flow veloity. Regression reltionships were developed, whih relted the roughness oeffiients to Reynolds numer nd either perent residue over or residue rte. Both surfe over nd residue rte re frequently used to desrie the mount of vegettive mteril found on soil surfe. Generlized equtions for prediting roughness oeffiients for other types of residue mteril re lso presented. Severl ftors my ontriute to hydruli resistne on uplnd res. Informtion is needed on roughness oeffiients provided y eh of these ftors, their ontriution to totl hydruli roughness, nd the effet of flow rte on roughness oeffiients. This informtion will improve our ility to understnd nd urtely model uplnd flow hydrulis. ACKNOWLEDGMENT This pper is ontriution from USDA-ARS, in oopertion with the Agriulturl Reserh Division, University of Nersk, Linoln, nd is pulished s Journl Series No APPENDIX I. REFERENCES Arhms, A. D., Prsons, A. J., Luk, S. H. (1986). "Resistne to overlnd flow on desert hillslopes." J. Hydro., 88, Chow, V. T. (1959). Open hnnel hydrulis. MGrw Hill, New York, N.Y. Colvin, T. S., Berry, E. C, Erh, D. C, nd Lflen, J. M. (1986). "Tillge implement effets on orn nd soyen residue." Trns. Am. So. Agri. Engrs., Amerin Soiety of Agriulturl Engineers, 29(1), Dunne, T., nd Dietrih, W. E. (1980). "Experimentl study of Horton overlnd flow on tropil hillslopes. 2. Hydruli hrteristis nd hillslope hydrogrphs." Z. Geomphol. Suppl. Bnd., 35, Emmett, W. W. (1970). "The hydrulis of overlnd flow on hillslopes." U.S. Geologil Survey Prof. Pper 662-A, U.S. Govt. Printing Offie, Wshington, D.C. 513

13 Engmn, E. T. (1986). "Roughness oeffiients for routing surfe runoff." /. Irrig. Drin. Engrg., ASCE, 112(1), Gilley, J. E., Kottwitz, E. R., nd Simnton, J. R. (1990). "Hydruli hrteristis of rills." Trns. Am. So. Agri. Engrs., Amerin Soiety of Agriulturl Engineers, 33(6), Lflen, J. M, Bker, J. L., Hrtwig, R. O., Buhele, W. F., nd Johnson, H. P. (1978). "Soil nd wter loss from ontinuous row ropping." Trns. Am. So. Agri. Engrs., Amerin Soiety of Agriulturl Engineers, 21, Liong, S. Y., Selvlingm, S., nd Brdy, D. K. (1989). "Roughness vlues for overlnd flow in suthments." J. Irrig. Drin. Engrg., ASCE, 115, Morris, H. M. (1963). Applied hydrulis in engineering. Ronld Press, New York, N.Y. Phelps, H. O. (1975). "Shllow lminr flows over rough grnulr surfes." J. Hydr. Div., ASCE, 101, Roels, J. M. (1984). "Flow resistne in onentrted overlnd flow on rough slope surfes." Erth Surfe Proesses nd Lndforms, 9, Svt, J. (1980). "Resistne to flow in rough superritil sheet flow." Erth Surfe Proesses nd Lndforms, 5, Shen, W. S., nd Li, R. H. (1973). "Rinfll effet on sheet flow over smooth surfe." J. Hydr. Div., ASCE, 99, Woo, D. C, nd Brter, E. F. (1961). "Lminr flow in rough retngulr hnnels." J. Geophys. Res., 66(12), APPENDIX II. The following NOTATION symols re used in this pper: A f g n P Q R R S V y V ross-setionl flow re; flow width; Dry-Weish roughness oeffiient; elertion due to grvity; Mnning roughness oeffiient; wetted perimeter; flow rte; hydruli rdius; Reynolds numer; verge slope; flow veloity; flow depth; nd kinemti visosity. 514

Review Topic 14: Relationships between two numerical variables

Review Topic 14: Relationships between two numerical variables Review Topi 14: Reltionships etween two numeril vriles Multiple hoie 1. Whih of the following stterplots est demonstrtes line of est fit? A B C D E 2. The regression line eqution for the following grph

More information

Activities. 4.1 Pythagoras' Theorem 4.2 Spirals 4.3 Clinometers 4.4 Radar 4.5 Posting Parcels 4.6 Interlocking Pipes 4.7 Sine Rule Notes and Solutions

Activities. 4.1 Pythagoras' Theorem 4.2 Spirals 4.3 Clinometers 4.4 Radar 4.5 Posting Parcels 4.6 Interlocking Pipes 4.7 Sine Rule Notes and Solutions MEP: Demonstrtion Projet UNIT 4: Trigonometry UNIT 4 Trigonometry tivities tivities 4. Pythgors' Theorem 4.2 Spirls 4.3 linometers 4.4 Rdr 4.5 Posting Prels 4.6 Interloking Pipes 4.7 Sine Rule Notes nd

More information

Darcy-Weisbach Roughness Coefficients for Gravel and Cobble Surfaces

Darcy-Weisbach Roughness Coefficients for Gravel and Cobble Surfaces University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Biological Systems Engineering: Papers and Publications Biological Systems Engineering 2-1992 Darcy-Weisbach Roughness Coefficients

More information

Generalization of 2-Corner Frequency Source Models Used in SMSIM

Generalization of 2-Corner Frequency Source Models Used in SMSIM Generliztion o 2-Corner Frequeny Soure Models Used in SMSIM Dvid M. Boore 26 Mrh 213, orreted Figure 1 nd 2 legends on 5 April 213, dditionl smll orretions on 29 My 213 Mny o the soure spetr models ville

More information

ANALYSIS AND MODELLING OF RAINFALL EVENTS

ANALYSIS AND MODELLING OF RAINFALL EVENTS Proeedings of the 14 th Interntionl Conferene on Environmentl Siene nd Tehnology Athens, Greee, 3-5 Septemer 215 ANALYSIS AND MODELLING OF RAINFALL EVENTS IOANNIDIS K., KARAGRIGORIOU A. nd LEKKAS D.F.

More information

University of Sioux Falls. MAT204/205 Calculus I/II

University of Sioux Falls. MAT204/205 Calculus I/II University of Sioux Flls MAT204/205 Clulus I/II Conepts ddressed: Clulus Textook: Thoms Clulus, 11 th ed., Weir, Hss, Giordno 1. Use stndrd differentition nd integrtion tehniques. Differentition tehniques

More information

Iowa Training Systems Trial Snus Hill Winery Madrid, IA

Iowa Training Systems Trial Snus Hill Winery Madrid, IA Iow Trining Systems Tril Snus Hill Winery Mdrid, IA Din R. Cohrn nd Gil R. Nonneke Deprtment of Hortiulture, Iow Stte University Bkground nd Rtionle: Over the lst severl yers, five sttes hve een evluting

More information

Something found at a salad bar

Something found at a salad bar Nme PP Something found t sld r 4.7 Notes RIGHT TRINGLE hs extly one right ngle. To solve right tringle, you n use things like SOH-H-TO nd the Pythgoren Theorem. n OLIQUE TRINGLE hs no right ngles. To solve

More information

Formula for Trapezoid estimate using Left and Right estimates: Trap( n) If the graph of f is decreasing on [a, b], then f ( x ) dx

Formula for Trapezoid estimate using Left and Right estimates: Trap( n) If the graph of f is decreasing on [a, b], then f ( x ) dx Fill in the Blnks for the Big Topis in Chpter 5: The Definite Integrl Estimting n integrl using Riemnn sum:. The Left rule uses the left endpoint of eh suintervl.. The Right rule uses the right endpoint

More information

THE INFLUENCE OF MODEL RESOLUTION ON AN EXPRESSION OF THE ATMOSPHERIC BOUNDARY LAYER IN A SINGLE-COLUMN MODEL

THE INFLUENCE OF MODEL RESOLUTION ON AN EXPRESSION OF THE ATMOSPHERIC BOUNDARY LAYER IN A SINGLE-COLUMN MODEL THE INFLUENCE OF MODEL RESOLUTION ON AN EXPRESSION OF THE ATMOSPHERIC BOUNDARY LAYER IN A SINGLE-COLUMN MODEL P3.1 Kot Iwmur*, Hiroto Kitgw Jpn Meteorologil Ageny 1. INTRODUCTION Jpn Meteorologil Ageny

More information

Project 6: Minigoals Towards Simplifying and Rewriting Expressions

Project 6: Minigoals Towards Simplifying and Rewriting Expressions MAT 51 Wldis Projet 6: Minigols Towrds Simplifying nd Rewriting Expressions The distriutive property nd like terms You hve proly lerned in previous lsses out dding like terms ut one prolem with the wy

More information

THE PYTHAGOREAN THEOREM

THE PYTHAGOREAN THEOREM THE PYTHAGOREAN THEOREM The Pythgoren Theorem is one of the most well-known nd widely used theorems in mthemtis. We will first look t n informl investigtion of the Pythgoren Theorem, nd then pply this

More information

AP CALCULUS Test #6: Unit #6 Basic Integration and Applications

AP CALCULUS Test #6: Unit #6 Basic Integration and Applications AP CALCULUS Test #6: Unit #6 Bsi Integrtion nd Applitions A GRAPHING CALCULATOR IS REQUIRED FOR SOME PROBLEMS OR PARTS OF PROBLEMS IN THIS PART OF THE EXAMINATION. () The ext numeril vlue of the orret

More information

(h+ ) = 0, (3.1) s = s 0, (3.2)

(h+ ) = 0, (3.1) s = s 0, (3.2) Chpter 3 Nozzle Flow Qusistedy idel gs flow in pipes For the lrge vlues of the Reynolds number typilly found in nozzles, the flow is idel. For stedy opertion with negligible body fores the energy nd momentum

More information

Numbers and indices. 1.1 Fractions. GCSE C Example 1. Handy hint. Key point

Numbers and indices. 1.1 Fractions. GCSE C Example 1. Handy hint. Key point GCSE C Emple 7 Work out 9 Give your nswer in its simplest form Numers n inies Reiprote mens invert or turn upsie own The reiprol of is 9 9 Mke sure you only invert the frtion you re iviing y 7 You multiply

More information

Lecture Notes No. 10

Lecture Notes No. 10 2.6 System Identifition, Estimtion, nd Lerning Leture otes o. Mrh 3, 26 6 Model Struture of Liner ime Invrint Systems 6. Model Struture In representing dynmil system, the first step is to find n pproprite

More information

Symmetrical Components 1

Symmetrical Components 1 Symmetril Components. Introdution These notes should e red together with Setion. of your text. When performing stedy-stte nlysis of high voltge trnsmission systems, we mke use of the per-phse equivlent

More information

Momentum and Energy Review

Momentum and Energy Review Momentum n Energy Review Nme: Dte: 1. A 0.0600-kilogrm ll trveling t 60.0 meters per seon hits onrete wll. Wht spee must 0.0100-kilogrm ullet hve in orer to hit the wll with the sme mgnitue of momentum

More information

1 PYTHAGORAS THEOREM 1. Given a right angled triangle, the square of the hypotenuse is equal to the sum of the squares of the other two sides.

1 PYTHAGORAS THEOREM 1. Given a right angled triangle, the square of the hypotenuse is equal to the sum of the squares of the other two sides. 1 PYTHAGORAS THEOREM 1 1 Pythgors Theorem In this setion we will present geometri proof of the fmous theorem of Pythgors. Given right ngled tringle, the squre of the hypotenuse is equl to the sum of the

More information

SIDESWAY MAGNIFICATION FACTORS FOR STEEL MOMENT FRAMES WITH VARIOUS TYPES OF COLUMN BASES

SIDESWAY MAGNIFICATION FACTORS FOR STEEL MOMENT FRAMES WITH VARIOUS TYPES OF COLUMN BASES Advned Steel Constrution Vol., No., pp. 7-88 () 7 SIDESWAY MAGNIFICATION FACTORS FOR STEEL MOMENT FRAMES WIT VARIOUS TYPES OF COLUMN BASES J. ent sio Assoite Professor, Deprtment of Civil nd Environmentl

More information

Comparing the Pre-image and Image of a Dilation

Comparing the Pre-image and Image of a Dilation hpter Summry Key Terms Postultes nd Theorems similr tringles (.1) inluded ngle (.2) inluded side (.2) geometri men (.) indiret mesurement (.6) ngle-ngle Similrity Theorem (.2) Side-Side-Side Similrity

More information

SECTION A STUDENT MATERIAL. Part 1. What and Why.?

SECTION A STUDENT MATERIAL. Part 1. What and Why.? SECTION A STUDENT MATERIAL Prt Wht nd Wh.? Student Mteril Prt Prolem n > 0 n > 0 Is the onverse true? Prolem If n is even then n is even. If n is even then n is even. Wht nd Wh? Eploring Pure Mths Are

More information

PAIR OF LINEAR EQUATIONS IN TWO VARIABLES

PAIR OF LINEAR EQUATIONS IN TWO VARIABLES PAIR OF LINEAR EQUATIONS IN TWO VARIABLES. Two liner equtions in the sme two vriles re lled pir of liner equtions in two vriles. The most generl form of pir of liner equtions is x + y + 0 x + y + 0 where,,,,,,

More information

Chapter 8 Roots and Radicals

Chapter 8 Roots and Radicals Chpter 8 Roots nd Rdils 7 ROOTS AND RADICALS 8 Figure 8. Grphene is n inredily strong nd flexile mteril mde from ron. It n lso ondut eletriity. Notie the hexgonl grid pttern. (redit: AlexnderAIUS / Wikimedi

More information

AP Calculus BC Chapter 8: Integration Techniques, L Hopital s Rule and Improper Integrals

AP Calculus BC Chapter 8: Integration Techniques, L Hopital s Rule and Improper Integrals AP Clulus BC Chpter 8: Integrtion Tehniques, L Hopitl s Rule nd Improper Integrls 8. Bsi Integrtion Rules In this setion we will review vrious integrtion strtegies. Strtegies: I. Seprte the integrnd into

More information

for all x in [a,b], then the area of the region bounded by the graphs of f and g and the vertical lines x = a and x = b is b [ ( ) ( )] A= f x g x dx

for all x in [a,b], then the area of the region bounded by the graphs of f and g and the vertical lines x = a and x = b is b [ ( ) ( )] A= f x g x dx Applitions of Integrtion Are of Region Between Two Curves Ojetive: Fin the re of region etween two urves using integrtion. Fin the re of region etween interseting urves using integrtion. Desrie integrtion

More information

Mathematics SKE: STRAND F. F1.1 Using Formulae. F1.2 Construct and Use Simple Formulae. F1.3 Revision of Negative Numbers

Mathematics SKE: STRAND F. F1.1 Using Formulae. F1.2 Construct and Use Simple Formulae. F1.3 Revision of Negative Numbers Mthemtis SKE: STRAND F UNIT F1 Formule: Tet STRAND F: Alger F1 Formule Tet Contents Setion F1.1 Using Formule F1. Construt nd Use Simple Formule F1.3 Revision of Negtive Numers F1.4 Sustitution into Formule

More information

21.1 Using Formulae Construct and Use Simple Formulae Revision of Negative Numbers Substitution into Formulae

21.1 Using Formulae Construct and Use Simple Formulae Revision of Negative Numbers Substitution into Formulae MEP Jmi: STRAND G UNIT 1 Formule: Student Tet Contents STRAND G: Alger Unit 1 Formule Student Tet Contents Setion 1.1 Using Formule 1. Construt nd Use Simple Formule 1.3 Revision of Negtive Numers 1.4

More information

Appendix C Partial discharges. 1. Relationship Between Measured and Actual Discharge Quantities

Appendix C Partial discharges. 1. Relationship Between Measured and Actual Discharge Quantities Appendi Prtil dishrges. Reltionship Between Mesured nd Atul Dishrge Quntities A dishrging smple my e simply represented y the euilent iruit in Figure. The pplied lternting oltge V is inresed until the

More information

1 This question is about mean bond enthalpies and their use in the calculation of enthalpy changes.

1 This question is about mean bond enthalpies and their use in the calculation of enthalpy changes. 1 This question is out men ond enthlpies nd their use in the lultion of enthlpy hnges. Define men ond enthlpy s pplied to hlorine. Explin why the enthlpy of tomistion of hlorine is extly hlf the men ond

More information

On the Scale factor of the Universe and Redshift.

On the Scale factor of the Universe and Redshift. On the Sle ftor of the Universe nd Redshift. J. M. unter. john@grvity.uk.om ABSTRACT It is proposed tht there hs been longstnding misunderstnding of the reltionship between sle ftor of the universe nd

More information

Maintaining Mathematical Proficiency

Maintaining Mathematical Proficiency Nme Dte hpter 9 Mintining Mthemtil Profiieny Simplify the epression. 1. 500. 189 3. 5 4. 4 3 5. 11 5 6. 8 Solve the proportion. 9 3 14 7. = 8. = 9. 1 7 5 4 = 4 10. 0 6 = 11. 7 4 10 = 1. 5 9 15 3 = 5 +

More information

5. Every rational number have either terminating or repeating (recurring) decimal representation.

5. Every rational number have either terminating or repeating (recurring) decimal representation. CHAPTER NUMBER SYSTEMS Points to Rememer :. Numer used for ounting,,,,... re known s Nturl numers.. All nturl numers together with zero i.e. 0,,,,,... re known s whole numers.. All nturl numers, zero nd

More information

1B40 Practical Skills

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

More information

EE 330/330L Energy Systems (Spring 2012) Laboratory 1 Three-Phase Loads

EE 330/330L Energy Systems (Spring 2012) Laboratory 1 Three-Phase Loads ee330_spring2012_l_01_3phse_lods.do 1/5 EE 330/330L Energy Systems (Spring 2012) Lortory 1 ThreePhse Lods Introdution/Bkground In this lortory, you will mesure nd study the voltges, urrents, impednes,

More information

CHENG Chun Chor Litwin The Hong Kong Institute of Education

CHENG Chun Chor Litwin The Hong Kong Institute of Education PE-hing Mi terntionl onferene IV: novtion of Mthemtis Tehing nd Lerning through Lesson Study- onnetion etween ssessment nd Sujet Mtter HENG hun hor Litwin The Hong Kong stitute of Edution Report on using

More information

Engr354: Digital Logic Circuits

Engr354: Digital Logic Circuits Engr354: Digitl Logi Ciruits Chpter 4: Logi Optimiztion Curtis Nelson Logi Optimiztion In hpter 4 you will lern out: Synthesis of logi funtions; Anlysis of logi iruits; Tehniques for deriving minimum-ost

More information

Magnetically Coupled Coil

Magnetically Coupled Coil Mgnetilly Coupled Ciruits Overview Mutul Indutne Energy in Coupled Coils Liner Trnsformers Idel Trnsformers Portlnd Stte University ECE 22 Mgnetilly Coupled Ciruits Ver..3 Mgnetilly Coupled Coil i v L

More information

A Study on the Properties of Rational Triangles

A Study on the Properties of Rational Triangles Interntionl Journl of Mthemtis Reserh. ISSN 0976-5840 Volume 6, Numer (04), pp. 8-9 Interntionl Reserh Pulition House http://www.irphouse.om Study on the Properties of Rtionl Tringles M. Q. lm, M.R. Hssn

More information

Calculus Cheat Sheet. Integrals Definitions. where F( x ) is an anti-derivative of f ( x ). Fundamental Theorem of Calculus. dx = f x dx g x dx

Calculus Cheat Sheet. Integrals Definitions. where F( x ) is an anti-derivative of f ( x ). Fundamental Theorem of Calculus. dx = f x dx g x dx Clulus Chet Sheet Integrls Definitions Definite Integrl: Suppose f ( ) is ontinuous Anti-Derivtive : An nti-derivtive of f ( ) on [, ]. Divide [, ] into n suintervls of is funtion, F( ), suh tht F = f.

More information

Electronic Circuits I Revision after midterm

Electronic Circuits I Revision after midterm Eletroni Ciruits I Revision fter miterm Dr. Ahme ElShfee, ACU : Fll 2018, Eletroni Ciruits I -1 / 14 - MCQ1 # Question If the frequeny of the input voltge in Figure 2 36 is inrese, the output voltge will

More information

, g. Exercise 1. Generator polynomials of a convolutional code, given in binary form, are g. Solution 1.

, g. Exercise 1. Generator polynomials of a convolutional code, given in binary form, are g. Solution 1. Exerise Genertor polynomils of onvolutionl ode, given in binry form, re g, g j g. ) Sketh the enoding iruit. b) Sketh the stte digrm. ) Find the trnsfer funtion T. d) Wht is the minimum free distne of

More information

Section 4.4. Green s Theorem

Section 4.4. Green s Theorem The Clulus of Funtions of Severl Vriles Setion 4.4 Green s Theorem Green s theorem is n exmple from fmily of theorems whih onnet line integrls (nd their higher-dimensionl nlogues) with the definite integrls

More information

TOPIC: LINEAR ALGEBRA MATRICES

TOPIC: LINEAR ALGEBRA MATRICES Interntionl Blurete LECTUE NOTES for FUTHE MATHEMATICS Dr TOPIC: LINEA ALGEBA MATICES. DEFINITION OF A MATIX MATIX OPEATIONS.. THE DETEMINANT deta THE INVESE A -... SYSTEMS OF LINEA EQUATIONS. 8. THE AUGMENTED

More information

MATH Final Review

MATH Final Review MATH 1591 - Finl Review November 20, 2005 1 Evlution of Limits 1. the ε δ definition of limit. 2. properties of limits. 3. how to use the diret substitution to find limit. 4. how to use the dividing out

More information

PYTHAGORAS THEOREM WHAT S IN CHAPTER 1? IN THIS CHAPTER YOU WILL:

PYTHAGORAS THEOREM WHAT S IN CHAPTER 1? IN THIS CHAPTER YOU WILL: PYTHAGORAS THEOREM 1 WHAT S IN CHAPTER 1? 1 01 Squres, squre roots nd surds 1 02 Pythgors theorem 1 03 Finding the hypotenuse 1 04 Finding shorter side 1 05 Mixed prolems 1 06 Testing for right-ngled tringles

More information

MATH 122, Final Exam

MATH 122, Final Exam MATH, Finl Exm Winter Nme: Setion: You must show ll of your work on the exm pper, legily n in etil, to reeive reit. A formul sheet is tthe.. (7 pts eh) Evlute the following integrls. () 3x + x x Solution.

More information

Section 1.3 Triangles

Section 1.3 Triangles Se 1.3 Tringles 21 Setion 1.3 Tringles LELING TRINGLE The line segments tht form tringle re lled the sides of the tringle. Eh pir of sides forms n ngle, lled n interior ngle, nd eh tringle hs three interior

More information

Effects of Drought on the Performance of Two Hybrid Bluegrasses, Kentucky Bluegrass and Tall Fescue

Effects of Drought on the Performance of Two Hybrid Bluegrasses, Kentucky Bluegrass and Tall Fescue TITLE: OBJECTIVE: AUTHOR: SPONSORS: Effets of Drought on the Performne of Two Hyrid Bluegrsses, Kentuky Bluegrss nd Tll Fesue Evlute the effets of drought on the visul qulity nd photosynthesis in two hyrid

More information

6.5 Improper integrals

6.5 Improper integrals Eerpt from "Clulus" 3 AoPS In. www.rtofprolemsolving.om 6.5. IMPROPER INTEGRALS 6.5 Improper integrls As we ve seen, we use the definite integrl R f to ompute the re of the region under the grph of y =

More information

Lecture Summaries for Multivariable Integral Calculus M52B

Lecture Summaries for Multivariable Integral Calculus M52B These leture summries my lso be viewed online by liking the L ion t the top right of ny leture sreen. Leture Summries for Multivrible Integrl Clulus M52B Chpter nd setion numbers refer to the 6th edition.

More information

I 3 2 = I I 4 = 2A

I 3 2 = I I 4 = 2A ECE 210 Eletril Ciruit Anlysis University of llinois t Chigo 2.13 We re ske to use KCL to fin urrents 1 4. The key point in pplying KCL in this prolem is to strt with noe where only one of the urrents

More information

Polynomials. Polynomials. Curriculum Ready ACMNA:

Polynomials. Polynomials. Curriculum Ready ACMNA: Polynomils Polynomils Curriulum Redy ACMNA: 66 www.mthletis.om Polynomils POLYNOMIALS A polynomil is mthemtil expression with one vrile whose powers re neither negtive nor frtions. The power in eh expression

More information

( ) as a fraction. Determine location of the highest

( ) as a fraction. Determine location of the highest AB/ Clulus Exm Review Sheet Solutions A Prelulus Type prolems A1 A A3 A4 A5 A6 A7 This is wht you think of doing Find the zeros of f( x) Set funtion equl to Ftor or use qudrti eqution if qudrti Grph to

More information

Tutorial Worksheet. 1. Find all solutions to the linear system by following the given steps. x + 2y + 3z = 2 2x + 3y + z = 4.

Tutorial Worksheet. 1. Find all solutions to the linear system by following the given steps. x + 2y + 3z = 2 2x + 3y + z = 4. Mth 5 Tutoril Week 1 - Jnury 1 1 Nme Setion Tutoril Worksheet 1. Find ll solutions to the liner system by following the given steps x + y + z = x + y + z = 4. y + z = Step 1. Write down the rgumented mtrix

More information

NEW CIRCUITS OF HIGH-VOLTAGE PULSE GENERATORS WITH INDUCTIVE-CAPACITIVE ENERGY STORAGE

NEW CIRCUITS OF HIGH-VOLTAGE PULSE GENERATORS WITH INDUCTIVE-CAPACITIVE ENERGY STORAGE NEW CIRCUITS OF HIGH-VOLTAGE PULSE GENERATORS WITH INDUCTIVE-CAPACITIVE ENERGY STORAGE V.S. Gordeev, G.A. Myskov Russin Federl Nuler Center All-Russi Sientifi Reserh Institute of Experimentl Physis (RFNC-VNIIEF)

More information

GM1 Consolidation Worksheet

GM1 Consolidation Worksheet Cmridge Essentils Mthemtis Core 8 GM1 Consolidtion Worksheet GM1 Consolidtion Worksheet 1 Clulte the size of eh ngle mrked y letter. Give resons for your nswers. or exmple, ngles on stright line dd up

More information

Trigonometry Revision Sheet Q5 of Paper 2

Trigonometry Revision Sheet Q5 of Paper 2 Trigonometry Revision Sheet Q of Pper The Bsis - The Trigonometry setion is ll out tringles. We will normlly e given some of the sides or ngles of tringle nd we use formule nd rules to find the others.

More information

Math 32B Discussion Session Week 8 Notes February 28 and March 2, f(b) f(a) = f (t)dt (1)

Math 32B Discussion Session Week 8 Notes February 28 and March 2, f(b) f(a) = f (t)dt (1) Green s Theorem Mth 3B isussion Session Week 8 Notes Februry 8 nd Mrh, 7 Very shortly fter you lerned how to integrte single-vrible funtions, you lerned the Fundmentl Theorem of lulus the wy most integrtion

More information

Green s Theorem. (2x e y ) da. (2x e y ) dx dy. x 2 xe y. (1 e y ) dy. y=1. = y e y. y=0. = 2 e

Green s Theorem. (2x e y ) da. (2x e y ) dx dy. x 2 xe y. (1 e y ) dy. y=1. = y e y. y=0. = 2 e Green s Theorem. Let be the boundry of the unit squre, y, oriented ounterlokwise, nd let F be the vetor field F, y e y +, 2 y. Find F d r. Solution. Let s write P, y e y + nd Q, y 2 y, so tht F P, Q. Let

More information

Intermediate Math Circles Wednesday 17 October 2012 Geometry II: Side Lengths

Intermediate Math Circles Wednesday 17 October 2012 Geometry II: Side Lengths Intermedite Mth Cirles Wednesdy 17 Otoer 01 Geometry II: Side Lengths Lst week we disussed vrious ngle properties. As we progressed through the evening, we proved mny results. This week, we will look t

More information

Probability. b a b. a b 32.

Probability. b a b. a b 32. Proility If n event n hppen in '' wys nd fil in '' wys, nd eh of these wys is eqully likely, then proility or the hne, or its hppening is, nd tht of its filing is eg, If in lottery there re prizes nd lnks,

More information

QUADRATIC EQUATION. Contents

QUADRATIC EQUATION. Contents QUADRATIC EQUATION Contents Topi Pge No. Theory 0-04 Exerise - 05-09 Exerise - 09-3 Exerise - 3 4-5 Exerise - 4 6 Answer Key 7-8 Syllus Qudrti equtions with rel oeffiients, reltions etween roots nd oeffiients,

More information

Introduction to Olympiad Inequalities

Introduction to Olympiad Inequalities Introdution to Olympid Inequlities Edutionl Studies Progrm HSSP Msshusetts Institute of Tehnology Snj Simonovikj Spring 207 Contents Wrm up nd Am-Gm inequlity 2. Elementry inequlities......................

More information

Distance Measurement. Distance Measurement. Distance Measurement. Distance Measurement. Distance Measurement. Distance Measurement

Distance Measurement. Distance Measurement. Distance Measurement. Distance Measurement. Distance Measurement. Distance Measurement IVL 1101 Surveying - Mesuring Distne 1/5 Distne is one of the most si engineering mesurements Erly mesurements were mde in terms of the dimensions of the ody very old wooden rule - Royl Egyptin uit uits

More information

12.4 Similarity in Right Triangles

12.4 Similarity in Right Triangles Nme lss Dte 12.4 Similrit in Right Tringles Essentil Question: How does the ltitude to the hpotenuse of right tringle help ou use similr right tringles to solve prolems? Eplore Identifing Similrit in Right

More information

Solutions to Assignment 1

Solutions to Assignment 1 MTHE 237 Fll 2015 Solutions to Assignment 1 Problem 1 Find the order of the differentil eqution: t d3 y dt 3 +t2 y = os(t. Is the differentil eqution liner? Is the eqution homogeneous? b Repet the bove

More information

Unit 4. Combinational Circuits

Unit 4. Combinational Circuits Unit 4. Comintionl Ciruits Digitl Eletroni Ciruits (Ciruitos Eletrónios Digitles) E.T.S.I. Informáti Universidd de Sevill 5/10/2012 Jorge Jun 2010, 2011, 2012 You re free to opy, distriute

More information

A Non-parametric Approach in Testing Higher Order Interactions

A Non-parametric Approach in Testing Higher Order Interactions A Non-prmetri Approh in Testing igher Order Intertions G. Bkeerthn Deprtment of Mthemtis, Fulty of Siene Estern University, Chenkldy, Sri Lnk nd S. Smit Deprtment of Crop Siene, Fulty of Agriulture University

More information

Lecture 6: Coding theory

Lecture 6: Coding theory Leture 6: Coing theory Biology 429 Crl Bergstrom Ferury 4, 2008 Soures: This leture loosely follows Cover n Thoms Chpter 5 n Yeung Chpter 3. As usul, some of the text n equtions re tken iretly from those

More information

8 THREE PHASE A.C. CIRCUITS

8 THREE PHASE A.C. CIRCUITS 8 THREE PHSE.. IRUITS The signls in hpter 7 were sinusoidl lternting voltges nd urrents of the so-lled single se type. n emf of suh type n e esily generted y rotting single loop of ondutor (or single winding),

More information

Thermal Diffusivity. Paul Hughes. Department of Physics and Astronomy The University of Manchester Manchester M13 9PL. Second Year Laboratory Report

Thermal Diffusivity. Paul Hughes. Department of Physics and Astronomy The University of Manchester Manchester M13 9PL. Second Year Laboratory Report Therml iffusivity Pul Hughes eprtment of Physics nd Astronomy The University of nchester nchester 3 9PL Second Yer Lbortory Report Nov 4 Abstrct We investigted the therml diffusivity of cylindricl block

More information

I1 = I2 I1 = I2 + I3 I1 + I2 = I3 + I4 I 3

I1 = I2 I1 = I2 + I3 I1 + I2 = I3 + I4 I 3 2 The Prllel Circuit Electric Circuits: Figure 2- elow show ttery nd multiple resistors rrnged in prllel. Ech resistor receives portion of the current from the ttery sed on its resistnce. The split is

More information

This chapter will show you. What you should already know. 1 Write down the value of each of the following. a 5 2

This chapter will show you. What you should already know. 1 Write down the value of each of the following. a 5 2 1 Direct vrition 2 Inverse vrition This chpter will show you how to solve prolems where two vriles re connected y reltionship tht vries in direct or inverse proportion Direct proportion Inverse proportion

More information

Finite Element Simulation on Frictional and Brittle Preseismic fault slip

Finite Element Simulation on Frictional and Brittle Preseismic fault slip Finite Element Simultion on Fritionl nd Brittle Preseismi fult slip Zhishen Wu (1) Yun Go (1) Yutk Murkmi (2) (1) Deprtment of Urn & Civil Engineering. Irki University, Jpn (e-mil: zswu@ip.irki..jp; goyun@hs.irki..jp,

More information

For a, b, c, d positive if a b and. ac bd. Reciprocal relations for a and b positive. If a > b then a ab > b. then

For a, b, c, d positive if a b and. ac bd. Reciprocal relations for a and b positive. If a > b then a ab > b. then Slrs-7.2-ADV-.7 Improper Definite Integrls 27.. D.dox Pge of Improper Definite Integrls Before we strt the min topi we present relevnt lger nd it review. See Appendix J for more lger review. Inequlities:

More information

Lecture 27: Diffusion of Ions: Part 2: coupled diffusion of cations and

Lecture 27: Diffusion of Ions: Part 2: coupled diffusion of cations and Leture 7: iffusion of Ions: Prt : oupled diffusion of tions nd nions s desried y Nernst-Plnk Eqution Tody s topis Continue to understnd the fundmentl kinetis prmeters of diffusion of ions within n eletrilly

More information

22: Union Find. CS 473u - Algorithms - Spring April 14, We want to maintain a collection of sets, under the operations of:

22: Union Find. CS 473u - Algorithms - Spring April 14, We want to maintain a collection of sets, under the operations of: 22: Union Fin CS 473u - Algorithms - Spring 2005 April 14, 2005 1 Union-Fin We wnt to mintin olletion of sets, uner the opertions of: 1. MkeSet(x) - rete set tht ontins the single element x. 2. Fin(x)

More information

( ) { } [ ] { } [ ) { } ( ] { }

( ) { } [ ] { } [ ) { } ( ] { } Mth 65 Prelulus Review Properties of Inequlities 1. > nd > >. > + > +. > nd > 0 > 4. > nd < 0 < Asolute Vlue, if 0, if < 0 Properties of Asolute Vlue > 0 1. < < > or

More information

Thermodynamics. Question 1. Question 2. Question 3 3/10/2010. Practice Questions PV TR PV T R

Thermodynamics. Question 1. Question 2. Question 3 3/10/2010. Practice Questions PV TR PV T R /10/010 Question 1 1 mole of idel gs is rought to finl stte F y one of three proesses tht hve different initil sttes s shown in the figure. Wht is true for the temperture hnge etween initil nd finl sttes?

More information

First compression (0-6.3 GPa) First decompression ( GPa) Second compression ( GPa) Second decompression (35.

First compression (0-6.3 GPa) First decompression ( GPa) Second compression ( GPa) Second decompression (35. 0.9 First ompression (0-6.3 GP) First deompression (6.3-2.7 GP) Seond ompression (2.7-35.5 GP) Seond deompression (35.5-0 GP) V/V 0 0.7 0.5 0 5 10 15 20 25 30 35 P (GP) Supplementry Figure 1 Compression

More information

On Implicative and Strong Implicative Filters of Lattice Wajsberg Algebras

On Implicative and Strong Implicative Filters of Lattice Wajsberg Algebras Glol Journl of Mthemtil Sienes: Theory nd Prtil. ISSN 974-32 Volume 9, Numer 3 (27), pp. 387-397 Interntionl Reserh Pulition House http://www.irphouse.om On Implitive nd Strong Implitive Filters of Lttie

More information

Chapter Gauss Quadrature Rule of Integration

Chapter Gauss Quadrature Rule of Integration Chpter 7. Guss Qudrture Rule o Integrtion Ater reding this hpter, you should e le to:. derive the Guss qudrture method or integrtion nd e le to use it to solve prolems, nd. use Guss qudrture method to

More information

Instructions to students: Use your Text Book and attempt these questions.

Instructions to students: Use your Text Book and attempt these questions. Instrutions to students: Use your Text Book nd ttempt these questions. Due Dte: 16-09-2018 Unit 2 Chpter 8 Test Slrs nd vetors Totl mrks 50 Nme: Clss: Dte: Setion A Selet the est nswer for eh question.

More information

April 8, 2017 Math 9. Geometry. Solving vector problems. Problem. Prove that if vectors and satisfy, then.

April 8, 2017 Math 9. Geometry. Solving vector problems. Problem. Prove that if vectors and satisfy, then. pril 8, 2017 Mth 9 Geometry Solving vetor prolems Prolem Prove tht if vetors nd stisfy, then Solution 1 onsider the vetor ddition prllelogrm shown in the Figure Sine its digonls hve equl length,, the prllelogrm

More information

Novel Fiber-Optical Refractometric Sensor Employing Hemispherically-Shaped Detection Element

Novel Fiber-Optical Refractometric Sensor Employing Hemispherically-Shaped Detection Element Novel Fier-Optil Refrtometri Sensor Employing Hemispherilly-Shped Detetion Element SERGEI KHOTIAINTSEV, VLADIMIR SVIRID Deprtment of Eletril Engineering, Fulty of Engineering Ntionl Autonomous University

More information

Calculating Tank Wetted Area Saving time, increasing accuracy

Calculating Tank Wetted Area Saving time, increasing accuracy Clulting Tnk Wetted Are ving time, inresing ur B n Jones, P.., P.E. C lulting wetted re in rtillfilled orizontl or vertil lindril or ellitil tnk n e omlited, deending on fluid eigt nd te se of te eds (ends)

More information

1.3 SCALARS AND VECTORS

1.3 SCALARS AND VECTORS Bridge Course Phy I PUC 24 1.3 SCLRS ND VECTORS Introdution: Physis is the study of nturl phenomen. The study of ny nturl phenomenon involves mesurements. For exmple, the distne etween the plnet erth nd

More information

Part 4. Integration (with Proofs)

Part 4. Integration (with Proofs) Prt 4. Integrtion (with Proofs) 4.1 Definition Definition A prtition P of [, b] is finite set of points {x 0, x 1,..., x n } with = x 0 < x 1

More information

6.3.2 Spectroscopy. N Goalby chemrevise.org 1 NO 2 H 3 CH3 C. NMR spectroscopy. Different types of NMR

6.3.2 Spectroscopy. N Goalby chemrevise.org 1 NO 2 H 3 CH3 C. NMR spectroscopy. Different types of NMR 6.. Spetrosopy NMR spetrosopy Different types of NMR NMR spetrosopy involves intertion of mterils with the lowenergy rdiowve region of the eletromgneti spetrum NMR spetrosopy is the sme tehnology s tht

More information

Forces on curved surfaces Buoyant force Stability of floating and submerged bodies

Forces on curved surfaces Buoyant force Stability of floating and submerged bodies Stti Surfe ores Stti Surfe ores 8m wter hinge? 4 m ores on plne res ores on urved surfes Buont fore Stbilit of floting nd submerged bodies ores on Plne res Two tpes of problems Horizontl surfes (pressure

More information

2.4 Linear Inequalities and Interval Notation

2.4 Linear Inequalities and Interval Notation .4 Liner Inequlities nd Intervl Nottion We wnt to solve equtions tht hve n inequlity symol insted of n equl sign. There re four inequlity symols tht we will look t: Less thn , Less thn or

More information

ERT 316: REACTION ENGINEERING CHAPTER 3 RATE LAWS & STOICHIOMETRY

ERT 316: REACTION ENGINEERING CHAPTER 3 RATE LAWS & STOICHIOMETRY ER 316: REIO EGIEERIG HER 3 RE LWS & SOIHIOMERY 1 OULIE R 1: Rte Lws Reltive Rtes of Retion Retion Orer & Rte Lw Retion Rte onstnt, k R 2: Stoihiometry th System Stoihiometri le low System Stoihiometri

More information

Factorising FACTORISING.

Factorising FACTORISING. Ftorising FACTORISING www.mthletis.om.u Ftorising FACTORISING Ftorising is the opposite of expning. It is the proess of putting expressions into rkets rther thn expning them out. In this setion you will

More information

Section 6: Area, Volume, and Average Value

Section 6: Area, Volume, and Average Value Chpter The Integrl Applied Clculus Section 6: Are, Volume, nd Averge Vlue Are We hve lredy used integrls to find the re etween the grph of function nd the horizontl xis. Integrls cn lso e used to find

More information

Proving the Pythagorean Theorem

Proving the Pythagorean Theorem Proving the Pythgoren Theorem W. Bline Dowler June 30, 2010 Astrt Most people re fmilir with the formul 2 + 2 = 2. However, in most ses, this ws presented in lssroom s n solute with no ttempt t proof or

More information

2. There are an infinite number of possible triangles, all similar, with three given angles whose sum is 180.

2. There are an infinite number of possible triangles, all similar, with three given angles whose sum is 180. SECTION 8-1 11 CHAPTER 8 Setion 8 1. There re n infinite numer of possile tringles, ll similr, with three given ngles whose sum is 180. 4. If two ngles α nd β of tringle re known, the third ngle n e found

More information

Learning Objectives of Module 2 (Algebra and Calculus) Notes:

Learning Objectives of Module 2 (Algebra and Calculus) Notes: 67 Lerning Ojetives of Module (Alger nd Clulus) Notes:. Lerning units re grouped under three res ( Foundtion Knowledge, Alger nd Clulus ) nd Further Lerning Unit.. Relted lerning ojetives re grouped under

More information

Influence of Knife Bevel Angle, Rate of Loading and Stalk Section on Some Engineering Parameters of Lilium Stalk

Influence of Knife Bevel Angle, Rate of Loading and Stalk Section on Some Engineering Parameters of Lilium Stalk Irni Journl of Energy & Environment 3 (4): 333-340, 01 ISSN 079-115 IJEE n Offiil Peer Reviewed Journl of Bol Noshirvni University of Tehnology DOI: 10.589/idosi.ijee.01.03.04.07 BUT Influene of Knife

More information

Reflection Property of a Hyperbola

Reflection Property of a Hyperbola Refletion Propert of Hperol Prefe The purpose of this pper is to prove nltill nd to illustrte geometrill the propert of hperol wherein r whih emntes outside the onvit of the hperol, tht is, etween the

More information