Determination of the Noise Level Produced by Road Traffic
|
|
- Merry Lamb
- 6 years ago
- Views:
Transcription
1 Deermnaon of he Nose evel Produced by Road Traffc lna Mhaela RĂDO Unversy POTHNC of Buchares, Splaul ndependene 33, Romana, Ncolae NSCU Deparmen of Mechancs, Unversy POTHNC of Buchares, Splaul ndependene 33, Romana, oan MGHȚ Deparmen of Mechancs, Unversy POTHNC of Buchares, Splaul ndependene 33, Romana, bsrac: - Ths paper presens he NMPB-996 ( Nouvelle Méhode de Prévson du Bru ) mehod for deermnng he level of nose produced by road raffc wh he sofware Cadna. n mos of he cases, he modellng of he road s smply performed, hrough he fllng n of he number of vehcles / hour and he vehcle percenage. n he wor hereby, n he modellng of he road, here were used he daa, measuremens and he calculaons, n order o esablsh he level of acousc power per lengh un. n conclusons are presened he comparave analyss beween values of he nose n he wo cases. Keywords: - raffc nose, road vehcles, nose level, nose measuremens. NTRODUCTON 2. MTHODS Nose polluon creaes dscomfor and become annoyng and even harmful n some areas of Buchares, raffc areres, near he arpor, near sources of nose. Based on nose measuremens performed s esmaed ha raffc on he man roads, and especally wh heavy raffc nose polluon frequenly exceeds he level of 70 db (), consdered admssble. Combned wh gas polluon, nose polluon n some pons of nersecon of he srees n Buchares becomes unbearable. Share of major sources of nose polluon, besdes he fxed ndusral orgn, held n he case of large urban areas n 80% moble sources,.e. road raffc. n he U, he sandard approach for analyzng a raffc nose problem n an urban area s based on calculaons wh smple models. Frs nose levels n he area are calculaed wh an engneerng nose model and nex emprcal exposure-response relaons are appled o esmae he prevalence of annoyance and sleep dsurbance. The focus s ofen on annoyance a home, and herefore he nose levels are calculaed a he facades of dwellngs. n hs paper, nose levels values obaned by on se measuremens are compared wh values obaned by calculaon usng formulas and he values obaned by modelng he area wh specalzed sofware Cadna. 2. Nose measuremens on se n mporan elemen n performng accurae measuremens s he choce of measuremen pons. Fgure n pon was nsalled on a rpod a sound level meer - ype 2250 o monor he nose level for 24 hours (fgure). Pons 2, 3 and 4 were chosen o he dsance of 2 m from he hospal buldng facades. Pon 5 was chosen a he mdway beween he wo juncons a 2 m from he curb. Duraon of recordng he ousde nose level was 30 mnues for perods of he, evenng and ngh (5 mnues for each drecon of movemen). Hourly raffc flows were deermned esmavely by exrapolaon (mulplcaon wh 4) of drec RJV vol X ssue 2/ SSN
2 recordngs. When he vehcles are couned, mus be made a dfference beween he 2 ypes of vehcles (lgh and heavy). Şefan cel Mare Road presens 6 raffc lanes (3 raffc lanes for each drecon) and he coun of he vehcles was performed for he 2 raffc drecons. For emporary perods of ( 7-9 h), evenng ( 9-23 h), ngh ( 23-7 h) here were measured he wo generc caegores of vehcles (lgh: m < 3.5, cars, buses, slen rams, pc-up and heavy vehcles : m > 3.5, buses, coaches, rucs, moorcycles). Repeang he measuremen a all recever posons was necessary o ensure sascal relably of he resuls (hree repeons). The able shows he nose measuremens performed n he 5 pons and he number of lgh/ heavy vehcles durng measuremens. Table No eq eq evenng eq ngh Pon Pon Pon Pon Pon No Day venng Ngh gh veh/h Heavy veh/h The eq s he mos approprae nose descrpor o use when measurng nose mpacs. eq: - weghed equvalen connuous sound pressure level n db; eq : Day equvalen level: -weghed, equvalen connuous sound pressure level, measured over he 2-hour perod hours eq evenng: venng equvalen level: - weghed, equvalen connuous sound pressure level, measured over he 4-hour perod hours eq ngh: Ngh equvalen level: -weghed, equvalen connuous sound pressure level, measured over he 8- hour perod hours 2.2 Nose level calculaon wh formulas n he desgn and execuon gude of he urban areas from an acousc pon of vew, ndcave P6 (Consrucon Bullen NCRC), s presened he mehod of calculang he raffc nose level wh he equaon: ex n f 0. 0 lg db 0 () T where: ex. f s he equvalen nose level from raffc ousde, near he proeced funconal un; - s he nose level on he sragh secons of he raffc areres n whch he dsances beween he buldng frons (locaed face o face) are smaller or a leas equal o 75 m; s calculaed accordng o he ype of he nose sources wh he equaon: 0csczv lg d d d d d 0 d d D 2 d 0 db D d D D 2 d0 d 0 d0 n whch (2) s characersc nose of a source " passng hrough he measurng pon deermned a m from he lm of he source; D = he dsance beween he buldng frons (m) d = he dsance from he source o he measuremen pon; d 0 = m d = dsance from he source o he fron of he buldng =0 (coeffcen of drecvy of he source consdered on he normal drecon o he fron of he buldngs) =3 (coeffcen of drecvy of he refleced waves beween he frons of buldngs n case of 4-8 floors on one sde of he road and no more han 5 floors on he oher sde) =0.03 (sound absorpon coeffcen of buldng facades, where s he measurng pon s locaed ) 2 = 0.03 (sound absorpon coeffcen of buldng facades, he oppose sde) c s= land surface coeffcen, c zv = coeffcen of he green area, c s = 0.90 (asphal); c zv =.75 The calculaon of he me correspondng o he acon s performed, n he case of he raffc, wh relaon: = n (s), n whch n s he number of raffc vehcles of a parcular ype, ha flows n he characersc perod T, for whch he RJV vol X ssue 2/ SSN
3 equvalen nose level s deermned by measuremen or sascal calculaons. n pon 5, values for n were deermned by measurng : - cars ( 3400 veh/ h- ; 800 veh/ h evenng ; 650 veh/ h- ngh) - rams ( 30 veh/ h- ; 20 veh/ h- evenng; 0 veh/ h- ngh) - mnbuses/ pc-up ( 290 veh/ h- ; 220 veh/ h evenng; 90 veh/ h ngh) - moorcycles ( 20 veh/ h- ; 20 veh/ h- evenng; 0 veh/ h-ngh) - rucs ( 82 veh/ h- ; 28 veh/ h- evenng; 6 veh /h- ngh) - buses ( 60 veh/h-; 50 veh/h- evenng; 8 veh/hngh) The values for dfferen ypes of raffc sources are presened such : cars (.2 s), rams ( 2 s), mnbuses (.2 s), moorcycles (.8 s), rucs (.2 s), buses (.8 s), where s he me when he vehcle passes hrough a dsance = 20 m. On he paved srees are consdered he lgh vehcles: cars, mnbuses and slen rams. The remanng conveyances are he heavy vehcle raffc. Nose levels characersc o he sources consdered are rounded for he calculaon, n 5 classes of nose: 70, 75, 80, 85, 90 db (); n each class fs he vehcles whose characersc nose devaes more han ± 2 db () from he value of he class defnon. The values for lgh vehcles on paved srees are: = 70 db() (cars ); = 75 db() (mnbuses); = 80 db() (slen rams) The values for heavy vehcles on paved srees are: = 85 db() (moorcycles) ; = 90 db() (rucs) ; = 85 db() ( buses) The equvalen nose level ousde, s calculaed a a pon wh he equaon (2) for n dfferen nose sources : - for example, pon 5 ( d= 2 m) : 0.03 cars lg ( cars)= db(); ( rams) = db(); db() ( buses)= db() ( moorcycles)= ( mnbuses)= db(); db() ex ( rucs)= ,67 72, lg 3400, , 20 77,68 82,68 87,68 82, ,80 82,20 60,80 ex db() ; ex db() evenng; ex db() ngh The values and same for pons - 4. ex. f are calculaed he 2.3 The modellng of he area wh he Cadna sofware The mehod of calculaon for raffc wh he sofware Cadna s NMPB-996 ( Nouvelle Méhode de Prévson du Bru ). : For modelng he road, he raffc flow Q (n vehcle / hour) and he percenage of heavy vehcles p% mus be specfed. QP Q Q V Q P and p% Q QV - number of he lgh vehcles raffc (max.mass <3.5 ), n veh/ h QP - number of he heavy vehcles raffc, n vehcles / hour Q = 94( number veh./h for sens of movemen) (3) p% = 4.2 (4) Q =069 (number veh./h ) (5) p% = 4.6 evenng (6) Q =387 (number veh./h) (7) p% =4.4 ngh (8) The sree has 6 raffc lanes (3 raffc lanes for each drecon) and he numberng of he vehcles was done for he 2 raffc drecons. he numberng of he vehcles n he raffc, was made a dsncon beween he 2 ypes of vehcles (lgh and heavy). s consdered he speed lm of 50 m / h for lgh vehcles and 40 m / h for heavy vehcles. Of he four ypes of raffc flows, s chosen he pulse non-dfferenaed. Horzonal graden of he road for sree and raffc flow pulse s 2.%. Because of he fac ha on he chosen sree here crculae more han 300 vehcles / hour, s consdered he lnear source of nfne lengh. ll hese aspecs and he 3-8 relaons are flled n he dalogue box of he road n fgure 2. RJV vol X ssue 2/ SSN
4 QP - number of he heavy vehcles raffc, n vehcles / hour Correcon for operang me: D 0lg / B (0) Fgure 2. Nose level () = measurng me (h); B = reference me (2 h-, 4h-evenng; 8h-ngh) D 0lg / = 0 lg( 60/720)= () B D =0 lg(60/240)= - 6,02 (evenng); D =0 lg(60/480)= (ngh) Correcon due o dsance and ar absorpon: dv =20 lg(d/do)+ () do = m; d= source-recever dsance n Cadna, for he frequency of 500 Hz, he amospherc absorpon coeffcen s db/m. The sound power level per lengh un s calculaed usng he equaon (9) such: Fgure 3. Nose level (evenng) 67,67 72,68 77,68 V = lg = 78.5dB; 82,68 87,68 82,68 P = lg =89.2dB w, = 87.4 db (); w, = db (evenng) ; w, = 8.70 db (ngh) The values of he acousc power level, on lengh un, calculaed based on relaon (9), are flled n he dalogue box of he road for he modellng of he nose level (fgure 5). Fgure 4. Nose level (ngh) : f s no flled he number of vehcles / hour, hen s calculaed and compleed he dalog box of he road, he sound power level per lengh un: Q Q V 0 lg V /0 P 0 lg P /0 w, 0 lg 0 0 correcons (9) V V - sound power level of he lgh vehcles, n db () Q - number of he lgh vehcles raffc (max.mass < 3.5 ), n veh/ h P - sound power level of he heavy vehcles (m> 3.5 ), n db () Fgure 5. Nose level () RJV vol X ssue 2/ SSN
5 Table 2: Dfferences of db beween values of he nose n he wo cases No. Pon eve nng ngh eve nng ngh Pon Pon Fgure 6. Nose level (evenng) Pon Pon Fgure 7. Nose level (ngh) Fgure 8. Modelng area Cadna 3D Ngh 3.CONCUSONS The overall fndngs of hs nose sudy show ha he Cadna nose modellng pacage s as accurae and effecve as he nose measuremens n road raffc. Therefore boh models are consdered compeen, relable and generally accurae n modellng raffc nose. n conclusons are presened he comparave analyss beween values of he nose n he wo cases and (able 2). n he modellng of he road (case ), here were used he daa and measuremens from 2. and he calculaons from 2.2, n order o esablsh he level of acousc power per lengh un (rel.9). So, he resul of he modellng s beer because of he qualy of he enry daa. RFRNCS [] Consrucon Bullen, NCRC, Vol. 3 [2]. M. Salomons, S.. Janssen, H..M. Verhagen, P. W.Wessels, xpermenal sudy of raffc nose and human response n an urban area, ner.nose 204. [3] P.Karanons, T.Gowen, M. Smon, Furher Comparson of Traffc Nose Predcons Usng he Cadna and SoundPN Nose, Proceedngs of 20h nernaonal Congress on couscs, C 200. [4].K. Shula, S.S. Jan, M. Parda, J.B. Srvasava, Performance of FHW model for predcng raffc nose: case sudy of meropolan cy, ucnow (nda), Transpor, 2009, pp [5] M.J Crocer, Handboo of Nose and Vbraon Conrol, 2007, pp [6] C.H. Hansen, D.. Bes, ngneerng Nose Conrol: Theory and Pracce, Fourh don, 2009, CRC Press. [7] V.K. Kuraula, M. Kuffer, 3D Nose Modelng for Urban nvronmenal Planng and Managemen, Real Corp, 2008 Proceedngs. [8] DaaKus GmbH, Cadna Reference Manual, 202. [9] Klujver D.H., Soer J.: Nose mappng and GS: opmsng qualy and effcency of nose effec sudes, Compuers, nvromenal and Urban Sysems, RJV vol X ssue 2/ SSN
Chapter Lagrangian Interpolation
Chaper 5.4 agrangan Inerpolaon Afer readng hs chaper you should be able o:. dere agrangan mehod of nerpolaon. sole problems usng agrangan mehod of nerpolaon and. use agrangan nerpolans o fnd deraes and
More informationSolution in semi infinite diffusion couples (error function analysis)
Soluon n sem nfne dffuson couples (error funcon analyss) Le us consder now he sem nfne dffuson couple of wo blocks wh concenraon of and I means ha, n a A- bnary sysem, s bondng beween wo blocks made of
More informationV.Abramov - FURTHER ANALYSIS OF CONFIDENCE INTERVALS FOR LARGE CLIENT/SERVER COMPUTER NETWORKS
R&RATA # Vol.) 8, March FURTHER AALYSIS OF COFIDECE ITERVALS FOR LARGE CLIET/SERVER COMPUTER ETWORKS Vyacheslav Abramov School of Mahemacal Scences, Monash Unversy, Buldng 8, Level 4, Clayon Campus, Wellngon
More informationIn the complete model, these slopes are ANALYSIS OF VARIANCE FOR THE COMPLETE TWO-WAY MODEL. (! i+1 -! i ) + [(!") i+1,q - [(!
ANALYSIS OF VARIANCE FOR THE COMPLETE TWO-WAY MODEL The frs hng o es n wo-way ANOVA: Is here neracon? "No neracon" means: The man effecs model would f. Ths n urn means: In he neracon plo (wh A on he horzonal
More information5th International Conference on Advanced Design and Manufacturing Engineering (ICADME 2015)
5h Inernaonal onference on Advanced Desgn and Manufacurng Engneerng (IADME 5 The Falure Rae Expermenal Sudy of Specal N Machne Tool hunshan He, a, *, La Pan,b and Bng Hu 3,c,,3 ollege of Mechancal and
More informationHEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD
Journal of Appled Mahemacs and Compuaonal Mechancs 3, (), 45-5 HEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD Sansław Kukla, Urszula Sedlecka Insue of Mahemacs,
More informationOn One Analytic Method of. Constructing Program Controls
Appled Mahemacal Scences, Vol. 9, 05, no. 8, 409-407 HIKARI Ld, www.m-hkar.com hp://dx.do.org/0.988/ams.05.54349 On One Analyc Mehod of Consrucng Program Conrols A. N. Kvko, S. V. Chsyakov and Yu. E. Balyna
More informationVariants of Pegasos. December 11, 2009
Inroducon Varans of Pegasos SooWoong Ryu bshboy@sanford.edu December, 009 Youngsoo Cho yc344@sanford.edu Developng a new SVM algorhm s ongong research opc. Among many exng SVM algorhms, we wll focus on
More informationTSS = SST + SSE An orthogonal partition of the total SS
ANOVA: Topc 4. Orhogonal conrass [ST&D p. 183] H 0 : µ 1 = µ =... = µ H 1 : The mean of a leas one reamen group s dfferen To es hs hypohess, a basc ANOVA allocaes he varaon among reamen means (SST) equally
More informationELASTIC MODULUS ESTIMATION OF CHOPPED CARBON FIBER TAPE REINFORCED THERMOPLASTICS USING THE MONTE CARLO SIMULATION
THE 19 TH INTERNATIONAL ONFERENE ON OMPOSITE MATERIALS ELASTI MODULUS ESTIMATION OF HOPPED ARBON FIBER TAPE REINFORED THERMOPLASTIS USING THE MONTE ARLO SIMULATION Y. Sao 1*, J. Takahash 1, T. Masuo 1,
More information[ ] 2. [ ]3 + (Δx i + Δx i 1 ) / 2. Δx i-1 Δx i Δx i+1. TPG4160 Reservoir Simulation 2018 Lecture note 3. page 1 of 5
TPG460 Reservor Smulaon 08 page of 5 DISCRETIZATIO OF THE FOW EQUATIOS As we already have seen, fne dfference appromaons of he paral dervaves appearng n he flow equaons may be obaned from Taylor seres
More informationRobustness Experiments with Two Variance Components
Naonal Insue of Sandards and Technology (NIST) Informaon Technology Laboraory (ITL) Sascal Engneerng Dvson (SED) Robusness Expermens wh Two Varance Componens by Ana Ivelsse Avlés avles@ns.gov Conference
More informationCubic Bezier Homotopy Function for Solving Exponential Equations
Penerb Journal of Advanced Research n Compung and Applcaons ISSN (onlne: 46-97 Vol. 4, No.. Pages -8, 6 omoopy Funcon for Solvng Eponenal Equaons S. S. Raml *,,. Mohamad Nor,a, N. S. Saharzan,b and M.
More informationMechanics Physics 151
Mechancs Physcs 5 Lecure 0 Canoncal Transformaons (Chaper 9) Wha We Dd Las Tme Hamlon s Prncple n he Hamlonan formalsm Dervaon was smple δi δ Addonal end-pon consrans pq H( q, p, ) d 0 δ q ( ) δq ( ) δ
More informationBernoulli process with 282 ky periodicity is detected in the R-N reversals of the earth s magnetic field
Submed o: Suden Essay Awards n Magnecs Bernoull process wh 8 ky perodcy s deeced n he R-N reversals of he earh s magnec feld Jozsef Gara Deparmen of Earh Scences Florda Inernaonal Unversy Unversy Park,
More informationNumerical Simulation of the Dispersion of a Plume of Exhaust Gases from Diesel and Petrol Engine Vehicles
World Academy of Scence, Engneerng and Technology 67 01 Numercal Smulaon of he Dsperson of a Plume of Exhaus Gases from Desel and Perol Engne Vehcles H. ZAHLOUL, and M. MERIEM-BENZIANE Absrac The obecve
More informationCH.3. COMPATIBILITY EQUATIONS. Continuum Mechanics Course (MMC) - ETSECCPB - UPC
CH.3. COMPATIBILITY EQUATIONS Connuum Mechancs Course (MMC) - ETSECCPB - UPC Overvew Compably Condons Compably Equaons of a Poenal Vecor Feld Compably Condons for Infnesmal Srans Inegraon of he Infnesmal
More informationComprehensive Integrated Simulation and Optimization of LPP for EUV Lithography Devices
Comprehense Inegraed Smulaon and Opmaon of LPP for EUV Lhograph Deces A. Hassanen V. Su V. Moroo T. Su B. Rce (Inel) Fourh Inernaonal EUVL Smposum San Dego CA Noember 7-9 2005 Argonne Naonal Laboraor Offce
More informationVolatility Interpolation
Volaly Inerpolaon Prelmnary Verson March 00 Jesper Andreasen and Bran Huge Danse Mares, Copenhagen wan.daddy@danseban.com brno@danseban.com Elecronc copy avalable a: hp://ssrn.com/absrac=69497 Inro Local
More informationGENERATING CERTAIN QUINTIC IRREDUCIBLE POLYNOMIALS OVER FINITE FIELDS. Youngwoo Ahn and Kitae Kim
Korean J. Mah. 19 (2011), No. 3, pp. 263 272 GENERATING CERTAIN QUINTIC IRREDUCIBLE POLYNOMIALS OVER FINITE FIELDS Youngwoo Ahn and Kae Km Absrac. In he paper [1], an explc correspondence beween ceran
More informationLinear Response Theory: The connection between QFT and experiments
Phys540.nb 39 3 Lnear Response Theory: The connecon beween QFT and expermens 3.1. Basc conceps and deas Q: ow do we measure he conducvy of a meal? A: we frs nroduce a weak elecrc feld E, and hen measure
More informationTime-interval analysis of β decay. V. Horvat and J. C. Hardy
Tme-nerval analyss of β decay V. Horva and J. C. Hardy Work on he even analyss of β decay [1] connued and resuled n he developmen of a novel mehod of bea-decay me-nerval analyss ha produces hghly accurae
More informationChapters 2 Kinematics. Position, Distance, Displacement
Chapers Knemacs Poson, Dsance, Dsplacemen Mechancs: Knemacs and Dynamcs. Knemacs deals wh moon, bu s no concerned wh he cause o moon. Dynamcs deals wh he relaonshp beween orce and moon. The word dsplacemen
More informationTHERMODYNAMICS 1. The First Law and Other Basic Concepts (part 2)
Company LOGO THERMODYNAMICS The Frs Law and Oher Basc Conceps (par ) Deparmen of Chemcal Engneerng, Semarang Sae Unversy Dhon Harano S.T., M.T., M.Sc. Have you ever cooked? Equlbrum Equlbrum (con.) Equlbrum
More informationExistence and Uniqueness Results for Random Impulsive Integro-Differential Equation
Global Journal of Pure and Appled Mahemacs. ISSN 973-768 Volume 4, Number 6 (8), pp. 89-87 Research Inda Publcaons hp://www.rpublcaon.com Exsence and Unqueness Resuls for Random Impulsve Inegro-Dfferenal
More informationII. Light is a Ray (Geometrical Optics)
II Lgh s a Ray (Geomercal Opcs) IIB Reflecon and Refracon Hero s Prncple of Leas Dsance Law of Reflecon Hero of Aleandra, who lved n he 2 nd cenury BC, posulaed he followng prncple: Prncple of Leas Dsance:
More informationComparison of Differences between Power Means 1
In. Journal of Mah. Analyss, Vol. 7, 203, no., 5-55 Comparson of Dfferences beween Power Means Chang-An Tan, Guanghua Sh and Fe Zuo College of Mahemacs and Informaon Scence Henan Normal Unversy, 453007,
More informationFI 3103 Quantum Physics
/9/4 FI 33 Quanum Physcs Aleander A. Iskandar Physcs of Magnesm and Phooncs Research Grou Insu Teknolog Bandung Basc Conces n Quanum Physcs Probably and Eecaon Value Hesenberg Uncerany Prncle Wave Funcon
More informationNew M-Estimator Objective Function. in Simultaneous Equations Model. (A Comparative Study)
Inernaonal Mahemacal Forum, Vol. 8, 3, no., 7 - HIKARI Ld, www.m-hkar.com hp://dx.do.org/.988/mf.3.3488 New M-Esmaor Objecve Funcon n Smulaneous Equaons Model (A Comparave Sudy) Ahmed H. Youssef Professor
More informationUNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 2017 EXAMINATION
INTERNATIONAL TRADE T. J. KEHOE UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 27 EXAMINATION Please answer wo of he hree quesons. You can consul class noes, workng papers, and arcles whle you are workng on he
More informationRELATIONSHIP BETWEEN VOLATILITY AND TRADING VOLUME: THE CASE OF HSI STOCK RETURNS DATA
RELATIONSHIP BETWEEN VOLATILITY AND TRADING VOLUME: THE CASE OF HSI STOCK RETURNS DATA Mchaela Chocholaá Unversy of Economcs Braslava, Slovaka Inroducon (1) one of he characersc feaures of sock reurns
More informationDynamic Team Decision Theory. EECS 558 Project Shrutivandana Sharma and David Shuman December 10, 2005
Dynamc Team Decson Theory EECS 558 Proec Shruvandana Sharma and Davd Shuman December 0, 005 Oulne Inroducon o Team Decson Theory Decomposon of he Dynamc Team Decson Problem Equvalence of Sac and Dynamc
More informationM. Y. Adamu Mathematical Sciences Programme, AbubakarTafawaBalewa University, Bauchi, Nigeria
IOSR Journal of Mahemacs (IOSR-JM e-issn: 78-578, p-issn: 9-765X. Volume 0, Issue 4 Ver. IV (Jul-Aug. 04, PP 40-44 Mulple SolonSoluons for a (+-dmensonalhroa-sasuma shallow waer wave equaon UsngPanlevé-Bӓclund
More informationPHYS 1443 Section 001 Lecture #4
PHYS 1443 Secon 001 Lecure #4 Monda, June 5, 006 Moon n Two Dmensons Moon under consan acceleraon Projecle Moon Mamum ranges and heghs Reerence Frames and relae moon Newon s Laws o Moon Force Newon s Law
More informationComb Filters. Comb Filters
The smple flers dscussed so far are characered eher by a sngle passband and/or a sngle sopband There are applcaons where flers wh mulple passbands and sopbands are requred Thecomb fler s an example of
More informationMulti-Fuel and Mixed-Mode IC Engine Combustion Simulation with a Detailed Chemistry Based Progress Variable Library Approach
Mul-Fuel and Med-Mode IC Engne Combuson Smulaon wh a Dealed Chemsry Based Progress Varable Lbrary Approach Conens Inroducon Approach Resuls Conclusons 2 Inroducon New Combuson Model- PVM-MF New Legslaons
More informationThis document is downloaded from DR-NTU, Nanyang Technological University Library, Singapore.
Ths documen s downloaded from DR-NTU, Nanyang Technologcal Unversy Lbrary, Sngapore. Tle A smplfed verb machng algorhm for word paron n vsual speech processng( Acceped verson ) Auhor(s) Foo, Say We; Yong,
More informationACEI working paper series RETRANSFORMATION BIAS IN THE ADJACENT ART PRICE INDEX
ACEI workng paper seres RETRANSFORMATION BIAS IN THE ADJACENT ART PRICE INDEX Andrew M. Jones Robero Zanola AWP-01-2011 Dae: July 2011 Reransformaon bas n he adjacen ar prce ndex * Andrew M. Jones and
More informationModeling and Solving of Multi-Product Inventory Lot-Sizing with Supplier Selection under Quantity Discounts
nernaonal ournal of Appled Engneerng Research SSN 0973-4562 Volume 13, Number 10 (2018) pp. 8708-8713 Modelng and Solvng of Mul-Produc nvenory Lo-Szng wh Suppler Selecon under Quany Dscouns Naapa anchanaruangrong
More informationResponse of MDOF systems
Response of MDOF syses Degree of freedo DOF: he nu nuber of ndependen coordnaes requred o deerne copleely he posons of all pars of a syse a any nsan of e. wo DOF syses hree DOF syses he noral ode analyss
More informationChapter 6: AC Circuits
Chaper 6: AC Crcus Chaper 6: Oulne Phasors and he AC Seady Sae AC Crcus A sable, lnear crcu operang n he seady sae wh snusodal excaon (.e., snusodal seady sae. Complee response forced response naural response.
More informationJohn Geweke a and Gianni Amisano b a Departments of Economics and Statistics, University of Iowa, USA b European Central Bank, Frankfurt, Germany
Herarchcal Markov Normal Mxure models wh Applcaons o Fnancal Asse Reurns Appendx: Proofs of Theorems and Condonal Poseror Dsrbuons John Geweke a and Gann Amsano b a Deparmens of Economcs and Sascs, Unversy
More informationAnisotropic Behaviors and Its Application on Sheet Metal Stamping Processes
Ansoropc Behavors and Is Applcaon on Shee Meal Sampng Processes Welong Hu ETA-Engneerng Technology Assocaes, Inc. 33 E. Maple oad, Sue 00 Troy, MI 48083 USA 48-79-300 whu@ea.com Jeanne He ETA-Engneerng
More informationAdvanced time-series analysis (University of Lund, Economic History Department)
Advanced me-seres analss (Unvers of Lund, Economc Hsor Dearmen) 3 Jan-3 Februar and 6-3 March Lecure 4 Economerc echnues for saonar seres : Unvarae sochasc models wh Box- Jenns mehodolog, smle forecasng
More informationPolymerization Technology Laboratory Course
Prakkum Polymer Scence/Polymersaonsechnk Versuch Resdence Tme Dsrbuon Polymerzaon Technology Laboraory Course Resdence Tme Dsrbuon of Chemcal Reacors If molecules or elemens of a flud are akng dfferen
More informationNPTEL Project. Econometric Modelling. Module23: Granger Causality Test. Lecture35: Granger Causality Test. Vinod Gupta School of Management
P age NPTEL Proec Economerc Modellng Vnod Gua School of Managemen Module23: Granger Causaly Tes Lecure35: Granger Causaly Tes Rudra P. Pradhan Vnod Gua School of Managemen Indan Insue of Technology Kharagur,
More information2.1 Constitutive Theory
Secon.. Consuve Theory.. Consuve Equaons Governng Equaons The equaons governng he behavour of maerals are (n he spaal form) dρ v & ρ + ρdv v = + ρ = Conservaon of Mass (..a) d x σ j dv dvσ + b = ρ v& +
More information12d Model. Civil and Surveying Software. Drainage Analysis Module Detention/Retention Basins. Owen Thornton BE (Mech), 12d Model Programmer
d Model Cvl and Surveyng Soware Dranage Analyss Module Deenon/Reenon Basns Owen Thornon BE (Mech), d Model Programmer owen.hornon@d.com 4 January 007 Revsed: 04 Aprl 007 9 February 008 (8Cp) Ths documen
More informationImplementation of Quantized State Systems in MATLAB/Simulink
SNE T ECHNICAL N OTE Implemenaon of Quanzed Sae Sysems n MATLAB/Smulnk Parck Grabher, Mahas Rößler 2*, Bernhard Henzl 3 Ins. of Analyss and Scenfc Compung, Venna Unversy of Technology, Wedner Haupsraße
More informationNotes on the stability of dynamic systems and the use of Eigen Values.
Noes on he sabl of dnamc ssems and he use of Egen Values. Source: Macro II course noes, Dr. Davd Bessler s Tme Seres course noes, zarads (999) Ineremporal Macroeconomcs chaper 4 & Techncal ppend, and Hamlon
More informationCapacities of Unsignalized Intersections Under Mixed Vehicular and Nonmotorized Traffic Conditions
apaces of Unsgnalzed Inersecons Under Mxed Vehcular and onmoorzed Traffc ondons Hayuan L, We Deng, Zong Tan, and Pefeng Hu Unsgnalzed nersecons conss of hree ypes wo-way sopconrolled, all-way sop-conrolled,
More informationDEEP UNFOLDING FOR MULTICHANNEL SOURCE SEPARATION SUPPLEMENTARY MATERIAL
DEEP UNFOLDING FOR MULTICHANNEL SOURCE SEPARATION SUPPLEMENTARY MATERIAL Sco Wsdom, John Hershey 2, Jonahan Le Roux 2, and Shnj Waanabe 2 Deparmen o Elecrcal Engneerng, Unversy o Washngon, Seale, WA, USA
More informationCHAPTER 10: LINEAR DISCRIMINATION
CHAPER : LINEAR DISCRIMINAION Dscrmnan-based Classfcaon 3 In classfcaon h K classes (C,C,, C k ) We defned dscrmnan funcon g j (), j=,,,k hen gven an es eample, e chose (predced) s class label as C f g
More informationAnalysis And Evaluation of Econometric Time Series Models: Dynamic Transfer Function Approach
1 Appeared n Proceedng of he 62 h Annual Sesson of he SLAAS (2006) pp 96. Analyss And Evaluaon of Economerc Tme Seres Models: Dynamc Transfer Funcon Approach T.M.J.A.COORAY Deparmen of Mahemacs Unversy
More informationJournal of Theoretical and Applied Information Technology.
Journal of heorecal and Appled Informaon echnology 5-9 JAI. All rghs reserved. www.ja.org NEW APPROXIMAION FOR ANDOFF RAE AND NUMBER OF ANDOFF PROBABILIY IN CELLULAR SYSEMS UNDER GENERAL DISRIBUIONS OF
More informationTight results for Next Fit and Worst Fit with resource augmentation
Tgh resuls for Nex F and Wors F wh resource augmenaon Joan Boyar Leah Epsen Asaf Levn Asrac I s well known ha he wo smple algorhms for he classc n packng prolem, NF and WF oh have an approxmaon rao of
More informatione-journal Reliability: Theory& Applications No 2 (Vol.2) Vyacheslav Abramov
June 7 e-ournal Relably: Theory& Applcaons No (Vol. CONFIDENCE INTERVALS ASSOCIATED WITH PERFORMANCE ANALYSIS OF SYMMETRIC LARGE CLOSED CLIENT/SERVER COMPUTER NETWORKS Absrac Vyacheslav Abramov School
More informationOnline Supplement for Dynamic Multi-Technology. Production-Inventory Problem with Emissions Trading
Onlne Supplemen for Dynamc Mul-Technology Producon-Invenory Problem wh Emssons Tradng by We Zhang Zhongsheng Hua Yu Xa and Baofeng Huo Proof of Lemma For any ( qr ) Θ s easy o verfy ha he lnear programmng
More information( ) () we define the interaction representation by the unitary transformation () = ()
Hgher Order Perurbaon Theory Mchael Fowler 3/7/6 The neracon Represenaon Recall ha n he frs par of hs course sequence, we dscussed he chrödnger and Hesenberg represenaons of quanum mechancs here n he chrödnger
More informationSklar: Sections (4.4.2 is not covered).
COSC 44: Dgal Councaons Insrucor: Dr. Ar Asf Deparen of Copuer Scence and Engneerng York Unversy Handou # 6: Bandpass Modulaon opcs:. Phasor Represenaon. Dgal Modulaon Schees: PSK FSK ASK APK ASK/FSK)
More informationAttribute Reduction Algorithm Based on Discernibility Matrix with Algebraic Method GAO Jing1,a, Ma Hui1, Han Zhidong2,b
Inernaonal Indusral Informacs and Compuer Engneerng Conference (IIICEC 05) Arbue educon Algorhm Based on Dscernbly Marx wh Algebrac Mehod GAO Jng,a, Ma Hu, Han Zhdong,b Informaon School, Capal Unversy
More information[Link to MIT-Lab 6P.1 goes here.] After completing the lab, fill in the following blanks: Numerical. Simulation s Calculations
Chaper 6: Ordnary Leas Squares Esmaon Procedure he Properes Chaper 6 Oulne Cln s Assgnmen: Assess he Effec of Sudyng on Quz Scores Revew o Regresson Model o Ordnary Leas Squares () Esmaon Procedure o he
More informationDual Approximate Dynamic Programming for Large Scale Hydro Valleys
Dual Approxmae Dynamc Programmng for Large Scale Hydro Valleys Perre Carpener and Jean-Phlppe Chanceler 1 ENSTA ParsTech and ENPC ParsTech CMM Workshop, January 2016 1 Jon work wh J.-C. Alas, suppored
More informationMotion in Two Dimensions
Phys 1 Chaper 4 Moon n Two Dmensons adzyubenko@csub.edu hp://www.csub.edu/~adzyubenko 005, 014 A. Dzyubenko 004 Brooks/Cole 1 Dsplacemen as a Vecor The poson of an objec s descrbed by s poson ecor, r The
More informationApproximate Analytic Solution of (2+1) - Dimensional Zakharov-Kuznetsov(Zk) Equations Using Homotopy
Arcle Inernaonal Journal of Modern Mahemacal Scences, 4, (): - Inernaonal Journal of Modern Mahemacal Scences Journal homepage: www.modernscenfcpress.com/journals/jmms.aspx ISSN: 66-86X Florda, USA Approxmae
More information( t) Outline of program: BGC1: Survival and event history analysis Oslo, March-May Recapitulation. The additive regression model
BGC1: Survval and even hsory analyss Oslo, March-May 212 Monday May 7h and Tuesday May 8h The addve regresson model Ørnulf Borgan Deparmen of Mahemacs Unversy of Oslo Oulne of program: Recapulaon Counng
More informationTHE PREDICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS
THE PREICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS INTROUCTION The wo dmensonal paral dfferenal equaons of second order can be used for he smulaon of compeve envronmen n busness The arcle presens he
More informationTools for Analysis of Accelerated Life and Degradation Test Data
Acceleraed Sress Tesng and Relably Tools for Analyss of Acceleraed Lfe and Degradaon Tes Daa Presened by: Reuel Smh Unversy of Maryland College Park smhrc@umd.edu Sepember-5-6 Sepember 28-30 206, Pensacola
More information19 th INTERNATIONAL CONGRESS ON ACOUSTICS MADRID, 2-7 SEPTEMBER 2007
9 h INTERNATIONAL CONGRESS ON ACOUSTICS MADRID -7 SEPTEMBER 7 SOUND INSULATION CHARACTERISTICS OF A MICROPERFORATED PANEL ITH A SUBDIVIDED AIR LAYER PACS:.55.T Toyoda Masahro ; Daj Takahash B Kyoo Unv.
More informationLecture 18: The Laplace Transform (See Sections and 14.7 in Boas)
Lecure 8: The Lalace Transform (See Secons 88- and 47 n Boas) Recall ha our bg-cure goal s he analyss of he dfferenal equaon, ax bx cx F, where we emloy varous exansons for he drvng funcon F deendng on
More informationIncreasing the Probablility of Timely and Correct Message Delivery in Road Side Unit Based Vehicular Communcation
Halmsad Unversy For he Developmen of Organsaons Producs and Qualy of Lfe. Increasng he Probablly of Tmely and Correc Message Delvery n Road Sde Un Based Vehcular Communcaon Magnus Jonsson Krsna Kuner and
More informationMath 128b Project. Jude Yuen
Mah 8b Proec Jude Yuen . Inroducon Le { Z } be a sequence of observed ndependen vecor varables. If he elemens of Z have a on normal dsrbuon hen { Z } has a mean vecor Z and a varancecovarance marx z. Geomercally
More informationDensity Matrix Description of NMR BCMB/CHEM 8190
Densy Marx Descrpon of NMR BCMBCHEM 89 Operaors n Marx Noaon If we say wh one bass se, properes vary only because of changes n he coeffcens weghng each bass se funcon x = h< Ix > - hs s how we calculae
More informationBayes rule for a classification problem INF Discriminant functions for the normal density. Euclidean distance. Mahalanobis distance
INF 43 3.. Repeon Anne Solberg (anne@f.uo.no Bayes rule for a classfcaon problem Suppose we have J, =,...J classes. s he class label for a pxel, and x s he observed feaure vecor. We can use Bayes rule
More informationHighway Passenger Traffic Volume Prediction of Cubic Exponential Smoothing Model Based on Grey System Theory
Inernaonal Conference on on Sof Compung n Informaon Communcaon echnology (SCIC 04) Hghway Passenger raffc Volume Predcon of Cubc Exponenal Smoohng Model Based on Grey Sysem heory Wenwen Lu, Yong Qn, Honghu
More informationHEAT FLUX MEASUREMENT OF URBAN BOUNDARY LAYERS IN KYOTO CITY AND ITS PREDICTION BY CFD SIMULATION
EAT FLUX MEASUREMENT OF URBAN BOUNDARY LAYERS IN KYOTO CITY AND ITS PREDICTION BY CFD SIMULATION Kazuya Takahash 1, arunor Yoshda 2, Yuzo Tanaka 3, Norko Aoake 1 and Fuln Wang 1 Eghh Inernaonal IBPSA Conference
More informationBandlimited channel. Intersymbol interference (ISI) This non-ideal communication channel is also called dispersive channel
Inersymol nererence ISI ISI s a sgnal-dependen orm o nererence ha arses ecause o devaons n he requency response o a channel rom he deal channel. Example: Bandlmed channel Tme Doman Bandlmed channel Frequency
More informationTHEORETICAL AUTOCORRELATIONS. ) if often denoted by γ. Note that
THEORETICAL AUTOCORRELATIONS Cov( y, y ) E( y E( y))( y E( y)) ρ = = Var( y) E( y E( y)) =,, L ρ = and Cov( y, y ) s ofen denoed by whle Var( y ) f ofen denoed by γ. Noe ha γ = γ and ρ = ρ and because
More information2/20/2013. EE 101 Midterm 2 Review
//3 EE Mderm eew //3 Volage-mplfer Model The npu ressance s he equalen ressance see when lookng no he npu ermnals of he amplfer. o s he oupu ressance. I causes he oupu olage o decrease as he load ressance
More informationExtracting Duration Facts in Qualitative Simulation using Comparison Calculus
Exracng Duraon Facs n Qualave Smulaon usng Comparson Calculus Tolga Könk 1 and A. C. Cem Say 2 1: konk@umch.edu Compuer Scence and Engneerng ATL., Unv. Mchgan, 1101 Beal Ave., Ann Arbor, 48105-2106 MI,
More informationDensity Matrix Description of NMR BCMB/CHEM 8190
Densy Marx Descrpon of NMR BCMBCHEM 89 Operaors n Marx Noaon Alernae approach o second order specra: ask abou x magnezaon nsead of energes and ranson probables. If we say wh one bass se, properes vary
More informationAlgorithm Research on Moving Object Detection of Surveillance Video Sequence *
Opcs and Phooncs Journal 03 3 308-3 do:0.436/opj.03.3b07 Publshed Onlne June 03 (hp://www.scrp.org/journal/opj) Algorhm Research on Movng Objec Deecon of Survellance Vdeo Sequence * Kuhe Yang Zhmng Ca
More informationMechanics Physics 151
Mechancs Physcs 5 Lecure 9 Hamlonan Equaons of Moon (Chaper 8) Wha We Dd Las Tme Consruced Hamlonan formalsm H ( q, p, ) = q p L( q, q, ) H p = q H q = p H = L Equvalen o Lagrangan formalsm Smpler, bu
More informationMechanics Physics 151
Mechancs Physcs 5 Lecure 9 Hamlonan Equaons of Moon (Chaper 8) Wha We Dd Las Tme Consruced Hamlonan formalsm Hqp (,,) = qp Lqq (,,) H p = q H q = p H L = Equvalen o Lagrangan formalsm Smpler, bu wce as
More informationApplication of Gauge Sensitivity for Calculating Vehicle Body Natural Frequencies
Inernaonal Journal of Mechancs and Applcaons 013, 3(6): 139-144 DOI: 10.593/j.mechancs.0130306.01 Applcaon of Sensvy for Calculang Vehcle Body Naural Frequences Shengyong Zhang College of Engneerng and
More informationEVALUATION OF FORCE COEFFICIENTS FOR A 2-D ANGLE SECTION USING REALIZABLE k-ε TURBULENCE MODEL
The Sevenh Asa-Pacfc Conference on Wnd Engneerng, November 8-, 009, Tape, Tawan EVALUATION OF FORCE COEFFICIENTS FOR A -D ANGLE SECTION USING REALIZABLE k-ε TURBULENCE MODEL S. Chra Ganapah, P. Harkrshna,
More informationRobustness of DEWMA versus EWMA Control Charts to Non-Normal Processes
Journal of Modern Appled Sascal Mehods Volume Issue Arcle 8 5--3 Robusness of D versus Conrol Chars o Non- Processes Saad Saeed Alkahan Performance Measuremen Cener of Governmen Agences, Insue of Publc
More informationV R. Electronics and Microelectronics AE4B34EM. Electronics and Microelectronics AE4B34EM. Voltage. Basic concept. Voltage.
Elecroncs and Mcroelecroncs AEBEM. lecure basc elecronc crcu conceps ressors, capacors, nducors Elecroncs and Mcroelecroncs AEBEM Sudng maerals: server MOODLE hp://moodle.kme.fel.cvu.cz AEBEM Elecroncs
More informationSampling Procedure of the Sum of two Binary Markov Process Realizations
Samplng Procedure of he Sum of wo Bnary Markov Process Realzaons YURY GORITSKIY Dep. of Mahemacal Modelng of Moscow Power Insue (Techncal Unversy), Moscow, RUSSIA, E-mal: gorsky@yandex.ru VLADIMIR KAZAKOV
More information@FMI c Kyung Moon Sa Co.
Annals of Fuzzy Mahemacs and Informacs Volume 8, No. 2, (Augus 2014), pp. 245 257 ISSN: 2093 9310 (prn verson) ISSN: 2287 6235 (elecronc verson) hp://www.afm.or.kr @FMI c Kyung Moon Sa Co. hp://www.kyungmoon.com
More informationJ i-1 i. J i i+1. Numerical integration of the diffusion equation (I) Finite difference method. Spatial Discretization. Internal nodes.
umercal negraon of he dffuson equaon (I) Fne dfference mehod. Spaal screaon. Inernal nodes. R L V For hermal conducon le s dscree he spaal doman no small fne spans, =,,: Balance of parcles for an nernal
More informationMachine Learning Linear Regression
Machne Learnng Lnear Regresson Lesson 3 Lnear Regresson Bascs of Regresson Leas Squares esmaon Polynomal Regresson Bass funcons Regresson model Regularzed Regresson Sascal Regresson Mamum Lkelhood (ML)
More information. The geometric multiplicity is dim[ker( λi. number of linearly independent eigenvectors associated with this eigenvalue.
Lnear Algebra Lecure # Noes We connue wh he dscusson of egenvalues, egenvecors, and dagonalzably of marces We wan o know, n parcular wha condons wll assure ha a marx can be dagonalzed and wha he obsrucons
More informationRobust and Accurate Cancer Classification with Gene Expression Profiling
Robus and Accurae Cancer Classfcaon wh Gene Expresson Proflng (Compuaonal ysems Bology, 2005) Auhor: Hafeng L, Keshu Zhang, ao Jang Oulne Background LDA (lnear dscrmnan analyss) and small sample sze problem
More informationEcon107 Applied Econometrics Topic 5: Specification: Choosing Independent Variables (Studenmund, Chapter 6)
Econ7 Appled Economercs Topc 5: Specfcaon: Choosng Independen Varables (Sudenmund, Chaper 6 Specfcaon errors ha we wll deal wh: wrong ndependen varable; wrong funconal form. Ths lecure deals wh wrong ndependen
More informationOrdinary Differential Equations in Neuroscience with Matlab examples. Aim 1- Gain understanding of how to set up and solve ODE s
Ordnary Dfferenal Equaons n Neuroscence wh Malab eamples. Am - Gan undersandng of how o se up and solve ODE s Am Undersand how o se up an solve a smple eample of he Hebb rule n D Our goal a end of class
More information. The geometric multiplicity is dim[ker( λi. A )], i.e. the number of linearly independent eigenvectors associated with this eigenvalue.
Mah E-b Lecure #0 Noes We connue wh he dscusson of egenvalues, egenvecors, and dagonalzably of marces We wan o know, n parcular wha condons wll assure ha a marx can be dagonalzed and wha he obsrucons are
More informationA NEW TECHNIQUE FOR SOLVING THE 1-D BURGERS EQUATION
S19 A NEW TECHNIQUE FOR SOLVING THE 1-D BURGERS EQUATION by Xaojun YANG a,b, Yugu YANG a*, Carlo CATTANI c, and Mngzheng ZHU b a Sae Key Laboraory for Geomechancs and Deep Underground Engneerng, Chna Unversy
More informationOMXS30 Balance 20% Index Rules
OMX30 Balance 0% ndex Rules Verson as of 30 March 009 Copyrgh 008, The NADAQ OMX Group, nc. All rghs reserved. NADAQ OMX, The NADAQ ock Marke and NADAQ are regsered servce/rademarks of The NADAQ OMX Group,
More informationTrack Properities of Normal Chain
In. J. Conemp. Mah. Scences, Vol. 8, 213, no. 4, 163-171 HIKARI Ld, www.m-har.com rac Propes of Normal Chan L Chen School of Mahemacs and Sascs, Zhengzhou Normal Unversy Zhengzhou Cy, Hennan Provnce, 4544,
More information