Determination of the Noise Level Produced by Road Traffic

Similar documents
Chapter Lagrangian Interpolation

Solution in semi infinite diffusion couples (error function analysis)

V.Abramov - FURTHER ANALYSIS OF CONFIDENCE INTERVALS FOR LARGE CLIENT/SERVER COMPUTER NETWORKS

In the complete model, these slopes are ANALYSIS OF VARIANCE FOR THE COMPLETE TWO-WAY MODEL. (! i+1 -! i ) + [(!") i+1,q - [(!

5th International Conference on Advanced Design and Manufacturing Engineering (ICADME 2015)

HEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD

On One Analytic Method of. Constructing Program Controls

Variants of Pegasos. December 11, 2009

TSS = SST + SSE An orthogonal partition of the total SS

ELASTIC MODULUS ESTIMATION OF CHOPPED CARBON FIBER TAPE REINFORCED THERMOPLASTICS USING THE MONTE CARLO SIMULATION

[ ] 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

Robustness Experiments with Two Variance Components

Cubic Bezier Homotopy Function for Solving Exponential Equations

Mechanics Physics 151

Bernoulli process with 282 ky periodicity is detected in the R-N reversals of the earth s magnetic field

Numerical Simulation of the Dispersion of a Plume of Exhaust Gases from Diesel and Petrol Engine Vehicles

CH.3. COMPATIBILITY EQUATIONS. Continuum Mechanics Course (MMC) - ETSECCPB - UPC

Comprehensive Integrated Simulation and Optimization of LPP for EUV Lithography Devices

Volatility Interpolation

GENERATING CERTAIN QUINTIC IRREDUCIBLE POLYNOMIALS OVER FINITE FIELDS. Youngwoo Ahn and Kitae Kim

Linear Response Theory: The connection between QFT and experiments

Time-interval analysis of β decay. V. Horvat and J. C. Hardy

Chapters 2 Kinematics. Position, Distance, Displacement

THERMODYNAMICS 1. The First Law and Other Basic Concepts (part 2)

Existence and Uniqueness Results for Random Impulsive Integro-Differential Equation

II. Light is a Ray (Geometrical Optics)

Comparison of Differences between Power Means 1

FI 3103 Quantum Physics

New M-Estimator Objective Function. in Simultaneous Equations Model. (A Comparative Study)

UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 2017 EXAMINATION

RELATIONSHIP BETWEEN VOLATILITY AND TRADING VOLUME: THE CASE OF HSI STOCK RETURNS DATA

Dynamic Team Decision Theory. EECS 558 Project Shrutivandana Sharma and David Shuman December 10, 2005

M. Y. Adamu Mathematical Sciences Programme, AbubakarTafawaBalewa University, Bauchi, Nigeria

PHYS 1443 Section 001 Lecture #4

Comb Filters. Comb Filters

Multi-Fuel and Mixed-Mode IC Engine Combustion Simulation with a Detailed Chemistry Based Progress Variable Library Approach

This document is downloaded from DR-NTU, Nanyang Technological University Library, Singapore.

ACEI working paper series RETRANSFORMATION BIAS IN THE ADJACENT ART PRICE INDEX

Modeling and Solving of Multi-Product Inventory Lot-Sizing with Supplier Selection under Quantity Discounts

Response of MDOF systems

Chapter 6: AC Circuits

John Geweke a and Gianni Amisano b a Departments of Economics and Statistics, University of Iowa, USA b European Central Bank, Frankfurt, Germany

Anisotropic Behaviors and Its Application on Sheet Metal Stamping Processes

Advanced time-series analysis (University of Lund, Economic History Department)

Polymerization Technology Laboratory Course

NPTEL Project. Econometric Modelling. Module23: Granger Causality Test. Lecture35: Granger Causality Test. Vinod Gupta School of Management

2.1 Constitutive Theory

12d Model. Civil and Surveying Software. Drainage Analysis Module Detention/Retention Basins. Owen Thornton BE (Mech), 12d Model Programmer

Implementation of Quantized State Systems in MATLAB/Simulink

Notes on the stability of dynamic systems and the use of Eigen Values.

Capacities of Unsignalized Intersections Under Mixed Vehicular and Nonmotorized Traffic Conditions

DEEP UNFOLDING FOR MULTICHANNEL SOURCE SEPARATION SUPPLEMENTARY MATERIAL

CHAPTER 10: LINEAR DISCRIMINATION

Analysis And Evaluation of Econometric Time Series Models: Dynamic Transfer Function Approach

Journal of Theoretical and Applied Information Technology.

Tight results for Next Fit and Worst Fit with resource augmentation

e-journal Reliability: Theory& Applications No 2 (Vol.2) Vyacheslav Abramov

Online Supplement for Dynamic Multi-Technology. Production-Inventory Problem with Emissions Trading

( ) () we define the interaction representation by the unitary transformation () = ()

Sklar: Sections (4.4.2 is not covered).

Attribute Reduction Algorithm Based on Discernibility Matrix with Algebraic Method GAO Jing1,a, Ma Hui1, Han Zhidong2,b

[Link to MIT-Lab 6P.1 goes here.] After completing the lab, fill in the following blanks: Numerical. Simulation s Calculations

Dual Approximate Dynamic Programming for Large Scale Hydro Valleys

Motion in Two Dimensions

Approximate Analytic Solution of (2+1) - Dimensional Zakharov-Kuznetsov(Zk) Equations Using Homotopy

( t) Outline of program: BGC1: Survival and event history analysis Oslo, March-May Recapitulation. The additive regression model

THE PREDICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS

Tools for Analysis of Accelerated Life and Degradation Test Data

19 th INTERNATIONAL CONGRESS ON ACOUSTICS MADRID, 2-7 SEPTEMBER 2007

Lecture 18: The Laplace Transform (See Sections and 14.7 in Boas)

Increasing the Probablility of Timely and Correct Message Delivery in Road Side Unit Based Vehicular Communcation

Math 128b Project. Jude Yuen

Density Matrix Description of NMR BCMB/CHEM 8190

Bayes rule for a classification problem INF Discriminant functions for the normal density. Euclidean distance. Mahalanobis distance

Highway Passenger Traffic Volume Prediction of Cubic Exponential Smoothing Model Based on Grey System Theory

HEAT FLUX MEASUREMENT OF URBAN BOUNDARY LAYERS IN KYOTO CITY AND ITS PREDICTION BY CFD SIMULATION

Bandlimited channel. Intersymbol interference (ISI) This non-ideal communication channel is also called dispersive channel

THEORETICAL AUTOCORRELATIONS. ) if often denoted by γ. Note that

2/20/2013. EE 101 Midterm 2 Review

Extracting Duration Facts in Qualitative Simulation using Comparison Calculus

Density Matrix Description of NMR BCMB/CHEM 8190

Algorithm Research on Moving Object Detection of Surveillance Video Sequence *

Mechanics Physics 151

Mechanics Physics 151

Application of Gauge Sensitivity for Calculating Vehicle Body Natural Frequencies

EVALUATION OF FORCE COEFFICIENTS FOR A 2-D ANGLE SECTION USING REALIZABLE k-ε TURBULENCE MODEL

Robustness of DEWMA versus EWMA Control Charts to Non-Normal Processes

V R. Electronics and Microelectronics AE4B34EM. Electronics and Microelectronics AE4B34EM. Voltage. Basic concept. Voltage.

Sampling Procedure of the Sum of two Binary Markov Process Realizations

@FMI c Kyung Moon Sa Co.

J i-1 i. J i i+1. Numerical integration of the diffusion equation (I) Finite difference method. Spatial Discretization. Internal nodes.

Machine Learning Linear Regression

. The geometric multiplicity is dim[ker( λi. number of linearly independent eigenvectors associated with this eigenvalue.

Robust and Accurate Cancer Classification with Gene Expression Profiling

Econ107 Applied Econometrics Topic 5: Specification: Choosing Independent Variables (Studenmund, Chapter 6)

Ordinary Differential Equations in Neuroscience with Matlab examples. Aim 1- Gain understanding of how to set up and solve ODE s

. The geometric multiplicity is dim[ker( λi. A )], i.e. the number of linearly independent eigenvectors associated with this eigenvalue.

A NEW TECHNIQUE FOR SOLVING THE 1-D BURGERS EQUATION

OMXS30 Balance 20% Index Rules

Track Properities of Normal Chain

Transcription:

Deermnaon of he Nose evel Produced by Road Traffc lna Mhaela RĂDO Unversy POTHNC of Buchares, Splaul ndependene 33, Romana, e-mal:ralna_upb@yahoo.com Ncolae NSCU Deparmen of Mechancs, Unversy POTHNC of Buchares, Splaul ndependene 33, Romana, e-mal:enescuncolae875@yahoo.com oan MGHȚ Deparmen of Mechancs, Unversy POTHNC of Buchares, Splaul ndependene 33, Romana, e-mal:oan_maghe@yahoo.com 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 2/206 63 SSN 584-7284

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 62.88 6.47 57.7 Pon 2 64.24 63.49 58.62 Pon 3 63.92 62.4 58. 33 Pon 4 63.02 6.24 58.2 Pon 5 73.78 72.0 67.32 No Day venng Ngh gh veh/h 3720 2040 740 Heavy veh/h 62 98 34 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 07.00-9.00 hours eq evenng: venng equvalen level: - weghed, equvalen connuous sound pressure level, measured over he 4-hour perod 9.00-23.00 hours eq ngh: Ngh equvalen level: -weghed, equvalen connuous sound pressure level, measured over he 8- hour perod 23.00-07.00 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 0 0 0 d d d d d 0 d d 0 0 5 D 2 d 0 db 0 0 5 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 2/206 64 SSN 584-7284

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 40 0 0.90.75lg 0 3 0 2 0 4 2 0 4 0 3 70 5 0.03 0.03 0 3 3 70 4 0 70 0 70 5 0.03 0.03 ( cars)= 67.67 db(); ( rams) = 77.68 db(); 82.68 db() ( buses)= 82.68 db() ( moorcycles)= ( mnbuses)= 72.68 db(); db() ex. 2 60 ( rucs)= 87.68 67,67 72,68 0 0 0lg 3400, 20 290, 20 77,68 82,68 87,68 82,68 0 0 0 0 3020 20,80 82,20 60,80 ex. 74.48 db() ; ex. 7.74 db() evenng; ex. 68.7 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 2/206 65 SSN 584-7284

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)= -0.79 () B D =0 lg(60/240)= - 6,02 (evenng); D =0 lg(60/480)= - 9.03 (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 0.002 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 = 0 0 0 0 lg 0 0 0 = 78.5dB; 82,68 87,68 82,68 P = 0 0 0 0 lg 0 0 0 =89.2dB w, = 87.4 db (); w, = 83.45 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 2/206 66 SSN 584-7284

Table 2: Dfferences of.2-2.4 db beween values of he nose n he wo cases No. Pon eve nng ngh eve nng ngh 67.9 65.6 6.4 66.7 63.3 6.7 Pon2 70 67.6 63.4 68.7 65.3 63.7 Pon3 69.7 67.4 63. 68.5 65 63.4 Fgure 6. Nose level (evenng) Pon4 69.5 67. 62.9 68.2 64.8 63. Pon5 76.8 74.3 69.9 75.5 72 70.2 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.234-240. [5] M.J Crocer, Handboo of Nose and Vbraon Conrol, 2007, pp.455-465. [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, 2004. RJV vol X ssue 2/206 67 SSN 584-7284