Disaster Mitigatio of Debris Flows, Slope Failures ad Ladslides 591 A Study for Moitorig System of Tuel Portal Slopes at Hati Tuel i Korea O-Il Kwo, 1) Yog Bae, 2) Ki-Tae Chag 3) ad Hee-Soo 4) 1) Geotechical Egieerig Research Departmet., Korea Istitute of Costructio Techology, 2311 Daehwa-Dog, Ilsa-Gu, Goyag-Si, Gyeoggi-Do 411-712, Republic of Korea (wooil@ict.re.r) 2) Geotechical Egieerig Research Departmet., Korea Istitute of Costructio Techology, 2311 Daehwa- Dog, Ilsa-Gu, Goyag-Si, Gyeoggi-Do 411-712, Republic of Korea (bae44@ict.re.r) 3) Departmet of Civil Egieerig, Kumoh Natioal Uiversity of Techology, 1 Yagho-Dog, Gumi-Si, Kyogsagbu-Do 730-701, Republic of Korea (tchag@umoh.ac.r) 4) Departmet of Civil Egieerig, Kumoh Natioal Uiversity of Techology, 1 Yagho-Dog, Gumi-Si, Kyogsagbu-Do 730-701, Republic of Korea (hahs@umoh.ac.r) Abstract This research is coducted to develop the qualified data aalysis system for predictig the behavior ad failure of slope. The sesor system istalled i target slopes ca measure the tesio, rotatio ad settlemet (TRS system), ad data measured by TRS system is trasmitted to cotrol ceter by CDMA commuicatio. I additio, x R maagemet method is used to aalyze the acquired data. I this paper, it is discussed whether the x R maagemet system is useful to aalyze the slope behavior or ot. maagemet system applied herei is to describe the slope behavior ad to mae a warig system by average ( x) ad stadard deviatio (R). Keywords: moitorig, tuel portal slope, TRS system, CDMA, maagemet Itroductio Because Korea is cosisted of steep moutai district over tha 70%, slope stability is the severe civil egieerig wor which could ot be avoided. Also research for slope maiteace is achieved to various ways worldwide; however util ow settig up the real-time moitorig for it is ot prepared eough. It is impossible actually to prevet ladslide before, because it happes usually whe localized dowpour drops, also ordiary sesor could ot detect the ome pheomea of ladslide. As well as, perfect graspig of soil coditio of slope is impossible actually because of uhomogeeity of it. Therefore, beside regular checig of slope ad costructio of safety diagosis system eed, real-time moitorig system should be eeded to cope with the outbrea situatio ad to grasp slope behavior always. Sesor System The sesor system istalled i target slopes ca measure the tesio, rotatio ad settlemet (TRS system), ad measured data measured is trasmitted to cotrol ceter by CDMA commuicatio. Measured data is chaged ito database real time ad it is composed to cotrol the data worldwide by iteret. Specially, warig message is ow through speaer if some symptom of ladslide is detected i office, ad recordig ca be trasmitted to egieer s cellular phoe by real time. Fig. 1 is actual images of sesor established soil sectio i slope i tuel pithead respectively. Target slope is located i Pohag city Kyogsag provice Korea, it is over 2 laes roadway ad maximum height is about 25 m, right side is soil sectio ad left side is roc sectio respectively, it is a slope i Hati tuel pithead of atioal road 31. Measure sectio fell ito greatly 3 sectios, ad first sectio is SE-1, it is cosisted of base roc sectio, ad plaed for cave-i perceptio. Secod sectio is SE-2 ad third sectio is SE-3, they are cosisted of soil sectios, ad plaed for behavior of soil slopes. Sesors istalled ca ow the legth chage ad horizotal ad vertical agles, they are established i 10 places all o 3 sectios (Fig. 2). pp. 591 595 c 2006 by Uiversal Academy Press, Ic. / Toyo, Japa
592 Fig. 1. Sesor i soil sectio Fig. 2. Istallatio of sesors Data Aalysis x cotrol chart It is supposed that the data from slope show ormal distributio because the slope would be measured cotiuously ad it will mae a lot of data, ad the average (µ) ad stadard deviatio (σ) of it is already ow. If x1, x2,..., x is idividual values from slope data whose specime size is, the data are tae by the slope(populatio). Average of this specime of ormally distributed data is as follows. P xi x1 + x2 + + x x = i=1 = (1) It is ow by cetral limit theorem that x is ormally distributed by average µ ad stadard deviatio σ. Also Equatio (2) is approved. Therefore, the data locatio probability of specime averages should be 1 α. P (Lower Cotrol Limit x U pper Cotrol Limit) = P (µ Z α2 αx x µ + Z α2 αx ) = 1 α 1 α (2) If the average(µ) ad stadard deviatio(σ) of measured slope data are ow, equatios (3-a) ad (3-b) could be used as upper cotrol limit ad lower cotrol limit. α LCL = µ Z α2 αx = µ Z α2 (3-a) α LCL = µ + Z α2 αx = µ + Z α2 (3-b)
Furthermore, if 3σ limit is applied to the cotrol chart, 3 is used to cotrol limits istead of Z α/2. If x is located upper positio of upper cotrol limit(ucl) or lower cotrol limit(lcl), it is said that slope maiteace is icapability state ad should give a warig sig because specime average( x) is ot equal to populatio average(µ). By the way, average(µ) ad stadard deviatio(σ) of measured slope data could ot be ow before sesor istallig actually. Therefore, their values ca ot but predict drawig the specime i stable slope. If x 1 + x 2 + + x is said as sum of averages of each specime, the expeditio value ( x) of measured average data is as follows. i=1 x = x i = x 1 + x 2 + x (4) x is used as ceter-lie of cotrol chart, i.e., Ceter Lie = x To mae a cotrol limit, the expeditio value of stadard deviatio(σ) is eeded. To do that, specime stadard deviatio(s) could be used, or simply the rage of each specime group could be used. If idividual observatio data are composed of x 1, x 2,, x which size is, the sample rage (R) is as follows. 593 R = x max x mi (5) Importat relatioship is oted betwee sample rage (R) ad stadard deviatio(σ) of ormal distributio. It is expressed as probability variable, W = R/σ, it is called relative rage. Distributio of W is depedet of sample size () of ormal distributio. The average (expeditio value)of W is d 2, which is determied accordig to sample size. From W = R/σ, σ = R/W,, Equatio (6) is acquired. E(σ) = σ = E ( R W By the way, expeditio value of R is E(R) = R i=1 = R i The expeditio value ( σ) of stadard deviatio (σ) is ) = E(R) E(W ) = E(R) d 2 (6) (7) σ = R d 2 (8) If x is used as the expeditio value of average (µ), R/d 2 is used as the expeditio value of stadard deviatio (σ), average (µ), also if Z α/2 is applied as 3. The parameters of x cotrol charter are as follows. If A 2 is expressed as UCR = x + 3 R/d 2 CL = x LCL = x 3 R/d 2 (9) A 2 = 3/d 2 = 3 d 2 (10) Equatio (9) is rearraged as equatio (11) to decide the upper ad lower limits ad ceter lie. UCL = x + A 2 R CL = x Costat A 2 is determied by sample size. LCL = x A 2 R (11) Applicatio of system Table 1 shows the average ad stadard deviatio util last poit of time by real time trasmissio. Table 2 shows the upper limit, lower limit ad ceter value by average cotrol chart ad stadard deviatio cotrol chart aalysis techiques of real-time moitorig program. Fig. 3 is the average cotrol chart; all data are located withi cotrol limits. It could be cocluded that there is ot importat tedecy of slope behavior. Accordig to Fig. 4, stadard deviatios cotrol values are show as upper limit 1.079mm, ceter 0.629mm, low limit 0.178mm, util preset, there is o sesor that escape maiteace limits.
594 Table 1. Average ad stadard deviatio of each sesor Table 2. Cotrol limits of x R Maagemet System Fig. 3. Average cotrol chart Coclusios 1) This research is coducted to develop the qualified data aalysis system for predictig the behavior ad failure of slope. I additio, x R maagemet method is used to aalyze the acquired data. 2) Sesors istalled ca ow the legth chage ad horizotal ad vertical agles, they are established i 10 places all o 3 sectios. 3) To do aalysis of slope stability statistically, average ad stadard deviatio of measured data from istalled sesors should be used as two parameters to fix the upper ad lower limits of cotrol chart. 4) All data of average are located withi cotrol limits. It could be cocluded that there is ot importat tedecy of slope behavior. 5) Accordig to stadard deviatio cotrol chart, the data of sesor No. 2, sesor No. 3, sesor No. 4 ad
595 Fig. 4. Stadard deviatios cotrol chart sesor No. 9 were closig to the lower cotrol limit, however, util ow, all data are located withi cotrol limits. Refereces Ha H., Chag K., Predictig the failure of slope by mathematical model, joural of Korea geotechical society, Vol. 21, No. 2, March, 2005. Chag K., Ha H., Yoo B., Aalysis of slope behavior usig FBG sesor ad icliometer, joural of Korea geotechical society, Vol. 19, No. 6, Dec., 2003. Chag K., Ha H., Yoo B., Estimatio of slope behavior by soil temperature, joural of Korea geotechical society, Vol. 19, No. 6, Dec., 2003.