EVALUATION OF WIND HAZARD OVER JEJU ISLAND

Transcription

1 The Seventh Asia-Pacific Conference on Wind Engineering, November 8-12, 2009, Taipei, Taiwan EVALUATION OF WIND HAZARD OVER JEJU ISLAND Young-Kyu Lee 1, Sungsu Lee 2 and Hak-Sun Kim 3 1 Ph.D Candidate, Structural Systems & CAE, Chungbuk National University 410 Seongbong-ro, Heungduk-gu, Cheongju, Republic of Korea, youngkyulee@cbnu.ac.kr 2 Professor, Schoool of Civil Engineering, Chungbuk National University 410 Seongbong-ro, Heungduk-gu, Cheongju, Republic of Korea, joshua@cbnu.ac.kr 3 Ph.D Candidate, Structural Systems & CAE, Chungbuk National University 410 Seongbong-ro, Heungduk-gu, Cheongju, Republic of Korea, haksun@cbnu.ac.kr ABSTRACT In the study the evaluation of wind hazard overall Jeju island, South Korea, is performed with a technique of the typhoon Monte Carlo simulation. Especially, the surface roughness model and the topographical effect model are used to consider the regional wind characteristics. The surface roughness model is developed by using the land cover map and the topographical effect model, the DEM (digital elevation model) and Korean Building Code- Structural. KEYWORDS: WIND HAZARD, SURFACE ROUGHNESS MODEL, TOPOGRAPHICAL EFFECT MODEL 1. Introduction Jeju island, South Korea, is located at the south point and experiences typhoons almost every year. A statistical extreme value analysis is not proper to estimate return period winds for the typhoon-prone regions such as Jeju. In these areas the typhoon Monte Carlo simulation is an alternative to the wind hazard assessment (Simiu and Scanlan, 1996). Surface roughness takes a roll to retard a wind speed near surface and determines the vertical wind profile in the boundary layer. In a channel flow a flow accelerates when the cross-section reduces. Similarly in the atmospheric boundary layer winds have a speed-up effect when a flow comes along with topology such as hills, ridges, or escarpments. In the study we develop a surface roughness model and a topographical effect model to represent these effects prescribed previously and evaluates the wind hazard with regional wind characteristics. Bietry et al. (1978) investigates roughness lengths for suburbs and centers of cities. Oliver (1971) examines the wind profiles for a forest canopy. These results are used to make the surface roughness model. Korean Building Code-Structural specifies the topographic effects by hills, ridges, and escarpments. The code and a DEM are applied to the topographical effect model. The use of mathematical simulation methods to estimate hurricane wind speeds was first implemented by Russell (1971, 1974) for the Texas coast. Others have used this approach to estimate extreme winds or to evaluate effects induced by tropical cyclones (Batts et al., 1980; Vickery and Twisdale, 1995a, 1995b). In chapter 2 the homogeneous wind-map model is explained, which is based on a typhoon Monte Carlo simulation. The surface roughness and the topographic effect models are introduced in chapter 3 and 4 respectively. Chapter 5 shows the wind hazard map for Jeju.

2 2. Homogeneous Wind-map Model A homogeneous wind-map model (HWM) is developed by the typhoon Monte Carlo simulation. The HWM is defined as a wind-map of the 100-year return period 10-minute averaged wind speed at 10m above ground on the homogeneous surface condition with no topographic features, on which a roughness length, z 0, equals to 0.07m. The climatological characteristics of the typhoons are estimated from the RSMC (Regional Specialized Meteorological Center) best tracks from 1951 to The typhoon Monte Carlo simulation is performed at Jeju, Seongsan, Seoguipo, and Gosan having meteorological stations. The sampled typhoons having approached within 250km into the sites are used to estimate the distributions of an annual occurrence rates, the central pressure depths (depict between peripheral and central pressures), the translation speeds, the nearest distances, and the headings. The radius of maximum winds is assumed to be correlated with the central pressure depth by Fujii s equation (1998). Table 1 shows the distributions of the climatological characteristics to the typhoons. Table 1: Climatological characteristics of the typhoons hitting Jeju Central pressure depths ( p Δ ) Nearest distances ( d min ) Translation speeds ( s ) Headings (θ ) Radii of max. winds ( R max ) Occurrence rate Weibull distribution b Δp Y = F( Δp a, b) = 1 exp, min( ΔPi ) Δp max( ΔPi ) a Uniform distribution Y = F( dmin a, b) = ( dmin a) /( b a), b > a Gamma distribution 1 s (, ) b 1 t Y = F s a b = t exp dt, min( Si) s max( Si) a b Γ( a) 0 b Extreme value distribution θ μ Y = F( θ μ, σ ) = 1 exp exp, min( Θi) θ max( Θi) σ Fujii s experimental formula (Fujii, 1998) R = 66.19logΔp (km) max + Poisson process The SPH (Standard Project Hurricane, 1972) wind field model and the Fujii s filling rate describing for central pressures to increase on the land are adopted into the typhoon Monte Carlo simulation. The typhoons are assumed to move with a constant speed and heading. 5,000 of typhoons are generated by the typhoon Monte Carlo simulation. The 100- year return period 10-min wind speeds on the homogeneous surface having 0.07m of the roughness length, z 0 are estimated to 27.0m/s, 27.7m/s, 27.9m/s and 27.5m/s at Jeju, Gosan, Seongsan, and Seoguipo respectively. The HWM overall Jeju island is developed by a inverse distance interpolation with the speeds of 4 sites (see Figure 1).

3 Figure 1: Homogeneous wind-map model for Jeju island. 3. Surface Roughness Model Surface roughness elements retard wind speeds and determine the vertical wind profile. Since surface roughness surroundings are not homogeneous all directions upwind, the surface roughness model should have directionality. The 8-directional SRM (Surface Roughness Model) is developed to consider the effects of the upwind surface roughness by manipulating the land cover map (LCM). The LCM categories are weighted to generate the SRM. The used LCM has 8 of categories such as water, built-up region, bare ground, swampy land, grassland, forest, rice field, and dry field. Each category has the weighting values shown in Table 2. Table 2: Weighting values for LCM categories LCM categories Weighting values Water 0 Built-up region 15 Bare ground 0.5 Swampy land 2 Grassland 1 Forest 15 Rice field 1 Dry field 1 In the study to estimate wind hazards 10m above ground we calculate an arithmetic mean over 1/8 circle fetch with 1000m upwind, which Korean Building Code-Structural recommends corresponding to 100 times of height. The arithmetic mean and the conditions on Table 3 generate the 8-directional SRMs which have 3 of surface roughness categories such

4 as 0.3m, 0.07m, and 0.005m of roughness lengths (Z0). Bietry et al. (1978) presents 20~40cm of roughness length for sparsely built-up suburbs. The zones on which the built-up region and the forest occupy over half are judged as 0.3m roughness length and correspond to over 8.5 of arithmetic mean. Oliver (1971) suggests 4~10cm of roughness length for high grass. We judge the zones on which the arithmetic mean exists between 1 and 8.5 as 0.07m of roughness length. The other zones are assigned to 0.005m of roughness length. Figure 2 shows the SRM for north upwind overall Jeju island. North coast has short roughness length while south has tall roughness length. The central region almost consists of forest so that 0.3m of roughness length is assigned. Table 3: Surface roughness categories corresponding to arithmetic mean Category conditions Surface roughness categories Arithmetic mean >= 8.5 Z0 = 0.3m 1 <= Arithmetic mean < 8.5 Z0 = 0.07m Arithmetic mean < 1.0 Z0 = 0.005m Figure 2: Surface roughness model for north upwind 4. Topographical Effect Model As shown in Figure 3, the wind speed accelerates when the winds flow along with topographic features such as hills or ridges. The TEM (Topographical Effect Model) is developed to represent the speed-up effects induced by topology. The TEM is developed for 8-direction to consider none-homogeneous topology to the fetch upwind. The 30m-resolution DEM and Korean Building Code-Structural are used in the process of the development. Bringing the elevation profile corresponding to the upwind direction from the DEM, we find

5 the parameters which substitute to Table 4 to calculate the topographic factor defined in Korean Building Code-Structural. In Table 4 the slope, φ is defined as φ = H /( 2Lh ) (1) where H is a height of hill or escarpment relative to the upwind terrain, Lh, a distance upwind of crest to where the difference in ground elevation is half the height of hill or escarpment. In Table 4 the values of topographic factor are given for some slopes, φ. For other than those shown, linear interpolation is permitted. Figure 4 shows the TEM for north upwind overall Jeju island. Jeju has many small hills called Oreum where the speed-up induced by topology exists. Halla mountain is located at the center, of which top has 1,950m of height, experiencing the speed-up. Table 4: Topographic factor for slopes φ Topographic factor = = = Figure 3: Speed-up description on hill, ridge, and escarpment.

6 Figure 4: Topographical effect model for north upwind. 5. Evaluation of Wind Hazard over Jeju island Figure 5 illustrates the process for wind hazard map generation. The SRM, TEM, and HWM are assumed to be independent. It makes 8 combination wind maps by raster-based upwind-wise operation. The wind hazard map (WHM) is a set of maximums among all combinations at each raster. The process of wind conversion into the other surface roughness categories uses the similarity model for the log-law profile (Simiu and Scanlan, 1996). Figure 6 shows the wind hazard map based on 100-year return period 10-min wind speed without considering wind directions. As shown in Figure 6 coast SRM TEM HWM Raster-based upwind-wise combination operation Wind Hazard Map =Set of maximums among all combinations at each raster Figure 5: Process of wind hazard map generation.

7 Figure 6 Wind hazard map for Jeju island. 6. Conclusions We performed the evaluation of wind hazard considering the local wind characteristics for Jeju island. The HWM developed by the typhoon Monte Carlo simulation, the SRM describing the surface roughness effect, and the TEM representing the speed-up effects are used in the process. According to the result it estimates the coastal areas to be more vulnerable and shows that urban and forest region is safe relatively. Acknowledgment This work was supported by the grant from Natural Hazard Mitigation Research Group funded by National Emergency Management Agency, South Korea. References Simiu, E and Scanlan, R. H. (1996), Wind Effects on Structures, 3 rd Edition, John Wiley & Sons, New York, NY, USA. Revised Standard Project Hurricane Criteria for the Atlantic and Gulf Coasts of the United States, Memorandum HUR7-120, U.S. Dept. of Commerce, NOAA, June Fujii, T. (1998), Statistical Analysis of the Characteristics of Severe Typhoons Hitting the Japanese Main Islands, Monthly Weather Review, Vol. 126, pp Bietry, J., Sacre, C., and Simiu, E. (1978), Mean Wind Profiles and Changes of Terrain Roughness, Journal of Structural Division, ASCE, Vol. 104, pp Oliver, H.R. (1971), Wind Profiles in and above a Forest Canopy, The Quaterly Journal of the Royal Meteorological Society, Vol. 97, pp Architectural Institute of Korea (2005), Korean Building Code-Structual, AIK, Seoul, South Korea

8 Russell, L.R. (1971), Probability Distributions for Texas Gulf Hurricane Effects, Journal of Waterways, Harbors, and Coastal Engineering Division, Proceedings of the American Society of Civil Engineers, No. 1, pp Russell, L.R., and Schueller, G.F. (1974), Probabilistic Models for Texas Gulf Coast Hurricane Occurrences, Journal Petroleum Technology, pp Batts, M.E., Cordes, M.R., Russell, C.R. and Simiu, E. (1980), Hurricane Wind Speeds in the United States, Naional Bureau of Standards Report Number BSS-124, U.S. Dept. of Commerce, Washington, DC. USA. Vickery, P.J. and Twisdale, L.A. (1995a), Wind-Field and Filling Models for Hurricane Wind-speed Predictions, Journal of Structural Engineering, Vol. 121, No. 11, pp Vickery, P.J. and Twisdale, L.A. (1995b), Prediction of Hurricane Wind Speeds in the United States, Journal of Structural Engineering, Vol. 121, No. 11, pp