基于短期风速资料的基本风压计算方法

doi:10.13229/j.cnki.jdxbgxb20190628

Abstract

Abstract:

Due to the lack of long-term wind speed data in some regions, the basic wind pressure can not be calculated according to the Building Structure Load Code. It is urgent to get a basic wind pressure for the design of bridges and other engineering structures according to the short-term wind speed data. In this paper, the short-term wind speed data of 54 representative cities in China in 2013~2017 are selected, respectively. The extreme value I-type distribution function is used to fit the parameter estimation with the monthly maximum wind speed data. The moment estimation method and Gumbel method are used to calculate the parameters, which are examined examined using the Kolmogorov-Smirnov test method. The results show that the monthly maximum wind speed data in 54 cities are in line with the extreme value type I distribution. When fitting the monthly maximum wind speed data with the extreme value type I distribution, the Gumbel method has a better fitting effect than the moment estimation method. Therefore, it is feasible to use the maximum monthly wind speed data to fit the extreme value I-type distribution to calculate the basic wind pressure in regions lacking long-term wind speed data. Based on this method, the basic wind pressure was calculated for a recurrence period of 6 months, 50 years and 100 years. The basic wind pressure with a return period of 6 months can provide reference for projects with short design life, such as demolition works. The basic wind pressure with a return period of 50 and 100 years can provide a reference for bridge structural design in areas without long-term wind speed data. Taking Fuyang city as an example, this paper provides an example for the basic wind pressure calculation which lacks long-term wind speed data. The basic wind pressure of lacking the long-term wind speed data and short recurrence period can be calculated.

Key words: civil engineering, basic wind pressure value, short-term wind speed, extreme value type I distribution, Gumbel method, Kolmogorov-Smirnov test

CLC Number:

TU312

Bo WANG,Yuan-zheng DONG,Li-xin DONG. Calculation of basic wind pressure based on short⁃term wind speed data[J].Journal of Jilin University(Engineering and Technology Edition), 2020, 50(5): 1739-1746.

Figures/Tables 4

Table 1

Result of fitting distribution of extreme value type I with monthly maximum wind speed data"

城市	估计方法	$a$	$u$	$σ$	$V$ /%	$K f$	城市	估计方法	$a$	$u$	$σ$	$V$ /%	$K f$
齐齐哈尔	矩估计法	2.2533	12.9000	0.4685	2.91	0.0672	郑州	矩估计法	1.6625	12.5700	0.3682	2.17	0.1205
齐齐哈尔	Gumbel法	2.4091	12.8720	0.4656	3.07	0.0799	郑州	Gumbel法	1.8702	12.5490	0.3683	2.19	0.1208
哈尔滨	矩估计法	2.6392	11.2290	0.5591	3.00	0.0473	许昌	矩估计法	1.3087	14.1440	0.4566	2.26	0.1079
哈尔滨	Gumbel法	3.0960	11.1090	0.5612	3.57	0.0534	许昌	Gumbel法	1.4370	14.1190	0.4587	2.33	0.1037
乌鲁木齐	矩估计法	2.2543	14.6720	0.7016	4.38	0.1223	汉中	矩估计法	1.4543	10.4993	0.2745	2.06	0.1002
乌鲁木齐	Gumbel法	2.4667	14.6280	0.6954	4.32	0.1198	汉中	Gumbel法	1.5704	10.4839	0.2705	2.17	0.1063
喀什	矩估计法	2.6048	13.6160	0.9127	5.73	0.0882	重庆	矩估计法	1.3953	13.4330	0.3129	1.75	0.0725
喀什	Gumbel法	2.7078	13.5390	0.8637	4.62	0.0673	重庆	Gumbel法	1.4957	13.4120	0.3063	1.90	0.0861
酒泉	矩估计法	2.4832	13.1330	0.5536	2.76	0.0852	宜昌	矩估计法	1.3732	10.7430	0.3042	1.93	0.0850
酒泉	Gumbel法	2.6164	13.0920	0.5362	2.63	0.0682	宜昌	Gumbel法	1.4910	10.7140	0.2794	1.52	0.0751
西宁	矩估计法	1.8583	10.7899	0.4997	3.46	0.1341	武汉	矩估计法	1.4658	12.8050	0.3003	1.90	0.0771
西宁	Gumbel法	1.9968	10.7683	0.5086	3.68	0.1361	武汉	Gumbel法	1.5581	12.7850	0.2942	1.86	0.0795
包头	矩估计法	2.0802	15.4770	0.6470	3.30	0.1161	长沙	矩估计法	1.5291	12.4430	0.2820	1.72	0.1143
包头	Gumbel法	2.2178	15.4430	0.6517	3.10	0.1053	长沙	Gumbel法	1.6600	12.4110	0.2419	1.48	0.0978
呼和浩特	矩估计法	1.6995	18.9800	0.4150	1.30	0.0705	毕节	矩估计法	1.1986	11.2819	0.2083	1.38	0.0905
呼和浩特	Gumbel法	1.8454	18.9440	0.3908	1.48	0.0838	毕节	Gumbel法	1.2129	11.2649	0.1985	1.55	0.1085
大同	矩估计法	1.5944	16.7970	0.4560	1.97	0.0877	岳阳	矩估计法	1.6540	12.9540	0.3315	1.82	0.0980
大同	Gumbel法	1.7310	16.7640	0.4422	2.16	0.0907	岳阳	Gumbel法	1.7740	12.9340	0.3293	2.01	0.1043
银川	矩估计法	2.5342	12.0840	0.5612	3.88	0.1460	赣州	矩估计法	1.0108	11.111	0.2833	1.54	0.0580
银川	Gumbel法	2.9851	12.0580	0.5693	3.86	0.1416	赣州	Gumbel法	1.0975	11.089	0.2739	1.57	0.0688
石家庄	矩估计法	1.7934	13.2980	0.4467	2.86	0.1069	贵阳	矩估计法	1.0274	11.9670	0.2504	1.17	0.0693
石家庄	Gumbel法	1.9470	13.2600	0.4224	2.35	0.0956	贵阳	Gumbel法	1.1156	11.9450	0.2357	1.36	0.0883
太原	矩估计法	1.3137	15.1280	0.4326	1.67	0.0823	桂林	矩估计法	1.1837	12.0840	0.2588	1.48	0.0765
太原	Gumbel法	1.4263	15.1010	0.4274	1.64	0.0749	桂林	Gumbel法	1.2294	12.0690	0.2589	1.51	0.0893
西安	矩估计法	1.7030	13.0130	0.5662	2.90	0.0765	常州	矩估计法	1.3151	14.1730	0.2173	1.01	0.0703
西安	Gumbel法	1.8488	12.9770	0.5600	2.86	0.0747	常州	Gumbel法	1.4108	14.1550	0.2060	0.92	0.0591
长春	矩估计法	2.3218	14.6720	0.4113	2.49	0.0813	蚌埠	矩估计法	1.0183	15.2400	0.3662	1.31	0.0642
长春	Gumbel法	2.6810	14.6430	0.4018	2.23	0.0658	蚌埠	Gumbel法	1.1056	15.2190	0.3651	1.31	0.0704
延吉	矩估计法	2.1057	15.4690	0.7419	4.09	0.1304	南京	矩估计法	1.1086	15.8010	0.2689	0.99	0.0476
延吉	Gumbel法	2.2862	15.4240	0.7381	3.77	0.1187	南京	Gumbel法	1.2071	15.7780	0.2546	1.01	0.0428
沈阳	矩估计法	2.1983	12.3350	0.3793	2.20	0.0585	合肥	矩估计法	1.2416	14.3880	0.4575	1.52	0.0880
沈阳	Gumbel法	2.5297	12.3070	0.3679	2.20	0.0636	合肥	Gumbel法	1.3714	14.3670	0.4632	1.93	0.1030
张家口	矩估计法	1.5898	17.0010	0.6016	2.35	0.1197	上海	矩估计法	2.3294	15.2240	0.2929	1.18	0.0654
张家口	Gumbel法	1.8399	16.9760	0.6129	2.39	0.1134	上海	Gumbel法	2.3861	15.2080	0.2933	1.16	0.0838
大连	矩估计法	2.3288	16.3020	0.6214	3.45	0.1352	杭州	矩估计法	1.2349	14.1990	0.2791	1.20	0.0626
大连	Gumbel法	2.4534	16.2620	0.6139	3.25	0.1371	杭州	Gumbel法	1.2802	14.1800	0.2733	1.22	0.0741
北京	矩估计法	1.6861	14.5580	0.4792	2.28	0.1700	金华	矩估计法	1.1369	13.7190	0.2663	1.30	0.0519
北京	Gumbel法	1.8205	14.5370	0.4880	2.36	0.1734	金华	Gumbel法	1.2180	13.7000	0.2590	1.27	0.0652
天津	矩估计法	1.5042	16.8090	0.4969	1.91	0.1025	南昌	矩估计法	1.9589	11.4730	0.2825	1.39	0.0603
天津	Gumbel法	1.6332	16.7770	0.4911	2.11	0.1015	南昌	Gumbel法	2.0756	11.4530	0.2773	1.60	0.0783
济南	矩估计法	1.4320	15.5750	0.2688	0.99	0.0936	福州	矩估计法	2.5044	14.5260	0.4334	2.13	0.0833
济南	Gumbel法	1.5939	15.5510	0.2525	0.97	0.1082	福州	Gumbel法	2.7933	14.4930	0.4192	2.17	0.0811
青岛	矩估计法	1.9150	17.7280	0.4233	2.09	0.1082	厦门	矩估计法	2.9360	13.1970	0.2499	1.27	0.0632
青岛	Gumbel法	2.0173	17.7030	0.4217	2.08	0.0933	厦门	Gumbel法	3.2960	13.1720	0.2267	1.29	0.0714
拉萨	矩估计法	1.1991	12.0220	0.4070	2.48	0.1350	广州	矩估计法	1.6028	14.3590	0.5708	3.09	0.1331
拉萨	Gumbel法	1.2231	12.0080	0.4177	2.71	0.1412	广州	Gumbel法	1.7895	14.3330	0.5798	3.04	0.1271
成都	矩估计法	1.3856	10.7460	0.3693	2.64	0.1219	南宁	矩估计法	1.4372	11.7290	0.2425	1.40	0.0596
成都	Gumbel法	1.4558	10.7252	0.3696	2.41	0.1069	南宁	Gumbel法	1.5603	11.6990	0.1982	1.03	0.0580
绵阳	矩估计法	1.1523	10.9890	0.3412	2.31	0.0918	深圳	矩估计法	2.7640	14.6610	0.3366	1.77	0.0907
绵阳	Gumbel法	1.2636	10.9670	0.3372	2.31	0.0837	深圳	Gumbel法	3.0590	14.6350	0.3246	1.86	0.1003
大理	矩估计法	2.6709	11.7880	0.2619	1.43	0.0908	海口	矩估计法	2.9869	15.042	1.0274	4.22	0.1452
大理	Gumbel法	3.1133	11.7560	0.2199	1.25	0.0768	海口	Gumbel法	3.3278	14.994	1.0408	4.97	0.1610
昆明	矩估计法	1.8512	12.1560	0.3242	1.85	0.0649	三亚	矩估计法	3.2478	16.5610	1.0028	2.70	0.0931
昆明	Gumbel法	2.0425	12.1230	0.2917	1.44	0.0493	三亚	Gumbel法	3.5261	16.4920	0.9831	3.58	0.1071

Table 1

Table 2

Fig.1

Fig.2

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