潜在震源区震级上限不确定性研究

潜在震源区的震级上限（Mu）是指在该潜在震源区内可能发生的最大地震的震级．预期未来发生超过该震级地震的概率趋于0．本文运用误差分析及逻辑树等方法,并结合发震模型的数值模拟得到的大震合成目录等结果,系统分析并最终得到了不同途径给出的不同类型潜在震源区震级上限的不确定性．该结果可直接应用于包括地震区划在内的工程地震以及活动断裂危险性评价等工作中．     

潜在震源区不确定性因素分析

本文根据洪华生(Der Kiureghian-Ang)断层破裂模型,对不同尺度的潜在震源区及各种震源参数进行了地震危险性数值计算。分析了潜在震源区划分范围,震级上限M_u及β值等地震活动性参数的不确定性对地震危险性分析的影响,其结果可供地震区划及工程地震等工作者参考。     

潜在震源区震级上限对基岩加速度反应谱特征周期的影响

地震学理论和强震观测者表明,强震反应谱在形状主要取决于震级、震中距和场地条件。由于我国现行的各种行业建筑物抗震设计规范中对标准加速度反应谱特征周期Ｔｇ作出的规定中一般只考虑场地和震中距的影响或只考虑场地影响,因此在某些情况下,由规范所得到的反应谱特征周期与由专门的地震危险性分析所得到的结果相差较大。本文通过理论分析和实际的算例,讨论了潜在震源区震级上限对基岩加速度反应谱特征周期的影响。所得到的结论     

划分潜在震源区的地震地质规则研究

根据近年来发震构造地质条件研究的进展，本文探讨了划分潜在震源区主要的地震地质规则，具体包括潜在震源区的识别；。它的位置，长度，宽度和震级上限的确定等内容。规则的归纳充分考虑了活动构造性质的差异和资料完备程度的不同。     

兰州邻区活断层潜在地震最大震级及其危险性评估

兰州附近的庄浪河断裂和白银白杨树沟断裂是对兰州市地震安全有一定影响的晚第四纪活动断裂,但沿断裂发生的中强破坏性地震较为复杂甚至不明确。如何评价西部地区此类断裂的最大潜在地震震级及其危险性是地震中长期预测和地震区划研究中较为重要的问题之一。本文借鉴闻学泽等(2007)对中国大陆东部中-弱活断层潜在地震最大震级评估的思路,建立了兰州地区最大地震震级Mmax与断层小区震级-频度关系参数at/b值之间的经验公式;并采用经验公式外推得到庄浪河断裂和白杨树沟断裂的震级上限Mu分别为MS6.9、6.3,进而评估了这两条断裂的地震平均复发间隔和发震概率。     

如何确定对场地地震危险性贡献量最大的潜在震源区

分别以北京市清河镇和密云水库大坝邻近地区作为场地,讨论了贡献量最大潜在震源区的确定问题。对于北京市清河镇场地,不同周期下对场地贡献量最大的潜在震源区都是北京潜在震源区;但对于密云水库大坝邻近地区,在年超越概率小于1-00E- 2 条件下,短周期( T= 0-1s) 时对场地贡献量最大的潜在震源区是怀柔潜在震源区,而长周期( T= 1-0s) 时对场地贡献量最大的潜在震源区是夏垫潜在震源区。这种变化说明近源在短周期时所起作用较为明显,而远源对长周期部分的贡献量增大。区分不同周期下贡献量最大的潜在震源区,对于确定期望地震或设定地震以及计算场地地震动持续时间等参数是重要的     

地震活动性参数估计的K方法及潜在震源区边界不确定性的影响

本文在两个方面介绍了可用于地震区划的新方法。一方面是在ｂ值及年发生率估计中，现有地震目录由两部分组成，一为历史地震目录，二为现今中小地震目录，仅用其一部分都具有缺陷。     

对沈阳地区地震危险性贡献量最大的潜在震源区的确定

在沈阳市中心选取一个场址进行地震危险性分析,分别计算0s、1.0s和6.0s周期下沈阳附近各潜在震源区对场址地震危险性的贡献量。计算结果说明在短周期时对场址贡献最大的是沈阳潜在震源区,长周期时对场址贡献最大的是海城潜在震源区。研究不同周期时贡献量最大的潜在震源区,符合工程实际情况,使最终确定的地震动参数更为合理可靠。     

潜在震源区综合评评判法在地震危险性分析中的应用

用多方案划分潜在震源区的方法对乌鲁木齐市某场地研究区进行地震危险性分析,可在研究区内划分出两套较成熟的潜在震源区方案,在这两个方案的基础上分别进行地震危险性分析,可得到两组危险性分析结果,之后由专家综合评判打分给出权重系数,对两个方案的两组危险性分析结果加权处理得到综合评判的结果。     

潜在震源区划分的不确定性分析

本文将潜在震源的不确定性分为震源类型与震源几何尺度的不确定性两类,用逻辑树方法概括了潜在震源区划分的各种可能方案,并据此给出了考虑潜在震源区划分不确定性的地震危险性分析的计算步骤。用本文的方法对上海市地震危险性进行了分析。     

根据截断的G-R模型计算东北地震区震级上限

震级上限是指一个地区可能发生地震的最大震级,其概率意义为发生超过该震级地震的概率几乎为0.在有些地区,由于对其内部的地震构造研究和认识存有局限性,很难根据构造或者地质学的原则来确定震级上限.因此,根据数学模型,采用统计手段,使用地震活动性资料来计算震级上限的估计值是一种可行的方法.本文根据截断的G-R关系模型,采用最大似然计算方法,使用东北地震区的地震目录,计算了东北地震区震级上限,结果表明东北地震区的震级上限应为Mu=7.5左右.计算中我们考虑了不同震级的转换、震级误差的修正以及计算方法的影响.最终结果表明,不论采用何种方案进行计算,东北地震区的震级上限值均始终保持在7.5左右,这说明我们采用本文中方法计算得到的东北地震区的震级上限值是合理可信的,同时也说明在以往的研究中对东北地震区震级上限的估计大都是偏小的.     

Earthquake magnitude or seismic moment in seismic hazard evaluation?

Seismic hazard analysis requires the estimation of the probabilities that earthquakes will take place within a region of interest, and the expected level of ground motion which will be received at a site during the nextt years. The earthquake magnitude has been used as a basic parameter, because it is available, under the assumption that the earthquake occurrence is a compound Poisson process with exponential or multinomial distribution of magnitude.For improving the hazard prediction, we used the seismic moment as a basic parameter to estimate the mean rate, , of occurrence of earthquakes in a function of seismic moment rate and slip rate released in a seismogenic region.As an illustration of the model, the seismic hazard analysis at different sites in and around the Gulf of Corinth, central Greece, is presented on the basis of the earthquake magnitude and the seismic moment. Comparison of the results shows that determination of the mean rate of earthquake occurrence, using the conventional Gutenberg-Richter recurrence model, underestimates the seismic hazard at a site.     

川滇地区地震危险性数值分析

川滇地区地处我国南北地震带南段,近百年来地震活动性持续较高,该地区未来强震预测研究备受关注.本文根据该区域百年时间内发生的30次M_S＞6.5历史地震,结合区域地质背景及GPS观测数据等,建立区域有限元准三维弹性模型,通过反演给定区域特定时刻合理的初始应力场.在此基础上,综合考虑地震孕育阶段和震后调整阶段的动力学过程,以库仑-摩尔破裂准则作为判断地震发生的条件,模拟单次地震过程和历史地震序列的发展过程.同时,对于数值模拟中的不确定性成分,通过大量Monte Carlo随机试验得到5000种初始应力场模型,确保所有模型均能重现历史地震的发震过程,最终得到现今应力场状态,并据此计算地震危险性系数,将不同模型的计算结果进行概率统计,初步得到研究区域2017年九寨沟地震后的地震危险性概率分布.结果显示历史地震破裂区的危险性概率大幅降低,相对安全;而龙门山断裂带东北段发震概率高达30%,主要是受2008年汶川地震震后应力扰动的影响;龙门山断裂带西南段(包括汶川地震破裂区与芦山地震破裂区的中间区域)与鲜水河断裂带交界处发震概率约为15%~20%;另外滇西南龙陵瑞丽断裂带及澜沧江断裂带附近发震概率约为10%~15%,近年来滇西南地区小震频发,该地区地震危险性同样值得注意.

     

Regional and local seismic hazard assessment

Recent earthquakes such as the M_JMA 7.2 Hyogo-ken Nambu earthquake and the M 7.4 Kocaeli earthquake demonstrate once again the need to include detailed soil investigation into hazard evaluation, that is the need of microzonation. Seismic hazard assessment evaluated at a regional scale generally does not consider soil effects but only in a limited way using an attenuation law that can be ‘soft soil’ or ‘rock’. However, the relevant role of seismic hazard in the assessment of seismic coefficients for the definition of the actions in seismic codes must be properly considered. That is to say, the level of protection of buildings is proportional to a definite level of hazard (generally considered to be the ground motion with 10% probability of exceedence in 50 years). When a microzonation is performed, this criterion cannot be ignored, therefore, a clear linkage must be established between hazard (regional scale) and microzonation. The crucial point is represented by the reference motion (or input motion) to be used for site effects analysis, that must be compatible with the regional seismic hazard. In this paper, three different approaches for reference motion evaluation are analysed: probabilistic; stochastic; and deterministic. Through the case history of Fabriano microzonation the three approaches are compared. It is shown that each approach presents advantages and disadvantages with respect to the others. For example, the probabilistic approach (the reference motion is directly derived from the expected response spectra for a given return period) is linked with hazard, but produces an overestimation in short periods range, while the deterministic approach correctly simulates the wave propagation, but it ends with a kind of conditional probability. Until now, clear criteria to choose the right approach do not appear to exist and the expert experience is of fundamental importance.     

Probabilistic seismic hazard assessment of the Pyrenean region

A unified probabilistic seismic hazard assessment (PSHA) for the Pyrenean region has been performed by an international team composed of experts from Spain and France during the Interreg IIIA ISARD project. It is motivated by incoherencies between the seismic hazard zonations of the design codes of France and Spain and by the need for input data to be used to define earthquake scenarios. A great effort was invested in the homogenisation of the input data. All existing seismic data are collected in a database and lead to a unified catalogue using a local magnitude scale. PSHA has been performed using logic trees combined with Monte Carlo simulations to account for both epistemic and aleatory uncertainties. As an alternative to hazard calculation based on seismic sources zone models, a zoneless method is also used to produce a hazard map less dependant on zone boundaries. Two seismogenic source models were defined to take into account the different interpretations existing among specialists. A new regional ground-motion prediction equation based on regional data has been proposed. It was used in combination with published ground-motion prediction equations derived using European and Mediterranean data. The application of this methodology leads to the definition of seismic hazard maps for 475- and 1,975-year return periods for spectral accelerations at periods of 0 (corresponding to peak ground acceleration), 0.1, 0.3, 0.6, 1 and 2 s. Median and percentiles 15% and 85% acceleration contour lines are represented. Finally, the seismic catalogue is used to produce a map of the maximum acceleration expected for comparison with the probabilistic hazard maps. The hazard maps are produced using a grid of 0.1°. The results obtained may be useful for civil protection and risk prevention purposes in France, Spain and Andorra.     

Recognition of the zones of seismic hazard in Polish Coal mines by using a seismic method

In the Upper Silesian Coal Field the seismic hazard induced by mining operations in collieries is closely related to the rockburst hazard. A seismic method is used for premonitory recognition of the zones of seismic hazard. It takes advantage of the relationship between the velocity of propagation of seismic waves and the state of stress existing in the rock. It consists of the determination of the velocity field of artificially induced seismic waves in a studied fragment of the rock, and of locating the velocity anomaly. The position of the velocity anomaly zones and their intensity are the basis for estimating the seismic hazard in advance of mining works.     

基于MGR模型的我国大陆地区各地震带1970年以来震级-频度关系和震级上限

本文利用两种常用的NGR和MGR模型,对我国大陆地区1970年以来各地震带的震级-频度关系和震级上限进行了修定.结果表明,MGR模型能很好地描述非线性的震级-频度关系,因此该模型更适合于我国大陆地区各地震带ML3.0以上地震的震级-频度关系,用MGR方法拟合确定震级上限时,样本量越高拟合的结果越准确.     

基于MGR模型修正我国大陆中强以上地震的震级-频度关系和确定震级极限值div

从理论上推导了修正的古登堡-里克特模型的震级上限的确定方法, 应用常用的两种模型对我国分区域进行了震级-频度关系的修正和震级极限值的确定. 结果表明, 我国大陆存在非线性的震级-频度关系, 传统的NGR模型不能反映非线性的震级-频度关系, 而MGR模型能反映适合非线性和线性的震级-频度关系, 因此MGR模型适合我国各研究区中强以上地震的震级-频度关系. 当震级 频度关系为非线性时, 用MGR模型确定的震级极限值较准确．      

A new seismic hazard analysis using FOSM algorithms

From recent lessons, it is evident that earthquake prediction is immature and impractical as of now. Under the circumstances, seismic hazard analysis is considered a more practical approach for earthquake hazard mitigation, by estimating the annual rate of earthquake ground motions (or seismic hazard) based on seismicity and other geological evidences. Like other earthquake studies for the high-seismicity region around Taiwan, this study aims to conduct a new seismic hazard assessment for the region using the well-established FOSM (first-order second-moment) algorithm, on the record of 55,000 earthquakes observed in the past 110 years. The new seismic hazard analysis from a different perspective shows that the annual rate for earthquake-induced PGA to exceed the current design value (i.e., 0.23g) in two major cities in Taiwan should be relatively low, with it no greater than 0.0006 per year. Besides, the FOSM estimates were found very close to those with Monte Carlo Simulation (MCS), mainly because the skewness of the three random variables (i.e., earthquake magnitude, location, and model error) considered in the probabilistic analysis is not very large.