液化风险计算器
根据地震参数和地基条件估算土壤液化概率。
Assessment了解地震中的土壤液化
液化是指饱和的松散颗粒状土壤在地震震动中失去其强度和刚度,表现得像液体而非固体。当地震波通过饱水的砂或粉土时,会增加土粒之间的水压(孔隙水压力)。如果该压力升高到等于上覆土壤的重量,土粒之间就会失去接触,土壤暂时像粘性流体一样流动。这种现象可导致建筑物下沉、倾斜或倒塌;管道和储罐等地下结构上浮到地面;以及斜坡发生侧向扩展破坏。
标准贯入试验(SPT)N值是评估液化敏感性的关键现场测量。它测量将取样管打入地下30厘米所需的锤击次数——N值越高表示土壤越密实、抗性越强。在饱和条件下SPT N值低于15的土壤通常被认为易于液化。地下水位深度同样重要:土壤必须饱和才能发生液化,因此地下水位浅(小于5米)的地区风险最高。填海造地和沿海填土特别脆弱,如1964年新潟地震和2011年克赖斯特彻奇地震所证实。
液化风险的关键因素
- 土壤类型:松散砂和粉砂最容易液化。粘土和砾石通常能抵抗液化,不过非塑性粉土在强烈震动下可能液化。
- 地下水位深度:较浅的地下水位(0-5米)大幅增加风险。地下水位深于15米的场地通常不会发生液化。
- 震动强度和持续时间:液化通常需要加速度超过0.1g的持续震动(数秒)。持续时间较长的地震会增加风险。
- 历史先例:过去地震中发生过液化的地区极有可能再次液化,因为导致液化的地质条件持续存在。
常见用途
- 在地震多发沿海地区进行房产评估时对液化可能性的初步评估。
- 了解哪些土壤条件和地震参数会导致液化。
- 评估填土地、填海造地或河流和海岸线附近场地的风险。
- 支持关于岩土地震工程的教育讨论。
How to Use
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1
Enter Soil and Site Data
Input your site's soil type (sand, silt, clay, fill), water table depth, and layer thickness. Sandy soils saturated with water at depths less than 10 meters carry the highest liquefaction potential.
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2
Specify the Earthquake Scenario
Enter the design earthquake magnitude (Mw) and peak ground acceleration (PGA) for your site. These can be obtained from the USGS seismic hazard map or from a site-specific hazard analysis at your return period of interest.
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3
Interpret the Liquefaction Potential Index
Review your Liquefaction Potential Index (LPI) value and qualitative risk category. LPI < 5 is considered low risk; LPI 5–15 moderate; LPI > 15 high. The tool follows the Iwasaki (1982) framework widely used in Japanese and US engineering practice.
About
Soil liquefaction has been recognized as a major earthquake hazard since the 1964 Niigata and Alaska earthquakes, which produced dramatic documentary evidence of ground failure. The modern analytical framework for liquefaction assessment was developed largely by H. Bolton Seed and colleagues at UC Berkeley in the 1970s–80s, based on Standard Penetration Test (SPT) blow counts as a proxy for soil density and resistance. The Seed-Idriss Simplified Procedure, subsequently updated by Youd et al. (2001) and Idriss and Boulanger (2008), remains the standard for routine engineering practice and forms the basis of most liquefaction screening tools.
Liquefaction assessment methods fall into two categories. Deterministic methods compute a factor of safety for each soil layer using measured in-situ properties (SPT N-value, CPT qc, shear wave velocity Vs) and the earthquake loading expressed as the Cyclic Stress Ratio. Probabilistic methods (Cetin et al., 2004; Boulanger and Idriss, 2014) incorporate uncertainty in both the demand and capacity parameters to produce probability-of-liquefaction values rather than binary pass/fail outcomes. Probabilistic approaches are increasingly favored in performance-based earthquake engineering (PBEE) frameworks, where risk is expressed as expected losses over the lifetime of a facility.
The 2010–2011 Canterbury earthquake sequence in New Zealand produced an unprecedented dataset for liquefaction research. The earthquakes affected Christchurch—a city founded on Holocene fluvial sediments—causing liquefaction across 80% of the residential Red Zone, the area ultimately purchased by the government for permanent managed retreat. GNS Science and the University of Canterbury deployed a multi-technique investigation including aerial photography, LiDAR surveys, and thousands of CPT soundings to map spatial variability in liquefaction manifestation at block-by-block resolution. The resulting Christchurch Liquefaction Vulnerability dataset is now one of the most comprehensive post-earthquake geotechnical records ever assembled and has driven significant advances in simplified liquefaction assessment procedures.