引力不稳定性的统一概念框架：从潜在系统状态到失效
A Unified Conceptual Framework for Gravitational Instabilities: From Latent System State to Failure
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中文总结 AI 辅助
研究引力不稳定性预测难题，提出统一概念框架，将其视为潜在系统状态受多种因素控制向灾难性失效的渐进演化，整合多学科概念，从重建系统状态角度助力灾害评估与预警。
中文摘要 AI 辅助
引力不稳定性是最普遍的自然灾害之一，在当前环境变化下预计会愈发显著。尽管在过程理解、监测和建模方面取得了重大进展，但预测失效时间仍是一项基本挑战，因为不稳定性源于跨多个时空尺度的复杂相互作用。现有方法往往聚焦特定过程等，导致对系统如何演变为失效的认识碎片化。本文提出一个统一概念框架，将引力不稳定性解释为由损伤积累、应力重新分布和外部强迫控制的潜在系统状态向灾难性失效的渐进演化。在此框架下，失效源于系统内部动力学和外部强迫的持续相互作用，可预测性取决于从不完整和间接观测中推断系统演化状态的能力。该框架提供了一个将多种引力灾害的物理过程、可观测表现、监测策略、建模方法和预测方法联系起来的共同结构。通过整合地质力学、断裂力学、统计物理学和数据驱动科学的概念，该框架将重点从寻找普遍前兆转向重建演化的系统状态及其接近不稳定性的程度。它为理解失效过程以及开发更稳健的灾害评估和预警方法提供了统一视角。
英文摘要
Gravitational instabilities are among the most widespread natural hazards and are expected to become increasingly significant under ongoing environmental change. Despite substantial advances in process understanding, monitoring, and modeling, predicting the timing of failure remains a fundamental challenge because instability emerges from complex interactions operating across multiple spatial and temporal scales. Existing approaches often focus on specific processes, forcing mechanisms, or observational signatures, resulting in a fragmented view of how systems evolve toward failure. This article propose a unified conceptual framework in which gravitational instabilities are interpreted as the progressive evolution of a latent system state controlled by damage accumulation, stress redistribution and external forcing to catastrophic failure. Within this perspective, failure emerges from the continuous interplay between internal system dynamics and external forcing, while predictability depends on our ability to infer the evolving state of the system from incomplete and indirect observations. The framework provides a common structure linking physical processes, observable manifestations, monitoring strategies, modeling approaches, and forecasting methods across a wide range of gravitational hazards. By integrating concepts from geomechanics, fracture mechanics, statistical physics, and data-driven sciences, the proposed framework shifts the focus from the search for universal precursors toward the reconstruction of evolving system states and their proximity to instability. It offers a unifying perspective for understanding failure processes and developing more robust approaches to hazard assessment and early warning.
