岩爆烈度预测的改进物元可拓模型与实例分析

Improved matter-element extension model and its application to prediction of rockburst intensity

应用改进的物元可拓理论,并选取影响岩爆烈度的主要因素,如硐室最大切向应力σθ、岩石单轴抗压强度σc、岩石单轴抗拉强度σt以及冲击倾向指数Wet,以σθ/σc、σc/σt及Wet作为岩爆烈度评价指标,建立岩爆烈度预测的改进物元可拓模型。该模型首先确定岩爆烈度分级标准,通过隶属函数对分级标准进行隶属化,并确定节域隶属化范围,弥补特征值可能超出节域而使关联函数失效的缺陷;然后运用博弈论,将评价指标客观动态权重与主观静态权重优化、融合,克服传统物元可拓评价中单纯依靠特征值赋权而忽略特征本身对评价结果的重要性的弊端;最后通过最大关联度准则对岩爆烈度等级进行预测,从而建立岩爆烈度预测的改进物元可拓模型。为进一步考察该模型有效性及实用性,运用该模型对国内外20个岩爆工程进行分析。应用结果表明:该模型预测结果与实际情况吻合较好,且与传统物元可拓评价方法和模糊数学综合评价方法得到的结果相比,具有更高的准确度。

Based on the improved matter-element extension theory, an improved matter-element extension model used to predict the rockburst intensity was established. Firstly, the main factors of rockburst intensity, such as the maximum tangential stress of the cavern wall σθ, uniaxial compressive strength σc, uniaxial tensile strength at, and the elastic energy index of rock Wet, were taken into account in the analysis. Three factors,σθ/σc、σc/σt and Wet were defined as the criterion indices for rockburst intensity prediction in the proposed model. Secondly, the classification standards of rockburst intensity were confirmed. In order to remedy the defect of the correlation function which may exceed the controlled field, the rockburst intensity classification standards were normalized. And then, based on the game theory, the synthetic weight values of eigenvalue were determined by integrating the objective-dynamic weight and subjective-static weight, solving problems occurred in traditional matter-element extension assessment method like indicator weight only depends on eigenvalue, ignoring the significance of feature. Lastly, the rockburst intensity level （RIL） was predicted by the maximum incidence degree criterion, then are improved matter-element extension model used to predict the rockburst intensity was proposed. 20 cases of the engineering project examples of the domestic and foreign were analyzed by using the proposed model to study the effectiveness and practicality of the model. The results show that the prediction results agrees well with the practical situations, and have higher accuracy compared with the results of the traditional matter-element extension method and the fuzzy mathematics comprehensive evaluation method.