摘要
机器人与机器学习每日新闻的新闻记者兼工作人员新闻编辑-关于机器学习的详细数据已经公布。根据《中华人民共和国上海消息》，BY NewsRx通讯员的研究称：“岩土工程的精确数值分析在很大程度上依赖于本构模型及其参数，先进的本构模型可以描述可能涉及多个参数的土体的复杂力学行为。”国家自然科学基金(NSFC)，上海市科学技术委员会(STCSM)。本文从上海交通大学的研究中得到一句话：“然而，确定本构参数的取值总是依靠人工试验和误差，这是一个耗时的过程，不适合广泛应用，本文提出了一种基于实验室和现场测试的机器学习与搜索算法相结合的识别方法。”通过研究土体超固结和结构参数变化对三轴试验和旁压试验结果的影响，分析了本构参数的敏感性，进而利用神经网络模型，从三轴试验中识别出土体的初始状态参数值和材料控制参数范围，从而准确确定本构参数值。在现场旁压试验的基础上，建立了数值模型，并采用通用算法寻找材料控制参数范围内的最优拟合值，最后将所提出的识别方法应用于上海粘土3~5层，反演参数与三轴试验和旁压试验结果吻合良好。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Data detailed on Machine Learning have been prese nted. According to news originating from Shanghai, People’s Republic of China, b y NewsRx correspondents, research stated, “Accurate numerical analysis in geotec hnical engineering heavily relies on the constitutive model and its parameters. The advanced constitutive model can describe the complex mechanical behaviors of soil that may involve a number of parameters.” Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Science & Technology Commission of Shanghai Mu nicipality (STCSM). Our news journalists obtained a quote from the research from Shanghai Jiao Tong University, “However, determining the values of constitutive parameters always r elies on manual trial-and-error, which can be a time-consuming process and not c onducive to widespread application. This paper presents an identification method that combines machine learning with search algorithm based on the laboratory an d in-situ testing. Initially, the sensitivity of constitutive parameters was ana lyzed by investigating the effects of variations in soil overconsolidation and s tructural parameters on the results of triaxial and pressuremeter tests. Subsequ ently, the initial state parameter values and material control parameter ranges of the soil can be identified from the triaxial tests, this is achieved by using the neural network model. In order to accurately determine the parameters value , the numerical model was established based on in-situ pressuremeter test, and t raversal algorithm was implemented to search for the optimal fit values within t he range of material control parameters. Finally, the proposed identification me thod was applied to layers 3 - 5 of Shanghai clay, and the inverted parameters e xhibited a good fit with the outcomes of triaxial tests and pressuremeter tests. ”
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