Reliability assessment of serviceability performance of braced retaining walls using a neural network approach

In urban environments, one major concern with deep excavations in soft clay is the potentially large ground deformations in and around the excavation. Excessive movements can damage adjacent buildings and utilities. There are many uncertainties associated with the calculation of the ultimate or serviceability performance of a braced excavation system. These include the variabilities of the loadings, geotechnical soil properties, and engineering and geometrical properties of the wall. A risk‐based approach to serviceability performance failure is necessary to incorporate systematically the uncertainties associated with the various design parameters. This paper demonstrates the use of an integrated neural network–reliability method to assess the risk of serviceability failure through the calculation of the reliability index. By first performing a series of parametric studies using the finite element method and then approximating the non‐linear limit state surface (the boundary separating the safe and ‘failure’ domains) through a neural network model, the reliability index can be determined with the aid of a spreadsheet. Two illustrative examples are presented to show how the serviceability performance for braced excavation problems can be assessed using the reliability index. Copyright © 2005 John Wiley & Sons, Ltd.     

Benthic Metabolism and Standing Stock in the Central and Northern Deep Red Sea

Abstract. Benthic metabolism and standing stocks were investigated in the deep Red Sea between 21^o and 27^oN, Activity was assessed by the determination of respiration rates with a shipboard method and by calculating oxygen consumption from the activity in the electron transport system. We attempted to compare results from different latitudes within the warm Red Sea and with data from cold Atlantic environments. Our investigations were part of an environmental risk assessment to evaluate future mining of metalliferous sediments from the Atlantis II Deep.     

烟台市污水处理深海排放工程设计方案研究与选择

沿海城市污水处理深海排放工程在我国起步较晚，烟台市污水处理深海排放工程我国目前规模最大的同类工程，且已进入施工阶段，本文详细阐述了该工程及水工设计方案，在我国城市污水２深海排放工程领域作了积极有益的探索。     

论上海软土地基⑦⑧⑨层压缩模量Es的定值问题

上海地区深部土层⑦⑧⑨层埋深在30～70m。对其压缩模量Es的定值问题,现行《上海市地基基础设计规范》(DGJ08 11 1999)(后文中简称《规范》)长期以来确定室内试验E0 1～0 2值为沉降计算值,导致沉降计算值与建(构)筑物实际沉降量之间相差2～8倍。为符合规范的变形要求,设计人员不得不采取桩加粗、加长、加密的办法,从而造成桩基投资的极大浪费。为了正确认识深部土层的Es值,上海岩土工程界进行了多种形式的试验研究。近年来,笔者结合上海高、大、深、重建(构)筑物的工程实践,深入进行上海深部⑦⑧⑨层压缩模量Es的试验研究,获得许多新的认识,对其定值问题作了研究,提出⑦⑧⑨层的建议值,供同行参考研讨。     

Study of crustal structure with S—wave data from Maqen—Jingbian profile

2-D crustal velocity structure and vp/vs are obtained by processing and interpretation of S-wave data from Maqen-Jingbian deep seismic sounding(DSS)profile.The result shows that there exist obvious differences in 2-D S-wave velocity structure and vp/vs ratio structure along the profile.The S-wave velocities are low and vp/vs ration is high for the westem section of the profile and Haiyuan region,while they are normal for the middle and eastern sections.The changes in lithologic characters of two major anomalous zones are discussed according to lateral variation of S-wave velocity structure and vp/vs ratio structure.It is concluded that the development and occurrence of the Haiyuan strong earthquake is not only related to tectonic activities,but also to lithologic characters of the region.     

高岭土深加工产品开发

当前世界上煅烧高岭土产品已瞄准高档化、专用化、精细化和功能化，深加工系列产品已应用于高档汽车、船舶、乳胶、颜料、化工、造纸、涂料等方面。内蒙古自治区有丰富的高岭土资源，我们应依托优势资源，尽快掌握高新技术，开发高岭土系列产品，争取在较短的时间内在国内外激烈的市场竞争中立于不败之地，为自治区的经济繁荣起到积极的推动作用。     

基于A- CGAN的深反射地震数据随机噪声压制方法研究

基于深度学习的地震数据噪声压制方法是当前地震数据去噪处理的重要方向。深度学习方法突破了传统滤波处理的局限,在对常规地震数据的噪声压制中表现出效率高、信噪分离效果好的特点。但针对深部弱有效反射数据,当前的深度学习方法特征提取能力有限,难以取得较好的去噪效果。笔者等结合深反射地震数据特点,针对当前深度学习噪声压制方法在特征提取及对数据集依赖上的局限,提出了基于注意力循环生成对抗网络(Attention Cycle- Consistent Generative Adversarial Networks,A- CGAN)的深反射地震数据随机噪声压制方法。借助循环一致生成对抗网络(Cycle- Consistent Generative Adversarial Networks,Cycle- GAN)的域映射思想,降低对数据集的要求。为了构建适用于深反射地震数据的去噪网络,从3个方面对Cycle- GAN进行改进：在Cycle- GAN的生成器（去噪器）中加入残差结构和注意力机制,用于加深网络深度和提高其特征提取能力;在Cycle- GAN的鉴别器中使用块判决,提高鉴别精度和准确度;在损失函数部分加入感知一致性损失函数,提升网络模型恢复纹理细节信息的能力。通过合成地震数据和实际深反射地震数据测试,验证了优化算法的有效性,体现了良好的应用价值。     

预测有效波高的深度学习模型研究

研究基于RNN、LSTM、GRU深度学习模型,针对NOAA浮标数据集中的44013、44014、44017浮标的数据,通过斯皮尔曼相关性分析提高模型预测效果。实验结果表明,在进行相关性分析后,S-RNN、S-LSTM、 S-GRU的预测效果均比原始RNN、LSTM、GRU模型预测效果好。此外,提出一种基于LSTM的LSTM-Attention 波高预测模型,并进行相关实验,量化LSTM-Attention模型的预测效果,实验结果表明LSTM-Attention模型有更好的预测效果。为评估模型的泛化能力,研究还提出了一种采用邻近浮标数据进行学习,预测浮标缺失数据的方 法。实验结果表明,该方法的预测精度可以达到97.93%。本研究为海浪预测提供了新的方法和思路,也为未来深 度学习模型在海浪预测中的应用提供了参考。     

深厚覆盖层高压旋喷凝结体的宏观力学参数研究

基于现有工程试验资料,通过将高压旋喷凝结体分成成芯凝结体和不成芯凝结体两组材料组成,提出了深厚覆盖层高压旋喷凝结体的统计力学模型。该模型除能反映成芯凝结体的小尺度力学性质外,还可以反映不成芯凝结体的力学性质,也可考虑试验钻孔中不同芯样获得率的影响。应用随机模拟理论,给出了大体积高喷体内成芯凝结体与不成芯凝结体的空间位置及各小尺度力学参数的抽样方法。并通过结合弹塑性有限元和随机模拟两方法,建立了高喷体宏观力学性质的计算机模拟方法。应用所提三维弹塑性有限元随机模拟方法,分析研究了向家坝水电站深厚覆盖层高压旋喷凝结体的宏观力学参数。     

Study on Eogene Basalts: Implication of the Deep Process over the Bohaiwan Basin Evolution

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