CIEM5740 Computer Methods for Slope Engineering 2Java

部署运行你感兴趣的模型镜像

Java Python CIEM5740 Computer Methods for Slope Engineering

Assignment 2

(Due: 11:00 pm, Friday 18 Oct 2024, submitted online)

Q1 (50 Marks) Please derive the expression of factor of safety for an infinite slope (with effective strength parameters c' and f') for a case of seepage parallel to the slope surface. You may wish to refer to Chapter 6 of the book by Duncan and Wright (2005) (uploaded in CANVAS → Modules→ Reading materials→CIEM5740-Reading-DW-Book-chpt6.pdf).

Q2 (50 Marks) The following case study involving a failure in fissured over-consolidated clay slope was reported by Henkel and Skempton in 1954 (Henkel, D.J. and A.W. Skempton, 1954. "A landslide at Jackfield, Shropshire, in an over-consolidated clay", Geotechnique, 5:2:131-137). The failure occurred in CIEM5740 Computer Methods for Slope Engineering Assignment 2Java 1952 in Jackfield, Shropshire, England. The slope profile is shown in Figure 1. The failure was a translational slide where the average depth to the failure plane was 17 ft. The ground water table was very near or at the surface. The peak strength parameters of the over-consolidated clay are: cohesion, c'= 220 psf and friction angle, φ'= 25°. The saturated unit weight of the soil is 145 pcf. (1) Please perform. a simple infinite slope analysis with seepage parallel to the slope to determine the factor of safety. Based on your results what can you conclude on the use of the peak strength parameters in long-term stability investigation of overconsolidated clays. (2) Please try to use SLOPE/W to verify your result in (1). Hint: you may use “fully specified slip surface” method to define the actual failure surface. Also please choose the correct unit in SLOPE/W         

您可能感兴趣的与本文相关的镜像

Llama Factory

Llama Factory

模型微调
LLama-Factory

LLaMA Factory 是一个简单易用且高效的大型语言模型(Large Language Model)训练与微调平台。通过 LLaMA Factory,可以在无需编写任何代码的前提下,在本地完成上百种预训练模型的微调

Nano-ESG数据资源库的构建基于2023年初至2024年秋季期间采集的逾84万条新闻文本,从中系统提炼出企业环境、社会及治理维度的信息。其构建流程首先依据特定术语在德语与英语新闻平台上检索,初步锁定与德国DAX 40成分股企业相关联的报道。随后借助嵌入技术对文本段落执行去重操作,以降低内容冗余。继而采用GLiNER这一跨语言零样本实体识别系统,排除与目标企业无关的文档。在此基础上,通过GPT-3.5与GPT-4o等大规模语言模型对文本进行双重筛选:一方面判定其与ESG议题的相关性,另一方面生成简明的内容概要。最终环节由GPT-4o模型完成,它对每篇文献进行ESG情感倾向(正面、中性或负面)的判定,并标注所涉及的ESG具体维度,从而形成具备时序特征的ESG情感与维度标注数据集。 该数据集适用于多类企业可持续性研究,例如ESG情感趋势分析、ESG维度细分类别研究,以及企业可持续性事件的时序演变追踪。研究者可利用数据集内提供的新闻摘要、情感标签与维度分类,深入考察企业在不同时期的环境、社会及治理表现。此外,借助Bertopic等主题建模方法,能够从数据中识别出与企业相关的核心ESG议题,并观察这些议题随时间的演进轨迹。该资源以其开放获取特性与连续的时间覆盖,为探究企业可持续性表现的动态变化提供了系统化的数据基础。 资源来源于网络分享,仅用于学习交流使用,请勿用于商业,如有侵权请联系我删除!
评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值