Seismic Performance of Sacrificial Exterior Shear Keys in Bridge Abutments

2009 ◽  
Vol 25 (3) ◽  
pp. 643-664 ◽  
Author(s):  
Pedro F. Silva ◽  
Sami Megally ◽  
Frieder Seible
Keyword(s):  
Performance Evaluation ◽  
Seismic Response ◽  
Seismic Loading ◽  
Experimental Results ◽  
Peak Performance ◽  
Cyclic Loads ◽  
Hysteretic Model ◽  
Bridge Abutments ◽  
Deformation Response ◽  
Shear Keys

Performance evaluation of sacrificial exterior shear keys in bridge abutments under simulated seismic loading was conducted in terms of damage levels that were observed during testing. These experiments provided results that were used to make realistic assumptions on the load-deformation response of as-built sacrificial exterior shear keys as well as their peak and post-peak performance under cyclic loads. Experimental results were subsequently used to develop a two-spring component hysteretic model for modeling the seismic response of shear keys at the abutments. The mathematical rules used to describe the hysteretic model are presented. Analyses show that this model was able to reproduce reasonably well the cyclic response of the investigated keys. The hysteretic model and key experimental results are presented in this paper.

scholarly journals A Dockers Storage Performance Evaluation: Impact of Backing File Systems

2021 ◽  
pp. 8-17
Author(s):  
Amer Ramadan ◽  
Keyword(s):  
Performance Evaluation ◽  
Experimental Design ◽  
File Systems ◽  
Experimental Results ◽  
File Server ◽  
Storage Performance ◽  
File Access ◽  
Mail Server ◽  
The Impact ◽  
E Mail

This paper reports on an in-depth examination of the impact of the backing filesystems to Docker performance in the context of Linux container-based virtualization. The experimental design was a 3x3x4 arrangement, i.e., we considered three different numbers of Docker containers, three filesystems (Ext4, XFS and Btrfs), and four application workloads related to Web server I/O activity, e-mail server I/O activity, file server I/O activity and random file access I/O activity, respectively. The experimental results indicate that Ext4 is the most optimal filesystem, among the considered filesystems, for the considered experimental settings. In addition, the XFS filesystem is not suitable for workloads that are dominated by synchronous random write components (e.g., characteristical for mail workload), while the Btrfs filesystem is not suitable for workloads dominated by random write and sequential write components (e.g., file server workload).

Data-driven seismic response prediction of structural components

2021 ◽  
pp. 875529302110533
Author(s):  
Huan Luo ◽  
Stephanie German Paal
Keyword(s):  
Experimental Data ◽  
Seismic Response ◽  
Computational Cost ◽  
Data Driven ◽  
Computational Time ◽  
Lateral Stiffness ◽  
Hysteretic Model ◽  
Structural Components ◽  
Rc Columns ◽  
Detailed Model

Lateral stiffness of structural components, such as reinforced concrete (RC) columns, plays an important role in resisting the lateral earthquake loads. The lateral stiffness relates the lateral force to the lateral deformation, having a critical effect on the accuracy of the lateral seismic response predictions. The classical methods (e.g. fiber beam–column model) to estimate the lateral stiffness require calculations from section, element, and structural levels, which is time-consuming. Moreover, the shear deformation and bond-slip effect may also need to be included to more accurately calculate the lateral stiffness, which further increases the modeling difficulties and the computational cost. To reduce the computational time and enhance the accuracy of the predictions, this article proposes a novel data-driven method to predict the laterally seismic response based on the estimated lateral stiffness. The proposed method integrates the machine learning (ML) approach with the hysteretic model, where ML is used to compute the parameters that govern the nonlinear properties of the lateral response of target structural components directly from a training set composed of experimental data (i.e. data-driven procedure) and the hysteretic model is used to directly output the lateral stiffness based on the computed parameters and then to perform the seismic analysis. We apply the proposed method to predict the lateral seismic response of various types of RC columns subjected to cyclic loading and ground motions. We present the detailed model formulation for the application, including the developments of a modified hysteretic model, a hybrid optimization algorithm, and two data-driven seismic response solvers. The results predicted by the proposed method are compared with those obtained by classical methods with the experimental data serving as the ground truth, showing that the proposed method significantly outperforms the classical methods in both generalized prediction capabilities and computational efficiency.

scholarly journals Comparison of Prediction Methods for Axial Strength of Grouted Connections with Shear Keys

2020 ◽  
Vol 10 (6) ◽  
pp. 1942
Author(s):  
You Xianhui ◽  
Wu Zhaoqi ◽  
Chen Zehao
Keyword(s):  
Health And Safety ◽  
Prediction Method ◽  
American Petroleum Institute ◽  
Experimental Results ◽  
Offshore Wind ◽  
Prediction Methods ◽  
Compression Tests ◽  
Axial Strength ◽  
Wide Range ◽  
Shear Keys

Grouted connections are commonly used in marine engineering, especially on oil platforms, cross-sea bridges, and offshore wind power turbines. The prediction methods for axial carrying capacity of grouted connections with shear keys and their application ranges in current codes were analyzed in this paper. The calculated results by using different codes were compared based on a practical grouted connection between steel piles and the jacket foundation of a wind turbine. The research team conducted axial compression tests on seven specimens, collected a wide range of experimental results to establish a database, and finally compared the standard calculation results with the experimental results. The study indicates that the axial strength of grouted connections predicted by different methods is distinct. The calculation formula of the British Health and Safety Executive (HSE, 2002) has obvious limitations; specifically, with increased shear keys, strength is overestimated, resulting in insecure design outcome of structures. The results calculated by the Norwegian Det Norske Veritas (DNV, 2013) are generally consistent with the experimental results, in which the reduction effect of multiple shear keys was considered. The prediction method of the American Petroleum Institute (API, 2007), which undervalues the bearing performance of connections, is excessively conservative. The method of the combined Norwegian and German Det Norske Veritas–Germanischer Lloyd (DNV-GL, 2016) has wider applicability and is safe, reliable, and economical.

Fabrication and performance evaluation of two multi-layer passive micromixers

Sensor Review ◽  
2018 ◽  
Vol 38 (3) ◽  
pp. 321-325 ◽  
Author(s):  
Xueye Chen ◽  
Jienan Shen ◽  
Zengliang Hu
Keyword(s):  
Reynolds Number ◽  
Performance Evaluation ◽  
Design Methodology ◽  
Experimental Results ◽  
Microfluidic Chips ◽  
Mixing Index ◽  
Number Range ◽  
Content Type ◽  
Chaotic Convection ◽  
And Performance

PurposeThe purpose of this study is to provide a micromixer for achieving effective mixing of two liquids. The mixing of two liquids is difficult to achieve in microfluidic chips because they cannot form turbulence at small dimensions and velocities.Design/methodology/approachIn this paper, four kinds of passive micromixers based on splitting–recombination and chaotic convection are compared. First, a better E-shape mixing unit based on the previous F-shape mixing unit has been designed. Then, the E-shape mixing units are further combined to form three micromixers (i.e. E-mixer, SESM and FESM).FindingsFinally, the mixing experimental results show that the mixing indexes of E-mixer, SESM and FESM are more than those of F-mixer when the Reynolds number range is from 0.5 to 100. And at Re = 15, the lowest mixing index of E-mixer is 71%, which is the highest of the four micromixers.Originality/valueAt Re = 80, the highest mixing index of F-mixer and E-mixer is 92 and 94 per cent, respectively, and then it begins to decrease. But the mixing index of SESM and FESM remains close to 100 per cent.

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