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Foundation Engineering for Expansive Soils
Your guide to the design and construction of foundations on expansive soils Foundation Engineering for Expansive Soils fills a significant gap in the current literature by presenting coverage of the design and construction of foundations for expansive soils. Written by an expert author team with nearly 70 years of combined industry experience, this important new work is the only modern guide to the subject, describing proven methods for identifying and analyzing expansive soils and developing foundation designs appropriate for specific locations. Expansive soils are found worldwide and are the leading cause of damage to structural roads. The primary problem that arises with regard to expansive soils is that deformations are significantly greater than in non-expansive soils and the size and direction of the deformations are difficult to predict. Now, Foundation Engineering for Expansive Soils gives engineers and contractors coverage of this subject from a design perspective, rather than a theoretical one. Plus, they'll have access to case studies covering the design and construction of foundations on expansive salts from both commercial and residential projects. * Provides a succinct introduction to the basics of expansive soils and their threats * Includes information on both shallow and deep foundation design * Profiles soil remediation techniques, backed-up with numerous case studies * Covers the most commonly used laboratory tests and site investigation techniques used for establishing the physical properties of expansive soils If you're a practicing civil engineer, geotechnical engineer or contractor, geologist, structural engineer, or an upper-level undergraduate or graduate student of one of these disciplines, Foundation Engineering for Expansive Soils is a must-have addition to your library of resources.
eBook
A Vision-Based Sensor for Noncontact Structural Displacement Measurement
Conventional displacement sensors have limitations in practical applications. This paper develops a vision sensor system for remote measurement of structural displacements. An advanced template matching algorithm, referred to as the upsampled cross correlation, is adopted and further developed into a software package for real-time displacement extraction from video images. By simply adjusting the upsampling factor, better subpixel resolution can be easily achieved to improve the measurement accuracy. The performance of the vision sensor is first evaluated through a laboratory shaking table test of a frame structure, in which the displacements at all the floors are measured by using one camera to track either high-contrast artificial targets or low-contrast natural targets on the structural surface such as bolts and nuts. Satisfactory agreements are observed between the displacements measured by the single camera and those measured by high-performance laser displacement sensors. Then field tests are carried out on a railway bridge and a pedestrian bridge, through which the accuracy of the vision sensor in both time and frequency domains is further confirmed in realistic field environments. Significant advantages of the noncontact vision sensor include its low cost, ease of operation, and flexibility to extract structural displacement at any point from a single measurement.
Journal Article
Future Circular Collider Feasibility Study Report
Volume 1 of the FCC Feasibility Report presents an overview of the physics case, experimental programme, and detector concepts for the Future Circular Collider (FCC). This volume outlines how FCC would address some of the most profound open questions in particle physics, from precision studies of the Higgs and EW bosons and of the top quark, to the exploration of physics beyond the Standard Model. The report reviews the experimental opportunities offered by the staged implementation of FCC, beginning with an electron-positron collider (FCC-ee), operating at several centre-of-mass energies, followed by a hadron collider (FCC-hh). Benchmark examples are given of the expected physics performance, in terms of precision and sensitivity to new phenomena, of each collider stage. Detector requirements and conceptual designs for FCC-ee experiments are discussed, as are the specific demands that the physics programme imposes on the accelerator in the domains of the calibration of the collision energy, and the interface region between the accelerator and the detector. The report also highlights advances in detector, software and computing technologies, as well as the theoretical tools/reconstruction techniques that will enable the precision measurements and discovery potential of the FCC experimental programme. The content and structure of this report are guided by the scope and priorities defined in the mandate of the FCC Feasibility Study. It is therefore not intended to serve as an exhaustive review of the full physics potential of FCC. Several topics, already covered in earlier reports such as the FCC CDR, are not reiterated here or are addressed only briefly, in alignment with the study’s focus. This volume reflects the outcome of a global collaborative effort involving hundreds of scientists and institutions, aided by a dedicated community-building coordination, and provides a targeted assessment of the scientific opportunities and experimental foundations of the FCC programme.
Journal Article
Deformation-induced martensite in austenitic stainless steels: A review
Recent progress in the understanding of the deformation-induced martensitic transformation, the transformation-induced plasticity (TRIP) effect, and the reversion annealing in the metastable austenitic stainless steels are reviewed in the present work. For this purpose, the introduced methods for the measurement of martensite content are summarized. Moreover, the austenite stability as the key factor for controlling the austenite to martensite transformation is critically discussed. This is realized by analyzing the effects of chemical composition, initial grain size, applied strain, deformation temperature, strain rate, and deformation mode (stress state). For instance, the effect of initial grain size is found to be complicated, especially in the ultrafine grained (UFG) regime. Furthermore, it seems that there is a critical grain size for changing the trend of α′-martensite formation. Decreasing the deformation temperature motivates the formation of α′-martensite, but there is a critical temperature for achieving the maximum tensile ductility. Afterwards, the modeling techniques for the transformation kinetics and the contribution of deformation-induced martensitic transformation to the strengthening of material and also strength-ductility trade-off are critically surveyed. The processing of UFG microstructure during reversion annealing, the effects of the recrystallization of the retained austenite, the martensitic shear and diffusional reversion mechanisms, and the annealing-induced martensitic transformation are also summarized. Accordingly, this overview presents the opportunities that the strain-induced martensitic transformation can offer for controlling the microstructure and mechanical properties of metastable austenitic stainless steels.
Journal Article
Machine learning-based seismic response and performance assessment of reinforced concrete buildings
Complexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data points of training dataset for developing data-driven techniques, Incremental Dynamic Analyses (IDAs) were performed considering 165 RC MRFs with two-, to twelve-Story elevations having the bay lengths of 5.0 m, 6.1 m, and 7.6 m assuming near-fault seismic excitations. Then, important structural features were considered in datasets to train and test the ML-based prediction models, which were improved with innovative techniques. The results show that improved algorithms have higher
R
2
values for estimating the Maximum Interstory Drift Ratio (IDR
max
), and two improved algorithms of artificial neural networks and extreme gradient boosting can estimate the Median of IDA curves (M-IDAs) of RC MRFs, which can be used to estimate the seismic limit-state capacity and performance assessment of existing or newly constructed RC buildings. To validate the generality and accuracy of the proposed ML-based prediction model, a five-Story RC building with different input features was used, and the results are promising. Therefore, graphical user interface is introduced as user-friendly tool to help researchers in estimating the seismic limit-state capacity of RC buildings, while reducing the computational cost and analytical efforts.
Journal Article