Estimation of Liquefaction Potential by in Situ Methods

1995 ◽  
Vol 11 (3) ◽  
pp. 431-455 ◽  
Author(s):  
Steven D. Glaser ◽  
Riley M. Chung
Keyword(s):  
Seismic Velocity ◽  
State Of The Art ◽  
Test Methods ◽  
Estimation Methods ◽  
Penetration Test ◽  
Liquefaction Potential ◽  
Current State ◽  
Undisturbed Samples ◽  
In Situ Methods

This report examines the state-of-the-art of in situ methods of estimating liquefaction potential in sands. In situ methods are especially important since “undisturbed” samples of loose sand for laboratory testing are virtually unobtainable. Various penetration test methods are examined, such as the SPT, DMT, and the CPT and variants. These methods are completely empirical in nature, and have worked well to date. The current state-of-practice is an SPT-based method. Intrusive, seismic-based tests are also examined: the cross-hole, down-hole tests, and down-hole logger. The seismic velocity-based predictors have a stronger physical basis than the penetration test-based estimation methods, but need a larger database. A non-intrusive test, the Spectral Analysis of Surface Waves technique, seems especially suited for examining sites of large areal extent.

Assessment of the range of variation of Nγ from 60 estimation methods for footings on sand

2013 ◽  
Vol 50 (7) ◽  
pp. 793-800 ◽  
Author(s):  
Edgar Giovanny Diaz-Segura
Keyword(s):  
Friction Angle ◽  
Standard Penetration Test ◽  
Estimation Methods ◽  
Penetration Test ◽  
In Situ Tests ◽  
Vertical Loading ◽  
Simplified Method ◽  
Bearing Capacity Factor ◽  
Range Of Variation

The range of variation of the bearing capacity factor, Nγ, was assessed using 60 estimation methods for rough footings on sand subjected to static vertical loading. The influence on the Nγ values of the use of correlations for the estimation of the friction angle, [Formula: see text], derived from in situ tests was also assessed. The analysis shows a marked dependency on the methods used to determine Nγ, showing differences for the same [Formula: see text] values of up to 267% between estimated values. Uncertainty in the estimation of [Formula: see text], due to the use of correlations with in situ tests, leads to a range of variation for Nγ higher than that seen using the 60 estimation methods. Finally, given the regular use of the in situ standard penetration test (SPT) on sands, and based on a series of analyses using finite elements, a simplified method in terms of the SPT N-values is proposed for estimation of Nγ in footings on sands.

scholarly journals Climate-dependent propagation of precipitation uncertainty into the water cycle

2020 ◽  
Author(s):  
Ali Fallah ◽  
Sungmin O ◽  
Rene Orth
Keyword(s):  
Hydrological Model ◽  
Water Cycle ◽  
State Of The Art ◽  
Rain Gauge ◽  
Multiple Sources ◽  
Current State ◽  
Wide Range ◽  
The Impact ◽  
Conceptual Hydrological Model

Abstract. Precipitation is a crucial variable for hydro-meteorological applications. Unfortunately, rain gauge measurements are sparse and unevenly distributed, which substantially hampers the use of in-situ precipitation data in many regions of the world. The increasing availability of high-resolution gridded precipitation products presents a valuable alternative, especially over gauge-sparse regions. Nevertheless, uncertainties and corresponding differences across products can limit the applicability of these data. This study examines the usefulness of current state-of-the-art precipitation datasets in hydrological modelling. For this purpose, we force a conceptual hydrological model with multiple precipitation datasets in > 200 European catchments. We consider a wide range of precipitation products, which are generated via (1) interpolation of gauge measurements (E-OBS and GPCC V.2018), (2) combination of multiple sources (MSWEP V2) and (3) data assimilation into reanalysis models (ERA-Interim, ERA5, and CFSR). For each catchment, runoff and evapotranspiration simulations are obtained by forcing the model with the various precipitation products. Evaluation is done at the monthly time scale during the period of 1984–2007. We find that simulated runoff values are highly dependent on the accuracy of precipitation inputs, and thus show significant differences between the simulations. By contrast, simulated evapotranspiration is generally much less influenced. The results are further analysed with respect to different hydro-climatic regimes. We find that the impact of precipitation uncertainty on simulated runoff increases towards wetter regions, while the opposite is observed in the case of evapotranspiration. Finally, we perform an indirect performance evaluation of the precipitation datasets by comparing the runoff simulations with streamflow observations. Thereby, E-OBS yields the best agreement, while furthermore ERA5, GPCC V.2018 and MSWEP V2 show good performance. In summary, our findings highlight a climate-dependent propagation of precipitation uncertainty through the water cycle; while runoff is strongly impacted in comparatively wet regions such as Central Europe, there are increasing implications on evapotranspiration towards drier regions.

In situ testing and its application to foundation engineering

1986 ◽  
Vol 23 (4) ◽  
pp. 573-594 ◽  
Author(s):  
P. K. Robertson
Keyword(s):  
Test Methods ◽  
Load Test ◽  
Foundation Engineering ◽  
Penetration Test ◽  
In Situ Testing ◽  
Cone Penetration ◽  
Specific Test ◽  
Pressuremeter Test ◽  
In Situ Test

The status of in situ testing and its application to foundation engineering are presented and discussed. The in situ test methods are discussed within the framework of three groups: logging, specific, and combined test methods. The major logging test methods discussed are standard penetration test (SPT), cone penetration test (CPT), and the flat plate dilatometer test (DMT). The major specific test methods discussed are the prebored pressuremeter test (PMT), the self-bored pressuremeter test (SBPMT), and the screw plate load test (SPLT). Discussion is also presented on recent tests that combine features of logging tests (using the CPT) and specific tests (e.g. the seismic, the electrical resistivity/dielectric, and the lateral stress sensing cone penetration tests). A brief discussion is also presented on the applicability, as perceived by the author, of existing in situ test methods and the future of in situ testing applied to foundation engineering. Key words: in situ testing, foundation engineering, penetration testing, pressuremeter.

Identification of the dynamic properties of a reinforced concrete coupled shear wall residential high-rise building

2012 ◽  
Vol 39 (6) ◽  
pp. 631-642 ◽  
Author(s):  
Natthapong Areemit ◽  
Michael Montgomery ◽  
Constantin Christopoulos ◽  
Agha Hasan
Keyword(s):  
Reinforced Concrete ◽  
State Of The Art ◽  
Dynamic Properties ◽  
Shear Wall ◽  
Full Scale ◽  
Design Parameters ◽  
High Rise ◽  
Coupled Shear Wall ◽  
Current State

As high-rise buildings increase with height and slenderness, they become increasingly sensitive to dynamic vibrations, and therefore the natural frequency of vibration and damping ratio are very important design parameters, as they directly impact the design wind forces. Recent advances in sensing and computing technology have made it possible to monitor the dynamic behaviour of full-scale structures, which was not possible in the past. Full-scale validation of the dynamic properties is useful for high-rise designers to verify design assumptions, especially since recent measurements have shown that damping decreases as the height of the building increases, and in situ damping measurements have been lower than many currently assumed design values, potentially leading to unconservative designs. A 50-storey residential building in downtown Toronto, with a reinforced concrete coupled shear wall lateral load resisting system with outriggers was monitored using current state-of-the-art sensing technologies and techniques to determine, in situ, the dynamic properties under real wind loads. The in situ measurements were then compared with results obtained using current state-of-the-art computer modelling techniques.

The Comparative Sensitivity of Intra-oral, in vitro, and Animal Models in the ‘Profile’ Evaluation of Topical Fluorides

1992 ◽  
Vol 71 (3_suppl) ◽  
pp. 884-894 ◽  
Author(s):  
D.J. White
Keyword(s):  
Animal Models ◽  
Basic Research ◽  
Test Methods ◽  
Appropriate Use ◽  
Rapid Methods ◽  
In Situ Methods ◽  
Historical Basis ◽  
Topical Fluorides

The development of predictive and rapid methods for the assessment of the anticaries activity of topical fluorides has been a longstanding objective of caries researchers. These methods can provide useful benefits in a number of applications, ranging from the identification of novel agents to progress into clinical testing to the regulatory screening of commercial product variations. In the latter applications, combinations of test methods (so-called profiles) are used by manufacturers to prove that changes in formulations do not alter the efficacy of the products. Historically, combinations of in vitro and animal models have been used for basic research as well as for profile testing purposes; however, in recent years, the use of intra-oral or in situ models has increased. In this paper, in vitro, animal, and in situ methods are reviewed in terms of the historical basis for their development, protocols currently used in testing, and the primary advantages and limitations of each as applied to ‘profile’ applications. Recommendations are provided concerning circumstances for the appropriate use of modern test methods in formulation screening.

In Situ Sensors for CIGS Deposition and Manufacture

2005 ◽  
Vol 865 ◽  
Author(s):  
I.L Repins ◽  
N. Gomez ◽  
L. Simpson ◽  
B. Joshi
Keyword(s):  
Process Control ◽  
State Of The Art ◽  
Control Optimization ◽  
Current State ◽  
In Situ Sensors ◽  
Industrial Environments ◽  
In Situ Diagnostics

AbstractIn situ sensors are an important tool for process control, optimization, and documentation, both in the laboratory and industrial environments. Their further application to deposition of CuInxGa1-xSe2 (CIGS) for photovoltaics is particularly important, as record device efficiencies produced in the laboratory have yet to be replicated in manufacturing. This paper provides an overview of the current state of the art of in situ diagnostics for devices based on coevaporated CIGS.

scholarly journals Climate-dependent propagation of precipitation uncertainty into the water cycle

2020 ◽  
Author(s):  
Ali Fallah Maraghi ◽  
Sungmin Oh ◽  
Rene Orth
Keyword(s):  
Hydrological Modeling ◽  
Hydrological Model ◽  
Water Cycle ◽  
State Of The Art ◽  
Rain Gauge ◽  
Multiple Sources ◽  
Current State ◽  
Wide Range ◽  
The Impact

<p>Precipitation is a crucial variable for hydro-meteorological applications. Unfortunately, rain gauge measurements are sparse and unevenly distributed, which substantially hampers the use of in-situ precipitation data in many regions of the world. The increasing availability of high-resolution gridded precipitation products presents a valuable alternative, especially over gauge-sparse regions. Nevertheless, uncertainties and corresponding differences across products can limit the applicability of these data. This study examines the usefulness of current state-of-the-art precipitation datasets in hydrological modeling. For this purpose, we force a conceptual hydrological model with multiple precipitation datasets in >200 European catchments. We consider a wide range of precipitation products, which are generated via (1) interpolation of gauge measurements (E-OBS and GPCC V.2018), (2) data assimilation into reanalysis models (ERA-Interim, ERA5, and CFSR) and (3) combination of multiple sources (MSWEP V2). For each catchment, runoff and evapotranspiration simulations are obtained by forcing the model with the various precipitation products. Evaluation is done at the monthly time scale during the period of 1984-2007. We find that simulated runoff values are highly dependent on the accuracy of precipitation inputs, and thus show significant differences between the simulations. By contrast, simulated evapotranspiration is generally much less influenced. The results are further analysed with respect to different hydro-climatic regimes. We find that the impact of precipitation uncertainty on simulated runoff increases towards wetter regions, while the opposite is observed in the case of evapotranspiration. Finally, we perform an indirect performance evaluation of the precipitation datasets by comparing the runoff simulations with streamflow observations. Thereby, E-OBS yields the best agreement, while furthermore ERA5, GPCC V.2018 and MSWEP V2 show good performance. In summary, our findings highlight a climate-dependent propagation of precipitation uncertainty through the water cycle; while runoff is strongly impacted in comparatively wet regions such as Central Europe, there are increasing implications on evapotranspiration towards drier regions.</p>

Evaluation of Liquefaction Potential Using Neural Networks Based on Adaptive Resonance Theory

2005 ◽  
Vol 1936 (1) ◽  
pp. 192-200 ◽  
Author(s):  
Pradeep U. Kurup ◽  
Amit Garg
Keyword(s):  
Neural Networks ◽  
Adaptive Resonance Theory ◽  
Fuzzy Artmap ◽  
Multilayer Perceptrons ◽  
Penetration Test ◽  
Resonance Theory ◽  
Liquefaction Potential ◽  
Adaptive Resonance ◽  
Artificial Neural

The incomprehensible loss of lives and extensive damages to transportation facilities caused by earthquakes emphasize the need for robust and reliable methods for evaluating the liquefaction potential of sites. Traditional methods for evaluating liquefaction potential are based on correlating data from the standard penetration test (blow count, N), cone penetration test (cone resistance, qc), or the shear wave velocity ( Vs) with the cyclic stress ratio. These methods are unable to incorporate the complex influence of various soil and in situ state parameters. This problem encouraged the development of numerous nontraditional methods such as artificial neural networks that try to learn and account for the influence of various soil and in situ state properties. The possibility of using neural networks based on adaptive resonance theory (ART) for the prediction of liquefaction potential was explored. These networks have been shown to be far more efficient and reliable than the commonly used backpropagation artificial neural network and other multilayer perceptrons. Two Fuzzy ARTMAP (FAM) models were developed and tested with qc and Vs data obtained from past case histories. The qc-and Vs-based FAM models gave overall successful prediction rates of 98% and 97%, respectively. The promising results obtained by the FAM models exemplify the potential of nontraditional computing methods for evaluating liquefaction potential.

scholarly journals STN-Homography: Direct Estimation of Homography Parameters for Image Pairs

2019 ◽  
Vol 9 (23) ◽  
pp. 5187 ◽  
Author(s):  
Qiang Zhou ◽  
Xin Li
Keyword(s):  
Neural Network ◽  
State Of The Art ◽  
Estimation Error ◽  
Estimation Methods ◽  
Real Time Processing ◽  
Current State ◽  
Potential Applications ◽  
Homography Estimation ◽  
Image Pairs ◽  
Magnitude Difference

Estimating a 2D homography from a pair of images is a fundamental task in computer vision. Contrary to most convolutional neural network-based homography estimation methods that use alternative four-point homography parameterization schemes, in this study, we directly estimate the 3 × 3 homography matrix value. We show that after coordinate normalization, the magnitude difference and variance of the elements of the normalized 3 × 3 homography matrix is very small. Accordingly, we present STN-Homography, a neural network based on spatial transformer network (STN), to directly estimate the normalized homography matrix of an image pair. To decrease the homography estimation error, we propose hierarchical STN-Homography and sequence STN-homography models in which the sequence STN-Homography can be trained in an end-to-end manner. The effectiveness of the proposed methods is demonstrated based on experiments on the Microsoft common objects in context (MSCOCO) dataset, and it is shown that they significantly outperform the current state-of-the-art. The average processing time of the three-stage hierarchical STN-Homography and the three-stage sequence STN-Homography models on a GPU are 17.85 ms and 13.85 ms, respectively. Both models satisfy the real-time processing requirements of most potential applications.

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