Efficiency analysis of open trench for impact pile driving through a single-variable method

Abstract

The ground vibrations during pile driving operation have a drastic potential to undermine the surrounding structures both in land and reclaimed land. Particularly, reclaimed land necessitates ample application of pile driving due to the weak land condition. To prevent the structural damage, attenuation of the ground vibrations to an allowable level through active isolation of circular open trench is the scope of this study. In this research, finite element simulations of continuous impact pile driving process from the ground surface was executed with particular attention to the pile-soil interaction, and thereby, the efficiency of open trench application in attenuation of the unsafe distance of different structures was surveyed using the vibration sensitivity degree. Regarding the crucial parameters of an open trench (depth, width, and location), it was concluded that a sufficient high depth can attenuate the unsafe distance up to 68%, the trench width variations are less effective, and an average pile-trench distance is the most efficient option. The excavation volume was also concluded as another crucial parameter in open trench design which takes all three parameters into account. The trench depth equal to the pile’s maximum critical depth of vibration was inferred for an optimum design.     

Evaluation of four supervised learning methods for groundwater spring potential mapping in Khalkhal region (Iran) using GIS-based features

One important tool for water resources management in arid and semi-arid areas is groundwater potential mapping. In this study, four data-mining models including K-nearest neighbor (KNN), linear discriminant analysis (LDA), multivariate adaptive regression splines (MARS), and quadric discriminant analysis (QDA) were used for groundwater potential mapping to get better and more accurate groundwater potential maps (GPMs). For this purpose, 14 groundwater influence factors were considered, such as altitude, slope angle, slope aspect, plan curvature, profile curvature, slope length, topographic wetness index (TWI), stream power index, distance from rivers, river density, distance from faults, fault density, land use, and lithology. From 842 springs in the study area, in the Khalkhal region of Iran, 70 % (589 springs) were considered for training and 30 % (253 springs) were used as a validation dataset. Then, KNN, LDA, MARS, and QDA models were applied in the R statistical software and the results were mapped as GPMs. Finally, the receiver operating characteristics (ROC) curve was implemented to evaluate the performance of the models. According to the results, the area under the curve of ROCs were calculated as 81.4, 80.5, 79.6, and 79.2 % for MARS, QDA, KNN, and LDA, respectively. So, it can be concluded that the performances of KNN and LDA were acceptable and the performances of MARS and QDA were excellent. Also, the results depicted high contribution of altitude, TWI, slope angle, and fault density, while plan curvature and land use were seen to be the least important factors.     

The impact of el Nino‐Southern oscillation on the temperature field over Canada: Research note

Abstract

The impact of the two phases of El Niño‐Southern Oscillation (ENSO), namely El Niño and La Niña, on the surface and lower tropospheric temperature fields over Canada is documented. Gridded surface temperature data for 91 years (1900–1990) and 500–1000 hPa thickness data for 49 years (1946–1994) have been analyzed statistically in the context of El Niño, La Niña and normal years.

Using a composite analysis, the present study conclusively demonstrates that significant positive surface temperature anomalies spread eastward from the west coast of Canada to the Labrador coast from the late fall to early spring (November through May) following the onset of El Niño episodes. The accompanying temperatures in the lower troposphere show a transition from the Pacific/North American (PNA) pattern to the Tropical/Northern Hemisphere (TNH) pattern over the North American sector during the same period. Conversely, significant negative surface temperature anomalies spread southeastward from the Yukon and extend into the upper Great Lakes region by the winter season following the onset of La Niña episodes. Furthermore, the lower tropospheric temperatures show a negatively‐phased PNA‐like pattern in early winter which weakens considerably by May of the following year. Thus, while western Canadian surface temperatures are influenced during both phases of ENSO, eastern Canadian surface temperature effects are found during the El Niño phase only. The impact of ENSO on the Canadian surface temperatures is the strongest during the winter season and nearly disappears by spring (April and May). The largest positive (negative) anomalies are found to be centred over two separate regions, one over the Yukon and the other just west of Hudson Bay in the El Niño (La Niña) years. Over western Canada, mean wintertime temperature distribution of the El Niño (La Niña) years is found to be shifted towards warmer (colder) values relative to the distribution of the normal years.

This study suggests the possibility of developing a long‐range forecasting technique for Canada using ENSO related indices.     

Non-stationary extreme value analysis in a changing climate

This paper introduces a framework for estimating stationary and non-stationary return levels, return periods, and risks of climatic extremes using Bayesian inference. This framework is implemented in the Non-stationary Extreme Value Analysis (NEVA) software package, explicitly designed to facilitate analysis of extremes in the geosciences. In a Bayesian approach, NEVA estimates the extreme value parameters with a Differential Evolution Markov Chain (DE-MC) approach for global optimization over the parameter space. NEVA includes posterior probability intervals (uncertainty bounds) of estimated return levels through Bayesian inference, with its inherent advantages in uncertainty quantification. The software presents the results of non-stationary extreme value analysis using various exceedance probability methods. We evaluate both stationary and non-stationary components of the package for a case study consisting of annual temperature maxima for a gridded global temperature dataset. The results show that NEVA can reliably describe extremes and their return levels.     

Comparison of Speed-Up Over Hills Derived from Wind-Tunnel Experiments,Wind-Loading Standards,and Numerical Modelling

We evaluate the accuracy of the speed-up provided in several wind-loading standards by comparison with wind-tunnel measurements and numerical predictions, which are carried out at a nominal scale of 1:500 and full-scale, respectively. Airflow over two- and three-dimensional bell-shaped hills is numerically modelled using the Reynolds-averaged Navier–Stokes method with a pressure-driven atmospheric boundary layer and three different turbulence models. Investigated in detail are the effects of grid size on the speed-up and flow separation, as well as the resulting uncertainties in the numerical simulations. Good agreement is obtained between the numerical prediction of speed-up, as well as the wake region size and location, with that according to large-eddy simulations and the wind-tunnel results. The numerical results demonstrate the ability to predict the airflow over a hill with good accuracy with considerably less computational time than for large-eddy simulation. Numerical simulations for a three-dimensional hill show that the speed-up and the wake region decrease significantly when compared with the flow over two-dimensional hills due to the secondary flow around three-dimensional hills. Different hill slopes and shapes are simulated numerically to investigate the effect of hill profile on the speed-up. In comparison with more peaked hill crests, flat-topped hills have a lower speed-up at the crest up to heights of about half the hill height, for which none of the standards gives entirely satisfactory values of speed-up. Overall, the latest versions of the National Building Code of Canada and the Australian and New Zealand Standard give the best predictions of wind speed over isolated hills.     

Empirical modeling of plate load test moduli of soil via gene expression programming

New empirical models were developed to predict the soil deformation moduli using gene expression programming (GEP). The principal soil deformation parameters formulated were secant (E_s) and reloading (E_r) moduli. The proposed models relate E_s and E_r obtained from plate load-settlement curves to the basic soil physical properties. The best GEP models were selected after developing and controlling several models with different combinations of the influencing parameters. The experimental database used for developing the models was established upon a series of plate load tests conducted on different soil types at depths of 1–24 m. To verify the applicability of the derived models, they were employed to estimate the soil moduli of a part of test results that were not included in the analysis. The external validation of the models was further verified using several statistical criteria recommended by researchers. A sensitivity analysis was carried out to determine the contributions of the parameters affecting E_s and E_r. The proposed models give precise estimates of the soil deformation moduli. The E_s prediction model provides considerably better results in comparison with the model developed for E_r. The simplified formulation for E_s significantly outperforms the empirical equations found in the literature. The derived models can reliably be employed for pre-design purposes.     

Limit states and failure mechanisms of viscous dampers and the implications for large earthquakes

Fluid viscous dampers are used to control story drifts and member forces in structures during earthquake events. These elements provide satisfactory performance at the design‐level or maximum considered earthquake. However, buildings using fluid viscous dampers have not been subjected to very large earthquakes with intensities greater than the design and maximum considered events. Furthermore, an extensive database of viscous damper performance during large seismic events does not exist. To address these issues, a comprehensive analytical and experimental investigation was conducted to determine the performance of damped structures subjected to large earthquakes. A critical component of this research was the development and verification of a detailed viscous damper mathematical model that incorporates limit states. The development of this model and the laboratory and simulation results conclude good correlation with the new model and the damper limit states and provide superior results compared with the typical damper model when considering near collapse evaluation of structures. Copyright © 2010 John Wiley & Sons, Ltd.     

The chronostratigraphy of a quaternary sequence at the distal part of the nile littoral cell,Haifa Bay,Israel

The current detailed chronostratigraphic framework of the last 1 Ma of an eastern Mediterranean sequence (Haifa Bay, Israel) aims to examine the relative roles of sea‐level changes, climate and tectonics. Seven continuous marine cores, up to ～120 m long, were recovered from shallow water depths. The cores were dated by optically stimulated luminescence, ¹⁴C, magnetostratigraphy, ²³⁰Th/²³⁴U, ²⁶Al/¹⁰Be, occurrence of index fossils and correlated to the global sea‐level curve and Marine Isotope Stages (MIS). The sedimentary sequence accumulated during the last ca. 1.0 Ma consists of 21 transgression–regression units with hiatuses between them. Five marine/terrestrial cycles, which occur in the lower part of the sequence, are attributed to the Jaramillo subchron and the Brunhes–Matuyama boundary, and correspond to MIS 29–21. The top ～50 m includes three sedimentary cycles deposited in the last ca. 400 ka. The regressive phases during this interval correspond to Glacial MIS 8, 6 and 2, while the transgressions correspond to Interglacial MIS 11, 7, 5 and 1. Thus, for the first time, this study documents the longest Quaternary succession dated so far in a key area of the Levant, sensitive to global history of sea‐level changes and glacial/interglacial fluctuations. Copyright © 2012 John Wiley & Sons, Ltd.     

Neuro-fuzzy models employing wavelet analysis for suspended sediment concentration prediction in rivers

Abstract

The study of sediment load is important for its implications to the environment and water resources engineering. Four models were considered in the study of suspended sediment concentration prediction: artificial neural networks (ANNs), neuro-fuzzy model (NF), conjunction of wavelet analysis and neuro-fuzzy (WNF) model, and the conventional sediment rating curve (SRC) method. Using data from a US Geological Survey gauging station, the suspended sediment concentration predicted by the WNF model was in satisfactory agreement with the measured data. Also the proposed WNF model generated reasonable predictions for the extreme values. The cumulative suspended sediment load estimated by this model was much higher than that predicted by the other models, and is close to the observed data. However, in the current modelling, the ANN, NF and SRC models underestimated sediment load. The WNF model was successful in reproducing the hysteresis phenomenon, but the SRC method was not able to model this behaviour. In general, the results showed that the NF model performed better than the ANN and SRC models.

Citation Mirbagheri, S. A., Nourani, V., Rajaee, T. & Alikhani, A. (2010) Neuro-fuzzy models employing wavelet analysis for suspended sediment concentration prediction in rivers. Hydrol. Sci. J. 55(7), 1175–1189.