Inverse Analysis of Deep Excavation Using Differential Evolution Algorithm

This paper presents the applications of the differential evolution (DE) algorithm in back analysis of soil parameters for deep excavation problems. A computer code, named Python‐based DE, is developed and incorporated into the commercial finite element software ABAQUS, with a parallel computing technique to run an FE analysis for all trail vectors of one generation in DE in multiple cores of a cluster, which dramatically reduces the computational time. A synthetic case and a well‐instrumented real case, that is, the Taipei National Enterprise Center (TNEC) project, are used to demonstrate the capability of the proposed back‐analysis procedure. Results show that multiple soil parameters are well identified by back analysis using a DE optimization algorithm for highly nonlinear problems. For the synthetic excavation case, the back‐analyzed parameters are basically identical to the input parameters that are used to generate synthetic response of wall deflection. For the TNEC case with a total of nine parameters to be back analyzed, the relative errors of wall deflection for the last three stages are 2.2, 1.1, and 1.0%, respectively. Robustness of the back‐estimated parameters is further illustrated by a forward prediction. The wall deflection in the subsequent stages can be satisfactorily predicted using the back‐analyzed soil parameters at early stages. Copyright © 2014 John Wiley & Sons, Ltd.     

School vulnerability to disaster: examination of school closure,demographic, and exposure factors in Hurricane Ike’s wind swath

Damage and destruction to schools from climate-related disasters can have significant and lasting impacts on curriculum and educational programs, educational attainment, and future income-earning potential of affected students. As such, assessing the potential impact of hazards is crucial to the ability of individuals, households, and communities to respond to natural disasters, extreme events, and economic crises. Yet, few studies have focused on assessing the vulnerability of schools in coastal regions of the USA. Using Hurricane Ike’s tropical storm wind swath in the State of Texas as our study area, we: (1) assessed the spatial distribution patterns of school closures and (2) tested the relationship between school closure and vulnerability factors (namely physical exposure and school demographics) using zero-inflated negative binomial regression models. The regression results show that higher probabilities of hurricane strikes, more urbanized school districts, and school districts located in coastal counties on the right side of Ike’s path have significant positive associations with an increase in the number of school closure days. Socioeconomic characteristics were not significantly associated with the number of days closed, with the exception of proportion of Hispanic youth in schools, a result which is not supported by the social vulnerability literature. At a practical level, understanding how hurricanes may adversely impact schools is important for developing appropriate preparedness, mitigation, recovery, and adaptation strategies. For example, school districts on the right side of the hurricane track can plan in advance for potential damage and destruction. The ability of a community to respond to future natural disasters, extreme events, and economic crises depends in part on mitigating these adverse effects.     

Über die Verteilung der aus Gezeitenbeobachtungen bestimmten gravimetrischen Faktoren in Europa

auamaumuu am, n u a¶rt;u nuu n ¶rt;a ₂, ₂, ₁ u ₁ (u. 1–4). na ¶rt;a ¶rt;am au ¶rt;um au an¶rt;u mu naam. a n¶rt;aam unam nu nuu nna m uu u u mmu mam ¶rt; uu u a a mau n.

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Vorgetragen am 2. Internationalen Symposium Geodäsie und Physik der Erde, Potsdam, Mai 1973.     

Neutron Stars with a Quark Core. II. Basic Integral and Structural Parameters

A broad sample of computed realistic equations of state of superdense matter with a quark phase transition is used to construct a series of models of neutron stars with a strange quark core. The integral characteristics of the stellar configurations are obtained: gravitational mass, rest mass, radius, relativistic moment of inertia, and red shift from the star's surface, as well as the mass and radius of the quark core within the allowable range of values for the central pressure. The parameters of some of the characteristic configurations of the calculated series are also given and these are studied in detail. It is found that a new additional region of stability for neutron stars with strange quark cores may exist for some models of the equation of state.     

Cloud effects on air-sea interactions during the 1979 Indian summer monsoon as studied from satellite observations

Summary The Indian summer monsoon, one of the earth's most vigorous and energetic seasonally occurring weather events, influences the global atmospheric circulation. Its onset, duration, and intensity are governed by large- and meso-scale geophysical processes, such as surface solar heating and air-sea interactions. In this paper, using innovative combinations of satellite sensor data, we investigate some of these fundamental processes which are closely tied to clouds and control the monsoon system's evolution. The study, which focuses on the monsoon period of June, 1979, examines the low-frequency variability of clouds and their effects on air-sea processes through an analysis of the complex influence clouds play on the surface heat and water budgets. First, the effects of clouds on both the solar and longwave components of the surface radiation budget are assessed using a cloud radiative forcing parameter. While the effects of clouds on the long-wave irradiance act in a manner opposite to their effects on the shortwave irradiance, only a partial compensation is found to take place and the net effect results in a maximum cloud forcing of 60 Wm^–2 in the southwestern Arabian Sea. Second, employing satellite-derived precipitation and evaporation estimates, the paper analyzes the net surface fresh water budget variability around the monsoon onset. This budget is important in that fresh water affects the upper ocean density distribution and, consequently, the thermohaline circulation. Two regions are found to dominate the analysis: the western Arabian Sea, where evaporation is dominant by more than 10 mm day^–1, and the eastern Arabian Sea, where precipitation is dominant by more than 10 mm day^–1. Thus, a strong zonal gradient of fresh water at the surface is established during the monsoon. The last topic investigated is the intraseasonal variability of convection as analyzed using a cloud parameter indicative of deep convection. Cloud oscillations of 30–50 days, associated with the different phases of the monsoon, are found to propagate northward in the eastern Indian Ocean and eastward in the Bay of Bengal. Our analysis not only supports the hypothesis that the 30–50-day oscillation is driven by deep convection but also, and more importantly, suggests that the ocean thermal forcing is modulated by 30–50-day oscillations through cloud-induced surface radiative forcing. Although the results presented are limited in scope and preliminary because of the diffculty in quantifying the accuracy of the parameters examined, they do demonstrate: 1) the role of clouds in modulating the surface heat and water budgets, 2) the advantage of using combinations of multi-sensor and multi-platform satellite observations to quantify interrelated surface heat/water budget processes, and 3) the potential to examine the intraseasonal variability of air-sea interaction processes associated with the monsoon, even though these processes are not directly measurable from space.With 6 FiguresB. DiJulio passed away in September 1990.     

A NEW APPROACH TO THE INVERSION OF SEISMIC DATA*

A new inversion method for seismic reflection data is based on impedance concepts and uses transformations to reduce the essentially non-linear problem to a linear eigenvalue formulation without approximation. A set of reflection data has been inverted using this method. The characteristic impedances of the layers so determined are compared with log data from a reference borehole.     

Relationship of galaxies from the second Byurakan survey to Zwicky clusters. II. Discussion

We analyze the data presented in a previous paper by Gyulzadyan and Petrosian, and discuss the results of a statistical investigation of the relationship between SBS galaxies and Zwicky clusters. The main results are that SBS galaxies follow the overall galaxy distribution in clusters and they do not avoid any type of Zwicky cluster. There is a significantly higher probability of finding SBS galaxies occurring in medium compact clusters than in open clusters. They also follow the well-established morphology-density relation. Earlier morphological type, higher luminosity, larger linear size, and redder SBS galaxies tend to be found in clusters with higher compactness, or in more compact regions of the clusters. The number distribution of SBS galaxies in Zwicky open clusters probably follows the distribution of normal galaxies. The number distribution of SBS galaxies in medium compact and compact clusters shows two-maxima structure. Published in Astrofizika, Vol. 52, No. 2, pp. 225–236 (May 2009).     

Forward induced seismic hazard assessment: application to a synthetic seismicity catalogue from hydraulic stimulation modelling

The M _w 3.2-induced seismic event in 2006 due to fluid injection at the Basel geothermal site in Switzerland was the starting point for an ongoing discussion in Europe on the potential risk of hydraulic stimulation in general. In particular, further development of mitigation strategies of induced seismic events of economic concern became a hot topic in geosciences and geoengineering. Here, we present a workflow to assess the hazard of induced seismicity in terms of occurrence rate of induced seismic events. The workflow is called Forward Induced Seismic Hazard Assessment (FISHA) as it combines the results of forward hydromechanical-numerical models with methods of time-dependent probabilistic seismic hazard assessment. To exemplify FISHA, we use simulations of four different fluid injection types with various injection parameters, i.e. injection rate, duration and style of injection. The hydromechanical-numerical model applied in this study represents a geothermal reservoir with preexisting fractures where a routine of viscous fluid flow in porous media is implemented from which flow and pressure driven failures of rock matrix and preexisting fractures are simulated, and corresponding seismic moment magnitudes are computed. The resulting synthetic catalogues of induced seismicity, including event location, occurrence time and magnitude, are used to calibrate the magnitude completeness M _c and the parameters a and b of the frequency-magnitude relation. These are used to estimate the time-dependent occurrence rate of induced seismic events for each fluid injection scenario. In contrast to other mitigation strategies that rely on real-time data or already obtained catalogues, we can perform various synthetic experiments with the same initial conditions. Thus, the advantage of FISHA is that it can quantify hazard from numerical experiments and recommend a priori a stimulation type that lowers the occurrence rate of induced seismic events. The FISHA workflow is rather general and not limited to the hydromechanical-numerical model used in this study and can therefore be applied to other fluid injection models.     

Nature of the small main belt Asteroid 3169 Ostro

We present a set of rotational lightcurve measurements of the small main belt Asteroid 3169 Ostro. Our observations reveal an unambiguous, double-peaked rotational lightcurve with a peak-to-peak variation up to 1.2±0.05 mag and a synodic period of 6.509±0.001 h. From the large flux variation and the overall shape of the lightcurves, we suggest that 3169 Ostro could be a tightly bound binary or a contact binary, similar to the Trojan Asteroid 624 Hektor. A shape model of this system is proposed on the assumption that 3169 Ostro is a Roche binary described by a pair of homogeneous elongated bodies, with a size ratio of 0.87, in hydrostatic equilibrium and in circular synchronous motion around each other. The direction of the spin axis is determined modulo 180° by its J2000 ecliptic coordinates λ₀=50±10°, β₀=±54±5°. The binary interpretation and the pole solution adequately fit the earlier photometric observations made in 1986 and 1988. However, additional supporting lightcurves are highly desirable especially in the next mutual events occurrence of 2008 and 2009 in order to remove the pole ambiguity and to confirm unambiguously the binary nature of 3169 Ostro.     

A comparative study of sequential minimal optimization-based support vector machines,vote feature intervals,and logistic regression in landslide susceptibility assessment using GIS

Landslide susceptibility assessment using GIS has been done for part of Uttarakhand region of Himalaya (India) with the objective of comparing the predictive capability of three different machine learning methods, namely sequential minimal optimization-based support vector machines (SMOSVM), vote feature intervals (VFI), and logistic regression (LR) for spatial prediction of landslide occurrence. Out of these three methods, the SMOSVM and VFI are state-of-the-art methods for binary classification problems but have not been applied for landslide prediction, whereas the LR is known as a popular method for landslide susceptibility assessment. In the study, a total of 430 historical landslide polygons and 11 landslide affecting factors such as slope angle, slope aspect, elevation, curvature, lithology, soil, land cover, distance to roads, distance to rivers, distance to lineaments, and rainfall were selected for landslide analysis. For validation and comparison, statistical index-based methods and the receiver operating characteristic curve have been used. Analysis results show that all these models have good performance for landslide spatial prediction but the SMOSVM model has the highest predictive capability, followed by the VFI model, and the LR model, respectively. Thus, SMOSVM is a better model for landslide prediction and can be used for landslide susceptibility mapping of landslide-prone areas.