The chemical evolution in a model of contracting cloud

The evolution of the different chemical species are followed in a model of contracting interstellar cloud. The central density increases from n = 10 cm^–3 diffuse initial cloud model to a dense cloud with central density number of n >- 10⁵ cm^–3 after a time of 1.2 × 10⁷ yr. A network of 622 reactions has been involved. The chemistry of the cloud is integrated simultaneously with the hydrodynamic equations of contraction.The results predict that the different molecular species increase in abundance as the contraction proceeds. The species which enhance significantly are CO, HCO, CS and NO. The fractional abundances of many of the other molecular species increase distinctly with contraction, e.g. CH, C₂H, CN, SO₂, CO₂, H₂O, C₂, NH₃, HCN, SO, OCS and SN. The transformation of the initial diffuse cloud model with small abundances of molecular species to a dense molecular cloud with enhancement of the different molecular species is confirmed. The results predict good agreements of our results with both the observations and other theoretical studies.     

Evaporation estimation using artificial neural networks and adaptive neuro-fuzzy inference system techniques

Evaporation, as a major component of the hydrologic cycle, plays a key role in water resources development and management in arid and semi-arid climatic regions. Although there are empirical formulas available, their performances are not all satisfactory due to the complicated nature of the evaporation process and the data availability. This paper explores evaporation estimation methods based on artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) techniques. It has been found that ANN and ANFIS techniques have much better performances than the empirical formulas (for the test data set, ANN R² = 0.97, ANFIS R² = 0.92 and Marciano R² = 0.54). Between ANN and ANFIS, ANN model is slightly better albeit the difference is small. Although ANN and ANFIS techniques seem to be powerful, their data input selection process is quite complicated. In this research, the Gamma test (GT) has been used to tackle the problem of the best input data combination and how many data points should be used in the model calibration. More studies are needed to gain wider experience about this data selection tool and how it could be used in assessing the validation data.     

Quantification of seismic potential failure modes in concrete dams

A comprehensive framework for potential failure modes (PFM) identification and quantification of concrete dams subjected to seismic excitation is presented. A quantifiable indicator of PFM is presented in the context of both linear and nonlinear analyses. As an illustrative example, a thin arch dam subjected to a set of ground motions at different seismic intensity levels is investigated and corresponding PFM quantified. An outcome of this analysis is the probabilistic‐based correlation between linear and nonlinear analyses and identification of the optimal intensity measure parameter. This study, is an adaptation and extension of well‐accepted procedures defined by the performance‐based earthquake engineering paradigm in buildings. Copyright © 2015 John Wiley & Sons, Ltd.     

Determining the Gravitational Gradient Tensor Using Satellite-Altimetry Observations over the Persian Gulf

With the advent of satellite altimetry in 1973, new scientific applications became available in oceanography, climatology, and marine geosciences. Moreover, satellite altimetry provides a significant source of information facilitated in the geoid determination with a high accuracy and spatial resolution. The information from this approach is a sufficient alternate for marine gravity data in the high-frequency modeling of the marine gravity field quantities. The gravity gradient tensor, consisting of the second-order partial derivatives of the gravity potential, provides more localized information than gravity measurements. Marine gravity observations always carry a high noise level due to environmental effects. Moreover, it is not possible to model the high frequencies of the Earth's gravity field in a global scale using these observations. In this article, we introduce a novel approach for a determination of the gravity gradient tensor at sea level using satellite altimetry. Two numerical techniques are applied and compared for this purpose. In particular, we facilitate the radial basis functions (RBFs) and the harmonic splines. As a case study, the gravitational gradient tensor is determined and results presented in the Persian Gulf. Validation of results reveals that the solution of the harmonic spline approach has a better agreement with a theoretical zero-value of the trace of the Marussi gravitational gradient tensor. However, the data-adaptive technique in the RBF approach allows more efficient selection of the parameters and 3-D configuration of RBFs compared to a fixed parameterization by the harmonic splines.     

A review of volunteered geographic information quality assessment methods

With the ubiquity of advanced web technologies and location-sensing hand held devices, citizens regardless of their knowledge or expertise, are able to produce spatial information. This phenomenon is known as volunteered geographic information (VGI). During the past decade VGI has been used as a data source supporting a wide range of services, such as environmental monitoring, events reporting, human movement analysis, disaster management, etc. However, these volunteer-contributed data also come with varying quality. Reasons for this are: data is produced by heterogeneous contributors, using various technologies and tools, having different level of details and precision, serving heterogeneous purposes, and a lack of gatekeepers. Crowd-sourcing, social, and geographic approaches have been proposed and later followed to develop appropriate methods to assess the quality measures and indicators of VGI. In this article, we review various quality measures and indicators for selected types of VGI and existing quality assessment methods. As an outcome, the article presents a classification of VGI with current methods utilized to assess the quality of selected types of VGI. Through these findings, we introduce data mining as an additional approach for quality handling in VGI.     

Temporal variations of tides on the west coast of Great Britain

Summary. Temporal variations of tides are investigated by analysing tidal observations from five ports on the west coast of Great Britain. Variations considered here are those occurring in the semi-diurnal species daily, in the tidal constituents resolved from analyses of 29 day sets over a period of two years, 1980–81, and in the tidal constituents resolved from 1 yr sets over a period of 19 yr. The time variations of tidal constituents are mainly due to inseparable terms grouping with the principal term due to the short length of data and the insufficiency of the procedures to account for them. Surges and surge-tide interaction are affecting the resolution of tides. Time variations of constituents of the diurnal species induced by non-tidal forces are spatially consistent. The use of equilibrium relationships to account for modulations of principal constituents by waves separable in an 18.61 yr nodal cycle improves the analysis. However, the modulation is smaller in the real tide than in the equilibrium tide. When the application of this principle is extended to a wider frequency band to cover constituents which cannot be resolved from one month of observations, it may produce the opposite effect. These problems start compounding with decreasing length of data, i.e. increasing band width of resolution.
Functional approximations of interaction coefficients (bi-admittance) of non-linear tides, similar to the response (admittance) of linear tides are computed for semi-diurnal, fourth-diurnal and sixth-diurnal bands. These functional estimates may be used to interpolate unseparable constituents to improve the quality of analyses. The results are consistent with the fact that the response of the sea does not change in a narrow frequency band covering a nodal cycle of the Moon. The change in the equilibrium relationship between the principal term and its nodal term can be interpreted in terms of the damping effect of bottom friction.     

Determination of the rate and volume of leakage using the slopes of time-drawdown data

Quantification of leakage is very important in the selection and design of the remediation systems of leaky aquifers that receive contaminated leakage. This is an approach for the calculation of leakage using only two slopes of time-drawdown data. These slopes represent before and after the start of leakage, and are applied to four examples. Results generally agree with those determined by the Hantush approach. Comparison of the two approaches, however, shows that the Hantush approach quantifies leakage using three aquifer parameters (transmissivity, storativity, and leakage factor), the value of which depend on the pumping test method used; it assumes constant hydraulic head in the aquifer supplying leakage, which may not be valid under field conditions; and it ignores differences between the viscosities of the leakage water and the aquifer water, which influence the leakage rate. The proposed approach is free from all three limitations.     

Geologic hazards along part of Al-sayl–Alkabeir Al-Jammum road in Saudi Arabia

 The geological hazards along part of Al-Sayl Alkabeir Al-Jammum road, western Saudi Arabia, were studied by the use of the sterographic projection to define the types of possible failures and the magnitude of safety factor on each slope face. The studied area consists of granite and granodiorite rocks that were cut by acidic and basic dikes. There are four sets of structural discontinuities which, besides a few strike slip faults, constitute the planes of weakness that lead to a variety of possible mode failures. The stability analysis indicates that sections of the road are unstable as their cut slopes exceed the maximum safe slope angles which range between 65° and 73°. Received: 16 June 1998 · Accepted: 2 March 1999     

Seasonal Short‐Term Prediction of Dissolved Oxygen in Rivers via Nature‐Inspired Algorithms

This study challenges the use of three nature‐inspired algorithms as learning frameworks of the adaptive‐neuro‐fuzzy inference system (ANFIS) machine learning model for short‐term modeling of dissolved oxygen (DO) concentrations. Particle swarm optimization (PSO), butterfly optimization algorithm (BOA), and biogeography‐based optimization (BBO) are employed for developing predictive ANFIS models using seasonal 15 min data collected from the Rock Creek River in Washington, DC. Four independent variables are used as model inputs including water temperature (T), river discharge (Q), specific conductance (SC), and pH. The Mallow's Cp and R² parameters are used for choosing the best input parameters for the models. The models are assessed by several statistics such as the coefficient of determination (R²), root‐mean‐square error (RMSE), Nash–Sutcliffe efficiency, mean absolute error, and the percent bias. The results indicate that the performance of all‐nature‐inspired algorithms is close to each other. However, based on the calculated RMSE, they enhance the accuracy of standard ANFIS in the spring, summer, fall, and winter around 13.79%, 15.94%, 6.25%, and 12.74%, respectively. Overall, the ANFIS‐PSO and ANFIS‐BOA provide slightly better results than the other ANFIS models.