Petrology of ultramafic rocks and Mg-rich carbonate minerals in southeast of Dehshir,Central Iran

The study area is located southeast of Dehshir between the Urumieh-Dokhtar Magmatic Arc and Nain-Baft Ophiolite Belt comprising the Nain, Dehshir, Shahr Babak, and Baft ophiolite complexes. The Dehshir Ophiolitic Complex which obducted in the Late Cretaceous, consists mainly of ultramafic rocks. These remnants of oceanic crust are extensively faulted and fractured. The severe faulting and brecciating of the ophiolite sequence have undergone high-grade alteration and changed it to the tectonic mélange. The Dehshir colored mélange is bounded to the west by Dehshir fault which is a right-lateral offset of the Nain-Baft suture. In this research, the petrographic studies of the area showed that the ultramafic rocks consist mainly of dunite and harzburgite intruded by diabasic dikes. Syntectonic hydrothermal fluids circulated throughout these rocks. Migration of Mg-rich fluids and hydrothermal brecciating occurred within highly altered and brecciated zones. Magnesite precipitated from hydrothermal solutions and formed the massive, lenticular, and vein-type ore deposits in serpentinized-hosted rocks. Later on, magnesite turned into hydromagnesite due to hydration at the lower depths near the surface. According to the X-ray diffraction and X-ray fluorescence analysis, hydromagnesite is the most dominant and widely occurring Mg-rich carbonate mineral in this area. The main alteration is serpentinization but birbiritization also occurs as a result of interaction between fluids and ultramafic rocks.     

Neural network prediction of solar cycle 24

The ability to predict the future behavior of solar activity has become extremely import due to its effect on the environment near the Earth.Predictions of both the amplitude and timing of the next solar cycle will assist in estimating the various consequences of space weather.The level of solar activity is usually expressed by international sunspot number (Rz).Several prediction techniques have been applied and have achieved varying degrees of success in the domain of solar activity prediction.We predict a...     

On lattice reduction algorithms for solving weighted integer least squares problems: comparative study

Decorrelation or reduction theory deals with identifying appropriate lattice bases that aid in accelerating integer search to find the optimal integer solution of the weighted integer least squares problem. Orthogonality defect has been widely used to measure the degree of orthogonality of the reduced lattice bases for many years. This contribution presents an upper bound for the number of integer candidates in the integer search process. This upper bound is shown to be a product of three factors: (1) the orthogonality defect, (2) the absolute value of the determinant of the inverse of the generator matrix of the lattice, and (3) the radius of the search space raised to the power of the dimension of the integer ambiguity vector. Four well-known decorrelation algorithms, namely LLL, LAMBDA, MLAMBDA, and Seysen, are compared. Many simulated data with varying condition numbers and dimensions as well as real GPS data show that the Seysen reduction algorithm reduces the condition number much better than the other algorithms. Also, the number of integer candidates, before and after the reduction process, is counted for all algorithms. Comparing the number of integer candidates, condition numbers, and orthogonality defect reveals that reducing the condition number and the orthogonality defect may not necessarily result in decreasing the number of integer candidates in the search process. Therefore, contrary to the common belief, reducing the orthogonality defect and condition number do not always result in faster integer least squares estimation. The results indicate that LAMBDA and MLAMBDA perform much better in reducing the number of integer candidates than the other two algorithms, despite having a larger orthogonality defect and condition number in some cases. Therefore, these two algorithms can speed up the integer least squares estimation problem in general and the integer ambiguity resolution problem in particular.     

Sensitivity analysis of the seismic demands of RC moment resisting frames to different aspects of ground motions

A weight vector representing the relative importance of various characteristics of ground motions (GMs) and a conditioning intensity measure (IM) are required to be able to use the generalized conditional IM framework for the purpose of GM selection. An inappropriate weight vector may result in the biased distributions of some important characteristics of GMs and, consequently, the bias in the structural responses. This article aims to provide the analyst with the understanding of which properties of GMs are important in capturing the accurate structural responses, to specifically assign a suitable weight to them and to select an appropriate conditioning IM as well. To this end, 4 reinforced concrete buildings, located at the site in which the seismic hazard is dominated by shallow crustal earthquakes, are considered. The findings reveal that the appropriate weight vectors depend on the characteristics of the employed structural systems. In addition, the role played by each IM in capturing the true structural responses changes over different earthquake intensity levels implying that different weight vectors are required over different earthquake levels. Furthermore, this study shows that, even in case of shorter‐duration GMs from shallow events, GM duration should be incorporated in GM selection as it has effects on the peak‐based structural responses in the earthquake levels beyond the level of 2%‐in‐50‐years. Specifically, the findings reveal that in case of shallow events, unlike large magnitude earthquakes, the shorter the duration of GM the more rapid release of energy and, consequently, the larger the peak‐based structural responses.     

Data-snooping procedure applied to errors-in-variables models

The theory of Baarda’s data snooping — normal and F tests respectively based on the known and unknown posteriori variance — is applied to detect blunders in errors-invariables (EIV) models, in which gross errors are in the vector of observations and/or in the coefficient matrix. This work is a follow-up to an earlier work in which we presented the formulation of the weighted total least squares (WTLS) based on the standard least squares theory. This method allows one to directly apply the existing body of knowledge of the least squares theory to the errors-in-variables models. Among those applications, data snooping methods in an EIV model are of particular interest, which is the subject of discussion in the present contribution. This paper generalizes the Baarda’s data snooping procedure of the standard least squares theory to an EIV model. Two empirical examples, a linear regression model and a 2-D affine transformation, using simulated and real data are presented to show the efficacy of the presented formulation. It is highlighted that the method presented is capable of detecting outlying equations (rather than outlying observations) in a straightforward manner. Further, the WTLS method can be used to handle different TLS problems. For example, the WTLS problem for the conditions and mixed models, the WTLS problem subject to constraints and variance component estimation for an EIV model can easily be established. These issues are in progress for future publications.     

Sustainable soil stabilisation with ground granulated blast-furnace slag activated by olivine and sodium hydroxide

Acta Geotechnica - Ground granulated blast-furnace slag (GGBS), activated with olivine (Mg2SiO4) and sodium hydroxide (NaOH), was used to stabilise a clayey soil. Mechanical and microstructural...     

Optimal Allocation of Water Resources Using a Two-Stage Stochastic Programming Method with Interval and Fuzzy Parameters

Natural Resources Research - Efficient water allocation is one of the most prominent issues in water resources management. In this research, a two-stage interval-parameter stochastic fuzzy...     

Control of Cambrian evaporites on fracturing in fault-related anticlines in the Zagros fold-and-thrust belt

Orientation and distribution of fractures in the Oligocene–Early Miocene Asmari Formation (a major reservoir rock of the Zagros petroleum system) were investigated in two anticlines of the Zagros fold-and-thrust belt. The Sim and Kuh-e-Asmari anticlines developed in the areas of the Zagros characterized by the occurrence and absence of Cambrian evaporites at the bottom of the stratigraphic pile, respectively. The aim was to outline major differences in terms of fracture spacing and saturation. Organic matter maturity and clay minerals-based geothermometers suggest that the depth of deformation for the top of the Asmari Formation in the Kuh-e-Asmari anticline was in the range of 1.5–2.7 km assuming a geothermal gradient of 22.5 °C/km. The Asmari Formation in the Sim anticline probably experienced a slightly deeper sedimentary burial (maximum 3 km) with a geothermal gradient of 20 °C/km. The spacing of fractures is generally 2–3 times larger (i.e., strain accommodated by fracturing is smaller) in the Sim anticline than in the Kuh-e-Asmari anticline. This is consistent with regional geological studies, analogue, and numerical models that suggest that thrust faults geometry and related folds are markedly different in the absence or presence of a weak decòllement (evaporites). The larger spacing in the Sim anticline is also consistent with higher temperature predicted for the Asmari Formation in this area. By contrast, the orientation of fractures with respect to the fold axes is the same in both anticlines. The fracture systems are rather immature in both anticlines. The amount and density of fractures in the twofolds are controlled by regional (occurrence/absence of salt and probably different burial), rather than local features (fold geometry).