REE mineralization in the carbonatites of the sung valley ultramafic-alkaline-carbonatite complex,Meghalaya, India

The Early Cretaceous Sung Valley Ultramafic-Alkaline-Carbonatite (SUAC) complex intruded the Proterozoic Shillong Group of rocks and located in the East Khasi Hills and West Jaintia Hills districts of Meghalaya. The SUAC complex is a bowl-shaped depression covering an area of about 26 km² and is comprised serpentinised peridotite forming the core of the complex with pyroxenite rim. Alkaline rocks are dominantly ijolite and nepheline syenite, occur as ring-shaped bodies as well as dykes. Carbonatites are, the youngest intrusive phase in the complex, where they form oval-shaped bodies, small dykes and veins. During the course of large scale mapping in parts of the Sung Valley complex, eleven carbonatite bodies were delineated. These isolated carbonatite bodies have a general NW-SE and E-W trend and vary from 20–125 m long and 10–40 m wide. Calcite carbonatite is the dominant variety and comprises minor dolomite and apatite and accessory olivine, magnetite, pyrochlore and phlogopite. The REE-bearing minerals identified in the Sung Valley carbonatites are bastnäsite-(Ce), ancylite-(Ce), belovite-(Ce), britholite-(Ce) and pyrochlore that are associated with calcite and apatite. The presence of REE carbonates and phosphates associated with REE-Nb bearing pyrochlore enhances the economic potential of the Sung Valley carbonatites. Trace-element geochemistry also reveals an enrichment of LREEs in the carbonatites and average ΣREE value of 0.102% in 26 bed rock samples. Channel samples shows average ΣREE values of 0.103 wt%. Moreover, few samples from carbonatite bodies has indicated relatively higher values for Sn, Hf, Ta and U. Since the present study focuses surface evaluation of REE, therefore, detailed subsurface exploration will be of immense help to determine the REE and other associated mineralization of the Sung Valley carbonatite prospect.     

Conditioning generative adversarial networks on nonlinear data for subsurface flow model calibration and uncertainty quantification

Conditioning complex subsurface flow models on nonlinear data is complicated by the need to preserve the expected geological connectivity patterns to maintain solution plausibility. Generative adversarial networks (GANs) have recently been proposed as a promising approach for low-dimensional representation of complex high-dimensional images. The method has also been adopted for low-rank parameterization of complex geologic models to facilitate uncertainty quantification workflows. A difficulty in adopting these methods for subsurface flow modeling is the complexity associated with nonlinear flow data conditioning. While conditional GAN (CGAN) can condition simulated images on labels, application to subsurface problems requires efficient conditioning workflows for nonlinear data, which is far more complex. We present two approaches for generating flow-conditioned models with complex spatial patterns using GAN. The first method is through conditional GAN, whereby a production response label is used as an auxiliary input during the training stage of GAN. The production label is derived from clustering of the flow responses of the prior model realizations (i.e., training data). The underlying assumption of this approach is that GAN can learn the association between the spatial features corresponding to the production responses within each cluster. An alternative method is to use a subset of samples from the training data that are within a certain distance from the observed flow responses and use them as training data within GAN to generate new model realizations. In this case, GAN is not required to learn the nonlinear relation between production responses and spatial patterns. Instead, it is tasked to learn the patterns in the selected realizations that provide a close match to the observed data. The conditional low-dimensional parameterization for complex geologic models with diverse spatial features (i.e., when multiple geologic scenarios are plausible) performed by GAN allows for exploring the spatial variability in the conditional realizations, which can be critical for decision-making. We present and discuss the important properties of GAN for data conditioning using several examples with increasing complexity.

     

Utilization of bituminous limestone ash from EL-Lajjun area in production of lightweight Masonry block

The following work aims at minimizing the environmental impact of the solid wastes (ash) that is produced after the utilization of the bituminous limestone in thermal power stations and/or retorting processes. The laboratory tests have been selected with respect to construction needs and possible post construction conditions. Utilization of the various types of ash in the production of lightweight concrete block has revealed optimum results. The compressive strength of various ash–glass sand mixes has ranged between 19 and 76 kg/cm² at 28 days. The compressive strength of ash–tuff mixes has ranged between 54 and 63 kg/cm² at 28 days. Ultra light mixtures using ash–polyester with a density of 0.88 kg/m³ and a compressive strength of 21 kg/cm² at 28 days are produced at normal room curing temperature without the use of ordinary Portland cement. The high alkalinity of El-Lajjun ash is considered a disadvantage when utilized in normal concrete mixes for structural purposes. Ash only can be mixed with aggregates to produce lean concrete for blinding purposes for use in foundations.     

Development of a new connection for precast concrete walls subjected to cyclic loading

The Industrialized Building System (IBS) was recently introduced to minimize the time and cost of project construction. Accordingly, ensuring the integration of the connection of precast components in IBS structures is an important factor that ensures stability of buildings subjected to dynamic loads from earthquakes, vehicles, and machineries. However, structural engineers still lack knowledge on the proper connection and detailed joints of IBS structure construction. Therefore, this study proposes a special precast concrete wall-to-wall connection system for dynamic loads that resists multidirectional imposed loads and reduces vibration effects (PI2014701723). This system is designed to connect two adjacent precast wall panels by using two steel U-shaped channels (i.e., male and female joints). During casting, each joint is adapted for incorporation into a respective wall panel after considering the following conditions: one side of the steel channel opens into the thickness face of the panel; a U-shaped rubber is implemented between the two channels to dissipate the vibration effect; and bolts and nuts are used to create an extension between the two U-shaped male and female steel channels. The developed finite element model of the precast wall is subjected to cyclic loads to evaluate the performance of the proposed connection during an imposed dynamic load. Connection performance is then compared with conventional connections based on the energy dissipation, stress, deformation, and concrete damage in the plastic range. The proposed precast connection is capable of exceeding the energy absorption of precast walls subjected to dynamic load, thereby improving its resistance behavior in all principal directions.     

Assessing flood inundation mapping through estimated discharge using GIS and HEC-RAS model

Water discharge is the main parameter in hydraulic modeling for flood hazard assessment. However, the unavailability of data on discharge and observed river morphologies resulted in erroneous calculations and irregularities in flood inundation mapping. The objectives of this study are (i) to investigate uncertainties of hydraulic parameters (width, cross-sectional depth, and channel slope) used in discharge equation and (ii) to examine the influence of estimate discharge on water extent and flood depth with different boundary conditions on interferometric synthetic aperture radar (IFSAR) and modified IFSAR DEMs. Sensitivity analysis was conducted with the Monte Carlo simulation method to generate random data combinations. Bjerklie’s equation was used to calculate discharge based on the three variables, and Manning’s n was substituted into the Hydrologic Engineering Center River Analysis System (HEC-RAS) model. TerraSAR-X was used to distinguish existing flood water bodies and normal water extent. The uncertainty of the combined variables was assessed with the likelihood measures such as F-statistic, mean absolute error, root mean square error, and Nash–Sutcliffe efficiency which compares observed and predicted inundated area as well as flood water depth simulated using the HEC-RAS model.     

The nexus between income inequality,economic growth and environmental degradation in Pakistan

This study examines the impact of income inequality and economic growth on environmental degradation in Pakistan using ARDL bounds testing approach for the period 1966–2011. Empirical results for the aggregate CO₂ emissions and its four sources such as CO₂ emissions from solid fuel, liquid fuel and gaseous fuel consumption as well as electricity and heat production confirm the existence of long run co-integrated relationship between income inequality, economic growth and environment degradation. The estimated results indicate that carbon emissions increase as the income gap expands in Pakistan. Besides the negative impact of industrial share and population density on CO₂ emissions, we also confirm that economic growth in Pakistan comes up with higher emissions. Hence, the hypothesis of EKC is not valid for Pakistan during the study period. Our empirical findings are robust as evidenced by dynamic ordinary least squared and the U-tests. Overall, this study suggests that the distribution of income matters to aggregate carbon emissions and focus should be made on sustained economic growth to reduce pollutants and hence CO₂ emission in the study area.     

Smooth particle hydrodynamics modelling of liquid-sediment system and coastal wave breaker

Ocean Dynamics - In this paper, a two-phase coastal liquid-sediment system and a wave breaker were numerically simulated using a particle-based smooth particle hydrodynamics (SPH). To verify the...     

A 3-tier tsunami vulnerability assessment technique for the north-west coast of Peninsular Malaysia

The 2004 tsunami that struck the Sumatra coast gave a warning sign to Malaysia that it is no longer regarded as safe from a future tsunami attack. Since the event, the Malaysian Government has formulated its plan of action by developing an integrated tsunami vulnerability assessment technique to determine the vulnerability levels of each sector along the 520-km-long coastline of the north-west coast of Peninsular Malaysia. The scope of assessment is focused on the vulnerability of the physical characteristics of the coastal area, and the vulnerability of the built environment in the area that includes building structures and infrastructures. The assessment was conducted in three distinct stages which stretched across from a macro-scale assessment to several local-scale and finally a micro-scale assessment. On a macro-scale assessment, Tsunami Impact Classification Maps were constructed based on the results of the tsunami propagation modelling of the various tsunami source scenarios. At this stage, highly impacted areas were selected for an assessment of the local hazards in the form of local flood maps based on the inundation modelling output. Tsunami heights and flood depths obtained from these maps were then used to produce the Tsunami Physical Vulnerability Index (PVI) maps. These maps recognize sectors within the selected areas that are highly vulnerable to a maximum tsunami run-up and flood event. The final stage is the development of the Structural Vulnerability Index (SVI) maps, which may qualitatively and quantitatively capture the physical and economic resources that are in the tsunami inundation zone during the worst-case scenario event. The results of the assessment in the form of GIS-based Tsunami-prone Vulnerability Index (PVI and SVI) maps are able to differentiate between the various levels of vulnerability, based on the tsunami height and inundation, the various levels of impact severity towards existing building structures, property and land use, and also indicate the resources and human settlements within the study area. Most importantly, the maps could help planners to establish a zoning scheme for potential coastline development based on its sensitivity to tsunami. As a result, some recommendations on evacuation routes and tsunami shelters in the potentially affected areas were also proposed to the Government as a tool for relief agencies to plan for safe evacuation.     

Group velocity dispersion analysis in northern Peninsular Malaysia

The crustal structure beneath three seismic stations over Malaysia has been investigated with the application of the group velocity dispersion analysis of the northern Sumatra earthquake data which occurred on 06 April 2010. Eighteen crustal layer models are constructed to assess the structure. Group velocity dispersions have been computed for the recorded earthquake data using a graphical method and modified Haskell matrix method for the models. Both dispersions have been presented for the interpretation of crustal layers. Findings have shown four major crustal layers having thicknesses of 2.5–4.0, 2.0–5.5, 5.0–8.0, and 8.5–9.0 km, while in Terengganu, it has shown three layers. Density, shear, and compressional wave velocities used in models have suggested that the crustal structure of the northern part of Peninsular Malaysia is crystalline. Major crustal minerals are of quartz, plagioclase, and mica. Most layers seem to have upward directions toward Perak from Kedah and Terengganu.