E. N. Dhanamjaya Rao’s research while affiliated with Andhra University and other places

Ulindakonda vent agglomerate of Neo-archean Gadwal Greenstone Belt in the Eastern Dharwar Craton (EDC), is located partly in the Kurnool district of Andhra Pradesh and partly in Jogulamba Gadwal district of Telangana state, India. Trachyandesite occurs as matrix of the agglomerate and at some places it exhibits massive and interbedded nature with granodiorite that mainly occurs as sub-rounded clasts in the agglomerate reflecting magma mixing and mingling. The rock is dotted with small dark specks of a ferromagnesian mineral which often shows a well-developed cleavage surface. The size of grains ranges from medium to fine-grained. Petrographically it is dominated by feldspars and mafic minerals like hornblende and biotite as accessory minerals and quartz in minor amounts. Further, titanite, allanite, carbonate and epidote occur as phenocrysts. Consertal texture is seen between amphibole and quartz, sieve texture also observed in plagioclase feldspar. The percentage of SiO2 ranges from 49.84 to 62.92%, TiO2 grades from 0.51 to 2.46%, Al2O3 varies from 11.43 to 15.99%, FeOT ranges from 5.88 to 18.28%, MnO grades from 0.07 to 0.14%, MgO varies from 1.27 to 4.95%, CaO shows variation from 2.58 to 7.62%, Na2O grades from 2.56 to 4.84%, K2O shows variation from 1.66 to 4.87%, P2O5 varies from 0.30 to 0.80% and LOI grades from 0.67 to 1.93%. In the primitive mantle-normalized spidergrams, all the samples of trachyandesitic matrix are depleted in high field strength elements (HFSE; Nb, Ti, Zr, Hf and Ta) but are enriched in large ion lithophile elements (LILE; Cs, Rb, Ba, Sr, U, K and Pb). The chondrite normalized REE pattern of trachyandesitic matrix show moderately fractionated LREE (La/SmN= 2.44-4.45, La/YbN= 5.85-23.29) with negligible negative Eu anomaly (0.71-0.91) and flat HREE (Gd/YbN=1.99-3.30) showing the normalized values are >10. The Ulindakonda trachyandesitic samples are plotted in the field of calc-alkaline basalts (CAB) and in the island/ volcanic arc in the tectonic discrimination diagram.

Assessment of pollutants and groundwater quality has attracted much attention worldwide as it is directly linked to human health. In view of this, groundwater samples were collected from a part of Guntur district, Andhra Pradesh, India, to assess groundwater pollution levels and groundwater quality, using Water Pollution Index (WPI) and Water Quality Index (WQI), respectively. Groundwater chemical composition results indicated that groundwater quality was characterized by alkaline and very hard categories with Na+ > Mg2+ > Ca2+ > K+: HCO3 $^{ - }$ > Cl $^{ - }$ > SO42 $^{ - }$ > NO3 $^{ - }$ > F $^{ - }$ facies. TDS, TH, Ca2+, Mg2+, Na+, K+, HCO3 $^{ - }$, Cl $^{ - }$, NO3 $^{ - }$, and F $^{ - }$ were above the recommended threshold limits in 100%, 100%, 35%, 100%, 100%, 100%, 100%, 95%, 85%, and 75% of groundwater samples, respectively, for drinking purposes. The geochemical diagram showed base exchange water type (Na+–HCO3 $^{ - }$) in 50% of groundwater samples resulting from weathering and dissolution of plagioclase feldspars under the influence of soil CO2 and ion exchange process. The remaining groundwater samples showed saline water type (Na+–Cl $^{ - }$) due to the influence of evaporation, sewage sludge, septic tank leaks, irrigation-return flows, agrochemicals, etc. Ionic relationships of Ca2+/Na+ vs HCO3$^{ - }$/Na+, Ca2+/Na+ vs Mg2+/Na+, higher Na+ than Ca2+, and occurrence of CaCO3 concretions further supported geogenic processes that alter groundwater chemistry. The positive linear trend of TDS vs Cl $^{ - }$ + NO3 $^{ - }$/HCO3 $^{ - }$ and the relationship of TDS with TH showed anthropogenic input as the main factor, causing groundwater contamination. The WPI indicated two categories of water quality: moderately polluted water (WPI: 0.75–1.00) and highly polluted water (WPI: > 1.00) in 60% and 40% of groundwater samples, which were 81.49% and 18.51% of the study area, respectively. Hierarchical cluster analysis identified three clusters: Cluster I (pH, F $^{ - }$, Ca2+, K+, NO3 $^{ - }$, Na+, and SO42−), Cluster II (TH, Mg2+, Cl $^{ - }$, and HCO3 $^{ - }$), and Cluster III (TDS) support WPI. Following WQI, 75% and 25% of groundwater samples fell under poor groundwater quality type (WQI: 100–200) and very poor groundwater quality type (> 200), respectively, especially due to the increased concentrations of Mg2+, Na+, K+, HCO32−, Cl $^{ - }$, NO3 $^{ - }$, and F $^{ - }$ ions, thereby increasing salinity (TDS) and hardness (TH) in groundwater. Spatially, they covered 85.84% and 14.06% of the study area. The quality of this groundwater is not suitable for drinking purposes. Therefore, the present study suggests preventive measures (safe drinking water supply, desalinization, defluoridation, denitrification, calcium food, and rainwater harvesting) to protect human health.

Building products designed at each level of detail provide single window solutions for Smart City applications. In view of this, the current study uses the tools and techniques to generate second level of detailed buildings that include building shape and height parameters. The extrusion from 2D has been performed altogether in multiple platforms and 3D data handling software. The basic inputs considered for extracting the polygon shapefiles are obtained from high-resolution stereo pair satellite images acquired using Cartosat-I imagery. Eight ground control points are collected using high precision Differential Global Positioning System having millimeters of accuracy. The image adjustments and Digital Surface Model are generated by using the process and concepts of Photogrammetry such as block creation using Rational Polynomial Coefficient text files, internal geometry set up such as interior and exterior orientation, Tie point generation and control point adjustments, and Automated Terrain Extraction. The thus obtained terrain model is overlaid on ortho photograph and the building heights are extracted and compared by using spatial profile graph as well as stereoscopic visualization methods. The height-derived attribute tables are attached to corresponding building footprints and are visualized in different GIS platforms.

Building Information Modeling is a sophisticated technology possessing intellectual tools that help planners and architects to design sustainable buildings and carryout performance analysis based on various aspects. Apart from the existing building elements, a network connecting each building component is of vital importance in order to generate organized plans. Building Information Modeling when embedded with Geographic Information System delivers versatile applications in the world of both Geo Spatial field of studies as well as Architecture, Engineering and Construction Industry. The current research is one such attempt to understand the power of Geographic Information System tools in building models especially in solving complicated network connections. Designing the electrical network and planning the circuitry information in such a way so as to avoid faulty or poor connections in between the inter circuit elements is successfully achieved with the help of this integration. Initially, building model is generated to the high level of detail and electrical fixtures are organized with in a power distribution system using Revit Architecture. The virtual network wiring made in Building model is physically connected using three dimensional Polyline features in Geographic Information System platform and the created Network of electrical elements is utilized for Geometric Network Analysis.

Electron Micro-Probe (EMP) analysis of accessory monazites in the cordierite-gneisses near Vizianagaram, Andhra Pradesh (AP) in the Eastern Ghats Granulite Belt shows 0.5-0.6% CaO, 28% ThO 2 and 0.1-0.2% UO 2. Data show the inverse relationship of Th and Ca with both light and heavy REE. This chemical data of monazite present in the rock, when compared with that of detrital monazite occuring in placer mineral sands of the nearby Kalingapatnam coast shows that the content of La, Ce, Pr, Nd, Th and U in both are comparable, whereas the content of Sm and Y in the former are much more than that of the latter, while Ca content in the former is less than that of the latter. Using the EMP-based chemical data on Th and Pb content in monazites under study, their dating reveal two age groups, one at 932 + 38 Ma, which corresponds to the ~ 1000 Ma granulite metamorphism in Visakhapatnam and Anakapalle regions of AP, and the second at 836 + 36 Ma, which corresponds to ~ 850 Ma age, reported for the intrusive granites and pegmatites occurring in Eastern Ghats Granulite Belt.