Arvind Kumar Jain

The northern Indian passive margin has witnessed at least two Wilson-cycle-related collisional events since the Proterozoic: the Early Paleozoic Bhimphedian Orogeny and the Cenozoic Himalayan Orogeny. The latter, triggered by the India–Asia collision, produced a series of orogen-scale structures including the Main Frontal Thrust, Main Boundary Thrust, Main Central Thrust (MCT), and South Tibetan Detachment System (STDS), which cut the Himalaya into distinct lithotectonic belts. However, the extent to which vestiges of the Early Paleozoic tectonism persist remains uncertain due to extensive overprinting by Cenozoic deformation. This ambiguity has revived debates on whether the major Himalayan fault systems are exclusively Cenozoic tectonic boundaries or the reactivation of long-lived, inherited Early Paleozoic structures.This study investigates the tectonic evolution of the MCT, a several-kilometre-thick, foreland-propagating, high-strain shear zone that activated ca. 27–11 Ma. It structurally juxtaposes the Neoproterozoic Greater Himalayan Sequence (GHS) over the Paleoproterozoic Lesser Himalayan Sequence. Integrated structural mapping and U-Pb zircon geochronology were conducted on the GHS rocks from the proximal hanging wall of the MCT in the Dhauliganga (Garhwal) and Pabbar (Himachal) valleys of the NW Himalaya. Ductilely deformed psammitic, ortho- and aplite gneisses, leucogranite, and migmatite display NE-dipping mylonite foliation, NNE-plunging stretching lineation, and persistent top-to-the-SW ductile shearing, consistent with regional MCT kinematics.Detrital zircon spectra constrain the maximum depositional age of the GHS metasedimentary protoliths to 849 ± 6.7 Ma. These country rocks were syn- to post-tectonically intruded by orthogneiss and leucogranite along a major crustal conduit, the proto-MCT, during the Early Paleozoic Bhimphedian Orogeny. In the Dhauliganga Valley, three distinct tectonothermal pluses are recorded at 554 ± 6.8 Ma, 489 ± 2.8 Ma, and 471 ± 3.2 Ma. In the Pabbar Valley, coeval crustal anatexis along the proto-MCT produced stromatic migmatite at 508 ± 6.7 Ma and 473 ± 3.1 Ma. These ages collectively reflect magmatism, regional metamorphism, and pervasive deformation along the proto-MCT during the Bhimphedian Orogeny. During the Cenozoic Himalayan Orogeny, this dormant proto-MCT was reactivated and subsequently evolved to present-day MCT. This is evident by tectonothermal pulses at 20 ± 3.0 Ma and 16 ± 1.2 Ma, recorded in the leucogranite and aplite gneiss in the Dhauliganga Valley. Notably, a comparable tectonic evolution of the STDS during the Early Paleozoic (a~499–467 Ma) and Cenozoic (~34–25 Ma and 23–13 Ma) has been documented in the upper reaches of the Dhauliganga Valley.Together, these findings demonstrate that both the MCT and STDS originated as coeval Early Paleozoic proto-tectonic structures and were subsequently reactivated during Late Eocene to Early Miocene Himalayan deformation phases. This dual-stage tectonic evolution underscores that the Himalayan crustal architecture is fundamentally inherited from Early Paleozoic orogenesis, with Cenozoic deformation preferentially exploiting these pre-existing anisotropies. Therefore, comprehensive Himalayan tectonic models must integrate the contributions of Early Paleozoic tectonism, rather than attributing these major shear zones solely to the Cenozoic displacement.

The South Tibetan Detachment System (STDS) represents a major extensional shear zone separating the Greater Himalayan Sequence (GHS) from the Tethyan Himalayan Sequence (THS), yet its long-term tectonomagmatic evolution remains poorly understood. The Dhauliganga Valley (Uttarakhand, NW Himalaya) is one of the few transects where the STDS is excellently exposed from Malari to Goting for ~10 km along its strike, remarkably showing cross-cutting relationship of the Paleozoic orthogneisses and Neoproterozoic mylonites and migmatite, which are further intruded by at least two generations of Mio–Oligocene leucogranites. Zircon U–Pb geochronology integrated with major, trace and rare-earth element geochemistry of representative granites and leucogranites constrain the timing and source characteristics of the magmatic events associated with the STDS and are crucial to develop a tectonic model that explains the role of the STDS as a fundamental Cambro–Ordovician terrane boundary that was subsequently reactivated during Cenozoic orogeny.Field observations and microstructural analyses in the STDS zone document a polyphase deformational history characterized by multi-phase shearing, syn-tectonic melt emplacement and overprinting brittle deformation. Structural and microstructural fabrics capture an evolution from D2 top-to-SW thrusting to D3 top-to-NE brittle–ductile extension with oblique-slip and transtensional components, producing a high-angle shear geometry unique to this transect.Detrital zircon populations from folded psammitic gneiss in the footwall preserve Neoproterozoic inheritance (~1075–860 Ma), overprinted by the Cambro–Ordovician granitoids with crystallization ages of 498.92 ± 5.5 Ma and 486.54 ± 2.3 Ma. It is hypothesized that STDS facilitated the emplacement of an extensive ~200km Cambro–Ordovician granite belt from Sutlej to Dhauliganga Valleys in NW Himalaya during the Kurgiakh/Bhimphedian Orogeny. In the post-orogenic phase, the STDS acted as a proto-tectonic marginal extensional boundary that facilitated the denudation of these granites and gneisses into the Tethyan basin resulting in a >10 km-thick THS.Leucogranites within the uppermost GHS yield ages from Late Eocene to Early Oligocene (35–23 Ma) indicating magmatism associated with SW-directed contraction and crustal thickening (35.3 ± 1.8 Ma, 33.99 ± 1.07 Ma). These leucogranites exhibit tight isoclinal folds with NE-dipping axial surfaces. Syn-tectonic emplacement occurred in the Late Oligocene–Early Miocene (25.03 ± 0.54 Ma 23.68 ± 0.94 Ma), followed by extension-induced exhumation. Magmatic activity abruptly ceased along the STDS in this transect by 13.30 ± 0.30 Ma, after a protracted melt generation and emplacement for nearly 10.0 Ma.Whole-rock geochemistry indicates that both Paleozoic granitoids and Miocene leucogranites represent syn-collisional, peraluminous crustal melts generated via fluid-absent muscovite-dehydration melting under high-pressure conditions.This study proposes a tectonomagmatic evolutionary framework for the STDS in the Dhauliganga Valley, a Paleozoic terrane boundary and a reactivated Cenozoic extensional structure mediating melt emplacement, strain localization and exhumation. The persistence of a complex thermal history suggests a foundation for future isotopic and thermochronological investigations into the architecture and rheology of the Himalayan orogen.

Standalone DC microgrids are popular in enhancing energy resilience and reliability in the dynamic energy system landscape. However, protection concerns, such as detection of fault types, identification of fault location, fault characteristics, etc., are major challenges in DC microgrids. Furthermore, the inclusion of power electronic-based DC loads and generators in standalone low-voltage DC microgrid systems (LVDCMG) renders traditional fault detection, classification, and location estimation schemes ineffectual. Therefore, early fault detection, precise fault event response, and fault location estimation are needed to ensure accuracy and reliability of the LVDCMG fault management framework. Thus, the emphasis persists on developing sophisticated tools for DC microgrid fault diagnosis. This paper presents a modern, fast, and reliable data-centric tri-layered deep learning-based framework for fault detection, classification, and location estimation in a standalone LVDCMG programmed through Adam optimization. The framework utilizes long short-term memory (LSTM) and bidirectional LSTM (Bi-LSTM) models for different layers of the application. Primarily, the LSTM layers detect and classify the fault in the system, followed by fault location prediction using a Bi-LSTM network. MATLAB/SIMULINK is used for the proposed method for simulating a 380 V standalone DC microgrid. The outcomes demonstrate the efficacy of the proposed fault diagnosis strategy, showing substantial improvements over conventional techniques. By capturing intricate temporal correlations in the microgrid data, the Bi-LSTM model offers more accurate fault location prediction in the system. Moreover, robust sensitivity analysis to assess its performance under typical and noisy environments has been encompassed in this work, leading the path for more reliable and sustainable electrical systems.