The Global Research Network for Verified Scholars

In our modern era of rapid development, the issue of noise pollution has become increasingly pressing. This relentless surge in noise pollution has brought about significant adverse effects on human health, extending beyond just auditory concerns. To combat this escalating problem, it becomes imperative to explore innovative solutions, such as the utilization of natural fiber-reinforced composites in acoustical applications. These composites offer environmental friendliness, cost-effectiveness, and enhanced mechanical and sound-absorbing qualities. In the context of this review, we examine various methods for evaluating both the mechanical and acoustical attributes of these composites. We examine significant acoustical metrics, including the sound absorption coefficient, sound transmission losses, and noise reflection coefficient, as well as mechanical aspects encompassing tensile, flexural, impact strengths, and hardness. Moreover, this comprehensive review delves into the realm of influencing parameters, which exert a notable impact on the mechanical and acoustical characteristics of natural fiber-reinforced composites. A range of variables is encompassed by these influencing parameters, including fiber properties, binder-filler amount, specimen thickness, etc. It is worth noting that manipulating these parameters can yield significant enhancements in mechanical strength and sound absorption. However, it is crucial to recognize and respect certain limitations to avoid adverse effects. In conclusion, this review emphasizes the importance of carefully considering these performance-influencing parameters to optimize the mechanical and acoustical attributes of natural fiber-reinforced composites. By doing so, we can fully harness the potential of these composites to address the challenges posed by escalating noise pollution effectively.

This paper provides a comprehensive review of existing literature on research design, philosophy, and quantitative approaches in scientific research methodology. It explores the theoretical foundations that influence researchers’ choices when developing a research strategy, with particular emphasis on the alignment between research philosophy and methodological choices. By examining key philosophical paradigms such as positivism, interpretivism, and pragmatism, the paper highlights how these frameworks shape the selection of quantitative, qualitative, and mixed-methods research approaches. The Research Onion Model is utilized to demonstrate the sequential layers of research design, from philosophical stance to data collection strategy. Through a review of current research, this paper provides insights into the importance of selecting the appropriate methodology based on the research objectives, questions, and underlying theoretical perspectives. The findings suggest that understanding the interplay between philosophy and methodology is crucial for ensuring a coherent and effective research design. By synthesizing existing theoretical perspectives, this paper contributes to a deeper understanding of the methodological choices available for scientific research.

Thermal enhancement in household, biomedical, and industrial appliances remains essential for technological advancement, thus motivating the search for advanced heat-transfer fluids with superior thermal and electromagnetic performance. Although hybrid nanofluids have shown considerable promise, the specific role of lightweight and corrosion-resistant aluminum-alloy nanoparticles (AA7072 and AA7075) dispersed in ethylene glycol under the combined influences of Hall current, ion-slip effect, and Darcy–Forchheimer permeability has not been previously reported. The present work addresses this gap by developing a three-dimensional, steady, incompressible magnetohydrodynamic (MHD) model for the flow of a Casson hybrid nanofluid over a vertically stretching sheet, incorporating nonlinear thermal radiation, viscous dissipation, Joule (Ohmic) heating, and heat generation. The thermophysical properties of the hybrid nanofluid are modeled within the Tiwari–Das framework, while the generalized Ohm’s law with Hall and ion-slip terms governs the electromagnetic body forces. Key assumptions include thermal equilibrium between the nanoparticles and the base fluid, the Boussinesq approximation for buoyancy, and the Rosseland approximation for radiative heat flux. The governing partial differential equations are reduced to systems of nonlinear ordinary differential equations via appropriate similarity transformations and solved numerically using the Chebyshev Collocation Method (CCM), whose accuracy and efficiency are validated against published benchmarks. The analysis reveals that: increasing the Hall parameter diminishes the Lorentz force by reducing effective electrical conductivity, thereby augmenting primary fluid velocity; the ion-slip parameter further boosts velocity through enhanced charge mobility while simultaneously suppressing the temperature field via reduced Joule heating; higher values of the nonlinear thermal radiation parameter amplify the thermal profile.

Hydrophobic and photocatalytic cotton fabric was created through a simple dip-coating combining with methyltrimethoxysilane (MTMS), tetraethyl orthosilicate (TEOS) and graphitic carbon nitride (g-C₃N₄). The hybrid silica g-C₃N₄ network exhibits hierarchical roughness, high thermal stability, and visible-light activity, as confirmed by XRD, SEM-EDX, FTIR, and TGA. The coated fabrics displayed robust water repellency with a contact angle of 133 ± 3° and achieved > 88% degradation of methylene blue under visible light, following pseudo-first-order kinetics (k = 0.00995 min−1). The synergy of MTMS+TEOS+g-C₃N₄ enabled durable self-cleaning behaviour and resistance to liquid penetration. This scalable, fluorine-free route demonstrates a sustainable pathway for multifunctional fabric, with applications spanning outdoor protective fabrics, environmental remediation and advanced military clothing.

Metacognition, colloquially understood as "thinking about thinking," serves as a criticaldeterminant of academic success and a foundational pillar for lifelong learning. This paperprovides a comprehensive examination of the dual-component framework of metacognition—comprising metacognitive knowledge and metacognitive regulation—and evaluates its urgentnecessity within the contemporary Indian education system. While modern Westernpsychology provides the essential structural vocabulary and empirical metrics formetacognition, this research argues that the ancient Indian Gurukul system utilized asophisticated, indigenous version of these strategies through the pedagogical triad of Shravana(attentive acquisition), Manana (reflective deliberation), and Nididhyasana (deepinternalization). By meticulously synthesizing these ancient reflective practices with modernpedagogical tools such as cognitive modeling and reflective scaffolding, this paper proposes astrategic roadmap designed to transition the Indian classroom from its current state of rote-dependency toward a model of cognitive autonomy. This transition aligns with thetransformative goals envisioned by the National Education Policy (NEP) 2020, aiming tocultivate self-regulated learners capable of navigating an increasingly complex globallandscape through heightened self-awareness and mental agility.

This study addresses the existing literature’s incomplete coverage of detailed LCOE (Levelised Cost of Electricity) and economic evaluation for bifacial photovoltaic (PV) systems. LCOE is a crucial metric in assessing the economic viability of energy generation. This paper introduces a novel model that captures the relationship between LCOE and the innovative technology of bifacial PV. It also analyzes the LCOE and energy payback period for an 8 kW bifacial PV plant, which is installed on the rooftop of the IIT Kharagpur campus. The LCOE derived from the real-time PV plant stands at 3.46 INR/kWh, while PVSyst predicts it as 3.37 INR/kWh. The corresponding payback period for the actual bifacial plant is approximately five years and five months, compared to five years and three months projected by PVSyst. It explicitly compares the economic feasibility of two rooftop PV systems: traditional monofacial panels and bifacial panels for scaled-up systems (1 MW). The analysis encompasses both systems’ initial costs, energy output, and payback periods. The findings reveal that the bifacial PV system outperforms the monofacial system in electricity generation and offers a shorter payback period. Consequently, the study demonstrates that the bifacial PV system represents a more economically advantageous choice for rooftop solar installations.

The power output of photovoltaic (PV) systems, especially bifacial modules, varies due to daily fluctuations in irradiance and temperature. Maximizing efficiency and power extraction are crucial. Hybrid DC off-grid topologies offer promise for rural electrification with solar energy and battery backup. These systems, tailored for household appliance use, feature low semiconductor count, continuous current ports for PV, battery, and DC loads, low-voltage levels for PV and battery, voltage regulation for DC loads, maximum power point tracking, proper battery charging and discharging, high-voltage boosting sans low-frequency transformers, and reduced power converter stages. However, existing schemes often lack critical features. Hence, this paper proposes a novel three-switch tri-port converter with integrated energy storage for standalone bifacial PV applications, with modeling and experimental validation. The battery serves as an energy storage component, regulating the DC link voltage for consistency. This paper underscores PV system power optimization and introduces a novel tri-port converter for standalone bifacial PV setups, emphasizing energy storage's role in voltage regulation.

Although the bifacial photovoltaic (PV) module is now a mature technology, there still exists a gap in the literature on its electrical modeling and equivalent circuit representation. Most published studies have mainly focused on the photocurrent while overlooking other crucial parameters for the electrical response of the module. Even so, the photocurrent of the bifacial module is simplistically treated as the sum of individual currents of the front and rear sides, a hypothesis challenged in this study. Notably, our research has uncovered a discrepancy that can exceed 15%, and we address this issue by introducing a correction factor in this article. This article introduces a comprehensive electrical model that effectively integrates bifacial PV modules' front and rear sides into a single − circuit representation. This novel model adopts the single − diode equivalent circuit, formulating each of the five parameters as a function of the individual side's parameters. Indoor and outdoor measurements validate the accuracy improvement brought by this model, which can benefit energy yield studies and our theoretical understanding of bifacial PV systems.

The energy yield from bifacial solar photovoltaic (PV) systems can be enhanced by optimizing the tilt angle. Bifacial modules boost the energy yield by 4% to 15% depending on the module type and ground reflectivity with an average of 9%. The selection of tilt angle depends on several factors, including the geographical location, weather variation, etc. Compared to the variable tilt angle, a constant angle is preferred from the point of view of the cost of installation and the cost of maintenance. This paper proposes a new method for analysing bifacial modules. A simpler rear-side irradiance model is presented to estimate the energy yield of a bifacial solar photovoltaic module. The detailed analysis also explores the optimum tilt angle for the inclined south–north orientation to obtain the maximum possible yield from the module. Taking four regions into account, i.e., Kharagpur, Ahmedabad, Delhi, and Thiruvananthapuram, in the Indian climate, we studied several cases. The Kharagpur system showed a monthly rear irradiance gain of 13%, and the Delhi climate showed an average performance ratio of 19.5%. We studied the impact of albedo and GCR on the tilt angle. Finally, the estimated model was validated with the PVSyst version 6.7.6 as well as real field test measurements taken from the National Renewable Energy Laboratory (NREL) located in the USA.

This study presents a comprehensive performance assessment of a bifacial photovoltaic (PV) system and real-time validation of a new energy estimation model. The system consists of 18 bifacial PV modules installed at a test site with a total capacity of 6.8 kWp. The system’s performance was evaluated based on its energy yield over one year. The energy estimation model was validated in real-time using data collected from the bifacial PV system. The results show that the bifacial PV system achieved an annual energy yield of 1569 kWh/kWp. The energy estimation model was accurate and reliable, with correlation coefficients of 1.04 and 1.40 for the front and rear sides, respectively. This study provides valuable insights into the performance of bifacial PV systems and the development of precise energy estimation models, which can help design and optimize PV systems in different environmental conditions.