Sādhanā最新文献

The current energy crisis is causing a transformation of tremendous scope and complexity. The natural gas, coal, and electricity sectors have experienced the largest tremors. In this regard, an effort was made to conserve energy by providing a compact heat exchanger that may be utilized to recover waste heat from power plants and industries. This article explores the effect of combined passive techniques on the performance of a CTHE fitted by twisted tapes at hot-side and Al₂O₃ nanofluid used as cold-side fluid. The experiments were conducted by incorporating the differently configured PVTTs and CFTTs (TR: 20, 13.3, and 9.8) in the inner tube with fixed flowrate (Re = 2500) of hot water and using different volume fractions of Al₂O₃ nanofluid (Vol.%: 0.05, 0.1 and 0.15) as cold fluid with varied flow rates (500 ≤ Re ≤ 5000) in the annulus. The results reveal that the PVTT (TR = 20) and 0.05% nanofluid combination increases the Nusselt number by 12.28% and the TPF by 1.127, while the CFTT (TR = 9.8) and 0.15% nanofluid combination increases the Nusselt number by 24.27% and the TPF by 1.263. Hence, CFTT (TR = 9.8) with 0.15% of Al₂O₃ nanofluid provided greater performance in the combinations tested, albeit at the expense of a little pressure loss.

Graphical Abstract

The significance of product freshness is heightened by the health-conscious market and the current circumstances. The quality of the product declines with time. In this case, the retailer implements a strategy of gradually reducing the selling price over time to mitigate the effects of product degradation. As a consequence, demand keeps growing over time. The demand for a product depends upon both its freshness and the price at which it is sold. In this research, a suggested retailer-customer supply chain for a fresh produce item is examined. The retailer implements a partial credit policy for the customer in order to increase the retailer’s order volume. The credit amount and credit period are found to be time-dependent in an increasing way. The optimal choice is determined by maximizing the total profit derived from the system. An optimization technique called particle swarm is developed, evaluated, and employed for the search process. According to the findings of this study, even if a merchant extends the credit term while a fresh product’s quality declines, overall profit will not improve since buyers would not jeopardize their health. A few examples are used to illustrate the concept.

This proposed work investigates the performance of dc voltage of a three-phase Active Front-End (AFE) Sinusoidal Pulse Width Modulated (SPWM) rectifier during load switching. To obtain desired performances, a transfer function is derived in synchronous reference frame (dq), from which the gain of the PI controllers are estimated and observed the performance accordingly. In this research, the load current is feed-forwarded with d-axis current by a suitable choice of gain factor, which results a fractional feedback d-axis current control and improves the transient behaviour simultaneously. This will unalter the other performance parameters of the system such as, UPF operation, less Total Harmonic Distortion (THD) of input current, dc voltage boost etc. All the simulation results exhibits satisfactory performance and validated with a prototype developed using STM32F303RE microcontroller accordingly.

Addressing the inherent uncertainties in geotechnical engineering, particularly concerning natural materials, this study focuses on the crucial aspect of reliability analysis in geotechnical structures. The research delves into the Factor of Safety, specifically examining the Moment Ratio, for cantilever sheet pile walls in cohesionless soil. The study employs both the First-Order Reliability Method (FORM) and Second-Order Reliability Method (SORM), integrating various optimization techniques such as Genetic Algorithm, Particle Swarm Optimization, Firefly Algorithm, and Biogeography-Based Optimization. The research systematically evaluates the performance of a model, utilizing the widely-adopted Adaptive Neuro-Fuzzy Inference System (ANFIS) to predict pile moment ratios based on soil properties such as the angle of shearing resistance and unit weight. Rigorous criteria are applied to assess the model's efficacy, revealing the superior predictive capabilities of the hybrid ANFIS and Particle Swarm Optimization (ANFIS-PSO) model. This abstract encapsulates a comprehensive methodology for evaluating and quantifying risk in civil engineering projects related to cantilever sheet pile walls, providing valuable insights for the development and implementation of robust structures in the field.

A large volume of solar energy dissemination in a supply grid originates extreme variations in the load, resulting in a duck-form load arc that can cause stability issues. Also, the cost of energy consumption is found to vary between the off-peak and peak loads observed in the duck-shaped load curve. Accurate load forecast and demand response program is a key task for duck curve management in a distribution structure. Hence, this work proposes a Demand Response (DR) program using deep learning neural networks namely Long Short-Term Memory (LSTM). The proposed DR program is implemented in a modified 12 bus radial distribution network for duck curve management, where voltage stability is taken care of simultaneously minimizing the electricity cost in an energetic pricing environment. LSTM is used for forecasting the load and linear programming is used for load shedding. Therefore, this paper resolves the dual aims of flattening the duck-shaped load arc and minimizing electricity costs by combining them into a single objective function.

IRNSS/NavIC is an independent navigation system developed by India. The dependence on external satellite-based navigation systems is gradually decreasing as a result of the deployment of our own navigation system, IRNSS/NavIC, which exhibits enhanced reliability. In this paper, a software-based IRNSS/NavIC receiver is developed using the standard Signal-In-Space Interface Control Document as a reference for signal structure, subframe patterns and parameter calculations. The IRNSS/NavIC receiver is validated with the I/Q data file as input which is generated by software based IRNSS/NavIC simulator. Analysis of the effect of a specific error on receiver output position necessitates repeated trials and modification, or in some cases, the development of new algorithms. The intermediate stage data can be viewed or stored as needed; a few examples are provided. In this paper Squared Correlators Code Discriminator (SCCD), a new multipath mitigation method has been designed and developed for IRNSS/NavIC receiver. The SCCD method is derived from Strobe Correlator (SC) and Combination of squared correlator method (CSC). The pseudorange bias is investigated and eliminated from the SCCD approach. The performance parameters of the IRNSS/NavIC receiver using each of the four approaches are compared, and the outcomes are discussed.