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Generators and condensers are the two vital equipment items that determine the output of vapor absorption refrigeration systems. Arid weather conditions produce a significant reduction in the performance of the vapor absorption refrigeration cycle due to low condenser heat dissipation despite high generator temperatures. Although numerous studies on condenser cooling methods in vapor compression systems have been reported in the literature, solar-operated vapor absorption systems have not been studied. Limitations in generator temperatures of solar-operated vapor absorption systems necessitate a focused study in this area. This study makes the selection of the best choice for condenser cooling from among four different condenser cooling methods which have an impact on the performance of the vapor absorption refrigeration system for effective cooling using solar energy. A solar vapor absorption refrigeration system working with low-grade heat using a compound parabolic collector is considered in this study. Analysis of a vapor absorption refrigeration system for cooling in arid weather conditions is carried out using different condenser cooling methods with Engineering Equation Solver. Initially, the model used in the study is compared with a similar study reported in the literature. Techniques considered are air, water, evaporative, and hybrid cooling techniques. The performance of the vapor absorption cooling system was analyzed using experimental values of a solar compound parabolic collector obtained from real-time measurements for simulating the model. Results show that water cooling can provide suitable condenser cooling and improve the coefficient of performance of the solar vapor absorption refrigeration system using the solar collector. The water-cooled condenser has 1.9%, 3.3%, and 2.1% higher COP when compared to air-cooled condensers for spring, summer, and autumn seasons respectively, whereas the water-cooled condenser cooling recorded 6%, 14%, and 8% higher COP relative to the evaporative cooling method. Cost comparison showed maximum cost for water-cooled condensers and minimum cost for hybrid-cooled condensers. The effect of each cooling method on the environment is discussed.

The ideal condenser with dielectric in general physics is delivered in a way that lacks in-depth explanation, leaving students in limbo when asked to explain how different surfaces on dielectric condensers when connected/disconnected with wires are charged. This paper will offer a relatively complete set of multiscale tutorials on different methods of applying Gauss’ law on condensers with a dielectric as well as a technique of abstracting condensers partially inserted with dielectric into parallel and series condenser models, both with an emphasis on how to better visualize different surfaces carrying charges of different origins. Special attention in this paper is paid to the best visualization to explain such concepts on different scales. This paper offers a relatively complete review and framework of ideal condensers with dielectric, 1 st proposed, which can serve as supplementary reading material for general physics learners and instructors for in-depth explanations or alternative perspectives on fundamental topics unavailable in textbooks.

Passive solar membrane distillation (MD) is an emerging technology to alleviate water scarcity. Recently, its performance has been enhanced by multistage design, though the gains are marginal due to constrained temperature and vapor pressure gradients across the device. This makes condenser cooling enhancement a questionable choice. We argue that condenser heating could suppress the marginal effect of multistage solar MD by unlocking the moisture transport limit in all distillation stages. Here, we propose a stage temperature boosting (STB) concept that directs low-temperature heat to the condensers in the last stages, enhancing moisture transport across all stages. Through STB in the last two stages with a heat flux of 250 W m −2 , a stage-averaged distillation flux of 1.13 L m −2 h −1 S −1 was demonstrated using an 8-stage MD device under one-sun illumination. This represents an 88% enhancement over the state-of-the-art 10-stage solar MD devices. More notably, our analysis indicates that 16-stage STB-MD devices driven by solar energy and waste heat can effectively compete with existing photovoltaic reverse osmosis (PV-RO) systems, potentially elevating freshwater production with low-temperature heat sources. Multistage solar membrane distillation is facing challenges with current system designs due to constrained temperature and vapor pressure gradients. Here, the authors propose a stage temperature-boosting concept that enhances moisture transport with up to 88% improvement in overall distillate flux.

This study experimentally investigates axial fan pressure recovery in an A-frame forced draft heat exchanger configuration using a scaled isothermal test facility. Three different scaled axial fans were tested to determine pressure recovery coefficients by analysing the discrepancies between design (ignoring recovery) and measured air volume flow rates. The experimental findings confirm the presence of pressure recovery, with calculated recovery coefficients ranging from 0.293 to 0.427.

As a reactive power compensation device, fault diagnosis of synchronous condensers is of great significance for ensuring the stable operation of UHV DC transmission systems. Traditional fault diagnosis methods based on vibration signals have limitations, and existing signal decomposition methods also have their respective shortcomings. This paper proposes a wide-domain feature decomposition (WDFD) method, which first performs preliminary mode decomposition of signals according to spectral trends, then calculates the wide-domain feature indicator of each mode to quantify fault information in both time and frequency domains, and finally uses envelope demodulation for fault diagnosis. Verifications through simulated signal and experimental signal of synchronous condenser show that WDFD can effectively extract the modulation pulse characteristics in the fault signal of condenser. Compared with traditional methods, it can more accurately realize fault diagnosis of synchronous condensers under complex interferences, which provides a new effective approach for fault diagnosis of synchronous condensers.

Steam flow-induced vibration (FIV) of cooling tubes poses critical failure risks in nuclear power plant condensers. However, accurate FIV prediction remains challenging due to the complex three-dimensional flow structures in full-scale condensers, which are often oversimplified in existing models. To address this gap, this study develops a novel full-scale Computational Fluid Dynamics (CFD) model that uniquely integrates the low-pressure exhaust cylinder, condenser throat, and tube bundles. This approach enables a comprehensive evaluation of shell-side flow characteristics and FIV phenomena under both Valve Wide Open (VWO) and partial-load conditions (with either Modules A/C or B/D active). The results quantitatively identify peak FIV risk coefficients in specific zones—particularly at branch-shaped channel inlets and certain tube bundle corners where steam impingement is most intense—with values reaching 0.7 under VWO, 0.67 with Modules A/C active, and 0.74 with Modules B/D active. Notably, the peak FIV risk under B/D active condition is approximately 10.4% higher than under A/C active condition, indicating that partial-load operation with Modules B/D active presents the highest FIV risk among investigated scenarios. These findings provide novel insights into FIV mechanisms and establish a critical theoretical foundation for optimizing condenser design and enhancing operational safety protocols.

The cooling system is essential for the safe and stable operation of power equipment, with the condenser as its principal component. This paper develops eight simulation models for the vertical tubes of a shell-and-tube condenser. Two-phase flow heat transfer simulations are used to determine the flow resistance and heat transfer characteristics of each configuration. The results are compared with theoretical calculations to validate the simulation approach. The simulations indicate that the reinforced tube 1 configuration delivers the best heat transfer performance, increasing heat output by 51.74% relative to the plain tube design while producing only a modest rise in pressure drop. This simulation result can provide guidance for the structural optimization of shell-and-tube condensers.

Access to safely managed drinking water (SMDW) remains a global challenge, and affects 2.2 billion people 1 , 2 . Solar-driven atmospheric water harvesting (AWH) devices with continuous cycling may accelerate progress by enabling decentralized extraction of water from air 3 – 6 , but low specific yields (SY) and low daytime relative humidity (RH) have raised questions about their performance (in litres of water output per day) 7 – 11 . However, to our knowledge, no analysis has mapped the global potential of AWH 12 despite favourable conditions in tropical regions, where two-thirds of people without SMDW live 2 . Here we show that AWH could provide SMDW for a billion people. Our assessment—using Google Earth Engine 13 —introduces a hypothetical 1-metre-square device with a SY profile of 0.2 to 2.5 litres per kilowatt-hour (0.1 to 1.25 litres per kilowatt-hour for a 2-metre-square device) at 30% to 90% RH, respectively. Such a device could meet a target average daily drinking water requirement of 5 litres per day per person 14 . We plot the impact potential of existing devices and new sorbent classes, which suggests that these targets could be met with continued technological development, and well within thermodynamic limits. Indeed, these performance targets have been achieved experimentally in demonstrations of sorbent materials 15 – 17 . Our tools can inform design trade-offs for atmospheric water harvesting devices that maximize global impact, alongside ongoing efforts to meet Sustainable Development Goals (SDGs) with existing technologies. Mapping of the global potential of atmospheric water harvesting using solar energy shows that it could provide safely managed drinking water for a billion people worldwide based on climate suitability.

Steam condensers are vital components of thermal power plants, responsible for converting turbine exhaust steam back into water for reuse in the power generation cycle. Effective pressure regulation is crucial to ensure operational efficiency and equipment safety. However, conventional control strategies, such as PI, PI-PDn and FOPID controllers, often struggle to manage the nonlinearities and disturbances inherent in steam condenser systems. This paper introduces a novel multistage controller, TDn(1 + PIDn), optimized using the diligent crow search algorithm (DCSA). The proposed controller is specifically designed to address system nonlinearities, external disturbances, and the complexities of dynamic responses in steam condensers. Key contributions include the development of a flexible multi-stage control framework and its optimization via DCSA to achieve enhanced stability, faster response times, and reduced steady-state errors. Simulation results demonstrate that the TDn(1 + PIDn) controller outperforms conventional control strategies, including those tuned with advanced metaheuristic algorithms, in terms of settling time, overshoot, and integral of time weighted absolute error (ITAE). This study marks a significant advancement in pressure regulation strategies, providing a robust and adaptive solution for nonlinear industrial systems.

This paper proposes an innovative approach for predicting faults in synchronous condensers in ultra-high voltage direct current (UHVDC) transmission systems. The framework combines Wavelet Packet Transform (WPT) for intelligent feature extraction with an enhanced Gated Recurrent Unit (GRU) network augmented by multi-head attention mechanisms. WPT is employed for efficient decomposition of fault signals into multiple frequency sub-bands, facilitating the extraction of fault features such as energy, entropy, and statistical moments. By applying Large Language Models (LLM) to WPT, an intelligent feature selection mechanism significantly improves both detection accuracy and processing efficiency. The Multi-Head Attention GRU (MHA-GRU) network architecture is designed to capture complex temporal dependencies in fault signals while maintaining computational efficiency. Comprehensive experimental results demonstrate that our framework consistently outperforms state-of-the-art methods across all performance metrics, including classification accuracy, detection time, and false alarm rate. The system exhibits robust stability under varying load conditions with particularly significant improvements in air-gap eccentricity fault detection. The proposed approach provides a reliable solution for early fault prediction in UHVDC synchronous condensers, enabling timely maintenance intervention before minor issues develop into critical failures.