Nanofluids, an advanced class of heat transfer fluids, have gained significant attention due to their superior thermophysical properties, making them highly effective for various engineering applications. This review explores the impact of nanoparticle integration on the thermal conductivity, viscosity, and overall heat transfer performance of base fluids, highlighting improvements in systems, such as heat exchangers, electronics cooling, PV/T systems, CSP technologies, and geothermal heat recovery. Key mechanisms such as nanolayer formation, Brownian motion, and nanoparticle aggregation are discussed, with a focus on hybrid nanofluids that show enhanced thermal conductivity. The increase in viscosity poses a trade-off, necessitating careful control of the nanoparticle properties to optimize heat transfer while reducing energy consumption. Empirical data show up to a 123% increase in the convective heat transfer coefficients, demonstrating the tangible benefits of nanofluids in energy efficiency and system miniaturization. The review also considers the environmental impacts of nanofluid use, such as potential toxicity and the challenges of sustainable production and disposal. Future research directions include developing hybrid nanofluids with specific properties, integrating nanofluids with phase change materials, and exploring new nanomaterials such as metal chalcogenides to enhance the efficiency and sustainability of thermal management systems.

Suspending particles of tiny solid in a fluid used to transport energy can enhance its thermal conductivity and heat transport properties. Our main goal of this examination is to study the radiative unsteady two-dimensional (2D) flow on a continuously diminishing, horizontal sheet. with suction for the hybrid water-based nanofluid and an aligned field of magnetic, including the combined suction, magnetic, and velocity slip conditions effect. The Tiwari & Das model of nanofluid equations is used, which takes into consideration the solid volume percentage. Equations of similarity are derived by employing the transformations of similarity, and the associated equations have been simplified numerically by employing the bvp4c method in MATLAB software for a variety of values of the nanoparticle volume fraction, the unsteadiness, and the wall mass suction in water. It is discovered that, within the given the unsteadiness parameter range, two solutions exist. Moreover, it is found that the fluid velocity slows down in 1st solution as volume fraction of copper nanoparticles rises but speeds up in the second solution at first before slowing down again. Using a temporal stability analysis, it is found that only one of the dual branches is stable over the long run, while the other is unstable.

During the non-contact geomagnetic detection of pipeline defects, measured signals generally contain noise, which reduces detection efficiency. Complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) has recently emerged as a signal filtering method, but its filtering performance is influenced by two parameters: the amplitude of added noise and the number of ensemble trials. To solve this issue and improve detection accuracy and distinguishability, a detection method based on improved CEEMDAN (ICEEDMAN) and the Teager energy operator (TEO) is proposed. The magnetic detection signal was first decomposed into a series of intrinsic mode functions (IMFs) by CEEMDAN with initial parameters. Signal IMFs were then distinguished using the Hurst exponent to reconstruct the preliminary filtered signal, and its maximum value (except the zero point) of the normalized autocorrelation function was defined as salp swarm algorithm (SSA) fitness. The optimal parameters that maximize fitness were found by SSA iterations, and their corresponding filtered signal was obtained. Finally, the gradient calculation and TEO were carried out to complete non-contact geomagnetic detection. The results of the simulated signal based on magnetic dipole under a noisy environment and field testing prove that ICEEMDAN denoising has better filtering performance than conventional CEEMDAN denoising methods, and ICEEMDAN-TEO has obvious advantages compared to other detection methods in the aspects of location error, peak side-lobe ratio, and integrated side-lobe ratio.

Since Polyethylene (PE) pipes are widely used in urban infrastructure development, their precise localization is paramount. The research on non-excavation localization of buried PE pipes using acoustic methods holds significant practical significance due to the expensive costs and permit issues associated with traditional excavation-based localization methods. A method based on elastic wave reflection for positioning buried PE pipes is proposed in this paper to address the challenges of non-excavation localization of buried PE pipes. Firstly, fundamental theoretical analysis and finite element simulation were carried out to investigate the propagation and reflection of elastic waves in the soil-PE pipe coupled system, guiding subsequent experiments. Secondly, an electromagnetic-driven excitation source is designed to locate buried PE pipelines based on the elastic wave signals reflected by the pipeline. The excitation source is driven by Gaussian pulse-modulated sine waves. Finally, the back projection algorithm (BPA) imaging method generates cross-sectional images of buried PE pipes. The potential economic and environmental benefits of this method are substantial, as it promises to streamline the process of pipeline inspection and maintenance, leading to cost savings. Furthermore, the research paves the way for future advancements in non-excavation technologies, contributing to the sustainable development of urban infrastructure. In conclusion, this study provides a practical and innovative solution for non-excavation positioning of buried PE pipes, influencing the widespread application of acoustic methods in infrastructure management.

Polyethylene (PE) pipes have been widely utilized in urban water supply and gas transportation fields due to their corrosion resistance, high impact resistance, and long lifespan. However, the non-metallic nature of PE pipes poses challenges for precise positioning and maintenance, rendering traditional metal pipeline detection techniques unsuitable. This paper proposes a pipeline excitation method based on acoustic waveguide resonance for locating buried PE pipes. The study first introduces the theoretical basis of acoustic waveguide, including the physical laws of sound vibration and the wave equation of sound waves in ideal homogeneous fluid media. Through finite element simulation, the resonance characteristics of sound waves in straight pipes and T-junction pipes are analyzed, along with the influence of different pipe diameters, pressure levels, and propagation distances on resonance peak values. In the experimental section, a complete excitation source system and data acquisition system are constructed, and experiments are conducted by burying PE pipes for signal collection under various burial depths and conditions. The results indicate that the horizontal orientation of the pipe can be determined by observing the maximum signal amplitude, while an algorithm based on frequency-selective depth positioning can effectively estimate the burial depth of the pipe. While the experiments were conducted on a buried PE pipeline with a depth of 1 m and a diameter of 110 cm, the proposed method demonstrates potential for the detection of various types of pipelines buried at greater depths.