This study investigates transient magnetohydrodynamic (MHD) flow and heat transfer of a hybrid nanofluid over a stretching sheet under thermal radiation and buoyancy effects. The governing equations are transformed into a nonlinear system of ordinary differential equations using similarity transformations and solved numerically using the Spectral Quasilinearisation Method (SQLM). The effects of the magnetic parameter, thermal radiation parameter, unsteadiness parameter, and buoyancy parameter on the velocity and temperature distributions, skin-friction coefficient, and Nusselt number are examined. The results show that increasing the magnetic parameter from M=1 to M=5 reduces the Nusselt number from 13.7509 to 13.1469 for the nanofluid and from 13.8487 to 13.2020 for the hybrid nanofluid. In contrast, increasing the thermal radiation parameter from Rd=1 to Rd=10 increases the Nusselt number from 6.3129 to 13.1469 for the nanofluid and from 6.7787 to 13.2020 for the hybrid nanofluid. Over the same magnetic-parameter range, the skin-friction values change from − 1.5528 to -2.8045 for the nanofluid and from − 1.0825 to -3.3566 for the hybrid nanofluid. The numerical temperature profiles are also used to assess an artificial neural network (ANN) trained through the Levenberg–Marquardt algorithm. For the evaluated temperature-profile datasets, the root-mean-square errors range from 2.44× 10^-5 to 4.96× 10^-5 , demonstrating close agreement between the ANN predictions and the corresponding SQLM profiles.
In recent years, the development of Autonomous Vehicles (AVs) has progressed at a rapid pace, which demonstrates that essential intelligent systems have become crucial for self-driving vehicles to achieve their mission through reliable Vehicle Detection (VD) methods that enable safe decision-making and planning processes. The assessment presents a new evaluation that examines image-based VD methods that AVs use through the implementation of three specific techniques, which include multimodal fusion, point cloud methods, and different 3D detection methods. The assessment of these methods investigates the historical development, current challenges, and the success rates, which depend on different weather conditions and the available datasets. The review analyzes the strengths and weaknesses of image-based detection systems, while it presents advanced single-stage, dual-stage, and 3D detection methods that researchers developed for aerial imagery analysis. The review establishes architectural systems that use Deep Learning (DL) methods to boost recognition performance while explaining the latest developments that have occurred in both monocular and stereo vision systems. This review uses publicly accessible datasets to conduct performance assessments, which produce detailed results about existing research patterns while identifying potential improvements for bettering AV detection technology.
The performance evaluation of corporate financial management refers to a company's ability to plan, control, and use financial resources effectively to meet strategic goals. This is done by analyzing financial indicators of profitability, liquidity, solvency, and operational efficiency. Such an evaluation will highlight strengths and weaknesses. Performance evaluation of corporate financial management is a multi-attribute decision-making (MADM) problem. Recently, the TODIM method and entropy technique have been widely and successfully applied to MADM problems. Double-valued neutrosophic sets (DVNSs) were introduced as an approach to deal with fuzzy and uncertain information during the evaluation process. In this paper, the TODIM approach is extended to MADM under the DVNS framework. In particular, the double-valued neutrosophic number TODIM (DVNN-TODIM) approach is proposed to solve MADM problems. To demonstrate its application, a numerical example concerning corporate financial management performance evaluation has been provided, which shows the applicability of the DVNN-TODIM approach.
Tall buildings with non-regular plans are increasingly built to use urban land efficiently, yet their aerodynamic design still relies on code provisions written for regular plans. This study measures the wind pressure distribution and aerodynamic loads on composite tall building models that combine a rectangular podium with a circular or an elliptical tower, each carrying a through opening. Boundary layer wind tunnel experiments at 1:250 scale and steady Reynolds-averaged simulations in ANSYS CFX were carried out over approach angles from 0° to 90° at 15° intervals. The elliptical tower reduced peak pressure and suction by 8–13
In the past few decades, numerous studies have been reported on using polypropylene (PP) for various engineering applications. Also, several studies have reported the development of PP composites reinforced with bakelite (a thermosetting polymer) via pyrolysis, yielding condensable liquid oil, solid char, syngas, etc. However, little has been reported on the use of the PP-bakelite composite for terminal block applications. This study highlights the development and fabrication of a PP-bakelite composite-based functional prototype, processed via fused filament fabrication (FFF), for use as an electrical insulator in terminal blocks. The PP composites were prepared with different weight proportions of bakelite (5
