Modeling magnetic nanopolymer flow with induction and nanoparticle solid volume fraction effects : solar magnetic nanopolymer fabrication simulation

A mathematical model is presented for the nonlinear steady, forced convection, hydromagnetic flow of electro-conductive magnetic nano-polymer with magnetic induction effects included. The transformed two-parameter, non-dimensional governing partial differential equations for mass, momentum, magnetic induction and heat conservation are solved with the local non-similarity method (LNM) subject to appropriate boundary conditions. Keller’s implicit finite difference “box” method (KBM) is used to validate solutions. Computations for four different nanoparticles and three different base fluids are included. Silver nanoparticles in combination with various base fluids enhance temperatures and induced magnetic field and accelerate the flow. An elevation in magnetic body force number decelerates the flow whereas an increase in magnetic Prandtl number elevates the magnetic induction. Furthermore, increasing nanoparticle solid volume fraction is found to substantially boost temperatures. Applications of the study arise in advanced magnetic solar nano-materials (fluids) processing technologies

Speed-up robust features based 3D object recognition for grasping by three fingered robot hand / Nurul Hanani Remeli

The ability to manipulate objects is one of the important requirements for industrial robots. Robot that exhibits human-like abilities needs the application of multiple sensors to recognise objects or environment for their tasks. In previous work, a 7-Degree Of Freedom (DOF) three fingered robot hand had been developed for a grasping task. The reference position of the robot hand however was programmed based on predetermined motor positions of the joints for grasping two different shapes of object. The work showed successful grasping by the robot but was unable to generate the motor position on its own since no external sensor was used to recognise the position of the targeted object, hence it is not fully automated. Thus, vision as one of the sensors that can provide rich information was adopted to the robot system where two object image processing methods which are the Speed-Up Robust Features (SURF) and Scale Invariant Feature Transform (SIFT) algorithms were investigated for 2D image recognition of target object in a cluttered environment. Both methods are compared based on the detection performance on several orientations of object in real scene. The information from the method with less detection error is later selected to calculate the object position. Next, the 3D position and grasping points of target object was determined by combining the recognised positions from two 2D SURF images and the triangulation method .The identified object grasping points were then converted to robot space using the robot’s transformation equation derived based on the locations and orientation of robot and camera in the 3D workplace. The proposed method was verified through real-time grasping experiments where the target object was displaced for several positions along the x-axis and y-axis directions. Meanwhile, the strength of the gripping force is measured by comparing the result of motor position angle with the voltage from a force sensor attached at each of the robot finger tips. The result proved that the capability of the SURF algorithm to be better in recognising 100% of the target object without fail for nine random images but it has produced accumulated error throughout the steps in getting the 3D position. However, the errors that occurred in the 3D positions were due to the limitation in SURF and human error during manual measurements with the highest error observed at 3.90 cm. Meanwhile, the transformation equation has successfully calculated that object positions to be inclined towards the direction of the actual measured position in the robot’s coordinates. Finally, the real-time experiment result proved the capability of robot to perform grasping task in real-time autonomous operations with the highest object’s position error produced by SURF was 1.24cm in x axis direction. All of the fingers grasped the object at the same time and lifted the object according to the reference position provided by vision

Experimental investigation on an integrated thermal management system with heat pipe heat exchanger for electric vehicle

An integrated thermal management system combining a heat pipe battery cooling/preheating system with the heat pump air conditioning system is presented to fulfill the comprehensive energy utilization for electric vehicles. A test bench with battery heat pipe heat exchanger and heat pump air conditioning for a regular five-chair electric car is set up to research the performance of this integrated system under different working conditions. The investigation results show that as the system is designed to meet the basic cabinet cooling demand, the additional parallel branch of battery chiller is a good way to solve the battery group cooling problem, which can supply about 20% additional cooling capacity without input power increase. Its coefficient of performance for cabinet heating is around 1.34 at −20 °C out-car temperature and 20 °C in-car temperature. The specific heat of the battery group is tested about 1.24 kJ/kg °C. There exists a necessary temperature condition for the heat pipe heat exchanger to start action. The heat pipe heat transfer performance is around 0.87 W/°C on cooling mode and 1.11 W/°C on preheating mode. The gravity role makes the heat transfer performance of the heat pipe on preheating mode better than that on cooling mode

Towards Reliable Multisensory Perception and Its Automotive Applications

Autonomous driving poses numerous challenging problems, one of which is perceiving and understanding the environment. Since self-driving is safety critical and many actions taken during driving rely on the outcome of various perception algorithms (for instance all traffic participants and infrastructural objects in the vehicle's surroundings must reliably be recognized and localized), thus the perception might be considered as one of the most critical subsystems in an autonomous vehicle. Although the perception itself might further be decomposed into various sub-problems, such as object detection, lane detection, traffic sign detection, environment modeling, etc. In this paper the focus is on fusion models in general (giving support for multisensory data processing) and some related automotive applications such as object detection, traffic sign recognition, end-to-end driving models and an example of taking decisions in multi-criterial traffic situations that are complex for both human drivers and for the self-driving vehicles as well

KEPUASAN PELANCONG TERHADAP PUSAT MEMBELI - BELAH DI A’ FAMOSA PREMIUM OUTLET (MPO)

Selari dengan haluan ke arah Negara berpendapatan perkapita yang tinggi dan gaya hidup moden, pusat membeli- belah semakin menjadi tumpuan orang ramai. Pusat membeli- belah pula pesat bercambah. Tujuan utama kajian ini diadakan adalah untuk mengenal pasti kepuasan pelancong terhadap pusat membeli- belah di A’ Famosa Premium Outlet (MPO) dan pembolehubah bebas itu, yang termasuk destinasi, imej dan kemudahan. Hasil analisis statistik dianalisis dengan menggunakan Pakej Statistik bagi Sains Sosial (SPSS) versi 24.0 . Beberapa analisis telah dijalankan unutk mengkaji hubungan kepuasan pelancong terhadap pusat membeli- belah di A’ Famosa Premium Outlet (MPO). Oleh itu, Ujian Pearson Kolerasi untuk analisis inferensi digunakan untuk menguji hipotesis dalam projek penyelidikan ini

Cabaran-cabaran tentang data bersepadu (data integration) / Mohd Ridwan Seman @ Kamarulzaman and Mohd Rozi Remeli @ Rameli

Data bersepadu (Data Integration) adalah merupakan satu teknologi yang amat penting di dunia atas talian (online world) terutamanya di kalangan organisasi perniagaan yang bergantung kepada ketepatan dan kepantasan data di dalam membuat keputusan strategik. Walaubagaimana pun, terdapat pelbagai cabaran dan isu di dalam mengimplementasikan teknologi ini. Antaranya ialah; isu data itu sendiri, isu keselamatan data, isu manusia (pengguna dan penxedia teknologi), teknologi dan perkasasan dan isu kos

Marangoni mixed convection boundary layer flow in ananofluid

The problem of Marangoni mixed convection boundary layer flow and heat transfer that can be formed along the interface of two immiscible fluids in a nanofluid is studied using different types of nanoparticles. Numerical solutions of the similarity equations are obtained using the shooting method. Three types of metallic or nonmetallic nanoparticles, namely copper (Cu ), alumina ( Al O2 3 ) and titania (TiO2 ) are consideredby using a water-based fluid to investigate the effect of the solid volume fraction or nanoparticle volume fraction parameter ϕ of the nanofluid. The influences of the interest parameters on the reduced velocity along the interface, velocity profiles as well as the reduced heat transfer at the interface and temperature profiles were presented in tables and figures

Assessing the impact of dual alcohol blends on diesel engine performance and exhaust emissions / Muhammad Fairuz Remeli, Muhammad Aiman Hakim Haron and Baljit Singh

The increasing reliance on diesel fuel has heightened concerns about depleting fossil fuel reserves and environmental impacts. In response, researchers are exploring alternative fuel options, such as blends of alcohol and diesel, to improve sustainability. This study investigates the performance and emissions characteristics of several ethanol, methanol, and diethyl ether (DEE) blends with biodiesel and diesel. The tested fuel blends include B10 (90% diesel, 10% biodiesel), BDE (75% diesel, 10% biodiesel, 15% ethanol), BDE2DEE (75% diesel, 10% biodiesel, 15% ethanol, 2% DEE), BDE5DEE (75% diesel, 10% biodiesel, 15% ethanol, 5% DEE), and MBD2DEE (75% diesel, 10% biodiesel, 15% methanol, 2% DEE). Engine performance was evaluated in terms of brake-specific fuel consumption (BSFC), brake power, exhaust gas temperature, and mass and volume flow rates at varying engine loads. The results demonstrate that fuel blends with diethyl ether, particularly BDE5DEE, exhibited superior performance in reducing emissions. NOx emissions decreased by up to 16.2%, while CO2 emissions were reduced by 15.0%. Additionally, blends with diethyl ether lowered brake-specific fuel consumption by 30.7% compared to standard diesel (B10). The blend MBD2DEE, which includes methanol, delivered the highest brake power at higher loads (75%), peaking at 2.91 kW, indicating its strong potential for high-load applications. These findings suggest that dual alcohol-diesel blends, especially those containing diethyl ethers, offer a promising route for improving fuel efficiency and reducing harmful emissions, making them viable alternatives to traditional diesel fuel