Countries in south east Asia are mostly experiencing tropical climate conditions. Therefore, the use of the air conditioning has been increased to reduce the tension and achieve thermal comfort inside the buildings. In order to reduce the energy consumption, thermal insulation has been introduced to lower down the indoor temperature. The main objective of this study is to determine the optimum thickness of the glass wool insulation. To conduct the study, a wooden room model is built based on the classroom that located at one of the Malaysian universities. The thicknesses of the glass wool insulation used in the experiment is 25 mm (one layer), 50 mm (two layers) and 75 mm (three layers). According to the results, the maximum temperature reduction for one layer of insulation is 1.0°C. Two layers of insulation reduces the indoor temperature by 1.3°C followed by the reduction of 1.5°C after applying three layers of insulation. The convection coefficient outside and inside is determined to calculate the heat flux of the roof with different insulation thickness. The heat flux gained by the roof reaches the highest value at 1 pm which is 0.648 W/m² without insulation. The heat flux has been reduced to 0.629 W/m² after applying one layer of glass wool insulation. The heat flux gained by the roof is further reduced to 0.573 W/m² and 0.518 W/m² when two and three layers of insulation are applied, respectively. Throughout the experiment, the temperature inside the room is reduced with the increase of the insulation thickness. Two layers of glass wool insulation has been selected as the optimum insulation thickness which is validated after performing calculation using the polynomial function as well as the cost analysis. Two layers of glass wool insulation yields a 27.40% of ROI per annum.

The concise review systematically summarises the state-of-the-art variants of Moving Least Squares (MLS) method. MLS method is a mathematical tool which could render cogent support in data interpolation, shape construction and formulation of meshfree schemes, particularly due to its flexibility to form complex arithmetic equation. However, the conventional MLS method is suffering to deal with discontinuity of field variables. Varied strategies of overcoming such shortfall are discussed in current work. Although numerous MLS variants were proposed since the introduction of MLS method in numerical/statistical analysis, there is no technical review made on how the methods evolve. The current review is structured according to major strategies on how to improvise MLS method: the modification of weight function, the manipulation of discrete norms, the inclusion of iterative feature for residuals minimising and integration of these strategies for more robust computation. A wide range of advanced MLS variants have been compiled, summarised, and reappraised according to its underlying principle of improvement. In addition, inherent limitation of MLS method and its possible strategy of improvement is discussed too in this article. The current work could render valuable reference to implement and develop advanced MLS schemes, whenever complexity of the specific scientific problems arose.

Now a days, the global warming has increased the temperature in the environment that forced the building occupant to get assisting from the air condition to reduce the heat tension inside the building, this could increase the electricity bill amount. The aim of this study is to measure the optimum thickness of Rockwool insulation to experimentally and numerically to reduce the heating load inside the buildings. Two devices have been used through this research, Infrared Thermometer to measure profile temperature of the walls along with VELOCICALC to measure the air temperature and air velocity. Three different layers of Rockwool insulation have been applied on the roof of wooden room. The data present the two layers thickness of Rockwool is the best selection to reduce the heating load inside the room, the differential between outside and inside is 0.9 °C, the Rockwool of one layer reduced only 0.5 °C and the maximum thickness with three layers reduced only 1 °C, which is not much effective compared to the two layers but even more costly. CFD analysis shows agreement with the experimental result. The results shows if the dimensions of a UCSI lecture room is to be considered, then applying Rockwool insulation with a thickness of 100 mm would cost around RM 1520 as a UCSI lecture room is of 8 m width and 9 m length. However, two layers of Rock wool insulation could save around 29.30% of ROI per annum.

Battery thermal management systems (BTMS) ensure the safety and performance of lithium-ion batteries, which power electric vehicles. However, designing an effective BTMS is challenging due to batteries' complex thermal behaviour and sensitivity to temperature variations. This review comprehensively explores the current vital technologies and trends in BTMS, explicitly focusing on analysing various cooling technologies and control strategies. To discuss four primary cooling technologies: air cooling, liquid cooling, immersion cooling, and phase change material (PCM) cooling. The advantages and disadvantages of each cooling technology are compared in terms of cost-effectiveness, applicability, and limitations when dealing with high-energy-density batteries. Furthermore, the review delves into the discussion of control strategies and data prediction methods for BTMS, emphasizing the importance of advanced data analysis and control strategies in optimising battery performance and safety. Different control strategies, such as passive, active, and hybrid control, are introduced and evaluated. Data prediction methods, such as artificial neural networks, fuzzy logic, and machine learning, are also presented and discussed. This comprehensive review provides an in-depth understanding of current battery thermal management technologies while serving as a valuable reference for future research and application.