Selection of phase‐change material for thermal management of electronic devices usingmulti‐attributedecision‐making technique

Abstract

Selection of proper phase-change material (PCM) plays a crucial role in the development of latent heat thermal management module. Very often, selection of improper material leads to early failure of the product which results in huge economic loss. Most of the researchers utilize PCM in a particular application based on their experience and availability. The designer needs to consider all possible alternatives and evaluate in terms of various conflicting criteria or attributes. The optimal selection of PCM for a particular application is a multiattribute decision-making problem. Here, two evaluation techniques such as technique for order of preference by similarity to ideal solution (TOPSIS) and fuzzy TOPSIS are employed to select the optimal PCM for thermal management of electronic components. The analytical hierarchy process technique is utilized to determine the weight of the attributes. The present study considers 30 PCMs and 11 attributes for the selection of best PCM. The results are compared with both the methods and it is observed that RT 44 HC is found to be optimal PCM for thermal management of electronic components. The model is validated and results are found to be in good agreement with the existing experimental results.

Optimal Design of an Eco-Friendly Transportation Network under Uncertain Parameters

“…According to Yang et al [46],"A monotone increasing function defined as ξ: ℜ→ [0, 1] will be called an uncertainty distribution if and only if the function's monotonicity is continuous excluding Θ(x) ≡ 0 and Θ(x) ≡ 1".…”

“…A variable that is uncertain denoted by 𝑍𝑍 (𝑎𝑎, 𝑏𝑏, 𝑐𝑐), with the condition 𝑎𝑎 < 𝑏𝑏 < 𝑐𝑐 for 𝑎𝑎, 𝑏𝑏, 𝑐𝑐 ∈ ℜ, is called zigzag if it is following a zigzag uncertainty distribution: To simplify the use of the zigzag uncertain variable, it has to be converted to equivalent crisp form using the reduction method based on the expected value. In the paper of Yang et al [46], the method of reduction based on the expected value is shown below:…”

“…To simplify the use of the zigzag uncertain variable, it has to be converted to equivalent crisp form using the reduction method based on the expected value. In the paper of Yang et al [46], the method of reduction based on the expected value is shown below:…”

“…Because of the simple methodological aspect of the TOPSIS, this study considers this method as well [45,46]. The correlation of attributes sometimes makes it difficult to keep the consistency of judgment in many MCDM methods, whereas TOPSIS does not focus on the correlation between attributes.…”

Development of Application Specific Intelligent Framework for the Optimized Selection of Industrial Grade Magnetic Material

“…They proved that the MCDM algorithm provides the best solution for solving the selection of suitable coating materials to minimize the wear issue. Similarly, Kumar et al [12] used MCDM, i.e., AHP and TOPSIS, for a selection of phase-change material (PCM) in thermal control of electronic components and found that AISI A2 steel is the best option for the mentioned application. In Iran's semi-arid area, two MADM methods have been used to design the best water supply plant.…”