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EN
Endurance capability is a key indicator to evaluate the performance of electric vehicles. Improving the energy density of battery packs in a limited space while ensuring the safety of the vehicle is one of the currently used technological solutions. Accordingly, a small space and high energy density battery arrangement scheme is proposed in this paper. The comprehensive performance of two battery packs based on the same volume and different space arrangements is compared. Further, based on the same thermal management system (PCM-fin system), the thermal performance of staggered battery packs with high energy density is numerically simulated with different fin structures, and the optimal fin structure parameters for staggered battery packs at a 3C discharge rate are determined using the entropy weight-TOPSIS method. The result reveals that increasing the contact thickness between the fin and the battery (X) can reduce the maximum temperature, but weaken temperature homogeneity. Moreover, the change of fin width (A) has no significant effect on the heat dissipation performance of the battery pack. Entropy weight-TOPSIS method objectively assigns weights to both maximum temperature (Tmax) and temperature difference (DT) and determines the optimal solution for the cooling system fin parameters. It is found that when X = 0:67 mm, A = 0:6 mm, the staggered battery pack holds the best comprehensive performance.
EN
Successful mine planning is necessary for the sustainability of mining activities. Since this process depends on many criteria, it can be considered a multi-criteria decision making (MCDM) problem. In this study, an integrated MCDM method based on the combination of the analytic hierarchy process (AHP) and the technique for order of preference by similarity to the ideal solution (TOPSIS) is proposed to select the optimum mine planning in open-pit mines. To prove the applicability of the proposed method, a case study was carried out. Firstly, a decision-making group was created, which consists of mining, geology, planning engineers, investors, and operators. As a result of studies performed by this group, four main criteria, thirteen sub-criteria, and nine mine planning alternatives were determined. Then, AHP was applied to determine the relative weights of evaluation criteria, and TOPSIS was performed to rank the mine planning alternatives. Among the alternatives evaluated, the alternative with the highest net present value was selected as the optimum mine planning alternative. It has been determined that the proposed integrated AHP-TOPSIS method can significantly assist decision-makers in the process of deciding which of the few mine planning alternatives should be implemented in open-pit mines.
EN
In our days' countries pursue not just to have higher or maintain economic growth, but society faces another challenge – to combat climate change: to slower increase of global temperature by decreasing amount of green gas emission. Globalization processes have increased green gas emission. The problem of climate change becomes an overall problem of all countries, as green gas emissions produced by any country has an overall impact on environment of the earth. Public administration and public policies face the problem how to combat climate change not constraining the economy too much. The purpose of the paper is to evaluate the extent to which EU countries are affected to climate change according economic and social factors of countries that can be seen as drivers of green gas emissions. The study relates green gas emission intensity to the extent to which the country is possible to be exploded to climate change according to its data on industry, energy, waste, and agriculture of EU countries. TOPSIS method is used to rank EU countries in combating climate change. The conceptual approach to ranking climate change through the prism of countries economic activities is developed. There are some research limitations – statistical data on the industry, energy, waste, agriculture is limited in order to fulfil the tasks of the research.
EN
Development of design characteristics based dynamic decision support framework is presented in the current study, to facilitate the decision makers in the transformation of system in the industry 4.0 paradigm. The model development is designed for a robust decision-making approach to integrating human and machine knowledge to adopt smart technologies and system design. The system is based on prioritization of the industry 4.0 design principles and characteristics including flexibility, self-adaptability, self-reconfigurability, context awareness, decision autonomy, and real-time capabilities. It has been revealed from an industrial field study, the companies facing difficulty to transform the system, and systematics approach needed to overcome the challenge. A decision support process has been developed as an integrated approach to embedding human knowledge. The developed process has been validated using Technique for Order of Preference by Similarity to Ideal Solution, the results depict the operational flexibility, has been most crucial transformation characteristics prioritized using the Analytical Hierarchical Process. The developed process has the capability to help the system development and estimate the factors involved in the transformation.
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