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The purpose of this paper is to show how, with a view to the shortcomings of traditional optimization methods, a multi‐objective optimization concerning the structure sizes of micro‐channel heat sink is performed by adaptive genetic algorithm. The optimized micro‐channel heat sink is simulated by computational fluid dynamics (CFD) method, and the total thermal resistance is calculated to compare with that of thermal resistance network model.

Taking the thermal resistance and the pressure drop as goal functions, a multi‐objective optimization model was proposed for the micro‐channel cooling heat sink based on the thermal resistance network model. The coupled solution of the flow and heat transfer is considered in the optimization process, and the aim of the procedure is to find the geometry most favorable to simultaneously maximize heat transfer while obtaining a minimum pressure drop. The optimized micro‐channel heat sink was numerically simulated by CFD software.

The results of optimization show that the base convection thermal resistance contributes to maximum the total thermal resistance, and base conduction thermal resistance contributes to least. The width of optimized micro‐channel and fin are 197 and 50 μm, respectively, and the corresponding total thermal resistance of the whole micro‐channel heat sink is 0.838 K/W, which agrees well with the analysis result of thermal resistance network model.

The convection heat transfer coefficient is calculated approximately here for convenience, and that may induce some errors.

The maximum difference in temperature of the optimized micro‐channel cooling heat sink is 84.706 K, which may satisfy the requirement for removal of high heat flux in new‐generation chips. The numerical simulation results are also presented, and the results of numerical simulation show that the optimized micro‐channel heat sink can enhance thermal transfer performance.

To give a new method to calculate the thermal conductivity of thin films which thickness is less than micro‐nanometer when non‐Fourier effect will appear in heat conduction and Fourier law is not applicable for calculating the thermal conductivity.

The Cattaneo equation based on the heat flow relaxation time approximation is used to calculate the thermal conductivity.

The results show that the thermal conductivity is not the thermophysical properties of material, but is the non‐linear function of temperature and film thickness when the dimension of film is less than micro‐nanometer.

The application of this method is limited by little experimental data of heat flow relaxation time for materials other than Ar crystals.

The paper demonstrates how the thermal conductivity of Ar crystals film can be calculated by NEMD algorithm and considers the non‐Fourier effect in the simulation.

This paper sets out to optimize the shape and size of microchannels cooling heat sink, which has been widely used to cool electronic chip for its high heat transfer coefficient and compact structure.

Sequential Quadratic Programming (SQP) method is used to optimize the cross‐section sizes of microchannels. Finite volume method is used to numerically simulate the cooling performance of optimal microchannel cooling heat sink.

The optimized cross‐section shape of microchannel is rectangular, and the width and depth of microchannel is 50 and 1,000 μm, respectively, the number of microchannels is 60, and the corresponding least thermal resistance is 0.115996°C/W. The results show that the heat transfer performance of microchannel cooling heat sink is affected intensively by its cross‐section shape and dimension. The convection heat resistance R_conv between inner surface in microchannels and working fluid has more influence in the total heat resistance. The heat flux of chip is 278 W/cm² and, through the optimization microchannel cooling heat sink, the highest temperature in the chip can be kept below 42°C, which is about half of that without optimizing heat sink and can ensure the stability and reliability of chip.

The convection heat transfer coefficient is calculated approximatively here for convenience, and that may induce some errors.

The optimized microchannels cooling heat sink may satisfy the request for removal of high heat flux in new‐generation chips.

The purpose of this paper is to optimize the configuration sizes of micro‐channel cooling heat sink using the thermal resistance network model. The optimized micro‐channel heat sink is simulated by computational fluid dynamics method, and the total thermal resistance is calculated to compare with that of thermal resistance network model.

Taking the thermal resistance and the pressure drop as goal functions, a multi‐objective optimization model was proposed for the micro‐channel cooling heat sink based on the thermal resistance net work model. The Sequential Quadratic Programming procedure was used to do the optimization design of the structure size of the micro‐channel. The optimized micro‐channel heat sink was numerically simulated by computational fluid dynamics (CFD) software.

For the heat sink to cool a chip with the sizes of L × W = 2.5 mm × 2.5 mm and the power of 8 W, the optimized width and height of the micro‐channel are 154 μm and 1,000 μm, respectively, and its corresponding total thermal resistance is 8.255 K/W. According to the simulation results, the total thermal resistance of whole micro‐channel heat sink R_total is 7.596 K/W, which agrees well with the analysis result of thermal resistance network model.

The convection heat transfer coefficient is calculated approximatively here for convenience, and that may induce some errors. Originality/value –The maximum difference in temperature of the optimized micro‐channel cooling heat sink is 59.064 K, which may satisfy the requirement for removal of high heat flux in new‐generation chips.

This study aims to satisfy the thermal management of gallium nitride (GaN) high-electron mobility transistor (HEMT) devices, microchannel-cooling is designed and optimized in this work.

A numerical simulation is performed to analyze the thermal and flow characteristics of microchannels in combination with computational fluid dynamics (CFD) and multi-objective evolutionary algorithm (MOEA) is used to optimize the microchannels parameters. The design variables include width and number of microchannels, and the optimization objectives are to minimize total thermal resistance and pressure drop under constant volumetric flow rate.

In optimization process, a decrease in pressure drop contributes to increase of thermal resistance leading to high junction temperature and vice versa. And the Pareto-optimal front, which is a trade-off curve between optimization objectives, is obtained by MOEA method. Finally, K-means clustering algorithm is carried out on Pareto-optimal front, and three representative points are proposed to verify the accuracy of the model.

Each design variable on the effect of two objectives and distribution of temperature is researched. The relationship between minimum thermal resistance and pressure drop is provided which can give some fundamental direction for microchannels design in GaN HEMT devices cooling.

This article will select 25 years of subdivided data to perform Kaplan–Meier survival analysis on the export trade relations of Chinese wooden flooring, use discrete-time cloglog models to analyze influencing factors, use logit and probit models to test the robustness, and try to systematically reveal the duration of China's wood flooring export trade and its influencing factors.

This study used Kaplan–Meier survival function estimation method. In the survival analysis, survival function and hazard rate function are often used to characterize the distribution of survival time.

The continuous average export time of China's wooden flooring is relatively long, about 14 years. China's wooden flooring has a negative time dependency. After the export trade exceeds the threshold value of 15 years, the failure rate of trade greatly decreases, which has a “threshold effect.” Gravity model variables have a significant impact on the duration of China's wooden floor export.

Studying the duration of forest products trade is of great significance for clearing deep-level trade relations and promoting sustainable development of forest products trade.

With development of the modern electronic and mechanical devices, cooling requirement has become a serious challenge. Innovative heat transfer enhancement methods are generally accompanied by undesirable increase of pressure drop and consequently a pumping power penalty. The current study aims to present a novel and easy method to manufacture a mini heat sink using porous fins and magnetite nanofluid (Fe₃O₄/water) as the coolant for simultaneous heat transfer enhancement and pressure drop reduction.

A three-dimensional numerical study is carried out to evaluate the thermal and hydrodynamic performance of the mini heat sink at different volume fractions, porosities and Reynolds numbers, using finite volume method. The solver specifications for discretization of the domain involve the SIMPLE, second-order upwind and second order for pressure, momentum and energy, respectively.

Results show that porous fins have a favorable effect on both heat transfer and pressure drop compared to solid fins. Creation of a virtual velocity slip on the channel-fin interfaces similar to the micro scale conditions and the flow permeation into the porous fins are the main mechanisms of pressure drop reduction. On the other hand, the heat transfer enhancement is attributed to the increase of the solid-fluid contact area and the improvement of the flow mixing because of the flow permeation into the porous fins. An optimal porosity for maximum convective heat transfer enhancement is obtained as a function of Reynolds number. However, taking both pressure drop and heat transfer effects into account, the overall heat sink performance is shown to be improved at high of Reynolds numbers, volume fractions and fin porosities.

Thermal radiation and gravity effects are ignored, and thermal equilibrium is assumed between solid and fluid phases.

A maximum of 32 per cent increase of convective heat transfer is achieved along with a maximum of 33 per cent reduction in the pressure drop using porous fins and ferrofluid in heat sink.

The purpose of this paper is to apply two optimization methods to the issue of sensible energy store design.

This paper is a comparison of topology optimization and genetic algorithms.

Genetic algorithms are prone to converge to local maxima while requiring significantly longer convergence times compared to topology optimization. Topology optimization resulted in structures representing parallel sheets, which are as thin as the grid allows. These configurations can maintain the maximum surface area between the low and high conductivity materials at high refinement, resulting in the best performance.

Time required for 99 per cent store discharge is decreased by 70 per cent using a 50 × 50 optimization grid at a loading of 10 Vol.%.

These approaches have not been compared nor applied to this specific problem before. Value is in the key finding that maximization of surface area is only possible with fins/sheets and not tree structures. This dictates the optimal solution for dynamic behaviour.

This article's purpose is to examine the effect of a Classification-Based Forest Management (CFM) program on farmers' income and determine whether its effect varies with the degree of farmers' concurrent occupations.

The authors use representative panel survey data from Longquan to explore the welfare effects of CFM on farmers. The analysis uses differences-in-differences with propensity score matching (PSM-DID) estimation techniques to deal with endogeneity problems when farmers make the decision to participate in CFM.

The results show that CFM has a positive effect on part-time forestry households (where forestry income accounts for between 5 and 50% of total income). In contrast, it has a negative impact on full-time forestry households (forestry income accounts for more than 50%), and no clear effect on nonforestry households whose forestry income is less than 5%. This research also shows that the positive effect of CFM on farmers' total income is mainly due to increase of off-farm income driven by CFM, while the negative effects consist of CFM's reduction of forestry income.

The extent of CFM's economic benefits to farmers is uncertain and largely unexplored. This paper analyzes the impact of CFM on income structure to explore the mechanisms explaining its effects on farmers' income. There are still challenges in ensuring the reliability and accuracy of CFM assessment. This paper collected natural experimental data and used the estimation technology of PSM-DID to solve the possible endogeneity problems.