Optimizing fin design for a PCM-based thermal storage device using dynamic Kriging

Augspurger, Mike; Choi, Kyung K.; Udaykumar, H. S.

doi:10.1016/j.ijheatmasstransfer.2017.12.143

Cited by 29 publications

(11 citation statements)

References 69 publications

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“…Mesh refinement was carried out at severe temperature variations, where the PCM and fractal net fins were in contact (see Figure 2a). In order to ensure the efficiency of the calculations and the accuracy of calculation results, a series of mesh sizes (16,942,31,556,46,750,56,794,63,138,66,706 and 70,954) were tried to ensure the present numerical results were independent of the mesh size. Duration time is the time consumption when the PCM completely melts in the thermal energy storage unit.…”

Section: Materials λ/W•(m•k)mentioning

confidence: 99%

“…In addition, PCMs generally have the disadvantages of poor thermal conductivity, low energy storage/release efficiency, and a heat transfer unit that is too large, which leads to a larger temperature gradient inside the PCM during the working process, increasing the energy loss of heat transfer and hindering the application of PCMs in thermal energy storage. A wide range of approaches have been applied to enhance the heat transfer performance of PCMs, including dispersing particles [12][13][14], adding fins [15,16], metal foam [17][18][19], composite methods [20,21], and more, which have proven that adding high thermal conductivity materials in various forms improves the heat transfer performance of the PCMs to a certain extent. After optimizing their performance, PCMs will have wider application prospects in the fields of building energy conservation, waste heat recovery, thermal protection of electronic devices, solar power plants, and so forth.…”

Section: Introductionmentioning

confidence: 99%

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Optimization of the Melting Performance of a Thermal Energy Storage Unit with Fractal Net Fins

Zheng

Chen

et al. 2019

Processes

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In this study, fractal net fins were introduced to improve the melting performance of a thermal energy storage unit. A transient model for melting heat transfer for phase change material (PCM) was presented and numerically analyzed, to study the melting performance in a thermal energy storage unit using fractal net fins. The melting phase change process was modelled using the apparent heat capacity method. The evolutions of temperature and the liquid fraction in the thermal energy storage unit were investigated and discussed. The effects of the length and width ratios of the fractal net on melting performance were analyzed to obtain the optimal fin configuration. The results indicated that the fractal net fins significantly enhanced the melting heat transfer performance of the PCM in a thermal energy storage unit. The fractal net fins configuration was optimal when the length and width ratios of the fractal net were 0.5. The temperature response at the corner points of the fractal net fins was faster than that in the central points.

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Section: Materials λ/W•(m•k)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimization of the Melting Performance of a Thermal Energy Storage Unit with Fractal Net Fins

Zheng

Chen

et al. 2019

Processes

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“…Over the years, researchers have employed both experimental and computational techniques to design and analyze thermal storage units. [1] simulate an optimization procedure for a fin based thermal storage unit. After selecting the factors that were significant, they carried out optimization using a multidimensional response surface method.…”

Section: Introductionmentioning

confidence: 99%

“…Simulation of processes and systems have been carried out for years by researchers with the aim of having an idea about what the outcomes of a system will be without having to incur cost associated with experimentation ( [9]; [10]; [11]; [2]; [12]; [13]; [14]; [1]; [8]). These simulations are useful as a guide in anticipation of possible challenges during experimentation.…”

Section: Introductionmentioning

confidence: 99%

Minimizing Heat Loss Rate in Kaolin Thermal Insulation Layer in the Range of 800 to 1000 0C

Enoch¹,

Lola²,

Amanda³

et al. 2020

International Journal of Engineering Research and Technology

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Storage of thermal energy has become a growing area of interest amongst researchers over the past few decades. This is so because of the wide variety of applications that can benefit from this technology. When perfected, waste heat from industrial plants and the sun can be stored for reuse at a later point in time, thus improving the energy efficiency of the system. Heat loss is a significant challenge that affects the efficiency of a thermal storage system especially at the high temperature range. In minimizing heat loss rate of thermal insulation layer, this work aims to use simulation models to determine and minimize rate of heat loss of a simulated cylindrical kaolin thermal insulator within the working temperature range of 800 -1000 o C. Two direction were used which are radial and axial. They were simulated and analyzed one after the other. Two simulation software were employed to validate the results from each of them. Length of thermal insulation, temperature of inner surface and ambient temperature were the independent variables accounted for this work while the rate of heat loss at the outer surface was the dependent variable. In the axial direction, the dependent variable was more sensitive to changes in the independent variables compared to the radial direction. The change in the length of the thermal insulation layer had the highest impact on the dependent variable followed by the temperature of the internal surface and then lastly by the combined effect of these two factors. The effect of ambient temperature was insignificant. From the results of the work, suggestion was made from the simulation results, that the length of 0.22 m will be used to construct a portable thermal storage unit within the operating temperature range of 700 -900 o C. In conclusion, results will also serve as framework for the simulation at higher working temperatures.

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“…The low heat transfer rate has a great impact on the heat transfer process, so it is very important to improve the thermal conductivity of PCMs. The common methods to enhance heat transfer are using fin structure [6], using capsule structure [7,8], using porous medium structure [9,10], and adding high thermal conductivity material [11,12]. Two or more methods can be used to further improve the thermal conductivity, such as mixing paraffin wax with expanded graphite and then adding the nanomixed material to the aluminum foam [13,14].…”

Section: Introductionmentioning

confidence: 99%

Study on the Thermal Conductivity of Mannitol Enhanced by Graphene Nanoparticles for Thermoelectric Power Generation

Yu¹,

Wang²,

Kong³

et al. 2020

Journal of Nanomaterials

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The existing thermoelectric materials are greatly affected by the temperature environment, which can provide better power output in a stable temperature environment by using composite phase change material with enhanced heat conduction. The graphene is dispersed in the liquid mannitol to make the nanomixed material. Test results show that the thermal conductivity of mannitol increased from 0.7 Wm-1 K-1 to 2.07 Wm-1 K-1, 179.73% times as much. The effective thermal conductivity of mannitol can be increased to 8.4236 Wm-1 K-1 by using a graphite foam with a porosity of 0.9. After adding 1 wt.% and 5 wt.% graphene particles, the effective thermal conductivity increased to 8.73 Wm-1 K-1 and 9.63 Wm-1 K-1, respectively. The simulation results in a large heat source environment show that mannitol with improved thermal conductivity can ensure the stable operation of the thermoelectric material in the optimal temperature environment for 120 s, and the open-circuit voltage is maintained at about 6.5 V in that time.

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Optimizing fin design for a PCM-based thermal storage device using dynamic Kriging

Cited by 29 publications

References 69 publications

Optimization of the Melting Performance of a Thermal Energy Storage Unit with Fractal Net Fins

Optimization of the Melting Performance of a Thermal Energy Storage Unit with Fractal Net Fins

Minimizing Heat Loss Rate in Kaolin Thermal Insulation Layer in the Range of 800 to 1000 0C

Study on the Thermal Conductivity of Mannitol Enhanced by Graphene Nanoparticles for Thermoelectric Power Generation

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