Using porous metals to enhance heat transfer in phase change materials (PCMs)

Heat transfer enhancement mechanism of Phase Change Materials (PCMs) by high-porosity metal foams was investigated in this study. The Darcy-Brinkman-Forchheimer modified flow model was employed in the numerical simulations to consider the non-Darcy effects in metal foams: viscous flow resistance and inertia flow resistance. Local Non-Thermal Equilibrium (LNTE) model was used to consider the temperature difference between PCM and metal foam. The results showed that in the solid and two-phase zone the heat transfer rate in PCMs was significantly increased by metal foams, whilst in the liquid zone, natural convection was found to be weakened by the large flow resistance of metal foams, despite which the overall heat transfer rate was still higher than the case where metal foams were not used. Metal foams of low porosity and high pore density were found to perform better than the ones of high porosity and low pore density

Phase change convective heat transfer in high porosity cellular metal foams

This Chapter discusses phase change convective heat transfer of high porosity cellular metal foams and their practical applications in thermal energy storage (TES). The following theoretical aspects are covered: volume-averaging method, Brinkman-Forchheimer porous flow model, two-equation non-thermal equilibrium heat transfer model, enthalpy method, and phase field method. Based on these models, metal foams have been investigated in two applications: metal foam-embedded phase change materials (PCMs), and metal foam-enhanced cascaded TES. The results indicate that metal foams can improve heat and exergy transfer rates in these applications by factors between 2 and 10

Exergy optimisation for cascaded thermal storage

Cascaded thermal storage, consisting of multiple Phase Change Materials (PCMs) with different melting temperatures, has been proposed to solve the problem of poor heat transfer caused by unavoidable decrease of temperature differences during heat exchange process. This paper conducts a theoretical study of the overall thermal performance for a cascaded thermal storage system. Both heat transfer rate and exergy efficiency are taken into account. The main findings are: the cascaded arrangement of PCMs enhances the heat transfer rate by up to 30%, whilst it does not always improve the exergy efficiency (-15 to +30%). Enhanced heat transfer and reduced exergy efficiency can both be attributed to the larger temperature differences caused by the cascaded arrangement. A new parameter hex (exergy transfer rate) has been proposed to measure the overall thermal performance. It is defined as the product of heat transfer rate and exergy efficiency, representing the transfer rate of the utilisable thermal energy. The simulation results indicate that the cascaded thermal storage has higher overall thermal performance than the single-staged storage despite of higher exergy efficiency loss

Analytical considerations of flow boiling heat transfer in metal-foam filled tubes

Flow boiling in metal-foam filled tube was analytically investigated based on a modified microstructure model, an original boiling heat transfer model and fin analysis for metal foams. Microstructure model of metal foams was established, by which fiber diameter and surface area density were precisely predicted. The heat transfer model for flow boiling in metal foams was based on annular pattern, in which two phase fluid was composed by vapor region in the center of the tube and liquid region near the wall. However, it was assumed that nucleate boiling performed only in the liquid region. Fin analysis and heat transfer network for metal foams were integrated to obtain the convective heat transfer coefficient at interface. The analytical solution was verified by its good agreement with experimental data. The parametric study on heat transfer coefficient and boiling mechanism was also carried out

Numerical investigations of heat transfer in phase change materials using non-equilibrium model

Phase change materials (PCMs) are drawing increasing attention of researchers nowadays, and they play a pivotal role in thermal energy storage (TES) used in renewable energy resources applications, since these renewable energy, such as solar energy, wind energy and tidal energy, are intermittent and not available at any time. However, most of PCMs suffer from low thermal conductivities prolonging the charging and discharging processes. Metal foams with relatively high thermal conductivities, are believed to be able to enhance heat transfer performance of PCMs for those applications. In this paper, a two-equation non-thermal equilibrium model has been employed to tackle the phase change heat transfer problem in PCMs composites embedded into metal foams. Numerical results show good agreement with experimental data, and indicate that a better heat transfer performance can be achieved by using the metal foams of smaller pore size and smaller porosity, and heat transfer performance of PCMs can be enhanced by up to 10 times by embedded metal foams into PCMs

Convective Transport Characteristics of Nanofluids in Light- Weight Metal Foams with High Porosity

Metal foams can be well used as ideal materials for various efficient heat transfer devices due to light weight, high specific, and high thermal conductivity. Nanofluids have higher thermal conductivities than traditional fluid, so it can be used as an efficient heat transfer characteristics medium. This paper focuses on heat transfer of nanofluid, metal foam and the combination of the two. The physical properties of nanofluid and metal foam are summarized. The characteristics of flow and heat transfer are introduced. This work creates a close connection between scientific research and practical applications of this dual heat transfer enhancement method

Flow and heat transfer in metal foam filled pipes under two extended Darcy models

The flow and heat transfer in pipes filled with metal foams were studied numerically.In this study,the two-equation model based on LNTE (Local Non-Thermal equilibrium) was employed as energy equations,furthermore the flow models extended by Brinkman and Brinkman-Forchheimer were employed as momentum equations respectively,and a comparison between these two models was made and analysed.The numerical results indicate that the velocity profiles under two models are different,but their temperature profiles are almost the same as each other,consequently,there are barely differences between the Nu numbers under two models.According to numerical results,the Nu number of metal-foam filled pipes is of the order of magnitude of 102～103,which is much bigger than that of bare pipes and conventional heat exchangers.The metal-foam filled pipes exhibit excellent heat transfer performance,however high pressure drop is produced at the same time.By using the program for heat transfer calculation of metal foam that is developed by us,someone can make optimization of heat transfer and pressure drop in practical applications

MILL: Mutual Verification with Large Language Models for Zero-Shot Query Expansion

Query expansion is a commonly-used technique in many search systems to better represent users' information needs with additional query terms. Existing studies for this task usually propose to expand a query with retrieved or generated contextual documents. However, both types of methods have clear limitations. For retrieval-based methods, the documents retrieved with the original query might not be accurate enough to reveal the search intent, especially when the query is brief or ambiguous. For generation-based methods, existing models can hardly be trained or aligned on a particular corpus, due to the lack of corpus-specific labeled data. In this paper, we propose a novel Large Language Model (LLM) based mutual verification framework for query expansion, which alleviates the aforementioned limitations. Specifically, we first design a query-query-document generation pipeline, which can effectively leverage the contextual knowledge encoded in LLMs to generate sub-queries and corresponding documents from multiple perspectives. Next, we employ a mutual verification method for both generated and retrieved contextual documents, where 1) retrieved documents are filtered with the external contextual knowledge in generated documents, and 2) generated documents are filtered with the corpus-specific knowledge in retrieved documents. Overall, the proposed method allows retrieved and generated documents to complement each other to finalize a better query expansion. We conduct extensive experiments on three information retrieval datasets, i.e., TREC-DL-2020, TREC-COVID, and MSMARCO. The results demonstrate that our method outperforms other baselines significantly