Thermal conductivity of packed beds: A review

Tsotsas, Evangelos; Martin, Holger

doi:10.1016/0255-2701(87)80025-9

Cited by 255 publications

(107 citation statements)

References 72 publications

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“…Tsotsas et al compiled multiple analytical approach methods for thermal conductivity determination of gas-filled packed beds [37]. Moreover, the layer based manufacturing methods induce porosity formation layer-by-layer and by each subsequent pass of the hot end compounds the development of air voids.…”

Section: Discussionmentioning

confidence: 99%

Thermal properties of 3-D printed polylactic acid-metal composites

et al. 2017

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Section: Discussionmentioning

confidence: 99%

Thermal properties of 3-D printed polylactic acid-metal composites

et al. 2017

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“…The thermal conductivity of the packed bed l B can be described according to the Krischer-Kröll model (Krischer & Kröll 1956) as an arrangement of serial and parallel components, (6.19) where the parameter a describes the amount of the serial component, j is the volume fraction of the continuous pure-ice phase and l P and l I are the thermal conductivities of the particles and the pure ice, respectively, as shown in figure 4 (Krischer & Kröll 1956;Tsotsas & Martin 1987). Assuming the packed bed to consist of 64 vol% particles and 36 vol% ice, Tsotsas & Martin (1987) suggest to use a = 0.2 for an appropriate description of its thermal conductivity.…”

Section: (D) Thermal Conductivity Of the Freeze-cast Solidmentioning

confidence: 99%

Biomaterials by freeze casting

Wegst

Schecter

Donius

et al. 2010

Phil. Trans. R. Soc. A.

312

254

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The functional requirements for synthetic tissue substitutes appear deceptively simple: they should provide a porous matrix with interconnecting porosity and surface properties that promote rapid tissue ingrowth; at the same time, they should possess sufficient stiffness, strength and toughness to prevent crushing under physiological loads until full integration and healing are reached. Despite extensive efforts and first encouraging results, current biomaterials for tissue regeneration tend to suffer common limitations: insufficient tissue-material interaction and an inherent lack of strength and toughness associated with porosity. The challenge persists to synthesize materials that mimic both structure and mechanical performance of the natural tissue and permit strong tissue-implant interfaces to be formed. In the case of bone substitute materials, for example, the goal is to engineer high-performance composites with effective properties that, similar to natural mineralized tissue, exceed by orders of magnitude the properties of its constituents. It is still difficult with current technology to emulate in synthetic biomaterials multi-level hierarchical composite structures that are thought to be the origin of the observed mechanical property amplification in biological materials. Freeze casting permits to manufacture such complex, hybrid materials through excellent control of structural and mechanical properties. As a processing technique for the manufacture of biomaterials, freeze casting therefore has great promise.

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“…A more detailed review may be found in the articles of Westerterp et al [23] and Tsotsas and Martin [24]. Such an approach requires thermal equilibrium between the two phases of a packed bed and is referred to as the one-equation model.…”

Section: One-phase (Homogeneous) Modelsmentioning

confidence: 99%

Simulation of thermal conversion of solid fuel by the discrete particle method

Peters¹,

Džiugys²,

Navakas³

2011

Lith. J. Phys.

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We introduce the discrete particle method (DPM) that derives from the discrete element method (DEM). This is an advanced numerical simulation tool that takes into account both motion and chemical conversion of granular material, such as coal or biomass, in furnaces in conjunction with computational fluid dynamics (CFD). However, predictions of solely motion or conversion in a decoupled mode are also applicable. The DPM uses object oriented computational techniques that support objects representing three-dimensional particles of various shapes, size, and physical properties of particle material. This makes DPM a highly versatile tool in dealing with a variety of problems related to different industrial applications of granular matter. A review of literature concerning different approaches to mass and heat transfer in packed beds is presented.

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Thermal conductivity of packed beds: A review

Cited by 255 publications

References 72 publications

Thermal properties of 3-D printed polylactic acid-metal composites

Thermal properties of 3-D printed polylactic acid-metal composites

Biomaterials by freeze casting

Simulation of thermal conversion of solid fuel by the discrete particle method

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