Heat Transfer Data Research Articles

Temperature effect on the kinetic profile of Ziegler–Natta catalyst in propene polymerization

Propene polymerization kinetic profiles with a diether-based Ziegler–Natta MgCl2-supported catalyst were investigated in a stainless-steel batch reactor. The initial 10 min period characterizes various temperature levels with a constant volume of liquid propene. The lowest temperature level corresponds to the usual prepolymerization temperature (10 °C), and the highest level corresponds to the usual main polymerization temperature (70 °C). The effects of the starting temperature levels were evaluated through polymerization kinetic patterns computed namely from the second polymerization period carried out at 70 °C for the next 90 min. Based on the heat transfer data, the kinetic profiles were fitted to suitable semi-empirical equations derived from fundamental kinetic approaches using the first and second orders of the catalyst active sites decay. Both approaches adequately describe the dependence of the initial activities and deceleration constants on the temperature during the initial period.

Aerothermal performance of two-pass channel with tilted grater-baffles

Aerothermal performances of four two-pass channels enhanced by tilted 90° or 60° grater-baffles with one- or two-rows of perforation are studied. Aerothermal impacts of baffle attack angle and perforation row-number on Nusselt number (Nu) distribution, friction factor (f), and aerothermal performance index (API) are cross examined. Cold streams from duct core are confluent in oval dimples to eject through inclined grater-baffle as impinging jets that diminish boundary layers at stagnation spots and augment core-to-wall mixings, leading to significant heat transfer enhancements (HTE). Heat transfer data reveals that the HTE impact increases and decreases with perforation-row number and Reynolds number (Re) respectively. With the sectional vortical flows tripped by the 60° grater-baffles, both Nu and f are raised from those with the 90° baffles. The Nusselt numbers and friction factors for the two-pass channel enhanced by the inclined 60° baffles with two perforation rows are elevated to 4.64–4.95and 33.67–34.16 times Dittus-Boelter correlation and Blasius equation levels, giving rise to the API in the range of 1.67 and 1.43 at Re between 5000 and 15,000. Empirical correlations of regional average Nu and channel average f for the four two-pass baffled channels are devised to assist engineering applications.

Experimental investigation on magneto-convective flows around two differentially heated horizontal cylinders

Liquid metal buoyant flow around two differentially heated horizontal cylinders in the presence of a uniform vertical magnetic field is investigated experimentally. While magneto-convection in pipes or ducts has been studied theoretically and experimentally in recent years, data for heat transfer at immersed obstacles are rare and, to our knowledge, detailed experimental investigations on this fundamental magnetohydrodynamic problem do not exist. In the present work, two horizontal cylinders inserted into an adiabatic rectangular cavity filled with gallium–indium–tin are kept at constant temperatures to establish a driving temperature gradient in the surrounding liquid metal. The buoyancy-driven flow, quantified by the Grashof number $Gr$ , is varied in the range ${10^{6} \leq Gr \leq ~5\times 10^{7}}$ . With increasing magnetic field, expressed via the Hartmann number $Ha$ , different flow regimes are identified from measurements for $0 \leq Ha \leq ~3000$ . The effect of the electromagnetic force primarily consists in suppressing turbulence and damping the convective flow. The heat transfer is quantified in terms of the non-dimensional Nusselt number $Nu$ , and its dependence on $Gr/{Ha}^{2}$ , which is identified as the important group governing the flow, is discussed.

Study on the flow and heat transfer characteristics inside high-porosity open-cell copper foams: Experimental and numerical explorations

A metal foam with an open-cell structure is a type of material with low flow resistance, high specific surface area, and strong fluid mixing ability. Open-cell metal foams have broad application prospects in electronic component cooling, multiphase heat exchangers, and compact heat exchangers for aerospace applications. This paper presented experimental and numerical analyses of the flow and heat transfer characteristics of five different copper foams under forced air convection. The pores per inch (PPI) of selected foams were 10, 20, 30, 40, and 60, with porosities ranging from 0.968 to 0.973. Analysis of the collected heat transfer and pressure drop data yielded the overall heat transfer coefficient, unit pressure drop, normalized average wall temperature, inertia coefficient, and resistance coefficient. The influence mechanisms of the porosity and flow velocity on heat transfer were analyzed and discussed. The numerical simulation and experiment fitted well. The results showed that increasing porosity led to a significant increase in heat transfer coefficient and unit pressure drop. The 60 PPI foam brought the maximum pressure drop while achieved the minimum thermal resistance.

Heat transfer evaluation of combined nanofluids in vertical annulus: An experimental and artificial neural network approach

Enhancing the thermal properties of the working fluid is a practical way to improve heat transfer performance. One of the suggested fluids for this purpose is nanofluids, which are suspensions of nanoparticles within a base fluid. Nanofluids have the potential to operate as a primary coolant or as an emergency coolant in a nuclear reactor. This paper investigates the thermal performance of a homogeneous hybrid nanofluid of Al2O3 and TiO2 in deionized water. The thermo-hydraulic performance of the nanofluid is analyzed in a high-pressure test loop capable of 25 bar pressure. The test section has an annular geometry, generating a cosine heat flux pattern. This flux pattern is representative of nuclear reactor cores. The experimental study is conducted to investigate the effects of nanoparticle concentration and Reynolds number on the heat transfer performance of nanofluids. The results show that increasing these two parameters significantly improved heat transfer. Specifically, raising the nanoparticle concentration from 0% to 1% leads to a reduction in surface temperature of 19% and 8% at Reynolds numbers of 825 and 4128, respectively. The calculated Nusselt numbers are compared with correlations from previous studies. Furthermore, an artificial neural network model is developed to predict heat transfer data for the studied system. The model consists of a single-layer feed-forward neural network trained with the stochastic gradient descent algorithm. To determine the optimal network, the number of neurons is optimized and evaluated based on the network's predictability. The neural network model demonstrates substantial improvements over previous experimental correlations (MAPE <2.5% and MSE <0.001).

Bayesian parameter estimation and evaluation of the K-ω shear stress transport model for plane impinging jets

Numerical simulations with semi-empirical turbulence models are commonly used to model impinging jets, often used for cooling solid surfaces. In this work, the constants in the k-ω shear stress transport model in ANSYS FLUENT are calibrated to experimental velocity and heat transfer data for a plane turbulent impinging air jet to determine if Kennedy-O’Hagan calibration (Kennedy and O’Hagan 2001 J. R. Stat. Soc. B 63 425–64) can improve predictions of near-surface velocities and surface Nusselt numbers for similar flows. Impinging jets have been proposed to cool the target plates of the divertor in future magnetic fusion energy reactors, where simulations are used to estimate divertor performance. The flat-plate divertor (Wang et al 2009 Fusion Sci. Technol. 56 1023–7) uses a plane jet of helium issuing from a B = 0.5 mm slot to cool a surface with radius of curvature of 44B at a distance 4B from the slot. Predictions from the calibrated numerical model are compared with independent experimental data at different flow conditions, as well as surface temperature data for a flat plate divertor test section. The contribution of this work is evaluation of the accuracy of a calibrated turbulence model for modest extrapolations in flow geometry and flow conditions for a plane impinging jet.

Study on the flow and heat transfer characteristics of hitec salt in solar vacuum collector tube

ABSTRACT With the continuous development of parabolic trough collectors technology, molten salt has gradually become a popular heat transfer fluid used in solar vacuum collector tubes. An experimental platform with Hitec salt (7% NaNO3, 53% KNO3, and 40% NaNO2) circulation loop was established to study the convective heat transfer characteristics of the molten salt side in the solar vacuum collector tube, and the convective heat transfer experiments were carried out under different irradiation intensities. The results show that increased irradiation intensity can effectively enhance the convection heat transfer. The experimental data under 0W/m2 have a significant deviation from the Nusselt number junction calculated by the classical heat transfer equations, and the deviation ranges from −7.9% to + 15.2%. The heat transfer equations under 0W/m2 and 850W/m2 were fitted, and the deviations between the experimental data and the calculated results of the fitted equations were −8% to + 8% and −9.9% to + 9.5%, respectively. A high-precision fitting strategy based on a neural network algorithm was introduced, the maximum deviation was −3.18% to + 3.35% and −3.9% to + 3.8%, which shows better fitting effect. This study can provide fundamental heat transfer data for the flow heat transfer of ternary molten salt in solar vacuum collector tubes, and provide theoretical guidance for the distribution of heat collection field in trough solar photovoltaic power station.

A Fully 3D-Printed Flexible Polymeric Heat Pipe

Abstract A fully 3D-printed polymeric heat pipe with high flexibility and low cost was demonstrated in this study. This wickless gravity-assisted heat pipe was fabricated using a commercial stereolithography 3D printer. The interconnected pocket array was designed to reduce the wall thickness to ∼0.1mm. The post-cured heat pipe can be flexed and twisted without tearing or permanent deformation. Experimental studies were conducted to characterize the performance of the heat pipe in vertical and 90° flexed configurations. In addition, visualization based on a high-speed camera was applied to study the boiling process inside the heat pipe. By charging with a compatible dielectric fluid HFE-7100, the present heat pipe achieved 18.6 W heat dissipation over a hot spot with an area of 25×25 mm2. The result showed an effective thermal conductivity of up to 102.7 W/(m·K) when placed vertically. The bubble dynamics and heat transfer data suggested little difference in performance between the vertical and flexed configuration after the startup of the heat pipe at 5.4 W, owing to a high charging mass. Last, a comparison of the present study and other reported fully polymeric flexible heat pipes was made, and future optimization of the heat pipe performance was discussed.

The effect of high values of relative surface roughness on heat transfer and pressure drop characteristics in the laminar, transitional, quasi-turbulent and turbulent flow regimes

This study investigated the effect of large values of relative surface roughness on the heat transfer and pressure drop characteristics using simultaneously measured heat transfer and pressure drop data. Experiments were conducted using a horizontal circular tube with a base inner diameter of 5 mm and length of 4 m. One smooth and two rough tubes, with relative roughnesses of 0.04 and 0.11, were tested at different constant heat fluxes between Reynolds numbers of 100 and 8 500. Water was used as the test fluid and the Prandtl number varied between 3 and 7. Contrary to the trend in the Moody Chart, a significant increase in laminar friction factors with increasing surface roughness was observed. Both the friction factors and Nusselt numbers as functions of Reynolds number showed a clear upward and leftward shift with increasing surface roughness across the different flow regimes. Furthermore, the boundaries between the flow regimes were the same for the pressure drop and heat transfer results. The width of the transitional flow regime was narrower for rough tubes and had a differing trend. The quasi-turbulent and turbulent flow regimes occurred at lower Reynolds numbers for increasing roughness. When investigating the relationship between heat transfer and pressure drop, it was found that an increase in surface roughness favoured heat transfer in the quasi-turbulent flow regime. This is useful for rough tubes as the quasi-turbulent flow regime onsets early with regards to the Reynolds number in tubes with large roughnesses.

Machine learning-assisted effective thermal management of rotor-stator systems

Rotor-stator systems are widely used to facilitate highly effective energy management and process intensification but have complex design characteristics, such as skittish flow and heat transfer. Due to the difficulty in obtaining heat transfer data for thermal management of rotor-stator systems, uneconomical designs with large margins often occur. Here, we propose a comprehensive design process using machine learning guided by convective heat transfer experimental data. We organize domain knowledge involving advection and convective heat transfer using a test rig employing a naphthalene sublimation method on large surfaces. Detailed heat transfer data elucidates that local thermal-fluid characteristics are non-linear as the operating conditions change, which is supported by numerical simulation models. We develop a machine learning-based heat transfer prediction model using pure experimental data and derive the optimal algorithm model. Thermal analysis via 2D thermal circuits provides an effective design process and enables rapid quantified evaluation of critical performance considerations. An improved rotor-stator system simultaneously achieves high heat flux of 1.9 kW/m2 and low thermal resistance of 17.1 K/W to both disks. We expect our experiment-based machine learning-assisted thermal management will serve as a robust and informative indicator for improving the efficiency and feasibility of applications with multivariate thermal-fluid systems.

Application of the fast 3D simplified simulation method for the large CAP1400 nuclear island evaporator based on the coupled source term method

As for the evaporator of the large CAP1400 nuclear power plant, it has a large volume with numerous tubes along with the complex flow heat transfer phenomenon. The traditional direct simulation method usually takes a lot of time and computing resources to obtain the flow heat transfer data. To solve the problem, a fast simulation method established on the porous medium source term was herein proposed. In this simplified simulation method, the complex evaporator model is replaced with the porous medium model, where the derived heat and momentum source terms are added into the governing equation to control the heat flows. Five kinds of simplified evaporator models with different numbers of pipes were set to be the research objects, the internal flows inside the evaporator were studied with the traditional direct simulation method and the newly proposed simplified simulation method. Via comparative analysis, it can be found that: 1) The newly proposed simplified simulation method accurately captures the distribution characteristics of pressure, temperature, and entropy production in the evaporator, serving as a viable alternative to traditional direct simulation methods. Specifically, the average simulation errors for inlet-outlet pressure difference and temperature difference are both less than 5 % and 7 %, respectively. 2) The newly proposed simplified simulation method can capture the mutual interference effects between the evaporator and the nuclear main pump. When the evaporator is connected in series with the main nuclear pump, the average head of the main pump increases by 0.34 m, while the efficiency decreases by an average of 0.34 %. The average simulation errors of the simplified simulation method are 0.06 m and 0.13 %, respectively. 3) The application of the simplified simulation method leads to a significant 85 % decrease in the average computational cost for evaporator calculations and a notable 36 % decrease for combined calculations of the evaporator and main pump. The study here is expected to provide technique support for the simulation and evaluation of the large nuclear island.

Experimental and numerical investigation of jet impingement cooling onto a rib roughened concave internal passage for leading edge cooling of a gas turbine blade

Considered is thermal protection of the concave surface within an internal passage, which models the leading edge cavity of vanes or blades of stationary or aero engine gas turbines. Included along the internal surface are different arrangements of V-shaped ribs to further augment surface cooling heat transfer rates. Impingement jets are employed for the cooling, which are configured so that associated cooling air exits the cavity through a crossflow outlet and an array of staggered film cooling holes. The curved part of the asymmetric, concave target plate features a constant radius and connects to straight lines on the pressure and suction sides. Addressed are H/Djet values of 2.7 and 4.0, and Reynolds number Re values of 18,000, 24,000, and 30,000. A maximum crossflow configuration is utilized wherein the coolant flow exits the cooling passage through the film cooling holes and from one end of the passage, as the opposite end is blocked. Different surface configurations are investigated, including 4 V-ribs in four different positions, 8 V-ribs in one position, and a smooth surface of the leading edge cavity. Each V-rib geometry consists of a regular V-rib pointing upstream. A transient thermochromic liquid crystal (TLC) technique is employed to obtain spatially-resolved surface heat transfer data on the internal wall of the leading edge cavity. Resulting experimental heat transfer data are used to validate and verify CFD simulations. Employed for this purpose are steady-state 3D RANS simulations obtained using the OpenFOAM Version 7 numerical code with a kω-shear-stress-transport (SST) turbulence model. Experimentally-measured surface Nusselt number results indicate significant local enhancements adjacent to rib wakes, provided local crossflow velocity values are substantial. Local surface Nusselt number enhancements thus depend upon rib position, but local surface heat transfer increases are most strongly tied to magnitudes of local crossflow velocity. In contrast to these experimental results, CFD simulation results do not show significant variations as rib position is altered. The best thermal performance is associated with 4 V-rib arrangements in two positions, and 8 V-ribs in one position.

Multimodal machine learning for predicting heat transfer characteristics in micro-pin fin heat sinks

As three-dimensional integrated circuit (3D-IC) chip technology advances, thermal management has become increasingly important because of increasing heat flux from thermal stacking. Micro-pin fin-embedded cooling has emerged as a promising solution for 3D-ICs, offering better thermal and hydraulic performance than conventional microchannel heat sinks. It is also easy to integrate into existing 3D-IC structures, such as through-silicon vias between stacks. The utilization of two-phase flow in micro-pin fins further enhances temperature uniformity and improves the heat transfer coefficient by leveraging latent heat. Nevertheless, predicting thermal performance in micro-pin fin heat sinks under boiling conditions remains challenging owing to intricate geometric shapes and diverse operating conditions. The present lack of correlation or theoretical models poses a significant obstacle. To address this problem, our study employed a Multimodal machine-learning (ML) approach, combining image data capturing boiling patterns of two-phase flow and information about geometric shape and operating conditions, to predict heat transfer characteristics in micro-pin fin heat sinks. We utilized experimental data comprising 155 types of boiling heat transfer data with the dielectric fluid FC-72 in two micro-fin shapes directly etched on Si. Four ML algorithms (XGBoost, LightGBM, Multilayer perceptron (MLP), and Multimodal ML) were employed to predict thermal performance. The correlation coefficient analysis before learning revealed the influence of each type of measurement data on the heater surface temperature during two-phase flow. Prediction accuracy was measured using mean absolute percent error (MAPE), and the results were compared in terms of maximum and average temperature depending on the characteristics of each ML algorithm. Overall, the Multimodal approach demonstrated superior capability in predicting temperature distributions with spatial details, surpassing conventional decision-tree algorithms and MLP in performance. When trained with boiling images, the Multimodal ML model achieved remarkable precision, evidenced by a MAPE of 1.81% for the maximum temperature and 0.84% for the average temperature, highlighting its exceptional accuracy in mapping the heated surface temperature profile. By contrast, the traditional MLP model, which lacked training on boiling images, showed diminished accuracy, with a MAPE of 2.54% for the maximum temperature and 1.77% for the average temperature, indicating a comparative shortfall against the Multimodal model results.

Data-driven diagnostics of boiling heat transfer on flat heaters from non-intrusive visualization

Rankine-based power generation cycles require the use of boiling heat exchangers for liquid–vapor phase change. However, operating boilers at too high heat fluxes can lead to heater meltdown due to onset of the boiling crisis. Despite recent advances in increasing this critical heat flux, the lack of fast and accurate diagnostics hinders boiling heat transfer safety at high heat fluxes. Here we show that neural networks fed on direct observation of bubble dynamics can be used to measure heat flux during nucleate boiling. The boiling heat transfer data was obtained with a horizontally oriented, circular flat heater with saturated water as the heat transfer fluid. A deep convolutional neural network (CNN) was trained using frames from videos acquired from 15 different heat dissipation values on the boiling curve to learn how these images correlate to the underlying heat flux. The CNN predicted heat fluxes with a mean square error of 14.6 W/cm2. Furthermore, the CNN presented high sensitivity to pixel intensity in image regions relevant to boiling heat transfer physics (e.g. bubble boundaries, contextual clues about bubble image distortion). Understanding this approach may allow future studies in unstable and critical boiling regimes that require fast transient heat flux diagnostics and cannot rely on slower thermohydraulic measurements.

Flow boiling heat transfer characteristics and correlation development of R290/R600a mixtures in an internally threaded tube

Excessive hydrofluorocarbons (HFCs) usage significantly contributes to the global warming. Therefore, there is a widespread shift toward natural refrigerants with low global warming potential (GWP). Among these alternative refrigerants, R290, R600a, and their mixtures have gained considerable attention. However, their flammability limits the charge. To decrease the equipment volume and reduce the refrigerant charge, internally threaded tubes have been introduced to enhance the heat transfer. Therefore, in this study, flow boiling experiments were conducted on R290, R600a, and mixtures inside an internally threaded tube, obtaining heat transfer data under a pressure of 0.216–0.416 MPa, heat flux of 10.5–73.0 kW m−2, mass flux of 70–190 kg m−2 s−1. To quantitatively discern the dominant heat transfer mechanism, a dimensionless number Nz was introduced. In the nucleate boiling dominant region, an increase in the heat flux markedly enhances the heat transfer, with pressure and mass flux playing minor roles. Furthermore, the heat transfer deterioration trend of the mixtures aligns with the variation trends of concentration slip and boiling range. In the convective heat transfer dominant region, a rise in the mass flux significantly increases the heat transfer coefficient, while the pressure and heat flux have minor effects. Additionally, at high R290 mole fraction and vapor quality, high surface tension maintains a continuous liquid film, enhancing the heat transfer. Furthermore, new heat transfer correlations for flow boiling inside the internally threaded tubes were established, which exhibit a mean relative deviation of −2.30 % and 8.80 % for the obtained experimental results and collected data, respectively.

Modelling the effect of roughness density on turbulent forced convection

By examining a systematic set of direct numerical simulations, we develop a model which captures the effect of roughness density on global and local heat transfer in forced convection. The surfaces considered are zero-skewed three-dimensional sinusoidal rough walls with solidities, $\varLambda$ (defined as the frontal area divided by the total plan area), ranging from low $\varLambda = 0.09$ , medium $\varLambda = 0.18$ to high $\varLambda = 0.36$ . For each solidity, we vary the roughness height characterised by the roughness Reynolds number, $k^+$ , from transitionally rough to fully rough conditions. The findings indicate that, as the fully rough regime is approached, there is a pronounced breakdown in the analogy between heat and momentum transfer, whereby the velocity roughness function $\Delta U^+$ continues to increase and the temperature roughness function $\Delta \varTheta ^+$ attains a peak with increasing $k^+$ . This breakdown occurs at higher sand-grain roughness Reynolds numbers ( $k_s^+$ ) with increasing solidity. Locally, we find that the heat transfer can be meaningfully partitioned into two categories: exposed, high-shear regions experiencing higher heat transfer obeying a local Reynolds analogy and sheltered, reversed-flow regions experiencing lower and spatially uniform heat transfer. The relative contribution of these distinct mechanisms to the global heat transfer depends on the fraction of the total surface area covered by these regions, which ultimately depends on $\varLambda$ . These insights enable us to develop a model for the rough-wall heat-transfer coefficient, ${C_{h,k}(k^+, \varLambda, Pr)}$ , where $Pr$ is the molecular Prandtl number, that assumes different heat-transfer laws in exposed and sheltered regions. We show that the exposed–sheltered surface-area fractions can be modelled through simple ray tracing that is solely dependent on the surface topography and a prescribed sheltering angle. Model predictions compare well when applied to heat-transfer data of traverse ribs from the literature.

Experimental analysis of flow boiling heat transfer in multi-microchannel evaporators

This paper provides an experimental analysis of flow boiling heat transfer in four finned evaporators with different aspect ratio and heated length have been tested. R245fa was the refrigerant chosen as working fluid for its good thermal characteristics. The imposed heat flux at the footprint covered a range from 30 to 330 kW/m2, while the fluid mass fluxes within the channel varied in a range between 17 and 225 kg/m2 s. The hydraulic diameters of the investigated evaporators were 1.15 mm and 2.09 mm, with aspect ratio (channel width/channel height) respectively of 0.3 and 0.72. Thanks to the measuring apparatus, heat transfer data were collected and then processed to calculate the local heat transfer coefficients, using the fin array heat transfer model. These local values of the heat transfer coefficient were then compared with those calculated from existing correlations for mini-micro channels flow boiling and the Mean Absolute Percent Error was finally assessed.

TURBULENCE MODELING OF SHOCK BOUNDARY LAYER INTERACTION IN HYPERSONIC FLOW

Computational fluid dynamics (CFD) simulations of shockwave turbulent boundary layer interactions using different turbulence modeling including Reynolds-averaged Navier-Stokes (RANS) with different closures (Menter's &lt;i&gt;k&lt;/i&gt;-&amp;omega;-SST, and Spalart-Allmaras) have been investigated. The objective of the study is to assess the capability of current CFD codes, Ansys Fluent and STARCCM, to model hypersonic flow over a large hollow cylinder flare for Mach 6 with Re&lt;sub&gt;&amp;#8734;&lt;/sub&gt; &amp;#61; 5.33 &amp;times; 10&lt;sup&gt;7&lt;/sup&gt; The results of heat transfer and pressure data over the surface are presented for two-dimensional, axisymmetric, and three-dimensional RANS models using experimental data of LENS II high Reynolds number shock/Ludweig tunnel at the CUBRC center. Effects of properties of real gas, perfect gas, and different types of mesh have been considered for the assessment.

Experimental data for flow boiling of R450A in a horizontal tube

According to the new European policies aimed at the replacement of highly-pollutant greenhouse gases refrigerants, the scientific community has focused on new synthetic environmentally friendly substances to be employed in vapor compression cycles for the refrigeration and the air conditioning fields.On this regard, R450A is a new blend made up of R134a (42%) and R1234ze (58%), having a GWP equal to 604, and therefore represents an attractive solution as pure R134a substitute. In this paper, new flow boiling heat transfer and pressure drop data of R450A collected at the refrigeration lab of Federico II University of Naples are presented. The data refer to a horizontal stainless-steel tube having an internal diameter of 6.0 mm. The effects of mass flux (from 150 to 400 kg m−2s−1), heat flux (from 10 to 20 kW m−2) and saturation temperature (from 30 to 50 °C) are presented and discussed, together with the assessment of the most quoted two-phase heat transfer and pressure drop prediction methods.

Heat and Mass Limitations in an Anaerobic Digestion Process

In this study, heat and mass limitations in an anaerobic reactor containing domestic solids were researched in batch reactors. The dynamic and static anaerobic data for 365 days showed that the methane production for the dynamic digestion reactor was measured as 176.86 m3 which is extremely high for static anaerobic one (102.78 m3). As the heat transfer data increased with elevated temperature the methane productions also were highlighted. The external mass transfer was observed for easily degradable solids. In the calculation of external mass transfer during the degradation of organics dissolved with difficulty some semiempirical regressions were used. In the calculation of internal mass transfer the microorganisms in the solids were taken into consideration and the diffusion was defined with Fick's law. The diffusion coefficient D, was found to be constant. Generally, the diffusion coefficient of solids in water (Dw) was &lt; 1.0. The effect of the total solid (TS) concentration in anaerobic batch reactors (TS between 12% and 39%) was investigated. The methane gas production decreased minorly when the TS levels elevated to 30%. At a TS percentage of 39%, the methane generation decreased significantly. At high TS, the mass transfer was inhibited and ended with lowered methane generations while the hydrolysis process did not affect significantly at high TS concentrations.