Determination of food particle residence time distributions in coiled tube and straight tube with bends at high temperature using correlation analysis

Chakrabandhu, Krittalak; Singh, Rakesh K.

doi:10.1016/j.jfoodeng.2005.04.047

Cited by 6 publications

(6 citation statements)

References 14 publications

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“…The internal volume and shape of the injection and detection systems can distort the tracer signal, compromising the RTD results (Mills and Dudukovic, 1989). When it is not possible to produce an instantaneous pulse signal at the entrance of the process, a supplementary detection system has to be placed at the entrance of the process to record the input signal (Chakrabandhu and Singh, 2006;Fillaudeau et al, 2009). Fig.…”

Section: Pfr + Cstr Associationmentioning

confidence: 99%

Residence time distribution in holding tubes using generalized convection model and numerical convolution for non-ideal tracer detection

Gutierrez

Dias

Gut

2010

Journal of Food Engineering

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a b s t r a c tA procedure is proposed for the determination of the residence time distribution (RTD) of curved tubes taking into account the non-ideal detection of the tracer. The procedure was applied to two holding tubes used for milk pasteurization in laboratory scale. Experimental data was obtained using an ionic tracer. The signal distortion caused by the detection system was considerable because of the short residence time. Four RTD models, namely axial dispersion, extended tanks in series, generalized convection and PFR + CSTR association, were adjusted after convolution with the E-curve of the detection system. The generalized convection model provided the best fit because it could better represent the tail on the tracer concentration curve that is caused by the laminar velocity profile and the recirculation regions. Adjusted model parameters were well correlated with the flow rate.

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Section: Pfr + Cstr Associationmentioning

confidence: 99%

Residence time distribution in holding tubes using generalized convection model and numerical convolution for non-ideal tracer detection

Gutierrez

Dias

Gut

2010

Journal of Food Engineering

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“…These velocity magnitudes would not occur in reality. As determined from the experimental study in [15], the maximum food particle velocity was around 1.8-times the mean product velocity in the holding tubes. Moreover, we assumed that the particle radial position remained the same during the process and also after passing the bends, whereas during the experiment, this may change along the tube.…”

Section: Resultsmentioning

confidence: 86%

“…u rel is the relative velocity between the particle velocity u p and the fluid velocity u f , which is the slip velocity that controls the interfacial heat transfer between fluid and particle. u p is calculated depending on the given particle normalized residence time NRT, which is defined as follows [15]:…”

Section: Heat Transfer Coefficientmentioning

confidence: 99%

“…NRT is defined as the ratio of the particle residence time t p to the mean product residence time t av [15].…”

Section: Heat Transfer Coefficientmentioning

confidence: 99%

“…These values can be determined experimentally, as there is no correlation available for predicting the residence time as a function of process variables. The NRTs in the tubular pipe from several experimental studies were presented in [1,15], where their values varied widely among different studies, depending on the experimental setup and product characteristics. It is also worthwhile to mention that the particle radial position depends on the NRTs.…”

Section: Heat Transfer Coefficientmentioning

confidence: 99%

See 2 more Smart Citations

Lethality Calculation of Particulate Liquid Foods during Aseptic Processing

et al. 2019

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In the past two decades, aseptic processing has been implemented in the food industry to sterilize particulate liquid food mixtures. To ensure that particulates in the liquid receive sufficient heating, mathematical modeling is employed to evaluate the temperature and lethality level in the particles. We developed a model for the thermal processing of liquid foods containing cubic particles in a continuous laminar pipe flow system, comprising a tubular heat exchanger. In our simplified approach, heat transfer equations for particulate liquid foods were solved analytically and numerically to evaluate the effect of certain process parameters on the time temperature profiles of particles and the lethality value in the products. A comparison of the particles’ lethality values was made between the experiment and simulation for two different particle residence times in a case study, and the model predictions were in good agreement with experimental data. Based on modeling studies, it was found that within the range of parameters studied, an increase in flow rate and particle size resulted in a decrease in the lethality value of the particles, while an increase in particle concentration and holding tube length resulted in the opposite effect.

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Investigation of the residence time distribution in a plate heat exchanger with series and parallel arrangements using a non-ideal tracer detection technique

Gutierrez

Dias

Gut

2011

Applied Thermal Engineering

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Determination of food particle residence time distributions in coiled tube and straight tube with bends at high temperature using correlation analysis

Cited by 6 publications

References 14 publications

Residence time distribution in holding tubes using generalized convection model and numerical convolution for non-ideal tracer detection

Residence time distribution in holding tubes using generalized convection model and numerical convolution for non-ideal tracer detection

Lethality Calculation of Particulate Liquid Foods during Aseptic Processing

Investigation of the residence time distribution in a plate heat exchanger with series and parallel arrangements using a non-ideal tracer detection technique

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