Airflow Simulation Inside Reefer Containers

Conference paper
Part of the Lecture Notes in Logistics book series (LNLO)

Abstract

Transporting of sensitive commodities in strict ambient conditions becomes necessity not only to fulfill regulations but also to maintain their quality and to reduce the rate of losses. Temperature, which mainly affects the transported produce, is controlled by airflow pattern in reefer containers. Consequently, obtaining airflow pattern enables predicting hot spots and then taking the necessary actions to minimize their effects. We present, in this paper, a k-ε simulation model to evaluate airflow pattern in reefer container loaded with bananas. Simulation results predict the place of the hot spots. Moreover, we found that the cooling distribution is improved by modification of the scheme for placing pallets in the container, the so-called chimney layout.

Keywords

Characterization Airflow k-ε simulation Banana transport Reefer container 

Notes

Acknowledgments

The research project “The Intelligent Container” is supported by the Federal Ministry of Education and Research, Germany, under the reference number 01IA10001.

References

  1. Jedermann R, Geyer M, Praeger U, Lang W (2013) Sea transport of bananas in containers—parameter identification for a temperature model. J Food Eng 115(3):330–338CrossRefGoogle Scholar
  2. Lloyd C, Issa S, Lang W, Jedermann R (2013) Empirical airflow pattern determination of refrigerated banana containers using thermal flow sensors. The intelligent container, cool-chain-management. 5th international workshop, University of BonnGoogle Scholar
  3. Moureh J, Tapsoba S, Derens E, Flick D (2009) Air velocity characteristics within vented pallets loaded in a refrigerated vehicle with and without air ducts. Int J Refrig 32:220–234CrossRefGoogle Scholar
  4. Nieuwstadt FTM, Eggels JGM, Janssen RJA, Pourquié MBJM (1994) Direct and Large–Eddy simulations of turbulence in fluids. Future Gener Comput Syst 10(2–3):189–205CrossRefGoogle Scholar
  5. Paull R (1999) Effect of temperature and relative humidity on fresh commodity quality. Postharvest Biol Technol 15(3):263–277CrossRefGoogle Scholar
  6. Smale NJ, Moureh J, Cortella G (2006) A review of numerical models of airflow in refrigerated food applications. Int J Refrig 29(6):911–930CrossRefGoogle Scholar
  7. Xie J, Qu XH, Shi JY, Sun DW (2006) Effects of design parameters on flow and temperature fields of a cold store by CFD simulation. J Food Eng 77(2):355–363CrossRefGoogle Scholar
  8. Zhai ZJ, Zhang Z, Zhang W, Chen QY (2007) Evaluation of various turbulence models in predicting airflow and turbulence in enclosed environments by CFD: part 1—summary of prevalent turbulence models. HVAC&R Res 13(6):853–870CrossRefGoogle Scholar
  9. Zou Q, Opara LU, McKibbin R (2005) A CFD modeling system for airflow and heat transfer in ventilated packaging for fresh foods. J Food Eng 77:1048–1058CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Institute for Microsensors, Actuators and Systems (IMSAS), Microsystems Center Bremen (MCB)University of BremenBremenGermany
  2. 2.International Graduate School for Dynamics in Logistics (IGS)University of BremenBremenGermany

Personalised recommendations