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CFD analysis of a tube-in-tube heat exchanger to recover waste heat for food drying


Food waste is an alarming issue for the modern world. Drying is one of the oldest and easiest solutions for overcoming unnecessary food waste. However, most of the conventional drying consumes a significant amount of energy to remove water from food. On the other hand, there are many sources, which cause heat waste. Smart utilization of waste heat from sources including IC engine, turbine, brick kiln and something like those would be a great solution to the energy consumption problem of food drying. There is no systematic theoretical analysis of waste-heat-based food drying system available in the literature. In this study, a comprehensive transport model of drying system using engine’s exhaust waste heat has been simulated. Utilization of a small lab-scale IC engine exhaust results in reducing about 1137.15 kg of CO2 every year that would be produced from a conventional food dryer of the same capacity. In addition, low installation cost and payback period offer a promising rational solution of drying system. The proposed system is also capable of reducing entropy to an appreciable extent. Therefore, successful implementation of this proposed technique would offer a high-energy efficient, low-cost drying system along with ensuring a green environment.

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\(\omega\) :

Specific dissipation rate

\(k\) :

Turbulence kinetic energy

\(u_{j}\) :

Velocity term in differential equation for k and \(\omega\)

\(u_{i}\) :

Velocity term in differential equation for k and \(\omega\)

\(x_{i}\) :

Length scale term in differential equation for k and \(\omega\)

\(x_{j}\) :

Length scale term in differential equation for k and \(\omega\)

t :


\(\varGamma_{\omega }\) :

Effective diffusivity of \(\omega\)

\(\varGamma_{k}\) :

Effective diffusivity of k

\(G_{\omega }\) :

Production of dissipation rate

\(G_{k}\) :

Production of turbulence kinetic energy

\(\sigma_{k,1}\) :


\(\sigma_{k,2}\) :


\(\sigma_{\omega ,1}\) :


\(\sigma_{\omega ,2}\) :


\(\alpha_{\infty }^{*}\) :


\(Re_{k}\) :


\(\phi_{1}\) :

Blending function constant

\(\phi_{2}\) :

Blending function constant

\(\mu\) :


\(S\) :

Modulus of the mean rate-of-strain tensor

\(\kappa\) :


\(\beta_{i,1}\) :


\(\beta_{\infty }^{*}\) :


\(k_{\text{eff}}\) :

Effective conductivity

\(h_{j}\) :

Enthalpy term in energy equation of species j

\(q\) :

Operating temperature

\(k_{\text{s}}\) :

Heat transfer

\(\sigma_{k,2}\) :

Temperature of hot gas

\(\sigma_{k,2}\) :

Thermal conductivity of wall

Δn :

Number of wall contributing to heat transfer

\(Y_{\text{k}}\) :

Dissipation of k

\(Y_{\omega }\) :

Dissipation of ω

\(F_{1}\) :

Cross-diffusion term

\(F_{2}\) :

Blending function

\(\sigma_{k}\) :

Blending function

\(\sigma_{\omega }\) :

The turbulent Prandtl numbers for k

\(\sigma_{k,2}\) :

Turbulent Prandtl numbers for ω

\(\mu_{t}\) :

Turbulent viscosity

\(s\) :

Magnitude of strain rate

\(\sigma_{k,2}\) :


\(\sigma_{k,2}\) :


\(\sigma_{k,2}\) :

\(0.31\) (FLUENT 2017)

\(\sigma_{k,2}\) :

Coefficient of low Reynolds number correction produced by damped turbulent viscosity

\(\sigma_{k,2}\) :


\(\sigma_{k,2}\) :

A constant of the equation for representing the production of \(\omega\)

\(\sigma_{k,2}\) :


\(Re_{t}\) :

A function for low Reynolds correction equation defined as \(\frac{\rho k}{\mu \omega }\)

\(D_{\omega }^{ + }\) :

Positive portion of the cross-diffusion term

\(y\) :

Distance to the next surface

\(u^{\prime}\) :

Fluctuating velocity component

\(f_{{\beta^{*} }}\) :


\(\beta_{i,2}\) :


\(R_{\beta }\) :


E :


\(k_{t}\) :

Turbulent thermal conductivity

\(\overrightarrow {{J_{j} }}\) :

Diffusion flux of species j

g :

Gravitational acceleration

h f :

Convective heat transfer coefficient

T w :

Temperature of wall

T s :

Surface temperature of the pip


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The authors of this study worked independently and did not receive any donation or financial support. The sole purpose of this is to impart knowledge and improve the general understanding on prospect of a waste heat convective dryer. The authors hereby do not acknowledge any third party for any type of financial contribution. Authors have the indefinite rights to all data and materials used in this study.

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Masud, M.H., Islam, T., Joardder, M.U.H. et al. CFD analysis of a tube-in-tube heat exchanger to recover waste heat for food drying. Int J Energ Water Res 3, 169–186 (2019).

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  • Food dryer
  • Heat exchanger, ANSYS 15
  • Waste heat
  • Feasibility analysis