Mathematical Modelling and Sensitivity-Based Optimization of Energy-Efficient Cassava Drying in Ghana

Pneumatic flash drying of cassava mash is a critical, energy-intensive unit operation among small- and medium-scale agro-processors in Ghana. While operational adjustments such as feed-rate tuning have demonstrated significant energy reductions in empirical trials, the stability of optimized operating points under shifting inlet conditions remains poorly quantified. This paper presents a thermodynamic and psychrometric mass-and-energy balance model tailored to small-scale Ghanaian pneumatic flash dryers. Benchmarked against commercial field trials (where feed-rate tuning increased dried-product output from 42.2 ± 7.3 to 65.0 ± 5.5 kg/h and reduced specific energy consumption from 4,388 ± 716 to 3,509 ± 527 kJ/kg water), the model investigates system sensitivity across fluctuating raw cassava moisture (0.40 ≤ Xi ≤ 0.60 kg/kg db) and feed rates (40 ≤ Fw ≤ 110 kg/h). The sensitivity analysis demonstrates that the reported optimal feed rate of 98.6 kg/h is strictly constrained by an exhaust air relative humidity threshold (RHout ≤ 55.3%) to prevent in-duct condensation and product caking. An increase in initial cassava moisture of 0.05 kg/kg shifts the minimum achievable specific energy consumption point downward in throughput by approximately 8.4 kg/h. A generalized operational decision matrix is proposed to enable local operators to dynamically adjust dryer settings to seasonal moisture variations.

Cassava drying; Pneumatic flash dryer; Mathematical modelling; Specific energy consumption; Process optimization; Ghana agro-industry; Sensitivity analysis

1. Chapuis, A., Lancement, C., Giraldo, F., Precoppe, M., Moreno, M. A., Dufour, D., & Tran, T. (2022). Extensive experimental validation of a model for pneumatic drying of cassava starch. Drying Technology, 40(14), 2963–2977. https://doi.org/10.1080/07373937.2022.2087668 [Google Scholar] [Crossref]

2. Chapuis, A., Precoppe, M., Kouame, C. A., Meziani, S., & Tran, T. (2017). Pneumatic drying of cassava starch: Numerical analysis and guidelines for the design of efficient small-scale dryers. Drying Technology, 35(4), 393–408. https://doi.org/10.1080/07373937.2016.1187714 [Google Scholar] [Crossref]

3. Kudra, T., & Mujumdar, A. S. (2009). Advanced drying technologies (2nd ed.). CRC Press. https://doi.org/10.1201/9781420073898 [Google Scholar] [Crossref]

4. Ojide, M., Adegbite, S. A., Lukombo, S., Sartas, M., Teeken, B., Kuate, A. F., Ndjouenkeu, R., Moreno, M., Belalcázar, J., Chapuis, A., & Tran, T. (2022). Processors’ experience in the use of flash dryer for cassava-derived products in Nigeria. Frontiers in Sustainable Food Systems, 6, Article 847285. https://doi.org/10.3389/fsufs.2022.847285 [Google Scholar] [Crossref]

5. Precoppe, M., Chapuis, A., Müller, J., & Abass, A. (2017). Tunnel dryer and pneumatic dryer performance evaluation to improve small-scale cassava processing in Tanzania. Journal of Food Process Engineering, 40(1), Article e12274. https://doi.org/10.1111/jfpe.12274 [Google Scholar] [Crossref]

6. Precoppe, M., & Komlaga, G. (2020). Improved energy performance of small-scale pneumatic dryers used for cassava processing (Technical Report). Natural Resources Institute, University of Greenwich, in partnership with CSIR-Food Research Institute, Ghana. [Google Scholar] [Crossref]

7. Precoppe, M., Komlaga, G. A., Chapuis, A., & Müller, J. (2020). Comparative study between current practices on cassava drying by small-size enterprises in Africa. Applied Sciences, 10(21), Article 7863. https://doi.org/10.3390/app10217863. [Google Scholar] [Crossref]

8. Suherman, S., Susanto, E. E., Zardani, A. W., Dewi, N. H. R., & Hadiyanto, H. (2020). Energy–exergy analysis and mathematical modeling of cassava starch drying using a hybrid solar dryer. Cogent Engineering, 7(1), Article 1771819. https://doi.org/10.1080/23311916.2020.1771819 [Google Scholar] [Crossref]

9. Tran, T., Abass, A., Taborda Andrade, L. A., Chapuis, A., Precoppe, M., Adinsi, L., Bouniol, A., Ojide, M., Adegbite, S. A., Lukombo, S., Sartas, M., Teeken, B., Kuate, A. F., Ndjouenkeu, R., Moreno, M., Belalcázar, J., López-Lavalle, L. A. B., & Dufour, D. (2022). Cost-effective cassava processing: Case study of small-scale flash-dryer reengineering. In G. Thiele, M. Friedmann, H. Campos, V. Polar, & J. W. Bentley (Eds.), Root, tuber and banana food system innovations: Value creation for inclusive outcomes (pp. 105–143). Springer, Cham. https://doi.org/10.1007/978-3-030-92022-7_4 [Google Scholar] [Crossref]

• Interplay of Students’ Emotional Intelligence and Attitude toward Mathematics on Performance in Grade 10 Algebra
• Numerical Simulation of Fitzhugh-Nagumo Dynamics Using a Finite Difference-Based Method of Lines
• Fixed Point Theorem in Controlled Metric Spaces
• Usage of Moving Average to Heart Rate, Blood Pressure and Blood Sugar
• Exploring Algebraic Topology and Homotopy Theory: Methods, Empirical Data, and Numerical Examples