CFD analysis of a flat bottom institutional cookstove

Commeh, Michael Kweku; Agyei-Agyemang, Anthony; Tawiah, Peter Oppong; Asaaga, Benjamin Atribawuni

doi:10.1016/j.sciaf.2022.e01117

Cited by 6 publications

(2 citation statements)

References 24 publications

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“…To select the optimum model input variables, the following criteria were considered to adjudge a model as excellent (0.75<NSE1; PBias<10; KGE 0.75), good (0.65<NSE0.75; PBias<15; 0.5≤ KGE < 0.75) and satisfactory (0.5<NSE0.65; PBias<25; 0.0 ≤ KGE < 0.5) (Commeh et al, 2022;Thiemig et al, 2013).…”

Section: Model Evaluation Statisticsmentioning

confidence: 99%

Evaluation of soft-computing techniques for pan evaporation estimation

KUMAR,

SARANGI,

SINGH

et al. 2024

J. Agrometeorol.

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Estimation of pan evaporation (Epan) can be useful in judicious irrigation scheduling for enhancing agricultural water productivity. The aim of present study was to assess the efficacy of state-of-the-art LSTM and ANN for daily Epan estimation using meteorological data. Besides this, the effect of static time-series (Julian date) as additional input variable was investigated on performance of soft-computing techniques. For this purpose,the models were trained, tested and validated with eight meteorological variables of 37 years by using preceding 1-, 3- and 5- days’ information. Data were partitioned into three groups as training (60%), testing (20%), and validation (20%) components. It was observed that the models performed well (best) with preceding 5-days meteorological information followed by 3-days and 1-day. However, all LSTMs simulated peak value of Epan was more accurate as compared to lower values. Meteorological data with julian date improved the performance of LSTMs (0.75<NSE 1; PBias< 10; KGE 0.75). The ANN trained using only meteorological data (preceding 5-days information) had better performance error statistics among all other ANNs and LSTMs with minimum MAE (0.68 to 0.86), RMSE (0.93 to 1.22), PBias (-0.73 to 2.44) and maximum NSE (0.83 to 0.84) and KGE (0.89 to 0.92). Overall, it was inferred that the forecasting of meteorological parameters using a few days preceding information along with Julian date as the time series variables resulted in better estimation of Epan for the study region.

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Section: Model Evaluation Statisticsmentioning

confidence: 99%

Evaluation of soft-computing techniques for pan evaporation estimation

KUMAR,

SARANGI,

SINGH

et al. 2024

J. Agrometeorol.

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“…A computational model for the conceptual design of biomass cookstoves would enable a more accurate, faster, and more adaptive understanding of heat transfer and flow within the stove (Commeh et al, 2022). Experimental data sets with thermal performance characteristics in terms of design characteristics are required for model validation.…”

Section: Application Of Computational Fluid Dynamics For Combustion M...mentioning

confidence: 99%

Current challenges and future prospect of biomass cooking and heating stoves in Asian Countries

Ahmad

Ilyas

et al. 2022

Front. Energy Res.

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The utilization of biomass for cooking and heating is old, occurring from the early stages of human evolution because of its wide and easy availability. In Asia, a majority of the population is dependent on solid biomass for cooking and heating applications. Biomass cookstove produces emissions like carbon monoxide (CO), and particulate matter with aerodynamic diameter ≤2.5 μm (PM2.5) which are dependent on the classifications and characteristics of fuel used in stoves. These emissions trigger many health risks because of the utilization of traditional cookstoves (TCS) which have less thermal efficiency. The literature contains a considerable amount of information on biomass cookstoves; however, it is dispersed particularly in Asian countries. In this principle, this paper gives an overview of available literature on biomass cookstoves for cooking and heating in Asian countries which are involving Bangladesh, China, India, Mongolia, Nepal, Pakistan, Sri Lanka, and Laos. This paper covers a detailed discussion on various aspects of biomass cookstoves: history, classification, fuel characteristics, health risks, design criteria, the scenario in selected Asian countries, thermal efficiency and emission comparison, and barriers to dissemination of improved biomass cookstoves (ICS). Learning from the review and comparison made conclude that the ICS has better thermal efficiency, and lesser emissions, as well as health risks but, have some potential barriers to dissemination.

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