Using Kriging surrogate model to analyze hydrogen generation with dimethyl ether in partial oxidation catalytic fluidized bed reactor

Wu, Chia Ching; Wang, Bo-Wei; Wu, Tung-Han; Chang, Shih-Peng

doi:10.1016/j.ijhydene.2023.01.322

Cited by 4 publications

(2 citation statements)

References 77 publications

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“…[ 41 ] At 298 K, hydrogen has a higher heating value of 141.8 MJ kg −1 and a lower heating value (LHV) of 120 MJ kg −1 . [ 42 ] Its value exceeds that of the majority of fuels, such as gasoline, which has a value of 44 MJ kg −1 at 298 K. However, liquid hydrogen has a density of 8 MJ L −1 as opposed to 32 MJ L −1 , which is a factor of four less energy per volume than hydrocarbon fuels like gasoline. Compared to hydrocarbons, hydrogen gas has a lower energy density by volume but a higher energy density by weight; hence it needs a larger storage tank.…”

Section: General Overview Of Hydrogenmentioning

confidence: 99%

Recent Advances and Challenges of Hydrogen Production Technologies via Renewable Energy Sources

Worku,

Ayele,

Deepak

et al. 2024

Adv Energy and Sustain Res

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Currently, fossil fuels play a major role in meeting the world's energy demand. Fossil fuels, in contrast, threaten the planet's ecosystems and biological processes, contribute to global warming, and result in unfavorable climatic shifts. These energy sources are also finite and will eventually deplete. Thus, energy transition, which is the key from fossil fuels to renewable energy sources, is regarded as an essential course of action for decarbonizing the global economy and reducing the catastrophic and irreversible effects of climate change. Thereby using/consuming green hydrogen energy is a vital solution to meet the world's challenges. Subsequently, the pros and cons of several hydrogen generation methods, such as the conversion of fossil fuels, biomass, water electrolysis, microbial fermentation, and photocatalysis, are then compared and outlined in terms of their technologies, economies, consumption of energy, environmental aspects, and costs. Currently, the chemical industry uses green hydrogen (H2) primarily to produce green emerging fuels methanol and ammonia (NH3), which are regarded as alternate sources of energy. Finally, the current state of energy demands, recent developments in renewable energy sources, and the potential of hydrogen as a future fuel are outlined. Moreover, the discussion concludes with predicted opportunities and challenges.

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Section: General Overview Of Hydrogenmentioning

confidence: 99%

Recent Advances and Challenges of Hydrogen Production Technologies via Renewable Energy Sources

Worku,

Ayele,

Deepak

et al. 2024

Adv Energy and Sustain Res

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“…Therefore, this method is called surrogate-based optimization (SBO). Common surrogate models include the response surface method (RSM) [36], support vector regression (SVR) [37], radial basis function (RBF) [38], and Kriging model (KM) [39]. In these surrogate models, KM takes values from regionalized variables in finite regions and makes optimal and unbiased estimates from the perspective of the correlation and variability of variables.…”

Section: Introductionmentioning

confidence: 99%

Prediction and Optimization of Heat Transfer Performance of Premixed Methane Impinging Flame Jet Using the Kriging Model and Genetic Algorithm

Chen,

2024

Applied Sciences

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In practical applications, rapid prediction and optimization of heat transfer performance are essential for premixed methane impinging flame jets (PMIFJs). This study uses computational fluid dynamics (CFD) combined with a methane detailed chemical reaction mechanism (GRI–Mech 3.0) to study the equivalence ratio (Φ), Reynolds number (Re) of the mixture, and the normalized nozzle–to–plate distance (H/d) on the heat transfer performance of PMIFJs. Moreover, the Kriging model (KM) was used to construct a prediction model of PMIFJ heat transfer performance. A genetic algorithm (GA) was used to determine the maximum likelihood function (MLE) of the model parameters for constructing KM and identify the points with the maximum root mean square error (RMSE) as the new infilled points for surrogate–based optimization (SBO). Combining these methods to analyze the simulation results, the results show that the global heat transfer performance of PMIFJs is enhanced with the increase in Φ, the increase in Re, and the decrease in H/d. Sensitivity analysis points out that Re and Φ significantly affect enhanced heat transfer, while H/d has a relatively small effect. In addition, GA was also used to search for the optimal heat transfer performance, and the global heat transfer performance at specific conditions was significantly enhanced. This study deepens the understanding of the heat transfer mechanism of impinging flame jets and provides an efficient method framework for practical applications.

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Breaking barriers: Novel approaches to proton-conducting oxide materials

Tayyab,

Rauf,

Khan

et al. 2024

Ceramics International

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Using Kriging surrogate model to analyze hydrogen generation with dimethyl ether in partial oxidation catalytic fluidized bed reactor

Cited by 4 publications

References 77 publications

Recent Advances and Challenges of Hydrogen Production Technologies via Renewable Energy Sources

Recent Advances and Challenges of Hydrogen Production Technologies via Renewable Energy Sources

Prediction and Optimization of Heat Transfer Performance of Premixed Methane Impinging Flame Jet Using the Kriging Model and Genetic Algorithm

Breaking barriers: Novel approaches to proton-conducting oxide materials

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