Study on ice-melting performance of gradient gas diffusion layer in proton exchange membrane fuel cell

In this study, a three-dimensional model was established using the lattice Boltzmann method (LBM) to study the internal ice melting process of the gas diffusion layer (GDL) of the proton exchange membrane fuel cell (PEMFC). The single-point second-order curved boundary condition was adopted. The effects of GDL carbon fiber number, growth slope of the number of carbon fibers and carbon fiber diameter on ice melting were studied. The results were revealed that the temperature in the middle and lower part of the gradient distribution GDL is significantly higher than that of the no-gradient GDL. With the increase of the growth slope of the number of carbon fiber, the temperature and melting rate gradually increase, and the position of the solid-liquid interface gradually decreases. The decrease in the number of carbon fibers has a similar effect as the increase in the growth slope of the number of carbon fibers. In addition, as the diameter of the carbon fiber increases, the position of the solid-liquid interface gradually decreases first and then increases.     

Effects of different metal corrosion inhibitors on hydrogen suppression and film formation with Mg–Zn alloy dust in NaCl solutions

To improve the safety of wet dust removal systems for processing magnesium-based alloys, a new method is proposed for preventing hydrogen generation. In this paper, hydrogen generation by Mg–Zn alloy dust was inhibited with six common metal corrosion inhibitors. The results showed that sodium dodecylbenzene sulfonate was the best hydrogen inhibitor, while CeCl₃ enhanced hydrogen precipitation. The film-forming stability of sodium dodecylbenzene sulfonate was tested with different contents, temperatures, Cl^? concentrations and perturbation rates. The results showed that this inhibitor formed stable protective films on the surfaces of Mg–Zn alloy particles, and adsorption followed the Langmuir adsorption model.     

Optimization of PEMFC system operating conditions based on neural network and PSO to achieve the best system performance

PEMFC system is a complex new clean power system. Based on MATLAB/Simulink, this paper develops a system-level dynamic model of PEMFC, including the gas supply system, hydrogen supply system, hydrothermal management system, and electric stack. The neural network fits the electric stack model to the simulation data. The effects of different operating conditions on the PEMFC stack power and system efficiency are analyzed. Combining the power of the reactor and the system efficiency to define the integrated performance index, the particle swarm optimization (PSO) algorithm is introduced to optimize the power density and system efficiency of the PEMFC with multiple objectives. The final optimal operating point increases the power density and system efficiency by 1.33% and 12.8%, respectively, which maximizes the output performance and reduces the parasitic power.     

Experimental and numerical study on tube-side flow and heat transfer characteristics of superheated vapor flow in catalyst-filled LH2 spiral wound heat exchanger

High energy consumption is considered to be one of the most persistent problems in liquid hydrogen (LH₂) plants. The combination of heat exchanger and ortho-para (O–P) hydrogen conversion has attracted considerable attention as a cutting-edge technology to reduce energy consumption. The flow and heat transfer characteristics of O–P hydrogen conversion catalyst-filled spiral wound heat exchanger (SWHE) were investigated in this study in two steps. In the first step, pressure-drop experiments were performed in a tube filled with porous media. The results indicated that the pressure drop was overestimated when using Ergun's equation. Therefore, a new empirical pressure-drop correlation for a channel filled with O–P catalyst was formulated. Subsequently, a novel heat transfer model was established based on this correlation for further numerical simulations. The distributions of the temperature, pressure, and para hydrogen content in a catalyst-filled tube were determined. In addition, the influence of the flow rate on the heat exchange coefficient and outlet para hydrogen was clarified; it was found that, with an increase in the flow rate, the heat exchange coefficient increased, whereas the outlet para hydrogen content decreased. At a flow rate of 0.5 m³/h, the para hydrogen content increased by 44% after hydrogen flowed through the channel filled with the O–P catalyst. Furthermore, a prediction model for the para hydrogen content with a flow rate range of 0–1.5 m³/h was derived. This study provides promising theoretical evidence for the engineering application of SWHEs filled with O–P catalysts in large-scale hydrogen liquefaction units.     

Influencer-defaulter mutation-based optimization algorithms for predicting electricity prices

Efficient electricity price forecasting plays a significant role in our society. In this paper, a novel influencer-defaulter mutation (IDM) mutation operator has been proposed. The IDM operator has been combined with six well-known optimization algorithms to create mutated optimization algorithms whose performance has been tested on twenty-four standard benchmark functions. Further, the artificial neural network is integrated with mutated optimization algorithms to solve the electricity price prediction problem. The policymakers can identify appropriate variables based on the predicted prices to help future market planning. The statistical results prove the efficacy of the IDM operator on the recent optimization algorithms.     

Icy affairs: Understanding recent advancements in the freezing and frozen storage of fish

Freezing methods have evolved over the last 30 years. This review states the effect of various freezing methods on the quality of fish and seafood. Freezing temperatures, freezing, and frozen storage temperatures were also analyzed and reviewed. The changes in the ice crystal, protein, and lipid affect the fish quality and nutritional value during freezing and frozen storage. Freezing methods when combined with various additives or preprocessing approaches help improve the efficacy of freezing and frozen storage. Several experimental or emerging methods also have positive effects on the products' quality. According to the metadata reanalysis of quality markers, freshly frozen fish using different freezing methods may vary much in terms of ice diameter, but not others. High pressure freezing or immersion freezing-derived fish retains the best quality through frozen storage. More data are required on freezing methods (electrical-assisted freezing, microwave-assisted freezing, magnetic-assisted freezing, radiofrequency-assisted freezing, and the commercial's application and investment should be considered in the future. This review sheds light on finding a balanced initial shear force during freezing and the use of certain additives to control freezing-related damages. Focusing on ice diameter alone may be futile (e.g., liquid N₂ freezing). Future optimization of technologies should be in a way that several processes along the farm to fork such as freezing, frozen storage, thawing, thermal processing of fish, and even refabrication of food should mutually complement each other's needs to deliver safe and high-quality fish to the consumer's plate, even after a prolonged shelf-life.     

Convolutional Neural Network Auto Encoder Channel Estimation Algorithm in MIMO-OFDM System

Higher transmission rate is one of the technological features of prominently used wireless communication namely Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO–OFDM). One among an effective solution for channel estimation in wireless communication system, specifically in different environments is Deep Learning (DL) method. This research greatly utilizes channel estimator on the basis of Convolutional Neural Network Auto Encoder (CNNAE) classifier for MIMO-OFDM systems. A CNNAE classifier is one among Deep Learning (DL) algorithm, in which video signal is fed as input by allotting significant learnable weights and biases in various aspects/objects for video signal and capable of differentiating from one another. Improved performances are achieved by using CNNAE based channel estimation, in which extension is done for channel selection as well as achieve enhanced performances numerically, when compared with conventional estimators in quite a lot of scenarios. Considering reduction in number of parameters involved and re-usability of weights, CNNAE based channel estimation is quite suitable and properly fits to the video signal. CNNAE classifier weights updation are done with minimized Signal to Noise Ratio (SNR), Bit Error Rate (BER) and Mean Square Error (MSE).     

Experimental evaluation of the luminescence performance of fired clay brick coated with SrAl2O4:Eu/Dy phosphor

This study evaluates the luminescence performance of fired clay bricks coated with SrAl₂O₄:Eu/Dy phosphor. To do so, SrAl₂O₄:Eu/Dy phosphor was first produced using the traditional solid-state reaction synthesis technique. The prepared phosphor was then used for coating fired clay bricks to analyze the luminescence performance via spectral analysis, decay characteristics, and microstructure of the bricks. The results reveal that excitation and emission spectra of the phosphor coated bricks range from 200 to 480 nm and 455 to 650 nm, respectively, suggesting that the phosphor coated bricks have the capacity of absorbing light with a wide range of wavelengths. The peak wavelength projected at 511 nm in the emission spectrum is achieved, which indicates 4f⁶5 d¹-4f⁷ transition of Europium (Eu²⁺). The repeated excitation and deexcitation of Eu²⁺ by using hole traps and trap levels offered by Dysprosium (Dy³⁺), exist between the ground and the excited state of Eu²⁺ leads to luminescent phenomenon. Moreover, the decay characteristics has revealed that phosphor coated bricks can emit light for a considerable amount of time (>8.5 min) upon the removal of the excitation source. The results reveal that phosphor coated bricks has the potential of increasing energy efficiency of residential and commercial buildings.     

Total Site Hydrogen Integration with fresh hydrogen of multiple quality and waste hydrogen recovery in refineries

This paper proposes a novel method combining Pinch Methodology and waste hydrogen recovery, aiming to minimise fresh hydrogen consumption and waste hydrogen discharge. The method of multiple-level resource Pinch Analysis is extended to the level of Total Site Hydrogen Integration by considering fresh hydrogen sources with various quality. Waste hydrogen after Total Site Integration is further regenerated. The technical feasibility and economy of the various purification approaches are considered, demonstrated with a case study of a refinery hydrogen network in a petrochemical industrial park. The results showed that fresh hydrogen usage and waste hydrogen discharge could be reduced by 21.3% and 67.6%. The hydrogen recovery ratio is 95.2%. It has significant economic benefits and a short payback period for Total Site Hydrogen Integration with waste hydrogen purification. The proposed method facilitates the reuse of waste hydrogen before the purification process that incurs an additional environmental footprint. In line with the Circular Economy principles, hydrogen resource is retained in the system as long as possible before discharge.     

Hydrogen production with an auto-thermal MSW steam gasification and direct melting system: A process modeling

Municipal solid waste steam gasification and direct melting system is proposed in this study for H₂ production and ash melting simultaneously. Part of the H₂ generated in gasification is extracted for combustion with pure oxygen in the melting zone to provide the energy necessary for auto-thermal operation. A simulation model is developed with Aspen Plus to investigate the performance and optimum conditions of the system. For the feedstock with a lower heating value of 18.91 MJ/kg used in this study, 39.8% of the generated H₂ needs to be extracted to maintain the heat balance of the system at the gasification temperature of 900 °C, melting temperature of 1400 °C, and S/M of 1. The net H₂ yield is ～77.3 kg/t-MSW with a net cold gas efficiency of 49.1% under the same operating condition. An optimum operation condition for T (850–1000 °C) and S/M (0.6–1.0) is determined considering the balance between H₂ production ability and the auto-thermal energy balance.