Machine learning algorithm selection for windage alteration fault diagnosis of mine ventilation system

Machine learning algorithms have been widely used in mine fault diagnosis. The correct selection of the suitable algorithms is the key factor that affects the fault diagnosis. However, the impact of machine learning algorithms on the prediction performance of mine fault diagnosis models has not been fully evaluated. In this study, the windage alteration faults (WAFs) diagnosis models, which are based on K-nearest neighbor algorithm (KNN), multi-layer perceptron (MLP), support vector machine (SVM), and decision tree (DT), are constructed. Furthermore, the applicability of these four algorithms in the WAFs diagnosis is explored by a T-type ventilation network simulation experiment and the field empirical application research of Jinchuan No. 2 mine. The accuracy of the fault location diagnosis for the four models in both networks was 100%. In the simulation experiment, the mean absolute percentage error (MAPE) between the predicted values and the real values of the fault volume of the four models was 0.59%, 97.26%, 123.61%, and 8.78%, respectively. The MAPE for the field empirical application was 3.94%, 52.40%, 25.25%, and 7.15%, respectively. The results of the comprehensive evaluation of the fault location and fault volume diagnosis tests showed that the KNN model is the most suitable algorithm for the WAFs diagnosis, whereas the prediction performance of the DT model was the second-best. This study realizes the intelligent diagnosis of WAFs, and provides technical support for the realization of intelligent ventilation.     

Pulsed electric field processing of a pomegranate (Punica granatum L.) fermented beverage

The aim of this study was to evaluate the effect of pulsed electric field (PEF) (11.7 or 18 kV/cm) and pasteurization (batch or slow (VAT) and high-temperature-short time (HTST)) on the microbial, physicochemical, bioactive and sensory characteristics of a pomegranate (Punica granatum) fermented beverage (PFB) through storage at 4 °C. Bioactive compounds (antioxidant capacity, phenolic compounds, flavonoids, anthocyanins content) and color were measured. The microbiological counts (initial mesophilic aerobic bacteria (MAB) of 9.77 × 10³ CFU/mL and initial molds plus yeasts (MY) of 2.04 × 10³ CFU/mL) showed that applying 6 ms of bipolar PEFs at 18 kV/cm with 200 Hz repetition frequency reduced the microbial loads in approximately 4-log cycles, remaining <10 CFU/mL of both types of microorganisms in the PFB. PEF barely affected the total soluble solids, pH, ethanol, total acidity and color. All PEF-treated and pasteurization samples showed a slight reduction in bioactive compounds during storage. In sensory acceptability, the lowest score was given to the VAT pasteurized sample; however, still acceptable (between like slightly and like moderately).Industrial relevanceThis research provides essential information on the microbiological, physicochemical, bioactive and sensory characteristics of a pomegranate fermented beverage processed with pulsed electric fields. The pulsed electric field processing of fermented beverages may provide criteria to the processing industry to use this novel technology as a processing method for delivering a microbiological safe beverage with good sensory and antioxidant characteristics to consumers.     

Carbon corrosion mechanism on nitrogen-doped carbon support — A density functional theory study

In this work, density functional theory (DFT) calculations were used to investigate the mechanism of carbon corrosion on nitrogen-doped carbon support. Free energy diagrams were generated based on three proposed reaction pathways to evaluate corrosion mechanisms. The most energetically preferred mechanism on nitrogen-doped carbon was determined. The results show that the step of water dissociation to form ^#OH was the rate-determining step for gra-G-1N (graphene doped with graphitic N) and pyrr-G-1N (graphene doped with pyrrolic N). As for graphene doped with pyridinic N, the step of C^#OC^#O formation was critical. It was found that the control of nitrogen concentration was necessary for precisely designing optimized carbon materials. Abundance of nitrogen moieties aggravated the carbon corrosion. When the high potential was applied, specific types of graphitic N and pyridinic N were found to be favorable carbon modifications to improve carbon corrosion resistance. Moreover, the solvent effect was also investigated. The results provide theoretical insights and design guidelines to improve corrosion resistance in carbon support through material modification by inhibiting the adsorption of surface oxides (OH, O, and OOH).     

Modeling unaccounted-for gas among residential natural gas consumers using a comprehensive fuzzy cognitive map

Residential natural gas consumption depends on several factors. Available tools and methods to identify, categorize, and validate effective factors have some limitations, making consumption modeling more complex. Once a comprehensive model of effective consumption factors is developed for residential gas consumers, it can predict consumption. In addition, such a model could be used to verify the accuracy of measuring devices in order to reduce unaccounted for gas (UFG). The key factors affecting residential gas consumption were identified based on previous studies and their mutual effects were analyzed using a fuzzy cognitive mapping (FCM) method. The most significant factors and their effects on natural gas consumption in the residential sector were determined. In this study, for the first time, the expected consumption for each consumer was estimated using a consumption index. Generally, if the estimated consumption is significantly different from the amount recorded by the meter, it could suggest a potential source of UFG. The proposed method was applied to the data collected from the residential gas consumers of a small region in Iran (Dasht-e Arjan region, Fars province), and the results demonstrate the effectiveness of the proposed method.     

A novel method of shrimp blanching by CO2 heat pump: Quality,energy, and economy analysis

To reduce the energy consumption of the shrimp blanching process and improve the economic value of the blanched product, a transcritical CO₂ heat pump blanching system (THPB system) was designed in this paper. The trends of astaxanthin were investigated at atmospheric pressure near boiling temperature, combined with the color and structural properties of shrimp samples, and the optimal blanching times of 270 s and 240 s were obtained at 90°C and 95°C, respectively. In contrast to the fuel blanching system (FB system) at 100°C, the annual standard coal consumption of the THPB system with 90°C blanching is decreased by 79%, and the annual operating cost can be saved by CNY 63,800, with a payback period of about 3.13 years.Industrial relevanceBlanching is one of the effective ways to prolong the shelf life of shrimp. However, the research on the blanching time and temperature of shrimp is not comprehensive. In addition, the traditional fuel blanching process has high energy consumption and pollution, and can no longer meet the quality requirements of the modern food processing industry. Heat pump has been shown to have better performance in food drying, but it is less used in blanching. The information presented in this study may provide other insights into food processing.     

Exploring the feasibility of green hydrogen production using excess energy from a country-scale 100% solar-wind renewable energy system

When planning large-scale 100% renewable energy systems (RES) for the year 2050, the system capacity is usually oversized for better supply-demand matching of electrical energy since solar and wind resources are highly intermittent. This causes excessive excess energy that is typically dissipated, curtailed, or sold directly. The public literature shows a lack of studies on the feasibility of using this excess for country-scale co-generation. This study presents the first investigation of utilizing this excess to generate green hydrogen gas. The concept is demonstrated for Jordan using three solar photovoltaic (PV), wind, and hybrid PV-wind RESs, all equipped with Lithium-Ion battery energy storage systems (ESSs), for hydrogen production using a polymer electrolyte membrane (PEM) system. The results show that the PV-based system has the highest demand-supply fraction (>99%). However, the wind-based system is more favorable economically, with installed RES, ESS, and PEM capacities of only 23.88 GW, 2542 GWh, and 20.66 GW. It also shows the highest hydrogen annual production rate (172.1 × 10³ tons) and the lowest hydrogen cost (1.082 USD/kg). The three systems were a better option than selling excess energy directly, where they ensure annual incomes up to 2.68 billion USD while having payback periods of as low as 1.78 years. Furthermore, the hydrogen cost does not exceed 2.03 USD/kg, which is significantly lower than the expected cost of hydrogen (3 USD/kg) produced using energy from fossil fuel-based systems in 2050.     

Comparison of the retarding mechanisms of zinc oxide and sucrose on cement hydration and interactions with supplementary cementitious materials

Sucrose and zinc oxide (ZnO) are effective cement hydration retarders. The goal of this study was to provide a new look into the ZnO cement hydration mechanism and to investigate impacts of various supplementary cementitious materials (SCMs) on retardation behavior of ZnO and sucrose. Changes in the pore solution composition and reaction kinetics were measured for cementitious systems with ZnO or sucrose that contained rice straw ash (RSA), wheat straw ash, silica fume, metakaolin, and fly ash. Among the SCMs used, RSA dramatically suppressed ZnO and sucrose retardation. Experimental results indicated that the mechanism by which ZnO retards hydration reaction could be nucleation and/or growth poisoning of C-S-H. Reduced retardation of paste samples containing RSA was attributed to the ability of RSA to provide nucleation sites for C-S-H precipitation. This study provides a better understanding of the interaction between SCMs and cement hydration retarders essential in predicting retarder–dose effects.