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.     

Hierarchical multi-reservoir optimization modeling for real-world complexity with application to the Three Gorges system

High dimensionality in real-world multi-reservoir systems greatly hinders the application and popularity of evolutionary algorithms, especially for systems with heterogeneous units. An efficient hierarchical optimization framework is presented for search space reduction, determining the best water distributions, not only between cascade reservoirs, but also among different types of hydropower units. The framework is applied to the Three Gorges Project (TGP) system and the results demonstrate that the difficulties of multi-reservoir optimization caused by high dimensionality can be effectively solved by the proposed hierarchical method. For the day studied, power output could be increased by 6.79 GWh using an optimal decision with the same amount of water actually used; while the same amount of power could be generated with 2.59 × 10⁷ m³ less water compared to the historical policy. The methodology proposed is general in that it can be used for other reservoir systems and other types of heterogeneous unit generators.     

The relationship between centrality and land use patterns: Empirical evidence from five Chinese metropolises

The relationship between location and land use patterns is one of the classic theoretical issues in urban studies. Classic models based on the monocentricity hypothesis have limitations in the interpretation of modern urban structure. China has experienced institutional transformation in recent decades, and the interaction of national government policy, market forces and the natural environment has influenced urban planning in Chinese metropolises, resulting in urban structures with special characteristics. This paper examines the distribution of location and land use intensity, and tested the Alonso model by the relationship between them in five Chinese metropolises using Point of Interest data, space syntax methodology, the grid weighted statistical method and the Geographically Weighted Regression (GWR) model. Universal patterns about the scaling relation between intensity of land use types and the centrality of location are revealed. The elasticity of land use types to location, from high to low sensitivity, is commercial, residential then industrial land in most of the five metropolises studied. The sensitivity sequence of land use studied suggests that the hypothetical model based on the classical Alonso model can explain the spatial structure of modern metropolises in China to some extent, especially for the commercial land. But the order of sensitivity of residential land and industrial land to location does not conform to the model. The spatial heterogeneity in land use intensity and centrality were explored and the factors embedded were discussed. It can be found that the relation between centrality and land use intensity conforms to power law. In most of the metropolises studied, when the scaling relation between land use intensity and centrality is super linear, the sequence of the frequency value from high to low are commercial, residential and industrial land; when the scaling relation is sublinear, the sequence of the frequency value is industrial, residential and commercial land.     

Comparative evaluation of the mesophilic and thermophilic biohydrogen production at optimized conditions using tequila vinasses as substrate

The objective of this work was to comparatively evaluate the production of biohydrogen (bio-H₂) from tequila vinasses at optimized mesophilic and thermophilic conditions and to elucidate the main metabolic routes involved. Optimal temperatures of 35 °C and 55 °C, and pH of 5.5 maximized the bio-H₂ production rates, 25.5 ± 0.01 NmL h⁻¹ and 169.9 ± 8.9 NmL h⁻¹ in the mesophilic and thermophilic regimens, respectively. During the operation of anaerobic sequencing batch reactors, the thermophilic process allowed a volumetric bio-H₂ production rate of 519 ± 13 NmL-H₂ L⁻¹ d⁻¹ equivalent to 750 ± 19 NmL-H₂ L_vinasse⁻¹, while the mesophilic one 448 ± 23 NmL-H₂ L⁻¹ d⁻¹ and 647 ± 33 NmL-H₂ L_vinasse⁻¹, respectively. Furthermore, the gas produced under thermophilic conditions showed high hydrogen content (86.5%). Finally, formate degradation and glucose fermentation to acetic and butyric acids were the main metabolic routes involved in bio-H₂ production under thermophilic conditions, while at mesophilic conditions, the lactate and formate degradation pathways governed.     

Alkali catalyzed liquefaction of corncob in supercritical ethanol–water

Corncob liquefaction in supercritical ethanol–water was performed with and without the addition of an alkali catalyst by direct addition or biomass impregnation in a 250-cm³ batch reactor. The effects of temperature, solvent and alkali addition on the biomass conversion level and oil yield were investigated to find the optimum condition. For non-catalytic liquefaction using a 1:1 (v/v) ethanol: water ratio, a maximum oil yield and conversion level of 49.0% and 93.4%, respectively, were obtained at 340 °C. For alkali catalytic liquefaction, the oil yield with KOH addition (57.5%) was higher than that from KOH-impregnated corncob liquefaction (43.3%). The oil from liquefaction with KOH addition had higher heating value (26.7–35.3 MJ kg⁻¹) than the corncob (19.1 MJ kg⁻¹). The dominant components of the obtained oil were found by GC/MS analysis to be aldehyde, ester, phenol derivatives and aromatic compounds.     

Solid–liquid phase equilibria of binary indole mixtures with some aromatic compounds using a solid–liquid–vapor equation-of-state

The separation of useful chemicals, such as indole from coal tar, is an important subject of research in the field of fossil energy, renewable energy, and utilization of byproducts and waste materials. High-pressure crystallization is one of the proposed separation methods. To understand the process requires detailed knowledge of solid–liquid phase behaviors. Solid–liquid phase equilibrium data of various binary mixtures of indole have been reported in the literature. In the present report, we analyze some of the experimental data with our unified solid–liquid–vapor equation-of-state to see whether our model can be useful for the calculation of solid–liquid equilibria in these organic systems. Good correlations of the data and predictions of phase behavior, at very high pressures, are demonstrated.     

Charge transport and luminescent properties of PMMA-dehydrate nanotubed titanic acid nanocomposites

In this paper, we doped p-type conductivity dehydrated nanotubed titanic acid (DNTA) into insulator polymer poly(methyl methacrylate) (PMMA). The electric properties of this nanocomposite were investigated. The photoluminescence efficiency of fluorescent dye 4-(dicyanomethylene)-2-t-butyl-6(1,1,7,7-tetramethyljulolidyl-9-enyl)-4H-pyran (DCJTB) in PMMA matrix was enhanced by doping with DNTA. Moreover, screen effect by DNTA with high permittivity caused the emission from DCJTB to be blue-shifted.