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Aiming at the problem of inaccurate and time-consuming of the fault diagnosis method for large-scale ship engine, an intelligent diagnosis method for large-scale ship engine fault in non-deterministic environment based on neural network is proposed. First, the possible fault of the engine was analyzed, and the downtime fault of large-scale ship engine and the main fault mode were identified. On this basis, the fault diagnosis model for large-scale ship engine based on neural network is established, and the intelligent diagnosis of engine fault is completed. The experiment proved that the proposed method has high diagnostic accuracy, engine fault diagnosis takes only about 3s, with a higher use value
At present, research on relationships between carbon dioxide emissions and its influencing factors are concerned with linear causality relationships, and most literature has focused on the economic field to find its influencing factors. This article aims to investigate the causality relationships between carbon dioxide emissions and its influencing factors in China through the traditional Granger causality test and the Hiemstra and Jones test. The paper not only considers economic factors, but also takes social factors into consideration. It has been concluded that linear Granger causality relationships exist from CO₂ emissions to GDP, gross national income, and freight traffic volume. Compared with linear relationships, unidirectional nonlinear Granger causality relationships run from CO₂ emissions to resident consumption levels, and also from the urban population to CO₂ emissions. Moreover, there are bidirectional nonlinear causality relationships between CO₂ emissions and GDP, and between CO₂ emissions and the possession of private automobiles. Finally, based on the above conclusions, this article analyzes energy-saving and emission reduction measures as proposed by the Chinese government, and puts forward policy recommendations to reduce carbon dioxide emissions.
The longitudinal motion characteristics of a slender trimaran equipped with and without a T-foil near the bow are investigated by experimental and numerical methods. Computational fluid dynamics ( CFD) method is used in this study. The seakeeping characteristics such as heave, pitch and vertical acceleration in head regular waves are analyzed in various wave conditions. Numerical simulations have been validated by comparisons with experimental tests. The influence of large wave amplitudes and size of T-foil on the longitudinal motion of trimaran are analyzed. The present systematic study demonstrates that the numerical results are in a reasonable agreement with the experimental data. The research implied that the longitudinal motion response values are greatly reduced with the use of T-foil
The availability of sample data, together with detailed environmental factors, has fueled a rapid increase in predictive modeling of species geographic distributions and environmental requirements. We founded that MaxEnt model has provided different descriptions of potential distributions based on different sample size, sample accuracy and environmental background. We used six combinations based on three sample data set and two kinds of environmental variables to estimate the potentially suitable areas of Brown Eared Pheasant (Crossoptilon mantchuricum) in MaxEnt model. The results show that the complex variables provided the higher AUC value and accurate potential distribution than simple variables based on the same size of samples. Complicated environmental factors combined with moderate size and accurate sample, can predict better results. The model results were scabrous based on simple environmental factors. Furthermore, big sample size and simple prediction environmental factors will reduce the prediction accuracy, whereas small samples provided a conservative description of ecological niche. Here, we highlighted that considering the big size and high accuracy of sample and many environmental factors of a species to minimize error when attempting to infer potential distributions from current data in MaxEnt model.
Heat-stable protein fraction in seeds is believed to enrich many proteins functioning in the acquisition of stress-tolerance of seeds. In this study, the composition of heat-stable protein fraction in imbibed cowpea (Vigna unguiculata) seeds was analyzed by SDS-PAGE and twodimensional gel electrophoresis coupled with mass spectrometry. The results indicated that approximately 12.4 % of seed soluble proteins were stable after heat treatment at 100 C for 10 min. Twenty-two putative heat-stable proteins were identified using MALDI-TOF/TOF MS. Most of these heat-stable proteins were late embryogenesis abundant proteins, and there were other stress-related proteins including Cu/Zn superoxide dismutase and 17.4 kDa Class I heat-shock protein. A cyclophilin protein, a cleavage and polyadenylation specificity factor and a Pumilio-family RNA binding protein were also present in the heat-stable fraction. The identified heat-stable proteins were more hydrophilic proteins and may accumulate to stabilize cellular components and maintain seed viability during seed development and germination.
This paper describes the application of computational fluid dynamics rather than a towing tank test for the prediction of hydrodynamic derivatives using a RANS-based solver. Virtual captive model tests are conducted, including an oblique towing test and circular motion test for a bare model scale KVLCC2 hull, to obtain linear and nonlinear hydrodynamic derivatives in the 3rd-order MMG model. A static drift test is used in a convergence study to verify the numerical accuracy. The computed hydrodynamic forces and derivatives are compared with the available captive model test data, showing good agreement overall. Simulations of standard turning and zigzag manoeuvres are carried out with the computed hydrodynamic derivatives and are compared with available experimental data. The results show an acceptable level of prediction accuracy, indicating that the proposed method is capable of predicting manoeuvring motions
As an important single source to carbon emissions, China’s power industry should bear social responsibility for mitigating climate change. To explore what low-carbon development means for the industry, a novel approach that combines the extended multilevel LMDI model with Tapio algorithm was conducted to study the drivers of carbon emissions in the power industry and whether CO₂ emissions from power output is out of sync with economic development, covering the period from 1996 to 2016. Our results come to the following: 1. Carbon emissions from electricity output are characterized by increases and volatility, with an average annual growth rate of 7.05%. The carbon emission factor of electricity, facilitating to compute CO₂ data, shows a decline. 2. The positive driving factors are economic activity effect (169.53%), population scale effect (9.29%), fuel mix structure effect (0.41%), and electricity trade effect (1.05%); the negative driving factors are electricity intensity effect (-46.38%), power generation efficiency effect (-24.93%), and power generation structure effect (-8.97%). 3. Weak decoupling and expansive decoupling are the main status during the research period. The electricity intensity effect is the main force to promote the decoupling process. 4. The market-oriented reform in the power industry in 2003 has a significant effect. The generation-side competition mechanism successfully changes the historical developmental trend of the decoupling elastic index.
A new hybrid inorganic-organic copolymer, aluminum chloride-poly(acrylamide-co-acrylic acid), was prepared using the free radical polymerization method and employed in this study. The hybrid copolymer was characterized by Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and energy-dispersive x-ray spectroscopy (EDS). This hybrid copolymer was used in the flocculation of wastewater as a new flocculant. The design variables in the flocculation experiments were hybrid copolymer dosage and wastewater pH. The central composite design (CCD) for the response surface methodology (RSM) approach was used to develop a mathematical model and to optimize the parameters of the flocculation process in terms of optimal removal of chemical oxygen demand (COD), total suspended solids (TSS), and turbidity. After applying the analysis of variance (ANOVA) of all quadratic models, it was found that the obtained value of the correlation coefficient (R2) was more than 0.98 for all models. The optimum hybrid copolymer dosage was 125 mg/l and the optimum pH 7.55. Under these optimum values, the wastewater treatment achieved 97%, 98.6%, and 88.6% removal of turbidity, TSS, and COD, respectively.
Based on the potential flow theory and traditional boundary element method (BEM), Taylor expansion boundary element method (TEBEM) is introduced in this paper for the prediction of the flow field around ship, as a result, hull gesture and pressure distribution on hull surface are obtained. By this method, dipole strength of every field point is expanded in Taylor expansion, so that approximately continuous hull and free surface boundary condition could be achieved. To close the new equation system, the boundary condition of tangent velocity in every control point is introduced. With the simultaneous solving of hull boundary condition and free surface condition, the disturbance velocity potential could be obtained. The present method is used to predict the flow field and hull gesture of Wigley parabolic hull, Series 60 and KVLCC2 models. To validate the numerical model for full form ship, the wave profile, the computed hull gesture and hull surface pressure of KVLCC2 model are compared with experimental results
The acceleration of urbanization has resulted in the increase of urban surface runoff. Bio-swale is a promising stormwater control measure that has been proven to be hydrologically effective on urban surface runoff. Column studies were conducted to determine the optimal bio-swale composition. Results demonstrated that water reduction was proportional to inflow decrease. Columns that planted border privet and Ophiopogon japonicus showed a larger water quantity reduction compared with that of planted boxwood and ryegrass, glossy privet and Chlorophytum comosum ‘Variegatum’ in vegetation tests, which was the same as the order of measured transpiration capacity of the plants. Water reduction rate increases dramatically with decreasing planting soil thickness. By contrast, no significant change occurs once the thickness of the artificial filler layer is altered. The bio-swale column with a high-infiltration rate artificial filler produced a good hydrological control effect. Sand was found to be the optimal media among the selected media compositions. Although the inclusion of an additional ponding depth affected total water reduction, it produced a stable outflow. SPSS software was used to assess the relationship between water reduction rate and its influence. On the one hand, water reduction rate increased linearly with increasing water inflow, soil thickness, and ponding depth. On the other, water reduction rate grew linearly with increasing plant factor and artificial filler infiltration rate. The multiple linear regression model revealing the relationship between the water reduction effect, and its influencing factors were obtained via the stepwise regression method in the SPSS software.
In order to overcome the defects of stronger subjectivity of common assessment methods of marine ecological environmental assessment, the entropy weight model was introduced. In the comprehensive assessment, because of different influence degrees of each index to the comprehensive assessment results, different improved measures can be adopted to increase policy ability. As Shannon information entropy has the advantages of objectivity and adaptability in determining weight value, it was applied to determine the weight value of each index in the comprehensive assessment model. Then the optimal and worst indexes were selected based on a double base point model. Through comparing the distance between the scheme point and double base points, the result of comprehensive assessment can be obtained. Then the model was employed to assess the ecological environment of a bay of China. Application results show the efficiency of this method.
The Chinese power industry’s CO₂ emissions account for the largest proportion of the country’s total CO₂ emissions. Therefore, studying the influencing factors of CO₂ emissions in the power industry and developing mitigation policies are of great significance for reducing CO₂ emissions. According to the electricity-related data from 2000 to 2014 in China, this paper employed the improved STIRPAT model to examine the impact factors of economic growth, urbanization level, industrialization level, power consumption efficiency, power generation efficiency, and electric power structure of the CO₂ emissions in China’s power industry. Then we adopted the Ridge Regression method to fit the extended STIRPAT model. The results show that power generation efficiency is a decisive factor of CO₂ emissions reduction. Electric power structure and economic growth play important roles in reducing CO₂ emissions. Power consumption efficiency has a large potential to mitigate CO₂ emissions, while urbanization and industrialization levels are less important impact factors. Based on the above conclusions, the Chinese government needs to formulate appropriate policies in terms of power generation, supply, and consumption to reduce the power industry’s CO₂ emissions.
Enteromorpha prolifera green algae is the main species that causes green tide in China’s Yellow Sea. To effectively realize the resourceful utilization of this biomass, batch experiments were carried out to investigate factors that impact the Acid Bordeaux B (ABB) absorption of E. prolifera powder, such as exposure time, pH, adsorbent dose, and oscillation frequency. The dye adsorption onto adsorbent was confirmed by Fourier transform infrared spectroscopy (FTIR). Results showed that amide, hydroxy, carboxylate, and C-O groups were involved in the adsorption process. The treatment conditions for dye concentration of 100 mg·L⁻¹ were optimized: contact time 60 min, pH value 4 to 9, water temperature 303 to 313 K, adsorbent dosage 0.25 g·L⁻¹ and oscillation frequency 150 rpm. Equilibrium data were analyzed by using the Freundlich and Langmuir models. The data fit well in both models. The maximum equilibrium adsorption capacity calculated by the Langmuir equation was 1,111.11-3,333.33 mg·g⁻¹. To clarify the sorption kinetic, the fitness of the Pseudofirst- order model, the Pseudo-second-order model, and the intra-particle diffusion model were tested, showing that the pseudo-second order model was suitable to describe the adsorption process. The sorption process was complex, and both the boundary of liquid film and intra-particle diffusion contributed to the rate-determining step. Thermodynamic parameters (e.g. ΔG⁰, ΔH⁰, and ΔS⁰) were calculated, which implied the exothermic and spontaneous nature of biosorption as well as the type of adsorption (physisorption). Results illustrate that the removal ratio from the wastewater with 100 mg·L⁻¹ ABB reached 90.86%, indicating that E. prolifera could be a potential biosorbent used for the removal of ABB from industrial effluents.
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