An approximate method for predicting the stationary response of stochastically excited nonlinear systems with continuous-time Markov jump is proposed. By using the stochastic averaging method, the original system is reduced to one governed by a 1D averaged Itô equation for the total energy with the Markov jump process as parameter. A Fokker-Planck-Kolmogorov (FPK) equation is then deduced, from which the approximate stationary probability density of the response of the original system is obtained for different jump rules. To illustrate the effectiveness of the proposed method, a stochastically excited Markov jump Duffing system is worked out in detail.

The impact-synchronous modal analysis (ISMA), which uses impact-synchronous time averaging (ISTA), allows modal testing to be performed during operation. ISTA is effective in filtering out the non-synchronous cyclic load component, its harmonics, and noises. However, it was found that at operating speeds that coincide with the natural modes, ISMA would require a high number of impacts to determine the dynamic characteristics of the system. This finding has subsequently reduced the effectiveness and practicality of ISMA. Preservation of signatures during ISTA depends on the consistency of their phase angles on every time block but not necessarily on their frequencies. Thus, the effect of phase angles with respect to impact is seen to be a very important parameter when performing ISMA on structures with dominant periodic responses due to cyclic load and ambient excitation. The responses from unaccounted forces that contain even the same frequency as that contained in the response due to impact are diminished with the least number of impacts when the phase of the periodic responses is not consistent with the impact signature for every impact applied. The assessment showed that a small number of averages are sufficient to eliminate the non-synchronous components with 98.48% improvement on simulation and 95.22% improvement on experimental modal testing when the phase angles with respect to impact are not consistent for every impact applied.

Liquid or gaseous fuel scramjet technology has made great progress, and there has been some research attention to solid-fuel scramjet. A new scramjet configuration using solid fuel as propellant, namely solid-fuel rocket scramjet, is tested experimentally. It consists of two combustors. One is a rocket combustor used as gas generator, and the other is a supersonic combustor used for secondary combustion. The experiment simulates a flight Mach number of 4 at high altitude (stagnation temperature and pressure are 1170 K and 1.16 MPa, respectively), and metalized solid fuel is used as propellant. The results reveal that fuel-rich gas from the gas generator can burn with air in the supersonic combustor. Preliminary evaluation results show that the combustion efficiency of the propellant is about 90%, and the total pressure recovery coefficient in the supersonic combustor is about 0.6. These results indicate that the configuration of solid-fuel rocket scramjet is feasible.

This paper presents a novel method of identifying coal type based on mechanistic methods. The ratio of the resonance line spectrum of a luminous flame and the continuous spectrum at the same wavelength eliminates the influence of temperature on spectral intensity. The atomic line spectra of Na and K are typical and significant over continuous flame spectra. The concentrations of elemental Na and K in the flame are exclusively relative to coal type and composition. Using an experimental furnace and charge-coupled device (CCD) optical spectrometer apparatus, the continuous spectra and atomic line spectra of Na and K elements were sampled from coal flames in real time. An empirical fitting method was used to simplify the formulas of absorption strength and flame temperature calculation, and rational solutions were obtained by using an iterative algorithm. Due to the change in reaction rate and absorption by soot particles, the relative contents of Na and K in a flame vary with the temperature and absorption strength. Arrhenius’s equation for temperature compensation was adopted. Compensation for soot density in the furnace was also satisfied by an exponential expression. At any one sampling position, the compensation parameters were identical for all coal types. After compensation for temperature and density of soot particles, the relative strength of the Na and K signals and the ratio between them uniquely matched the coal type burnt in various conditions. The results were replicated and verified in various conditions, and the response time of the system was of the order of seconds.

In this study, we propose a digital image processing technology for estimating the macro permeability property of heterogeneous geomaterials. The technology is based on a connected-component labeling algorithm and provides a novel and effective method for geometry vectorization and microstructure identification. A color photo of a soil and rock mixture (SRM) is taken as an example. Information about the distribution of aggregate and a vectorgraph, which can be used in numerical analysis, are obtained automatically. A numerical permeability test is carried out to estimate the macro permeability coefficient of the heterogeneous medium. The effects on macro permeability of three parameters, scale dependency, material heterogeneity and the rock fraction, are discussed. The results indicate that the SRM has a scale dependent property and the representative element volume (REV) length is about six times the maximum major axis of the aggregate. The heterogeneity parameter has a major effect on macro permeability characteristics within a certain range. There is a weak tendency for the macro permeability to decrease as the rock fraction increases. Although the rock fraction is not the only factor, it does have an influence on the macro permeability. We conclude that the novel method developed in this study has good prospects for widespread application in macro parameter estimation and related research fields.

Positively charged composite nanofiltration (NF) membranes with good stability were prepared by dopamine (DA) assisted poly(ethylene imine) (PEI) deposition on a polysulfone ultrafiltration (UF) substrate followed by a cross-linking step. Attenuated total reflectance Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, scanning electronic microscopy, and atom force microscopy were employed to characterize the surface chemistry and morphology of the obtained composite membranes. The DA and PEI co-deposition conditions were optimized based on knowledge of the co-deposition mechanism. The effects of the cross-linker concentration, cross-linking time, and reaction temperature on the permeation and separation properties of the prepared composite membranes were investigated in detail. Under optimized conditions, the MgCl₂ rejection and permeation flux of the composite membrane reached 80.4% and 19.6 L/(m²·h), respectively (the feed was 0.01 mol/L of MgCl₂ solution under a test pressure of 0.4 MPa). The rejection of various salts followed the order MgCl₂≈CaCl₂> MgSO₄>NaCl>Na₂SO₄, suggesting the membranes were positively charged. The composite membranes showed good durability under alkaline aqueous conditions. This study provided new insights into the fabrication of mussel-inspired thin-film composite nanofiltration membranes.

Air pollution has become the predominant environmental problem caused by rapid industrialization and urbanization in China. In this study, measurements of the concentrations of PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃ at six monitoring stations in Baotou, China were used to investigate the characteristics of heavy haze pollution in Dec. 12–25, 2013. Source locations of PM_2.5 in Baotou were identified using satellite remote sensing data, an air mass trajectory model, and a conditional probability function (CPF). The results showed that the average concentrations of PM_2.5 and PM₁₀ were (113.8±84.0) μg/m³ and (211.1±149.2) μg/m³, respectively. The similar trends in temporal variation of the air pollutants PM_2.5, PM₁₀, SO₂, NO₂, and CO suggested they may share common sources. The results of satellite observations and backward trajectories supported the hypothesis that the pollutants causing the haze event originated mainly from local anthropogenic sources. According to the CPF analysis, low-speed winds from the south and southwest, upwind industrial emissions, and the northern mountains were mainly responsible for the formation of haze in Baotou. The study provides some insights to help governments optimize industrial layouts for improving air quality in the future.