Numerical analysis of geosynthetic-reinforced embankment performance under moving loads

The performance of geosynthetic-reinforced embankments under traffic moving loads is always a hotspot in the geotechnical engineering field.A three-dimensional(3D)model of a geosynthetic-reinforced embankment without drainage consolidation was established using the finite element software ABAQUS.In this model,the traffic loads were simulated by two moving loads of rectangular pattern,and their amplitude,range,and moving speed were realized by a Fortran subroutine.The embankment fill was simulated by an equivalent linear viscoelastic model,which can reflect its viscoelasticity.The geogrid was simulated by the truss element,and the geocell was simulated by the membrane element.Infinite elements were utilized to weaken the boundary effect caused by the model geometry at the boundaries.Validation of the established numerical model was conducted by comparing the predicted deformations in the cross-section of the geosynthetic-reinforced embankment with those from the existing literature.On this basis,the dynamic stress and strain distribution in the pavement structure layer of the geosynthetic-reinforced embankment under a moving load was also analyzed.Finally,a parametric study was conducted to examine the influences of the different types of reinforcement,overload,and the moving load velocity on the geosynthetic-reinforced embankment.

Chemical looping gasification of sewage sludge using copper slag modified by NiO as an oxygen carrier

Chemical looping gasification(CLG) provides a novel approach to dispose the sewage sludge.In order to improve the reactivity of the calcined copper slag,NiO modification is considered as one of the good solutions.The copper slag calcined at 1100℃ doped with 20 wt% NiO(Ni20-CS) was used as an oxygen carrier(OC) in sludge CLG in the work.The modification of NiO can evidently enhance the reactivity of copper slag to promote the sludge conversion,especially for sludge char conversion.The carbon conversion and valid gas yield(V_(g)) increase from 67.02% and 0.23 m^(3)·kg^(-1) using the original OC to 78.34% and 0.29 m^(3)·kg^(-1) using the Ni20-CS OC, respectively.The increase of equivalent coefficient(Ω) facilitates the sludge conversion and a suitable Ω value is determined at 0.47 to obtain the highest valid gas yield(0.29 m^(3)·kg^(-1)).A suitable steam content is assigned at 27.22% to obtain the maximum carbon conversion of 87.09%,where an acceptable LHV of 12.63 MJ·m^(-3) and Vg of 0.39 m^(3)·kg^(-1)are obtained.Although the reactivity of Ni20-CS OC gradually decreases with the increase in cycle numbers because of the generation of NiFe_(2) O_(4-δ) species,the deposition of sludge ash containing many metallic elements is beneficial to the sludge conversion.As a result,the carbon conversion shows a slight uptrend with the increase of cycle numbers in sludge CLG.It indicates that the Ni20-CS sample is a good OC for sludge CLG.

Experimental and simulation investigation of electrical and plasma parameters in a low pressure inductively coupled argon plasma

The electrical and plasma parameters of a low pressure inductively coupled argon plasma are investigated over a wide range of parameters（RF power, flow rate and pressure） by diverse characterizations. The external antenna voltage and current increase with the augment of RF power, whereas decline with the enhancement of gas pressure and flow rate conversely.Compared with gas flow rate and pressure, the power transfer efficiency is significantly improved by RF power, and achieved its maximum value of 0.85 after RF power injected excess125 W. Optical emission spectroscopy（OES） provides the local mean values of electron excited temperature and electron density in inductively coupled plasma（ICP） post regime, which vary in a range of 0.81 eV to 1.15 eV and 3.7×10^（16）m^（-3）to 8.7×10^（17）m^（-3）respectively. Numerical results of the average magnitudes of electron temperature and electron density in twodimensional distribution exhibit similar variation trend with the experimental results under different operating condition by using COMSOL Multiphysics. By comprehensively understanding the characteristics in a low pressure ICP, optimized operating conditions could be anticipated aiming at different academic and industrial applications.

Co-synthesis of vertical graphene nanosheets and high-value gases using inductively coupled plasma enhanced chemical vapor deposition

One-step controllable synthesis of vertical graphene nanosheets （VGs） and high-value gases was achieved using inductively coupled plasma enhanced chemical vapor deposition （ICPECVD）. The basic physical properties of the ICPECVD process were revealed via electrical diagnosis and optical emission spectroscopy. The coil current and voltage increased linearly with the augmenting of injected power, and CH, C2, H2 and H were detected at a wavelength from 300 to 700 nm, implying the generation of abundant graphene-building species. The morphology and structure of solid carbon products, graphene nanosheets, were systemically characterized in terms of the variations of operating conditions, such as pressure, temperature, gas proportion, etc. The results indicated that an appropriate operating condition was indispensable for the growth process of graphene nanosheets. In the present work, the optimized result was achieved at the pressure, heating temperature, applied power and gas proportion of 600 mTorr, 800 ~C, 500 W and 20：20：15, respectively, and the augmenting of both CH4 and H2 concentrations had a positive effect on the etching of amorphous carbon. Additionally, H2 and C2 hydrocarbons were detected as the main exhaust gases. The selectivity of H2 and C2H2, measured in exhaust gases, reached up to 52% and 8%, respectively, which implied a process of free radical reactions and electron collision dissociation. Based on a comprehensive investigation of spectral and electrical parameters and synthesized products, the reaction mechanism of collision, dissociation, diffusion, etc, in ICPECVD could be speculated, providing a probable guide for experimental and industrial applications.

Synthesis of vertical graphene nanowalls by cracking n-dodecane using RF inductively-coupled plasma-enhanced chemical vapor deposition

A facile and controllable one-step method to treat liquid hydrocarbons and synthesize vertical graphene nanowalls has been developed by using the technique of inductively-coupled plasma-enhanced chemical vapor deposition for plasma cracking of n-dodecane.Herein,the morphology and microstructure of solid carbon material and graphene nanowalls are characterized in terms of different operating conditions,i.e.input power,H2/Ar ratio,injection rate and reaction temperature.The results reveal that the optimal operating conditions were 500 W,5:10,30μl min^-1 and 800℃ for the input power,H2/Ar ratio,injection rate and reaction temperature,respectively.In addition,the degree of graphitization and the gaseous product are analyzed by Raman spectroscopy and gas chromatography detection.It can be calculated from the Raman spectrum that the relative intensity of ID/IG is approximately 1.55,and I2D/IG is approximately 0.48,indicating that the graphene prepared from n-dodecane has a rich defect structure and a high degree of graphitization.By calculating the mass loading and detecting the outlet gas,we find that the cracking rate of n-dodecane is only 6%-7%and that the gaseous products below C2 mainly include CH4,C2H2,C2H4,C2H6 and H2.Among them,the proportion of hydrogen in the outlet gas of n-dodecane cracking ranges from 1.3%-15.1%under different hydrogen flows.Based on our research,we propose a brand new perspective for both liquid hydrocarbon treatment and other value-added product syntheses.

Vision-based survey method for extraordinary loads on buildings

The statistical modeling of extraordinary loads on buildings has been stagnant for decades due to the laborious and error-prone nature of existing survey methods,such as questionnaires and verbal inquiries.This study proposes a new vision-based survey method for collecting extraordinary load data by automatically analyzing surveillance videos.For this purpose,a crowd head tracking framework is developed that integrates crowd head detection and reidentification models based on convolutional neural networks to obtain head trajectories of the crowd in the survey area.The crowd head trajectories are then analyzed to extract crowd quantity and velocities,which are the essential factors for extraordinary loads.For survey areas with frequent crowd movements during temporary events,the equivalent dynamic load factor can be further estimated using crowd velocity to consider dynamic effects.A crowd quantity investigation experiment and a crowd walking experiment are conducted to validate the proposed survey method.The experimental results prove that the proposed survey method is effective and accurate in collecting load data and reasonable in considering dynamic effects during extraordinary events.The proposed survey method is easy to deploy and has the potential to collect substantial and reliable extraordinary load data for determining design load on buildings.

An improved window opening behavior model involving the division of the dummy variable’s interval level:Case study of an office building in Xi’an during summer

Window opening behavior significantly impacts indoor air quality,thermal comfort,and energy consumption.A field measurement was carried out in three typical rooms(a standard office,a meeting room and a smoking office)within an office building.The window state and the physical environment were continuously recorded during the measured periods.Three typical window opening behaviors were found in the measured samples,namely,active,moderate,and passive.The common logistic regression coefficient indicated that solar radiation exhibited the greatest effect on window opening behavior in the smoking office and standard office.Typically,window opening behavior in the meeting room was the most strongly correlated with time of the day,mainly because of the meeting schedule for occupants in the meeting room.This study discussed the dividing principles involved in setting the dummy variable interval level(discretizing continuous variables and dividing them into different intervals),and proposed a method to determine the optimal interval level of each variable.The improved model led to the increase in the prediction accuracy rate of the window being opened by 2.0%and 3.3%according to the comparison with the original model based on dummy variables and the common model based on continuous variables,respectively.This study can provide a reference value for simulating energy consumption in office buildings in the future.

Catalytic ozonation treatment of papermaking wastewater by Ag-doped NiFe2O4 : Performance and mechanism

The catalytic ozonation treatment of secondary biochemical effluent for papermaking wastewater by Ag-doped nickel ferrite was investigated.Ag-doped catalysts prepared by sol-gel method were characterized,illustrating that Ag entirely entered the crystalline of Ni Fe2O4 and changed the surface properties.The addition of catalyst enhanced the removal efficiency of chemical oxygen demand and total organic carbon.The results of gas chromatography-mass spectrometer,ultraviolet light absorbance at 254 nm and threedimensional fluorescence excitation-emission matrix suggested that aromatic compounds were efficiently degraded and toxic substances,such as dibutyl phthalate.In addition,the radical scavenging experiments confirmed the hydroxyl radicals acted as the main reactive oxygen species and the surface properties of catalysts played an important role in the reaction.Overall,this work validated potential applications of Ag-doped Ni Fe2O4 catalyzed ozonation process of biologically recalcitrant wastewater.

Dynamic forecasting and optimal scheduling of by-product gases in integrated iron and steel works

The by-product gases, which are generated in ironmaking, coking and steel making processes, can be used as fuel for the metallurgical processes and on-site power plants. However, if the supply and demand of by-product gases are imbalanced, gas flaring may occur, leading to energy wastage and environmental pollution. Therefore, optimal scheduling of by-product gases is important in iron and steel works. A BP_LSSVM model, which combines back-propagation (BP) neural network and least squares support vector machine (LSSVM), and an improved mixed integer linear programming model were proposed to forecast the surplus gases and allocate them optimally. To maximize energy utilization, the stability of gas holders and boilers was considered and a concise heuristic procedure was proposed to assign penalties for boilers and gas holders. Moreover, the optimal level of gas holder was studied to enhance the stability of the gas system. Compared to the manual operation, the optimal results showed that the electricity generated by the power plant increased by 2.93% in normal condition and by 22.2% in overhaul condition. The proposed model minimizes the total cost by optimizing the boiler load with less adjustment frequency and the stability of gas holders and can be used as a guidance in dynamic forecasting and optimal scheduling of by-product gases in integrated iron and steel works.