The galvanic corrosion behavior of metal-matrix composite plain carbon steel/boron carbide (B₄C) in 3.5% NaCl solution was studied. The composite was locally produced as a weld band on carbon steel by means of the gas tungsten arc welding process and using nickel as the wetting agent. Samples from the weld band, heat-affected zone and parent metal region were extracted precisely and DC/AC electrochemical tests in combination with techniques such as scanning electron microcopy and energy dispersive spectrometry were conducted. The results of the electrochemical tests show that the corrosion resistance of the parent metal sample is higher than that of the welded composite and the HAZ samples. However, as the corrosion potential (E_Corr) of the parent metal is more positive than other two samples, this becomes the cathode in galvanic couples with two other samples. On the other hand, the weld composite sample is also cathodic due to its more positive E_Corr compared to HAZ sample. This means that the HAZ can be particularly at risk of preferential dissolution. The approach can be used in specific areas on plain carbon steel to locally increase hardness and resistance to abrasion and reduce manufacturing costs.

Research has been conducted about the hardness prediction for the carburizing and quenching process based on an optimized hardness simulation model, in accordance with the calculation rule of mixed phases. The coupling field model incorporates carburizing field analysis, temperature field analysis, phase transformation kinetics analysis and a modified hardness calculation model. In determination of the calculation model for hardness, calculation equations are given to be applied to low carbon content (x(C)≤0.5%) for the child phases and the martensite hardness is calculated for high carbon content (x(C)>0.5%) in alloy. Then, the complete carburizing-quenching hardness calculation model is built, and the hardness simulation data are corrected considering the influence of residual austenite (RA) on hardness. Hardness simulations of the carburizing and quenching process of 17CrNiMo6 samples have been performed using DEFORM-HT_V10.2 and MATLAB R2013a. Finally, a series of comparisons of simulation results and measured values show a good agreement between them, which validates the accuracy of the proposed mathematical model.

Vertical hot ring rolling (VHRR) process has the characteristics of nonlinearity, time-variation and being susceptible to disturbance. Furthermore, the ring’s growth is quite fast within a short time, and the rolled ring’s position is asymmetrical. All of these cause that the ring’s dimensions cannot be measured directly. Through analyzing the relationships among the dimensions of ring blanks, the positions of rolls and the ring’s inner and outer diameter, the soft measurement model of ring’s dimensions is established based on the radial basis function neural network (RBFNN). A mass of data samples are obtained from VHRR finite element (FE) simulations to train and test the soft measurement NN model, and the model’s structure parameters are deduced and optimized by genetic algorithm (GA). Finally, the soft measurement system of ring’s dimensions is established and validated by the VHRR experiments. The ring’s dimensions were measured artificially and calculated by the soft measurement NN model. The results show that the calculation values of GA-RBFNN model are close to the artificial measurement data. In addition, the calculation accuracy of GA-RBFNN model is higher than that of RBFNN model. The research results suggest that the soft measurement NN model has high precision and flexibility. The research can provide practical methods and theoretical guidance for the accurate measurement of VHRR process.

Refined carbon (RC) derived from coal fly ash (CFA) as well as powdered activated carbon (PAC) was investigated as adsorbent to remove residual amine collector HAY from aqueous solution. The RC and PAC were characterized by scanning electron microscopy (SEM), surface area measurement, Zeta potential measurement and Fourier transform infrared (FTIR) spectroscopy. The effect factors and mechanisms of HAY adsorption onto RC and PAC were studied in detail. The results show that the experimental kinetic data agree well with the pseudo second-order equation, and the Langmuir isotherm model is found to be more appropriate to explicate the experimental equilibrium isotherm results than the Freundlich model. The adsorption capacities of PAC and RC increase with pH. It is found that alkaline condition is conducive to the adsorption of HAY onto PAC and RC and the adsorption efficiency of RC is close to PAC at pH near 11. Zeta potential variation of adsorbents suggests that HAY generates electrostatic adsorption onto RC and PAC. FTIR analysis shows that the adsorption is dominantly of a physical process. The Box-Behnken design optimization conditions of process are RC 1 g/L, pH 11, temperature 302 K and initial HAY concentration 100 mg/L. Under these conditions, the measured adsorption ratio and adsorption capacity are 87.91% and 87.91 mg/g, respectively. Thus, the RC is considered to be a potential adsorbent for the removal of residual amine from aqueous solution.

The effect of sinter basicity on softening-melting behaviors of mixed burden made from chromium-bearing vanadium-titanium magnetite (Cr-V-Ti magnetite) was investigated and the function mechanism was simultaneously analyzed. The results show that with increasing sinter basicity from 1.71 to 2.36, the softening interval tends to increase from 149.3 °C to 181.7 °C while the melting interval tends to decrease from 178.0 °C to 136.7 °C. The location of cohesive zone moves downwards firstly and then ascends slightly, but the cohesive zone becomes thinner. The softening-melting characteristic value becomes small, which indicates that the permeability of burden column is improved. The dripping ratio of mixed burden tends to increase firstly and then decrease, which comes to the highest value of 74.50% when the sinter basicity is 2.13. The content and the recovery of V and Cr in dripping iron are all increased. The generation amount of components with high melting point in slag becomes little with the increase of sinter basicity, which could improve the permeability of mixed burden. Taking softening-melting behaviors of mixed burden and recovery of valuable elements into account, the proper sinter basicity is no less than 2.13 for smelting mixed burden made from Cr-V-Ti magnetite in blast furnace.

The single hot thermocouple technique (SHTT) and high temperature equilibrium technique were combined to investigate the phase diagram of the CaO−SiO₂−5%MgO−20%Al₂O₃−TiO₂ system. The 1300 °C to 1500 °C liquidus lines are calculated according to the thermodynamic equations based on the pseudo-melting temperatures measured by the single hot thermocouple technique. The phase equilibria relationships are experimentally determined at 1400 °C using the high temperature equilibria technique followed by X-ray fluorescence (XRF), X-ray diffraction(XRD), scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX) analysis. The liquid phase(L), melilite solid solution phase ((C₂MS₂,C₂AS)ss), diopside phase(CMS₂) and perovskite phase (CaO·TiO₂) are found. Coupled with the liquidus lines and equilibria results, the phase diagram is constructed for the specified region of the CaO−SiO₂−5%MgO−20%Al₂O₃−TiO₂ system.

To investigate effect of metallic ion activation on different particle sizes of quartz in butyl xanthate solution, six common ions (Pb²⁺, Cu²⁺, Fe³⁺, Fe²⁺, Mg²⁺ and Ca²⁺) were introduced as activators. The approaches of micro-flotation, adsorption test and zeta potential measurement were adopted to reveal the mechanism of ion activation. The results show that Pb²⁺, Cu²⁺ and Fe³⁺ are effective activators for the flotation of quartz in butyl xanthate solution because of their absorption on activated quartz surface. Average recoveries of fine particles (<37 μm) are greater than those of coarser particles (37−74 μm), suggesting that the former is easier to be activated and more likely to be floated and thus entrained in sulphide concentrate. From another perspective, addition of metallic ions (Pb²⁺, Cu²⁺ and Fe³⁺) renders zeta potentials move positively, and addition of the same metallic ions and butyl xanthate makes zeta potential drop apparently, which support a mechanism where they adsorb onto quartz surface, resulting in an expected increase in butyl xanthate collector adsorption with a concomitant increase in the flotation recoveries.

Proper utilization of the FeSO₄·7H₂O waste slag generated from TiO₂ industry is an urgent need, and Fe₃O₄ particles are currently being widely used in the wastewater flocculation field. In this work, magnetite was recovered from ferrous sulphate by a novel co-precipitation method with calcium hydroxide as the precipitant. Under optimum conditions, the obtained spherical magnetite particles are well crystallized with a Fe₃O₄ purity of 88.78%, but apt to aggregate with a median particle size of 1.83 μm. Magnetic measurement reveals the obtained Fe₃O₄ particles are soft magnetic with a saturation magnetization of 81.73 A·m²/kg. In addition, a highly crystallized gypsum co-product is obtained in blocky or irregular shape. Predictably, this study would provide additional opportunities for future application of low-cost Fe₃O₄ particles in water treatment field.

The high precision assemblies with considerable radial interference should be accompanied by heating and cooling processes. However, the mechanical properties of metals are greatly affected by thermal operations. So, for evaluating the stress distribution and distortion of teeth profiles in a gear/shaft assembly, a transient thermal analysis is necessary for finding the change in mechanical properties. The friction on the contact surface is another important parameter in interaction of the gear with the shaft. Evaluating the gear stress and deformation fields for several modes of heat transfer and friction coefficients showed that the maximum radial or tangential stresses on contact surface of the joint may have more than 8% increase by increasing friction coefficient; while the intensity of heat transfer at cooling stage has lower effect on stress distribution.

In this research combustion of aluminum dust particles in a quiescent medium with spatially discrete sources distributed in a random way was studied by a numerical approach. A new thermal model was generated to estimate flame propagation speed in a lean/rich reaction medium. Flame speed for different particle diameters and the effects of various oxidizers such as carbon dioxide and oxygen on flame speed were studied. Nitrogen was considered the inert gas. In addition, the quenching distance and the minimum ignition energy (MIE) were studied as a function of dust concentration. Different burning time models for aluminum were employed and their results were compared with each other. The model was based on conduction heat transfer mechanism using the heat point source method. The combustion of single-particle was first studied and the solution was presented. Then the dust combustion was investigated using the superposition principle to include the effects of surrounding particles. It is found that larger particles have higher values of quenching distance in comparison with smaller particles in an assumed dust concentration. With the increase of dust concentration the value of MIE would be decreased for an assumed particle diameter. Considering random discrete heat sources method, the obtained results of random distribution of fuel particles in space provide closer and realistic predictions of the combustion physics of aluminum dust flame as compared with the experimental findings.

In distribution systems, network reconfiguration and capacitor placement are commonly used to diminish power losses and keep voltage profiles within acceptable limits. Moreover, the problem of DG allocation and sizing is great important. In this work, a combination of a fuzzy multi-objective approach and bacterial foraging optimization (BFO) as a meta-heuristic algorithm is used to solve the simultaneous reconfiguration and optimal sizing of DGs and shunt capacitors in a distribution system. Each objective is transferred into fuzzy domain using its membership function. Then, the overall fuzzy satisfaction function is formed and considered a fitness function inasmuch as the value of this function has to be maximized to gain the optimal solution. The numerical results show that the presented algorithm improves the performance much more than other meta-heuristic algorithms. Simulation results found that simultaneous reconfiguration with DG and shunt capacitors allocation (case 5) has 77.41%, 42.15%, and 56.14% improvements in power loss reduction, load balancing, and voltage profile indices, respectively in 33-bus test system. This result found 87.27%, 35.82%, and 54.34% improvements of mentioned indices respectively for 69-bus system.

Ride and handling are two paramount factors in design and development of vehicle suspension systems. Conflicting trends in ride and handling characteristics propel engineers toward employing multi-objective optimization methods capable of providing the best trade-off designs compromising both criteria simultaneously. Although many studies have been performed on multi-objective optimization of vehicle suspension system, only a few of them have used probabilistic approaches considering effects of uncertainties in the design. However, it has been proved that optimum point obtained from deterministic optimization without taking into account the effects of uncertainties may lead to high-risk points instead of optimum ones. In this work, reliability-based robust multi-objective optimization of a 5 degree of freedom (5-DOF) vehicle suspension system is performed using method of non-dominated sorting genetic algorithm-II (NSGA-II) in conjunction with Monte Carlo simulation (MCS) to obtain best designs considering both comfort and handling. Road profile is modeled as a random function using power spectral density (PSD) which is in better accordance with reality. To accommodate the robust approach, the variance of all objective functions is also considered to be minimized. Also, to take into account the reliability criterion, a reliability-based constraint is considered in the optimization. A deterministic optimization has also been performed to compare the results with probabilistic study and some other deterministic studies in the literature. In addition, sensitivity analysis has been performed to reveal the effects of different design variables on objective functions. To introduce the best trade-off points from the obtained Pareto fronts, TOPSIS method has been employed. Results show that optimum design point obtained from probabilistic optimization in this work provides better performance while demonstrating very good reliability and robustness. However, other optimum points from deterministic optimizations violate the regarded constraints in the presence of uncertainties.

To decrease breakdown time and improve machine operation reliability, accurate residual useful life (RUL) prediction has been playing a critical role in condition based monitoring. A data fusion method was proposed to achieve online RUL prediction of slewing bearings, which consisted of a reliability based RUL prediction model and a data driven failure rate (FR) estimation model. Firstly, an RUL prediction model was developed based on modified Weibull distribution to build the relationship between RUL and FR. Secondly, principal component analysis (PCA) was introduced to process multi-dimensional life-cycle vibration signals, and continuous squared prediction error (CSPE) and its time-domain features were employed as equipment performance degradation features. Afterwards, an FR estimation model was established on basis of the degradation features and relevant FRs using simplified fuzzy adaptive resonance theory map (SFAM) neural network. Consequently, real-time FR of equipment can be obtained through FR estimation model, and then accurate RUL can be calculated through the RUL prediction model. Results of a slewing bearing life test show that CSPE is an effective indicator of performance degradation process of slewing bearings, and that by combining actual load condition and real-time monitored data, the calculation time is reduced by 87.3% and the accuracy is increased by 0.11%, which provides a potential for online RUL prediction of slewing bearings and other various machineries.

Modeling of rough surfaces with given roughness parameters is studied, where surfaces with Gaussian height distribution and exponential auto-correlation function (ACF) are concerned. A large number of micro topography samples are randomly generated first using the rough surface simulation method with FFT. Then roughness parameters of the simulated roughness profiles are calculated according to parameter definition, and the relationship between roughness parameters and statistical distribution parameters is investigated. The effects of high-pass filtering with different cut-off lengths on the relationship are analyzed. Subsequently, computing formulae of roughness parameters based on standard deviation and correlation length are constructed with mathematical regression method. The constructed formulae are tested with measured data of actual topographies, and the influences of auto-correlation variations at different lag lengths on the change of roughness parameter are discussed. The constructed computing formulae provide an approach to active modeling of rough surfaces with given roughness parameters.

An iterative direct-forcing immersed boundary method is extended and used to solve convection heat transfer problems. The pressure, momentum source, and heat source at immersed boundary points are calculated simultaneously to achieve the best coupling. Solutions of convection heat transfer problems with both Dirichlet and Neumann boundary conditions are presented. Two approaches for the implementation of Neumann boundary condition, i.e. direct and indirect methods, are introduced and compared in terms of accuracy and computational efficiency. Validation test cases include forced convection on a heated cylinder in an unbounded flow field and mixed convection around a circular body in a lid-driven cavity. Furthermore, the proposed method is applied to study the mixed convection around a heated rotating cylinder in a square enclosure with both iso-heat flux and iso-thermal boundary conditions. Computational results show that the order of accuracy of the indirect method is less than the direct method. However, the indirect method takes less computational time both in terms of the implementation of the boundary condition and the post processing time required to compute the heat transfer variables such as the Nusselt number. It is concluded that the iterative direct-forcing immersed boundary method is a powerful technique for the solution of convection heat transfer problems with stationary/moving boundaries and various boundary conditions.

To make backfilling body meet strength requirement, physical-chemical evaluation and proportioning tests were conducted on several backfilling materials. Jigging sands, #32.5 cement and fly ash were determined as backfilling aggregate, binding material and modified material, respectively. An optimized proportion of backfilling materials with a solid mass fraction of 78% and cement: fly ash: jigging sands mass ratio of 1:2:14, was suggested to Jiangan Pyrite Mine, China. The slurry made by optimized proportion produced obvious shear thinning phenomena, and was confirmed as paste-like slurry. To analyze its rheological characteristics, L-type pipeline test and Haake VT550 rotational viscometer test were conducted. Bingham and Casson fluid models were applied to several paste-like slurry samples to simulate flow and stress states; Casson fluid model was proved to have better simulation effect on paste-like slurry with shear thinning phenomena; rheological parameters of backfilling slurry made by suggested proportion were measured. Initial yield stress, average apparent viscosity and limiting viscosity are 55.35 Pa, 1.216 Pa·s and 0.48 Pa·s, respectively. Compared with Bingham fluid model, Casson fluid model has a better simulation effect on paste-like slurry with shear thinning phenomena, through calculating the residual standard deviations.

The concepts of rock strength intervals are presented in this work, furthermore, central values of intervals and their corresponding credibility are provided using two-case study based on blind data theory and fuzzy interval estimation. 60 granite specimens are first tested, the compressive strength interval and tensile strength interval are [103.68, 219.61] and [7.53, 11.86] MPa, while the tested mean values of compressive strength and tensile strength are 152.86 and 10.14 MPa, the credibilities are less than 58.4% and around 70.4%, respectively, the credibility of shear strength is between 40% and 60%. Then 70 other rock specimens are designed and tested, the similar conclusions can be reached. The results show that the conventional definite values are the particular values within the intervals, and the credibility of them often fails to reach the high-precision engineering requirement. The results demonstrate the feasibility and application potential of this proposed algorithm for the engineering practice. The references for engineering value selection of rock strength under different credibility or according to frequency distribution of central values are provided to increase the reliability and precision of calculation.

The structural system failure probability (SFP) is a valuable tool for evaluating the global safety level of concrete gravity dams. Traditional methods for estimating the failure probabilities are based on defined mathematical descriptions, namely, limit state functions of failure modes. Several problems are to be solved in the use of traditional methods for gravity dams. One is how to define the limit state function really reflecting the mechanical mechanism of the failure mode; another is how to understand the relationship among failure modes and enable the probability of the whole structure to be determined. Performing SFP analysis for a gravity dam system is a challenging task. This work proposes a novel nonlinear finite-element-based SFP analysis method for gravity dams. Firstly, reasonable nonlinear constitutive modes for dam concrete, concrete/rock interface and rock foundation are respectively introduced according to corresponding mechanical mechanisms. Meanwhile the response surface (RS) method is used to model limit state functions of main failure modes through the Monte Carlo (MC) simulation results of the dam-interface-foundation interaction finite element (FE) analysis. Secondly, a numerical SFP method is studied to compute the probabilities of several failure modes efficiently by simple matrix integration operations. Then, the nonlinear FE-based SFP analysis methodology for gravity dams considering correlated failure modes with the additional sensitivity analysis is proposed. Finally, a comprehensive computational platform for interfacing the proposed method with the open source FE code Code Aster is developed via a freely available MATLAB software tool (FERUM). This methodology is demonstrated by a case study of an existing gravity dam analysis, in which the dominant failure modes are identified, and the corresponding performance functions are established. Then, the dam failure probability of the structural system is obtained by the proposed method considering the correlation relationship of main failure modes on the basis of the mechanical mechanism analysis with the MC-FE simulations.

Mechanical behaviors of granular materials are complicated and greatly influenced by the particle shape. Current, some composite approaches have been proposed for realistic particle shape modelling within discrete element method (DEM), while they cannot give a good representation to the shape and mass properties of a real particle. In this work, a novel algorithm is developed to model an arbitrary particle using a cluster of non-overlapping disks. The algorithm mainly consists of two components: boundary filling and domain filling. In the boundary filling, some disks are placed along the boundary for a precise representation of the particle shape, and some more disks are placed in the domain to give an approximation to the mass properties of the particle in the domain filling. Besides, a simple method is proposed to correct the mass properties of a cluster after domain filling and reduce the number of the disks in a cluster for lower computational load. Moreover, it is another great merit of the algorithm that a cluster generated by the algorithm can be used to simulate the particle breakage because of no overlaps between the disks in a cluster. Finally, several examples are used to show the robust performance of the algorithm. A current FORTRAN version of the algorithm is available by contacting the author.

In order to study the differences in vertical component between onshore and offshore motions, the vertical-to-horizontal peak ground acceleration ratio (V/H PGA ratio) and vertical-to-horizontal response spectral ratio (V/H) were investigated using the ground motion recordings from the K-NET network and the seafloor earthquake measuring system (SEMS). The results indicate that the vertical component of offshore motions is lower than that of onshore motions. The V/H PGA ratio of acceleration time histories at offshore stations is about 50% of the ratio at onshore stations. The V/H for offshore ground motions is lower than that for onshore motions, especially for periods less than 0.8 s. Furthermore, based on the results in statistical analysis for offshore recordings in the K-NET, the simplified V/H design equations for offshore motions in minor and moderate earthquakes are proposed for seismic analysis of offshore structures.

For calculating the thermal storage time for an annular tube with phase change material (PCM), a novel method is proposed. The method is suitable for either low-temperature PCM or high-temperature PCM whose initial temperature is near the melting point. The deviation fit is smaller than 8% when the time is below 2×10⁴ s. Comparison between the predictions and the reported experimental data of thermal storage time at same conditions is investigated and good agreements have been got. Based on this method, the performance of the thermal storage unit and the role of natural convection are also investigated. Results show a linear relation between the maximum amount of stored heat and thermal storage time, and their ratio increases with the height of the thermal storage unit. As the thickness of the cavity increases, natural convection plays an increasingly important role in promoting the melting behavior of paraffin. When the thickness of the cavity is small, natural convection restrains the melting behavior of paraffin.

The classical elastic impedance (EI) inversion method, however, is based on the L2-norm misfit function and considerably sensitive to outliers, assuming the noise of the seismic data to be the Guassian-distribution. So we have developed a more robust elastic impedance inversion based on the L1-norm misfit function, and the noise is assumed to be non-Gaussian. Meanwhile, some regularization methods including the sparse constraint regularization and elastic impedance point constraint regularization are incorporated to improve the ill-posed characteristics of the seismic inversion problem. Firstly, we create the L1-norm misfit objective function of pre-stack inversion problem based on the Bayesian scheme within the sparse constraint regularization and elastic impedance point constraint regularization. And then, we obtain more robust elastic impedances of different angles which are less sensitive to outliers in seismic data by using the IRLS strategy. Finally, we extract the P-wave and S-wave velocity and density by using the more stable parameter extraction method. Tests on synthetic data show that the P-wave and S-wave velocity and density parameters are still estimated reasonable with moderate noise. A test on the real data set shows that compared to the results of the classical elastic impedance inversion method, the estimated results using the proposed method can get better lateral continuity and more distinct show of the gas, verifying the feasibility and stability of the method.

Metro passenger flow control problem is studied under given total inbound demand in this work, which considers passenger demand control and train capacity supply. Relevant connotations are analyzed and a mathematical model is developed. The decision variables are boarding limiting and stop-skipping strategies and the objective is the maximal passenger profit. And a passenger original station choice model based on utility theory is built to modify the inbound passenger distribution among stations. Algorithm of metro passenger flow control scheme is designed, where two key technologies of stopping-station choice and headway adjustment are given and boarding limiting and train stopping-station scheme are optimized. Finally, a real case of Beijing metro is taken for example to verify validity. The results show that in the three scenarios with different ratios of normal trains to stop-skipping trains, the total limited passenger volume is the smallest and the systematic profit is the largest in scenario 3.