Random vibration analysis for train–track interaction from the aspect of uncertainty quantification

This work is devoted to constructing a stochastic analysis model for train–track​ interaction. The fundamentals of the modelling framework in the establishment of the dynamic model, simulation of system uncertainties and randomness propagation process have been properly illustrated and unified in detail. For modelling train–track interaction, a matrix representation method is developed to depict the displacement compatibility and force equilibrium between the train and tracks. This dynamic model possesses advantages in computational stability and accuracy. Using uncertainty quantification approaches, the randomness of system geometries and longitudinal inhomogeneity of system properties can be simulated properly. Finally, the probabilistic transmission between the system inputs and response outputs are investigated from physical concepts, and a family of probability density evolution methods is introduced. Following the fundamental framework of train–track stochastic analysis, numerical examples are presented in detail to show the efficiency and accurateness of the proposed model. Moreover, the applications and advancements of this model in reliability assessment, response and frequency analysis, derailment, etc., are illustrated.     

Development of a reduced-order model for large-scale Eulerian–Lagrangian simulations

Multiphase flows with solid particles are commonly encountered in various industries. The CFD–DEM method is extensively used to simulate their dynamical behavior. However, the application of the CFD–DEM method to simulate industrial-scale powder processes unavoidably leads to huge computational costs. With the aim of overcoming this issue, we propose a nonintrusive reduced-order model for Eulerian–Lagrangian simulations (ROM-EL) to efficiently reproduce gas–solid flow in fluidized beds. In the model, a Lanczos based proper orthogonal decomposition (LPOD) is newly employed to efficiently generate a set of POD bases. After the numerical snapshots are projected onto the reduced space spanned by the POD bases, a series of multidimensional functions of POD coefficients are constructed using a surrogate interpolation method. To demonstrate the effectiveness of this model, validation studies are performed based on the simulations of a fluidized bed. The macroscopic properties, such as the particle distribution, bed height, pressure drop, and distribution of bubble size, are shown to agree well in the CFD–DEM model and ROM-EL. Further, our proposed ROM-EL reduces the computational cost by several orders of magnitude compared with the CFD–DEM simulation. Accordingly, the ROM-EL could significantly contribute to the progress of modeling and simulation for industrial granular flows.     

On effects of track random irregularities on random vibrations of vehicle–track interactions

As the integrated reflection of track substructure deformations and the most important excitation for vehicle–track interactions, track irregularities show random nature, and generally being regarded as weak stationary random processes. To better expose the full statistical characteristics of track random irregularities on amplitude and wavelength, a time–frequency transform and probability theory based model is developed to simulate representative and realistic track irregularity sets by combining with random sampling methods. Moreover, a three-dimensional (3-D) vehicle–track coupled model is established by finite element method and dynamic equilibrium equations, where the nonlinearity of wheel/rail interaction is considered. Finally, a probability density evolution method (PDEM) is introduced to solve the probabilistic transmission issues between track irregularity sets and dynamic responses of vehicle–track coupled systems. There is a clear demonstration that the results derived by proposed methods are comparable to the experimental measurements. Through effectively applying the above methodologies, the probabilistic and random characteristics of vehicle–track interaction can be properly revealed.     

Reconstruction model of vehicle impact speed in pedestrian–vehicle accident

Reconstruction of pedestrian–vehicle accident is a worldwide problem. Numerous previous studies have been carried out on accidents with vehicular skid marks or definite pedestrian throw distances. However, little could be done if marks or throw distances cannot be obtained in accident reconstruction. This paper first describes the physical model of dynamic process of pedestrian head impact on windshield glazing. Some simplifications are made to obtain a better and more practical model, including discussing the support boundary conditions. Firstly, the paper modeled the relations between pedestrian impact speed and deflection of windshield glazing based on the impact dynamics and thin plate theory. Later, the relations of vehicle impact speed and deflection are discussed. Therefore, a model of vehicle impact speed versus deflection of windshield glazing is developed. The model is then verified by ten real-world accident cases to demonstrate its accuracy and reliability. This model provides investigators a new method to reconstruct pedestrian–vehicle accidents.     

Development of a multidisciplinary–multiresponse robust design optimization model

Robust design is an efficient process improvement methodology that combines experimentation with optimization to create systems that are tolerant to uncontrollable variation. Most traditional robust design models, however, consider only a single quality characteristic, yet customers judge products simultaneously on a variety of scales. Additionally, it is often the case that these quality characteristics are not of the same type. To addresses these issues, a new robust design optimization model is proposed to solve design problems involving multiple responses of several different types. In this new approach, noise factors are incorporated into the robust design model using a combined array design, and the results of the experiment are optimized using a new approach that is formulated as a nonlinear goal programming problem. The results obtained from the proposed methodology are compared with those of other robust design methods in order to examine the trade-offs between meeting the objectives associated with different optimization approaches.     

Space–time computational analysis of bio-inspired flapping-wing aerodynamics of a micro aerial vehicle

We present a detailed computational analysis of bio-inspired flapping-wing aerodynamics of a micro aerial vehicle (MAV). The computational techniques used include the Deforming-Spatial-Domain/Stabilized Space?CTime (DSD/SST) formulation, which serves as the core computational technique. The DSD/SST formulation is a moving-mesh technique, and in the computations reported here we use the space?Ctime version of the residual-based variational multiscale (VMS) method, which is called ??DSD/ SST-VMST.?? The motion and deformation of the wings are based on data extracted from the high-speed, multi-camera video recordings of a locust in a wind tunnel. A set of special space?Ctime techniques are also used in the computations in conjunction with the DSD/SST method. The special techniques are based on using, in the space?Ctime flow computations, NURBS basis functions for the temporal representation of the motion and deformation of the wings and for the mesh moving and remeshing. The computational analysis starts with the computation of the base case, and includes computations with increased temporal and spatial resolutions compared to the base case. In increasing the temporal resolution, we separately test increasing the temporal order, the number of temporal subdivisions, and the frequency of remeshing. In terms of the spatial resolution, we separately test increasing the wing-mesh refinement in the normal and tangential directions and changing the way node connectivities are handled at the wingtips. The computational analysis also includes using different combinations of wing configurations for the MAV and investigating the beneficial and disruptive interactions between the wings and the role of wing camber and twist.     

Dynamic analysis of bridge–vehicle system with uncertainties based on the finite element model

A new method of dynamic analysis on the bridge–vehicle interaction problem considering uncertainties is proposed in this paper. The bridge is modeled as a simply supported Euler–Bernoulli beam with Gaussian random elastic modulus and mass density of material with moving forces on top. These forces are time varying with a coefficient of variation at each time instance and they are considered as Gaussian random processes. The mathematical model of the bridge–vehicle system is established based on the finite element model in which the Gaussian random processes are represented by the Karhunen–Loéve expansion and the equations will be solved by the Newmark  -β$\beta$ method. The proposed method is compared with the Monte Carlo method in numerical simulations with good agreements for cases with different vehicle speed and level of uncertainties in the excitation and system parameters. The mean value and variance of the structural responses are found to be very accurate even with large uncertainties in the excitation forces. The proposed method is also found to have superior performance in the computational efficiency compared with the Monte Carlo method.     

Detailed analysis of particle–substrate interaction based on a centrifugal method

The interaction between particles and inclined substrates in a centrifuge was investigated theoretically and experimentally. First, the balance of the force acting on a particle adhering to the substrate, with an inclination angle from 0 to 90° to the horizontal, was formulated separately in the normal and tangential directions. The adhesion force was then derived based on the point-mass model as a function of the angular velocity. Next, the balance of the moments of the forces acting on a particle adhering to the substrate was formulated; theoretical equations for the adhesion force and the effective contact radius were then derived from the angular velocities, obtained at any two inclination angles, based on the rigid-body model. Finally, the removal fraction curves of spherical/nonspherical particles with median diameters of less than 10 µm were experimentally obtained by increasing the angular velocity at each inclination angle. The experimentally obtained angular velocities were substituted into the theoretical equations to compare the point-mass and rigid-body models. The effects of the particle shape on the adhesion force and effective contact radius and that of the inclination angle on the removal fraction curves based on the theoretical equation were also investigated.     

Multidimensional parallelepiped model—a new type of non-probabilistic convex model for structural uncertainty analysis

Non-probabilistic convex models need to be provided only the changing boundary of parameters rather than their exact probability distributions; thus, such models can be applied to uncertainty analysis of complex structures when experimental information is lacking. The interval and the ellipsoidal models are the two most commonly used modeling methods in the field of non-probabilistic convex modeling. However, the former can only deal with independent variables, while the latter can only deal with dependent variables. This paper presents a more general non-probabilistic convex model, the multidimensional parallelepiped model. This model can include the independent and dependent uncertain variables in a unified framework and can effectively deal with complex ‘multi-source uncertainty’ problems in which dependent variables and independent variables coexist. For any two parameters, the concepts of the correlation angle and the correlation coefficient are defined. Through the marginal intervals of all the parameters and also their correlation coefficients, a multidimensional parallelepiped can easily be built as the uncertainty domain for parameters. Through the introduction of affine coordinates, the parallelepiped model in the original parameter space is converted to an interval model in the affine space, thus greatly facilitating subsequent structural uncertainty analysis. The parallelepiped model is applied to structural uncertainty propagation analysis, and the response interval of the structure is obtained in the case of uncertain initial parameters. Finally, the method described in this paper was applied to several numerical examples. Copyright © 2015 John Wiley & Sons, Ltd.     

Development of a procedure for spherical alginate–boehmite particle preparation

Herein we describe a versatile new strategy for producing spherical solid particles with 2 mm in size using integrated gelling process. The method involves the formation of spherical droplets by using a peristatic pump device and shaping the droplets in a liquid calcium chloride solution. The shape and size of these calcium alginate macroparticles depend strongly on the calcium solution concentration. The shaping mechanism of the macroparticles and the impact of the experimental conditions on particle shape and size are investigated. This method has the following features: (1) A new level of control over the shapes of the particles is offered. (2) The procedure can be scaled up to produce large numbers of particles. (3) The final porous structure of the developed particle can be designed for a specific application (adsorption, catalysis).     

Theoretical study of high-performance frontal analysis: a chromatographic method for determination of drug-protein interaction

High-performance frontal analysis (HPFA), a chromatographic method to determine unbound drug concentration in drug-protein binding equilibrium, has been considered on the basis of a theoretical plate model, where a rapid equilibrium of drug-protein binding in the mobile phase in the interstices of packing materials and a chromatographic partition equilibrium of the drug were taken into account simultaneously. When a certain excess volume of drug-protein mixed solution is injected directly into a HPFA column packed with a restricted-access type phase that excludes protein but retains drug in the micropores, the drug is eluted as a zonal peak with a plateau region. The elution profile can be well simulated by the mass balance equation derived according to a relatively simple plate theory concept, which confirms that the drug concentration in the plateau range agrees with the unbound drug concentration in the sample solution. The model was applied to the theoretical and systematic investigation of the dependence of the HPFA profile on several chromatographic conditions and the properties of the sample solution, such as injection volume of sample solution, drug and protein concentrations in sample solution, capacity factor of the drug, theoretical plate number, and binding parameters. The smaller capacity factor and the higher column efficiency lead to the larger plateau volume. The lower drug concentration, the higher protein concentration, and the stronger binding constant, which give the lower unbound drug fraction, lead to the larger plateau volume and allow frontal analysis with a smaller sample size.     

Study of validity of the single-diode model for solar cells by I–V curves parameters extraction using a simple numerical method

The I–V measurement of solar cells is one of the most employed electrical characterization techniques in the photovoltaics research field due to the valuable information one can obtain from such a curve. Parameters like Voc, Isc and the maximum power can be easily observed at a glance. Furthermore, additional information can be extracted by a more exhaustive analysis involving the equivalent electrical circuit of a solar cell which is based on ideal electrical components with a well-defined behavior. This equivalent circuit is typically assumed to be formed by a current source in parallel with a single diode and a shunt resistor, connected to a series resistor. However, this model does not take into account the separate contributions of the different carrier transport mechanisms in solar cells; for example, carrier diffusion and recombination-generation in the depletion region. Therefore, the single diode model may not be suitable in many practical cases. In this work, a simple numerical method was developed to extract the parameters for both single diode and double diode models from experimental I–V curves of solar cells. The developed numerical algorithm was applied to extract the parameters for a published benchmark solar cell which has been used for testing this kind of algorithms. The extracted parameters using our simple method are comparable with other more sophisticated and computer power demanding algorithms. Thereafter, we applied the developed algorithm to extract the single-diode parameters from simulated “experimental” I–V curves, where two carrier transport mechanisms are present, trying to understand under what conditions the single diode approximation would provide meaningful parameters for such experimental curves. It is shown that the extracted parameters can vary strongly, particularly for the dark saturation current and ideality factor, without much variation of the root mean square error between the experimental data and the model, causing these values to be unreliable and its physical interpretation misleading. We show that the same algorithm can be applied to a double diode (two exponentials) model providing physically meaningful parameters without much computing power requirements. In summary, there is no further justification for using a single diode model to interpret the experimental I–V curves of real solar cells.     

Development of structure and effect of processing parameters on Strength–structure relationships for two ferritic stainless steels

Abstract

The development of substructure as material passes through the roll gap has been examined for a ferritie stainless steel and it is shown that the final structure evolves close to the roll gap exit. Temperature variations as the material was rolled were monitored and the subsequent effect on substructure investigated. The variation of substructure with processing for two ferritic steels is discussed and the effect of this variation on room temperature properties is presented. It is shown that the strength–structure relationship is highly dependent upon retained martensite which degrades the tensile strength.

MST/380     

Dynamic analysis of dam–reservoir-foundation interaction in time domain

In this paper, a time domain dynamic analysis of the dam–reservoir-foundation interaction problem is developed by coupling the dual reciprocity boundary element method (DRBEM) for the infinite reservoir and foundation domain and the finite element method for the finite dam domain. An efficient coupling procedure is formulated by using the substructuring method. Sharans boundary condition at the far end of the infinite fluid domain is implemented. To verify the proposed scheme, numerical examples are carried out and compared with available exact solutions and finite–finite element coupling results for the problem of the dam–reservoir interaction. Finally, a complete dam–reservoir-foundation interaction problem is solved and its solution is compared with previously published results.The author is thankful to the anonymous reviewer of this paper for his suggestions and comments, which improved considerably the present paper.     

A stochastic damage model for evaluating the internal deterioration of concrete due to freeze–thaw action

This paper presents a stochastic damage model for evaluating the internal deterioration of concrete due to freeze–thaw action, which involves great uncertainty and randomness. In this model, the structural element of concrete is discretized into infinite microelements, whose lifetimes are assumed to be independent random variables. Then expressions for the mean and variance of the damage of concrete are analytically derived. To calibrate the model parameters, a series of freeze–thaw tests in water on non-air-entrained concrete were conducted and back-calculation analyses were performed on the test results of dynamic modulus. The reliability of the proposed stochastic damage model is further validated through comparisons with the results of 80 other existing test specimens. The present model offers a theoretical basis for exploring the statistical aspect of concrete behavior during freeze–thaw.     

Three-dimensional hybrid enterprise input–output model for material metabolism analysis: a case study of coal mines in China

China’s energy use has been, and will be for a long time, dominated by coal. The literature has studied little on the material metabolism of coal mines, especially for China, from a systems perspective. The aim of this study is to develop a quantitative framework to investigate the internal material metabolism of coal mining enterprises in China. This framework, three-dimensional hybrid enterprise input–output (3D-HEIO) model, combines scenario analysis and the enterprise input–output model. To illustrate the application of this framework, the material metabolism of Wang Coal-mine (WCM) in Shanxi, China is analyzed. Results show that the WCM has the annual potential to recover 10,862 tonnes of coal, reduce 404,515 tonnes of water consumption, 13 million kWh of electricity consumption, 70 tonnes of coagulant agents, 90,000 pieces of paper, and 146 tonnes of sulfur dioxide and dust emissions, and reuse 100,000 tonnes of coal gangue. The potential of economic profit can be 14.24 million yuan per year.     

Development of ADEM–CFD model for analyzing dynamic and breakage behavior of aggregates in wet ball milling

A new simulation method was developed for analyzing the grinding mechanisms of aggregates in wet ball milling. The calculation of the following five behaviors is needed in this case: dynamics and breakage behaviors of aggregates, collisions of aggregates, a motion of fluid including aggregates, ball-fluid interaction forces and aggregate-fluid interaction forces. The dynamic and breakage behaviors of aggregates were calculated by advanced discrete element method (ADEM). The collisions of aggregates were represented by DEM. The motion of fluid including aggregates was solved by spatially-averaged equations of the fluid with finite difference method (FDM). The ball-fluid interaction forces were calculated by immersed boundary method (IBM). The model for the aggregate-fluid interaction forces has not been established, so that a new simulation model for estimating them was developed and named ADEM-computational fluid dynamics (ADEM-CFD) model. The ADEM-CFD model was verified by comparing the fluid drag coefficients obtained by White’s equation. The new simulation method considering the five behaviors was validated by comparing with an experiment about dynamic and breakage behaviors of aggregates around a falling ball in liquid. It is found that the new simulation method proposed could analyze the dynamic and breakage behaviors of aggregates in wet ball milling.     

Development of a nanogel formulation for transdermal delivery of tenoxicam: a pharmacokinetic–pharmacodynamic modeling approach for quantitative prediction of skin absorption

This study investigates potentials of solid lipid nanoparticles (SLN)-based gel for transdermal delivery of tenoxicam (TNX) and describes a pharmacokinetic–pharmacodynamic (PK–PD) modeling approach for predicting concentration–time profile in skin. A 2³ factorial design was adopted to study the effect of formulation factors on SLN properties and determine the optimal formulation. SLN-gel tolerability was investigated using rabbit skin irritation test. Its anti-inflammatory activity was assessed by carrageenan-induced rat paw edema test. A published Hill model for in vitro inhibition of COX-2 enzyme was fitted to edema inhibition data. Concentration in skin was represented as a linear spline function and coefficients were estimated using non-linear regression. Uncertainty in predicted concentrations was assessed using Monte Carlo simulations. The optimized SLN was spherical vesicles (58.1?±?3.1?nm) with adequate entrapment efficiency (69.6?±?2.6%). The SLN-gel formulation was well-tolerated. It increased TNX activity and skin level by 40?±?13.5, and 227?±?116%, respectively. Average C_max and AUC_0–24 predicted by the model were 2- and 3.6-folds higher than the corresponding values computed using in vitro permeability data. SLN-gel is a safe and efficient carrier for TNX across skin in the treatment of inflammatory disorders. PK–PD modeling is a promising approach for indirect quantitation of skin deposition from PD activity data.