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Dynamic analysis of high-speed train–track–bridge (TTB) system presents engineering challenges, particularly under complex conditions like track irregularity and crosswinds. Achieving a balance between computational efficiency and accuracy using the traditional substructure method, i.e. modeling the train and track–bridge separately and possibly performing iterations between them, can be difficult. In this paper, a practical unified three-dimensional (3D) TTB model is presented by using two coordinate systems: a stationary system for the track–bridge, and a moving system for the high-speed train. A wheel–rail interaction (WRI) element model is further extended such that the wheel and rail nodes in WRI element belong to moving and stationary systems, respectively, so as to make the train and track–bridge models consistently combined into one unified model. The unified modeling method simplifies computations and improves efficiency and stability. The modeling method has been implemented into an open source finite element platform, i.e. OpenSees, and applied for dynamic response analysis of a train traveling at 50m/s over a seven-span simply supported bridge. Running safety assessments are performed using three criteria, i.e. the Nadal criterion, Prud’homme criterion and unloading criterion, considering track irregularities and crosswind loads. The analysis results provide practically useful references for engineering.

Gravitational and electroweak interactions can be unified in analogy with the unification in the Weinberg–Salam theory. The Yang–Mills framework is generalized to include spacetime translational group T(4), whose generators T_μ ( = ∂/∂x^μ) do not have constant matrix representations. By gauging T(4) × SU(2) × U(1) in flat spacetime, we have a new tensor field ϕ_μν which universally couples to all particles and anti-particles with the same constant g, which has the dimension of length. In this unified model, the T(4) gauge symmetry dictates that all wave equations of fermions, massive bosons and the photon in flat spacetime reduce to a Hamilton–Jacobi equation with the same "effective Riemann metric tensor" in the geometric-optics limit. Consequently, the results are consistent with experiments. We demonstrated that the T(4) gravitational gauge field can be quantized in inertial frames.

In this paper, a unified model is presented for two-lane lattice traffic flow, with comparing different effects in the various lattice hydrodynamic models. Results of linear and nonlinear analysis show that multiple density difference effect (MDDE) is the strongest to enlarge the stable region in two-lane systems. Followed by density difference effect (DDE), multiple flux difference effect (MFDE), and finally flux difference effect (FDE). But when density is around 0.25, MFDE is better to enlarge the stable region than DDE. The reason is that a small flow-rate value might correspond to either a light traffic or a heavy traffic. Also energy consumption and traffic emissions are analyzed and shown to be the same marshaling sequence as linear and nonlinear analysis results. Numerical simulations validate theoretical analysis. And this is consistent with the realistic.

The two prevalent s-domain models for current-mode control, the continuous-time model and the unified model, exhibit noticeable differences in their small-signal predictions and therefore have become the subject of comparisons and clarifications. The current letter presents an alternative way of deriving the unified model, thereby providing an additional guide for assessing the validity of the unified model. This letter also presents experimental data that support the accuracy of the unified model.

Due to the significant challenges in the measurements, evaluation of permeability coefficient for unsaturated soil is of immense importance for investigating the seepage and hydro-mechanical coupling problems of unsaturated soil. However, the predictions of existing typical models reveal significance divergence for permeability coefficient of unsaturated soils even under identical conditions. In particular, the existing models are greatly restricted in their practical application due to their complexity in the form of integral expressions that require significant computational effort. Here, a simplified unified model is presented to estimate the relative permeability coefficient. First, a fractal-form of soil–water characteristic curve (SWCC) is derived from fractal theory. Then, on the basis of the proposed SWCC models, the classical models (i.e. Childs and Collis-George (CCG) model, Burdine model, Mualem model and Tao and Kong model, respectively) for evaluating the permeability coefficient of unsaturated soil are converted to be presented in fractal forms. It is interestingly found that the fractal forms of these models are enormously similar. Based on these observations, a simplified unified fractal model for the relative permeability coefficient of unsaturated soil is proposed, where only two parameters (i.e. fractal dimension and air-entry value) are included, thereby significantly reducing the computational efforts. The detailed procedure for determining model parameters is elaborated. The accuracy of this model is verified by comparing its predictions with the experimental data for over 12 types of unsaturated soils. The results highlight that, compared with existing models, the proposed model would be much more efficiently used for estimating the relative permeability coefficient of unsaturated soils, thereby facilitating its application for investigating the associated seepage and hydro-mechanical coupling problems in practice.

The paper surveys almost two decades of progress by me and colleagues in three psychometric research areas involving the probability modeling and statistical analysis of standardized ability test data: nonparametric multidimensional latent ability structure modeling and assessment, test fairness modeling and assessment, and modeling and assessment of skills diagnosis via educational testing. In the process, it is suggested that the unidimensional scoring testing paradigm that has driven standardized ability testing research for over half a century is giving way to a new multidimensional latent ability modeling and multiple scoring paradigm that in particular explains and allows the effective detection of test bias and embraces skills-level formative assessment, opening up a plethora of challenging, exciting, and societally important research problems for psychometricians. It is hoped that this light-stepping history will interest probabilists and statisticians in exploring the field of psychometrics.

Informally, test bias occurs when an examinee is under or over evaluated by his test score in terms of the purpose of the test. Also informally, skills diagnosis refers to evaluating examinee levels of mastery (usually done dichotomously as master versus nonmaster of each skill) on a moderate number of carefully selected skills for which having student skills profiles can greatly help individual student learning and classroom level.

My strategy, strongly influenced by his probabilistic background, for producing interesting and effective psychometric research is to choose psychometric research questions from practical challenges facing educational testing. Then, I and colleagues bring to bear sophisticated probability modeling and modern statistical thought to solve these questions, making effectiveness of the resulting research in meeting the educational testing challenges the ultimate criterion for judging its worth.

It is somebody's ancient proverb that the acorn sometimes falls far from the oak tree. Y. S. Chow taught me the tools of probability limit theorem research, taught me to approach research with enthusiasm and tenacity, and provided a very supportive environment for me and his other graduate students. Although psychometrics/educational measurement is far from the probabilistic oak tree, whatever success I've had as a psychometrician has been strongly influenced by the supportive, demanding, and creative environment Y. S. creates for his students. By now I have had many Ph.D. students in psychometrics: it was the just described model of Y. S.'s for mentoring Ph.D. students that I followed with all of them.