# Xu Guo

## Contact Details

NameXu Guo |
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## Pubs By Year |
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## Pub CategoriesStatistics - Methodology (5) Physics - Materials Science (3) Mathematics - Numerical Analysis (1) Computer Science - Distributed; Parallel; and Cluster Computing (1) Computer Science - Numerical Analysis (1) Physics - Chemical Physics (1) Physics - Soft Condensed Matter (1) Physics - Atomic and Molecular Clusters (1) Physics - Computational Physics (1) Computer Science - Computational Engineering; Finance; and Science (1) Physics - Other (1) Physics - Instrumentation and Detectors (1) High Energy Physics - Phenomenology (1) High Energy Physics - Experiment (1) Nuclear Theory (1) High Energy Physics - Lattice (1) Physics - Optics (1) |

## Publications Authored By Xu Guo

The fast detection of terahertz radiation is of great importance for various applications such as fast imaging, high speed communications, and spectroscopy. Most commercial products capable of sensitively responding the terahertz radiation are thermal detectors, i.e. Read More

One of the challenging issues in additive manufacturing (AM) oriented topology optimization is how to design structures that are self-supportive in a manufacture process without introducing additional supporting materials. In the present contribution, it is intended to resolve this problem under an explicit topology optimization framework where optimal structural topology can be found by optimizing a set of explicit geometry parameters. Two solution approaches established based on the Moving Morphable Components (MMC) and Moving Morphable Voids (MMV) frameworks, respectively, are proposed and some theoretical issues associated with AM oriented topology optimization are also analyzed. Read More

Three dimensional (3D) topology optimization problems always involve huge numbers of Degrees of Freedom (DOFs) in finite element analysis (FEA) and design variables in numerical optimization, respectively. This will inevitably lead to large computational efforts in the solution process. In the present paper, an efficient and explicit topology optimization approach which can reduce not only the number of design variables but also the number of degrees of freedom in FEA is proposed based on the Moving Morphable Voids (MMVs) solution framework. Read More

Residual marked empirical process-based tests are commonly used in regression models. However, they suffer from data sparseness in high-dimensional space when there are many covariates. This paper has three purposes. Read More

Heteroscedasticity testing is of importance in regression analysis. Existing local smoothing tests suffer severely from curse of dimensionality even when the number of covariates is moderate because of use of nonparametric estimation. In this paper, a dimension reduction-based model adaptive test is proposed which behaves like a local smoothing test as if the number of covariates were equal to the number of their linear combinations in the mean regression function, in particular, equal to 1 when the mean function contains a single index. Read More

Nonparametric generalized likelihood ratio test is popularly used for model checking for regressions. However, there are two issues that may be the barriers for its powerfulness. First, the bias term in its liming null distribution causes the test not to well control type I error and thus Monte Carlo approximation for critical value determination is required. Read More

We study the $\eta$-$\eta'$ mixing up to next-to-next-to-leading-order in $U(3)$ chiral perturbation theory in the light of recent lattice simulations and phenomenological inputs. A general treatment for the $\eta$-$\eta'$ mixing at higher orders, with the higher-derivative, kinematic and mass mixing terms, is addressed. The connections between the four mixing parameters in the two-mixing-angle scheme and the low energy constants in the $U(3)$ chiral effective theory are provided both for the singlet-octet and the quark-flavor bases. Read More

Local smoothing testing that is based on multivariate nonparametric regression estimation is one of the main model checking methodologies in the literature. However, relevant tests suffer from the typical curse of dimensionality resulting in slow convergence rates to their limits under the null hypotheses and less deviation from the null under alternatives. This problem leads tests to not well maintain the significance level and to be less sensitive to alternatives. Read More

In the present work, a new computational framework for structural topology optimization based on the concept of moving deformable components is proposed. Compared with the traditional pixel or node point-based solution framework, the proposed solution paradigm can incorporate more geometry and mechanical information into topology optimization directly and therefore render the solution process more flexible. It also has the great potential to reduce the computational burden associated with topology optimization substantially. Read More

**Category:**Statistics - Methodology

A novel general framework is proposed in this paper for dimension reduction in regression to fill the gap between linear and fully nonlinear dimension reduction. The main idea is to transform first each of the raw predictors monotonically, and then search for a low-dimensional projection in the space defined by the transformed variables. Both user-specified and data-driven transformations are suggested. Read More

Many problems in geophysical and atmospheric modelling require the fast solution of elliptic partial differential equations (PDEs) in "flat" three dimensional geometries. In particular, an anisotropic elliptic PDE for the pressure correction has to be solved at every time step in the dynamical core of many numerical weather prediction models, and equations of a very similar structure arise in global ocean models, subsurface flow simulations and gas and oil reservoir modelling. The elliptic solve is often the bottleneck of the forecast, and an algorithmically optimal method has to be used and implemented efficiently. Read More

We show that electrodynamic dipolar interactions, responsible for long-range fluctuations in matter, play a significant role in the stability of molecular crystals. Density functional theory calculations with van der Waals interactions determined from a semilocal "atom-in-a-molecule" model result in a large overestimation of the dielectric constants and sublimation enthalpies for polyacene crystals from naphthalene to pentacene, whereas an accurate treatment of non-local electrodynamic response leads to an agreement with the measured values for both quantities. Our findings suggest that collective response effects play a substantial role not only for optical excitations, but also for cohesive properties of non-covalently bound molecular crystals. Read More

In the present paper, a temperature-dependent meshless numerical framework based on the thermo-related quasi-continuum constitutive model is developed for predicting the thermal mechanical properties of single-walled carbon nanotubes (SWCNTs) at finite temperature. The extended thermal-related higher order Cauchy-Born (THCB) rule included second order deformation gradient relates the deformation of bond vectors of the atomic system and that of the continuous medium, which can capture the curvature effect of carbon nanotubes (CNTs) conveniently. Helmholtz free energy is employed to allow for the thermal effect of SWCNTs. Read More

In this paper, adhesive contact of a rigid cylinder on an elastic power-law graded half-space is studied analytically with the theory of weakly singular integral equation and orthogonal polynomial method. Emphasis is placed on the coupling effect between tangential and normal directions which was often neglected in previous works. Our analysis shows that the coupling effect tends to minimize the contact area in the compressive regime. Read More