Narrow Results

The traditional dynamic analysis method is less efficient in the global and local vibrations analysis of long-span bridge structures. Therefore, to meet the need for an efficient solution of the refined analysis model of the train–track–bridge coupled system (TTBCS), a new hybrid dynamic model of the TTBCS based on the transfer matrix method (TMM) is proposed in this paper. It can solve the local high-frequency vibration response of the track structure and the global and local vibrations responses of the bridge structure simultaneously, accurately, and efficiently. First, according to the periodic characteristics of track and bridge structure, the periodic repeating parts are divided into cellular structures. For the bridge subsystem, fine cells are established to achieve the accurate solution of local vibration, and the rest of the super element cells are established by model condensation technology, which can significantly reduce the number of cells and save the transmission time. The state vector transfer model of the track and bridge subsystem is established based on the TMM, and the coupling calculation is realized by combining rail bridge force. The train system adopts the model of 10degrees of freedom and realizes the coupling with the rail system through the wheel–rail interaction force. With the movement of train load, the track and bridge cells established by the hybrid dynamic model approach (HMA) dynamically update the arrangement information, which not only realizes the calculation of ultra-long track based on a fixed number of track cells, but also moves the fine cell models of bridge with the change of load position. These dynamic update measures reduce both the number of cells and transfer solutions, save the transfer time, and further improve the calculation efficiency. Taking CRH-2 EMU passing through a 3-span simply supported steel truss bridge as an example, the results and time-consuming of the direct stiffness method, TMM, and HMA are compared, and the accuracy and efficiency of the hybrid model are proved.

We present a highly efficient lattice Boltzmann (LB) kinetic model for thermal liquid–vapor system. Three key components are as below: (i) a discrete velocity model (DVM) by Kataoka et al. [Phys. Rev. E69, 035701(R) (2004)]; (ii) a forcing term I_i aiming to describe the interfacial stress and recover the van der Waals (VDW) equation of state (EOS) by Gonnella et al. [Phys. Rev. E76, 036703 (2007)] and (iii) a Windowed Fast Fourier Transform (WFFT) scheme and its inverse by our group [Phys. Rev. E84, 046715 (2011)] for solving the spatial derivatives, together with a second-order Runge–Kutta (RK) finite difference scheme for solving the temporal derivative in the LB equation. The model is verified and validated by well-known benchmark tests. The results recovered from the present model are well consistent with previous ones [Phys. Rev. E84, 046715 (2011)] or theoretical analysis. The usage of less discrete velocities, high-order RK algorithm and WFFT scheme with 16th-order in precision makes the model more efficient by about 10 times and more accurate than the original one.

We present efficient implementations of a number of operations for quantum computers. These include controlled phase adjustments of the amplitudes in a superposition, permutations, approximations of transformations and generalizations of the phase adjustments to block matrix transformations. These operations generalize those used in proposed quantum search algorithms.

High-fidelity beamline models typically involve particle-tracking and particle–matter interaction, which are intensive computationally demanding and time-consuming. This has led researchers to adopt data-driven surrogate models as an alternative to complex physics simulations. Training a data-driven model requires many labeled data, prompting researchers to simulate diverse beamline settings and obtain corresponding labels. However, the required dataset grows increasingly large as the number of adjustable parameters increases. Therefore, this study proposes a data-efficient surrogate modeling method that employs a student–teacher framework combined with active learning (AL) query strategies to minimize labeled samples while ensuring model accuracy. The proposed method is evaluated on the energy selection system (ESS) design of the Huazhong University of Science and Technology proton therapy facility (HUST-PTF). The results show that: (i) Training the surrogate model using 684 labeled samples selected via query strategy achieves a relative error below 5% for 90% of the samples in the test set. (ii) Compared to the beamline model built by Beam Delivery Simulation (BDSIM), the computational efficiency of the surrogate model is enhanced by a factor of $\mathcal{𝒪}(10^7)$.

Exclusion processes are hot study issues in statistical physics and corresponding complex systems. Among fruitful exclusion processes, totally asymmetric simple exclusion process (namely, TASEP) attracts much attention due to its insight physical mechanisms in understanding such nonequilibrium dynamical processes. However, interactions among isolated TASEP are the core of controlling the dynamics of multiple TASEPs that are composed of a certain amount of isolated one-dimensional TASEP. Different from previous researches, the interaction factor is focused on the critical characteristic parameter used to depict the interaction intensity of these components of TASEPs. In this paper, a much weaker constraint condition ${\prod }_{i=1}^K{\omega }_i^d={\prod }_{i=1}^K{\omega }_i^u$ is derived as the analytical expression of interaction factor. Self-propelled particles in the subsystem $i$ of multiple TASEPs can perform hopping forward at $p_i$, moving into the target site of the (i − 1)th TASEP channel at ${\omega }_i^u$ or updating into the (i + 1)th TASEP channel at ${\omega }_i^d$. The comparison of this proposed interaction factor and other previous factors is performed by investigating the computational efficiency of obtaining analytical solutions and simulation ones of order parameters of the proposed TASEP system. Obtained exact solutions are observed to match well with Monte Carlo simulations. This research attempts to have a more comprehensive interpretation of physical mechanisms in the impact of interaction factors on TASEPs, especially corresponding to stochastic dynamics of self-propelled particles in such complex statistical dynamical systems.

An explicit, computationally efficient, recursive formula is presented for computing the normal form and center manifold of general n-dimensional systems associated with Hopf bifurcation. Maple program is developed based on the analytical formulas, and shown to be computationally efficient, using two examples.

Traffic forecasting is an integral part of modern intelligent transportation systems. Although many techniques have been proposed in the literature to address the problem, most of them focus almost exclusively on forecasting accuracy and ignore other important aspects of the problem. In the paper at hand, a new method for both accurate and fast large-scale traffic forecasting, named “sparse feature regression”, is presented. Initially, a set of carefully selected features is extracted from the available traffic data. Then, some of the initial features are sparsified, namely they are transformed into sets of sparse features. Finally, a linear regression model is designed using the sparse feature set, which is trained by solving an optimization problem using a sparse approximate pseudoinverse as a preconditioner. We evaluated the proposed method by conducting experiments on two real-world traffic datasets, and the experimental results showed that the method presents the best balance between accuracy of predictions and time required for achieving them, in comparison with a set of benchmark models.

This paper develops optimal family of fourth-order iterative techniques in order to find a single root and to generalize them for simultaneous finding of all roots of polynomial equation. Convergence study reveals that for single root finding methods, its optimal convergence order is 4, while for simultaneous methods, it is 12. Computational cost and numerical illustrations demonstrate that the newly developed family of methods outperformed the previous methods available in the literature.

In this work, we construct a new family of inverse iterative numerical technique for extracting all roots of nonlinear equation simultaneously. Convergence analysis verifies that the proposed family of methods has local 10th-order convergence. Among the test models investigated are blood rheology, a fractional nonlinear equation model, fluid permeability in biogels, and beam localization models. In comparison to other methods, the family of inverse simultaneous iterative techniques gets initial estimations to exact roots within a given tolerance while using less function evaluations in each iterative step. Numerical results, basins of attraction for fractional nonlinear equation, residual graphs are presented in detail for the simultaneous iterative techniques. The newly developed simultaneous iterative techniques were thoroughly investigated and proven to be efficient, robust, and authentic in their domain.

This research paper introduces a novel fractional Caputo-type simultaneous method for finding all simple and multiple roots of polynomial equations. Without any additional polynomial and derivative evaluations using suitable correction, the order of convergence of the basic Aberth–Ehrlich simultaneous method has been increased from three to $\alpha +3$. In terms of accuracy, residual graph, computational efficiency and computation CPU time, the newly proposed families of simultaneous methods outperforms existing methods in numerical applications.

The calculation efficiency of the conventional single-domain acoustic BEM (SBEM) is important for analyzing large scaled or complicated acoustic cavity systems. Although the multi-domain BEM (MBEM) has been developed to deal with such complex shaped and large size acoustic systems effectively, it is generally known that the MBEM requires more computation time and computer memory space than the SBEM. However, if the proper division were applied on a single cavity, it is thought that the MBEM could be the better method than the SBEM in the viewpoint of accuracy and efficiency. This might be possible when one reminds the fact that the effort in the MBEM calculations also depends strongly on the shape of the total acoustic cavity. In this article, the general computational characteristics of the MBEM for analyzing the interior acoustic fields are investigated to provide a guideline in the division of a single cavity into several subdomains for having better computational performance than using the SBEM. A two-dimensional long duct comprised of a number of linear elements is taken as a demonstration example. It is clearly shown that the modification of MBEM model through the present guidelines achieves more accurate and efficient computation than using the SBEM.

The high frequency asymptotic formulas for the acoustic impedance modal coefficients of a clamped circular plate located at the boundary of the three-wall corner region have been obtained. The method of contour integral analysis, the series for the Bessel and Neumann functions and the stationary phase method have been used. Some sample modal coefficients of the acoustic resistance and reactance together with the absolute approximation error have been illustrated as the functions of a parameter proportional to the vibration frequency. The computational efficiency of the presented asymptotic formulas has been compared with the computational efficiency of the integral formulas. The cases, in which the asymptotic formulas allow to reduce the calculation time in comparison with the integral formulas, have been determined. The presented formulas can be used to decrease the computation time of the acoustics power radiated by a clamped circular plate located at the boundary of the three-wall corner region. Moreover, the sound pressure calculations can be performed much faster by using these formulas when the acoustic attenuation is included.

The sound radiation inside an acoustic canyon has been analyzed for a surface sound source located at the bottom. Based on rigorous mathematical manipulations, the formulas of a high computational efficiency describing the sound pressure and sound power have been obtained. They can be easily adapted to describe the sound radiation of an arbitrary system of sound sources. As an example of their application, the sound radiation of a piston has been investigated. The asymptotic formulas of the sound power modal coefficients have been obtained. They can be used to significantly improve the numerical calculation of the sound power.

A schema database functions as a repository for interconnected data points, facilitating comprehension of data structures by organizing information into tables with rows and columns. These databases utilize established connections to arrange data, with attribute values linking related tuples. This integrated approach to data management and distributed processing enables schema databases to maintain models even when the working set size surpasses available RAM. However, challenges such as data quality, storage, scarcity of data science professionals, data validation, and sourcing from diverse origins persist. Notably, while schema databases excel at reviewing transactions, they often fall short in updating them effectively. To address these issues, a Chimp-based radial basis neural model (CbRBNM) is employed. Initially, the Schemaless database was considered and integrated into the Python system. Subsequently, compression functions were applied to both schema and schema-less databases to optimize relational data size by eliminating redundant files. Performance validation involved calculating compression parameters, with the proposed method achieving memory usage of 383.37Mb, a computation time of 0.455s, a training time of 167.5ms, and a compression rate of 5.60%. Extensive testing demonstrates that CbRBNM yields a favorable compression ratio and enables direct searching on compressed data, thereby enhancing query performance.

A new family of time integration methods is formulated. The recommended technique is useful and robust for the loads with large variations and the systems with nonlinear damping behavior. It is also applicable for the structures with lots of degrees of freedom, and can handle general nonlinear dynamic systems. By comparing the presented scheme with the fourth-order Runge–Kutta and the Newmark algorithms, it is concluded that the new strategy is more stable. The authors’ formulations have good results on amplitude decay and dispersion error analyses. Moreover, the family orders of accuracy are $m+2$ and $m+3$ for even and odd values of $m$, respectively. Findings demonstrate the superiority of the new family compared to explicit and implicit methods and dissipative and non-dissipative algorithms.

Used extensively in structural dynamics analysis, the energy method is advantageous for transforming boundary value problems of differential equations into variational extremum problems. Recent applications include analyzing the wave and vibration characteristics of track structures. However, traditional energy methods for dynamic modeling and analysis of ballastless track structures require obtaining the global stiffness matrix and mass matrix of the entire coupled system, which decreases computational efficiency. The EM-CMS algorithm for frequency domain dynamic response analysis of ballastless track structures has been proposed to address this issue. The core of EM-CMS is the development of model reduction strategies within the framework of the energy method to reduce matrix dimensions and thereby improve computational efficiency. Specifically, the steel spring floating slab track is the focus of this research. Utilizing the energy functional variational method, the modal properties of the rail and floating slab structures are obtained, and truncation is performed. A reduced-order model for the steel spring floating slab track is established by considering the boundary conditions between the rail-floating slab and the floating slab foundation (connected through fastener springs and steel springs, respectively, and considering the springs’ elastic potential energy). Comparatively, the computational efficiency of EM-CMS is approximately ten times greater than that of the energy method. The method’s accuracy is also carefully validated against finite element simulations.

The complex damping model can only be used to calculate the steady-state responses, while the transient responses are divergent. Based on the complex damping model, the Hilbert transform is introduced to establish a hysteretic damping model, eliminating the divergence phenomenon. However, with the increase of the loss factor, the damped natural frequency also increases. To overcome this shortcoming, a frequency-independent damping model is proposed based on the hysteretic damping model. However, traditional time-domain methods are no longer applicable to frequency-independent damping models. Therefore, the transient response and steady-state response are separated, and the assumption of external excitation acceleration is introduced. Time-domain methods-based linear polynomial assumption, quadratic polynomial assumption and trigonometric function assumption are proposed, respectively. Numerical examples show that the time-domain methods based on linear polynomial assumption and quadratic polynomial assumption have high computational efficiency. But these two methods cannot take into account the vibration frequency of external excitation acceleration. Hence, the computational accuracy is low. Compared with them, the time-domain method based on trigonometric function assumption has the lowest computational efficiency and the highest computational accuracy.

This paper presents a thorough evaluation of a bistable system versus a matched filter in detecting bipolar pulse signals. The detectability of the bistable system can be optimized by adding noise, i.e. the stochastic resonance (SR) phenomenon. This SR effect is also demonstrated by approximate statistical detection theory of the bistable system and corresponding numerical simulations. Furthermore, the performance comparison results between the bistable system and the matched filter show that (a) the bistable system is more robust than the matched filter in detecting signals with disturbed pulse rates, and (b) the bistable system approaches the performance of the matched filter in detecting unknown arrival times of received signals, with an especially better computational efficiency. These significant results verify the potential applicability of the bistable system in signal detection field.

From some modifications of Chebyshev's method, we consider a uniparametric family of iterative methods that are more efficient than Newton's method, and we then construct two iterative methods in a similar way to the Secant method from Newton's method. These iterative methods do not use derivatives in their algorithms and one of them is more efficient than the Secant method, which is the classical method with this feature.

We present an extension of a well-known result of Traub to increase the R-order of convergence of one-point iterative methods by a simple modification of this type of methods. We consider the extension to one-point iterative methods with memory and present a particular case where Kurchatov's method is used. Moreover, we analyze the efficiency and the semilocal convergence of this method. Finally, two applications are presented, where differentiable and nondifferentiable equations are considered, that illustrate the above-mentioned.