Response of railway track system on poroelastic half-space soil medium subjected to a moving train load

AbstractBased on the dynamic poroelastic theory of Biot, dynamic responses of a track system and poroelastic half-space soil medium subjected to moving train passages are investigated by the substructure method. The whole system is divided into two separately formulated substructures, the track and the ground, and the rail is described by introducing the Green function for an infinitely long Euler beam subjected to the action of moving axle loads of the train and the reactions of the sleeper. Sleepers are represented by a continuous mass and the effect of the ballast is considered by introducing the Cosserat model for granular medium. Using the double Fourier transform, the governing equations of motion are then solved analytically in the frequency-wave-number domain. The time domain responses are evaluated by the inverse Fourier transform computation for a certain train speed. Computed results show that the shape of the rail displacements of the elastic and poroelastic soil medium are in good agreement with each other of the low train velocity, but the result of the poroelastic soil medium is significantly different to that of the elastic soil medium for the high train velocity which is higher than Rayleigh-wave speed in the soil. The influence of the soil intrinsic permeability on soil responses is discussed with great care in both time domain and frequency domain. The dynamic responses of the soil medium are considerably affected by the fluid phase as well as the load velocity

Coordinating Supply Chains with a Credit Mechanism

This paper studies the supply chain coordination with a trade credit under symmetric and asymmetric information, where the retailer has an individual profit target from the business and the vendor is the decision-maker of the supply chain. We propose a coordination mechanism through credit contracts and show that a win-win outcome is achieved by redistributing the cost savings from coordination mechanism under certain constraints. Numerical examples are given to illustrate our results

Characteristics of Braced Excavation under Asymmetrical Loads

Numerous excavation practices have shown that large discrepancies exist between field monitoring data and calculated results when the conventional symmetry-plane method (with half-width) is used to design the retaining structure under asymmetrical loads. To examine the characteristics of a retaining structure under asymmetrical loads, we use the finite element method (FEM) to simulate the excavation process under four different groups of asymmetrical loads and create an integrated model to tackle this problem. The effects of strut stiffness and wall length are also investigated. The results of numerical analysis clearly imply that the deformation and bending moment of diaphragm walls are distinct on different sides, indicating the need for different rebar arrangements when the excavation is subjected to asymmetrical loads. This study provides a practical approach to designing excavations under asymmetrical loads. We analyze and compare the monitoring and calculation data at different excavation stages and find some general trends. Several guidelines on excavation design under asymmetrical loads are drawn

Interpretable and Efficient Beamforming-Based Deep Learning for Single Snapshot DOA Estimation

We introduce an interpretable deep learning approach for direction of arrival (DOA) estimation with a single snapshot. Classical subspace-based methods like MUSIC and ESPRIT use spatial smoothing on uniform linear arrays for single snapshot DOA estimation but face drawbacks in reduced array aperture and inapplicability to sparse arrays. Single-snapshot methods such as compressive sensing and iterative adaptation approach (IAA) encounter challenges with high computational costs and slow convergence, hampering real-time use. Recent deep learning DOA methods offer promising accuracy and speed. However, the practical deployment of deep networks is hindered by their black-box nature. To address this, we propose a deep-MPDR network translating minimum power distortionless response (MPDR)-type beamformer into deep learning, enhancing generalization and efficiency. Comprehensive experiments conducted using both simulated and real-world datasets substantiate its dominance in terms of inference time and accuracy in comparison to conventional methods. Moreover, it excels in terms of efficiency, generalizability, and interpretability when contrasted with other deep learning DOA estimation networks.Comment: 10 pages, 10 figure

Convergence of regional economic cycles in Turkey

Dissimilar economic fluctuations and asymmetric shocks across the regions of a country might create severe policy distortions that, under these circumstances, aggregate policy interventions (such as taxation and interest rates), are likely to be sub-optimal for at least a fraction of the regions. For instance, monetary policy can hardly satisfy the needs of all regions when some of the regions are experiencing a boom while others are in a recession phase. For these reasons, similarity of regional business cycles and their convergence are highly desirable from a policy viewpoint. The aim of this paper is, therefore, to provide empirical evidence and policy implications in that context. In particular, I analyze business cycle correlations across Turkish provinces and the tendency of these cycles to converge over the period of analysis between 1975-2000 and 2004-2008 (for Nomenclature of Territorial Units for Statistics [NUTS]-2 regions). I find that regional business cycle asymmetries have tended to decrease in recent decades. This result, although it seems to provide evidence in favor of rising correlations, shows that the convergence process is rather slow and there still exist asymmetries across the regional business cycles

Two-stage quadratic games under uncertainty and their solution by progressive hedging algorithms

A model of a two-stage N-person noncooperative game under uncertainty is studied, in which at the first stage each player solves a quadratic program parameterized by other players’ decisions and then at the second stage the player solves a recourse quadratic program parameterized by the realization of a random vector, the second-stage decisions of other players, and the first-stage decisions of all players. The problem of finding a Nash equilibrium of this game is shown to be equivalent to a stochastic linear complementarity problem. A linearly convergent progressive hedging algorithm is proposed for finding a Nash equilibrium if the resulting complementarity problem is monotone. For the nonmonotone case, it is shown that, as long as the complementarity problem satisfies an additional elicitability condition, the progressive hedging algorithm can be modified to find a local Nash equilibrium at a linear rate. The elicitability condition is reminiscent of the sufficient second-order optimality condition in nonlinear programming. Various numerical experiments indicate that the progressive hedging algorithms are efficient for mid-sized problems. In particular, the numerical results include a comparison with the best response method that is commonly adopted in the literature

Consolidation considering clogging

In land reclamation projects, the vacuum preloading method has been widely used to strengthen dredged fills by removing water. However, during the improvement process, clogging inevitably occurs in the drains and soils, hindering water drainage and causing inhomogeneous consolidation results. Therefore, it is essential to evaluate the effect of clogging on the consolidation behavior of dredged slurry at different radii. In this study, analytical solutions are derived under an uneven strain assumption to calculate the consolidation in the clogging zone and the normal zone, with time-dependent discharge capacity and clogging in the soil considered. Results calculated by the proposed solutions indicated that the clogging effect slows down the development of consolidation, reduces the final consolidation degree, and increases the difference between consolidations at different radii. It is found that the influence of the clogging effect's varies with the speed of the discharge capacity decay, the value of the initial discharge capacity of the drain, the permeability, and the radius of the clogging zone. Finally, a practical application of the proposed solution is discussed, and the proposed solution is suggested for the calculation of consolidation when treating high-water-content slurry