The Experts below are selected from a list of 34902 Experts worldwide ranked by ideXlab platform

Xuesong Jin - One of the best experts on this subject based on the ideXlab platform.

  • analysis on thermal effect on high speed wheel rail adhesion under interfacial contamination using a three dimensional model with surface roughness
    Wear, 2016
    Co-Authors: Zefeng Wen, Bing Wu, Tao Wu, Xuesong Jin
    Abstract:

    Abstract A three-dimensional numerical model of wheel/rail in rolling contact is established to study the adhesion characteristics under interfacial contamination considering surface roughness at high speed. The thermal partial elastohydrodynamic lubrication (EHL) theory in elliptical contact is used in the model. The numerical model is successfully solved by applying the iterative algorithm between the pressure field and temperature field. Multilevel Method is used to solve modified Reynolds equation. Sweeping column Method is used to solve energy and heat conduction equations. The effects of train speed, surface roughness amplitudes, roughness orientation and axle load on the adhesion coefficient under interfacial contamination are numerically investigated. A typical creepage-traction curve under oil contamination is obtained at high speed by the present model. In addition, the effects of temperature and the elastic-plastic deformation behaviour of asperities on the adhesion coefficient are discussed in the paper. Furthermore, the effect of different interfacial contaminations on wheel/rail adhesion using the present model on the adhesion coefficient is investigated. In order to validate the present model, the numerical results are compared with the experimental results that were obtained by JD-2 high-speed wheel/rail rolling contact machine under water/oil contaminations.

  • Analysis on thermal effect on high-speed wheel/rail adhesion under interfacial contamination using a three-dimensional model with surface roughness
    Wear, 2016
    Co-Authors: Bing Wu, Zefeng Wen, Tao Wu, Xuesong Jin
    Abstract:

    A three-dimensional numerical model of wheel/rail in rolling contact is established to study the adhesion characteristics under interfacial contamination considering surface roughness at high speed. The thermal partial elastohydrodynamic lubrication (EHL) theory in elliptical contact is used in the model. The numerical model is successfully solved by applying the iterative algorithm between the pressure field and temperature field. Multilevel Method is used to solve modified Reynolds equation. Sweeping column Method is used to solve energy and heat conduction equations. The effects of train speed, surface roughness amplitudes, roughness orientation and axle load on the adhesion coefficient under interfacial contamination are numerically investigated. A typical creepage-traction curve under oil contamination is obtained at high speed by the present model. In addition, the effects of temperature and the elastic-plastic deformation behaviour of asperities on the adhesion coefficient are discussed in the paper. Furthermore, the effect of different interfacial contaminations on wheel/rail adhesion using the present model on the adhesion coefficient is investigated. In order to validate the present model, the numerical results are compared with the experimental results that were obtained by JD-2 high-speed wheel/rail rolling contact machine under water/oil contaminations.

Bing Wu - One of the best experts on this subject based on the ideXlab platform.

  • analysis on thermal effect on high speed wheel rail adhesion under interfacial contamination using a three dimensional model with surface roughness
    Wear, 2016
    Co-Authors: Zefeng Wen, Bing Wu, Tao Wu, Xuesong Jin
    Abstract:

    Abstract A three-dimensional numerical model of wheel/rail in rolling contact is established to study the adhesion characteristics under interfacial contamination considering surface roughness at high speed. The thermal partial elastohydrodynamic lubrication (EHL) theory in elliptical contact is used in the model. The numerical model is successfully solved by applying the iterative algorithm between the pressure field and temperature field. Multilevel Method is used to solve modified Reynolds equation. Sweeping column Method is used to solve energy and heat conduction equations. The effects of train speed, surface roughness amplitudes, roughness orientation and axle load on the adhesion coefficient under interfacial contamination are numerically investigated. A typical creepage-traction curve under oil contamination is obtained at high speed by the present model. In addition, the effects of temperature and the elastic-plastic deformation behaviour of asperities on the adhesion coefficient are discussed in the paper. Furthermore, the effect of different interfacial contaminations on wheel/rail adhesion using the present model on the adhesion coefficient is investigated. In order to validate the present model, the numerical results are compared with the experimental results that were obtained by JD-2 high-speed wheel/rail rolling contact machine under water/oil contaminations.

  • Analysis on thermal effect on high-speed wheel/rail adhesion under interfacial contamination using a three-dimensional model with surface roughness
    Wear, 2016
    Co-Authors: Bing Wu, Zefeng Wen, Tao Wu, Xuesong Jin
    Abstract:

    A three-dimensional numerical model of wheel/rail in rolling contact is established to study the adhesion characteristics under interfacial contamination considering surface roughness at high speed. The thermal partial elastohydrodynamic lubrication (EHL) theory in elliptical contact is used in the model. The numerical model is successfully solved by applying the iterative algorithm between the pressure field and temperature field. Multilevel Method is used to solve modified Reynolds equation. Sweeping column Method is used to solve energy and heat conduction equations. The effects of train speed, surface roughness amplitudes, roughness orientation and axle load on the adhesion coefficient under interfacial contamination are numerically investigated. A typical creepage-traction curve under oil contamination is obtained at high speed by the present model. In addition, the effects of temperature and the elastic-plastic deformation behaviour of asperities on the adhesion coefficient are discussed in the paper. Furthermore, the effect of different interfacial contaminations on wheel/rail adhesion using the present model on the adhesion coefficient is investigated. In order to validate the present model, the numerical results are compared with the experimental results that were obtained by JD-2 high-speed wheel/rail rolling contact machine under water/oil contaminations.

Tao Wu - One of the best experts on this subject based on the ideXlab platform.

  • analysis on thermal effect on high speed wheel rail adhesion under interfacial contamination using a three dimensional model with surface roughness
    Wear, 2016
    Co-Authors: Zefeng Wen, Bing Wu, Tao Wu, Xuesong Jin
    Abstract:

    Abstract A three-dimensional numerical model of wheel/rail in rolling contact is established to study the adhesion characteristics under interfacial contamination considering surface roughness at high speed. The thermal partial elastohydrodynamic lubrication (EHL) theory in elliptical contact is used in the model. The numerical model is successfully solved by applying the iterative algorithm between the pressure field and temperature field. Multilevel Method is used to solve modified Reynolds equation. Sweeping column Method is used to solve energy and heat conduction equations. The effects of train speed, surface roughness amplitudes, roughness orientation and axle load on the adhesion coefficient under interfacial contamination are numerically investigated. A typical creepage-traction curve under oil contamination is obtained at high speed by the present model. In addition, the effects of temperature and the elastic-plastic deformation behaviour of asperities on the adhesion coefficient are discussed in the paper. Furthermore, the effect of different interfacial contaminations on wheel/rail adhesion using the present model on the adhesion coefficient is investigated. In order to validate the present model, the numerical results are compared with the experimental results that were obtained by JD-2 high-speed wheel/rail rolling contact machine under water/oil contaminations.

  • Analysis on thermal effect on high-speed wheel/rail adhesion under interfacial contamination using a three-dimensional model with surface roughness
    Wear, 2016
    Co-Authors: Bing Wu, Zefeng Wen, Tao Wu, Xuesong Jin
    Abstract:

    A three-dimensional numerical model of wheel/rail in rolling contact is established to study the adhesion characteristics under interfacial contamination considering surface roughness at high speed. The thermal partial elastohydrodynamic lubrication (EHL) theory in elliptical contact is used in the model. The numerical model is successfully solved by applying the iterative algorithm between the pressure field and temperature field. Multilevel Method is used to solve modified Reynolds equation. Sweeping column Method is used to solve energy and heat conduction equations. The effects of train speed, surface roughness amplitudes, roughness orientation and axle load on the adhesion coefficient under interfacial contamination are numerically investigated. A typical creepage-traction curve under oil contamination is obtained at high speed by the present model. In addition, the effects of temperature and the elastic-plastic deformation behaviour of asperities on the adhesion coefficient are discussed in the paper. Furthermore, the effect of different interfacial contaminations on wheel/rail adhesion using the present model on the adhesion coefficient is investigated. In order to validate the present model, the numerical results are compared with the experimental results that were obtained by JD-2 high-speed wheel/rail rolling contact machine under water/oil contaminations.

Zefeng Wen - One of the best experts on this subject based on the ideXlab platform.

  • analysis on thermal effect on high speed wheel rail adhesion under interfacial contamination using a three dimensional model with surface roughness
    Wear, 2016
    Co-Authors: Zefeng Wen, Bing Wu, Tao Wu, Xuesong Jin
    Abstract:

    Abstract A three-dimensional numerical model of wheel/rail in rolling contact is established to study the adhesion characteristics under interfacial contamination considering surface roughness at high speed. The thermal partial elastohydrodynamic lubrication (EHL) theory in elliptical contact is used in the model. The numerical model is successfully solved by applying the iterative algorithm between the pressure field and temperature field. Multilevel Method is used to solve modified Reynolds equation. Sweeping column Method is used to solve energy and heat conduction equations. The effects of train speed, surface roughness amplitudes, roughness orientation and axle load on the adhesion coefficient under interfacial contamination are numerically investigated. A typical creepage-traction curve under oil contamination is obtained at high speed by the present model. In addition, the effects of temperature and the elastic-plastic deformation behaviour of asperities on the adhesion coefficient are discussed in the paper. Furthermore, the effect of different interfacial contaminations on wheel/rail adhesion using the present model on the adhesion coefficient is investigated. In order to validate the present model, the numerical results are compared with the experimental results that were obtained by JD-2 high-speed wheel/rail rolling contact machine under water/oil contaminations.

  • Analysis on thermal effect on high-speed wheel/rail adhesion under interfacial contamination using a three-dimensional model with surface roughness
    Wear, 2016
    Co-Authors: Bing Wu, Zefeng Wen, Tao Wu, Xuesong Jin
    Abstract:

    A three-dimensional numerical model of wheel/rail in rolling contact is established to study the adhesion characteristics under interfacial contamination considering surface roughness at high speed. The thermal partial elastohydrodynamic lubrication (EHL) theory in elliptical contact is used in the model. The numerical model is successfully solved by applying the iterative algorithm between the pressure field and temperature field. Multilevel Method is used to solve modified Reynolds equation. Sweeping column Method is used to solve energy and heat conduction equations. The effects of train speed, surface roughness amplitudes, roughness orientation and axle load on the adhesion coefficient under interfacial contamination are numerically investigated. A typical creepage-traction curve under oil contamination is obtained at high speed by the present model. In addition, the effects of temperature and the elastic-plastic deformation behaviour of asperities on the adhesion coefficient are discussed in the paper. Furthermore, the effect of different interfacial contaminations on wheel/rail adhesion using the present model on the adhesion coefficient is investigated. In order to validate the present model, the numerical results are compared with the experimental results that were obtained by JD-2 high-speed wheel/rail rolling contact machine under water/oil contaminations.

Raul Tempone - One of the best experts on this subject based on the ideXlab platform.

  • importance sampling for a robust and efficient Multilevel monte carlo estimator for stochastic reaction networks
    Statistics and Computing, 2020
    Co-Authors: Chiheb Ben Hammouda, Nadhir Ben Rached, Raul Tempone
    Abstract:

    The Multilevel Monte Carlo (MLMC) Method for continuous-time Markov chains, first introduced by Anderson and Higham (SIAM Multiscal Model Simul 10(1):146–179, 2012), is a highly efficient simulation technique that can be used to estimate various statistical quantities for stochastic reaction networks, in particular for stochastic biological systems. Unfortunately, the robustness and performance of the Multilevel Method can be affected by the high kurtosis, a phenomenon observed at the deep levels of MLMC, which leads to inaccurate estimates of the sample variance. In this work, we address cases where the high-kurtosis phenomenon is due to catastrophic coupling (characteristic of pure jump processes where coupled consecutive paths are identical in most of the simulations, while differences only appear in a tiny proportion) and introduce a pathwise-dependent importance sampling (IS) technique that improves the robustness and efficiency of the Multilevel Method. Our theoretical results, along with the conducted numerical experiments, demonstrate that our proposed Method significantly reduces the kurtosis of the deep levels of MLMC, and also improves the strong convergence rate from $$\beta =1$$ for the standard case (without IS), to $$\beta =1+\delta $$ , where $$0<\delta <1$$ is a user-selected parameter in our IS algorithm. Due to the complexity theorem of MLMC, and given a pre-selected tolerance, $$\text {TOL}$$ , this results in an improvement of the complexity from $${\mathcal {O}}\left( \text {TOL}^{-2} \log (\text {TOL})^2\right) $$ in the standard case to $${\mathcal {O}}\left( \text {TOL}^{-2}\right) $$ , which is the optimal complexity of the MLMC estimator. We achieve all these improvements with a negligible additional cost since our IS algorithm is only applied a few times across each simulated path.

  • Importance sampling for a robust and efficient Multilevel Monte Carlo estimator for stochastic reaction networks
    Statistics and Computing, 2020
    Co-Authors: Chiheb Ben Hammouda, Nadhir Ben Rached, Raul Tempone
    Abstract:

    The Multilevel Monte Carlo (MLMC) Method for continuous-time Markov chains, first introduced by Anderson and Higham (SIAM Multiscal Model Simul 10(1):146–179, 2012), is a highly efficient simulation technique that can be used to estimate various statistical quantities for stochastic reaction networks, in particular for stochastic biological systems. Unfortunately, the robustness and performance of the Multilevel Method can be affected by the high kurtosis, a phenomenon observed at the deep levels of MLMC, which leads to inaccurate estimates of the sample variance. In this work, we address cases where the high-kurtosis phenomenon is due to catastrophic coupling (characteristic of pure jump processes where coupled consecutive paths are identical in most of the simulations, while differences only appear in a tiny proportion) and introduce a pathwise-dependent importance sampling (IS) technique that improves the robustness and efficiency of the Multilevel Method. Our theoretical results, along with the conducted numerical experiments, demonstrate that our proposed Method significantly reduces the kurtosis of the deep levels of MLMC, and also improves the strong convergence rate from $$\beta =1$$ β = 1 for the standard case (without IS), to $$\beta =1+\delta $$ β = 1 + δ , where $$0

  • importance sampling for a robust and efficient Multilevel monte carlo estimator for stochastic reaction networks
    arXiv: Numerical Analysis, 2019
    Co-Authors: Chiheb Ben Hammouda, Nadhir Ben Rached, Raul Tempone
    Abstract:

    The Multilevel Monte Carlo (MLMC) Method for continuous time Markov chains, first introduced by Anderson and Higham (2012), is a highly efficient simulation technique that can be used to estimate various statistical quantities for stochastic reaction networks (SRNs), and in particular for stochastic biological systems. Unfortunately, the robustness and performance of the Multilevel Method can be deteriorated due to the phenomenon of high kurtosis, observed at the deep levels of MLMC, which leads to inaccurate estimates for the sample variance. In this work, we address cases where the high-kurtosis phenomenon is due to \textit{catastrophic coupling} (characteristic of pure jump processes where coupled consecutive paths are identical in most of the simulations, while differences only appear in a very small proportion), and introduce a pathwise dependent importance sampling technique that improves the robustness and efficiency of the Multilevel Method. Our analysis, along with the conducted numerical experiments, demonstrates that our proposed Method significantly reduces the kurtosis of the deep levels of MLMC, and also improves the strong convergence rate from $\beta=1$ for the standard case (without importance sampling), to $\beta=1+\delta$, where $0<\delta<1$ is a user-selected parameter in our importance sampling algorithm. Due to the complexity theorem of MLMC and given a pre-selected tolerance, $TOL$, this results in an improvement of the complexity from $\mathcal{O}\left(TOL^{-2} \log(TOL)^2\right)$ in the standard case to $\mathcal{O}\left(TOL^{-2}\right)$.

  • importance sampling for a robust and efficient Multilevel monte carlo estimator for stochastic reaction networks
    arXiv: Numerical Analysis, 2019
    Co-Authors: Chiheb Ben Hammouda, Nadhir Ben Rached, Raul Tempone
    Abstract:

    The Multilevel Monte Carlo (MLMC) Method for continuous-time Markov chains, first introduced by Anderson and Higham (SIAM Multiscal Model. Simul. 10(1), 2012), is a highly efficient simulation technique that can be used to estimate various statistical quantities for stochastic reaction networks (SRNs), in particular for stochastic biological systems. Unfortunately, the robustness and performance of the Multilevel Method can be affected by the high kurtosis, a phenomenon observed at the deep levels of MLMC, which leads to inaccurate estimates of the sample variance. In this work, we address cases where the high-kurtosis phenomenon is due to \textit{catastrophic coupling (characteristic of pure jump processes where coupled consecutive paths are identical in most of the simulations, while differences only appear in a tiny proportion) and introduce a pathwise-dependent importance sampling (IS) technique that improves the robustness and efficiency of the Multilevel Method. Our theoretical results, along with the conducted numerical experiments, demonstrate that our proposed Method significantly reduces the kurtosis of the deep levels of MLMC, and also improves the strong convergence rate from $\beta=1$ for the standard case (without IS), to $\beta=1+\delta$, where $0<\delta<1$ is a user-selected parameter in our IS algorithm. Due to the complexity theorem of MLMC, and given a pre-selected tolerance, $\text{TOL}$, this results in an improvement of the complexity from $\mathcal{O}\left(\text{TOL}^{-2} \log(\text{TOL})^2\right)$ in the standard case to $\mathcal{O}\left(\text{TOL}^{-2}\right)$, which is the optimal complexity of the MLMC estimator. We achieve all these improvements with a negligible additional cost since our IS algorithm is only applied a few times across each simulated path.