The Experts below are selected from a list of 1494 Experts worldwide ranked by ideXlab platform

Jiuhong Yang - One of the best experts on this subject based on the ideXlab platform.

  • Steel Ball Temperature Uniform Distribution Time Calculation Method in Annealing Process
    2016
    Co-Authors: Xiaozeng Wang, Jiuhong Yang
    Abstract:

    Abstract. The paper presents a fitness formula which is adopted to calculate the steel ball temperature uniform distribution time in the annealing process, analyses the steel ball temperature distribution in the process of heating. After the heat conduction equation of the steel ball is deduced, the Spherical Bessel Function is adopted to solve it. The temperature distribution series solution is obtained. Using this formula, the steel ball temperature uniform distribution time of the different radius is calculated in the process of annealing. The result shows that the steel ball temperature uniform distribution time is the quadratic Function of the steel ball radius. The time and radius data is adopted to deduce a second-order fitness polynomial. The steel ball temperature distribution is obtained in the different position. The steel ball temperature uniform distribution time is calculated by the fitness formula and the temperature distribution series one. The error between them is only 0.03%. The fitness formula can be used to calculate the steel ball temperature uniform distribution time. The change of the steel ball surface temperature is more severe than the internal. It often results in the crack of the steel ball in the annealing process

Yang Jiu-hong - One of the best experts on this subject based on the ideXlab platform.

  • Calculation on Uniformization Time of Steel Ball Temperature Besed on Spherical Bessel Function
    2012
    Co-Authors: Yang Jiu-hong
    Abstract:

    The heat conduction equation of the ball is deduced,the Spherical Bessel Function is adopted to solve the equation,and the temperature variation in ball with different radius in the heat treatment process is analyzed.The fitting formulas for temperature uniformization time of ball with different radius are obtained by using experiments and charts.The results show that the temperature uniformization time of ball is the quadratic Function of ball radius,the error is 0.6%.The ball surface temperature change more sharply than the center,the small cracks on the surface results in the crack of the ball.

Vlah Zvonimir - One of the best experts on this subject based on the ideXlab platform.

  • Rotation method for accelerating multiple-Spherical Bessel Function integrals against a numerical source Function
    eScholarship University of California, 2020
    Co-Authors: Slepian Zachary, Li Yin, Schmittfull Marcel, Vlah Zvonimir
    Abstract:

    A common problem in cosmology is to integrate the product of two or more Spherical Bessel Functions (sBFs) with different configuration-space arguments against the power spectrum or its square, weighted by powers of wavenumber. Naively computing them scales as $N_{\rm g}^{p+1}$ with $p$ the number of configuration space arguments and $N_{\rm g}$ the grid size, and they cannot be done with Fast Fourier Transforms (FFTs). Here we show that by rewriting the sBFs as sums of products of sine and cosine and then using the product to sum identities, these integrals can then be performed using 1-D FFTs with $N_{\rm g} \log N_{\rm g}$ scaling. This "rotation" method has the potential to accelerate significantly a number of calculations in cosmology, such as perturbation theory predictions of loop integrals, higher order correlation Functions, and analytic templates for correlation Function covariance matrices. We implement this approach numerically both in a free-standing, publicly-available \textsc{Python} code and within the larger, publicly-available package \texttt{mcfit}. The rotation method evaluated with direct integrations already offers a factor of 6-10$\times$ speed-up over the naive approach in our test cases. Using FFTs, which the rotation method enables, then further improves this to a speed-up of $\sim$$1000-3000\times$ over the naive approach. The rotation method should be useful in light of upcoming large datasets such as DESI or LSST. In analysing these datasets recomputation of these integrals a substantial number of times, for instance to update perturbation theory predictions or covariance matrices as the input linear power spectrum is changed, will be one piece in a Monte Carlo Markov Chain cosmological parameter search: thus the overall savings from our method should be significant

  • Rotation method for accelerating multiple-Spherical Bessel Function integrals against a numerical source Function
    2019
    Co-Authors: Slepian Zachary, Li Yin, Schmittfull Marcel, Vlah Zvonimir
    Abstract:

    A common problem in cosmology is to integrate the product of two or more Spherical Bessel Functions (sBFs) with different configuration-space arguments against the power spectrum or its square, weighted by powers of wavenumber. Naively computing them scales as $N_{\rm g}^{p+1}$ with $p$ the number of configuration space arguments and $N_{\rm g}$ the grid size, and they cannot be done with Fast Fourier Transforms (FFTs). Here we show that by rewriting the sBFs as sums of products of sine and cosine and then using the product to sum identities, these integrals can then be performed using 1-D FFTs with $N_{\rm g} \log N_{\rm g}$ scaling. This "rotation" method has the potential to accelerate significantly a number of calculations in cosmology, such as perturbation theory predictions of loop integrals, higher order correlation Functions, and analytic templates for correlation Function covariance matrices. We implement this approach numerically both in a free-standing, publicly-available \textsc{Python} code and within the larger, publicly-available package \texttt{mcfit}. The rotation method evaluated with direct integrations already offers a factor of 6-10$\times$ speed-up over the naive approach in our test cases. Using FFTs, which the rotation method enables, then further improves this to a speed-up of $\sim$$1000-3000\times$ over the naive approach. The rotation method should be useful in light of upcoming large datasets such as DESI or LSST. In analysing these datasets recomputation of these integrals a substantial number of times, for instance to update perturbation theory predictions or covariance matrices as the input linear power spectrum is changed, will be one piece in a Monte Carlo Markov Chain cosmological parameter search: thus the overall savings from our method should be significant.Comment: 21 pages, 14 figures, submitted MNRAS; code available at https://github.com/eelregit/sbf_rotatio

Harry A. Mavromatis - One of the best experts on this subject based on the ideXlab platform.

Xiaozeng Wang - One of the best experts on this subject based on the ideXlab platform.

  • Steel Ball Temperature Uniform Distribution Time Calculation Method in Annealing Process
    2016
    Co-Authors: Xiaozeng Wang, Jiuhong Yang
    Abstract:

    Abstract. The paper presents a fitness formula which is adopted to calculate the steel ball temperature uniform distribution time in the annealing process, analyses the steel ball temperature distribution in the process of heating. After the heat conduction equation of the steel ball is deduced, the Spherical Bessel Function is adopted to solve it. The temperature distribution series solution is obtained. Using this formula, the steel ball temperature uniform distribution time of the different radius is calculated in the process of annealing. The result shows that the steel ball temperature uniform distribution time is the quadratic Function of the steel ball radius. The time and radius data is adopted to deduce a second-order fitness polynomial. The steel ball temperature distribution is obtained in the different position. The steel ball temperature uniform distribution time is calculated by the fitness formula and the temperature distribution series one. The error between them is only 0.03%. The fitness formula can be used to calculate the steel ball temperature uniform distribution time. The change of the steel ball surface temperature is more severe than the internal. It often results in the crack of the steel ball in the annealing process