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    • 4. 发明申请
    • Visual analysis module for investigation of specific physical processes
    • 用于特定物理过程调查的视觉分析模块
    • US20110113356A1
    • 2011-05-12
    • US12590660
    • 2009-11-12
    • Georgy SamsonidzeGuram Samsonidze
    • Georgy SamsonidzeGuram Samsonidze
    • G06F3/048
    • G09B19/0053
    • The Visual Analysis Module (VAM) is a graphical user interface that can be linked to any computational code for solving time-dependent multi-parameter problems. VAM has two modes that can be toggled between, an active mode and an inactive mode. VAM operating in the inactive mode accumulates the data being computed and visualizes them in real-time. Upon switching to the active mode, VAM can be used to analyze the accumulated data and change the parameters of the system being studied, while the execution of the computational code is paused. Once VAM is switched back to the inactive state, the calculation continues with a new set of system parameters. The analysis of the accumulated computational data guides the user through the process of modifying system parameters in order to reach the optimal solution of the problem. VAM has multiple diverse capabilities to perform such analysis. By using VAM, one can explore the phase space of system parameters without the need to run a large number of calculations in order to examine each set of parameters individually. Thus, the unknown solutions are classified into different groups according to their time evolution, and the optimal solution is found within the designated group. This method is similar to the analytical treatment, but can also be used to solve highly-nonlinear problems with multiple parameters for which no analytical solution have yet been discovered.
    • 视觉分析模块(VAM)是一种图形用户界面,可以链接到任何计算代码,以解决时间依赖的多参数问题。 VAM有两种可以切换的模式,即活动模式和非活动模式。 在非活动模式下运行的VAM会累积正在计算的数据并实时显示它们。 在切换到活动模式时,可以使用VAM来分析累积的数据并改变正在研究的系统的参数,同时暂停计算代码的执行。 一旦VAM切换回无效状态,计算将继续使用一组新的系统参数。 累积计算数据的分析指导用户通过修改系统参数的过程,以达到问题的最优解。 VAM具有多种不同的功能来执行此类分析。 通过使用VAM,可以探索系统参数的相位空间,而无需运行大量计算,以便单独检查每组参数。 因此,未知方案根据其时间演化分为不同的组,最优解在指定组内。 该方法与分析处理相似,但也可用于解决尚未发现分析解的多个参数的高非线性问题。