对m(>1)次单元,基于单元能量投影(element energy projection,简称EEP)法提出的简约格式位移解u∗具有比常规有限元解uh至少高一阶的精度,据此提出了EEP单元概念,并给出以EEP单元作为最终解的自适应有限元求解策略.通过编制相应的计...对m(>1)次单元,基于单元能量投影(element energy projection,简称EEP)法提出的简约格式位移解u∗具有比常规有限元解uh至少高一阶的精度,据此提出了EEP单元概念,并给出以EEP单元作为最终解的自适应有限元求解策略.通过编制相应的计算程序分析了一维非自伴随问题,计算结果与理论预期吻合较好,验证了自适应求解策略的有效性和可靠性.研究结果表明:该法可以给出按最大模度量、逐点满足误差限的解答,相较于常规单元,最终的求解单元数更少.展开更多
基于对单元能量投影(element energy projection,EEP)法误差项的直接推导及分析,用EEP简约格式的解计算出略掉的误差项,反补后得到比简约格式高一阶精度的EEP超收敛计算的加强格式。该文以一维Galerkin有限元为例,给出EEP加强格式的算...基于对单元能量投影(element energy projection,EEP)法误差项的直接推导及分析,用EEP简约格式的解计算出略掉的误差项,反补后得到比简约格式高一阶精度的EEP超收敛计算的加强格式。该文以一维Galerkin有限元为例,给出EEP加强格式的算法公式和数学证明。理论分析和算例验证表明:对于m (≥1)次单元,采用EEP加强格式计算的内点位移和内点导数都具有h^(min(m+3,2m))阶的收敛精度,对系数特例问题二者甚至可以分别达到h^(min(m+5,2m))和h^(min(m+4,2m))阶的收敛精度。并对该法的进一步拓展作了讨论。展开更多
对于结构动力分析中的离散系统运动方程,现有算法的计算精度和效率均依赖于时间步长的选取,这是时间域问题求解的难点.基于EEP(element energy projection)超收敛计算的自适应有限元法,以EEP超收敛解代替未知真解,估计常规有限元解的误...对于结构动力分析中的离散系统运动方程,现有算法的计算精度和效率均依赖于时间步长的选取,这是时间域问题求解的难点.基于EEP(element energy projection)超收敛计算的自适应有限元法,以EEP超收敛解代替未知真解,估计常规有限元解的误差,并自动细分网格,目前已对诸类以空间坐标为自变量的边值问题取得成功.对离散系统运动方程建立弱型Galerkin有限元解,引入基于EEP法的自适应求解策略,在时间域上自动划分网格,最终得到所求时域内任一时刻均满足给定误差限的动位移解,进而建立了一种时间域上的新型自适应求解算法.展开更多
利用单元能量投影(Element Energy Projection,简称EEP)法所计算的EEP超收敛解,在不改变有限元网格及其整体刚度矩阵的情况下,导出残差的等效结点荷载向量,只经回代过程即可得到具有更高阶精度的结点位移的误差估计,使结点位移精度得到...利用单元能量投影(Element Energy Projection,简称EEP)法所计算的EEP超收敛解,在不改变有限元网格及其整体刚度矩阵的情况下,导出残差的等效结点荷载向量,只经回代过程即可得到具有更高阶精度的结点位移的误差估计,使结点位移精度得到极大提高。该文以一般的二阶常微分方程边值和初值问题为例,给出算法和相应的数值算例。从中可以看出,本法十分简单而高效:对于m≥1次单元,采用EEP简约格式和凝聚格式修正后的结点位移,分别具有O(h^(2m+2))和O(h^(3m+mod(m,2)))的超常规的超收敛阶。该文给出了典型算例,并对该法的进一步拓展和应用作了讨论。展开更多
为了降低入侵检测系统的误报率和漏报率,我们将两阶段分类算法(Classification of EssentialEmerging Pattern in Two Phases)CEEPTP应用到入侵检测中。该算法结合两阶段思想和基本显露模式eEP在分类方面的优势,使用两个阶段挖掘eEP并...为了降低入侵检测系统的误报率和漏报率,我们将两阶段分类算法(Classification of EssentialEmerging Pattern in Two Phases)CEEPTP应用到入侵检测中。该算法结合两阶段思想和基本显露模式eEP在分类方面的优势,使用两个阶段挖掘eEP并用于分类,分类时考虑第二阶段对第一阶段的修正作用,实验表明具有较好的分类结果。展开更多
Objective: To observe the relationship of deep slow respiratory pattern and respiratory impedance(RI) in patients with chronic obstructive pulmonary disease (COPD). Methods: RI under normal respiration and during deep...Objective: To observe the relationship of deep slow respiratory pattern and respiratory impedance(RI) in patients with chronic obstructive pulmonary disease (COPD). Methods: RI under normal respiration and during deep slow respira tion was measured one after the other with impulse oscillometry for 8 patients with COPD and for 9 healthy volunteers as control. Results: When r espiration was changed from normal pattern to the deep slow pattern, the tida l volume increased and respiratory frequency significantly decreased in both gro ups , the total respiratory impedance (Z respir) showed a decreasing trend in COPD group, but with no obvious change in the control group. No chang e in the resonant frequency (fres) was found in both groups, and the respiratory viscous resistance obviously decreased in the COPD group(R5: P =0.0168 ; R20: P =0.0498; R5—R20: P =0.0388),though in the control group it was unchanged. Conclusion: IOS detection could reflect the response he terogeneity of different compartments of respiratory system during tidal breathi ng. During deep slow respiration, the viscous resistance in both central airw ay and peripheral airway was decreased in patients with COPD. RI measurement by impulse oscillometry may be a convenient pathophysiological method for studying the application of breathing exercise in patients with COPD.展开更多
文摘对m(>1)次单元,基于单元能量投影(element energy projection,简称EEP)法提出的简约格式位移解u∗具有比常规有限元解uh至少高一阶的精度,据此提出了EEP单元概念,并给出以EEP单元作为最终解的自适应有限元求解策略.通过编制相应的计算程序分析了一维非自伴随问题,计算结果与理论预期吻合较好,验证了自适应求解策略的有效性和可靠性.研究结果表明:该法可以给出按最大模度量、逐点满足误差限的解答,相较于常规单元,最终的求解单元数更少.
文摘基于对单元能量投影(element energy projection,EEP)法误差项的直接推导及分析,用EEP简约格式的解计算出略掉的误差项,反补后得到比简约格式高一阶精度的EEP超收敛计算的加强格式。该文以一维Galerkin有限元为例,给出EEP加强格式的算法公式和数学证明。理论分析和算例验证表明:对于m (≥1)次单元,采用EEP加强格式计算的内点位移和内点导数都具有h^(min(m+3,2m))阶的收敛精度,对系数特例问题二者甚至可以分别达到h^(min(m+5,2m))和h^(min(m+4,2m))阶的收敛精度。并对该法的进一步拓展作了讨论。
文摘对于结构动力分析中的离散系统运动方程,现有算法的计算精度和效率均依赖于时间步长的选取,这是时间域问题求解的难点.基于EEP(element energy projection)超收敛计算的自适应有限元法,以EEP超收敛解代替未知真解,估计常规有限元解的误差,并自动细分网格,目前已对诸类以空间坐标为自变量的边值问题取得成功.对离散系统运动方程建立弱型Galerkin有限元解,引入基于EEP法的自适应求解策略,在时间域上自动划分网格,最终得到所求时域内任一时刻均满足给定误差限的动位移解,进而建立了一种时间域上的新型自适应求解算法.
文摘利用单元能量投影(Element Energy Projection,简称EEP)法所计算的EEP超收敛解,在不改变有限元网格及其整体刚度矩阵的情况下,导出残差的等效结点荷载向量,只经回代过程即可得到具有更高阶精度的结点位移的误差估计,使结点位移精度得到极大提高。该文以一般的二阶常微分方程边值和初值问题为例,给出算法和相应的数值算例。从中可以看出,本法十分简单而高效:对于m≥1次单元,采用EEP简约格式和凝聚格式修正后的结点位移,分别具有O(h^(2m+2))和O(h^(3m+mod(m,2)))的超常规的超收敛阶。该文给出了典型算例,并对该法的进一步拓展和应用作了讨论。
文摘为了降低入侵检测系统的误报率和漏报率,我们将两阶段分类算法(Classification of EssentialEmerging Pattern in Two Phases)CEEPTP应用到入侵检测中。该算法结合两阶段思想和基本显露模式eEP在分类方面的优势,使用两个阶段挖掘eEP并用于分类,分类时考虑第二阶段对第一阶段的修正作用,实验表明具有较好的分类结果。
文摘Objective: To observe the relationship of deep slow respiratory pattern and respiratory impedance(RI) in patients with chronic obstructive pulmonary disease (COPD). Methods: RI under normal respiration and during deep slow respira tion was measured one after the other with impulse oscillometry for 8 patients with COPD and for 9 healthy volunteers as control. Results: When r espiration was changed from normal pattern to the deep slow pattern, the tida l volume increased and respiratory frequency significantly decreased in both gro ups , the total respiratory impedance (Z respir) showed a decreasing trend in COPD group, but with no obvious change in the control group. No chang e in the resonant frequency (fres) was found in both groups, and the respiratory viscous resistance obviously decreased in the COPD group(R5: P =0.0168 ; R20: P =0.0498; R5—R20: P =0.0388),though in the control group it was unchanged. Conclusion: IOS detection could reflect the response he terogeneity of different compartments of respiratory system during tidal breathi ng. During deep slow respiration, the viscous resistance in both central airw ay and peripheral airway was decreased in patients with COPD. RI measurement by impulse oscillometry may be a convenient pathophysiological method for studying the application of breathing exercise in patients with COPD.
