To estimate the parameters of the mixed additive and multiplicative(MAM)random error model using the weighted least squares iterative algorithm that requires derivation of the complex weight array,we introduce a deriv...To estimate the parameters of the mixed additive and multiplicative(MAM)random error model using the weighted least squares iterative algorithm that requires derivation of the complex weight array,we introduce a derivative-free cat swarm optimization for parameter estimation.We embed the Powell method,which uses conjugate direction acceleration and does not need to derive the objective function,into the original cat swarm optimization to accelerate its convergence speed and search accuracy.We use the ordinary least squares,weighted least squares,original cat swarm optimization,particle swarm algorithm and improved cat swarm optimization to estimate the parameters of the straight-line fitting MAM model with lower nonlinearity and the DEM MAM model with higher nonlinearity,respectively.The experimental results show that the improved cat swarm optimization has faster convergence speed,higher search accuracy,and better stability than the original cat swarm optimization and the particle swarm algorithm.At the same time,the improved cat swarm optimization can obtain results consistent with the weighted least squares method based on the objective function only while avoiding multiple complex weight array derivations.The method in this paper provides a new idea for theoretical research on parameter estimation of MAM error models.展开更多
Offshore platforms are susceptible to structural damage due to prolonged exposure to random loads,such as wind,waves,and currents.This is particularly true for platforms that have been in service for an extended perio...Offshore platforms are susceptible to structural damage due to prolonged exposure to random loads,such as wind,waves,and currents.This is particularly true for platforms that have been in service for an extended period.Identifying the modal parameters of offshore platforms is crucial for damage diagno sis,as it serves as a prerequisite and foundation for the process.Therefore,it holds great significance to prioritize the identification of these parameters.Aiming at the shortcomings of the traditional Fast Bayesian Fast Fourier Transform(FBFFT) method,this paper proposes a modal parameter identification method based on Automatic Frequency Domain Decomposition(AFDD) and optimized FBFFT.By introducing the AFDD method and Powell optimization algorithm,this method can automatically identify the initial value of natural frequency and solve the objective function efficiently and simply.In order to verify the feasibility and effectiveness of the proposed method,it is used to identify the modal parameters of the IASC-ASCE benchmark model and the j acket platform structure model,and the Most Probable Value(MPV) of the modal parameters and their respective posterior uncertainties are successfully identified.The identification results of the IASC-ASCE benc hmark model are compared with the identification re sults of the MODE-ID method,which verifies the effectivene ss and accuracy of the proposed method for identifying modal parameters.It provides a simple and feasible method for quantifying the influence of uncertain factors such as environmental parameters on the identification results,and also provide s a reference for modal parameter identification of other large structures.展开更多
It has been ten years since the fourth edition of the Oxford Classical Dictionary(OCD)was published.There are five contributors to the Cicero entry(pp.1514-1519):J.P.V.D.Balsdon,M.T.Griffin(both for the"Life"...It has been ten years since the fourth edition of the Oxford Classical Dictionary(OCD)was published.There are five contributors to the Cicero entry(pp.1514-1519):J.P.V.D.Balsdon,M.T.Griffin(both for the"Life"part);J.G.F.Powell(sections"Speeches,""Works on rhetoric,""Poem,"and "Letters,"in the "Works"part);J.H.Simon and D.Obbink("Philosophica"section in the "Works"part).Although the first four scholars,especially Professor Griffin and Professor Powell,are among those to whom all earnest readers of Cicero nowadays are certainly grateful and would like to show respect,it seems to me that they did not provide as perfect contributions as Cicero himself might have wished for.As for Obbink,he is more an expert on the Stoic Philodemus and papyrology than on Cicero the philosopher.The following remarks will provide some corrigenda to their OCD entry.展开更多
The U.S.cannot defeat China by acting like an economic bully The United States economy could be headed for tougher times this year as U.S.Federal Reserve Chairman Jerome Powell is giving hints that the Fed will contin...The U.S.cannot defeat China by acting like an economic bully The United States economy could be headed for tougher times this year as U.S.Federal Reserve Chairman Jerome Powell is giving hints that the Fed will continue to raise benchmark rates,leading to tighter monetary policy and increasing borrowing costs.展开更多
孔腔流动中含有复杂的流体振荡,不但能够引起明显的噪声,而且会造成物体脉动压力和阻力的急剧增加,因而孔腔流动与流激噪声已经成为流声耦合研究领域的重要内容。文章首先对于Powell涡声理论进行了介绍,给出了涡声方程及其求解的详细推...孔腔流动中含有复杂的流体振荡,不但能够引起明显的噪声,而且会造成物体脉动压力和阻力的急剧增加,因而孔腔流动与流激噪声已经成为流声耦合研究领域的重要内容。文章首先对于Powell涡声理论进行了介绍,给出了涡声方程及其求解的详细推导过程,随后利用圆柱/机翼组合体与方腔流激噪声测试结果验证了计算方法的可靠性,最后采用大涡模拟方法结合Powell涡声方程数值计算了两型孔腔在不同水速下的流激噪声,并与中国船舶科学研究中心循环水槽试验结果进行了对比分析,结果表明数值计算方法能够较准确地预报孔腔流激噪声,并能展示孔腔内外涡旋结构。计算结果表明:在500 Hz以下的低频段,格栅1型孔腔的流激噪声显著高于格栅2型孔腔;在500 Hz-10 k Hz高频段,格栅2型孔腔流激噪声比格栅1型孔腔高,但随着流速的增高,两种孔腔流激噪声在高频段的幅值基本一致。这些现象与孔腔内的涡旋结构密切相关。文中对孔腔流激噪声的数值预报方法进行了验证,有益于理解孔腔非定常流动的物理机理,且为抑制孔腔流激噪声奠定了基础。展开更多
基金supported by the National Natural Science Foundation of China(No.42174011 and No.41874001).
文摘To estimate the parameters of the mixed additive and multiplicative(MAM)random error model using the weighted least squares iterative algorithm that requires derivation of the complex weight array,we introduce a derivative-free cat swarm optimization for parameter estimation.We embed the Powell method,which uses conjugate direction acceleration and does not need to derive the objective function,into the original cat swarm optimization to accelerate its convergence speed and search accuracy.We use the ordinary least squares,weighted least squares,original cat swarm optimization,particle swarm algorithm and improved cat swarm optimization to estimate the parameters of the straight-line fitting MAM model with lower nonlinearity and the DEM MAM model with higher nonlinearity,respectively.The experimental results show that the improved cat swarm optimization has faster convergence speed,higher search accuracy,and better stability than the original cat swarm optimization and the particle swarm algorithm.At the same time,the improved cat swarm optimization can obtain results consistent with the weighted least squares method based on the objective function only while avoiding multiple complex weight array derivations.The method in this paper provides a new idea for theoretical research on parameter estimation of MAM error models.
基金financially supported by the Natural Science Foundation of Heilongjiang Province of China (Grant No. LH2020E016)the National Natural Science Foundation of China (Grant No.11472076)。
文摘Offshore platforms are susceptible to structural damage due to prolonged exposure to random loads,such as wind,waves,and currents.This is particularly true for platforms that have been in service for an extended period.Identifying the modal parameters of offshore platforms is crucial for damage diagno sis,as it serves as a prerequisite and foundation for the process.Therefore,it holds great significance to prioritize the identification of these parameters.Aiming at the shortcomings of the traditional Fast Bayesian Fast Fourier Transform(FBFFT) method,this paper proposes a modal parameter identification method based on Automatic Frequency Domain Decomposition(AFDD) and optimized FBFFT.By introducing the AFDD method and Powell optimization algorithm,this method can automatically identify the initial value of natural frequency and solve the objective function efficiently and simply.In order to verify the feasibility and effectiveness of the proposed method,it is used to identify the modal parameters of the IASC-ASCE benchmark model and the j acket platform structure model,and the Most Probable Value(MPV) of the modal parameters and their respective posterior uncertainties are successfully identified.The identification results of the IASC-ASCE benc hmark model are compared with the identification re sults of the MODE-ID method,which verifies the effectivene ss and accuracy of the proposed method for identifying modal parameters.It provides a simple and feasible method for quantifying the influence of uncertain factors such as environmental parameters on the identification results,and also provide s a reference for modal parameter identification of other large structures.
文摘It has been ten years since the fourth edition of the Oxford Classical Dictionary(OCD)was published.There are five contributors to the Cicero entry(pp.1514-1519):J.P.V.D.Balsdon,M.T.Griffin(both for the"Life"part);J.G.F.Powell(sections"Speeches,""Works on rhetoric,""Poem,"and "Letters,"in the "Works"part);J.H.Simon and D.Obbink("Philosophica"section in the "Works"part).Although the first four scholars,especially Professor Griffin and Professor Powell,are among those to whom all earnest readers of Cicero nowadays are certainly grateful and would like to show respect,it seems to me that they did not provide as perfect contributions as Cicero himself might have wished for.As for Obbink,he is more an expert on the Stoic Philodemus and papyrology than on Cicero the philosopher.The following remarks will provide some corrigenda to their OCD entry.
文摘The U.S.cannot defeat China by acting like an economic bully The United States economy could be headed for tougher times this year as U.S.Federal Reserve Chairman Jerome Powell is giving hints that the Fed will continue to raise benchmark rates,leading to tighter monetary policy and increasing borrowing costs.
文摘孔腔流动中含有复杂的流体振荡,不但能够引起明显的噪声,而且会造成物体脉动压力和阻力的急剧增加,因而孔腔流动与流激噪声已经成为流声耦合研究领域的重要内容。文章首先对于Powell涡声理论进行了介绍,给出了涡声方程及其求解的详细推导过程,随后利用圆柱/机翼组合体与方腔流激噪声测试结果验证了计算方法的可靠性,最后采用大涡模拟方法结合Powell涡声方程数值计算了两型孔腔在不同水速下的流激噪声,并与中国船舶科学研究中心循环水槽试验结果进行了对比分析,结果表明数值计算方法能够较准确地预报孔腔流激噪声,并能展示孔腔内外涡旋结构。计算结果表明:在500 Hz以下的低频段,格栅1型孔腔的流激噪声显著高于格栅2型孔腔;在500 Hz-10 k Hz高频段,格栅2型孔腔流激噪声比格栅1型孔腔高,但随着流速的增高,两种孔腔流激噪声在高频段的幅值基本一致。这些现象与孔腔内的涡旋结构密切相关。文中对孔腔流激噪声的数值预报方法进行了验证,有益于理解孔腔非定常流动的物理机理,且为抑制孔腔流激噪声奠定了基础。
