Euler’s First-Order Explicit Method–Peridynamic Differential Operator for Solving Population Balance Equations of the Crystallization Process

Using Euler’s first-order explicit(EE)method and the peridynamic differential operator(PDDO)to discretize the time and internal crystal-size derivatives,respectively,the Euler’s first-order explicit method–peridynamic differential operator(EE–PDDO)was obtained for solving the one-dimensional population balance equation in crystallization.Four different conditions during crystallization were studied:size-independent growth,sizedependent growth in a batch process,nucleation and size-independent growth,and nucleation and size-dependent growth in a continuous process.The high accuracy of the EE–PDDO method was confirmed by comparing it with the numerical results obtained using the second-order upwind and HR-van methods.The method is characterized by non-oscillation and high accuracy,especially in the discontinuous and sharp crystal size distribution.The stability of the EE–PDDO method,choice of weight function in the PDDO method,and optimal time step are also discussed.

Energy Stable Nodal DG Methods for Maxwell’s Equations of Mixed-Order Form in Nonlinear Optical Media

In this work,we develop energy stable numerical methods to simulate electromagnetic waves propagating in optical media where the media responses include the linear Lorentz dispersion,the instantaneous nonlinear cubic Kerr response,and the nonlinear delayed Raman molecular vibrational response.Unlike the first-order PDE-ODE governing equations considered previously in Bokil et al.(J Comput Phys 350:420–452,2017)and Lyu et al.(J Sci Comput 89:1–42,2021),a model of mixed-order form is adopted here that consists of the first-order PDE part for Maxwell’s equations coupled with the second-order ODE part(i.e.,the auxiliary differential equations)modeling the linear and nonlinear dispersion in the material.The main contribution is a new numerical strategy to treat the Kerr and Raman nonlinearities to achieve provable energy stability property within a second-order temporal discretization.A nodal discontinuous Galerkin(DG)method is further applied in space for efficiently handling nonlinear terms at the algebraic level,while preserving the energy stability and achieving high-order accuracy.Indeed with d_(E)as the number of the components of the electric field,only a d_(E)×d_(E)nonlinear algebraic system needs to be solved at each interpolation node,and more importantly,all these small nonlinear systems are completely decoupled over one time step,rendering very high parallel efficiency.We evaluate the proposed schemes by comparing them with the methods in Bokil et al.(2017)and Lyu et al.(2021)(implemented in nodal form)regarding the accuracy,computational efficiency,and energy stability,by a parallel scalability study,and also through the simulations of the soliton-like wave propagation in one dimension,as well as the spatial-soliton propagation and two-beam interactions modeled by the two-dimensional transverse electric(TE)mode of the equations.

The forecasting efficiency under different selected regions by Pattern Informatics Method and seismic potential estimation in the North-South Seismic Zone

In 2022,four earthquakes with M_(S)≥6.0 including the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes occurred in the North-South Seismic Zone(NSSZ),which demonstrated high and strong seismicity.Pattern Informatics(PI)method,as an effective long and medium term earthquake forecasting method,has been applied to the strong earthquake forecasting in Chinese mainland and results have shown the positive performance.The earthquake catalog with magnitude above M_(S)3.0 since 1970 provided by China Earthquake Networks Center was employed in this study and the Receiver Operating Characteristic(ROC)method was applied to test the forecasting efficiency of the PI method in each selected region related to the North-South Seismic Zone systematically.Based on this,we selected the area with the best ROC testing result and analyzed the evolution process of the PI hotspot map reflecting the small seismic activity pattern prior to the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes.A“forward”forecast for the area was carried out to assess seismic risk.The study shows the following.1)PI forecasting has higher forecasting efficiency in the selected study region where the difference of seismicity in any place of the region is smaller.2)In areas with smaller differences of seismicity,the activity pattern of small earthquakes prior to the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes can be obtained by analyzing the spatio-temporal evolution process of the PI hotspot map.3)The hotspot evolution in and around the southern Tazang fault in the study area is similar to that prior to the strong earthquakes,which suggests the possible seismic hazard in the future.This study could provide some ideas to the seismic hazard assessment in other regions with high seismicity,such as Japan,Californi,Turkey,and Indonesia.

Research on the Application of Montessori Education Method in Cognitive Training of Patients with Alzheimer’s Disease

Objective:To study the application of the Montessori education method in cognitive training in patients with Alzheimer’s disease(AD).Methods:40 cases of senile dementia patients who were admitted to our hospital from January 2022 to January 2023 were selected and randomly divided into an intervention group and a control group according to the single and double number table method,with 20 cases in each group.The intervention group used the Montessori education method,the principle of which was to implement individualized health interventions based on the individual conditions of the patients,for a period of 6 months;the control group was given conventional treatment and nursing of the disease.The Mini-Mental State Examination(MMSE)was used to compare the effects of the two groups of patients before and after health intervention and conduct statistical analysis.Results:The score of the intervention group was higher than that of the control group,and there was a statistical difference between the two(P<0.05).Conclusion:Implementing the Montessori education method for diagnosed Alzheimer’s patients can effectively improve their cognitive function and delay the progress of further dementia.

Powell's optimal identification of material constants of thin-walled box girders based on Fibonacci series search method

A dynamic Bayesian error function of material constants of the structure is developed for thin-walled curve box girders. Combined with the automatic search scheme with an optimal step length for the one-dimensional Fibonacci series, Powell＇s optimization theory is used to perform the stochastic identification of material constants of the thin-walled curve box. Then, the steps in the parameter identification are presented. Powell＇s identification procedure for material constants of the thin-walled curve box is compiled, in which the mechanical analysis of the thin-walled curve box is completed based on the finite curve strip element （FCSE） method. Some classical examples show that Powell＇s identification is numerically stable and convergent, indicating that the present method and the compiled procedure are correct and reliable. During the parameter iterative processes, Powell＇s theory is irrelevant with the calculation of the FCSE partial differentiation, which proves the high computation efficiency of the studied methods. The stochastic performances of the system parameters and responses axe simultaneously considered in the dynamic Bayesian error function. The one-dimensional optimization problem of the optimal step length is solved by adopting the Fibonacci series search method without the need of determining the region, in which the optimized step length lies.

QPSO算法和Powell法结合的多分辨率医学图像配准

图像配准一直是图像研究领域的热点话题,互信息的配准方法由于其精度高、鲁棒性强等特点,成为图像配准中的常用方法。但其目标函数存在局部极值问题。针对这个问题,提出一种量子行为的粒子群优化算法(QPSO)和Powell法相结合的多分辨率搜索优化算法。QPSO参数个数少,其每一个迭代步的取样空间能覆盖整个解空间,能保证算法的全局收敛,因此可以有效地解决Powell算法的缺点。该算法将量子行为的粒子群优化算法(QPSO)与Powell法结合起来对二维的MRI图像进行配准。实验结果表明,该方法能够有效地克服互信息函数的局部极值问题,并提高了配准精度和速度。

ADASYN与类别逆比例加权法在阿尔茨海默病不平衡数据中的应用

目的利用自适应合成抽样(adaptive synthetic sampling,ADASYN)与类别逆比例加权法处理类别不平衡数据,结合分类器构建模型对阿尔茨海默病(alzheimer′s disease,AD)患者疾病进程进行分类预测。方法数据源自阿尔茨海默病神经影像学计划(Alzheimer′s disease neuroimaging initiative,ADNI),经随机森林填补缺失值,弹性网络筛选特征子集后,利用ADASYN与类别逆比例加权法处理类别不平衡数据。分别结合随机森林(random forest,RF)、支持向量机(support vector machine,SVM)构建四种模型:ADASYN-RF、ADASYN-SVM、加权随机森林(weighted random forest,WRF)、加权支持向量机(weighted support vector machine,WSVM),与RF、SVM比较分类性能。模型评价指标为宏观平均精确率(macro-average of precision,macro-P)、宏观平均召回率(macro-average of recall,macro-R)、宏观平均F1值(macro-average of F1-score,macro-F1)、准确率(accuracy,ACC)、Kappa值和AUC(area under the ROC curve)。结果ADASYN-RF的分类性能最优(Kappa值为0.938,AUC为0.980),ADASYN-SVM次之。利用ADASYN-RF预测得到的重要分类特征分别为CDRSB、LDELTOTAL、MMSE,在临床上均可得到证实。结论ADASYN与类别逆比例加权法都能辅助提升分类器性能,但ADASYN算法更优。

基于S-R和分解定理的二维几何非线性问题的虚单元法求解

应变-旋转(Strain-Rotation,S-R)和分解定理为分析几何非线性问题提供了合理可靠的理论基础,但用有限元求解时会遇到大变形发生后的网格畸变问题。近年提出的虚单元法(Virtual element method,VEM)适用于一般的多边形网格,因此,该文尝试使用一阶虚单元求解基于S-R和分解定理的二维几何非线性问题,以克服网格畸变的影响。基于重新定义的多项式位移空间基函数,推演获得一阶虚单元分析线弹性力学问题时允许位移空间向多项式位移空间的投影表达式;按照虚单元法双线性格式的计算规则,分析处理基于更新拖带坐标法和势能率原理的增量变分方程;进而建立离散系统方程及其矩阵表达形式,并编制MATLAB求解程序;采用常规多边形网格和畸变网格,应用该文算法分析均布荷载下的悬臂梁和均匀内压下的厚壁圆筒变形。结果与已有文献和ANSYS软件的对比表明:该文算法在两种网格中均可有效执行且具备足够数值精度。总体该文算法为基于S-R和分解定理的二维几何非线性问题求解提供了一种鲁棒方法。

基于S-CAD方法的宅基地“三权分置”改革试点政策评估——以新疆试点市县为例

采用S-CAD政策评估方法对新疆宅基地“三权分置”政策试点地区伊宁市和奇台县的政策执行效果进行评价,研究发现伊宁市和奇台县两试点政策整体逻辑一致性较好、政策要素之间具备充分性与必要性,利益相关者支持程度较高,有效实现了宅基地“三权分置”改革的政策目标,但仍存在政策手段与政策目标充要性不足,预期政策效果与实际政策效果有一定偏差等问题。针对此,提出宅基地“三权分置”改革政策应适应城乡融合发展趋势,加强农户利益保障机制建设;坚持因地制宜,创新农村宅基地“三权分置”改革思路;兼顾多方利益与公平,提升综合价值效应的建议。

广义概率密度演化方程的Chebyshev拟谱法

概率密度演化方法(probability density evolution equation,PDEM)为非线性随机结构的动力响应分析提供了新的途径.通过PDEM获得结构响应概率密度函数(probability density function,PDF)的关键步骤是求解广义概率密度演化方程(generalized probability density evolution equation,GDEE).对于GDEE的求解通常采用有限差分法,然而,由于GDEE是初始条件间断的变系数一阶双曲偏微分方程,通过有限差分法求解GDEE可能会面临网格敏感性问题、数值色散和数值耗散现象.文章从全局逼近的角度出发,基于Chebyshev拟谱法为GDEE构造了全局插值格式,解决了数值色散、数值耗散以及网格敏感性问题.考虑GDEE的系数在每个时间步长均为常数,推导了GDEE在每一个时间步长内时域上的序列矩阵指数解.由于序列矩阵指数解形式上是解析的,从而很好地克服了数值稳定性问题.两个数值算例表明,通过Chebyshev拟谱法结合时域的序列矩阵指数解求解GDEE得到的结果与精确解以及Monte Carlo模拟的结果非常吻合,且数值耗散和数值色散现象几乎可以忽略.此外,拟谱法具有高效的收敛性且序列矩阵指数解不受CFL (Courant-Friedrichs-Lewy)条件的限制,因此该方法具有良好的数值稳定性和计算效率.

电液3-UPS/S并联稳定平台参数振动特性分析

针对电液3-UPS/S并联稳定平台驱动液压缸的压力脉动所产生的参数振动,建立了稳定平台的参数振动方程并利用多尺度法求解了主共振响应与组合共振响应的一次近似解;分析了主共振与组合共振响应特性以及振动幅值在初始工作空间内的变化规律,最后采用四阶龙格库塔法与模态试验对参数振动模型进行验证。结果表明:数值解与理论解之间的最大误差为4.20%,固有频率理论值与试验值之间的最大误差为4.66%,可验证参数振动模型的正确性。

2024年1月23日乌什M_(S)7.1地震序列频谱偏移特征分析

采用P波初动方法计算了乌什M_(S)7.1地震序列中M_(S)≥4.0地震的震源机制解,震源机制解在时间上存在前期一致性较好,后期一致性紊乱的特点。空间上,乌什县内震源机制解类型多为逆冲型,阿合奇县内震源机制解类型多为走滑型。利用新疆地震台网数字波形资料和快速傅里叶变换方法,计算乌什M_(S)7.1地震序列中M_(S)≥5.0地震序列的频率谱,计算结果显示,乌什县内发生的5级余震前期有频谱偏移特征,最后一个5级地震频带变宽,频谱偏移特征消失;阿合奇县内发生的5级余震均出现了频谱偏移特征。

基于D-S证据理论改进AHP-熵权的流域洪涝灾害评估研究

考虑致灾因子危险性、孕灾环境敏感性以及承灾体易损性,选取指标构建小清河流域洪涝灾害风险评估指标体系,提出一种基于D-S证据理论的改进AHP-熵权法计算指标权重,求取洪涝灾害风险指数,运用自然断点分级法确定洪涝灾害风险等级,分析小清河流域洪涝灾害风险空间分布情况。结果表明:小清河流域洪涝灾害风险总体上表现出南低北高的趋势,其中高风险区和较高风险区分别占流域面积的8.7%和14.3%,主要分布在小清河干流以及主要支流两岸。所得评估结果同“利奇马”台风发生期间实际洪灾风险分布情况一致,对比证明基于D-S证据理论的改进AHP-熵权法优于AHP和熵权法,可为小清河流域防洪减灾决策提供依据。

Continuum Skyrme Hartree-Fock-Bogoliubov theory with Green’s function method for neutron-rich Ca,Ni,Zr,and Sn isotopes

The possible exotic nuclear properties in the neutron-rich Ca,Ni,Zr,and Sn isotopes are examined with the continuum Skyrme Hartree-Fock-Bogoliubov theory in the framework of the Green’s function method.The pairing correlation,the couplings with the continuum,and the blocking effects for the unpaired nucleon in odd-A nuclei are properly treated.The Skyrme interaction SLy4 is adopted for the ph channel and the density-dependentinteraction is adopted for the pp chan-nel,which well reproduce the experimental two-neutron separation energies S_(2n)and one-neutron separation energies Sn.It is found that the criterion S_(n)>0 predicts a neutron drip line with neutron numbers much smaller than those for S_(2n)>0.Owing to the unpaired odd neutron,the neutron pairing energies−E_(pair)in odd-A nuclei are much lower than those in the neighbor-ing even-even nuclei.By investigating the single-particle structures,the possible halo structures in the neutron-rich Ca,Ni,and Sn isotopes are predicted,where sharp increases in the root-mean-square(rms)radii with significant deviations from the traditional rA^(1∕3)rule and diffuse spatial density distributions are observed.Analyzing the contributions of various partial waves to the total neutron densityρlj(r)∕ρ(r)reveals that the orbitals located around the Fermi surface-particularly those with small angular momenta-significantly affect the extended nuclear density and large rms radii.The number of neutrons Nλ(N_(0))occupying above the Fermi surfacen(continuum threshold)is discussed,whose evolution as a function of the mass number A in each isotope is consistent with that of the pairing energy,supporting the key role of the pairing correlation in halo phenomena.

Modal Parameter Identification Method of Jacket Platform Structure Based on AFDD and Optimized FBFFT

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.

On the Approximation of Fractal-Fractional Differential Equations Using Numerical Inverse Laplace Transform Methods

Laplace transform is one of the powerful tools for solving differential equations in engineering and other science subjects.Using the Laplace transform for solving differential equations,however,sometimes leads to solutions in the Laplace domain that are not readily invertible to the real domain by analyticalmeans.Thus,we need numerical inversionmethods to convert the obtained solution fromLaplace domain to a real domain.In this paper,we propose a numerical scheme based on Laplace transform and numerical inverse Laplace transform for the approximate solution of fractal-fractional differential equations with orderα,β.Our proposed numerical scheme is based on three main steps.First,we convert the given fractal-fractional differential equation to fractional-differential equation in Riemann-Liouville sense,and then into Caputo sense.Secondly,we transformthe fractional differential equation in Caputo sense to an equivalent equation in Laplace space.Then the solution of the transformed equation is obtained in Laplace domain.Finally,the solution is converted into the real domain using numerical inversion of Laplace transform.Three inversion methods are evaluated in this paper,and their convergence is also discussed.Three test problems are used to validate the inversion methods.We demonstrate our results with the help of tables and figures.The obtained results show that Euler’s and Talbot’s methods performed better than Stehfest’s method.

Powell dynamic identification of displacement parameters of indeterminate thin-walled curve box based on FCSE theory

The FCSE controlling equation of pinned thinwalled curve box was derived and the indeterminate problem of continuous thin-walled curve box with diaphragm was solved based on flexibility theory. With Bayesian statistical theory,dynamic Bayesian error function of displacement parameters of indeterminate curve box was founded. The corresponding formulas of dynamic Bayesian expectation and variance were deduced. Combined with one-dimensional Fibonacci automatic search scheme of optimal step size,the Powell optimization theory was utilized to research the stochastic identification of displacement parameters of indeterminate thin-walled curve box. Then the identification steps were presented in detail and the corresponding calculation procedure was compiled. Through some classic examples,it is obtained that stochastic performances of systematic parameters and systematic responses are simultaneously deliberated in dynamic Bayesian error function. The one-dimensional optimization problem of the optimal step size is solved by adopting Fibonacci search method. And the Powell identification of displacement parameters of indeterminate thin-walled curve box has satisfied numerical stability and convergence,which demonstrates that the presented method and the compiled procedure are correct and reliable.During parameters鈥？iterative processes,the Powell theory is irrelevant with the calculation of finite curve strip element（FCSE） partial differentiation,which proves high computation effciency of the studied method.

Sargent改进的Powell方法在桥梁沉降基础预测中的应用

Sargent改进的Powell方法是曲线拟合中的一种重要方法。本文利用这种方法针对蕴藻浜特大桥沉降中的实测数据给出了五种模型下的沉降预测,这些模型包括双曲线斜率倒数模型、Vander Veen指数模型、宇都一马指数模型、龚帕兹模型、以及波松曲线模型,并发现这种方法对波松旋回模型和灰色系统模型适用性不强。

基于S-CAD方法的四川省单元式乡村国土空间规划政策评价与优化研究

国土空间规划改革以来,各地开展了探索与实践,2021年四川在全省推行以片区为单元编制乡村国土空间规划,是全国第一个在全省范围开展单元式乡村国土空间规划的省域。通过运用S-CAD方法和政策工具分析法对其政策体系进行分析,并结合规划编制成果对政策进行综合评价,发现其存在以下不足:一是政策体系不完善,主要出台了规划编制相关政策,而在规划实施和监督方面缺乏专门政策;二是政策价值观和政策预期结果超出了政策目标和政策手段所能够实现的范围,政策元素之间具有不一致性;三是政策工具结构不平衡,在规划区域衔接、对上衔接等方面非常薄弱。因此,需要进一步完善政策体系、调适政策元素关系、优化政策工具结构。通过这一研究,以期为深化乡村国土空间规划探索提供借鉴。

Stochastic Programming for Hub Energy Management Considering Uncertainty Using Two-Point Estimate Method and Optimization Algorithm

To maximize energy profit with the participation of electricity,natural gas,and district heating networks in the day-ahead market,stochastic scheduling of energy hubs taking into account the uncertainty of photovoltaic and wind resources,has been carried out.This has been done using a new meta-heuristic algorithm,improved artificial rabbits optimization(IARO).In this study,the uncertainty of solar and wind energy sources is modeled using Hang’s two-point estimating method(TPEM).The IARO algorithm is applied to calculate the best capacity of hub energy equipment,such as solar and wind renewable energy sources,combined heat and power(CHP)systems,steamboilers,energy storage,and electric cars in the day-aheadmarket.The standard ARO algorithmis developed to mimic the foraging behavior of rabbits,and in this work,the algorithm’s effectiveness in avoiding premature convergence is improved by using the dystudynamic inertia weight technique.The proposed IARO-based scheduling framework’s performance is evaluated against that of traditional ARO,particle swarm optimization(PSO),and salp swarm algorithm(SSA).The findings show that,in comparison to previous approaches,the suggested meta-heuristic scheduling framework based on the IARO has increased energy profit in day-ahead electricity,gas,and heating markets by satisfying the operational and energy hub limitations.Additionally,the results show that TPEM approach dependability consideration decreased hub energy’s profit by 8.995%as compared to deterministic planning.