Response Spectrum Analysis of 7-story Assembled Frame Structure with Energy Dissipation System

Viscoelastic damper is an effective passive damping device,which can reduce the seismic response of the structure by increasing the damping and dissipating the vibration energy of structures.It has a wide application prospect in actual structural vibration control because of simple device and economical material.In view of the poor seismic behaviors of assembled frame structure connections,various energy dissipation devices are proposed to improve the seismic performance.The finite element numerical analysis method is adopted to analyze relevant energy dissipation structural parameters.The response spectrum of a 7-story assembled frame structure combined the ordinary steel support,ordinary viscoelastic damper,and viscoelastic damper with displacement amplification device is analyzed.The analysis results show that the mechanical behavior of assembled frame structure with ordinary steel supports are not significantly different from those without energy dissipation devices.The assembled frame structure with viscoelastic damper has better seismic performance and energy dissipation,especially for the viscoelastic damper with displacement amplification devices.The maximum value of inter-story displacement angle decreases by 32.24%;the maximum floor displacement decreases by 31.91%,and the base shear decreases by 13.62%compared with the assembled frame structures without energy dissipation devices.The results show that the seismic fortification ability of the structure is significantly improved,and the overall structure is more uniformly stressed.The damping structure with viscoelastic damper mainly reduces the dynamic response of the structure by increasing the damping coefficient,rather than by changing the natural vibration period of the structure.This paper provides an effective theoretical basis and reference for improving the energy dissipation system and the seismic performance of assembled frame structures.

Quantitative energy-dispersive X-ray fluorescence analysis for unknown samples using full-spectrum least-squares regression

The full-spectrum least-squares(FSLS) method is introduced to perform quantitative energy-dispersive X-ray fluorescence analysis for unknown solid samples.Based on the conventional least-squares principle, this spectrum evaluation method is able to obtain the background-corrected and interference-free net peaks, which is significant for quantization analyses. A variety of analytical parameters and functions to describe the features of the fluorescence spectra of pure elements are used and established, such as the mass absorption coefficient, the Gi factor, and fundamental fluorescence formulas. The FSLS iterative program was compiled in the C language. The content of each component should reach the convergence criterion at the end of the calculations. After a basic theory analysis and experimental preparation, 13 national standard soil samples were detected using a spectrometer to test the feasibility of using the algorithm. The results show that the calculated contents of Ti, Fe, Ni, Cu, and Zn have the same changing tendency as the corresponding standard content in the 13 reference samples. Accuracies of 0.35% and 14.03% are obtained, respectively, for Fe and Ti, whose standard concentrations are 8.82% and 0.578%, respectively. However, the calculated results of trace elements (only tens of lg/g) deviate from the standard values. This may be because of measurement accuracy and mutual effects between the elements.

Theoretical research on structural damage alarming of long-span bridges using wavelet packet analysis

The state equation and observation equation of the structural dynamic systems under various analysis scales are derived based on wavelet packet analysis. The time-frequency properties of structural dynamic response under various scales are further formulated. The theoretical analysis results reveal that the wavelet packet energy spectrum （WPES） obtained from wavelet packet decomposition of structural dynamic response will detect the presence of structural damage. The sensitivity analysis of the WPES to structural damage and measurement noise is also performed. The transfer properties of the structural system matrix and the observation noise under various analysis scales are formulated, which verify the damage alarming reliability using the proposed WPES with preferable damage sensitivity and noise robusticity.

Freak wave simulation based on nonlinear model and the research on the time-frequency energy spectrum of simulation results

VOF （volume of fluid） method has been used to make the numerical simulation of freak wave come true. The comparisons between the numerical results and linear theoretical results corresponding to Eq.（5） have been carried out to show that the numerical results have a better exhibition of nonlinear characteristics. Wavelet analysis method has been adopted to investigate the time-frequency energy spectrum of simulation freak waves and the results reveal strong nonlinear interaction enables energy to be transferred to high harmonics during the progress of its formation. Varying water depth can enhance the nonlinear interaction, making much more energy be transferred to high harmonics and freak waves with higher asymmetry be generated.

Structural health monitoring of long-span suspension bridges using wavelet packet analysis

During the service life of civil engineering structures such as long-span bridges, local damage at key positions may continually accumulate, and may finally result in their sudden failure. One core issue of global vibration-based health monitoring methods is to seek some damage indices that are sensitive to structural damage, This paper proposes an online structural health monitoring method for long-span suspension bridges using wavelet packet transform （WPT）. The WPT- based method is based on the energy variations of structural ambient vibration responses decomposed using wavelet packet analysis. The main feature of this method is that the proposed wavelet packet energy spectrum （WPES） has the ability to detect structural damage from ambient vibration tests of a long-span suspension bridge. As an example application, the WPES-based health monitoring system is used on the Runyang Suspension Bridge under daily environmental conditions. The analysis reveals that changes in environmental temperature have a long-term influence on the WPES, while the effect of traffic loadings on the measured WPES of the bridge presents instantaneous changes because of the nonstationary properties of the loadings. The condition indication indices VD reflect the influences of environmental temperature on the dynamic properties of the Runyang Suspension Bridge. The field tests demonstrate that the proposed WPES-based condition indication index VD is a good candidate index for health monitoring of long-span suspension bridges under ambient excitations.

Study on element detection and its correction in iron ore concentrate based on a prompt gamma-neutron activation analysis system

A prompt gamma-neutron activation analysis(PGNAA) system was developed to detect the iron content of iron ore concentrate. Because of the self-absorption effect of gamma-rays and neutrons, and the interference of chlorine in the neutron field, the linear relationship between the iron analytical coefficient and total iron content was poor, increasing the error in the quantitative analysis. To solve this problem, gamma-ray self-absorption compensation and a neutron field correction algorithm were proposed, and the experimental results have been corrected using this algorithm. The results show that the linear relationship between the iron analytical coefficient and total iron content was considerably improved after the correction. The linear correlation coefficients reached 0.99 or more.

Analysis of Turbulence Structure in the Stirred Tank with a Deep Hollow Blade Disc Turbine by Time-resolved PIV

The turbulence structure in the stirred tank with a deep hollow blade(semi-ellispe) disc turbine(HEDT) was investigated by using time-resolved particle image velocimetry(TRPIV) and traditional PIV.In the stirred tank,the turbulence generated by blade passage includes the periodic components and the random turbulent ones.Traditional PIV with angle-resolved measurement and TRPIV with wavelet analysis were both used to obtain the random turbulent kinetic energy as a comparison.The wavelet analysis method was successfully used in this work to separate the random turbulent kinetic energy.The distributions of the periodic kinetic energy and the random turbulent kinetic energy were obtained.In the impeller region,the averaged random turbulent kinetic energy was about 2.6 times of the averaged periodic one.The kinetic energies at different wavelet scales from a6 to d1 were also calculated and compared.TRPIV was used to record the sequence of instantaneous velocity in the impeller stream.The evolution of the impeller stream was observed clearly and the sequence of the vorticity field was also obtained for the identification of vortices.The slope of the energy spectrum was approximately-5/3 in high frequency representing the existence of inertial subrange and some isotropic properties in stirred tank.From the power spectral density(PSD) ,one peak existed evidently,which was located at f0(blade passage frequency) generated by the blade passage.

A novel approach for feature extraction from a gamma‑ray energy spectrum based on image descriptor transferring for radionuclide identification

This study proposes a novel feature extraction approach for radionuclide identification to increase the precision of identification of the gamma-ray energy spectrum set.For easier utilization of the information contained in the spectra,the vectors of the gamma-ray energy spectra from Euclidean space,which are fingerprints of the different types of radionuclides,were mapped to matrices in the Banach space.Subsequently,to make the spectra in matrix form easier to apply to image-based deep learning frameworks,the matrices of the gamma-ray energy spectra were mapped to images in the RGB color space.A deep convolutional neural network(DCNN)model was constructed and trained on the ImageNet dataset.The mapped gamma-ray energy spectrum images were applied as inputs to the DCNN model,and the corresponding outputs of the convolution layers and fully connected layers were transferred as descriptors of the images to construct a new classification model for radionuclide identification.The transferred image descriptors consist of global and local features,where the activation vectors of fully connected layers are global features,and activations from convolution layers are local features.A series of comparative experiments between the transferred image descriptors,peak information,features extracted by the histogram of the oriented gradients(HOG),and scale-invariant feature transform(SIFT)using both synthetic and measured data were applied to 11 classical classifiers.The results demonstrate that although the gamma-ray energy spectrum images are completely unfamiliar to the DCNN model and have not been used in the pre-training process,the transferred image descriptors achieved good classification results.The global features have strong semantic information,which achieves an average accuracy of 92.76%and 94.86%on the synthetic dataset and measured dataset,respectively.The results of the statistical comparison of features demonstrate that the proposed approach outperforms the peak-searching-based method,HOG,and SIFT on the synthetic and measured datasets.

新能源汽车电池的在线监测与原位分析技术

为控制新能源汽车电池耗电量,并对其电能消耗行为进行原位分析,针对新能源汽车电池的在线监测与原位分析技术展开研究。完善动力锂电池组结构模型,根据汽车电池的热耦合特性,推导监测核函数,实现新能源汽车电池的在线监测。在此基础上,确定汽车电池的电极材料,并分别从表征特性、拉曼光谱两个角度,对其电池元件的原位特性进行研究。

无人机载CeBr3航空监测系统无限大面源探测能力研究

在核设施发生重大事故后,快速获取事故应急区内的辐射水平,对后续应急决策及救援、保护公众免受辐射危害具有至关重要的意义,核应急航空辐射监测是核应急早期快速获取辐射水平的重要技术手段和方法之一,因此核工业航测遥感中心自主研发了无人机载CeBr3航空监测系统。为准确评估该监测系统的探测能力,文章使用蒙特卡罗方法对该监测系统进行了建模,并通过60Co点源对模型的准确性进行了验证。在此基础上,采用全能谱分析、蒙特卡罗及实验相结合的方法获得监测系统对天然辐射单位能谱,并以核事故后地面受到一个新的137Cs放射性沉降场景为例,计算监测系统在不同测量条件下(天然辐射本底、晶体体积、测量高度)对无限大137Cs面源的探测效率及最小可探测活度浓度。通过模拟及计算监测系统对天然辐射本底及核应急人工放射性核素的单位能谱,准确评估了自研的无人机载CeBr3核应急航空监测系统的探测能力,为后续利用该监测系统开展核与辐射航空监测可提供重要理论依据及数据支撑。

不同产地蓝铜矿矿物学及谱学特征研究

蓝铜矿是含铜的碳酸盐矿物,它产于铜矿床的氧化带,是一种次生矿物,因此蓝铜矿的出现可作为寻找原生铜矿床的标志。国内学者对蓝铜矿的谱学研究比较少,且对世界不同著名产地蓝铜矿矿物学与谱学特征对比是空白区。通过扫描电镜能谱分析仪、粉晶X射线衍射仪、同步热分析仪、红外光谱仪等仪器对2块中国产地蓝铜矿矿物样品(安徽六峰山、广东阳春)与2块外国产地蓝铜矿矿物样品(老挝、澳大利亚)的成分、结构及谱学特征进行了分析与探讨。能谱元素分析结果显示4块矿物样品的主要元素为C、O、Cu三种元素。X衍射结果表明除产于安徽六峰山矿物外,其他3种产地矿物X衍射物相分析结果均为蓝铜矿Cu_(3)(OH)_(2)(CO_(3))_(2)。产于安徽六峰山矿物除了主物相蓝铜矿的衍射峰外,在其他位置也检测出衍射峰,表明产于安徽六峰山的矿物含有第二物相孔雀石CuCO_(3)·Cu(OH)_(2)。从同步热分析仪热重曲线可以看出主要有两个失重台阶,300℃之前的失重可能是蓝铜矿中含有小部分的孔雀石的分解失重,而300~600℃的失重对应的是蓝铜矿的分解失重。从红外光谱上看主要的红外峰为蓝铜矿的特征峰,四个不同产地的红外光谱比较相似。结合蓝铜矿的外观特征,可为不同产地蓝铜矿的产地鉴定和检测提供依据。

沥青老化前后宏-微观性能相关性

为探索沥青老化过程中微观结构变化对其宏观力学性能的内在影响机制,结合动态剪切流变仪测定的流变学参数与红外光谱仪及荧光显微镜获取的化学官能团和微观结构数据,揭示了基质沥青与SBS改性沥青在不同老化阶段的宏-微观性能关联。研究发现,SBS改性沥青的微观空间网络结构赋予其卓越的黏弹特性。识别了SBS改性剂特有的红外光谱特征峰,为快速识别和评估SBS改性沥青提供了一种方法。通过灰色关联度分析,发现官能团指数与复数剪切模量的关联度排序为:亚砜基官能团指数>芳香环官能团指数>羰基官能团指数,与沥青表面能的关联度顺序为:芳香环官能团指数>羰基官能团指数>亚砜基官能团指数。研究进一步证实,沥青老化过程中官能团的氧化和微观形貌的重构是影响其复数剪切模量变化的关键因素,为沥青材料的老化行为提供了新的理论解释。

通道奇异谱分析的绿色建筑能耗预测方法仿真

建筑能耗受到外部环境、用户行为等因素的影响,这些因素难以准确预测或低频率更新,使得能耗预测存在一定的不确定性。为了得到高准确率的绿色建筑能耗预测结果,提出一种面向绿色建筑的能耗贝叶斯预测方法。通过多通道奇异谱分析(MSSA)对历史绿色建筑能耗数据去噪,将去噪后的数据作为训练样本。利用训练样本展开目标定位和搜索,对获取的目标展开特征提取,根据获取的目标特征和目标身份之间的关联关系建立能耗贝叶斯预测模型,通过相关判决条件,输出目标预测结果,完成绿色建筑能耗预测。仿真结果表明,所提方法可以获取高准确率的绿色建筑能耗预测结果,同时具有良好的数据去噪能力。

基于SSA-LSTM模型的水电站能效综合评价方法

随着我国电力体制改革不断深化,水电已告别传统粗放型发展模式,亟需配套更为成熟、通用的能效评价体系指导水电运行调度工作。因此,提出一种基于深度学习的水电站能效综合评价方法,引入长短期记忆网络(LSTM)构建水电站理论发电量模型,对于给定的原始发电序列,利用奇异谱分析(SSA)提取出其趋势项、周期项及噪声,对前二者分别构建LSTM网络模拟后叠加得到理论发电量计算结果,在此基础上提出相对增发效益指标、能效相对提高率指标,利用熵权法得到水电站综合得分值,进而对南部某省12座电站进行能效评价。结果表明,该方法可以充分反映水电在调度运行中的能效特点,研究结果对优化水电站调度策略、提高水电调度水平具有借鉴意义。

Sizing of Energy Storage Systems for Output Smoothing of Renewable Energy Systems

光伏、风力发电等可再生能源（renewable energysources，RESs）具有随机性、间歇性等特点。为了抑制RESs输出波动对电网的不利影响，提出了用于平滑RESs发电系统功率输出的储能系统（energy storage system，ESS）容量优化确定方法。利用离散傅里叶变换（discrete Fouriertransform，DFT）对RESs输出功率进行频谱分析，基于频谱分析结果，考虑ESS充放电效率、荷电状态（stateofcharge，soc）及RESs发电系统目标功率输出波动率的约束，确定所需ESS最小容量。采用美国华盛顿州实际观测风速数据及日本东北电力公司风电场接入电网20rnin有功功率波动规范（最大波动率为10％），在一风力发电系统中对该方法进行了验证。算例结果表明采用该方法能够以较小的容量将风机输出最大波动率由61．7％降到9．9％。

一种测定煤储层水相赋存空间的新方法

提出一种基于扫描电子显微镜和能谱分析相结合的含气煤样水相空间分布特征测试方法,采用新方法开展沁南盆地高阶煤样品水相赋存特征试验。结果表明:测试结果与核磁共振试验结果吻合性较好,验证了新方法的可靠性;煤岩微孔(孔径小于2 nm)和介孔(孔径为2~5 nm)多为疏水性壁面,水相在毛管阻力作用力影响下难以进入孔径约20 nm以下的孔隙和裂隙中;与现有核磁共振试验等方法相比,新方法具有测试流程简便、成本低廉等优势。

物相定性分析的综合实验设计与实践

物相定性分析主要用来判定物质组成及其存在状态,是材料、化工和地质等学科专业学生必须掌握的综合性实验技能。为培养学生对材料的物相分析测试能力,设计了未知粉末物相定性分析的综合实验。以氧钼矿、黑铜矿、斜锆石和六方软锰矿的混合粉末作为盲样,依据X射线衍射和能谱元素结果,通过实验数据和综合解析推导,撰写实验分析报告,全面提高学生的仪器操作和数据分析能力。

放射性同位素分离在线检测软件设计与实现

核素分离是放射性同位素制备的关键技术之一,其中快速准确地判断目标核素的分离情况对同位素分离十分重要。本研究针对放射性同位素分离典型过程,基于闪烁体探测器设计和开发了一款放射性同位素分离在线检测软件,用于测量分离过程中管路内流动的放射性情况,包括计数率、放射性核素组成。测量信号传输至分离装置控制系统,进行分析、处理、显示。核素判别中利用序贯贝叶斯核素识别算法,并基于遗传算法优化卡尔曼滤波器,实现更优的参数估计,准确快速地判别混合物中特定放射性核素,提高核素分离过程的效率和准确性。该软件基于串口通信实现设备与系统之间的数据传输,实现了数据采集、实时测量、可视化显示、γ能谱绘制、γ能谱分析、系统设置、流程控制、核素识别等功能,软件界面简洁,经实验测试,运行稳定,人机交互友好,具有较好的实用性和可维护性,可为放射性同位素分离制备在线检测提供技术参考。

船模水动力噪声及孔腔激励载荷试验与计算对比分析

开展某远洋客船光体船模水下噪声测试及带孔腔船模的水动力激励载荷测试,并进行孔腔处稳态和瞬态流场计算,孔腔处脉动压力频谱计算曲线与试验曲线吻合较好。孔腔脉动压力线谱频率测试值与经验公式频率计算值对比良好,说明该公式在一定情况下适用于船体条形格栅孔腔线谱频率的预估。采用统计能量法分析法计算光体船模中高频流激噪声,将流体激励以频率-波数功率谱的形式施加,可大大减少流场计算工作量,适合于工程快速预估。在工程一般范围内,阻尼损耗因子取值可导致噪声结果相差5.5 dB,说明阻尼损耗因子的取值会较大影响计算结果,有必要形成材料损耗因子随频率变化的数据库,为船舶噪声快速计算提供支撑。