Nonlinear Time History Analysis for the Different Column Orientations under Seismic Wave Synthetic Approach

The significant impact of earthquakes on human lives and the built environment underscores the extensive human and economic losses caused by structural collapses. Over the years, researchers have focused on improving seismic design to mitigate earthquake-induced damages and enhance structural performance. In this study, a specific reinforced concrete (RC) frame structure at Kyungpook National University, designed for educational purposes, is analyzed as a representative case. Utilizing SAP 2000, the research conducts a nonlinear time history analysis to assess the structural performance under seismic conditions. The primary objective is to evaluate the influence of different column section designs, while maintaining identical column section areas, on structural behavior. The study employs two distinct seismic waves from Abeno (ABN) and Takatori (TKT) for the analysis, comparing the structural performance under varying seismic conditions. Key aspects examined include displacement, base shear force, base moment, joint radians, and layer displacement angle. This research is anticipated to serve as a valuable reference for seismic restraint reinforcement work on RC buildings, enriching the methods used for evaluating structures through nonlinear time history analysis based on the synthetic seismic wave approach.

Fuzzy Synthetic Evaluation of Water Quality of Naoli River Using Parameter Correlation Analysis

In order to improve the effectiveness of Fuzzy Synthetic Evaluation (FSE) models, a Parameter Correlation Analysis (PCA) was introduced into the FSE and a case study was carried out in the Naoli River in the Sanjiang Plain, Northeast China. The basic principle of the PCA is that the pairs of parameters which are highly correlated and linear with each other would contribute the same information to an assessment and one of them should be eliminated. The method of the PCA is that a correlation relationship among candidate parameters is examined before the FSE. If there is an apparent nonlinear or curvilinear relationship between two parameters, then both will be retained; if the correlation is significant (p<0.01), and the scatter plot suggests a linear relationship, then one of them will be deleted. However, which one will be deleted? For solving this problem, a sensitivity test was conducted and the higher sensitivity parameters remained. The results indicate that the original data should be preprocessed through the PCA for redundancy and variability. The study shows that introducing the PCA into the FSE can simplify the FSE calculation process greatly, while the results have not been changed much.

The Synthetic Effect of Magnetorheological Finishing Technology:Analysis,Modeling,and Control

The controllable key factors in magnetorheological finishing device were studied to determine their influence on efficiency of magnetorheological finishing(MRF)and surface of MRF,as well as interaction between efficiency and surface.Based on theoretical and experimental research,the law of material removal was explored and a new process variable based material removal model(PVMR)was proposed.The experimental findings demonstrate that PVMR reveals the law of the material removal with introduction of three concepts and makes a material removal function z(y i)where the magnetorheological finishing process parameters are considered since they are easy to control and adjust.So the material function of this model is quadratic curve function which is readily suitable for stability and online control magnetorheological finishing.

Application of synthetic principal component analysis model to mine area farmland heavy metal pollution assessment

Referring to GB5618-1995 about heavy metal pollution,and using statistical analysis SPSS,the major pollutants of mine area farmland heavy metal pollution were identified by variable clustering analysis.Assessment and classification were done to the mine area farmland heavy metal pollution situation by synthetic principal components analysis (PCA).The results show that variable clustering analysis is efficient to identify the principal components of mine area farmland heavy metal pollution.Sort and clustering were done to the synthetic principal components scores of soil sample,which is given by synthetic principal components analysis.Data structure of soil heavy metal contaminations relationships and pollution level of different soil samples are discovered.The results of mine area farmland heavy metal pollution quality assessed and classified with synthetic component scores reflect the influence of both the major and compound heavy metal pol- lutants.Identification and assessment results of mine area farmland heavy metal pollution can provide reference and guide to propose control measures of mine area farmland heavy metal pollution and focus on the key treatment region.

Grey relationship analysis and grey forecasting modeling on thermal stability of synthetic single diamond

Through analyzing 7 Ib-type samples of synthetic single diamonds by their DTA and TG in air, we ascertained the extrapolated onset temperature on the curves of DTA as the characteristic temperature of their thermal stabilities. Based on the grey system theory, we analyzed 4 factors influential in the thermal stability by the grey relationship analysis, a quantitative method, and derived the grey relationship sequence, that is, the rank of the influence extent of 4 factors on the thermal stability. Furthermore, we established the grey forecasting model, namely GM(1,5), for predicting the thermal stability of single diamonds with their intrinsic properties, which was then examined by a deviation-probability examination. The results illustrate that it is reasonable to take the Extrapolated Onset Temperature in DTA as the characteristic temperature for thermal stability (TS) of Ib-type synthetic single diamonds. The nitrogen content and grain shape regularity of diamonds are dominating factors. Likewise, grain size and compressive strength are minor factors. In addition, GM(1,5) can be used to predict the thermal stability of Ib-type synthetic single diamonds available. The precision rank of GM(1,5) is ‘GOOD’.

Dimensional analysis of the impact toughness test for synthetic diamond grits

The method,in which a few carats of diamond grits are placed inside a capsule together with a steel ball,shaken for a number of times,and the unbroken ratio of the grits is then used to evaluate the quality of the diamond,has been well established for many years.However,the unbroken percentage,in an equivalent view,represents the impact toughness of the grits and cannot reflect the value of the crushing energy.Most of the previous empirical formulas obtained from experiments by scholars cannot be applied to practical tests.In this paper,a dimensional analysis was applied to investigate the impact toughness experiment,and the dimensionless relationship has been built among those variables such as the toughness index,the impact time,the impact frequency and the crushing energy per unit area.According to the results of a large number of experiments with synthetic diamond grits of mesh size 45/50,the percentage of the broken grits H is proportional to the impact time T^（1.14） when the impact frequency is 2400 r/min,and the impact frequency f^（2.576） when the number of impacts is 2000.

Comparison and Finite Element Analysis of Steel or Synthetic Fiber Reinforced Precast, Prestressed Beams

Usage of fiber reinforced concrete to replace shear reinforcement has become more common in the precast industry in recent years. In some cases, the use of steel fibers could be problematic because of corrosion, hence, synthetic material could be a suitable alternative material solution. Thus, it would appear logical to undertake a comparison of these fibers＇ load bearing capacity to determine suitability in each case. In this paper, the bending and the shear tests of four large-scale and prestressed beams made of steel or synthetic fiber reinforced concrete without stirrups are presented. The post-cracking residual tensile strength diagram of the fibers, according to RILEM （International Union of Laboratories and Experts in Construction Materials, Systems and Structures） TC162, is given and the experimental behavior of the fiber solutions is compared. The modified fracture energy method is used to define an advanced material model for the fiber reinforced concrete in the finite element analysis. The numerical calculations and the test results are compared in terms of crack propagation and the loading-deflect＇ion process. As a consequence, both steel and synthetic fibers seem to be good alternatives to replace the stirrups. However, the behavior of each fiber is not the same. The numerical calculation provided a good approximation for the real scale tests.

Multi-factor analysis of initial poor graft function after orthotopic liver transplantation

BACKGROUND: In the early period of orthotopic liver transplantation (OLT), initial poor graft function (IPGF) is one of the complications which leads to primary graft non-function (PGNF) in serious cases. This study set out to establish the clinical risk factors resulting in IPGF after OLT. METHODS: Eighty cases of OLT were analyzed. The IPGF group consisted of patients with alanine aminotransferase (ALT) and/or aspartate aminotransferase (AST) above 1500 IU/L within 72 hours after OLT, while those in the non-IPGF group had values below 1500 IU/L. Recipient-associated factors before OLT analyzed were age, sex, primary liver disease and Child-Pugh classification; factors analyzed within the peri-operative period were non-heart beating time (NHBT), cold ischemia time (CIT), rewarming ischemic time (RWIT), liver biopsy at the end of cold ischemia; and factors analyzed within 72 hours after OLT were ALT and/or AST values. A logistic regression model was applied to filter the possible factors resulting in IPGF. RESULTS: Donor NHBT, CIT and RWIT were significantly longer in the IPGF group than in the non-IPGF group; in the logistic regression model, NHBT was the risk factor leading to IPGF (P < 0.05), while CIT and RWIT were possible risk factors. In one case in the IPGF group, PGNF appeared with moderate hepatic steatosis. CONCLUSIONS: Longer NHBT is an important risk factor leading to IPGF, while serious steatosis in the donor liver, CIT and RWIT are potential risk factors.

A Hybrid Neural Network Model for Marine Dissolved Oxygen Concentrations Time-Series Forecasting Based on Multi-Factor Analysis and a Multi-Model Ensemble

Dissolved oxygen(DO)is an important indicator of aquaculture,and its accurate forecasting can effectively improve the quality of aquatic products.In this paper,a new DO hybrid forecasting model is proposed that includes three stages:multi-factor analysis,adaptive decomposition,and an optimizationbased ensemble.First,considering the complex factors affecting DO,the grey relational(GR)degree method is used to screen out the environmental factors most closely related to DO.The consideration of multiple factors makes model fusion more effective.Second,the series of DO,water temperature,salinity,and oxygen saturation are decomposed adaptively into sub-series by means of the empirical wavelet transform(EWT)method.Then,five benchmark models are utilized to forecast the sub-series of EWT decomposition.The ensemble weights of these five sub-forecasting models are calculated by particle swarm optimization and gravitational search algorithm(PSOGSA).Finally,a multi-factor ensemble model for DO is obtained by weighted allocation.The performance of the proposed model is verified by timeseries data collected by the pacific islands ocean observing system(PacIOOS)from the WQB04 station at Hilo.The evaluation indicators involved in the experiment include the Nash–Sutcliffe efficiency(NSE),Kling–Gupta efficiency(KGE),mean absolute percent error(MAPE),standard deviation of error(SDE),and coefficient of determination(R^(2)).Example analysis demonstrates that:①The proposed model can obtain excellent DO forecasting results;②the proposed model is superior to other comparison models;and③the forecasting model can be used to analyze the trend of DO and enable managers to make better management decisions.

Multi-factor sensitivity analysis of shallow unsaturated clay slope stability

An unsaturated clay slope, with various sloping angles and a thickness of 14 m, consists of backfill, slope soil and residual soil. Slide interfaces were determined by geophysical approaches and the original slope was reconstructed. Sub-slope masses were classified based on the varieties of sloping angle. A force recursive principle was proposed to calculate the stability coefficient of the sub-slope masses. The influencing factors such as sloping angle, water content, hydrostatic pressure, seismic force as well as train load were analyzed. The range and correlation of the above-mentioned factors were discussed and coupled wave equations were established to reflect the relationships between unit weight, cohesion, internal frictional angle, and water content, as well as between internal frictional angle and cohesion. The sensitivity analysis of slope stability was carried out and susceptive factors were determined when the factors were taken as independent and dependent variables respectively. The results show that sloping angle, water content and earthquake are the principal susceptive factors influencing slope stability. The impact of hydrostatic pressure on slope stability is similar to the seismic force in quantity. Train load plays a small role in slope stability and its influencing only reaches the roadbed and its neighboring slope segment. If the factors are taken as independent variables, the influencing extent of water content and cohesion on slope stability can be weakened and train load can be magnified.

Dynamic synthetic analysis of circulation field of tropical cyclones affecting Shanghai

Eleven tropical cyclones(TCs)affected Shanghai and crossed the same latitude as Shanghai from 2007 to 2018.According to similar tracks from best-track data,TCs that cause significant precipitation in Shanghai can be divided into three types:landfall TCs,nearshore northward TCs,and western TCs.Based on ERA5 reanalysis data,the dynamic synthesis method was used to synthesize TC circulation situations to compare thermal,dynamic,water vapor,and stability conditions within TC circulations during the period when they affected Shanghai.The conclusions are as follows.1)When the three TC types are at the same latitude as Shanghai,they are all in the divergent field in the upper troposphere.For the landfall type,the subtropical high at 500 hPa is stronger and farther north than usual,and there is a high-pressure dam on the north side of the TCs.2)The warm advection of the three TC types at 925 hPa is located in the northern quadrant of the TCs.The dynamic and water vapor conditions are good in the north-western quadrant of landfall and western TCs,and more favorable in the eastern quadrant of nearshore northward TCs.3)The favorable effects of all three types on precipitation in Shanghai come from the boundary layer.Water vapor,upward motion,and instability conditions of landfall TCs are superior to the other two TC types.The best water vapor,dynamic,and convective instability conditions are at the northern boundary in Shanghai during landfall TCs,and the main sources of water vapor in Shanghai come from the eastern and northern boundaries.During nearshore northward TCs,the main contribution to precipitation is from the eastern boundary,while better dynamic and water vapor conditions come from the western and northern boundaries during western TCs.The above findings provide scientific and technical support for operational forecasting precipitation from TCs affecting mega-cities.

Thermal oxidation of two aviation synthetic lubricant base oils

The thermal degradation of two synthetic lubricants base oils, poly-a-olefins （PAO） and di-esters （DE）, was investigated under oxidative pyrolysis condition and their properties were characterized in simulated ＂areo-engine＂ by comparing the thermal stability and identifying the products of thermal decomposition as a function of exposure temperature. The characterization of the products were performed by means of Fourier transform infrared spectrometry （FTIR）, gas chromatography/mass spectrometry （GC/MS） and viscosity experiments. The results show that PAO has the lower thermal stability, being degraded at 200℃ different from 300 ℃ for DE. Several by-products are identified during the thermal degradation of two lubricant base oils. The majority of PAO products consist of alkenes and olefins, while more oxygen-contained organic compounds are detected in DE samples based on GC/MS analysis. The related reaction mechanisms are discussed based on the experimental results.

Joint multivariate statistical model and its applications to synthetic earthquake predic-tion

针对目前地震综合预报中的一些问题，利用近30年来迅速发展的多元统计分析中主成分分析、判别分析组成多元统计组合模型，在众多的地震预报指标(预报因子)中采用信息最大化方法，选择对中期预测信息累积贡献率大于90％地震预报指标，分别进行相关分析、预测、检验，最终应用马氏距离判别作外推综合预报；并以华北地区(30°～42°N，108°125°E)为例进行模型的应用检验，初步研究已取得了较好的效果．

CO_2 Density-Raman Shift Relation Derived from Synthetic Inclusions in Fused Silica Capillaries and Its Application

The densities of CO2 inclusions in minerals are commonly used to determine the crystallizing conditions of the host minerals. However, conventional microthermometry is difficult to apply for inclusions of small size （〈 5-10 μm） or low density. Raman analysis is an alternative method for determining CO2 density, provided that the CO2 density-Raman shift relation is known. This study aims to establish this CO2 density-Raman shift relation by using CO2 inclusions synthesized in fused silica capillaries. By using this newly-developed synthetic technique, we formed pure CO2 inclusions, and their densities were determined by microthermometry. The Raman analysis showed that the relation between CO2 density （D in g/cm^3） and the separations （△ in cm^-1） between the two main bands （i.e. Fermi diad bands） in CO2 Raman spectra can be represented by a cubic equation： D （g/cm^3）=0.74203（-0.019^3＋5.90332△^2-610.79472△＋21050.30165）-3.54278 （r^2=0.99920）. Our calculated D value for a given A is between those obtained from two previously-reported equations, which were derived from different experimental methods. An example was given in this study to demonstrate that the densities of natural CO2 inclusions that could not be derived from microthermometry could be determined by using our method.

SAR image denoising based on wavelet-fractal analysis

Wavelet-fractal based SAR （synthetic aperture radar） image processing is one of the advanced technologies in image processing. The main concept of analysis is that after wavelet transformation, multifractal spectrum of the signal is different from that of noise. This difference is used to alleviate the noise produced by SAR image.The method to denoise SAR image using the process based on wavelet-fractai analysis is discussed in detail. Essentially, the present method focuses on adjusting the Hoelder exponent α of multifractal spectrum. After simulation, α should be adjusted to 1.72-1.73. The more the value of α exceeds 1.73, the less distinctive the edges of SAR image become. According to the authors denoising is optimal at α=1.72-1.73. In other words, when α =1.72-1.73, a smooth and denoised SAR image is produced.

Analysis of the Quality of Daily DEM Generation with Geosynchronous InSAR

Up-to-date digital elevation model(DEM)products are essential in many fields such as hazards mitigation and urban management.Airborne and low-earth-orbit(LEO)space-borne interferometric synthetic aperture radar(InSAR)has been proven to be a valuable tool for DEM generation.However,given the limitations of cost and satellite repeat cycles,it is difficult to generate or update DEMs very frequently(e.g.,on a daily basis)for a very large area(e.g.,continental scale or greater).Geosynchronous synthetic aperture radar(GEOSAR)satellites fly in geostationary earth orbits,allowing them to observe the same ground area with a very short revisit time(daily or shorter).This offers great potential for the daily DEM generation that is desirable yet thus far impossible with space-borne sensors.In this work,we systematically analyze the quality of daily GEOSAR DEM.The results indicate that the accuracy of a daily GEOSAR DEM is generally much lower than what can be achieved with typical LEO synthetic aperture radar(SAR)sensors;therefore,it is important to develop techniques to mitigate the effects of errors in GEOSAR DEM generation.

SAR tomography imaging via higher-order spectrum analysis

To deal with the non-Caussian noise in standard 2-D SAR images, the deramped signal in imaging plane, and the possible symmetric distribution of complex noise, the fourth-order cumulant of complex process is introduced into SAR tomography. With the estimated AR parameters of ARMA model of noise through Yule-Walker equation, the signal series of height is pre-filtered. Then, through ESPRIT, the spectrum is obtained and the aperture in height direction is synthesized. Finally, the SAR tomography imaging of scene is achieved. The results of processing on signal with non-Gaussian noise demonstrate the robustness of the proposed method. The tomography imaging of the scenes shows that the higher-order spectrum analysis is feasible in the application.

Seismic reliability assessment of a steel moment-resisting frame with two different ductility levels using a cloud analysis approach

A cloud method for generating percentile engineering demand parameter versus intensity measure(EDP-IM) curves of a structure subjected to a set of synthetic ground motions is presented. To this end, an ensemble of synthetic ground motions based on available real ones is generated. This is done by using attenuation relationships, duration and suitable Gutenberg-Richter relations attributed to the considered seismic hazard at a given site by estimating a suitable distribution of magnitude and site to source distance. The study aims to clarify the significance of the duration and frequency content on the seismic performance of structures, which were not considered in developing percentile incremental dynamic analysis(IDA) curves. The collapse probabilities of two steel moment-resisting frames with different ductility levels generated by IDA and the proposed cloud method are compared at different intensity levels. When compared with conventional IDA, the suggested cloud analysis(SCA) methodology with the same run number of dynamic analyses was able to develop response hazard curves that were more consistent with site-specific seismic hazards. Eliminating the need to find many real records by generating synthetic records consistent with site-specific seismic hazards from a few available recorded ground motions is another advantage of using this scheme over the IDA method..

NEW SAR IMAGE INTERPRETATION METHOD OF AIRCRAFT BASED ON JOINT TIME-FREQUENCY ANALYSIS

With the continuous improvement of Synthetic Aperture Radar(SAR) resolution, interpreting the small targets like aircraft in SAR images becomes possible and turn out to be a hot spot in SAR application research. However, due to the complexity of SAR imaging mechanism, interpreting targets in SAR images is a tough problem. This paper presents a new aircraft interpretation method based on the joint time-frequency analysis and multi-dimensional contrasting of basic structures. Moreover, SAR data acquisition experiment is designed for interpreting the aircraft. Analyzing the experiment data with our method, the result shows that the proposed method largely makes use of the SAR data information. The reasonable results can provide some auxiliary support for the SAR images manual interpretation.