• Animal Bioscience
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• v.36 no.2
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• pp.256-263
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• 2023

Objective: Feed molecular structures can affect its availability to gastrointestinal enzymes which impact its digestibility and absorption. The molecular spectroscopy-attenuated total reflectance Fourier transform infrared vibrational spectroscopy (ATR-FTIR) is an advanced technique that measures the absorbance of chemical functional groups on the infrared region so that we can identify and quantify molecules and functional groups in a feed. The program aimed to reveal the association of intrinsic molecular structure with nutrient supply to animals from canola feedstocks and co-products from bio-oil processing. The objective of this study was to characterize special intrinsic carbohydrate and protein-related molecular structure spectral profiles of feedstock and co-products (meal and pellets) from bio-oil processing from two source origins: Canada (CA) and China (CH). Methods: The samples of feedstock and co-products were obtained from five different companies in each country arranged by the Canola Council of Canada (CCC). The molecular structure spectral features were analyzed using advanced vibrational molecular spectroscopy-ATR-FTIR. The spectral features that accessed included: i) protein-related spectral features (Amide I, Amide II, α-helix, β-sheet, and their spectral intensity ratios), ii) carbohydrate-related spectral features (TC1, TC2, TC3, TC4, CEC, STC1, STC2, STC3, STC4, TC, and their spectral intensity ratios). Results: The results showed that significant differences were observed on all vibrationally spectral features related to total carbohydrates, structural carbohydrates, and cellulosic compounds (p<0.05), except spectral features of TC2 and STC1 (p>0.05) of co-products, where CH meals presented higher peaks of these structures than CA. Similarly, it was for the carbohydrate-related molecular structure of canola seeds where the difference between CA and CH occurred except for STC3 height, CEC and STC areas (p>0.05). The protein-related molecular structures were similar for the canola seeds from both countries. However, CH meals presented higher peaks of amide I, α-helix, and β-sheet heights, α-helix:β-sheet ratio, total amide and amide I areas (p<0.05). Conclusion: The principal component analysis was able to explain over 90% of the variabilities in the carbohydrate and protein structures although it was not able to separate the samples from the two countries, indicating feedstock and coproducts interrelationship between CH and CA.

• Structural Engineering and Mechanics
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• v.81 no.2
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• pp.219-230
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• 2022

Due to the large number of railway bridges along China's high-speed railway (HSR) lines, which cover a wide area with many lines crossing the seismic zone, the possibility of a HSR train running over a bridge when an earthquake occurs is relatively high. Since the safety performance of the train will be threatened, it is necessary to study the safety of trains running over HSR bridges during earthquakes. However, ground motion (GM) is highly random and selecting the appropriate ground-motion intensity measures (IMs) for train running safety analysis is not trivial. To deal this problem, a model of a coupled train-bridge system under seismic excitation was established and 104 GM samples were selected to evaluate the correlation between 16 different IMs and train running safety over HSR bridges during earthquakes. The results show that spectral velocity (SvT₁) and displacement (SdT₁) at the fundamental period of the structure have good correlation with train running safety for medium-and long-period HSR bridges, and velocity spectrum intensity (VSI) and Housner intensity (HI) have good correlation for a wide range of structural periods. Overall, VSI and HI are the optimal IMs for safety analysis of trains running over HSR bridges during earthquakes. Finally, based on VSI and HI, the IM thresholds of an HSR bridge at different speed were analyzed.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.18-21
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• 2008

Lee (2008) proposed the pansharpening method to reconstruct at the higher resolution the multispectral images which agree with the spectral values observed from the sensor of the lower resolution values. It outperformed over several current techniques for the statistical analysis with quantitative measures, and generated the imagery of good quality for visual interpretation. However, if a small object stretches over two adjacent pixels with different spectral characteristics at the lower resolution, the pixels of the object at the higher resolution may have different multispectral values according to their location even though they have a same intensity in the panchromatic image of higher resolution. To correct this problem, this study employed an iterative technique similar to the image restoration scheme of Point-Jacobian iterative MAP estimation. The effect of pansharpening on image segmentation/classification was assessed for various techniques. The method was applied to the IKONOS image acquired over the area around Anyang City of Korea.

• Structural Engineering and Mechanics
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• v.23 no.4
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• pp.409-430
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• 2006

The aim of this study is to investigate the reliability of strong motion records processed by causal and acausal Butterworth filters in comparison to the results obtained from a synthetic accelerogram. For this purpose, the fault parallel component of the Bolu record of the Duzce earthquake is modeled with a sum of exponentially damped sinusoidal components. Noise-free velocities and displacements are then obtained by analytically integrating the synthetic acceleration model. The analytical velocity and displacement signals are used as a standard with which to judge the validity of the signals obtained by filtering with causal and acausal filters and numerically integrating the acceleration model. The results show that the acausal filters are clearly preferable to the causal filters due to the fact that the response spectra obtained from the acausal filters match the spectra obtained from the simulated accelerogram better than that obtained by causal filters. The response spectra are independent from the order of the filters and from the method of integration (whether analytical integration after a spline fit to the synthetic accelerogram or the trapezoidal rule). The response spectra are sensitive to the chosen corner frequency of both the causal and the acausal filters and also to the inclusion of the pads. Accurate prediction of the static residual displacement (SRD) is very important for structures traversing faults in the near-fault regions. The greatest adverse effect of the high pass filters is their removal of the SRD. However, the noise-free displacements obtained by double integrating the synthetic accelerogram analytically preserve the SRD. It is thus apparent that conventional high pass filters should not be used for processing near-fault strong-motion records although they can be reliably used for far-fault records if applied acausally. The ground motion parameters such as ARIAS intensity, HUSID plots, Housner spectral intensity and the duration of strong-motion are found to be insensitive to the causality of filters.

• Journal of Biosystems Engineering
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• v.33 no.5
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• pp.355-361
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• 2008

As agricultural machinery has become larger and tillage practices have changed in recent decades, compaction as a result of wheel traffic and tillage has caused increasing concern. If strategies to manage compaction, such as deep tillage, could be applied only where needed, economic and environmental benefits would result. For such site-specific compaction management to occur, compacted areas within fields must be efficiently sensed and mapped. We previously developed an on-the-go soil strength profile sensor (SSPS) for this purpose. The SSPS measures within-field variability in soil strength at five soil depths up to 50 cm. Determining the variability structure of SSPS data is needed for site-specific field management since the variability structure determines the required intensity of data collection and is related to the delineation of compaction management zones. In this paper, soil bin data were analyzed by a spectral analysis technique to determine the variability structure of the SSPS data, and to investigate causes and implications of this variability. In the soil bin, we observed a repeating pattern due to soil fracture with an approximate 12- to 19-cm period, especially at the 10-cm depth, possibly due to cyclic development of soil fracture on this interval. These findings will facilitate interpretation of soil strength data and enhance application of the SSPS.

• Journal of the Earthquake Engineering Society of Korea
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• v.7 no.6
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• pp.35-47
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• 2003

Seismic ground motion can vary significantly over distances comparable to the length of a majority of highway bridges on multiple supports. This paper presents results of fragility analysis of two actual highway bridges under ground motion with spatial variation. Ground motion time histories are artificially generated with different amplitudes, phases, as well as frequency contents at different support locations. Monte Carlo simulation is performed to study dynamic responses of the bridges under these ground motions. The effect of spatial variation on the seismic response is systematically examined and the resulting fragility curves are compared with those under identical support ground motion. This study shows that ductility demands for the bridge columns can be underestimated if the bridge is analyzed using identical support ground motions rather than differential support ground motions. Fragility curves are developed as functions of different measures of ground motion intensity including peak ground acceleration(PGA), peak ground velocity(PGV), spectral acceleration(SA), spectral velocity(SV) and spectral intensity(SI). This study represents a first attempt to develop fragility curves under spatially varying ground motion and provides information useful for improvement of the current seismic design codes so as to account for the effects of spatial variation in the seismic design of long-span bridges.

• Earthquakes and Structures
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• v.14 no.6
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• pp.577-587
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• 2018

The quantitative assessment of the seismic collapse risk of a structure requires the usage of an optimal intensity measure (IM) which can adequately characterise the severity of the ground motion. Research suggests that the average spectral acceleration ($Sa_{avg}$) may be an efficient and sufficient alternate IM as compared to the more traditional first mode spectral acceleration, $Sa(T_1)$, particularly during seismic collapse risk estimation. This study primarily presents a comparative evaluation of the sufficiency of the average spectral acceleration with respect to ground motion duration, and secondarily assesses the impact of ground motion duration on collapse risk estimation. By assembling a suite of 100 historical ground motions, incremental dynamic analysis of 60 different inelastic single-degree-of-freedom (SDF) oscillators with varying periods and ductility capacities were analysed, and collapse risk estimates obtained. Linear regression models are used to comparatively quantify the sufficiency of $Sa_{avg}$ and $Sa(T_1)$ using four significant duration metrics. Results suggests that an improved sufficiency may exist for $Sa_{avg}$ when the period of the SDF system increases, particularly beyond 0.5, as compare to $Sa(T_1)$. In reference to the ground motion duration measures, results indicated that the sufficiency of $Sa_{avg}$ is more sensitive to significant duration definitions that consider almost the full wave train of an accelerogram ($SD_{a5-95}$ and $SD_{v5-95}$). In order to obtain a reduced variability of the collapse risk estimate, the 5-95% significant duration metric defined using the Arias integral ($SD_{a5-95}$) should be used for seismic collapse risk estimation in conjunction with $Sa_{avg}$.

• Earthquakes and Structures
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• v.7 no.4
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• pp.485-510
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• 2014

In performance-based seismic design procedures Peak Ground Acceleration (PGA) and pseudo-Spectral acceleration ($S_a$) are commonly used to predict the response of structures to earthquake. Recently, research has been carried out to evaluate the predictive capability of these standard Intensity Measures (IMs) with respect to different types of structures and Engineering Demand Parameter (EDP) commonly used to measure damage. Efforts have been also spent to propose alternative IMs that are able to improve the results of the response predictions. However, most of these IMs are not usually employed in probabilistic seismic demand analyses because of the lack of reliable Ground Motion Prediction Equations (GMPEs). In order to define seismic hazard and thus to calculate demand hazard curves it is essential, in fact, to establish a GMPE for the earthquake intensity. In the light of this need, new GMPEs are proposed here for the elastic input energy spectra, energy-based intensity measures that have been shown to be good predictors of both structural and non-structural damage for many types of structures. The proposed GMPEs are developed using mixed-effects models by empirical regressions on a large number of strong-motions selected from the NGA database. Parametric analyses are carried out to show the effect of some properties variation, such as fault mechanism, type of soil, earthquake magnitude and distance, on the considered IMs. Results of comparisons between the proposed GMPEs and other from the literature are finally shown.

• Nuclear Engineering and Technology
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• v.52 no.1
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• pp.192-205
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• 2020

Seismic design practices and seismic response analyses of civil structures and nuclear power plants (NPPs) have conventionally used the peak ground acceleration (PGA) or spectral acceleration (S_a) as an intensity measure (IM) of an earthquake. However, there are many other earthquake IMs that were proposed by various researchers. The aim of this study is to investigate the correlation between seismic responses of NPP components and 23 earthquake IMs and identify the best IMs for correlating with damage of NPP structures. Particularly, low- and high-frequency ground motion records are separately accounted in correlation analyses. An advanced power reactor NPP in Korea, APR1400, is selected for numerical analyses where containment and auxiliary buildings are modeled using SAP2000. Floor displacements and accelerations are monitored for the non- and base-isolated NPP structures while shear deformations of the base isolator are additionally monitored for the base-isolated NPP. A series of Pearson's correlation coefficients are calculated to recognize the correlation between each of the 23 earthquake IMs and responses of NPP structures. The numerical results demonstrate that there is a significant difference in the correlation between earthquake IMs and seismic responses of non-isolated NPP structures considering low- and high-frequency ground motion groups. Meanwhile, a trivial discrepancy of the correlation is observed in the case of the base-isolated NPP subjected to the two groups of ground motions. Moreover, a selection of PGA or S_a for seismic response analyses of NPP structures in the high-frequency seismic regions may not be the best option. Additionally, a set of fragility curves are thereafter developed for the base-isolated NPP based on the shear deformation of lead rubber bearing (LRB) with respect to the strongly correlated IMs. The results reveal that the probability of damage to the structure is higher for low-frequency earthquakes compared with that of high-frequency ground motions.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2A
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• pp.119-130
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• 2009

Seismic fragility curves of a structure represent the probability of exceeding the prescribed structural damage state for a given various levels of ground motion intensity such as peak ground acceleration (PGA), spectral acceleration ($S_a$) and spectral displacement ($S_d$). So those are very essential to evaluate the structural seismic performance and seismic risk. The purpose of this paper is to develop seismic fragility curves for PSC box girder bridges. In order to construct numerical fragility curve of bridge structure using nonlinear time history analysis, a set of ground motions corresponding to design spectrum are artificially generated. Assuming a lognormal distribution, the fragility curve is estimated by using the methodology proposed by Shinozuka et al. PGA is simple and generally used parameter in fragility curve as ground motion intensity. However, the PGA has not good relationship with the inelastic structural behavior. So, $S_a$ and $S_d$ with more direct relationship for structural damage are used in fragility analysis as more useful intensity measures instead of PGA. The numerical fragility curves based on nonlinear time history analysis are compared with those obtained from simple method suggested in HAZUS program.