scholarly journals The Effects of Earthquake Significant Duration D595 to the Earthquake Intensity Measures and the Inelastic Response of SDOF Reinforced Concrete Structure

2019 ◽  
Vol 280 ◽  
pp. 01005
Author(s):  
Widodo Pawirodikromo
Keyword(s):  
Spectral Response ◽  
Damage Index ◽  
Structural Response ◽  
Strong Relationship ◽  
Seismic Intensity ◽  
Reinforced Concrete Structure ◽  
Earthquake Intensity ◽  
Intensity Measures ◽  
Earthquake Frequency

The concept of seismic intensity measures has long beendiscussed and has been collected by researchers among whom are by [1-6]. However, the effect of earthquake duration on the structural response hasnot received attention from the researcher so it has not been seen in the listof the existing seismic intensity measures. In the spectral response, forexample, it has been accommodated peak value and earthquake frequencycontent but has not accommodated the duration of the earthquake. Theeffect of earthquake duration on a response, damage or collapse capacity ofthe structure has been done by the researchers [7-10]. The spectrallyequivalent approach/control has been used by [9,10]., while the collapsecapacity approach is cursed by [8]. The use of the classification of theearthquake frequency content as independent variables has been suggestedby [7]. In this study, the classification of earthquake frequency (lowfrequency), earthquake duration as the independent variable and peakacceleration control have been used. Single degree of Freedom (SDOF)structures excited by 15-earthquakes with effective durations varyingbetween te = 6.34 to 30.18 s have been used. The results showed that notall seismic intensity measure used had a strong relationship with effectiveduration. The earthquake effective duration has a positive relationship withthe damage index but the relationship is relatively weak

scholarly journals Identifying Optimal Intensity Measures for Predicting Damage Potential of Mainshock–Aftershock Sequences

2020 ◽  
Vol 10 (19) ◽  
pp. 6795
Author(s):  
Zhou Zhou ◽  
Xiaohui Yu ◽  
Dagang Lu
Keyword(s):  
Structural Damage ◽  
Damage Index ◽  
Damage Potential ◽  
Earthquake Intensity ◽  
Period Range ◽  
Intensity Measures ◽  
Aftershock Sequences ◽  
Optimal Intensity ◽  
Reasonable Prediction ◽  
Large Earthquakes

Large earthquakes are followed by a sequence of aftershocks. Therefore, a reasonable prediction of damage potential caused by mainshock (MS)–aftershock (AS) sequences is important in seismic risk assessment. This paper comprehensively examines the interdependence between earthquake intensity measures (IMs) and structural damage under MS–AS sequences to identify optimal IMs for predicting the MS–AS damage potential. To do this, four categories of IMs are considered to represent the characteristics of a specific MS–AS sequence, including mainshock IMs, aftershock IMs (i.e., IMMS and IMAS, respectively), and two newly proposed IMs through taking an entire MS–AS sequence as one nominal ground motion (i.e., IM1MS–AS), or determining the ratio of IMAS to IMMS (i.e., IM2MS–AS), respectively. The single-degree-of-freedom systems with varying hysteretic behaviors are subjected to 662 real MS–AS sequences to estimate structural damage in terms the Park–Ang damage index. The intensities in terms of IMMS, IMAS, and IM1MS–AS are correlated with the accumulative damage of structures (i.e., DI1MS–AS). Moreover, the ratio (i.e., DI2MS–AS) of the AS-induced damage increment to the MS-induced damage is related to IM2MS–AS. The results show that IM2MS–AS exhibits significantly better performance than IMMS, IMAS, and IM1MS–AS for predicting the MS–AS damage potential, due to its high interdependence with DI2MS–AS. Among the considered 22 classic IMs, Arias intensity, root-square velocity, and peak ground displacement are respectively the optimal acceleration-, velocity-, and displacement-related IMs to formulate IM2MS–AS. Finally, two empirical equations are proposed to predict the correlations between IM2MS–AS and DI2MS–AS in the entire structural period range.

scholarly journals Seismic Fragility Analysis of the Reinforced Concrete Continuous Bridge Piers Based on Machine Learning and Symbolic Regression Fusion Algorithms

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Hanbo Zhu ◽  
Changqing Miao
Keyword(s):  
Machine Learning ◽  
Reinforced Concrete ◽  
Damage Index ◽  
Regression Function ◽  
Element Model ◽  
Seismic Intensity ◽  
Symbolic Regression ◽  
Fragility Analysis ◽  
Seismic Fragility ◽  
Intensity Measures

In the fragility analysis, researchers mostly chose and constructed seismic intensity measures (IMs) according to past experience and personal preference, resulting in large dispersion between the sample of engineering demand parameter (EDP) and the regression function with IM as the independent variable. This problem needs to be solved urgently. Firstly, the existing 46 types of ground motion intensity measures were taken as a candidate set, and the composite intensity measures (IMs) based on machine learning methods were selected and constructed. Secondly, the modified Park–Ang damage index was taken as EDP, and the symbolic regression method was used to fit the functional relationship between the composite intensity measures (CIMs) and EDP. Finally, the probabilistic seismic demand analysis (PSDA) and seismic fragility analysis were performed by the cloud-stripe method. Taking the pier of a three-span continuous reinforced concrete hollow slab bridge as an example, a nonlinear finite element model was established for vulnerability analysis. And the composite IM was compared with the linear composite IM constructed by Kiani, Lu Dagang, and Liu Tingting. The functions of them were compared. The analysis results indicated that the standard deviation of the composite IM fragility curve proposed in this paper is 60% to 70% smaller than the other composite indicators which verified the efficiency, practicality, proficiency, and sufficiency of the proposed machine learning and symbolic regression fusion algorithms in constructing composite IMs.

scholarly journals Growth Stages Classification of Potato Crop Based on Analysis of Spectral Response and Variables Optimization

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3995 ◽  
Author(s):  
Ning Liu ◽  
Ruomei Zhao ◽  
Lang Qiao ◽  
Yao Zhang ◽  
Minzan Li ◽  
...  
Keyword(s):  
Growth Stage ◽  
Spectral Response ◽  
Classification Model ◽  
Growth Stages ◽  
Potato Field ◽  
Spectral Bands ◽  
Svm Model ◽  
Selection Algorithms ◽  
Potato Crops

Potato is the world’s fourth-largest food crop, following rice, wheat, and maize. Unlike other crops, it is a typical root crop with a special growth cycle pattern and underground tubers, which makes it harder to track the progress of potatoes and to provide automated crop management. The classification of growth stages has great significance for right time management in the potato field. This paper aims to study how to classify the growth stage of potato crops accurately on the basis of spectroscopy technology. To develop a classification model that monitors the growth stage of potato crops, the field experiments were conducted at the tillering stage (S1), tuber formation stage (S2), tuber bulking stage (S3), and tuber maturation stage (S4), respectively. After spectral data pre-processing, the dynamic changes in chlorophyll content and spectral response during growth were analyzed. A classification model was then established using the support vector machine (SVM) algorithm based on spectral bands and the wavelet coefficients obtained from the continuous wavelet transform (CWT) of reflectance spectra. The spectral variables, which include sensitive spectral bands and feature wavelet coefficients, were optimized using three selection algorithms to improve the classification performance of the model. The selection algorithms include correlation analysis (CA), the successive projection algorithm (SPA), and the random frog (RF) algorithm. The model results were used to compare the performance of various methods. The CWT-SPA-SVM model exhibited excellent performance. The classification accuracies on the training set (Atrain) and the test set (Atest) were respectively 100% and 97.37%, demonstrating the good classification capability of the model. The difference between the Atrain and accuracy of cross-validation (Acv) was 1%, which showed that the model has good stability. Therefore, the CWT-SPA-SVM model can be used to classify the growth stages of potato crops accurately. This study provides an important support method for the classification of growth stages in the potato field.

scholarly journals Empirical Correlation between Inelastic and Elastic Spectral Displacement Demands

2016 ◽  
Vol 32 (3) ◽  
pp. 1419-1448 ◽  
Author(s):  
Peter J. Stafford ◽  
Timothy J. Sullivan ◽  
Domenico Pennucci
Keyword(s):  
Seismic Hazard ◽  
Hazard Assessment ◽  
Spectral Response ◽  
Seismic Hazard Assessment ◽  
Assessment Process ◽  
Earthquake Intensity ◽  
Empirical Relationships ◽  
Wide Range ◽  
Performance Based Seismic Design ◽  
Displacement Demand

Inelastic spectral displacement demand is arguably one of the most effective, simplified means of relating earthquake intensity to building damage. However, seismic hazard assessment is typically conducted using empirical ground-motion prediction equations (GMPEs) that only provide indications of elastic spectral response quantities, which an engineer subsequently relates to inelastic demands using empirical relationships such as the equal-displacement rule. An alternative approach is to utilize relationships for the inelastic spectral displacement demand directly within the seismic hazard assessment process. Such empirical relationships are developed in this work, as a function of magnitude, distance, building period, and yield strength coefficient, for four different hysteretic models that are representative of a wide range of possible structural typologies found in practice. The new relationships are likely to be particularly useful for performance-based seismic design and assessment.

scholarly journals ACCURACY ASSESSMENTS OF PAN-SHARPENED IMAGE FOR BENTHIC HABITATS MAPPING

2017 ◽  
Vol 4 (1) ◽  
pp. 27 ◽  
Author(s):  
Pramaditya Wicaksono ◽  
Faza Adhimah
Keyword(s):  
Spatial Resolution ◽  
Classification Scheme ◽  
Spectral Response ◽  
Hierarchical Classification ◽  
Visual Interpretation ◽  
Benthic Habitats ◽  
Visual Appearance ◽  
Accuracy Assessments

Image-sharpening process integrates lower spatial resolution multispectral bands with higher spatial resolution panchromatic band to produce multispectral bands with finer spatial detail called pan-sharpened image. Although the pan-sharpened image can greatly assist the process of information extraction using visual interpretation, the benefit and setback of using pan-sharpened image on the accuracy of digital classification for mapping remain unclear. This research aimed at 1) highlighting the issue of using pan-sharpened image to perform benthic habitats mapping and 2) comparing the accuracy of benthic habitats mapping using original and pan-sharpened bands. In this study, Quickbird image was used and Kemujan Island was selected as the study area. Two levels of hierarchical classification scheme of benthic habitats were constructed based on the composition of in situ benthic habitats. PC Spectral sharpening method was applied on Quickbird image. Image radiometric corrections, PCA transformation, and image classifications were performed on both original and pan-sharpened image. The results showed that the accuracy of benthic habitats classification of pan-sharpened image (maximum overall accuracy 64.28% and 73.30% for per-pixel and OBIA, respectively) was lower than the original image (73.46% and 73.10%, respectively). The main setback of using pan-sharpened image is the inability to correct the sunglint, hence adversely affects the process of water column correction, PCA transformation and image classification. This is mainly because sunglint do not only affect object’s spectral response but also the texture of the object. Nevertheless, the pan-sharpened image can still be used to map benthic habitats using visual interpretation and digital image processing. Pan-sharpened image will deliver better classification accuracy and visual appearance especially when the sunglint is low.

scholarly journals Suitability of Protein Content Measured by MilkoScan FT-Plus Milk Analyzer to Evaluate Bovine and Ovine Colostrum Quality

Animals ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 2587
Author(s):  
Anna Antonella Spina ◽  
Carlotta Ceniti ◽  
Francesca Trimboli ◽  
Domenico Britti ◽  
Vincenzo Lopreiato
Keyword(s):  
Regression Analysis ◽  
Protein Content ◽  
Indirect Method ◽  
Strong Relationship ◽  
Poor Quality ◽  
Bovine Colostrum ◽  
Gold Standard Method ◽  
Average Value ◽  
Correlation And Regression Analysis

The objective of this study was to evaluate MilkoScan FT-plus for the estimation of the immunoglobulin G (IgG) content in bovine and ovine colostrum. Between April and May 2016, a total of 94 colostrum samples (54 from Simmental dairy cows and 39 from Sarda ewes) were collected within 6 h (T0) and after 24 h (T24) from parturition. Colostrum samples were subjected to the radial immunodiffusion (RID) assay for the quantification of IgG and to MilkoScan FT-plus for the estimation of protein content (TP, %), which was then used as an indirect method for the evaluation of colostrum quality. To compare the two methods, correlation and regression analysis of IgG quantification by RID and protein (%) content estimation by MilkoScan FT-plus data was performed using Procedure CORR and Procedure REG of SAS, respectively (version 9.3, SAS Institute Inc., Cary, NC, USA). Thresholds for the classification of good colostrum quality (as determined by RID assay, the gold standard method) were set at 50 g of IgG/L in cows and 20 g of IgG/L in ewes. The concentration of IgG in bovine colostrum assayed by RID showed a variation ranging from 41.45 to 199.97 g/L with an average of 99.85 ± 40.84 g/L at T0, and from 2.83 to 75.93 g/L with an average of 19.76 ± 19.01 g/L at T24. Regarding ovine colostrum, the concentration of IgG assayed by RID ranged from 34.45 to 156.32 g/L with an average value of 77.82 ± 37.58 g/L at T0, and from 5.6 to 69.74 g/L with an average of 27.90 ± 19.81 g/L at T24. Colostrum TP ranged from 3.70 to 23.96% for bovine colostrum and 6.32 to 22.88% for ovine colostrum using MilkoScan FT-plus. MilkoScan FT-plus and RID data were highly and significantly correlated (r = 0.91 for bovine and r = 0.94 for ovine colostrum), and regression analysis showed a strong relationship between IgG concentration provided by RID assay and TP provided by MilkoScan FT-plus (R2 = 0.84 and 0.88 for bovine and ovine, respectively). Optimal cut-off points for the greatest accuracy of TP (%) determined by MilkoScan FT-plus were 12.8% in cows [with 88.9% sensitivity (Se) and 100% specificity (Sp)] and 9% in ewes (with 96.7% Se and 100% Sp). In conclusion, these outcomes indicate that MilkoScan FT-plus as an indirect method may be a reliable tool for the estimation of the total IgG concentration and quality in bovine and ovine colostrum. Moreover, the cut-off levels of 12.8% for bovine and 9% for ovine of TP, seem sufficient to ensure that all poor-quality colostrum can be classified as such, with only a low proportion of good-quality colostrum being misclassified as poor-colostrum, thereby increasing the probability of delivering good-quality colostrum to new-born calves and lambs.

Seismic intensity measures for above-ground liquid storage tanks

2018 ◽  
Vol 47 (9) ◽  
pp. 1844-1863 ◽  
Author(s):  
Konstantinos Bakalis ◽  
Mohsen Kohrangi ◽  
Dimitrios Vamvatsikos
Keyword(s):  
Seismic Intensity ◽  
Storage Tanks ◽  
Intensity Measures ◽  
Liquid Storage

From Speech Acoustics to Communicative Participation in Dysarthria: Toward a Causal Framework

2021 ◽  
pp. 1-14
Author(s):  
Stephanie A. Borrie ◽  
Camille J. Wynn ◽  
Visar Berisha ◽  
Tyson S. Barrett
Keyword(s):  
Speech Rate ◽  
Objective Measure ◽  
Strong Relationship ◽  
World Health ◽  
International Classification Of Functioning ◽  
Speech Acoustics ◽  
Communicative Participation ◽  
Causal Framework ◽  
Moderate Relationship

Purpose: We proposed and tested a causal instantiation of the World Health Organization's International Classification of Functioning, Disability and Health (ICF) framework, linking acoustics, intelligibility, and communicative participation in the context of dysarthria. Method: Speech samples and communicative participation scores were collected from individuals with dysarthria ( n = 32). Speech was analyzed for two acoustic metrics (i.e., articulatory precision and speech rate), and an objective measure of intelligibility was generated from listener transcripts. Mediation analysis was used to evaluate pathways of effect between acoustics, intelligibility, and communicative participation. Results: We observed a strong relationship between articulatory precision and intelligibility and a moderate relationship between intelligibility and communicative participation. Collectively, data supported a significant relationship between articulatory precision and communicative participation, which was almost entirely mediated through intelligibility. These relationships were not significant when speech rate was specified as the acoustic variable of interest. Conclusion: The statistical corroboration of our causal instantiation of the ICF framework with articulatory acoustics affords important support toward the development of a comprehensive causal framework to understand and, ultimately, address restricted communicative participation in dysarthria.

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