An archive of data from resonant column and cyclic torsional shear tests performed on Italian clays

2020 ◽  
pp. 875529302093669
Author(s):  
Johann Facciorusso
Keyword(s):  
Earthquake Engineering ◽  
Multiple Testing ◽  
Laboratory Tests ◽  
Dynamic Properties ◽  
Damping Ratio ◽  
Large Data ◽  
Dynamic Parameters ◽  
Data Set ◽  
Geotechnical Earthquake Engineering ◽  
Geotechnical Tests

Measurement of soil properties under cyclic and dynamic loading conditions is a critical task in the solution of most geotechnical earthquake engineering problems. The main dynamic properties of soils are usually expressed in terms of shear modulus, G, and damping ratio, D, and they are generally obtained from laboratory tests at different strain levels. Dynamic geotechnical problems often require a site-level or territorial approach involving a considerable number of dynamic laboratory tests that might be too expensive and time-consuming. Thus, it is a common practice to use empirical relationships between dynamic parameters and measurements from routine geotechnical tests. Therefore, the availability of a large and reliable archive of multiple testing results constitutes a fundamental step for geotechnical earthquake engineers and researchers. To this aim, a large data-set of the index and dynamic parameters measured from 170 undisturbed clay samples obtained from 90 sites in Central and Northern Italy is made available, and its use and application are further described and discussed.

scholarly journals Influence of Structure on the Aseismic Stability and Dynamic Responses of Liquefiable Soil

2021 ◽  
Author(s):  
Pengfei Dou ◽  
Chengshun Xu ◽  
Xiuli Du ◽  
Su Chen
Keyword(s):  
Earthquake Engineering ◽  
Damping Ratio ◽  
Free Field ◽  
Shaking Table ◽  
Dynamic Responses ◽  
Seismic Stability ◽  
Geotechnical Earthquake Engineering ◽  
Liquefiable Soil ◽  
Porewater Pressure ◽  
Lateral Displacements

Abstract In previous major earthquakes, the damage and collapse of structures located in liquefied field which caused by site failure a common occurrence, and the problem of evaluation and disscusion on site liquefaction and the seismic stability is still a key topic in geotechnical earthquake engineering. To study the influence of the presence of structure on the seismic stability of liquefiable sites, a series of shaking table tests on liquefiable free field and non-free field with the same soil sample was carried out. It can be summarized from experimental results as following. The natural frequency of non-free field is larger and the damping ratio is smaller than that of free field. For the weak seismic loading condition, the dynamic response of sites show similar rules and trend. For the strong ground motion condition, soils in both experiments all liquefied obviously and the depth of liquefaction soil in the free field is significantly greater than that in the non-free field, besides, porewater pressure in the non-free field accumulated relately slow and the dissapited quikly from analysis of porewater pressure ratios(PPRs) in both experiments. The amplitudes of lateral displacements and acceleration of soil in the non-free field is obviously smaller than that in the free field caused by the effect of presence of the structure. In a word, the presence of structures will lead to the increase of site stiffness, site more difficult to liquefy, and the seismic stability of the non-free site is higher than that of the free site due to soil-structure interaction.

FRACTAL ASPECTS OF PROTEIN STRUCTURE AND DYNAMICS

Fractals ◽  
1993 ◽  
Vol 01 (02) ◽  
pp. 179-189 ◽  
Author(s):  
T. GREGORY DEWEY
Keyword(s):  
Dynamic Properties ◽  
Linear Chain ◽  
Protein Structures ◽  
Three Dimensional ◽  
Alpha Helix ◽  
Large Data ◽  
Thermal Fluctuations ◽  
Radius Of Gyration ◽  
Data Set ◽  
Long Range Correlations

Proteins have well-defined three dimensional structures which are dictated by their amino acid sequence. Despite this great specificity, general structural and dynamic properties exist. Scaling relationships for the radius of gyration and surface area of a large data set of proteins are demonstrated in this work. These results show that proteins scale as collapsed polymers. Thermal fluctuations are examined for two different proteins by an analysis of the Debye-Waller factors derived from X-ray crystallographic data. Long-range correlations exist between fluctuations along the backbone. A disordered Ising model is presented which gives similar correlations. To further examine the role of multiple connectivity in protein structures, the vibrational spectrum for an alpha helix (linear chain with H-bonds) is analyzed from recursive relationships derived using a decimation technique.

Test Study on the Dynamic Parameters of Compound Composite Foundation

2012 ◽  
Vol 450-451 ◽  
pp. 1548-1552
Author(s):  
Na Wang ◽  
Zhen Feng ◽  
Yong Da ◽  
Wei Lin
Keyword(s):  
Regression Analysis ◽  
Seismic Design ◽  
Dynamic Properties ◽  
Damping Ratio ◽  
Confining Pressure ◽  
Composite Foundation ◽  
Dynamic Parameters ◽  
Simple Method ◽  
Test Study ◽  
Wide Range

Influence of factors such as displacement ratio and confining pressure on the dynamic properties of composite specimen with GC pile and CFG pile was studied under a wide range of strains by regression analysis，a simple method for calculating the dynamic elastic modulus and damping ratio is Proposed and an empirical formula considering the mentioned factors above is also presented to provide a elementary reference for anti-seismic design of composite foundations with GC piles and CFG piles.

Experimental and numerical investigation on dynamic parameters of broaching machine

2015 ◽  
Vol 231 (10) ◽  
pp. 1907-1920
Author(s):  
Shenshun Ying ◽  
Shiming Ji ◽  
Yangyu Wang ◽  
Zhixin Li ◽  
Lvgao Lin ◽  
...  
Keyword(s):  
Modal Analysis ◽  
Natural Frequencies ◽  
Dynamic Properties ◽  
Structural Parameters ◽  
Damping Ratio ◽  
Experimental Results ◽  
Mode Shapes ◽  
Fe Model ◽  
Dynamic Parameters ◽  
Machine Structure

Dynamic properties of the whole broaching machine structure greatly contribute to the broaching quality and efficiency. However, it is hard to measure the dynamic parameters because they will change during operation compared with the static results from classic experimental modal analysis. This study is to examine the dynamic parameters of broaching machine LG7120KT using both the numerical finite element (FE) method and the experimental operational modal analysis (OMA). Firstly, FE analysis model of the broaching machine with the real dimension is constructed and calculated. Second, experimental results are obtained from OMA in practical broaching process, which can be used to identify steady-state modes. Modal parameters including mode shapes, damping ratio, and natural frequencies are examined, using both LMS SCADAS III-305 system and PolyMAX method in OMA. The numerical and experimental results show high agreement in their calculated natural frequencies. From the modal analysis results, it is also found the vibration normal to cutting direction can be greatly reduced by adjusting broaching speed. From the topology optimization result based on the already correlated FE model, we redesigned a lightweight machine structure with a better dynamic performance, due to its lower displacement of broaching machine at force point and its higher first-order natural frequency. The experimental and numerical results in this paper help to design the structural parameters of broaching machine and propose a better broaching process.

Study on Dynamical Modulus and Damping Ratio of Lime-Treated Soil

2012 ◽  
Vol 487 ◽  
pp. 534-538
Author(s):  
Min Wang ◽  
Ling Wei Kong ◽  
Xiao Yan Wang
Keyword(s):  
Laboratory Tests ◽  
Dynamic Stress ◽  
General Trend ◽  
Dynamic Properties ◽  
Damping Ratio ◽  
Expansive Soil ◽  
Confining Pressure ◽  
Test System ◽  
Expansive Clay ◽  
Number Of Cycles

In order to study dynamic properties of lime-treated expansive clay, a comprehensive series of laboratory tests were conducted via dynamic triaxial test system. The influences of factors such as moisture content, confining pressure, vibration frequency, consolidation ratio and the number of cycles on dynamic characteristics were discussed. It is found that the dynamic stress-strain curves of lime-treated expansive clay show the general trend of hyperbola. Compared with the remoulded expansive soil, the bearing capacity of lime improved expansive soil is higher than remolded soil.

scholarly journals THE DYNAMIC PARAMETERS OF PASSIVE HUMAN AT TEMPORARY DEMOUNTABLE GRANDSTANDS DURING EXPOSURE TO LATERAL VIBRATION

2018 ◽  
Vol 24 (4) ◽  
pp. 265-283 ◽  
Author(s):  
Jian Yuan ◽  
Lin He ◽  
Feng Fan ◽  
Cong Liu
Keyword(s):  
Natural Frequency ◽  
Dynamic Properties ◽  
Damping Ratio ◽  
Reference Value ◽  
Shaking Table ◽  
Model Parameters ◽  
Dynamic Parameters ◽  
Random Waves ◽  
Mass Ratio ◽  
Dynamic Features

Modelling the interaction between crowds and temporary demountable grandstands with identifying the human dynamic properties are challenges for structure optimal design. In this paper, for investigating and understanding the human and structural lateral dynamic features. A demountable grandstand was tested to obtain its model parameters firstly. Then it is tested at amplitudes between 0.16 m/s2 to 1.54 m/s2 with 75 random waves through a shaking table when occupied by twenty persons. Afterword a simplified two-degree of freedom lumped dynamic model of the joint human-structure system is reinterpreted. Utilizing the state-space model, the passive crowd dynamic parameters are obtained, based on root mean square accumulation error analysis. Statistical analysis of the predictive results concludes that seated crowd model damping ratio is 0.5, and the probable natural frequency is 2.0 Hz with the model mass ratio 0.7. For standing crowd model, the probable natural frequency is 1.5 Hz with the model mass damping ratio 0.4, and the model mass ratio is 0.7. It may have ability to serve as a reference value that can be utilized in vibration safety and serviceability assessment of TDGs, to estimate realistically the vibration response on the occasions when crowd are seated or standing.

Some statistical and CI models to predict chaotic high-frequency financial data

2020 ◽  
Vol 39 (5) ◽  
pp. 6419-6430
Author(s):  
Dusan Marcek
Keyword(s):  
Time Series Data ◽  
Moving Average ◽  
Methodological Approach ◽  
Back Propagation ◽  
Large Data ◽  
Series Data ◽  
Data Set ◽  
Training Time ◽  
Optimal Population ◽  
Forecast Time

To forecast time series data, two methodological frameworks of statistical and computational intelligence modelling are considered. The statistical methodological approach is based on the theory of invertible ARIMA (Auto-Regressive Integrated Moving Average) models with Maximum Likelihood (ML) estimating method. As a competitive tool to statistical forecasting models, we use the popular classic neural network (NN) of perceptron type. To train NN, the Back-Propagation (BP) algorithm and heuristics like genetic and micro-genetic algorithm (GA and MGA) are implemented on the large data set. A comparative analysis of selected learning methods is performed and evaluated. From performed experiments we find that the optimal population size will likely be 20 with the lowest training time from all NN trained by the evolutionary algorithms, while the prediction accuracy level is lesser, but still acceptable by managers.

In silico Prediction of Inhibitory Constant of Thrombin Inhibitors Using Machine Learning

2019 ◽  
Vol 21 (9) ◽  
pp. 662-669 ◽  
Author(s):  
Junnan Zhao ◽  
Lu Zhu ◽  
Weineng Zhou ◽  
Lingfeng Yin ◽  
Yuchen Wang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Prediction Models ◽  
Regression Tree ◽  
Large Data ◽  
Thrombin Inhibitors ◽  
Coagulation Cascade ◽  
Gradient Boosting ◽  
Support Vector ◽  
Data Set ◽  
Descriptor Selection

Background: Thrombin is the central protease of the vertebrate blood coagulation cascade, which is closely related to cardiovascular diseases. The inhibitory constant Ki is the most significant property of thrombin inhibitors. Method: This study was carried out to predict Ki values of thrombin inhibitors based on a large data set by using machine learning methods. Taking advantage of finding non-intuitive regularities on high-dimensional datasets, machine learning can be used to build effective predictive models. A total of 6554 descriptors for each compound were collected and an efficient descriptor selection method was chosen to find the appropriate descriptors. Four different methods including multiple linear regression (MLR), K Nearest Neighbors (KNN), Gradient Boosting Regression Tree (GBRT) and Support Vector Machine (SVM) were implemented to build prediction models with these selected descriptors. Results: The SVM model was the best one among these methods with R2=0.84, MSE=0.55 for the training set and R2=0.83, MSE=0.56 for the test set. Several validation methods such as yrandomization test and applicability domain evaluation, were adopted to assess the robustness and generalization ability of the model. The final model shows excellent stability and predictive ability and can be employed for rapid estimation of the inhibitory constant, which is full of help for designing novel thrombin inhibitors.

scholarly journals Correlation between the structure and skin permeability of compounds

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ruolan Zeng ◽  
Jiyong Deng ◽  
Limin Dang ◽  
Xinliang Yu
Keyword(s):  
Large Data ◽  
Qsar Model ◽  
Coefficient Of Determination ◽  
Support Vector ◽  
Skin Permeability ◽  
Data Set ◽  
Test Set ◽  
Svm Algorithm ◽  
Svm Model ◽  
Toxicity Relationship

AbstractA three-descriptor quantitative structure–activity/toxicity relationship (QSAR/QSTR) model was developed for the skin permeability of a sufficiently large data set consisting of 274 compounds, by applying support vector machine (SVM) together with genetic algorithm. The optimal SVM model possesses the coefficient of determination R2 of 0.946 and root mean square (rms) error of 0.253 for the training set of 139 compounds; and a R2 of 0.872 and rms of 0.302 for the test set of 135 compounds. Compared with other models reported in the literature, our SVM model shows better statistical performance in a model that deals with more samples in the test set. Therefore, applying a SVM algorithm to develop a nonlinear QSAR model for skin permeability was achieved.

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