Search results for: models of seismic prediction

Authors: Raghabendra Yadav, Baochun Chen, Huihui Yuan, Zhibin Lian

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Concrete Filled Steel Tube (CFST) columns are widely used in Civil Engineering Structures due to their abundant properties. CFST-RC column is a built up column in which CFST members are connected with RC web. The CFST-RC column has excellent static and earthquake resistant properties, such as high strength, high ductility and large energy absorption capacity. CFST-RC columns have been adopted as piers in Ganhaizi Bridge in high seismic risk zone with a highest pier of 107m. The experimental investigation on scaled models of similar type of the CFST-RC pier are carried out. The experimental investigation on scaled models of similar type of the CFST-RC pier are carried out. Under cyclic loading, the hysteretic performance of CFST-RC columns, such as failure modes, ductility, load displacement hysteretic curves, energy absorption capacity, strength and stiffness degradation are studied in this paper.

Keywords: CFST, cyclic load, Ganhaizi bridge, seismic performance

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Authors: Emad Amar, Tawfik Khattab, Fatma Zada

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Predicting earthquakes is an important issue in the study of geography. Accurate prediction of earthquakes can help people to take effective measures to minimize the loss of personal and economic damage, such as large casualties, destruction of buildings and broken of traffic, occurred within a few seconds. United States Geological Survey (USGS) science organization provides reliable scientific information of Earthquake Existed throughout history & Preliminary database from the National Center Earthquake Information (NEIC) show some useful factors to predict an earthquake in a seismic area like Aleutian Arc in the U.S. state of Alaska. The main advantage of this prediction method that it does not require any assumption, it makes prediction according to the future evolution of object's time series. The article compares between simulation data result from trained BP and RBF neural network versus actual output result from the system calculations. Therefore, this article focuses on analysis of data relating to real earthquakes. Evaluation results show better accuracy and higher speed by using radial basis functions (RBF) neural network.

Keywords: BP neural network, prediction, RBF neural network, earthquake

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Authors: Woo Young Jung, Min Ho Kwon, Bu Seog Ju

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A failure of the non-structural component can cause significant damages in critical facilities such as nuclear power plants and hospitals. Historically, it was reported that the damage from the leakage of sprinkler systems, resulted in the shutdown of hospitals for several weeks by the 1971 San Fernando and 1994 North Ridge earthquakes. In most cases, water leakages were observed at the cross joints, sprinkler heads, and T-joint connections in piping systems during and after the seismic events. Hence, the primary objective of this study was to understand the seismic performance of T-joint connections and to develop an analytical Finite Element (FE) model for the T-joint systems of 2-inch fire protection piping system in hospitals subjected to seismic ground motions. In order to evaluate the FE models of the piping systems using OpenSees, two types of materials were used: 1) Steel 02 materials and 2) Pinching 4 materials. Results of the current study revealed that the nonlinear moment-rotation FE models for the threaded T-joint reconciled well with the experimental results in both FE material models. However, the system-level fragility determined from multiple nonlinear time history analyses at the threaded T-joint was slightly different. The system-level fragility at the T-joint, determined by Pinching 4 material was more conservative than that of using Steel 02 material in the piping system.

Keywords: fragility, t-joint, piping, leakage, sprinkler

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Authors: Reza E. Sedgh, Rajesh P. Dhakal

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Shear walls have been used extensively as the main lateral force resisting systems in multi-storey buildings. The recent development in performance based design urges practicing engineers to conduct nonlinear static or dynamic analysis to evaluate seismic performance of multi-storey shear wall buildings by employing distinct analytical models suggested in the literature. For practical purpose, application of macroscopic models to simulate the global and local nonlinear behavior of structural walls outweighs the microscopic models. The skill level, computational time and limited access to RC specialized finite element packages prevents the general application of this method in performance based design or assessment of multi-storey shear wall buildings in design offices. Hence, this paper organized to verify capability of nonlinear shell element in commercially available package (Sap2000) in simulating results of some specimens under monotonic and cyclic loads with very oversimplified available cyclic material laws in the analytical tool. The selection of constitutive models, the determination of related parameters of the constituent material and appropriate nonlinear shear model are presented in detail. Adoption of proposed simple model demonstrated that the predicted results follow the overall trend of experimental force-displacement curve. Although, prediction of ultimate strength and the overall shape of hysteresis model agreed to some extent with experiment, the ultimate displacement(significant strength degradation point) prediction remains challenging in some cases.

Keywords: analytical model, nonlinear shell element, structural wall, shear behavior

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Authors: Soner Güler, Mustafa Gülen, Eylem Güzel

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Masonry buildings constitute major part of building stock in Turkey. Masonry buildings were built up especially in rural areas and underdeveloped regions due to economic reasons. Almost all of these masonry buildings are not designed and detailed according to any design guidelines by designers. As a result of this, masonry buildings were totally collapsed or heavily damaged when subjected to destructive earthquake effects. Thus, these masonry buildings that were built up in our country must be retrofitted to improve their seismic performance. In this study, new seismic retrofitting techniques that is easy to apply and low-cost are summarized and the importance of seismic retrofitting is also emphasized for existing masonry buildings in Turkey.

Keywords: masonry buildings, earthquake effects, seismic retrofitting techniques, seismic performance

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Authors: Gram Y. Rivas Sanchez

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The seismic design codes in the world allow the analysis of structures considering an elastic-linear behavior; however, against earthquakes, the structures exhibit non-linear behaviors that induce damage to their elements. For this reason, it is necessary to use non-linear methods to analyze these structures, being the dynamic methods that provide more reliable results but require a lot of computational costs; on the other hand, non-linear static methods do not have this disadvantage and are being used more and more. In the present work, the nonlinear static analysis (pushover) of RC frame buildings of three, five, and seven stories is carried out considering models of concentrated plasticity using plastic hinges; and the seismic performance points are determined using ATC-40, FEMA 356, and FEMA 440 guidelines. Using this last standard, the highest inelastic displacements and basal shears are obtained, providing designs that are more conservative.

Keywords: pushover, nonlinear, RC building, FEMA 440, ATC 40

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Authors: Smail Tigani, Mohamed Ouzzif

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This work presents a discrete quantitative state prediction algorithm with intelligent behavior making it able to self-improve some performance aspects. The specificity of this algorithm is the capacity of self-rectification of the prediction strategy before the final decision. The auto-rectification mechanism is based on two parallel mathematical models. In one hand, the algorithm predicts the next state based on event transition matrix updated after each observation. In the other hand, the algorithm extracts its residues trend with a linear regression representing historical residues data-points in order to rectify the first decision if needs. For a normal distribution, the interactivity between the two models allows the algorithm to self-optimize its performance and then make better prediction. Designed key performance indicator, computed during a Monte Carlo simulation, shows the advantages of the proposed approach compared with traditional one.

Keywords: discrete state, Markov Chains, linear regression, auto-adaptive systems, decision making, Monte Carlo Simulation

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Authors: Amit R. Bhende, G. K. Awari

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Remaining useful life (RUL) prediction is one of key technologies to realize prognostics and health management that is being widely applied in many industrial systems to ensure high system availability over their life cycles. The present work proposes a data-driven method of RUL prediction based on multiple health state assessment for rolling element bearings. Bearing degradation data at three different conditions from run to failure is used. A RUL prediction model is separately built in each condition. Feed forward back propagation neural network models are developed for prediction modeling.

Keywords: bearing degradation data, remaining useful life (RUL), back propagation, prognosis

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Authors: Ankur Mundhra, Shubhadeep Chakraborty, Y. R. Singh, Vishal Das

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Seismic data scaling affects the dynamic range of a data and with present day lower costs of storage and higher reliability of Hard Disk data, scaling is not suggested. However, in dealing with data of different vintages, which perhaps were processed in 16 bits or even 8 bits and are need to be processed with 32 bit available data, scaling is performed. Also, scaling amplifies low amplitude events in deeper region which disappear due to high amplitude shallow events that saturate amplitude scale. We have focused on significance of scaling data to aid interpretation. This study elucidates a proper seismic loading procedure in workstations without using default preset parameters as available in most software suites. Differences and distribution of amplitude values at different depth for seismic data are probed in this exercise. Proper loading parameters are identified and associated steps are explained that needs to be taken care of while loading data. Finally, the exercise interprets the un-certainties which might arise when correlating scaled and unscaled versions of seismic data with synthetics. As, seismic well tie correlates the seismic reflection events with well markers, for our study it is used to identify regions which are enhanced and/or affected by scaling parameter(s).

Keywords: clipping, compression, resolution, seismic scaling

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Authors: Hadi Ghasemi, Mark Leonard, Spiliopoulos Spiro, Phil Cummins, Mathew Moihoi, Felix Taranu, Eric Buri, Chris Mckee

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In this study the level of seismic hazard in terms of Peak Ground Acceleration (PGA) was calculated for return period of 475 years, using modeled seismic sources and assigned ground-motion equations. The calculations were performed for bedrock site conditions (Vs30=760 m/s). From the results it is evident that the seismic hazard reaches its maximum level (i.e. PGA≈1g for 475 yr return period) at the Huon Peninsula and southern New Britain regions. Disaggregation analysis revealed that moderate to large earthquakes occurring along the New Britain Trench mainly control the level of hazard at these locations. The open-source computer program OpenQuake developed by Global Earthquake Model foundation was used for the seismic hazard computations. It should be emphasized that the presented results are still preliminary and should not be interpreted as our final assessment of seismic hazard in PNG.

Keywords: probabilistic seismic hazard assessment, Papua New Guinea, building code, OpenQuake

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Authors: Kudzanayi Chiteka, Wellington Makondo

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The whole world is on the drive to go green owing to the negative effects of burning fossil fuels. Therefore, there is immediate need to identify and utilise alternative renewable energy sources. Among these energy sources solar energy is one of the most dominant in Zimbabwe. Solar power plants used to generate electricity are entirely dependent on solar radiation. For planning purposes, solar radiation values should be known in advance to make necessary arrangements to minimise the negative effects of the absence of solar radiation due to cloud cover and other naturally occurring phenomena. This research focused on the prediction of Global Horizontal Irradiation values for the sixth day given values for the past five days. Artificial intelligence techniques were used in this research. Three models were developed based on Support Vector Machines, Radial Basis Function, and Feed Forward Back-Propagation Artificial neural network. Results revealed that Support Vector Machines gives the best results compared to the other two with a mean absolute percentage error (MAPE) of 2%, Mean Absolute Error (MAE) of 0.05kWh/m²/day root mean square (RMS) error of 0.15kWh/m²/day and a coefficient of determination of 0.990. The other predictive models had prediction accuracies of MAPEs of 4.5% and 6% respectively for Radial Basis Function and Feed Forward Back-propagation Artificial neural network. These two models also had coefficients of determination of 0.975 and 0.970 respectively. It was found that prediction of GHI values for the future days is possible using artificial intelligence-based predictive models.

Keywords: solar energy, global horizontal irradiation, artificial intelligence, predictive models

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Authors: Mohammad Parsaeimaram, Fang Congqi

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In this paper, one of the significant seismic design parameter as response modification factor in reinforced concrete (RC) buildings with base isolation system was evaluated. The seismic isolation system is a capable approach to absorbing seismic energy at the base and transfer to the substructure with lower response modification factor as compared to non-isolated structures. A response spectrum method and static nonlinear pushover analysis in according to Uniform Building Code (UBC-97), have been performed on building models involve 5, 8, 12 and 15 stories building with fixed and isolated bases consist of identical moment resisting configurations. The isolation system is composed of lead rubber bearing (LRB) was designed with help UBC-97 parameters. The force-deformation behavior of isolators was modeled as bi-linear hysteretic behavior which can be effectively used to create the isolation systems. The obtained analytical results highlight the response modification factor of considered base isolation system with higher values than recommended in the codes. The response modification factor is used in modern seismic codes to scale down the elastic response of structures.

Keywords: response modification factor, base isolation system, pushover analysis, lead rubber bearing, bi-linear hysteretic

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Authors: Ayman Abd-Elhamed, Sayed Mahmoud

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The present research work investigates the seismic response of reinforced concrete (RC) frame building considering the effect of modeling masonry infill (MI) walls. The seismic behavior of a residential 6-storey RC frame building, considering and ignoring the effect of masonry, is numerically investigated using response spectrum (RS) analysis. The considered herein building is designed as a moment resisting frame (MRF) system following the Egyptian code (EC) requirements. Two developed models in terms of bare frame and infill walls frame are used in the study. Equivalent diagonal strut methodology is used to represent the behavior of infill walls, whilst the well-known software package ETABS is used for implementing all frame models and performing the analysis. The results of the numerical simulations such as base shear, displacements, and internal forces for the bare frame as well as the infill wall frame are presented in a comparative way. The results of the study indicate that the interaction between infill walls and frames significantly change the responses of buildings during earthquakes compared to the results of bare frame building model. Specifically, the seismic analysis of RC bare frame structure leads to underestimation of base shear and consequently damage or even collapse of buildings may occur under strong shaking. On the other hand, considering infill walls significantly decrease the peak floor displacements and drifts in both X and Y-directions.

Keywords: masonry infill, bare frame, response spectrum, seismic response

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Authors: Haidy S. Ghali, Engy Serag, A. Samer Ezeldin

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Copper is an essential raw material used in the construction industry. During the year 2021 and the first half of 2022, the global market suffered from a significant fluctuation in copper raw material prices due to the aftermath of both the COVID-19 pandemic and the Russia-Ukraine war, which exposed its consumers to an unexpected financial risk. Thereto, this paper aims to develop two ANN-LSTM price prediction models, using Python, that can forecast the average monthly copper prices traded in the London Metal Exchange; the first model is a multivariate model that forecasts the copper price of the next 1-month and the second is a univariate model that predicts the copper prices of the upcoming three months. Historical data of average monthly London Metal Exchange copper prices are collected from January 2009 till July 2022, and potential external factors are identified and employed in the multivariate model. These factors lie under three main categories: energy prices and economic indicators of the three major exporting countries of copper, depending on the data availability. Before developing the LSTM models, the collected external parameters are analyzed with respect to the copper prices using correlation and multicollinearity tests in R software; then, the parameters are further screened to select the parameters that influence the copper prices. Then, the two LSTM models are developed, and the dataset is divided into training, validation, and testing sets. The results show that the performance of the 3-Month prediction model is better than the 1-Month prediction model, but still, both models can act as predicting tools for diverse economic situations.

Keywords: copper prices, prediction model, neural network, time series forecasting

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Authors: Ali Etemadi, Claudia Fernanda Yasar

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Elevated water storage tank structures (EWSTs) are high elevated-ponderous structural systems and very vulnerable to seismic vibrations. In past earthquake events, many of these structures exhibit poor performance and experienced severe damage. The dynamic analysis of the EWSTs under earthquake loads is, therefore, of significant importance for the design of the structure and a key issue for the development of modern methods, such as active control design. In this study, a reduced model of the EWSTs is explained, which is based on a tuned mass damper model (TMD). Vibration analysis of a structure under seismic excitation is presented and then used to propose an active vibration controller. MATLAB/Simulink is employed for dynamic analysis of the system and control of the seismic response. A single degree of freedom (SDOF) and two degree of freedom (2DOF) models of ELSTs are going to be used to study the concept of active vibration control. Lab-scale experimental models similar to pendulum are applied to suppress vibrations in ELST under seismic excitation. One of the most important phenomena in liquid storage tanks is the oscillation of fluid due to the movements of the tank body because of its base motions during an earthquake. Simulation results illustrate that the EWSTs vibration can be reduced by means of an input shaping technique that takes into account the dominant mode shape of the structure. Simulations with which to guide many of our designs are presented in detail. A simple and effective real-time control for seismic vibration damping can be, therefore, design and built-in practice.

Keywords: elevated water storage tank, tuned mass damper model, real time control, shaping control, seismic vibration control, the laplace transform

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Authors: Babak H. Mamaqani, Alimohammad Entezarmahdi

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There are many researches on parameters affecting seismic behavior of steel moment frames. Great deal of these researches considers cover plate connections with or without haunch and direct beam to column connection for exterior columns. Also there are experimental results for interior connections with equal beam depth on both sides but not much research has been performed on the seismic behavior of joints with unequal beam depth. Based on previous experimental results, a series of companion analyses have been set up considering different beam height and connection detailing configuration to investigate the seismic behavior of the connections. Results of this study indicate that when the differences between beams height on both side increases, use of haunch connection system leads to significant improvement in the seismic response whereas other configurations did not provide satisfying results.

Keywords: analytical modeling, Haunch connection, seismic design, unequal beam depth

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Authors: Nuwan Kuruwitaarachchi, M. K. M. Peiris, C. N. Madawala, K. M. A. R. Perera, V. U. N Perera

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Dealing with businesses with the foreign market always took a special place in a country’s economy. Political and social factors came into play making currency rate changes fluctuate rapidly. Currency rate prediction has become an important factor for larger international businesses since large amounts of money exchanged between countries. This research focuses on comparing the accuracy of mainly three models; Autoregressive Integrated Moving Average (ARIMA), Artificial Neural Networks(ANN) and Support Vector Machines(SVM). series of data import, export, USD currency exchange rate respect to LKR has been selected for training using above mentioned algorithms. After training the data set and comparing each algorithm, it was able to see that prediction in SVM performed better than other models. It was improved more by combining SVM and SVR models together.

Keywords: ARIMA, ANN, FFNN, RMSE, SVM, SVR

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Authors: W. Badla

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A significant portion of the buildings constructed in Algeria is structural frames with infill panels which are usually considered as non structural components and are neglected in the analysis. However, these masonry panels tend to influence the structural response. Thus, these structures can be regarded as seismic risk buildings, although in the Algerian seismic code there is little guidance on the seismic evaluation of infilled frame buildings. In this study, three RC frames with 2, 4, and 8 story and subjected to three recorded Algerian accelerograms are studied. The diagonal strut approach is adopted for modeling the infill panels and a fiber model is used to model RC members. This paper reports on the seismic evaluation of RC frames with brick infill panels. The results obtained show that the masonry panels enhance the load lateral capacity of the buildings and the infill panel configuration influences the response of the structures.

Keywords: seismic design, RC frames, infill panels, non linear dynamic analysis

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Authors: Konstantinos G. Kostinakis, Asimina M. Athanatopoulou

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A key issue in seismic risk analysis within the context of Performance-Based Earthquake Engineering is the evaluation of the expected seismic damage of structures under a specific earthquake ground motion. The assessment of the seismic performance strongly depends on the choice of the seismic Intensity Measure (IM), which quantifies the characteristics of a ground motion that are important to the nonlinear structural response. Several conventional IMs of ground motion have been used to estimate their damage potential to structures. Yet, none of them has been proved to be able to predict adequately the seismic damage. Therefore, alternative, scalar intensity measures, which take into account not only ground motion characteristics but also structural information have been proposed. Some of these IMs are based on integration of spectral values over a range of periods, in an attempt to account for the information that the shape of the acceleration, velocity or displacement spectrum provides. The adequacy of a number of these IMs in predicting the structural damage of 3D R/C buildings is investigated in the present paper. The investigated IMs, some of which are structure specific and some are nonstructure-specific, are defined via integration of spectral values. To achieve this purpose three symmetric in plan R/C buildings are studied. The buildings are subjected to 59 bidirectional earthquake ground motions. The two horizontal accelerograms of each ground motion are applied along the structural axes. The response is determined by nonlinear time history analysis. The structural damage is expressed in terms of the maximum interstory drift as well as the overall structural damage index. The values of the aforementioned seismic damage measures are correlated with seven scalar ground motion IMs. The comparative assessment of the results revealed that the structure-specific IMs present higher correlation with the seismic damage of the three buildings. However, the adequacy of the IMs for estimation of the structural damage depends on the response parameter adopted. Furthermore, it was confirmed that the widely used spectral acceleration at the fundamental period of the structure is a good indicator of the expected earthquake damage level.

Keywords: damage measures, bidirectional excitation, spectral based IMs, R/C buildings

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Authors: Lee P. Leon, Raymond Charles

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This paper presents a method of evaluating the effect of aggregate angularity on hot mix asphalt (HMA) properties and its relationship to the Permanent Deformation resistance. The research concluded that aggregate particle angularity had a significant effect on the Permanent Deformation performance, and also that with an increase in coarse aggregate angularity there was an increase in the resistance of mixes to Permanent Deformation. A comparison between the measured data and predictive data of permanent deformation predictive models showed the limits of existing prediction models. The numerical analysis described the permanent deformation zones and concluded that angularity has an effect of the onset of these zones. Prediction of permanent deformation help road agencies and by extension economists and engineers determine the best approach for maintenance, rehabilitation, and new construction works of the road infrastructure.

Keywords: aggregate angularity, asphalt concrete, permanent deformation, rutting prediction

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Authors: Seung-Won Lee, JongSoo Lee, Won-Jik Yang, Hyung-Joon Kim

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A capacity spectrum method (CSM), one of methodologies to evaluate seismic fragilities of building structures, has been long recognized as the most convenient method, even if it contains several limitations to predict the seismic response of structures of interest. This paper proposes the procedure to estimate seismic fragility curves using an incremental dynamic analysis (IDA) rather than the method adopting a CSM. To achieve the research purpose, this study compares the seismic fragility curves of a 5-story reinforced concrete (RC) moment frame obtained from both methods, an IDA method and a CSM. Both seismic fragility curves are similar in slight and moderate damage states whereas the fragility curve obtained from the IDA method presents less variation (or uncertainties) in extensive and complete damage states. This is due to the fact that the IDA method can properly capture the structural response beyond yielding rather than the CSM and can directly calculate higher mode effects. From these observations, the CSM could overestimate seismic vulnerabilities of the studied structure in extensive or complete damage states.

Keywords: seismic fragility curve, incremental dynamic analysis, capacity spectrum method, reinforced concrete moment frame

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Authors: Ozden Saygili, Eser Cakti

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Mosques and minarets can be severely damaged as a result of earthquakes. Non-linear behavior of minarets of Mihrimah Sultan and Süleymaniye Mosques and the minaret of St. Sophia are analyzed to investigate seismic response, damage and failure mechanisms of minarets during earthquake. Selected minarets have different height and diameter. Discrete elements method was used to create the numerical minaret models. Analyses were performed using sine waves. Two parameters were used for evaluating the results: the maximum relative dislocation of adjacent drums and the maximum displacement at the top of the minaret. Both parameters were normalized by the drum diameter. The effects of minaret geometry on seismic behavior were evaluated by comparing the results of analyses.

Keywords: discrete element method, earthquake safety, nonlinear analysis, masonry structures

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Authors: Z. Sadeghi, M. R. Omidkhah, M. E. Masoomi

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The purpose of this paper is to examine gas transport behavior of mixed matrix membranes (MMMs) combined with porous particles. Main existing models are categorized in two main groups; two-phase (ideal contact) and three-phase (non-ideal contact). A new coefficient, J, was obtained to express equations for estimating effect of the particle porosity in two-phase and three-phase models. Modified models evaluates with existing models and experimental data using Matlab software. Comparison of gas permeability of proposed modified models with existing models in different MMMs shows a better prediction of gas permeability in MMMs.

Keywords: mixed matrix membrane, permeation models, porous particles, porosity

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Authors: Xiaogang Li, Jieqiong Miao

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As for the problem of the grey forecasting model prediction accuracy is low, an improved grey prediction model is put forward. Firstly, use trigonometric function transform the original data sequence in order to improve the smoothness of data , this model called SGM( smoothness of grey prediction model), then combine the improved grey model with support vector machine , and put forward the grey support vector machine model (SGM - SVM).Before the establishment of the model, we use trigonometric functions and accumulation generation operation preprocessing data in order to enhance the smoothness of the data and weaken the randomness of the data, then use support vector machine (SVM) to establish a prediction model for pre-processed data and select model parameters using genetic algorithms to obtain the optimum value of the global search. Finally, restore data through the "regressive generate" operation to get forecasting data. In order to prove that the SGM-SVM model is superior to other models, we select the battery life data from calce. The presented model is used to predict life of battery and the predicted result was compared with that of grey model and support vector machines．For a more intuitive comparison of the three models, this paper presents root mean square error of this three different models .The results show that the effect of grey support vector machine (SGM-SVM) to predict life is optimal, and the root mean square error is only 3.18%. Keywords: grey forecasting model, trigonometric function, support vector machine, genetic algorithms, root mean square error

Keywords: Grey prediction model, trigonometric functions, support vector machines, genetic algorithms, root mean square error

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Authors: Jianwei Ma, Diriba Gemechu

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In seismic data processing, attenuation of random noise is the basic step to improve quality of data for further application of seismic data in exploration and development in different gas and oil industries. The signal-to-noise ratio of the data also highly determines quality of seismic data. This factor affects the reliability as well as the accuracy of seismic signal during interpretation for different purposes in different companies. To use seismic data for further application and interpretation, we need to improve the signal-to-noise ration while attenuating random noise effectively. To improve the signal-to-noise ration and attenuating seismic random noise by preserving important features and information about seismic signals, we introduce the concept of anisotropic total fractional order denoising algorithm. The anisotropic total fractional order variation model defined in fractional order bounded variation is proposed as a regularization in seismic denoising. The split Bregman algorithm is employed to solve the minimization problem of the anisotropic total fractional order variation model and the corresponding denoising algorithm for the proposed method is derived. We test the effectiveness of theproposed method for synthetic and real seismic data sets and the denoised result is compared with F-X deconvolution and non-local means denoising algorithm.

Keywords: anisotropic total fractional order variation, fractional order bounded variation, seismic random noise attenuation, split Bregman algorithm

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Authors: Noureddine Litim

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This work is to theoretical and numerical studying the real analysis of the seismic response of the soil with an Elasto-plastic behavior. To perform this analysis, we used different core drilling performed at the tunnel T4 in El Horace section of the highway east-west. The two-dimensional model (2d) was established by the code of finite element plaxis to estimate the displacement amplification and accelerations caused by the seismic wave in the different core drilling and compared with the factor of acceleration given by the RPA (2003) in the area studying. Estimate the displacement amplification and accelerations caused by the seismic wave.

Keywords: seismic response, deposition of soil, plaxis, elasto-plastic

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Authors: Chang Seok Lee, Sang Whan Han, Girbo Ko, Debbie Kim

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Existing reinforced concrete structures are designed and built without considering seismic loads. The columns in such buildings generally exhibit widely spaced transverse reinforcements without using seismic hooks. Due to the insufficient reinforcement details in columns, brittle shear failure is expected in columns that may cause pre-mature building collapse mechanism during earthquakes. In order to retrofit those columns, the accurate seismic behavior of the columns needs to be predicted with proper analytical models. In this study, an analytical model is proposed for accurately simulating the cyclic behavior of shear critical columns. The parameters for pinching and cyclic deterioration in strength and stiffness are calibrated using test data of column specimens failed by shear.

Keywords: analytical model, cyclic deterioration, existing reinforced concrete columns, shear failure

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Authors: Amadou Wurry Jallow, Adama N. S. Bah, Karamo Bah, Shih-Ye Wang, Kuo-Chung Chu, Chien-Yeh Hsu

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Chronic kidney disease (CKD) is a major public health challenge with high prevalence, rising incidence, and serious adverse consequences. Developing effective risk prediction models is a cost-effective approach to predicting and preventing complications of chronic kidney disease (CKD). This study aimed to develop an accurate machine learning model that can dynamically identify individuals at risk of CKD using various kinds of diagnostic data, with or without laboratory data, at different follow-up points. Creatinine is a key component used to predict CKD. These models will enable affordable and effective screening for CKD even with incomplete patient data, such as the absence of creatinine testing. This retrospective cohort study included data on 19,429 adults provided by a private research institute and screening laboratory in Taiwan, gathered between 2001 and 2015. Univariate Cox proportional hazard regression analyses were performed to determine the variables with high prognostic values for predicting CKD. We then identified interacting variables and grouped them according to diagnostic data categories. Our models used three types of data gathered at three points in time: non-laboratory, laboratory, and metabolic indices data. Next, we used subgroups of variables within each category to train two machine learning models (Random Forest and XGBoost). Our machine learning models can dynamically discriminate individuals at risk for developing CKD. All the models performed well using all three kinds of data, with or without laboratory data. Using only non-laboratory-based data (such as age, sex, body mass index (BMI), and waist circumference), both models predict chronic kidney disease as accurately as models using laboratory and metabolic indices data. Our machine learning models have demonstrated the use of different categories of diagnostic data for CKD prediction, with or without laboratory data. The machine learning models are simple to use and flexible because they work even with incomplete data and can be applied in any clinical setting, including settings where laboratory data is difficult to obtain.

Keywords: chronic kidney disease, glomerular filtration rate, creatinine, novel metabolic indices, machine learning, risk prediction

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Authors: Sijing Xiong, Ran Su, Lit-Hsin Loo, Daniele Zink

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The kidney is a major target for toxic effects of drugs, industrial and environmental chemicals and other compounds. Typically, nephrotoxicity is detected late during drug development, and regulatory animal models could not solve this problem. Validated or accepted in silico or in vitro methods for the prediction of nephrotoxicity are not available. We have established the first and currently only pre-validated in vitro models for the accurate prediction of nephrotoxicity in humans and the first predictive platforms based on renal cells derived from human pluripotent stem cells. In order to further improve the efficiency of our predictive models, we recently developed a high content screening (HCS) platform. This platform employed automated imaging in combination with automated quantitative phenotypic profiling and machine learning methods. 129 image-based phenotypic features were analyzed with respect to their predictive performance in combination with 44 compounds with different chemical structures that included drugs, environmental and industrial chemicals and herbal and fungal compounds. The nephrotoxicity of these compounds in humans is well characterized. A combination of chromatin and cytoskeletal features resulted in high predictivity with respect to nephrotoxicity in humans. Test balanced accuracies of 82% or 89% were obtained with human primary or immortalized renal proximal tubular cells, respectively. Furthermore, our results revealed that a DNA damage response is commonly induced by different PTC-toxicants with diverse chemical structures and injury mechanisms. Together, the results show that the automated HCS platform allows efficient and accurate nephrotoxicity prediction for compounds with diverse chemical structures.

Keywords: high content screening, in vitro models, nephrotoxicity, toxicity prediction

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Authors: Razmik Atabekyan, V. Atabekyan

Abstract:

This article discusses a new alternative method for determination of seismic loads on buildings, based on resistance of structures to deformations of vibrations. The basic principles for determining seismic loads by spectral method were developed in 40… 50ies of the last century and further have been improved to pursuit true assessments of seismic effects. The base of the existing methods to determine seismic loads is response spectrum or dynamicity coefficient β (norms of RF), which are not definitively established. To this day there is no single, universal method for the determination of seismic loads and when trying to apply the norms of different countries, significant discrepancies between the results are obtained. On the other hand there is a contradiction of the results of macro seismic surveys of strong earthquakes with the principle of the calculation based on accelerations. It is well-known, on soft soils there is an increase of destructions (mainly due to large displacements), even though the accelerations decreases. Obviously, the seismic impacts are transmitted to the building through foundation, but paradoxically, the existing methods do not even include foundation data. Meanwhile acceleration of foundation of the building can differ several times from the acceleration of the ground. During earthquakes each building has its own peculiarities of behavior, depending on the interaction between the soil and the foundations, their dynamic characteristics and many other factors. In this paper we consider a new, alternative method of determining the seismic loads on buildings, without the use of response spectrum. The following main conclusions: 1) Seismic loads are revealed at the foundation level, which leads to redistribution and reduction of seismic loads on structures. 2) The proposed method is universal and allows determine the seismic loads without the use of response spectrum and any implicit coefficients. 3) The possibility of taking into account important factors such as the strength characteristics of the soils, the size of the foundation, the angle of incidence of the seismic ray and others. 4) Existing methods can adequately determine the seismic loads on buildings only for first form of vibrations, at an average soil conditions.

Keywords: seismic loads, response spectrum, dynamic characteristics of buildings, momentum

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