• Title/Summary/Keyword: non-linear dynamic

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3-D Configuration Effects of Prestressing Cable Bracing Used for Retrofitting a RC Frame Subjected to Seismic Damage (RC 골조의 내진 보강을 위한 예압 가새의 3-D 배치)

  • Lee, Jin-Ho;Oh, Sang-Gyun;Hisham, El-Ganzori
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.7 no.3
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    • pp.183-191
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    • 2003
  • A four-story reinforced concrete moment resisting frame damaged from an ultimate limit state earthquake is upgraded with prestressing cable bracing. The purpose of this study is to investigate the bracing configuration effects on the 3-D building response using thee different locations of the bracing systems for the retrofitted building. Since the previous work done by the author proved that static incremental loads to collapse analysis as a substitute to dynamic non-linear time history analysis was a valid alternative tool. Thus, static load to collapse analysis is solely applied to evaluate the seismic performance parameters of both the original and upgraded buildings in this study. In results, the exterior bracing system is effective in restraining torsional behavior of the structure under seismic loads, and no sudden failure occurs in this system that enhances the ductility of the building due to the gradual change of building stiffness as the lateral load increases.

Analysis of PIG Dynamics through Curved Section in Natural Gas Pipeline (천연가스 배관 곡관부에서의 피그 동적 거동 해석)

  • Kim D. K.;Nguyen T. T.;Yoo H. R.;Rho Y. W.;Kho Y.T.;Kim S. B.
    • Journal of the Korean Institute of Gas
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    • v.6 no.1 s.17
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    • pp.1-9
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    • 2002
  • This paper presents simple models for flow and the PIG dynamics when it passes through a $90^{\circ}$ curved section of pipeline. The simulation has been done with two different operational boundary conditions. The solution fur non-linear hyperbolic partial equations for flow is given by using MOC. The Runge-Kuta method is used to solve the initial condition equation fur flow and the PIG dynamics equation. The simulation results show that the proposed model and solution can be used fur estimating the PIG dynamics when the pig runs in the pipeline including curved section. In this paper, dynamic modeling and its analysis for the PIG flow through $90^{\circ}$ curved pipe with compressible and unsteady flow are studied. The PIG dynamics model is derived by using Lagrange equation under assumption that it passes through 3 different sections in the curved pipeline such that it moves into, inside and out of the curved section. The downstream and up stream flow dynamics including the curved sections are solved using MOC. The effectiveness of the derived mathematical models is estimated by simulation results fur a low pressure natural gas pipeline including downward and upward curved sections. The simulation results show that the proposed model and solution can be used for estimating the PIG dynamics when we pig the pipeline including curved section.

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The Implementation of a Battery Simulator with Atypical Characteristics of Batteries (비정형적 배터리 특성을 포함한 배터리 시뮬레이터의 구현)

  • Lee, Dong Sung;Lee, Seong-Won
    • KIPS Transactions on Computer and Communication Systems
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    • v.3 no.11
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    • pp.419-426
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    • 2014
  • The recent trend of performance increase in the smart mobile devices demands more power consumption and lower batter life time. Among three battery models of mathematical model, electrochemical model and electric model, the Thevenin's equivalent circuit with non-linear function model of SOC in the electrical model is widely used. However, the OCV results have only limited accuracy because of the characteristic shift caused by temperature and age and atypical impedance property that cannot expressed by electrical components. In this paper, the new battery model that improves the accuracy of the existing models is proposed. In the proposed simulator the mathematical model for SOC characteristic is improved and the adjustment for the temperature, the age of battery and atypical electrical characteristics. In the experimental results of predicting of the battery in the static and dynamic state, the proposed simulator shows improved MSE comparing to the results of the existing methods.

Effect of nonlinear elastic foundations on dynamic behavior of FG plates using four-unknown plate theory

  • Nebab, Mokhtar;Atmane, Hassen Ait;Bennai, Riadh;Tahar, Benabdallah
    • Earthquakes and Structures
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    • v.17 no.5
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    • pp.447-462
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    • 2019
  • This present paper concerned with the analytic modelling for vibration of the functionally graded (FG) plates resting on non-variable and variable two parameter elastic foundation, based on two-dimensional elasticity using higher shear deformation theory. Our present theory has four unknown, which mean that have less than other higher order and lower theory, and we denote do not require the factor of correction like the first shear deformation theory. The indeterminate integral are introduced in the fields of displacement, it is allowed to reduce the number from five unknown to only four variables. The elastic foundations are assumed a classical model of Winkler-Pasternak with uniform distribution stiffness of the Winkler coefficient (kw), or it is with variables distribution coefficient (kw). The variable's stiffness of elastic foundation is supposed linear, parabolic and trigonometry along the length of functionally plate. The properties of the FG plates vary according to the thickness, following a simple distribution of the power law in terms of volume fractions of the constituents of the material. The equations of motions for natural frequency of the functionally graded plates resting on variables elastic foundation are derived using Hamilton principal. The government equations are resolved, with respect boundary condition for simply supported FG plate, employing Navier series solution. The extensive validation with other works found in the literature and our results are present in this work to demonstrate the efficient and accuracy of this analytic model to predict free vibration of FG plates, with and without the effect of variables elastic foundations.

Detection of Land Subsidence and its Relationship with Land Cover Types using ESA Sentinel Satellites data: A case study of Quetta valley, Pakistan

  • Ahmad, Waqas;Kim, Dongkyun
    • Proceedings of the Korea Water Resources Association Conference
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    • 2018.05a
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    • pp.148-148
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    • 2018
  • Land subsidence caused by excessive groundwater pumping is a serious hydro-geological hazard. The spatial variability in land use, unbalanced groundwater extraction and aquifer characteristics are the key factors which make the problem more difficult to monitor using conventional methods. This study uses the European Space Agency (ESA) Sentinel satellites to investigate and monitor land subsidence varying with different land covers and groundwater use in the arid Quetta valley, Pakistan. The Persistent Scattering Differential Interferometry of Synthetic Aperture Radar (PS-DInSAR) method was used to develop 28 subsidence interferograms of the study area for the period between 16 Oct 2014 and 06 Oct 2016 using ESA's Sentinel-1 SAR data. The uncertainty of DInSAR result is first minimized by removing the dynamic effect caused by atmospheric factors and then filtered using the radar Amplitude Dispersion Index (ADI) to select only the stable pixels. Finally the subsidence maps were generated by spatially interpolating the land subsidence at the stable pixels, the comparison of DInSAR subsidence with GPS readings showed an R 2 of 0.94 and mean absolute error of $5.7{\pm}4.1mm$. The subsidence maps were also analysed for the effect of aquifer type and 4 land covers which were derived from Sentienl-2 multispectral images. The analysis show that during the two year period, the study area experienced highly non-linear land subsidence ranging from 10 to 280 mm. The subsidence at different land covers was significantly different from each other except between the urban and barren land. The barren land and seasonally cultivated area show minor to moderate subsidence while the orchard and urban area with high groundwater extraction rate showed excessive amount of land subsidence. Moreover, the land subsidence and groundwater drawdown was found to be linearly proportional to each other.

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Decision based uncertainty model to predict rockburst in underground engineering structures using gradient boosting algorithms

  • Kidega, Richard;Ondiaka, Mary Nelima;Maina, Duncan;Jonah, Kiptanui Arap Too;Kamran, Muhammad
    • Geomechanics and Engineering
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    • v.30 no.3
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    • pp.259-272
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    • 2022
  • Rockburst is a dynamic, multivariate, and non-linear phenomenon that occurs in underground mining and civil engineering structures. Predicting rockburst is challenging since conventional models are not standardized. Hence, machine learning techniques would improve the prediction accuracies. This study describes decision based uncertainty models to predict rockburst in underground engineering structures using gradient boosting algorithms (GBM). The model input variables were uniaxial compressive strength (UCS), uniaxial tensile strength (UTS), maximum tangential stress (MTS), excavation depth (D), stress ratio (SR), and brittleness coefficient (BC). Several models were trained using different combinations of the input variables and a 3-fold cross-validation resampling procedure. The hyperparameters comprising learning rate, number of boosting iterations, tree depth, and number of minimum observations were tuned to attain the optimum models. The performance of the models was tested using classification accuracy, Cohen's kappa coefficient (k), sensitivity and specificity. The best-performing model showed a classification accuracy, k, sensitivity and specificity values of 98%, 93%, 1.00 and 0.957 respectively by optimizing model ROC metrics. The most and least influential input variables were MTS and BC, respectively. The partial dependence plots revealed the relationship between the changes in the input variables and model predictions. The findings reveal that GBM can be used to anticipate rockburst and guide decisions about support requirements before mining development.

Applying Least Mean Square Method to Improve Performance of PV MPPT Algorithm

  • Poudel, Prasis;Bae, Sang-Hyun;Jang, Bongseog
    • Journal of Integrative Natural Science
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    • v.15 no.3
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    • pp.99-110
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    • 2022
  • Solar photovoltaic (PV) system shows a non-linear current (I) -voltage (V) characteristics, which depends on the surrounding environment factors, such as irradiance, temperature, and the wind. Solar PV system, with current (I) - voltage (V) and power (P) - Voltage (V) characteristics, specifies a unique operating point at where the possible maximum power point (MPP) is delivered. At the MPP, the PV array operates at maximum power efficiency. In order to continuously harvest maximum power at any point of time from solar PV modules, a good MPPT algorithms need to be employed. Currently, due to its simplicity and easy implementation, Perturb and Observe (P&O) algorithms are the most commonly used MPPT control method in the PV systems but it has a drawback at suddenly varying environment situations, due to constant step size. In this paper, to overcome the difficulties of the fast changing environment and suddenly changing the power of PV array due to constant step size in the P&O algorithm, least mean Square (LMS) methods is proposed together with P&O MPPT algorithm which is superior to traditional P&O MPPT. PV output power is predicted using LMS method to improve the tracking speed and deduce the possibility of misjudgment of increasing and decreasing the PV output. Simulation results shows that the proposed MPPT technique can track the MPP accurately as well as its dynamic response is very fast in response to the change of environmental parameters in comparison with the conventional P&O MPPT algorithm, and improves system performance.

Modelling headed stud shear connectors of steel-concrete pushout tests with PCHCS and concrete topping

  • Lucas Mognon Santiago Prates;Felipe Piana Vendramell Ferreira;Alexandre Rossi;Carlos Humberto Martins
    • Steel and Composite Structures
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    • v.46 no.4
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    • pp.451-469
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    • 2023
  • The use of precast hollow-core slabs (PCHCS) in civil construction has been increasing due to the speed of execution and reduction in the weight of flooring systems. However, in the literature there are no studies that present a finite element model (FEM) to predict the load-slip relationship behavior of pushout tests, considering headed stud shear connector and PCHCS placed at the upper flange of the downstand steel profile. Thus, the present paper aims to develop a FEM, which is based on tests to fill this gap. For this task, geometrical non-linear analyses are carried out in the ABAQUS software. The FEM is calibrated by sensitivity analyses, considering different types of analysis, the friction coefficient at the steel-concrete interface, as well as the constitutive model of the headed stud shear connector. Subsequently, a parametric study is performed to assess the influence of the number of connector lines, type of filling and height of the PCHCS. The results are compared with analytical models that predict the headed stud resistance. In total, 158 finite element models are processed. It was concluded that the dynamic implicit analysis (quasi-static) showed better convergence of the equilibrium trajectory when compared to the static analysis, such as arc-length method. The friction coefficient value of 0.5 was indicated to predict the load-slip relationship behavior of all models investigated. The headed stud shear connector rupture was verified for the constitutive model capable of representing the fracture in the stress-strain relationship. Regarding the number of connector lines, there was an average increase of 108% in the resistance of the structure for models with two lines of connectors compared to the use of only one. The type of filling of the hollow core slab that presented the best results was the partial filling. Finally, the greater the height of the PCHCS, the greater the resistance of the headed stud.

Multivariate Congestion Prediction using Stacked LSTM Autoencoder based Bidirectional LSTM Model

  • Vijayalakshmi, B;Thanga, Ramya S;Ramar, K
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.1
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    • pp.216-238
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    • 2023
  • In intelligent transportation systems, traffic management is an important task. The accurate forecasting of traffic characteristics like flow, congestion, and density is still active research because of the non-linear nature and uncertainty of the spatiotemporal data. Inclement weather, such as rain and snow, and other special events such as holidays, accidents, and road closures have a significant impact on driving and the average speed of vehicles on the road, which lowers traffic capacity and causes congestion in a widespread manner. This work designs a model for multivariate short-term traffic congestion prediction using SLSTM_AE-BiLSTM. The proposed design consists of a Bidirectional Long Short Term Memory(BiLSTM) network to predict traffic flow value and a Convolutional Neural network (CNN) model for detecting the congestion status. This model uses spatial static temporal dynamic data. The stacked Long Short Term Memory Autoencoder (SLSTM AE) is used to encode the weather features into a reduced and more informative feature space. BiLSTM model is used to capture the features from the past and present traffic data simultaneously and also to identify the long-term dependencies. It uses the traffic data and encoded weather data to perform the traffic flow prediction. The CNN model is used to predict the recurring congestion status based on the predicted traffic flow value at a particular urban traffic network. In this work, a publicly available Caltrans PEMS dataset with traffic parameters is used. The proposed model generates the congestion prediction with an accuracy rate of 92.74% which is slightly better when compared with other deep learning models for congestion prediction.

Identifying immunodominant multi-epitopes from the envelope glycoprotein of the Lassa mammarenavirus as vaccine candidate for Lassa fever

  • Adekunle Babajide Rowaiye;Ezinne Janefrances Nwonu;Titilayo Mercy Asala;Amoge Chidinma Ogu;Doofan Bur;Chimaobi Chukwu;Angus Nnamdi Oli;Tarimoboere Agbalalah
    • Clinical and Experimental Vaccine Research
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    • v.11 no.3
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    • pp.249-263
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    • 2022
  • Purpose: Lassa fever is a zoonotic acute viral hemorrhagic disease caused by Lassa virus (LASV). There is currently no licensed vaccine for the prevention of the disease. This study is aimed at discovering immunodominant epitopes from the envelope glycoprotein of the Lassa mammarenavirus and designing of a multi-epitope vaccine candidate (VC). Materials and Methods: The amino acid sequences of the envelope glycoprotein of 26 strains of LASV from five countries were selected. After evaluation for antigenicity, immunogenicity, allergenicity, and toxicity, immunodominant CD8, CD4, and linear B lymphocytes were also selected. The selected epitopes were modelled and a molecular docking with the appropriate major histocompatibility complex (MHC) proteins was performed. Using an adjuvant and linkers, a multi-epitope VC was designed. The VC was evaluated for its physicochemical and immunological properties and structurally refined, validated, and mutated (disulphide engineering). The complex formed by the VC and the toll-like receptor-4 receptor was subjected to molecular dynamic simulation (MDS) followed by in silico cloning in a plasmid vector. Results: A VC with 203 sequences, 22.13 kDa weight, isoelectric point of 9.85 (basic), instability index value of 27.62, aliphatic index of 68.87, and GRAVY value of -0.455 (hydrophilic) emerged. The VC is predicted to be non-allergenic with antigenicity, MHC I immunogenicity, and solubility upon overexpression values of 0.81, 2.04, and 0.86 respectively. The VC also has an estimated half-life greater than 10 hours in Escherichia coli and showed stability in all the parameters of MDS. Conclusion: The VC shows good promise in the prevention of Lassa fever but further tests are required to validate its safety and efficacy.