• Steel and Composite Structures
• /
• v.45 no.3
• /
• pp.409-423
• /
• 2022

Nowadays, there is a high demand for great structural implementation and multifunctionality with excellent mechanical properties. The porous structures reinforced by graphene platelets (GPLs) having valuable properties, such as heat resistance, lightweight, and excellent energy absorption, have been considerably used in different engineering implementations. However, stiffness of porous structures reduces significantly, due to the internal cavities, by adding GPLs into porous medium, effective mechanical properties of the porous structure considerably enhance. This paper is relating to vibration analysis of fluidconveying cantilever porous graphene platelet reinforced (GPLR) pipe with fractional viscoelastic model resting on foundations. A dynamical model of cantilever porous GPLR pipes conveying fluid and resting on a foundation is proposed, and the vibration, natural frequencies and primary resonant of such a system are explored. The pipe body is considered to be composed of GPLR viscoelastic polymeric pipe with porosity in which Halpin-Tsai scheme in conjunction with the fractional viscoelastic model is used to govern the construction relation of nanocomposite pipe. Three different porosity distributions through the pipe thickness are introduced. The harmonic concentrated force is also applied to the pipe and the excitation frequency is close to the first natural frequency. The governing equation for transverse motions of the pipe is derived by the Hamilton principle and then discretized by the Galerkin procedure. In order to obtain the frequency-response equation, the differential equation is solved with the assumption of small displacement, damping coefficient, and excitation amplitude by the multiple scale method. A parametric sensitivity analysis is carried out to reveal the influence of different parameters, such as nanocomposite pipe properties, fluid velocity and nonlinear viscoelastic foundation coefficients, on the primary resonance and linear natural frequency. Results indicate that the GPLs weight fraction porosity coefficient, fractional derivative order and the retardation time have substantial influences on the dynamic response of the system.

• Steel and Composite Structures
• /
• v.50 no.2
• /
• pp.201-216
• /
• 2024

This paper is motivated by the lack of studies relating to vibration and nonlinear resonance of fluid-conveying cantilever porous GPLR pipes with fractional viscoelastic model resting on nonlinear foundations. A dynamical model of cantilever porous Graphene Platelet Reinforced (GPLR) pipes conveying fluid and resting on nonlinear foundation is proposed, and the vibration, natural frequencies and primary resonant of such system are explored. The pipe body is considered to be composed of GPLR viscoelastic polymeric pipe with porosity in which Halpin-Tsai scheme in conjunction with fractional viscoelastic model is used to govern the construction relation of the nanocomposite pipe. Three different porosity distributions through the pipe thickness are introduced. The harmonic concentrated force is also applied on pipe and excitation frequency is close to the first natural frequency. The governing equation for transverse motion of the pipe is derived by the Hamilton principle and then discretized by the Galerkin procedure. In order to obtain the frequency-response equation, the differential equation is solved with the assumption of small displacement, damping coefficient, and excitation amplitude by the multiple scale method. A parametric sensitivity analysis is carried out to reveal the influence of different parameters, such as nanocomposite pipe properties, fluid velocity and nonlinear viscoelastic foundation coefficients, on the primary resonance and linear natural frequency. Results indicate that the GPLs weight fraction porosity coefficient, fractional derivative order and the retardation time have substantial influences on the dynamic response of the system.

• Journal of Biosystems Engineering
• /
• v.39 no.4
• /
• pp.377-388
• /
• 2014

Purpose: Determining the spatial structure of data is important in understanding within-field variability for site-specific crop management. An understanding of the spatial structures present in the data may help illuminate interrelationships that are important in subsequent explanatory analyses, especially when site variables are correlated or are a combined response to multiple causative factors. Methods: In this study, correlation, principal component analysis, and single and nested variogram models were applied to soil electrical conductivity and chemical property data of two fields in central Missouri, USA. Results: Some variables that were highly correlated, or were strongly expressed in the same principal component, exhibited similar spatial ranges when fitted with a single variogram model. However, single variogram results were dependent on the active lag distance used, with short distances (30 m) required to fit short-range variability. Longer active lag distances only revealed long-range spatial components. Nested models generally yielded a better fit than single models for sensor-based conductivity data, where multiple scales of spatial structure were apparent. Gaussian-spherical nested models fit well to the data at both short (30 m) and long (300 m) active lag distances, generally capturing both short-range and long-range spatial components. As soil conductivity relates strongly to profile texture, we hypothesize that the short-range components may relate to the scale of erosion processes, while the long-range components are indicative of the scale of landscape morphology. Conclusion: In this study, we investigated the effect of changing active lag distance on the calculation of the range parameter. Future work investigating scale effects on other variogram parameters, including nugget and sill variances, may lead to better model selection and interpretation. Once this is achieved, separation of nested spatial components by factorial kriging may help to better define the correlations existing between spatial datasets.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.5
• /
• pp.36-41
• /
• 2016

In this study, numerical analyses were used to investigate the performance of a coupling control method for the dynamic responses of adjacent buildings under multiple hazards. Numerical simulations were done using the earthquake loads of regions with strong seismicity in Los Angeles, California, and the wind loads in regions with strong winds in Charleston, North Carolina. The artificial earthquake and wind loads were made using SIMQKE and Kaimal Spectrum based on ASCE 7-10. Ten-story and twenty-story adjacent buildings were selected as example structures, and nonlinear hysteretic dampers were used to connect them. The Bouc-Wen model was used to model the nonlinear hysteretic dampers. The results show that the proposed control method could effectively reduce the dynamic responses, and the optimal control designs were different for each hazard.

• Animal Bioscience
• /
• v.37 no.6
• /
• pp.1077-1084
• /
• 2024

Objective: The present work was conducted to evaluate suitable variables and develop prediction equations using chemical composition and physical characteristics for estimating standardized ileal digestibility (SID) of lysine (Lys) in full-fat soybeans (FFSB). Methods: The chemical composition and physical characteristics were determined including trypsin inhibitor activity (TIA), urease activity (UA), protein solubility in 0.2% potassium hydroxide (KOH), protein dispersibility index (PDI), lysine to crude protein ratio (Lys:CP), reactive Lys:CP ratio, neutral detergent fiber, neutral detergent insoluble nitrogen (NDIN), acid detergent insoluble nitrogen (ADIN), acid detergent fiber, L* (lightness), and a* (redness). Pearson's correlation (r) was computed, and the relationship between variables was determined by linear or quadratic regression. Stepwise multiple regression was performed to develop prediction equations for SID of Lys. Results: Negative correlations (p<0.01) between SID of Lys and protein quality indicators were observed for TIA (r = -0.80), PDI (r = -0.80), and UA (r = -0.76). The SID of Lys also showed a quadratic response (p<0.01) to UA, NDIN, TIA, L*, KOH, a* and Lys:CP. The best-fit model for predicting SID of Lys in FFSB included TIA, UA, NDIN, and ADIN, resulting in the highest coefficient of determination (R² = 0.94). Conclusion: Quadratic regression with one variable indicated the high accuracy for UA, NDIN, TIA, and PDI. The multiple linear regression including TIA, UA, NDIN, and ADIN is an alternative model used to predict SID of Lys in FFSB to improve the accuracy. Therefore, multiple indicators are warranted to assess either insufficient or excessive heat treatment accurately, which can be employed by the feed industry as measures for quality control purposes to predict SID of Lys in FFSB.

• Journal of the Korean Society of Safety
• /
• v.35 no.4
• /
• pp.84-91
• /
• 2020

The Korean nuclear industry developed the SPACE (Safety and Performance Analysis Code for nuclear power plants) code and this code adpots two-phase flows, two-fluid, three-field models which are comprised of gas, continuous liquid and droplet fields and has a capability to simulate three-dimensional model. According to the revised law by the Nuclear Safety and Security Commission (NSSC) in Korea, the multiple failure accidents that must be considered for accident management plan of nuclear power plant was determined based on the lessons learned from the Fukushima accident. Generally, to improve the reliability of the calculation results of a safety analysis code, verification work for separate and integral effect experiments is required. In this reason, the goal of this work is to verify calculation capability of SPACE code for multiple failure accident. For this purpose, it was selected the experiment which was conducted to simulate a Multiple Steam Generator Tube Rupture(MSGTR) accident with Passive Auxiliary Feedwater System(PAFS) operation by Korea Atomic Energy Research Institute (KAERI) and focused that the comparison between the experiment results and code calculation results to verify the performance of the SPACE code. The MSGR accident has a unique feature of the penetration of the barrier between the Reactor Coolant System (RCS) and the secondary system resulting from multiple failure of steam generator U-tubes. The PAFS is one of the advanced safety features with passive cooling system to replace a conventional active auxiliary feedwater system. This system is passively capable of condensing steam generated in steam generator and feeding the condensed water to the steam generator by gravity. As the results of overall system transient response using SPACE code showed similar trends with the experimental results such as the system pressure, mass flow rate, and collapsed water level in component. In conclusion, it could be concluded that the SPACE code has sufficient capability to simulate a MSGTR accident.

• Land and Housing Review
• /
• v.12 no.4
• /
• pp.93-101
• /
• 2021

As the number of small households (1 to 2 persons per household) in Korea gradually increases, so does the importance of housing supply policies for small households. In response to the increase in small households, the government has been continuously supplying urban housing for these households. Since housing for small households is a sales and rental business similar to apartments and general business facilities, it is important for the building owner to calculate the project's estimated construction duration during the planning stage. Review of literature found a model for estimating the duration of construction of large-scale buildings but not for small-scale buildings such as urban housing for small households. Therefore this study aimed to develop and verify a model for estimating construction duration for urban housing at the planning stage based on multiple regression analysis. Independent variables inputted into the estimation model were building site area, building gross floor area, number of below ground floors, number of above ground floors, number of buildings, and location. The modified coefficient of determination (R_a²) of the model was 0.547. The developed model resulted in a Root Mean Square Error (RMSE) of 171.26 days and a Mean Absolute Percentage Error (MAPE) of 26.53%. The developed estimation model is expected to provide reliable construction duration calculations for small-scale urban residential buildings during the planning stage of a project.

• Advances in aircraft and spacecraft science
• /
• v.6 no.6
• /
• pp.529-550
• /
• 2019

The effect of multiple process parameters on a set of continuous response variables is, especially in experimental designs, difficult and intricate to determine. Due to the complexity in aeroacoustic and vibroacoustic studies, the often-performed simple one-factor-at-a-time method turns out to be the least effective approach. In contrast, the statistical Design of Experiments is a technique used with the objective to maximize the obtained information while keeping the experimental effort at a minimum. The presented work aims at giving insights on Design of Experiments applied to aeroacoustic and vibroacoustic problems while comparing different experimental designs and approximation models. For this purpose, an experimental rig of a ducted low-pressure fan is developed that allows gathering data of both, aerodynamic and aeroacoustic nature while analysing three independent process parameters. The experimental designs used to sample the design space are a Central Composite design and a Box-Behnken design, both used to model a response surface regression, and Latin Hypercube sampling to model an Artificial Neural network. The results indicate that Latin Hypercube sampling extracts information that is more diverse and, in combination with an Artificial Neural network, outperforms the quadratic response surface regressions. It is shown that the Latin Hypercube sampling, initially developed for computer-aided experiments, can also be used as an experimental design. To further increase the benefit of the presented approach, spectral information of every experimental test point is extracted and Artificial Neural networks are chosen for modelling the spectral information since they show to be the most universal approximators.

• Smart Structures and Systems
• /
• v.21 no.4
• /
• pp.449-467
• /
• 2018

In this paper, a theoretical and numerical study on bridge simultaneous damage detection procedure for identifying both the system parameters and input excitation mass, are presented. This method is called 'Adjoint Variable Method' which is an iterative gradient-based model updating method based on the dynamic response sensitivity. The main advantage of proposed method is inclusion of an analytical method to augment the accuracy and speed of the solution. Moving mass is a model which takes into account the inertia effects of the vehicle. This interaction model is a time varying system and proposed method is capable of detecting damage in this variable system. Robustness of proposed method is illustrated by correctly detection of the location and extension of predetermined single, multiple and random damages in all ranges of speed and mass ratio of moving vehicle. A comparison study of common sensitivity and proposed method confirms its efficiency and performance improvement in sensitivity-based damage detection methods. Various sources of errors including the effects of measurement noise and initial assumption error in stability of method are also discussed.

• Smart Structures and Systems
• /
• v.17 no.6
• /
• pp.1017-1030
• /
• 2016

This study focuses on the system identification of reinforced concrete bridges using vector autoregressive model (VAR). First, the time series output response from a bridge establishes the autoregressive (AR) models. AR models are one of the most accurate methods for stationary time series. Burg's algorithm estimates the autoregressive coefficients (ARCs) at p-lag by reducing the sum of the forward and the backward errors. The computed ARCs are assembled in the state system matrix and the eigen-system realization algorithm (ERA) computes: the eigenvector matrix that contains the vectors of the mode shapes, and the eigenvalue matrix that contains the associated natural frequencies. By taking advantage of the characteristic of the AR model with ERA (ARMERA), civil engineering can address problems related to damage detection. Operational modal analysis using ARMERA is applied to three experiments. One experiment is coupled with an artificial neural network algorithm and it can detect damage locations and extension. The neural network uses a specific number of ARCs as input and multiple submatrix scaling factors of the structural stiffness matrix as output to represent the damage.