• International Journal of Aeronautical and Space Sciences
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• v.11 no.4
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• pp.326-337
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• 2010

This work addresses problems regarding trajectory planning for unmanned aerial vehicle sensors. Such sensors are used for taking measurements of large nonlinear systems. The sensor investigations presented here entails methods for improving estimations and predictions of large nonlinear systems. Thoroughly understanding the global system state typically requires probabilistic state estimation. Thus, in order to meet this requirement, the goal is to find trajectories such that the measurements along each trajectory minimize the expected error of the predicted state of the system. The considerable nonlinearity of the dynamics governing these systems necessitates the use of computationally costly Monte-Carlo estimation techniques, which are needed to update the state distribution over time. This computational burden renders planning to be infeasible since the search process must calculate the covariance of the posterior state estimate for each candidate path. To resolve this challenge, this work proposes to replace the computationally intensive numerical prediction process with an approximate covariance dynamics model learned using a nonlinear time-series regression. The use of autoregressive time-series featuring a regularized least squares algorithm facilitates the learning of accurate and efficient parametric models. The learned covariance dynamics are demonstrated to outperform other approximation strategies, such as linearization and partial ensemble propagation, when used for trajectory optimization, in terms of accuracy and speed, with examples of simplified weather forecasting.

• Coupled systems mechanics
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• v.1 no.3
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• pp.247-268
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• 2012

A finite element model is developed for dynamic response prediction of floating offshore wind turbine systems considering coupling of wind turbine, floater and mooring system. The model employs Morison's equation with Srinivasan's model for hydrodynamic force and a non-hydrostatic model for restoring force. It is observed that for estimation of restoring force of a small floater, simple hydrostatic model underestimates the heave response after the resonance peak, while non-hydrostatic model shows good agreement with experiment. The developed model is used to discuss influence of heave plates and modeling of mooring system on floater response. Heave plates are found to influence heave response by shifting the resonance peak to longer period, while response after resonance is unaffected. The applicability of simplified linear modeling of mooring system is investigated using nonlinear model for Catenary and Tension Legged mooring. The linear model is found to provide good agreement with nonlinear model for Tension Leg mooring while it overestimates the surge response for Catenary mooring system. Floater response characteristics under different wave directions for the two types of mooring system are similar in all six modes but heave, pitch and roll amplitudes is negligible in tension leg due to high restraint. The reduced amplitude shall lead to reduction in wind turbine loads.

• Journal of the Society of Naval Architects of Korea
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• v.50 no.1
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• pp.49-58
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• 2013

Recently, the design of commercial ships with less green-house gas is one of great interests in naval architecture fields. Ship designers are asked to find optimum hull forms with minimum resistance in ocean waves. The accurate computation of added resistance, therefore, is getting more important for the prediction of power increase in random ocean waves. This study focuses on the numerical computation of added resistance on ships with Ax-bow shapes which are designed to reduce added resistance. To this end, the time-domain Rankine panel methods based on weakly-nonlinear and weak-scatterer approaches are applied, which can reflect the influence of above-still-water bow shape. As computational models, KCS and KVLCC2 hull forms are considered. Each ship is combined with the three types of Ax-bow shape, and computational results are compared each other.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.2
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• pp.137-143
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• 2011

The pitch motion of a gravity-gradient satellite can be chaotic, depending on the ratio of mass moments of inertia and the eccentricity of the satellite orbit. For a precise prediction of motion, chaotic pitch motion has to be changed to non-chaotic motion. Feedback control can be used to obtain nonchaotic pitch motion. For chaos control and stabilization of the pitch motion of a gravity-gradient satellite, a feedback control system is designed, based on the linear nonautonomous system obtained by linearizing the nonlinear pitch motion. The control law obtained has two parameters and is applied to chaotic nonlinear pitch motion. The nonlinear control system satisfies the proposed control objectives in the range of the nonchaotic parameter space.

• Geomechanics and Engineering
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• v.18 no.3
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• pp.299-313
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• 2019

This research investigated the nonlinear compressibility, permeability, the yielding due to structural degradation and their effects on consolidation behavior of structured soft soils. Based on oedometer and hydraulic conductivity test results of natural and reconstituted soft clays, linear log (1+e) ~ $log\;{\sigma}^{\prime}$ and log (1+e) ~ $log\;k_v$ relationships were developed to capture the variations in compressibility and permeability, and the yield stress ratio (YSR) was introduced to characterize the soil structure of natural soft clay. Semi-analytical solutions for one-dimensional consolidation of soft clay under time-dependent loading incorporating the effects of soil nonlinearity and soil structure were proposed. The semi-analytical solutions were verified against field measurements of a well-documented test embankment and they can give better accuracy in prediction of excess pore pressure compared to the predictions using the existing analytical solutions. Additionally, parametric studies were conducted to analyze the effects of YSR, compression index (${\lambda}_r$ and ${\lambda}_c$), and permeability index (${\eta}_k$) on the consolidation behavior of structured soft clays. The magnitude of the difference between degree of consolidation based on excess pore pressure ($U_p$) and that based on strain ($U_s$) depends on YSR. The parameter ${\lambda}_c/{\eta}_k$ plays a significant role in predicting consolidation behavior.

• Structural Engineering and Mechanics
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• v.72 no.2
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• pp.191-201
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• 2019

Finite element analysis is one of the most used tools for studying femoral neck fracture. Nerveless, consensus concerning either the choice of material characteristics, damage law and /or geometric models (linear on nonlinear) remains unreached. In this work, we propose a numerical quasi-brittle damage model to describe the behavior of the proximal femur associated with two methods to evaluate the Young modulus. Eight proximal femur finite elements models were constructed from CT scan data (4 donors: 3 women; 1 man). The numerical computations showed a good agreement between the numerical curves (load - displacement) and the experimental ones. A very encouraging result is obtained when a comparison is made between the computed fracture loads and the experimental ones ($R^2=0.825$, Relative error =6.49%). All specific numerical computation provided very fair qualitative matches with the fracture patterns for the sideway fall simulation. Finally, the comparative study based on 32 simulations adopting linear and nonlinear meshing led to the conclusion that the quantitatively results are improved when a nonlinear mesh is used.

• Steel and Composite Structures
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• v.48 no.4
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• pp.461-474
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• 2023

Concrete-filled steel tubes are among the most efficient compressive structural members because the strength of the concrete is enhanced given that the surrounding steel tube confines the concrete laterally and the steel tube is restrained with regard to inward deformation due to the concrete existing inside. Accurate estimations of the ultimate compressive strength of CFT are important for efficient designs of CFT members. In this study, an analytical procedure that directly formulates the interaction between the concrete and steel tube by considering the nonlinear Poisson effect and stress-strain curve of the concrete including the confinement effect is proposed. The failure stress of concrete and von-Mises failure yield criterion of steel were used to consider multi-dimensional stresses. To verify the prediction capabilities of the proposed analytical procedure, 99 circular CFT experimental data instances from other studies were used for a comparison with AISC, Eurocode 4, and other researchers' predictions. From the comparison, it was revealed that the proposed procedure more accurately predicted the ultimate compressive strength of a circular CFT regardless of the range of the design variables, in this case the concrete compressive strength, yield strength of the steel tube and diameter relative to the thickness ratio of the tube.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.4
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• pp.286-294
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• 2016

In the initial design stage, the geometry of systems needs to be optimized regarding its performance. However, performance analysis is very time-consuming. Therefore, optimization becomes difficult/impossible problems because we need to evaluate the system performance for alternative design cases. To overcome this problem, many researchers perform prediction of system performance using the approximation model. The response surface method (RSM) is typically used to predict the system performance in the various research fields, but it presents prediction errors for highly nonlinear systems. The major objective of this paper is to propose a proper prediction method for marine system problems. Case studies of marine systems (the substructure of a floating offshore wind turbine considering hydrodynamic performance and bulk carrier bottom stiffened panels considering structure performance) verify that the proposed method is applicable to performance prediction in marine systems.

• International Journal of Computer Science & Network Security
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• v.24 no.9
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• pp.63-76
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• 2024

Weather forecasting has become a very popular topic nowadays among researchers because of its various effects on global lives. It is a technique to predict the future, what is going to happen in the atmosphere by analyzing various available datasets such as rain, snow, cloud cover, temperature, moisture in the air, and wind speed with the help of our gained scientific knowledge i.e., several approaches and set of rules or we can say them as algorithms that are being used to analyze and predict the weather. Weather analysis and prediction are required to prevent nature from natural losses before it happens by using a Deep Learning Approach. This analysis and prediction are the most challenging task because of having multidimensional and nonlinear data. Several Deep Learning Approaches are available: Numerical Weather Prediction (NWP), needs a highly calculative mathematical equation to gain the present condition of the weather. Quantitative precipitation nowcasting (QPN), is also used for weather prediction. In this article, we have implemented and analyzed the various distinct techniques that are being used in data mining for weather prediction.

• Smart Structures and Systems
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• v.33 no.5
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• pp.365-374
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• 2024

This paper adopts a new approach in which nonlinear vibrations can be controlled using fuzzy controllers by optimal grey evolutionary algorithm. If the fuzzy controller cannot stabilize the systems, then the high frequency is injected into the system to assist the controller, and the system is asymptotically stabilized by adjusting the parameters. This paper uses the GM (grey model) and the neural network prediction model. The structure of the neural network is improved from a single factor, and multiple data inputs are extended to various factors and numerous data inputs. The improved model expands the applicable range of uncontrolled elements and improves the accuracy of controlled prediction, using the model that has been trained and stabilized by multiple learning. The simulation results show that the improved gray neural network model has higher prediction accuracy and reliability than the traditional GM model, improving controlled management and pre-control ability. In the combined prediction, the time series parameters and the predicted values obtained from the GM (1,1) (Grey Model of first order and one variable) are simultaneously used as the input terms of the neural network, considering the influence of the non-equal spacing of the data, which makes the results of the combined gray neural network model more rationalized. By adjusting the model structure and system parameters to simulate and analyze the controlled elements, the corresponding risk change trend graphs and prediction numerical calculation results are obtained, which also realize the effective prediction of controlled elements. According to the controlled warning principle and objective, the fuzzy evaluation method establishes the corresponding early warning response method. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage.