• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.7
• /
• pp.3309-3328
• /
• 2017

The application of Internet of Things (IoT) in the next generation cellular networks imposes a new characteristic on the data traffic, where a massive number of small packets need to be transmitted. In addition, some emerging IoT-based emergency services require a real-time data delivery within a few milliseconds, referring to as ultra-low latency transmission. However, current techniques cannot provide such a low latency in combination with a mice-flow traffic. In this paper, we propose a dynamic resource reservation schema based on an air-interface slicing scheme in the context of a massive number of sensors with emergency flows. The proposed schema can achieve an air-interface latency of a few milliseconds by means of allowing emergency flows to be transported through a dedicated radio connection with guaranteed network resources. In order to schedule the delay-sensitive flows immediately, dynamic resource updating, silence-probability based collision avoidance, and window-based re-transmission are introduced to combine with the frame-slotted Aloha protocol. To evaluate performance of the proposed schema, a probabilistic model is provided to derive the analytical results, which are compared with the numerical results from Monte-Carlo simulations.

• Polymer(Korea)
• /
• v.35 no.6
• /
• pp.513-519
• /
• 2011

Molecular simulations via the molecular dynamics method have been carried out to investigate the dynamic collision properties of penetrable-sphere model fluids. The collision frequencies, the mean free paths, the angle distributions of the hard-type reflection and the soft-type penetration, and the effective packing fractions are computed over a wide range of the packing fraction ${\phi}$ and the repulsive energy ${\varepsilon}^*$. The soft-type collisions are dominated for lower repulsive energy systems, while the hardtype collisions for higher repulsive energy systems. Very interestingly, the ratio of the soft-type (or, the hard-type) collision frequency to the total collision frequency is directly related with the Boltzmann factor of acceptance (or rejection) probabilities in the canonical ensemble Monte Carlo calculations. Such dynamic collision properties are shown to be restricted for highly repulsive and dense systems of ${\varepsilon}^*{\geqq}3.0 $and ${\phi}{\geqq}0.7$, indicating the cluster forming structures in the penetrable-sphere model.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.21 no.3
• /
• pp.211-216
• /
• 2008

Recently a lot of researches have been conducted on the progressive collapse of structures which is the total collapse of structures initiated by localized damage. Most of the previous studies on the field of progressive collapse have followed deterministic approach without considering uncertainty involved in design variables, which results in unknown reliability of the analysis results. In this study the sensitivity analyses are carried out with design variables such as yield strength, live load, damping ratio, and elastic modulus on the vertical deflection of the joint from which a column is suddenly removed. The Monte Calro simulation, tornado diagram method, and the first order second moment method(FOSM) are applied for the sensitivity study. According to the nonlinear static analysis results, the vertical deflection is most affected by the variation of yield strength of beams. The nonlinear dynamic analyses show that the behaviour of model structures is highly sensitive to variation of the yield strength of beams and the structural damping ratio.

• Structural Engineering and Mechanics
• /
• v.42 no.2
• /
• pp.175-189
• /
• 2012

This paper presents an algorithm for structural reliability with the response surface method. For this aim, an approach with three stages is proposed named as improved response surface method. In the algorithm, firstly, a quadratic approximate function is formed and design point is determined with First Order Reliability Method. Secondly, a point close to the exact limit state function is searched using the design point. Lastly, vector projected method is used to generate the sample points and Second Order Reliability Method is performed to obtain reliability index and probability of failure. Five numerical examples are selected to illustrate the proposed algorithm. The limit state functions of three examples (cantilever beam, highly nonlinear limit state function and dynamic response of an oscillator) are defined explicitly and the others (frame and truss structures) are defined implicitly. ANSYS finite element program is utilized to obtain the response of the structures which are needed in the reliability analysis of implicit limit state functions. The results (reliability index, probability of failure and limit state function evaluations) obtained from the improved response surface are compared with those of Monte Carlo Simulation, First Order Reliability Method, Second Order Reliability Method and Classical Response Surface Method. According to the results, proposed algorithm gives better results for both reliability index and limit state function evaluations.

• Advances in aircraft and spacecraft science
• /
• v.7 no.5
• /
• pp.405-423
• /
• 2020

Non-linear energy sink (NES) is an emerging passive absorber able to mitigate the dynamic response of structures without any external energy supply, resonating with all the modes of the primary structure to control. However, its inherent non-linearities hinder its large-scale use and leads to complicated design procedures. For this purpose, an approximate design approach is herein proposed in a stochastic framework. Since loads are random in nature, the stochastic analysis of non-linear systems may be performed by means of computational intensive techniques such as Monte Carlo simulations (MCS). Alternatively, the Stochastic Linearisation (SL) technique has proven to be an effective tool to investigate the performance of different passive control systems under random loads. Since controlled systems are generally non-classically damped and most of SL algorithms operate recursively, the computational burden required is still large for those problems that make intensive use of SL technique, as optimal design procedures. Herein, a procedure to speed up the Stochastic Linearisation technique is proposed by avoiding or strongly reducing numerical evaluations of response statistics. The ability of the proposed procedure to effectively reduce the computational effort and to reliably design the NES is showed through an application on a well-known case study related to the vibrations mitigation of an aircraft wing.

• Earthquakes and Structures
• /
• v.12 no.3
• /
• pp.359-374
• /
• 2017

The seismic events in Northern Italy, May 2012, have revealed the seismic vulnerability of typical Italian precast industrial buildings. The aim of this paper is to present a seismic fragility model for Italian RC precast buildings, to be used in earthquake loss estimation and seismic risk assessment by comparing two building typologies and three different codes: D.M. 3-03-1975, D.M. 16-01-1996 and current Italian building code that has been released in 2008. Based on geometric characteristics and design procedure applied, ten different building classes were identified. A Monte Carlo simulation was performed for each building class in order to generate the building stock used for the development of fragility curves trough analytical method. The probabilistic distributions of geometry were mainly obtained from data collected from 650 field surveys, while the material properties were deduced from the code in place at the time of construction or from expert opinion. The structures were modelled in 2D frameworks; since the past seismic events have identified the beam-column connection as the weakest element of precast buildings, two different modelling solutions were adopted to develop fragility curves: a simple model with post processing required to detect connection collapse and an innovative modelling solution able to reproduce the real behaviour of the connection during the analysis. Fragility curves were derived using both nonlinear static and dynamic analysis.

• Structural Engineering and Mechanics
• /
• v.25 no.3
• /
• pp.311-330
• /
• 2007

Model-based predictions of structural behavior are negatively affected by uncertainties of various type and in various stages of the structural analysis. The present paper focusses on dynamic analysis and addresses the effects of uncertainties concerning material and geometric parameters, mainly in the context of modal analysis of large-scale structures. Given the large number of uncertain parameters arising in this case, highly scalable simulation-based methods are adopted, which can deal with possibly thousands of uncertain parameters. In order to solve the reliability problem, i.e., the estimation of very small exceedance probabilities, an advanced simulation method called Line Sampling is used. In combination with an efficient algorithm for the estimation of the most important uncertain parameters, the method provides good estimates of the failure probability and enables one to quantify the error in the estimate. Another aspect here considered is the uncertainty quantification for closely-spaced eigenfrequencies. The solution here adopted represents each eigenfrequency as a weighted superposition of the full set of eigenfrequencies. In a case study performed with the FE model of a satellite it is shown that the effects of uncertain parameters can be very different in magnitude, depending on the considered response quantity. In particular, the uncertainty in the quantities of interest (eigenfrequencies) turns out to be mainly caused by very few of the uncertain parameters, which results in sharp estimates of the failure probabilities at low computational cost.

• Structural Engineering and Mechanics
• /
• v.25 no.3
• /
• pp.347-363
• /
• 2007

A novel methodology, referred to as Auxiliary Domain Method (ADM), allowing for a very efficient solution of nonlinear reliability problems is presented. The target nonlinear failure domain is first populated by samples generated with the help of a Markov Chain. Based on these samples an auxiliary failure domain (AFD), corresponding to an auxiliary reliability problem, is introduced. The criteria for selecting the AFD are discussed. The emphasis in this paper is on the selection of the auxiliary linear failure domain in the case where the original nonlinear reliability problem involves multiple objectives rather than a single objective. Each reliability objective is assumed to correspond to a particular response quantity not exceeding a corresponding threshold. Once the AFD has been specified the method proceeds with a modified subset simulation procedure where the first step involves the direct simulation of samples in the AFD, rather than standard Monte Carlo simulation as required in standard subset simulation. While the method is applicable to general nonlinear reliability problems herein the focus is on the calculation of the probability of failure of nonlinear dynamical systems subjected to Gaussian random excitations. The method is demonstrated through such a numerical example involving two reliability objectives and a very large number of random variables. It is found that ADM is very efficient and offers drastic improvements over standard subset simulation, especially when one deals with low probability failure events.

• Smart Structures and Systems
• /
• v.3 no.3
• /
• pp.245-261
• /
• 2007

Nonlinear time-domain system identification (SI) algorithm is proposed to assess damage in a shear building by synchronously estimating time-varying stiffness and damping parameters using measured acceleration data. Mass properties have been assumed as the a priori known information. Viscous damping was utilized for the current research. To chase possible nonlinear dynamic behavior under severe vibration, an incremental governing equation of vibrational motion has been utilized. Stiffness and damping parameters are estimated at each time step by minimizing the response error between measured and computed acceleration increments at the measured degrees-of-freedom. To solve a nonlinear constrained optimization problem for optimal structural parameters, sensitivities of acceleration increment were formulated with respect to stiffness and damping parameters, respectively. Incremental state vectors of vibrational motion were computed numerically by Newmark-${\beta}$ method. No model is pre-defined in the proposed algorithm for recovering the nonlinear response. A time-window scheme together with Monte Carlo iterations was utilized to estimate parameters with noise polluted sparse measured acceleration. A moving average scheme was applied to estimate the time-varying trend of structural parameters in all the examples. To examine the proposed SI algorithm, simulation studies were carried out intensively with sample shear buildings under earthquake excitations. In addition, the algorithm was applied to assess damage with laboratory test data obtained from free vibration on a three-story shear building model.

• The Bulletin of The Korean Astronomical Society
• /
• v.41 no.2
• /
• pp.61.1-61.1
• /
• 2016

Black hole (BH) mass is a fundamental quantity to understand BH growth, galaxy evolution, and connection between them. Thus, obtaining accurate and precise BH mass estimates over cosmic time is of paramount importance. The rest-frame UV CIV ${\lambda}1549$ broad emission line is commonly used for BH mass estimates in high-redshift AGNs (i.e., $2{\leq}z{\leq}5$) when single-epoch (SE) optical spectra are available. Achieving correct and accurate calibration for CIV-based SE BH mass estimators against the most reliable reverberation-mapping based BH mass estimates is thus practically important and still useful. By performing multi-component spectral decomposition analysis to obtained high-quality HST UV spectra for the updated sample of local reverberation-mapped AGNs including new HST STIS observations, CIV emission line widths and continuum luminosities are consistently measured. Using a Bayesian hierarchical model with MCMC sampling based on Hamiltonian Monte Carlo algorithm (Stan NUTS), we provide the most consistent and accurate calibration of CIV-based BH mass estimators for the three line width characterizations, i.e., full width at half maximum (FWHM), line dispersion (${\sigma}_{line}$), and mean absolute deviation (MAD), in the extended BH mass dynamic range of log $M_{BH}/M_{\odot}=6.5-9.1$.