• Earthquakes and Structures
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• v.3 no.1
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• pp.17-35
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• 2012

Simplified equations for fundamental period of vibration of skeletal structures provided by most seismic design provisions suffer from the absence of any associated confidence levels and of any reference to their empirical basis. Therefore, such equations may typically give a sector of designers the false impression of yielding a fairly accurate value of the period of vibration. This paper, although not addressing simplified codes equations, introduces a set of mathematical equations utilizing the theory of error propagation and First-Order Second-Moment (FOSM) techniques to determine bounds on the relative error in theoretically calculated fundamental period of vibration of skeletal structures. In a complementary step, and for verification purposes, Monte Carlo simulation technique has been also applied. The latter, despite involving larger computational effort, is expected to provide more precise estimates than FOSM methods. Studies of parametric uncertainties applied to reinforced concrete frame bents - potentially idealized as SDOF systems - are conducted demonstrating the effect of randomness and uncertainty of various relevant properties, shaping both mass and stiffness, on the variance (i.e. relative error) in the estimated period of vibration. Correlation between mass and stiffness parameters - regarded as random variables - is also thoroughly discussed. According to achieved results, a relative error in the period of vibration in the order of 19% for new designs/constructions and of about 25% for existing structures for assessment purposes - and even climbing up to about 36% in some special applications and/or circumstances - is acknowledged when adopting estimates gathered from the literature for relative errors in the relevant random input variables.

• Journal of the Society of Naval Architects of Korea
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• v.49 no.5
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• pp.400-409
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• 2012

It is not easy to know the accurate mass and mass moment of inertia of robot. Because of this uncertainty, error may exist when we control the robot based on the inaccurate mass information. Moreover the properties of the portable robot can change during its operation. Therefore we developed the motion simulator based on the adaptive control. First, the computed torque control was carried out in order to minimize an error between target angles and real angles. The computed torque control is based on the equation of robot motion, which is derived from the Lagrange-Euler equation. To minimize the error between the real model and the approximated model, the adaptive control was carried out. During this simulation, the interference check was also carried out. The interference check verifies that the robot can move successfully without any collision.

• Tunnel and Underground Space
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• v.15 no.2 s.55
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• pp.129-136
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• 2005

This paper describes the implementation of rock mass rating evaluation based on genetic algorithm(GA) and conditional simulation technique to estimate RMR in the area without sufficient borehole data RMR were estimated by GA and conditional simulation technique with reflecting distribution feature and spatial correlation. And RMR determined by GA were compared with the results from kriging. Through the analysis of the results from 30 simulations, the uncertainty of estimation could be quantified.

• Smart Structures and Systems
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• v.24 no.4
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• pp.447-457
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• 2019

The use of Tuned mass dampers (TMD) has proved to be effective in reducing the effects of vibrations caused by wind loads and far-field seismic action. However, its effectiveness in controlling the dynamic response of structures under near-fault earthquakes is still under discussion. In this case, the uncertainty about the TMD performance arises from the short significant duration of near-fault ground motions. In this work, the TMD effectiveness for increasing the safety margin against collapse of structures subjected to near-fault earthquakes is investigated. In order to evaluate the TMD performance in the proposed scenario, the nonlinear dynamic response of two reinforced concrete (RC) frames was analyzed. TMDs with different mass values were added to these structures, and a set of near-fault records with frequency content close to the fundamental frequency of the structure was employed. Through a series of nonlinear dynamic analysis, the minimum amplitude of each seismic record that causes the structural collapse was found. By comparing this value, called collapse acceleration, for the case of the structures with and without TMD, the benefit produced by the addition of the control device was established.

• Fire Science and Engineering
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• v.33 no.4
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• pp.35-40
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• 2019

In this study, the mass flow rate of the heat release rate equation, which is the major factor of the oxygen consumption method, was analyzed for the fundamental investigation of the cone-calorimeter (5 m length and 0.3 m diameter). The shapes of a completely empty inside, 3 mm pore diameter mesh and pore diameter 10 mm honeycomb with 0.76 porosity were constructed using the cone-calorimeter. To calculate the mass flow rate, four bi-directional probes and thermocouples were installed in a uniform position in the vertical direction of flow. The velocity gradient and flow perturbation were measured from the increase in Reynolds number. As the flow capacity increased, the speed gradient increased in all three shapes relative to the turbulence intensity. In addition, the deviation of extended uncertainty to the mass flow was completely low in the order of empty space, mesh (d_p = 3 mm) and honeycomb (d_p = 10 mm and 𝜖 = 0.76) at the 95% confidence level. The results can be used in designs to improve the flow stability of the cone calorimeter.

• Nuclear Engineering and Technology
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• v.53 no.11
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• pp.3563-3579
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• 2021

Measured decay heat data of light water reactor (LWR) spent nuclear fuel (SNF) assemblies are adopted to train machine learning (ML) models. The measured data is available for fuel assemblies irradiated in commercial reactors operated in the United States and Sweden. The data comes from calorimetric measurements of discharged pressurized water reactor (PWR) and boiling water reactor (BWR) fuel assemblies. 91 and 171 measurements of PWR and BWR assembly decay heat data are used, respectively. Due to the small size of the measurement dataset, we propose: (i) to use the method of multiple runs (ii) to generate and use synthetic data, as large dataset which has similar statistical characteristics as the original dataset. Three ML models are developed based on Gaussian process (GP), support vector machines (SVM) and neural networks (NN), with four inputs including the fuel assembly averaged enrichment, assembly averaged burnup, initial heavy metal mass, and cooling time after discharge. The outcomes of this work are (i) development of ML models which predict LWR fuel assembly decay heat from the four inputs (ii) generation and application of synthetic data which improves the performance of the ML models (iii) uncertainty analysis of the ML models and their predictions.

• Nuclear Engineering and Technology
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• v.50 no.7
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• pp.1120-1130
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• 2018

An analysis of a pyroprocessing safeguards methodology employing the Pu-to-$^{244}Cm$ ratio is presented. The analysis includes characterization of representative used nuclear fuel assemblies with respect to computed nuclide composition. The nuclide composition data computationally generated is appropriately reformatted to correspond with the material conditions after each step in the head-end stage of pyroprocessing. Uncertainty in the Pu-to-$^{244}Cm$ ratio is evaluated using the Geary-Hinkley transformation method. This is because the Pu-to-$^{244}Cm$ ratio is a Cauchy distribution since it is the ratio of two normally distributed random variables. The calculated uncertainty of the Pu-to-$^{244}Cm$ ratio is propagated through the mass flow stream in the pyroprocessing steps. Finally, the probability of Type-I error for the plutonium Material Unaccounted For (MUF) is evaluated by the hypothesis testing method as a function of the sizes of powder particles and granules, which are dominant parameters to determine the sample size. The results show the probability of Type-I error is occasionally greater than 5%. However, increasing granule sample sizes could surmount the weakness of material accounting because of the non-uniformity of nuclide composition.

• International Journal of Aeronautical and Space Sciences
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• v.13 no.1
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• pp.43-57
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• 2012

In a modern aircraft, there are many variations in its mass, stiffness, and aerodynamic characteristics. Recently, an analytical approach was proposed, and this approach uses the idea of uncertainty to find out the most critical flight flutter boundary due to the variations in such aerodynamic characteristics. An analytical method that has been suggested to predict robust stability is the mu method. We previously analyzed the robust flutter boundary by using the mu method, and in that study, aerodynamic variations in the Mach number, atmospheric density, and flight speed were taken into consideration. The authors' previous attempt and the results are currently quoted as varying Mach number mu analysis. In the author's previous method, when the initial flight conditions were located far from the nominal flutter boundary, conservative predictions were obtained. However, relationships among those aerodynamic parameters were not applied. Thus, the varying Mach number mu analysis results required validation. Using an optimization approach, the varying Mach number mu analysis was found out to be capable of capturing a reasonable robust flutter boundary, i.e., with a low percentage difference from boundaries that were obtained by optimization. Regarding the optimization approach, a discrete nominal flutter boundary is to be obtained in advance, and based on that boundary, an interpolated function was established. Thus, the optimization approach required more computational effort for a larger number of uncertainty variables. And, this produced results similar to those from the mu method which had lower computational complexity. Thus, during the estimation of robust aeroelastic stability, the mu method was regarded as more efficient than the optimization method was. The mu method predicts reasonable results when an initial condition is located near the nominal flutter boundary, but it does not consider the relationships that are among the aerodynamic parameters, and its predictions are not very accurate when the initial condition is located far from the nominal flutter boundary. In order to provide predictions that are more accurate, the relationships among the uncertainties should also be included in the mu method.

• Mass Spectrometry Letters
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• v.3 no.2
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• pp.58-61
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• 2012

A method based on flow injection-isotope dilution-cold vapor-inductively coupled plasma mass spectrometry (FI-IDCV-ICP/MS) has been applied to determine trace level of mercury in fly ash. $^{200}Hg$ isotopic spike was added to 0.25 g of BCR176R fly ash and then decomposed by microwave digestion procedure with acid mixture A (8 mL $HNO_3$ + 2 mL HCl + 2 mL HF) and acid mixture B (8 mL $HNO_3$ + 2 mL $HClO_4$ + 2 mL HF) for applying IDMS. Mercury cold vapor was generated by using reductant solution of 0.2% (w/w) $NaBH_4$ and 0.05% (w/w) NaOH. The measurements of n($^{200}Hg$)/n($^{202}Hg$) isotope ratio was made using a quadrupole ICP/MS system. The accuracy in this method was verified by the analysis of certified reference material (CRM) of fly ash (BCR 176R). The indicative value of Hg in BCR 176R fly ash was $1.60{\pm}0.23$ mg/kg (k = 2). The determined values of Hg in BCR 176R fly ash by the method of FI-CV-ID-ICP/MS described in this paper were $1.60{\pm}0.24$ mg/kg (k = 3.18) and the analysis results were in well agreement with the indicative value within the range of uncertainty.

• Particle and aerosol research
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• v.9 no.3
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• pp.163-171
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• 2013

Soot particles emitted from combustion processes are often coated by non-absorbing organic materials, which enhance the global warming effect of soot particles. It is of importance to study the condensation characteristics of soot particles experimentally and theoretically to reduce the uncertainty of the climate impact of soot particles. In this study, the condensational growth of soot particles in a tubular coater was modeled by a one-dimensional (1D) plug flow model and a two-dimensional (2D) laminar flow model. The effects of 2D heat and mass transports on the predicted particle growth were investigated. The temperature and coating material vapor concentration distributions in radial direction, which the 1D model could not accounted for, affected substantially the particle growth in the coater. Under the simulated conditions, the differences between the temperatures and vapor concentrations near the wall and at the tube center were large. The neglect of these variations by the 1D model resulted in a large error in modeling the mass transfer and aerosol dynamics occurring in the coater. The 1D model predicted the average temperature and vapor concentration quite accurately but overestimated the average diameter of the growing particles considerably. At the outermost grid, at which condensation begins earliest due to the lowest temperature and saturation vapor concentration, condensing vapor was exhausted rapidly because of the competition between condensations on the wall and on the particle surface, decreasing the growth rate. At the center of the tube, on the other hand, the growth rate was low due to high temperature and saturation vapor concentration. The effects of Brownian diffusion and thermophoresis were not high enough to transport the coating material vapor quickly from the tube center to the wall. The 1D model based on perfect radial mixing could not take into account this phenomenon, resulting in a much higher growth rate than what the 2D model predicted. The result of this study indicates that contrary to a previous report for a thermodenuder, 2D heat and mass transports must be taken into account to model accurately the condensational particle growth in a coater.