• Structural Engineering and Mechanics
• /
• v.56 no.6
• /
• pp.959-982
• /
• 2015

In this study, a non-stationary random earthquake Clough-Penzien model is used to describe earthquake ground motion. Using stochastic direct integration in combination with an equivalent linear method, a solution is established to describe the non-stationary response of lead-rubber bearing (LRB) system to a stochastic earthquake. Two parameters are used to develop an optimization method for bearing design: the post-yielding stiffness and the normalized yield strength of the isolation bearing. Using the minimization of the maximum energy response level of the upper structure subjected to an earthquake as an objective function, and with the constraints that the bearing failure probability is no more than 5% and the second shape factor of the bearing is less than 5, a calculation method for the two optimal design parameters is presented. In this optimization process, the radial basis function (RBF) response surface was applied, instead of the implicit objective function and constraints, and a sequential quadratic programming (SQP) algorithm was used to solve the optimization problems. By considering the uncertainties of the structural parameters and seismic ground motion input parameters for the optimization of the bearing design, convex set models (such as the interval model and ellipsoidal model) are used to describe the uncertainty parameters. Subsequently, the optimal bearing design parameters were expanded at their median values into first-order Taylor series expansions, and then, the Lagrange multipliers method was used to determine the upper and lower boundaries of the parameters. Moreover, using a calculation example, the impacts of site soil parameters, such as input peak ground acceleration, bearing diameter and rubber shore hardness on the optimization parameters, are investigated.

• Proceedings of the Korean Nuclear Society Conference
• /
• 2001.05a
• /
• pp.68.1-68
• /
• 2001

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2013.05a
• /
• pp.799-800
• /
• 2013

• Proceedings of the Korean Nuclear Society Conference
• /
• 2001.05a
• /
• pp.58-58
• /
• 2001

• 제어로봇시스템학회:학술대회논문집
• /
• 1987.10b
• /
• pp.63-68
• /
• 1987

In this study, a pantograph leg of the four legged walking vehicle is analysed with regard to mechanical energy consumption. Energy efficiency of the vehicle is estimated in terms of specific resistance varying body height, stride length and walking speed. The interaction between specific resistance and the parameters is investigated.

• Proceedings of the Korean Nuclear Society Conference
• /
• 2005.10a
• /
• pp.995-996
• /
• 2005

• 한국신재생에너지학회:학술대회논문집
• /
• 2009.06a
• /
• pp.373-373
• /
• 2009

Relative humidity, membrane conductivity and water activity are critical parameters of polymer electrolyte membrane fuel cells (PEMFC) for high performance and reliability. These parameters are closely related with temperature. Moreover, the ideal values of these parameters are not always identical along the channels. Therefore, the cooling channel design and its operating condition should be well optimized along the all location of the channels. In the present study, we have performed a numerical investigation on the effects of cooling channels on performance of a PEMFC. Three-dimensional Navier-Stokes equations are solved with the energy equation including heat generated by the electrochemical reactions in the fuel cell. The present numerical model includes the gas diffusion layers (GDL) and serpentine channels for both anode and cathode gas flows, as well as cooling channels. To accurately predict the water transport across the membrane, the distribution of water content in the membrane is calculated by solving a nonlinear differential equation with a nonlinear coefficient, i.e., the water diffusivity which is a function of water content as well as temperature. Main emphasis is placed on the heat transfer between the solid bipolar plate and coolant flow. The present results show that local current density is affected by cooling channels due to the change of the oxygen concentration and the membrane conductivity as well as the water content. It is also found that the relative humidity is influenced by the generated water and the gas temperature and thus it affects the distribution of fuel concentration and the conductivity of the membrane, ultimately fuel cell performance. Unit-cell experiments are also carried out to validate the numerical models. The performance curves between the models and experiments show reasonable results.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.12
• /
• pp.5904-5927
• /
• 2019

Many artificial intelligence (AI) techniques have been embedded into various engineering technologies to assist them in achieving different goals. The integration of modern technologies with energy consumption management system and occupant's comfort inside buildings results in the introduction of intelligent building concept. The major aim of this integration is to manage the energy consumption effectively and keeping the occupant satisfied with the internal environment of the building. The last few couple of years have seen many applications of AI techniques for optimizing the energy consumption with maximizing the user comfort in smart buildings but still there is much room for improvement in this area. In this paper, a hybrid of two AI algorithms called firefly algorithm (FA) and genetic algorithm (GA) has been used for user comfort maximization with minimum energy consumption inside smart building. A complete user friendly system with data from various sensors, user, processes, power control system and different actuators is developed in this work for reducing power consumption and increase the user comfort. The inputs of optimization algorithms are illumination, temperature and air quality sensors' data and the user set parameters whereas the outputs of the optimization algorithms are optimized parameters. These optimized parameters are the inputs of different fuzzy controllers which change the status of different actuators according to user satisfaction.

• Journal of Radiation Protection and Research
• /
• v.45 no.4
• /
• pp.171-177
• /
• 2020

Background: This study aims to determine the effective atomic number (Zeff) from dual-energy image sets obtained using a conventional computed tomography (CT) simulator. The estimated Zeff can be used for deriving the stopping power and material decomposition of CT images, thereby improving dose calculations in radiation therapy. Materials and Methods: An electron-density phantom was scanned using Philips Brilliance CT Big Bore at 80 and 140 kVp. The estimated Zeff values were compared with those obtained using the calibration phantom by applying the Rutherford, Schneider, and Joshi methods. The fitting parameters were optimized using the nonlinear least squares regression algorithm. The fitting curve and mass attenuation data were obtained from the National Institute of Standards and Technology. The fitting parameters obtained from stopping power and material decomposition of CT images, were validated by estimating the residual errors between the reference and calculated Zeff values. Next, the calculation accuracy of Zeff was evaluated by comparing the calculated values with the reference Zeff values of insert plugs. The exposure levels of patients under additional CT scanning at 80, 120, and 140 kVp were evaluated by measuring the weighted CT dose index (CTDIw). Results and Discussion: The residual errors of the fitting parameters were lower than 2%. The best and worst Zeff values were obtained using the Schneider and Joshi methods, respectively. The maximum differences between the reference and calculated values were 11.3% (for lung during inhalation), 4.7% (for adipose tissue), and 9.8% (for lung during inhalation) when applying the Rutherford, Schneider, and Joshi methods, respectively. Under dual-energy scanning (80 and 140 kVp), the patient exposure level was approximately twice that in general single-energy scanning (120 kVp). Conclusion: Zeff was calculated from two image sets scanned by conventional single-energy CT simulator. The results obtained using three different methods were compared. The Zeff calculation based on single-energy exhibited appropriate feasibility.

• Wind and Structures
• /
• v.37 no.6
• /
• pp.445-460
• /
• 2023

Accurate estimation of modal parameters (i.e., natural frequency, damping ratio) of tall buildings is of great importance to their structural design, structural health monitoring, vibration control, and state assessment. Based on the combination of variational mode decomposition, smoothed discrete energy separation algorithm-1, and Half-cycle energy operator (VMD-SH), this paper presents a method for structural modal parameter estimation. The variational mode decomposition is proved to be effective and reliable for decomposing the mixed-signal with low frequencies and damping ratios, and the validity of both smoothed discrete energy separation algorithm-1 and Half-cycle energy operator in the modal identification of a single modal system is verified. By incorporating these techniques, the VMD-SH method is able to accurately identify and extract the various modes present in a signal, providing improved insights into its underlying structure and behavior. Subsequently, a numerical study of a four-story frame structure is conducted using the Newmark-β method, and it is found that the relative errors of natural frequency and damping ratio estimated by the presented method are much smaller than those by traditional methods, validating the effectiveness and accuracy of the combined method for the modal identification of the multi-modal system. Furthermore, the presented method is employed to estimate modal parameters of a full-scale tall building utilizing acceleration responses. The identified results verify the applicability and accuracy of the presented VMD-SH method in field measurements. The study demonstrates the effectiveness and robustness of the proposed VMD-SH method in accurately estimating modal parameters of tall buildings from acceleration response data.