• Journal of Environmental Science International
• /
• v.19 no.8
• /
• pp.971-981
• /
• 2010

The objectives of this study were to measure ambient total gaseous mercury (TGM) concentrations in Seoul, to analyze the characteristics of TGM concentration, and to identify of possible source areas for TGM using back-trajectory based hybrid receptor models like PSCF (Potential Source Contribution Function) and RTWC (Residence Time Weighted Concentration). Ambient TGM concentrations were measured at the roof of Graduate School of Public Health building in Seoul for a period of January to October 2004. Average TGM concentration was $3.43{\pm}1.17\;ng/m^3$. TGM had no notable pattern according to season and meteorological phenomena such as rainfall, Asian dust, relative humidity and so on. Hybrid receptor models incorporating backward trajectories including potential source contribution function (PSCF) and residence time weighted concentration (RTWC) were performed to identify source areas of TGM. Before hybrid receptor models were applied for TGM, we analysed sensitivities of starting height for HYSPLIT model and critical value for PSCF. According to result of sensitivity analysis, trajectories were calculated an arrival height of 1000 m was used at the receptor location and PSCF was applied using average concentration as criterion value for TGM. Using PSCF and RTWC, central and eastern Chinese industrial areas and the west coast of Korea were determined as important source areas. Statistical analysis between TGM and GEIA grided emission bolsters the evidence that these models could be effective tools to identify possible source area and source contribution.

• Journal of Radiation Protection and Research
• /
• v.29 no.4
• /
• pp.269-273
• /
• 2004

The hybrid dead time model adopting paralyzable (or extendable) and non-paralyzable (or non-extendable) dead times has been introduced to extend the usable range of G-M counters in high counting rate environment and the relationship between true and observed counting rates is more accurately expressed in the hybrid model. GMSIM, dead time effects simulator, has been developed to analyze the counting statistics of G-M counters using Monte Carlo simulations. GMSIM accurately described the counting statistics of the paralyzable and non-paralyzable models. For G-M counters that follow the hybrid model, the counting statistics behaved in between two idealized models. In the future, GMSIM may be used in predicting counting statistics of three G-M dead time models, which are paralyzable, non-paralyzable and hybrid models.

• Structural Monitoring and Maintenance
• /
• v.1 no.4
• /
• pp.427-449
• /
• 2014

A hybrid optimization method for the identification of state-space models is presented in this study. Hybridization is succeeded by combining the advantages of deterministic and stochastic algorithms in a superior scheme that promises faster convergence rate and reliability in the search for the global optimum. The proposed hybrid algorithm is developed by replacing the original stochastic mutation operator of Evolution Strategies (ES) by the Levenberg-Marquardt (LM) quasi-Newton algorithm. This substitution results in a scheme where the entire population cloud is involved in the search for the global optimum, while single individuals are involved in the local search, undertaken by the LM method. The novel hybrid identification framework is assessed through the Monte Carlo analysis of a simulated system and an experimental case study on a shear frame structure. Comparisons to subspace identification, as well as to conventional, self-adaptive ES provide significant indication of superior performance.

• Steel and Composite Structures
• /
• v.48 no.4
• /
• pp.367-383
• /
• 2023

A coupled wall consists of two or more reinforced concrete (RC) shear walls (SWs) connected by RC coupling beams (CBs) or steel CBs (hybrid-coupled walls). To fill the gap in the literature on the plastic hinge length of coupled walls, including coupled and hybrid-coupled shear walls, a parametric study using experimentally validated numerical models was conducted considering the axial stress ratio (ASR) and coupling ratio (CR) as the study variables. A total of sixty numerical models, including both coupled and hybrid-coupled SWs, have been developed by varying the ASR and CR within the ranges of 0.027-0.25 and 0.2-0.5, respectively. A detailed analysis was conducted in order to estimate the ultimate drift, ultimate capacity, curvature profile, yielding height, and plastic hinge length of the models. Compared to hybrid-coupled SWs, coupled SWs possess a relatively higher capacity and curvature. Moreover, increasing the ASR changes the walls' behavior to a column-like member which decreases the walls' ultimate drift, ductility, curvature, and plastic hinge length. Increasing the CR of the coupled SWs increases the walls' capacity and the risk of abrupt shear failure but decreases the walls' ductility, ultimate drift and plastic hinge length. However, CR has a negligible effect on hybrid-coupled walls' ultimate drift and moment, curvature profile, yielding height and plastic hinge length. Lastly, using the obtained results two equations were derived as a function of CR and ASR for calculating the plastic hinge length of coupled and hybrid-coupled SWs.

• Journal of ILASS-Korea
• /
• v.5 no.2
• /
• pp.35-42
• /
• 2000

A number of atomization and droplet breakup models have been developed and used to predict the diesel spray characteristics. Of the many atomization and droplet breakup models based on the breakup mechanism due to aerodynamic liquid and gas interaction, four models classified as mathematical models, such as TAB, modified TAB, DDB, WB and one of the hybrid model based on WB and TAB models were selected for the assessment of prediction ability of diesel spray dynamics. The assessment of these models by using KIVA-II code was performed by comparing with the experimental data of spray tip penetration and sauter mean diameter(SMD) from the literature. It is found that the prediction of spray tip penetration and SMD by the hybrid model was only influenced by the initial parcel number. All the atomization and droplet breakup models considered here was strongly dependent on the grid resolution. Therefore it is important to check the grid resolution to get an acceptable results in selecting the models. At low injection pressure, modified TAB model could only give the good agreement with experimental data of spray tip penetration and both of modified TAB and DDB models were recommendable for the prediction of SMD. At high injection pressure, hybrid model could only give the good agreement with the experimental data of spray tip penetration and the prediction of all of the selected models did not match the experimental data. Spray tip penetration was increased with the increase the $B_1$ and the increase of $B_1$ did not affected the prediction of SMD.

• Computers and Concrete
• /
• v.21 no.1
• /
• pp.103-110
• /
• 2018

This study introduces the supervised committee fuzzy model as a hybrid fuzzy model to predict compressive strength (CS) of geopolymers prepared from alumina-silica products. For this purpose, more than 50 experimental data that evaluated the effect of $Al_2O_3/SiO_2$, $Na_2O/Al_2O_3$, $Na_2O/H_2O$ and Na/[Na+K] on (CS) of geopolymers were collected from the literature. Then, three different Fuzzy Logic (FL) models (Sugeno fuzzy logic (SFL), Mamdani fuzzy logic (MFL), and Larsen fuzzy logic (LFL)) were adopted to overcome the inherent uncertainty of geochemical parameters and to predict CS. After validating the model, it was found that the SFL model is superior to MFL and LFL models, but each of the FL models has advantages to predict CS. Therefore, to achieve the optimal performance, the supervised committee fuzzy logic (SCFL) model was developed as a hybrid method to combine the benefits of individual FL models. The SCFL employs an artificial neural network (ANN) model to re-predict the CS of three FL model predictions. The results also show significant fitting improvement in comparison with individual FL models.

• International Journal of Automotive Technology
• /
• v.7 no.4
• /
• pp.459-468
• /
• 2006

The objective of this paper is the development of the forward-looking dynamic simulation model of a hybrid electric vehicle(HEV) for a fuel economy study. The specification of the vehicle is determined based on two factors, engine peak power to curb weight ratio and specific engine power. The steady state efficiency models of the powertrain components are explained in detail. These include a spark ignition direct injection(SIDI) engine, an integrated starter alternator(ISA), and an infinitely variable transmission(IVT). The paper describes the integration of these models into a forward facing dynamic simulation diagram using the AMESim environment. Appropriate vehicle and driver models have been added and described. The controller was designed in Simulink and was combined with the physical powertrain model by the co-simulation interface. Finally, the simulation results of the HEV are compared with those of a baseline vehicle in order to demonstrate the fuel economy potential. Results for the vehicle speed error and the fuel economy over standard driving cycles are illustrated.

• Journal of Welding and Joining
• /
• v.26 no.6
• /
• pp.67-73
• /
• 2008

Three-dimensional transient simulation of laser-GMA hybrid welding involving multiple physical phenomena is conducted neglecting the interaction effect of laser and arc heat sources. To reproduce the bubble and pore formations in welding process, a new bubble model is suggested and added to the established laser and arc welding models comprehending VOF, Gaussian laser and arc heat source, recoil pressure, arc pressure, electromagnetic force, surface tension, multiple reflection and Fresnel reflection models. Based on the models mentioned above, simulations of laser-GMA hybrid butt welding are carried out and besides the molten pool flow, top and back bead formations could be observed. In addition, the laser induced keyhole formation and bubble generation duo to keyhole collapse are investigated. The bubbles are ejected from the molten pool through its top and bottom regions. However, some of those are entrapped by solid-liquid interface and remained as pores. Those bubbles and pores are intensively generated when the absorption of laser power is largely reduced and consequently the full penetration changes to the partial penetration.

• International Journal of Control, Automation, and Systems
• /
• v.1 no.3
• /
• pp.289-300
• /
• 2003

In this paper, we introduce an identification method in Fuzzy Relation-based Fuzzy Neural Networks (FRFNN) through a hybrid identification algorithm. The proposed FRFNN modeling implement system structure and parameter identification in the efficient form of "If...., then... " statements, and exploit the theory of system optimization and fuzzy rules. The FRFNN modeling and identification environment realizes parameter identification through a synergistic usage of genetic optimization and complex search method. The hybrid identification algorithm is carried out by combining both genetic optimization and the improved complex method in order to guarantee both global optimization and local convergence. An aggregate objective function with a weighting factor is introduced to achieve a sound balance between approximation and generalization of the model. The proposed model is experimented with using two nonlinear data. The obtained experimental results reveal that the proposed networks exhibit high accuracy and generalization capabilities in comparison to other models.er models.

• Journal of Electrical Engineering and Technology
• /
• v.11 no.6
• /
• pp.1684-1692
• /
• 2016

In order to adapt the fast dynamic performances of Buck DC/DC converter, and reduce the influence on converter performance owing to uncertain factors such as the disturbances of parameters and load, a control strategy based on two-dimensional hybrid cloud model is proposed. Firstly, two cloud models corresponding to the specific control inputs are determined by maximum determination approach, respectively, and then a control rule decided by the two cloud models is selected by a rule selector, finally, according to the reasoning structure of the rule, the control increment is calculated out by a two-dimensional hybrid cloud decision module. Both the simulation and experiment results show that the strategy can dramatically improve the dynamic performances of the converter, and enhance the adaptive ability to resist the random disturbances, and its control effect is superior to that of the current-mode control.