• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.24 no.12
• /
• pp.1140-1147
• /
• 2013

In this paper, The path loss model of Air Traffic Control(ATC) telecommunication radio channel has been studied at the Incheon International Airport(IIA) Cargo Terminal. We measured one frequency among VHF channel bands. The transmitting site was located at different locations with different heights. The transmitting site radiated the Continuous Wave(CW). The propagation measurement was taken using the moving vehicle equipped with receiver and antenna. The transmitting power, frequency and antenna height are the same as the current operating condition. The path loss exponent and intercept parameters were extracted by the basic path loss model and hata model. The path loss exponent at IIA Cargo terminal area were 3.67 and 3.39 respectively in first and second transmitting sites. The deviation of prediction error is 14.42 and 10.38. The new path loss equation at the IIA Cargo terminal area was also developed using the derived path loss parameters. The new path loss was compared with other models. This result will be helpful for the ATC site selection and service quality evaluation.

• The Journal of the Acoustical Society of Korea
• /
• v.27 no.2E
• /
• pp.45-50
• /
• 2008

In recent years, quantitative ultrasound (QUS) technologies have played a growing role in the diagnosis of osteoporosis. Most of the commercial bone somometers measure speed of sound (SOS) and/or broadband ultrasonic attenuation (EUA) at peripheral skeletal sites. However, the QUS parameters are purely empirical measures that have not yet been firmly linked to physical parameters such as bone strength or porosity. In the present study, the theoretical models for wave propagation in cancellous bone, such as the Biot model, the stratified model, and the modified Biot-Attenborough (MBA) model, were applied to predict the dependence of phase velocity on porosity in cancellous bone. The optimum values for the input parameters of the three models in cancellous bone were determined by comparing the predictions with the previously published measurements in human cancellous bone in vitro. This modeling effort is relevant to the use of QUS in the diagnosis of osteoporosis because SOS is negatively correlated to the fracture risk of bone, and also advances our understanding of the relationship between phase velocity and porosity in cancellous bone.

• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
• /
• v.6 no.3
• /
• pp.24-35
• /
• 1995

In this paper, we study the Spectrum Use Measure(SUM) model for quantifying the extent of spectrum use by existing radio communication systems. This model calculates the interference level between transmitters and receivers by applying the EMC analysis technique of interference prediction process such as antenna radiation pattern model and propagation model which are well known. While several previous works have described the spectrum resources by constructing the interference contours around existing radio systems, the SUM technique is developed for quantifying and portraying the spectrum resources used by radio communication systems in a geographic area. Computer simula- tion results are illustrated to verify the calculations for the Spectrum Use Bandwidth(SUB) and Spectrum Use Factor (SUF) performed by the SUM model and find the usefulness of the SUM model.

• Journal of the Society of Naval Architects of Korea
• /
• v.61 no.1
• /
• pp.44-50
• /
• 2024

In order to reasonably predict damage extents of naval ships under in-compartment explosion (INCEX) loads, two conditions should be fulfilled in terms of accurate INCEX load generation and fracture estimation. This paper seeks to predict damage extents of various naval ships by applying the CONWEP model to generate INCEX loads, combined with the Hosford-Coulomb (HC) and localized necking (LN) fracture model. This study selected a naval ship with a 2,000-ton displacement, using associated specifications collected from references. The CONWEP model that is embedded in a commercial finite element analysis software ABAQUS/Explicit was used for INCEX load generation. The combined HC-LN model was used to simulate fracture initiation and propagation. The permanent failures with some structural fractures occurred where at the locations closest to the explosion source points in case of the near field explosions, while, some significant fractures were observed in way of the interfaces between bulkheads and curtain plates under far field explosion. A large thickness difference would lead to those interface failures. It is expected that the findings of this study enhances the vulnerability design of naval ships, enabling more accurate predictions of damage extents under INCEX loads.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.16 no.9 s.114
• /
• pp.949-957
• /
• 2006

In this Paper, reduction of noise and vibration in ship cabins by using floating floor is studied. Two theoretical models are presented and predicted insertion losses of floating floor are compared to experimental results, where measurements have been done in mock-up built for simulating typical ship cabin structures. In ships, mineral wool is usually used as the impact absorbing materials. The first model (M-S-Plate Model) is that upper plate and mineral wool are assumed as a one-dimensional mass-spring system, which is in turn attached to the simply supported elastic floor. The second model (Wave-Plate Model) is that mineral wool is assumed as an elastic medium for wave propagation. The comparisons show that M-S-Plate model is in good agreement with experimental results when density of mineral wool is 140K, and fiber direction is horizontal. For higher density and vertical fiber direction, Wave-Plate model shows good agreements with measurements. It is found that including the elastic behavior of the floor is essential in improving accuracy of the prediction for low frequency ranges below $100{sim}200Hz$.

• Computers and Concrete
• /
• v.28 no.6
• /
• pp.635-642
• /
• 2021

In this paper, soft learning techniques are used to predict the ultimate torsional capacity of Reinforced Concrete beams strengthened with Fiber Reinforced Polymer. Soft computing techniques, namely Artificial Neural Network, trained by various back propagation algorithms, and Particle Swarm Optimization (PSO) algorithm, have been used to model and predict the torsional strength of Reinforced Concrete beams strengthened with Fiber Reinforced Polymer. The performance of each model has been evaluated by using statistical parameters such as coefficient of determination (R²), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE). The hybrid PSO NN model resulted in an R² of 0.9292 with an RMSE of 5.35 for training and an R² of 0.9328 with an RMSE of 4.57 for testing. Another model, ANN BP, produced an R² of 0.9125 with an RMSE of 6.17 for training and an R² of 0.8951 with an RMSE of 5.79 for testing. The results of the PSO NN model were in close agreement with the experimental values. Thus, the PSO NN model can be used to predict the ultimate torsional capacity of RC beams strengthened with FRP with greater acceptable accuracy.

• Advances in concrete construction
• /
• v.10 no.6
• /
• pp.479-488
• /
• 2020

The experimental and numerical works were carried out on high performance fiber reinforced concrete (HPFRC) with w/cm ratios ranging from 0.25 to 0.40, fiber volume fraction (Vf)=0-1.5% and 10% silica fume replacement. Improvements in compressive and flexural strengths obtained for HPFRC are moderate and significant, respectively, Empirical equations developed for the compressive strength and flexural strength of HPFRC as a function of fiber volume fraction. A relation between flexural strength and compressive strength of HPFRC with R=0.78 was developed. Due to the complex mix proportions and non-linear relationship between the mix proportions and properties, models with reliable predictive capabilities are not developed and also research on HPFRC was empirical. In this paper due to the inadequacy of present method, a back propagation-neural network (BP-NN) was employed to estimate the 28-day compressive strength of HPFRC mixes. BP-NN model was built to implement the highly non-linear relationship between the mix proportions and their properties. This paper describes the data sets collected, training of ANNs and comparison of the experimental results obtained for various mixtures. On statistical analyses of collected data, a multiple linear regression (MLR) model with R2=0.78 was developed for the prediction of compressive strength of HPFRC mixes, and average absolute error (AAE) obtained is 6.5%. On validation of the data sets by NNs, the error range was within 2% of the actual values. ANN model has given the significant degree of accuracy and reliability compared to the MLR model. ANN approach can be effectively used to estimate the 28-day compressive strength of fibrous concrete mixes and is practical.

• Journal of the Korean Geotechnical Society
• /
• v.19 no.2
• /
• pp.267-278
• /
• 2003

Artificial neural networks are efficient computing techniques that are widely used to solve complex problems in many fields. In this study, in order to predict tunnel-induced ground movements, Tunnel Behavior Prediction System (TBPS) was developed by using these artificial neural networks model, based on a Held instrumentation database (i.e. crown settlement, convergence, axial force of rock bolt, compressive and shear stress of shotcrete, stress of concrete lining etc.) obtained from 193 location data of 31 different tunnel sites where works are completed. The study and test of the network were performed by Back Propagation Algorithm which is known as a systematic technique for studying the multi-layer artificial neural network. The tunnel behaviors predicted by TBPS were compared with monitored data in the tunnel sites and numerical analysis results. This study showed that the values obtained from TBPS were within allowable limits. It is concluded that this system can effectively estimate the tunnel ground movements and can also be used f3r tunneling feasibility study, and basic and detailed design and construction of tunnel.

• Structural Engineering and Mechanics
• /
• v.70 no.6
• /
• pp.671-681
• /
• 2019

This paper examines the applicability of artificial neural network (ANN) and multivariate adaptive regression splines (MARS) to predict the compressive strength of bacteria incorporated geopolymer concrete (GPC). The mix is composed of new bacterial strain, manufactured sand, ground granulated blast furnace slag, silica fume, metakaolin and fly ash. The concentration of sodium hydroxide (NaOH) is maintained at 8 Molar, sodium silicate ($Na_2SiO_3$) to NaOH weight ratio is 2.33 and the alkaline liquid to binder ratio of 0.35 and ambient curing temperature ($28^{\circ}C$) is maintained for all the mixtures. In ANN, back-propagation training technique was employed for updating the weights of each layer based on the error in the network output. Levenberg-Marquardt algorithm was used for feed-forward back-propagation. MARS model was developed by establishing a relationship between a set of predictors and dependent variables. MARS is based on a divide and conquers strategy partitioning the training data sets into separate regions; each gets its own regression line. Six models based on ANN and MARS were developed to predict the compressive strength of bacteria incorporated GPC for 1, 3, 7, 28, 56 and 90 days. About 70% of the total 84 data sets obtained from experiments were used for development of the models and remaining 30% data was utilized for testing. From the study, it is observed that the predicted values from the models are found to be in good agreement with the corresponding experimental values and the developed models are robust and reliable.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.11 no.4
• /
• pp.25-31
• /
• 2007

For areas such as the Korean Peninsula, which have moderate seismic activity but no available records of strong ground motion, synthetic seismograms can be used to evaluate ground motion without waiting for a strong earthquake. Such seismograms represent the estimated ground motions expected from a set of possible earthquake scenarios. Local site effects are especially important in assessing the seismic hazard and possible ground motion scenarios for a specific fault. The earthquake source and rupture dynamics can be described as a two-step process of rupture initiation and front propagation controlled by a frictional sliding mechanism. The seismic wavefield propagates through heterogeneous geological media and finally undergoes near-surface modulations such as amplification or deamplification. This is a complex system in which various scales of physical phenomena are integrated. A unified approach incorporates multi-scale problems of dynamic rupture, radiated wave propagation, and site effects into an all-in-one model using a three-dimensional, fourth-order, staggered-grid, finite-difference method. The method explains strong ground motions as products of complex systems that can be modified according to a variety of fine-scale rupture scenarios and friction models. A series of such deterministic earthquake scenarios can shed light on the kind of damage that would result and where it would be located.