• Journal of Korean Society for Atmospheric Environment
• /
• v.3 no.1
• /
• pp.34-40
• /
• 1987

The Texas Climatological Model (TCM) Predicts long-term pollutant concentrations for a rectilinear array or receptors defined by the user. This paper describes the TCM and compares predictions from TCM with predictions from the Climatological Dispersion Model (CDMQC). A number of model runs have been made with the TCM and CDMQC using the same source inventories and sets of climatology. The concentrations predicted by these two models are compared and the result of several types of statistical analyses are reported. In most cases, the TCM predicts concentrations that are equivalent to those predicted by the CDMQC. However, in certain cases, the CDMQC tends to predict concentrations that are unrealistically high. In the computer time, the TCM requires about one-eights of the computer time used by the CDMQC.

• Computers and Concrete
• /
• v.16 no.1
• /
• pp.67-97
• /
• 2015

This article presents a computing procedure developed to predict the torsional strength of axially restrained reinforced concrete beams. This computing procedure is based on a modification of the Variable Angle Truss Model to account for the influence of the longitudinal compressive stress state due to the axial restraint conditions provided by the connections of the beams to other structural elements. Theoretical predictions from the proposed model are compared with some experimental results available in the literature and also with some numerical results from a three-dimensional nonlinear finite element analysis. It is shown that the proposed computing procedure gives reliable predictions for the ultimate behaviour, namely the torsional strength, of axially restrained reinforced concrete beams under torsion.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2008.04a
• /
• pp.355-358
• /
• 2008

This study deals with a substantial problems with SEA modeling methods in shipboard noise predictions. As a first problems with respect to modeling, fineness of model that represents a real structure is numerically investigated by comparison among 3 models, Fine, Coarse and Simplified models. Comparison reveals that Fine model shows the lowest noise level among them since this model involve more energy transfer paths than the other models. Influence of in-plane wave is also examined by numerical comparison. It is clear that inclusion of in-plane wave affects the high frequency and the cabin far from a source.

• Computers and Concrete
• /
• v.26 no.5
• /
• pp.397-409
• /
• 2020

The current study targets to estimate the contribution of the end-anchored FRP composites in resisting shear force using a soft computing tool i.e., adaptive neuro-fuzzy inference system (ANFIS). A total of 107 sets of data accumulated from literature was utilized for the development and evaluation of the current ANFIS model. A comparative analysis between the ANFIS predictions and the acquired experimental results has shown that the ANFIS predictions are in very good agreement with that of experimental ones. Additionally, the accuracy of the current ANFIS model has been weighed up against the estimates of nine widely adopted design guidelines. Based on various statistical parameters, it has been deduced that the effectiveness of the current ANFIS model is better than the considered design guidelines. Besides this, a parametric study was carried out to explore the combined effect of different parameters as well as the impact of individual parameters.

• Journal of ILASS-Korea
• /
• v.3 no.4
• /
• pp.65-76
• /
• 1998

An experimental and numerical study of a spray flow is performed to investigate the spray characteristics using an air-assisted atomizer. A Partical Dynamic Analyzer(PDA) is used to measure SMD, dmp velocity, and drop number density whose the initial conditions have considerable effect on the numerical results. The measured experimental data have been used to asses the accuracy of model predictions. Numerical investigation is made with the Eulerian - Lagrangian formulism. Turbulent dispersion effects using a Monte-Carlo method, turbulent modulation effect and entrainment of air are also numerically simulated. Results show that the numerical predictions of SSF(Stochastic Separated Flow) analysis yielded reasonable agreement with the experimental data. However, the model calculations for small drops produced the inconsistent numerical results due to the effect of surrounding air entrainment.

• Proceedings of the Korean Powder Metallurgy Institute Conference
• /
• 2006.09b
• /
• pp.704-705
• /
• 2006

Discrete element analysis is used to map various log-normal particle size distributions into measures of the in-sphere pore size distribution. Combinations evaluated range from monosized spheres to include bimodal mixtures and various log-normal distributions. The latter proves most useful in providing a mapping of one distribution into the other (knowing the particle size distribution we want to predict the pore size distribution). Such metrics show predictions where the presence of large pores is anticipated that need to be avoided to ensure high sintered properties.

• Computers and Concrete
• /
• v.30 no.5
• /
• pp.301-310
• /
• 2022

Cement-based sensors have been widely used as structural health monitoring systems, however, their long-term sensing performance have not actively investigated. In this study, a deep learning-based methodology is adopted to predict the long-term piezoresistive properties of cement-based sensors. Samples with different multi-walled carbon nanotube contents (0.1, 0.3, and 0.5 wt.%) are fabricated, and piezoresistive tests are conducted over 10,000 loading cycles to obtain the training data. Time-dependent degradation is predicted using a modified long short-term memory (LSTM) model. The effects of different model variables including the amount of training data, number of epochs, and dropout ratio on the accuracy of predictions are analyzed. Finally, the effectiveness of the proposed approach is evaluated by comparing the predictions for long-term piezoresistive sensing performance with untrained experimental data. A sensitivity of 6% is experimentally examined in the sample containing 0.1 wt.% of MWCNTs, and predictions with accuracy up to 98% are found using the proposed LSTM model. Based on the experimental results, the proposed model is expected to be applied in the structural health monitoring systems to predict their long-term piezoresistice sensing performances during their service life.

• Nuclear Engineering and Technology
• /
• v.56 no.6
• /
• pp.2343-2351
• /
• 2024

Accurately predicting the thermal hydraulic parameters of a transient reactor core under different working conditions is the first step toward reactor safety. Mass flow rate and temperature are important parameters of core thermal hydraulics, which have often been modeled as time series prediction problems. This study aims to achieve accurate and continuous prediction of core thermal hydraulic parameters under instantaneous conditions, as well as test the feasibility of a newly constructed gated recurrent unit (GRU) model based on the soft attention mechanism for core parameter predictions. Herein, the China Experimental Fast Reactor (CEFR) is used as the research object, and CEFR 1/2 core was taken as subject to carry out continuous predictive analysis of thermal parameters under transient conditions., while the subchannel analysis code named SUBCHANFLOW is used to generate the time series of core thermal-hydraulic parameters. The GRU model is used to predict the mass flow and temperature time series of the core. The results show that compared to the adaptive radial basis function neural network, the GRU network model produces better prediction results. The average relative error for temperature is less than 0.5 % when the step size is 3, and the prediction effect is better within 15 s. The average relative error of mass flow rate is less than 5 % when the step size is 10, and the prediction effect is better in the subsequent 12 s. The GRU model not only shows a higher prediction accuracy, but also captures the trends of the dynamic time series, which is useful for maintaining reactor safety and preventing nuclear power plant accidents. Furthermore, it can provide long-term continuous predictions under transient reactor conditions, which is useful for engineering applications and improving reactor safety.

• Proceedings of the Korean Nuclear Society Conference
• /
• 1996.05b
• /
• pp.284-289
• /
• 1996

The predictions of the COBRA-IV-I code with the modified turbulent mixing and void drift models have been compared with the diabatic two-phase flow data on equilibrium quality. The turbulent mixing model based on an equal mass exchange of the existing COBRA-IV-I code has been modified to that based on an equal volume exchange between adjacent subchannels, and a void drift model has been newly incorporated in the code. To evaluate the performance of the equal volume exchange turbulent mixing model and the effects of the void drift model, the diabatic steam-water two-phase flow data obtained for the 9-rod bundle test under the typical operating conditions of the boiling water reactor(BWR) conducted by the General Electric (GE) were analyzed by the modified COBRA-IV-I code. The analysis indicates that the equal volume exchange turbulent mixing model with void drift predicts the observed two-phase flow data trends better than the equal mass exchange model, and to predict the correct data trends a more physically based void drift model need to be developed.

• Journal of Korean Society for Atmospheric Environment
• /
• v.14 no.3
• /
• pp.219-228
• /
• 1998

In the present investigation, a numerical model developed for the prediction of the wind flow over complex terrain is validated by comparing with the field experiments. For the solution of the Reynolds - Averaged Clavier- stokes equations which are the governing equations of the microscale atmospheric flow, the model is constructed based on the finite-volume formulation and the SIMPLEC pressure-correction algorithm for the hydrodynamic computation. The boundary- fitted coordinate system is employed for the detailed depiction of topography. The boundary conditions and the modified turbulence constants suitable for an atmospheric boundary- layer are applied together with the k- s turbulence model. The full- scale experiments of Cooper's Ridge, Kettles Hill and Askervein Hill are chosen as the validation cases . Comparisons of the mean flow field between the field measurements and the predicted results show good agreement. In the simulation of the wind flow over Askervein Hill , the numerical model predicts the three dimensional flow separation in the downslope of the hill including the blockage effect due to neighboring hills . Such a flow behavior has not been simulated by the theoretical predictions. Therefore, the present model may offer the most accurate prediction of flow behavior in the leeside of the hill among the existing theoretical and numerical predictions.