• Computers and Concrete
• /
• v.32 no.4
• /
• pp.373-381
• /
• 2023

Fly ash, granulated blast furnace slag, marble waste powder, etc. are just some of the by-products of other sectors that the construction industry is looking to include into the many types of concrete they produce. This research seeks to use surrogate machine learning methods to forecast the compressive strength of self-compacting concrete. The surrogate models were developed using Gradient Boosting Machine (GBM), Support Vector Machine (SVM), Random Forest (RF), and Gaussian Process Regression (GPR) techniques. Compressive strength is used as the output variable, with nano silica content, cement content, coarse aggregate content, fine aggregate content, superplasticizer, curing duration, and water-binder ratio as input variables. Of the four models, GBM had the highest accuracy in determining the compressive strength of SCC. The concrete's compressive strength is worst predicted by GPR. Compressive strength of SCC with nano silica is found to be most affected by curing time and least by fine aggregate.

• Computers and Concrete
• /
• v.27 no.4
• /
• pp.319-332
• /
• 2021

The performance of gene expression programming (GEP) in predicting the compressive strength of bacteria-incorporated geopolymer concrete (GPC) was examined in this study. Ground-granulated blast-furnace slag (GGBS), new bacterial strains, fly ash (FA), silica fume (SF), metakaolin (MK), and manufactured sand were used as ingredients in the concrete mixture. For the geopolymer preparation, an 8 M sodium hydroxide (NaOH) solution was used, and the ambient curing temperature (28℃) was maintained for all mixtures. The ratio of sodium silicate (Na2SiO3) to NaOH was 2.33, and the ratio of alkaline liquid to binder was 0.35. Based on experimental data collected from the literature, an evolutionary-based algorithm (GEP) was proposed to develop new predictive models for estimating the compressive strength of GPC containing bacteria. Data were classified into training and testing sets to obtain a closed-form solution using GEP. Independent variables for the model were the constituent materials of GPC, such as FA, MK, SF, and Bacillus bacteria. A total of six GEP formulations were developed for predicting the compressive strength of bacteria-incorporated GPC obtained at 1, 3, 7, 28, 56, and 90 days of curing. 80% and 20% of the data were used for training and testing the models, respectively. R2 values in the range of 0.9747 and 0.9950 (including train and test dataset) were obtained for the concrete samples, which showed that GEP can be used to predict the compressive strength of GPC containing bacteria with minimal error. Moreover, the GEP models were in good agreement with the experimental datasets and were robust and reliable. The models developed could serve as a tool for concrete constructors using geopolymers within the framework of this research.

• Journal of Environmental Health Sciences
• /
• v.22 no.1
• /
• pp.99-106
• /
• 1996

The purpose of this study is to observe a specific removal efficiency of synthethetic wastewater which is managed by upflow submerged type at porous media which was sinteringed on a comparative low temperature 600$\circ$C, was annexed slag and humus soil with main material kaolinite. Observing removal efficiency quality of each media, a mixed media of kaolinite and humus soil by gravity percent 60, 40% respectively showed the most excellent removal utility, and applied predictive models for suspended culture kinetics without consideration diffusion limitation, and when analyzed kinetic which had been processed by this study the removal efficiency accompanied by carbon, nitrogen, phosphorous volumetric loading rate variation standed for a comparative large change rate 61~71%, it means the selection of the most proper load factor had a great effect on the highly removal efficiency, yield coefficient(Y) and specific microbial attach equation showed 1.53 mgVSS/mgCOD, $m_p=10039.4\times ((S_0)/(6.75+S_0))$ repectively.

• Proceedings of the Korea Concrete Institute Conference
• /
• 2010.05a
• /
• pp.469-470
• /
• 2010

The high-strength concrete(HSC) compared to normal concrete represents higher autogenous shrinkage due to lower water-to-binder ratio(W/B) and supplementaries, fly ash(FA) and granulated blast-furnace slag(BFS), etc. The potential of early age cracking which reduces durability of concrete structures is normally influenced by autogenous shrinkage and degree of restraint. Therefore, this paper studies on the evaluation of the characteristics of autogenous shrinkage for HSC, ultra-high-strength concrete(UHSC) containing admixtures by experimental test and the test results are compared with existed prediction models.

• Journal of Astronomy and Space Sciences
• /
• v.20 no.3
• /
• pp.205-216
• /
• 2003

The attitude motion of a spin-stabilized, upper-stage spacecraft is investigated based on a two-body model, consisting of a symmetric body, representing the spacecraft, and a spherical pendulum, representing the liquid slag pool entrapped in the aft section of the rocket motor. Exact time-varying nonlinear equations are derived and used to eliminate the drawbacks of conventional linear models. To study the stability of the spacecraft's attitude motion, both the spacecraft and pendulum are assumed to be in states of steady spin about the symmetry axis of the spacecraft and the coupled time-varying nonlinear equation of the pendulum is simplified. A quasi-stationary solution to that equation and approximate resonance conditions are determined in terms of the system parameters. The analysis shows that the pendulum is subject to a combination of parametric and external-type excitation by the main body and that energy from the excited pendulum is fed into the main body to develop the coning instability. In this paper, numerical examples are presented to explain the mechanism of the coning angle growth and how angular momenta and disturbance moments are generated.

• 한국신재생에너지학회:학술대회논문집
• /
• 2010.11a
• /
• pp.131.1-131.1
• /
• 2010

This study was conducted for engineering optimization for the gasification process which is the key factor for success of Taean IGCC gasification plant which has been driven forward under the government support in order to expand to supply new and renewable energy and diminish the burden of the responsibility for the reduction of the green house gas emission. The gasification process consists of coal milling and drying, pressurization and feeding, gasification, quenching and HP syngas cooling, slag removal system, dry flyash removal system, wet scrubbing system, and primary water treatment system. The configuration optimization is essential for the high efficiency and the cost saving. For this purpose, it was designed to have syngas cooler to recover the sensible heat as much as possible from the hot syngas produced from the gasifier which is the dry-feeding and entrained bed slagging type and also applied with the oxygen combustion and the first stage cylindrical upward gas flow. The pressure condition inside of the gasifier is around 40~45Mpg and the temperature condition is up to $1500{\sim}1700^{\circ}C$. It was designed for about 70% out of fly ash to be drained out throughout the quenching water in the bottom part of the gasifier as a type of molten slag flowing down on the membrane wall and finally become a byproduct over the slag removal system. The flyash removal system to capture solid particulates is applied with HPHT ceramic candle filter to stand up against the high pressure and temperature. When it comes to the residual tiny particles after the flyash removal system, wet scurbbing system is applied to finally clean up the solids. The washed-up syngas through the wet scrubber will keep around $130{\sim}135^{\circ}C$, 40~42Mpg and 250 ppmv of hydrochloric acid(HCl) and hydrofluoric acid(HF) at maximum and it is turned over to the gas treatment system for removing toxic gases out of the syngas to comply with the conditions requested from the gas turbine. The result of this study will be utilized to the detailed engineering, procurement and manufacturing of equipments, and construction for the Taean IGCC plant and furthermore it is the baseline technology applicable for the poly-generation such as coal gasification(SNG) and liquefaction(CTL) to reinforce national energy security and create new business models.

• Applied Chemistry for Engineering
• /
• v.26 no.4
• /
• pp.477-482
• /
• 2015

This study examined the adsorption characteristics of heavy metal ions ($Cr^{6+}$, $As^{3+}$) in an aqueous solution using recycled aggregate (RA) and recycled aggregate (RA)/steel slag (SS) composites. The RA and SS are favorable for the absorbent because it contains about 91% and 86.9%, respectively, which are some of the major adsorbent ingredients (CaO, $SiO_2$, $Al_2O_3$ and $Fe_2O_3$) for heavy metal. Kinetic equilibrium of $Cr^{6+}$ and $As^{3+}$ in RA and RA/SS composites reached within 180 min and 360 min, respectively. The kinetic data presented that the slow course of adsorption follows the Pseudo first and second order models. The equilibrium data were well fitted by the Freundlich model and showed the affinity order of $As^{3+}$ > $Cr^{6+}$. The results of $As^{3+}$ also showed that the adsorption capacity slightly increased with increasing pH from 6 to 10. Meanwhile, the adsorption capacity of $Cr^{6+}$ was slightly decreased. From these results, it was concluded that the RA and RA/SS composites can be successfully used for removing the heavy metals ($Cr^{6+}$ and $As^{3+}$) from aqueous solutions.

• Journal of Hydrogen and New Energy
• /
• v.22 no.3
• /
• pp.386-401
• /
• 2011

Mathematical models for various steps in coal gasification reactions were developed and applied to investigate the effects of operation parameters on dynamic behavior of gasification process. Chemical reactions considered in these models were pyrolysis, volatile combustion, water shift reaction, steam-methane reformation, and char gasification. Kinetics of heterogeneous reactions between char and gaseous agents was based on Random pore model. Momentum balance and Stokes' law were used to estimate the residence time of solid particles (char) in an up-flow reactor. The effects of operation parameters on syngas composition, reaction temperature, carbon conversion were verified. Parameters considered here for this purpose were $O_2$-to-coal mass ratio, pressure of reactor, composition of coal, diameter of char particle. On the basis of these parametric studies some quantitative parameter-response relationships were established from both dynamic and steady-state point of view. Without depending on steady state approximation, the present model can describe both transient and long-time limit behavior of the gasification system and accordingly serve as a proto-type dynamic simulator of coal gasification process. Incorporation of heat transfer through heterogenous boundaries, slag formation and steam generation is under progress and additional refinement of mathematical models to reflect the actual design of commercial gasifiers will be made in the near futureK.

• Journal of the Korean Ceramic Society
• /
• v.38 no.9
• /
• pp.829-833
• /
• 2001

There have been many studies about the chemical corrosion of converter's refractories. However, few studies have been reported for the stress corrosion induced by the weight of the refractories and by the two bottom shape models designed for the converter. In this study, the stress distributions of the two converter models were analyzed by FEM. Model 1 has the step edge shape and model 2 has the round edge shape. Simulation results show that model 2 of round bottom edge has higher gravitational stress just below the slag line than the model 1. Model 2 is considered to suffers more serious corrosion than model 1 during the middle working stage by the thermal and chemical factors.

• Computers and Concrete
• /
• v.32 no.2
• /
• pp.149-163
• /
• 2023

One of the main design parameters traditionally utilized in projects of geotechnical engineering is the uniaxial compressive strength. The present paper employed three artificial intelligence methods, i.e., the stochastic fractal search (SFS), the multi-verse optimization (MVO), and the vortex search algorithm (VSA), in order to determine the compressive strength of concrete (CSC). For the same reason, 1030 concrete specimens were subjected to compressive strength tests. According to the obtained laboratory results, the fly ash, cement, water, slag, coarse aggregates, fine aggregates, and SP were subjected to tests as the input parameters of the model in order to decide the optimum input configuration for the estimation of the compressive strength. The performance was evaluated by employing three criteria, i.e., the root mean square error (RMSE), mean absolute error (MAE), and the determination coefficient (R²). The evaluation of the error criteria and the determination coefficient obtained from the above three techniques indicates that the SFS-MLP technique outperformed the MVO-MLP and VSA-MLP methods. The developed artificial neural network models exhibit higher amounts of errors and lower correlation coefficients in comparison with other models. Nonetheless, the use of the stochastic fractal search algorithm has resulted in considerable enhancement in precision and accuracy of the evaluations conducted through the artificial neural network and has enhanced its performance. According to the results, the utilized SFS-MLP technique showed a better performance in the estimation of the compressive strength of concrete (R²=0.99932 and 0.99942, and RMSE=0.32611 and 0.24922). The novelty of our study is the use of a large dataset composed of 1030 entries and optimization of the learning scheme of the neural prediction model via a data distribution of a 20:80 testing-to-training ratio.