• Geomechanics and Engineering
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• v.17 no.5
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• pp.485-496
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• 2019

Sealing of leakage in waterfront or water-retaining structures is one of the major issues in geotechnical engineering practices. With demands for biological methods as sustainable ground improvement techniques, bioclogging, defined as the reduction in hydraulic conductivity of soils caused by microbial activities, has been considered as an alternative to the chemical grout techniques for its economic advantages and eco-friendliness of microbial by-products. This study investigated the feasibility of bioaugmentation and biostimulation methods to induce fermentation-based bioclogging effect in coarse sands. In the bioaugmentation experiments, effects of various parameters and conditions, including grain size, pH, and biogenic gas generation, on hydraulic conductivity reduction were examined through a series of column experiments while Leuconostoc mesenteroides, which produce an insoluble biopolymer called dextran, was used as the model bacteria. The column test results demonstrate that the accumulation of bacterial biopolymer can readily reduce the hydraulic conductivity by three-to-four orders of magnitudes or by 99.9-99.99% in well-controlled environments. In the biostimulation experiments, two inoculums of indigenous soil bacteria sampled from waterfront embankments were prepared and their bioclogging efficiency was examined. With one inoculum containing species capable of fermentation and biopolymer production, the hydraulic conductivity reduction by two orders of magnitude was achieved, however, no clogging was found with the other inoculum. This implies that presence of indigenous species capable of biopolymer production and their population, if any, play a key role in causing bioclogging, because of competition with other indigenous bacteria. The presented results provide fundamental insights into the bacterial biopolymer formation mechanism, its effect on soil permeability, and potential of engineering bacterial clogging in subsurface.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.2
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• pp.1-12
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• 2019

Open space planners and designers should consider scientific and quantified functions of trees when they have to locate where to plant the tree. However, until now, most planners and designers could not consider them because of lack of tool for considering scientific and quantitative tree functions. This study introduces a tree location supporting tool which focuses on the multi-objective including scientific function using ACO (Ant colony optimization). We choose shading effect (scientific function), shielding, and openness as objectives for test application. The results show that when the user give a high weight to a particular objective, they can obtain the optimal results with high value of that objective. When we allocate higher weight for the shading effect, the tree plans provide larger shadow value. Even when compared with current tree plan, the study result has a larger shading effect plan. This result will reduce incident radiation to the ground and make thermal friendly open space in the summer. If planners and designers utilize this tool and control the objectives, they would get diverse optimal tree plans and it will allow them to make use of the many environmental benefits from trees.

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

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.815-827
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• 2020

The epidermal growth factor (EGF) transgenic soybean was developed and biosynthesis of human epidermal growth factor (hEGF) in soybean seeds was confirmed. Also, EGF transgenic soybean were found to contain a herbicide resistance selectable marker by introduction of phosphinothricin acetyltransferase (PAT) gene from the Streptomyces hygroscopicus. For biosafety assessment, the EGF transgenic soybean expressing the EGF biosynthesis gene EGF and herbicide resistant gene PAT was tested to determine effects on survival of Cyprinus carpio, commonly used as a model organism in ecotoxicological studies. C. carpio was fed 100% ground soybean suspension, EGF soybean or non-genetically modified (GM) counterpart soybean (Gwangan). Gene expression of EGF soybean was confirmed by PCR and ELISA to have EGF/PAT. Feeding test showed that no significant differences in cumulative immobility or abnormal response between C. carpio samples fed on EGF soybean and non-GM counterpart soybean. The 48 h-EC50 values of the EGF and non-GM soybean were 1,688 mg·L-1 (95% confidence limits: 1,585 - 1,798 mg·L-1) and 1,575 mg·L-1 (95% confidence limits: 1,433 - 1,731 mg·L-1), respectively. The soybean NOEC (no observed effect concentration) value for C. carpio was suggested to be 625 mg·L-1. We concluded that there was no significant difference in toxicity for non-target organisms (C. carpio) between the EGF soybean and non-GM counterparts.

• Journal of the Korean Geotechnical Society
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• v.37 no.6
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• pp.21-28
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• 2021

The factors of landslides depend on rainfall intensity, duration, and the characteristics of the soil slope. The conventional slope stability analysis has been carried out by assuming that the slope is saturated. But, a site slope consisting of unsaturated ground must be imitated and interpreted in order to explain a proper behavior of the slope due to rainfall. In this study, by using two major categories of soils in Korea, such as granite and gneiss weathered soils, landslide model test and numerical analysis have been compared with the difference of seepage and volumetric water content. In general, the permeability of gneiss weathered soil, which contains a lot of fines content, is slower than that of granite weathered soil. As a result, in extreme rainfall, numerical analysis can show results that can penetrate quickly, resulting in saturation or more dangerous collapse.

• Journal of the Korean Geotechnical Society
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• v.24 no.2
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• pp.59-65
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• 2008

Digital close-range photogrammetric technique can measure and describe 3D geometric farm from 2D image. This technique is increasingly applied in the field of sciences. In the fields of civil and mechanical engineering, which need precise measurements for design, expensive measuring equipments are widely used. In occasions where visual inspection is required in addition to other forms of measurements, appropriate measuring equipments have not been yet available. This study utilizes digital close-range photogrammetric technique to quantitatively analyze behavior patterns before and after destruction from test model of reinforced-soil wall. Then the results are compared with the measurements obtained using digital theodolite to verify the reliability of the proposed method.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.18 no.4
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• pp.12-21
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• 2022

Steam assisted gravity drainage(SAGD) is a process that drills well in the underground oil sands layer, injects hightemperature steam, lowers the viscosity of buried bitumen, and recovers it to the ground. Recently, direct contact steam generator(DCSG) is being developed to maximize steam efficiency for SAGD process. The DCSG requires high technology to achieve pressurized combustion and steam generation in accordance with underground pressurized conditions. Therefore, it is necessary to develop a combustion technology that can control the heat load and exhaust gas composition. In this study, process analysis of high-pressurized DCSG was conducted to apply oxygen enrichment technology in which nitrogen of the air was partially removed for increasing steam production and reducing fuel consumption. As the process analysis conditions, methane as the fuel and normal air or oxygen enriched air as the oxidizing agent were applied to high-pressurized DCSG process model. A simple combustion reaction program was used to calculate the property variations for combustion temperature, steam ratio and residual heat in exhaust gas. As a major results, the steam production efficiency of DCSG using the pure oxygen was about 6% higher than that of the normal air due to the reducing nitrogen in the air. The results of this study will be used as operating data to test the demonstration device.

• Journal of Korean Tunnelling and Underground Space Association
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• v.11 no.4
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• pp.419-425
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• 2009

Recently, the number of shallow tunnel construction increases to improve the structural safety and environment-friendliness. In Semi-Cut and Cover Method, ground is excavated to the crown arch level and braced rib arch is set to backfill before the excavation of lower face. Semi-Cut and Cover Method is proposed to solve the problems occurred by the conventional Cut and Cover Method, such as unstability, high-cost and the large cutting slope to be reinforced. In this paper, the behaviors of Braced Rib Arch in shallow tunnel excavated by semi-cut and cover method was studied. Model tests in 1:10 Scale were performed in real construction sequences. The distance between supports of rib arch was 1.8 m and the length of spacer was 1.0 m. the size of test pit was 4.0 m (width)$\times$3.3 m (length) 4.0 m (height) in dimension. Tests results show that backfill load acting on arch was smaller than that in the conventional Open-Cut Method.

• Steel and Composite Structures
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• v.52 no.3
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• pp.293-312
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• 2024

Researchers are actively investigating the potential for utilizing alternative materials in construction to tackle the environmental and economic challenges linked to traditional concrete-based materials. Nevertheless, conventional laboratory methods for testing the mechanical properties of concrete are both costly and time-consuming. The limitations of traditional models in predicting the tensile strength of concrete composited with geopolymer have created a demand for more advanced models. Fortunately, the increasing availability of data has facilitated the use of machine learning methods, which offer powerful and cost-effective models. This paper aims to explore the potential of several machine learning methods in predicting the tensile strength of geopolymer concrete under different curing conditions. The study utilizes a dataset of 221 tensile strength test results for geopolymer concrete with varying mix ratios and curing conditions. The effectiveness of the machine learning models is evaluated using additional unseen datasets. Based on the values of loss functions and evaluation metrics, the results indicate that most models have the potential to estimate the tensile strength of geopolymer concrete satisfactorily. However, the Takagi Sugeno fuzzy model (TSF) and gene expression programming (GEP) models demonstrate the highest robustness. Both the laboratory tests and machine learning outcomes indicate that geopolymer concrete composed of 50% fly ash and 40% ground granulated blast slag, mixed with 10 mol of NaOH, and cured in an oven at 190°F for 28 days has superior tensile strength.

• Smart Structures and Systems
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• v.33 no.4
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• pp.291-300
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• 2024

Uncertainty of the model, system delay and drive dynamics can be considered as normal uncertainties, and the main source of uncertainty in the seismic control system is related to the nature of the simulated seismic error. In this case, optimizing the management strategy for one particular seismic record will not yield the best results for another. In this article, we propose a framework for online management of active structural management systems with seismic uncertainty. For this purpose, the concept of reinforcement learning is used for online optimization of active crowd management software. The controller consists of a differential controller, an unplanned gain ratio, the gain of which is enhanced using an online reinforcement learning algorithm. In addition, the proposed controller includes a dynamic status forecaster to solve the delay problem. To evaluate the performance of the proposed controllers, thousands of ground motion data sets were processed and grouped according to their spectrum using fuzzy clustering techniques with spatial hazard estimation. Finally, the controller is implemented in a laboratory scale configuration and its operation is simulated on a vibration table using cluster location and some actual seismic data. The test results show that the proposed controller effectively withstands strong seismic interference with delay. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results is believed to achieved in the near future by the ongoing development of AI and control theory.