• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.1
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• pp.39-50
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• 2022

In this study, we suggested the optimal training period for predicting the streamflow using the LSTM (Long Short-Term Memory) model based on the deep learning and CMIP5 (The fifth phase of the Couple Model Intercomparison Project) future climate scenarios. To validate the model performance of LSTM, the Jinan-gun (Seongsan-ri) site was selected in this study. We comfirmed that the LSTM-based streamflow was highly comparable to the measurements during the calibration (2000 to 2002/2014 to 2015) and validation (2003 to 2005/2016 to 2017) periods. Additionally, we compared the LSTM-based streamflow to the SWAT-based output during the calibration (2000~2015) and validation (2016~2019) periods. The results supported that the LSTM model also performed well in simulating streamflow during the long-term period, although small uncertainties exist. Then the SWAT-based daily streamflow was forecasted using the CMIP5 climate scenario forcing data in 2011~2100. We tested and determined the optimal training period for the LSTM model by comparing the LSTM-/SWAT-based streamflow with various scenarios. Note that the SWAT-based streamflow values were assumed as the observation because of no measurements in future (2011~2100). Our results showed that the LSTM-based streamflow was similar to the SWAT-based streamflow when the training data over the 30 years were used. These findings indicated that training periods more than 30 years were required to obtain LSTM-based reliable streamflow forecasts using climate change scenarios.

• Journal of KIBIM
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• v.12 no.1
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• pp.42-54
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• 2022

BIM facilitates data transparency and consistency through three-dimensional parametric modeling and promotes the accurate managing and sharing of project information. In Korea, however, BIM-based detailed design of architectural interior finishes required during the Construction Documents phase increases the burden on architectural firms due to frequent design changes and manual workload. Therefore, the purpose of this study was to establish rule-based modules using parametric modeling that automates repetitive tasks that occur during the detailed design of interior finishing. Interviews with practitioners were conducted to analyze the major finishing elements. Of these floors, walls, and ceilings, which were the most rudimentary and common items, were selected as the subjects of the study. The modules developed in this study have two functions. One is to create new finish types, and the other is the automatic modeling of new types into rooms. For these functions, parameters that belonged to each finish and room element in a BIM model were analyzed and valid parameters directly used for parametric modeling were derived. Then, based on these parameters, rule-based modules for three elements, I.e., floors, walls, and ceilings were constructed with Revit Dynamo, and the effectiveness of the modules was verified with a pilot test. In conclusion, this study suggested a series of processes for automatic finishing to improve the efficiency of BIM-based architectural detailed design of finishes and to contribute in solving the chronic problems occuring during current design processes.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.2
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• pp.101-107
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• 2022

This study proposes the deconvolution method for the nanoindentation test results of geopolymer employing the Gaussian mixture model. Geopolymer has been studied extensively as an alternative construction material because it emits relatively lower CO₂ compared to ordinary Portland cement. Geopolymer is made of aluminosilicate and alkaline solution, and the Si/Al molar ratio affects its mechanical properties. Previous studies revealed that the Si/Al molar ratio of 1.8~2.0 results in the highest compressive strength, and the Si/Al molar ratio over 1.8 degrades the compressive strength of geopolymer severely; however the reason for the compressive strength degradation is still unclear. To understand the effect of the Si/Al molar ratio on the geopolymer structure, this study exploits the nanoindentation. The phase deconvolution of the indent modulus data is successful using the Gaussian mixture model, and it is observed that the Si/Al molar ratio alters the homogeneity of the geopolymer. Geopolymer becomes more homogeneous up to an Si/Al molar ratio of 1.8 at which geopolymer exhibits the highest compressive strength. The examination of this study is assumed to be adopted as evidence of strength degradation by the Si/Al ratio higher than the optimum value.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.1
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• pp.135-144
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• 2022

This paper aimed to analyze the type of urban shrinkage over the past 20 years for four case cities designated as abandoned mining area promotion zones and present the direction of future urban spatial policies through the analysis of shrinking status. According to the analysis of urban shrinkage in the past 20 years, all of the case cities were analyzed as fixed-type shrinking cities, showing a population decrease of more than 30% over the past 40 years compared to the peak population. Despite the decrease in population, the designated area of urbanization and non-urban areas is increasing every year, and the development permit and construction permit in non-urban areas are also increasing, requiring efficient management and operation of urban space. It is necessary to study military-level cities in the high-risk phase of extinction in the future, and to develop various indicators for segmentation of urban shrinkage types and analysis of status by type.

• Safety and Health at Work
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• v.13 no.3
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• pp.364-371
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• 2022

Background: Respiratory masks can provide healthcare workers with protection from biological hazards when they have good performance. There is a direct relationship between the visual specifications of a mask and its efficacy; thus, the aim of this study was to develop tools for qualitative assessment of the performance of masks used by healthcare workers. Methods: A mixed-methods design was used to develop a qualitative assessment tool for medical face masks (MFM) and particle filtering half masks (PFHM). The development of domains and items was undertaken using observation and interviews, the opinions of an expert panel, and a review of texts and international standards. The second phase evaluated the psychometric properties of tools. Finally, the validated Mask Qualitative Assessment Tools (MQAT) were used to assess six samples from 10 brands of the two types of masks. Results: MQAT-MFM and MQAT-PHFM shared 42 items across seven domains: "cleanliness," "design," "marking, labeling and packaging," "mask layers," "mask strap," "materials and construction," and "nose clip." MQAT-MFM included one additional item. MQAT-PHFM included another nine items associated with an eighth "Practical Performance" domain, and the valve version had another additional "Exhalation Valve" domain and six items. The evaluation indicated 80% compliance for MFM and 71% compliance for PFHM. "Marking, labeling and packaging" and "Layers" were associated with the least compliance in both types of masks and should be checked carefully for defining mask quality. Conclusion: MQAT can be used for immediate screening and initial assessment of MFM and PHFM through appearance, simple tools, and visual inspection.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.94-107
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• 2022

Accidents prevention and mitigation is the highest priority of nuclear power plant (NPP) operation, particularly in the aftermath of the Fukushima Daiichi accident, which has reignited public anxieties and skepticism regarding nuclear energy usage. To deal with accident scenarios more effectively, operators must have ample and precise information about key safety parameters as well as their future trajectories. This work investigates the potential of machine learning in forecasting NPP response in real-time to provide an additional validation method and help reduce human error, especially in accident situations where operators are under a lot of stress. First, a base-case SGTR simulation is carried out by the best-estimate code RELAP5/MOD3.4 to confirm the validity of the model against results reported in the APR1400 Design Control Document (DCD). Then, uncertainty quantification is performed by coupling RELAP5/MOD3.4 and the statistical tool DAKOTA to generate a large enough dataset for the construction and training of neural-based machine learning (ML) models, namely LSTM, GRU, and hybrid CNN-LSTM. Finally, the accuracy and reliability of these models in forecasting system response are tested by their performance on fresh data. To facilitate and oversee the process of developing the ML models, a Systems Engineering (SE) methodology is used to ensure that the work is consistently in line with the originating mission statement and that the findings obtained at each subsequent phase are valid.

• Steel and Composite Structures
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• v.46 no.5
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• pp.689-707
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• 2023

Geopolymer concrete production is interesting as it is an alternative to portland cement concrete. However, workability, setting time and strength expectations limit the sustainable application of geopolymer concrete in practice. This study aims to improve the production of geopolymer concrete to mitigate these drawbacks. The improvement in the workability and setting time were achieved with the additional use of NaOH solution whereas an increase in the strength was gained with the addition of recycled steel fibers from waste tires. In addition, the use of 25% basalt powder instead of fly ash and the addition of recycled steel fibers from waste tires improved its environmental feature. The samples with steel fiber ratios ranging between 0.5% and 5% and basalt powder of 25%, 50% and 75% were tested under both compressive and flexure forces. The compressive and flexural capacities were significantly enhanced by utilizing recycled steel fibers from waste tires. However, decreases in these capacities were detected as the basalt powder ratio increased. In general, as the waste wire ratio increased, the compressive strength gradually increased. While the compressive strength of the reference sample was 26 MPa, when the wire ratio was 5%, the compressive strength increased up to 53 MPa. With the addition of 75% basalt powder, the compressive strength decreases by 60%, but when the 3% wire ratio is reached, the compressive strength is obtained as in the reference sample. In the sample group to which 25% basalt powder was added, the flexural strength increased by 97% when the waste wire addition rate was 5%. In addition, while the energy absorption capacity was 0.66 kN in the reference sample, it increased to 12.33 kN with the addition of 5% wire. The production phase revealed that basalt powder and waste steel wire had a significant impact on the workability and setting time. Furthermore, SEM analyses were performed.

• Structural Engineering and Mechanics
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• v.87 no.6
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• pp.585-599
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• 2023

Geopolymer concrete (GC) can be competently utilized as a practical replacement for cement to prevent a high carbon footprint and to give a direction toward sustainable concrete construction. Moreover, previous studies mostly focused on the axial response of glass fiber reinforced polymer (glass-FRP) concrete compressive elements without determining the effectiveness of repairing them after their partial damage. The goal of this study is to assess the structural effectiveness of partially damaged GC columns that have been restored using carbon fiber reinforced polymer (carbon-FRP). Bars made of glass-FRP and helix made of glass-FRP are used to reinforce these columns. For comparative study, six of the twelve circular specimens-each measuring 300 mm×1200 mm-are reinforced with steel bars, while the other four are axially strengthened using glass-FRP bars (referred to as GSG columns). The broken columns are repaired and strengthened using carbon-FRP sheets after the specimens have been subjected to concentric and eccentric compression until a 30% loss in axial strength is attained in the post-peak phase. The study investigates the effects of various variables on important response metrics like axial strength, axial deflection, load-deflection response, stiffness index, strength index, ductility index, and damage response. These variables include concentric and eccentric compression, helix pitch, steel bars, carbon-FRP wrapping, and glass-FRP bars. Both before and after the quick repair process, these metrics are evaluated. The results of the investigation show that the axial strengths of the reconstructed SSG and GSG columns are, respectively, 15.3% and 20.9% higher than those of their original counterparts. In addition, compared to their SSG counterparts, the repaired GSG samples exhibit an improvement in average ductility indices of 2.92% and a drop in average stiffness indices of 3.2%.

• Korean Journal of Environmental Agriculture
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• v.42 no.3
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• pp.253-258
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• 2023

In the environment, chromium often exists in a highly mobile and toxic form of Cr(VI). Therefore, the reduction of Cr(VI) to less toxic Cr(III) is considered an effective remediation strategy for Cr(VI)-contamination. In this study, the biological reduction of hexavalent chromium was examined at the concentrations of 0.01 mM, 0.1 mM, and 1 mM Cr(VI) by the dissimilatory metal-reducing bacterium, Shewanella sp. HN-41 in the presence of ferric-citrate. With the relatively condensed cell densities, the aqueous phase Cr(VI) was reduced at the proportions of 42%, 23%, and 31%, respectively for the 0.01 mM, 0.1 mM, and 1 mM Cr(VI) incubations, while Fe(III)-citrate was reduced at 95%, 88%, and 73%, respectively. Although the strain HN-41 was not considered to reduce Cr(VI) as the sole electron acceptor for anaerobic metabolism in the preliminary experiment, it has been presumed that outer-membrane c-type cytochromes such as MtrC and OmcA reduced Cr(VI) in the presence of ferric-citrate as the electron acceptor. Since this study indicated the potential of relatively high cell density for Cr(VI) reduction, it might propose a bioremediation strategy for Cr(VI) removal from contaminated waters using engineered systems such as bioreactors employing high cell growths.

• Advances in concrete construction
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• v.14 no.3
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• pp.169-183
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• 2022

In this article, vibrational behavior and wave propagation characteristics in (FG) functionally graded plates resting on Kerr foundation with three parameters is studied using a 2D dimensional (HSDT) higher shear deformation theory. The new 2D higher shear deformation theory has only four variables in field's displacement, which means has few numbers of unknowns compared with others theories. The shape function used in this theory satisfies the nullity conditions of the shear stresses on the two surfaces of the FG plate without using shear correction factors. The FG plates are considered to rest on the Kerr layer, which is interconnected with a Pasternak-Kerr shear layer. The FG plate is materially inhomogeneous. The material properties are supposed to vary smoothly according to the thickness of the plate by a Voigt's power mixing law of the volume fraction. The equations of motion due to the dynamics of the plate resting on a three-parameter foundation are derived using the principle of minimization of energies; which are then solved analytically by the Navier technique to find the vibratory characteristics of a simply supported plate, and the wave propagation results are derived by using the dispersion relations. Perceivable numerical results are fulfilled to evaluate the vibratory and the wave propagation characteristics in functionally graded plates and some parameters such wave number, thickness ratio, power index and foundation parameters are discussed in detail.