For the quick rehabilitation of a fire-damaged tunnel structure, it is the most important procedure to investigate the fire-induced damaged zone rapidly. This study aims to propose a new drilling resistance testing method by which mechanical properties of tunnel concrete lining altered by high temperature can be estimated easily and continuously. Especially, it alms to derive the relationships to estimate mechanical properties of mortar and concrete materials from drilling parameters. To obtain the optimum testing condition, a series of drilling resistance tests were carried out for mortar specimens. When the rotation per minute of drill bit, tile penetration rate and the bit diameter were 1,300 rpm, 1.40 mm/sec, and 10 mm respectively, the deviation of measured drilling resistance forces was minimal. Under the optimum testing condition, the relationships between drilling resistance and mechanical properties of mortar specimens were shown to be very favorable. The concept of replacing a mean value of resistance farces measured during drilling with the resistance energy was proposed to consider the effects of randomly distributed aggregates inside a concrete material on drilling resistance. When the concept was applied to concrete materials, a favorable relationship between actual compressive strength and drilling resistance energy was also successfully derived.
Data modelling and interpretation for structural health monitoring (SHM) field data are critical for evaluating structural performance and quantifying the vulnerability of infrastructure systems. In order to improve the data modelling accuracy, and extend the application range from data regression analysis to out-of-sample forecasting analysis, an improved most likely heteroscedastic Gaussian process (iMLHGP) methodology is proposed in this study by the incorporation of the outof-sample forecasting algorithm. The proposed iMLHGP method overcomes this limitation of constant variance of Gaussian process (GP), and can be used for estimating non-stationary typhoon-induced response statistics with high volatility. The first attempt at performing data regression and forecasting analysis on structural responses using the proposed iMLHGP method has been presented by applying it to real-world filed SHM data from an instrumented cable-stay bridge during typhoon events. Uncertainty quantification and correlation analysis were also carried out to investigate the influence of typhoons on bridge strain data. Results show that the iMLHGP method has high accuracy in both regression and out-of-sample forecasting. The iMLHGP framework takes both data heteroscedasticity and accurate analytical processing of noise variance (replace with a point estimation on the most likely value) into account to avoid the intensive computational effort. According to uncertainty quantification and correlation analysis results, the uncertainties of strain measurements are affected by both traffic and wind speed. The overall change of bridge strain is affected by temperature, and the local fluctuation is greatly affected by wind speed in typhoon conditions.
Korean Journal of Agricultural and Forest Meteorology
/
v.25
no.3
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pp.208-217
/
2023
Accurate estimation of dormancy breaking and first bloom dates is crucial for effective fire blight control by disease model such as Maryblyt in apple orchards. The duration from dormancy breaking to first bloom in apple trees was influenced by daily minimum temperatures during the dormant period. The purpose of this study is to investigate the relationship between minimum temperatures during this period and the time taken for flowering to commence. Webcam data from eight apple orchards, equipped by the National Institute of Horticultural and Herbal Science, were observed from 2019 to 2023 to determine the dates of starting bloom (B1). Additionally, the dormancy breaking dates for these eight sites were estimated using an apple chill day model, with a value of -100.5 DD, based on collected weather data. Two regressions were performed to analyze the relationships: the first regression between the number of days under 0℃ (X1) and the time from calculated dormancy breaking to observed first bloom (Y), resulting in Y = 0.87 × X1 + 40.76 with R2 = 0.84. The second regression examined the starting date of breaking dormancy (X2) and the duration from dormancy breaking to observed first bloom (Y), resulting in Y = -1.07 × X2 + 143.62 with R2 = 0.92. These findings suggest that apple anti-chill days are significantly affected by minimum temperatures during the period from dormancy breaking to flowering, indicating their importance in fire blight control measures.
The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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v.29
no.1
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pp.1-13
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2024
The southwestern part of the East Sea is known to have a high primary productivity compared to those in the northern and eastern parts, which is attributed to nutrients supplies either by Tsushima Warm Current or by coastal upwelling. However, research on the biological pump in this area is limited. We developed machine learning models to estimate net community production (NCP), a measure of biological pump, with high spatial and time scales of 4 km and 8 days, respectively. The models were fed with the input parameters of sea surface temperature, chlorophyll-a, mixed layer depths, and photosynthetically active radiation and trained with observed NCP derived from high resolution measurements of surface O2/Ar. The root mean square error between the predicted values by the best performing machine model and the observed NCP was 6 mmol O2 m-2 d-1, corresponding to 15% of the average of observed NCP. The NCP in the central part of the Ulleung Basin was highest in March at 49 mmol O2 m-2 d-1 and lowest in June and July at 18 mmol O2 m-2 d-1. These seasonal variations were similar to the vertical nitrate flux based on the 3He gas exchange rate and to the particulate organic carbon flux estimated by the 234Th disequilibrium method. To expand this method, which produces NCP estimate for spring and summer, to autumn and winter, it is necessary to devise a way to correct bias in NCP by the entrainment of subsurface waters during the seasons.
Yongseok Kim;Jina Hur;Eung-Sup Kim;Kyo-Moon Shim;Sera Jo;Min-Gu Kang
Korean Journal of Agricultural and Forest Meteorology
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v.26
no.1
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pp.53-62
/
2024
In this study, we built a model to estimate frost occurrence in South Korea using single-input deep learning and multi-input deep learning. Meteorological factors used as learning data included minimum temperature, wind speed, relative humidity, cloud cover, and precipitation. As a result of statistical analysis for each factor on days when frost occurred and days when frost did not occur, significant differences were found. When evaluating the frost occurrence models based on single-input deep learning and multi-input deep learning model, the model using both GRU and MLP was highest accuracy at 0.8774 on average. As a result, it was found that frost occurrence model adopting multi-input deep learning improved performance more than using MLP, LSTM, GRU respectively.
Linhu Hui;Fengli Wu;Yuanyuan Xu;Guangjun Yang;Qiaorong Luo;Yangyang Li;Long Ma;Xinsheng Yao;Jun Li
Animal Bioscience
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v.37
no.12
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pp.2178-2188
/
2024
Objective: The liver plays a dual role in regulating temperature and immune responses. Examining the influence of heat stress (HS) on liver T cells contributes significantly to understanding the intricate interplay between the immune system and hepatic tissues under thermal stress. This study focused on investigating the characteristics of the T-cell receptor (TCR) β chain CDR3 repertoire in bovine liver samples under both HS and pairfed (PF) environmental conditions. Methods: Sequencing data from six samples sourced from the GEO database underwent annotation. Utilizing immunarch and VDJtool software, the study conducted comprehensive analyses encompassing basic evaluation, clonality assessment, immune repertoire comparison, diversity estimation, gene usage profiling, VJ gene segment pairing scrutiny, clonal tracking, and Kmers analysis. Results: All four TCR chains, namely α, β, γ, and δ, were detected, with the α chains exhibiting the highest detection frequency, followed closely by the β chains. The prevalence of αβ TCRs in bovine liver samples underscored their crucial role in governing hepatic tissue's physiological functions. The TCR β CDR3 repertoire showcased substantial inter-individual variability, featuring diverse clonotypes exhibiting distinct amino acid lengths. Intriguingly, HS cattle displayed heightened diversity and clonality, suggesting potential peripheral T cell migration into the liver under environmental conditions. Notably, differential VJ gene pairings were observed in HS cattle compared to the PF, despite individual variations in V and J gene utilization. Additionally, while most high-frequency amino acid 5-mers remained consistent between the HS and PF, GELHF, and YDYHF were notably prevalent in the HS group. Across all samples, a prevalent trend of high-frequency 5mers skewed towards polar and hydrophobic amino acids was evident. Conclusion: This study elucidates the characteristics of liver TCR β chain CDR3 repertoire under HS conditions, enhancing our understanding of HS implications.
In this study, data from the Gwangyang Automated Synoptic Observing System (ASOS) meteorological observatory were utilized for drought assessment. Drought occurrence days were evaluated using the Precipitation-based Standardized Precipitation Index (SPI) and two types of Standardized Precipitation Evapotranspiration Index (SPEI) (SPEI_Thornthwaite and SPEI_Penman-Monteith), considering precipitation and evapotranspiration. The SPI and SPEIs yielded generally similar quantitative results for drought occurrence days. However, the SPEI_Penman-Monteith, which uses the physically-based Penman-Monteith method for evapotranspiration estimation, showed a higher number of drought days compared to the SPI_Thornthwaite. The amount of evapotranspiration by the Penman-Monteith method had high seasonal variability and high moisture loss, while the amount of evapotranspiration by the Thornthwaite method had low variability and low moisture loss. Consequently, the SPEI_Thornthwaite had a higher correlation with the SPI compared to the SPEI_Penman-Monteith. Since the SPEI_Penman-Monteith index can more accurately calculate the amount of water loss caused by the hydrological circulation, more reasonable results are derived in calculating the number of drought occurrence days. However, due to the lack of sufficient high-quality meteorological data at ASOS observatories, the Penman-Monteith method may be difficult to apply. In such cases, the SPEI_Thornthwaite, estimating evapotranspiration based solely on monthly average temperature, can be used as an alternative.
Kim, Moonil;Yoo, Somin;Kim, Nahui;Lee, Wona;Ham, Boyoung;Song, Cholho;Lee, Woo-Kyun
Korean Journal of Environmental Biology
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v.35
no.3
/
pp.413-425
/
2017
This manuscript describes the relationship between climate change and forest growth, forest species, carbon stocks, and tree mortality. 1) In the aspect of forest growth, the growth of major coniferous species, including Pinus densiflora, had a negative correlation with temperature. On the other hand, major deciduous oak species, including Quercus variabilis and Quercus mongolica, had a positive correlation with temperature. 2) When considered in the aspect of the forest species distribution, various models commonly showed a decrease in the distribution of coniferous species and an increase in oak species due to climate change in the medium to long term. 3) From the carbon stock perspective, there was a difference in the estimation according to the status of forest management. Most of Korean forests will mature to become over-matured forest after year 2030 and are estimated to produce approximately 410 million ton forest biomass until 2090 with the current cutting regulations for sustainable forest management announced by the Korean Forest Service. 4) In the forest mortality, the mortality rate of the major coniferous species showed a clear tendency to increase higher temperatures while it decreased for the oak species with no verification of statistical significance. Moreover, the mortality of the subalpine coniferous species was projected to progress rapidly. considering the overall impacts described above, there should be a management strategy for coniferous species that are relatively vulnerable to climate change. Moreover, a sustainable forest plan in the aspect of ecosystem services, carbon sequestration and storage, which is linked to global issues such as Sustainable Development Goals, ecosystem services and negative emission.
Yun, Sung-Wook;Choi, Man Kwon;Kim, Ha Neul;Kang, Donghyeon;Lee, Siyoung;Son, Jinkwan;Yoon, Yong Cheol
Journal of Bio-Environment Control
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v.25
no.2
/
pp.83-88
/
2016
In this study, previously reported surplus solar energy-related study result and current status of fan coil unit (FCU) for cooling and heating installed in the current sites were briefly examined and then a method to determine the number of FCUs required to recover surplus solar energy was schematically proposed to provide basic data for researchers and technical engineers in this field. The maximum, mean, and minimum outside temperatures during the experiment period were about $28.2^{\circ}C$, $4.4^{\circ}C$, and $-11.5^{\circ}C$, respectively. The horizontal surface solar radiation level outside the greenhouse was in a range of $0.8-20.5MJ{\cdot}m^{-2}$ and mean and total solar radiation were $10.8MJ{\cdot}m^{-2}$ and $1,187.5MJ{\cdot}m^{-2}$. The mean temperature and relative humidity in the greenhouse during the daytime were in a range of 18.8-45.5 and 53.5-77.5%. The total surplus solar energy recovered from the greenhouse during the experiment period was approximately 6,613.4MJ, which could supplement about 6.7% of the total heating energy 98,600.2 MJ. In addition, the number of FCUs installed for heating varies case to case, although similar FCUs are used. Thus, it is necessary to study the installation height, orientation and installation distance as well as the appropriate number of FCUs from the efficient and economical viewpoints. The required numbers of FCUs for surplus solar energy recovery were 8.4-10.9units and 6.1-8.0units based on air mass and circular flow rate that passed through the FCUs. Considering calculation methods and the risks such as efficiency and use environments of FCUs, it was found that about nine units (one unit per $24m^3$ approximately) needed to be installed. The required number of FCUs for surplus solar energy recovery was around one unit per $24m^3$ approximately.
The considerable portion of energy demand has been satisfied by the combustion of fossil fuel and the consequent $CO_2$ emission was considered as a main cause of global warming. As a technology option for $CO_2$ emission mitigation, absorption process has been used in $CO_2$ capture from large scale emission sources. To set up optimal operating parameters in $CO_2$ absorption and solvent regeneration units are important for the better performance of the whole $CO_2$ absorption plant. Optimal operating parameters are usually selected through a lot of actual operation data. However theoretical approach are also useful because the arbitrary change of process parameters often limited for the stability of process operation. In this paper, a theoretical approach based on vapor-liquid equilibrium was proposed to estimate optimal operating conditions of $CO_2$ absorption process. Two $CO_2$ absorption processes using 12 wt% aqueous $NH_3$ solution and 20 wt% aqueous MEA solution were investigated in this theoretical estimation of optimal operating conditions. The results showed that $CO_2$ loading of rich absorbent should be kept below 0.4 in case of 12 wt% aqueous $NH_3$ solution for $CO_2$ absorption but there was no limitation of $CO_2$ loading in case of 20 wt% aqueous MEA solution for $CO_2$ absorption. The optimal regeneration temperature was determined by theoretical approach based on $CO_2$ loadings of rich and lean absorbent, which determined to satisfy the amount of absorbed $CO_2$. The amount of heating medium at optimal regeneration temperature is also determined to meet the difference of $CO_2$ loading between rich and lean absorbent. It could be confirmed that the theoretical approach, which accurately estimate the optimal regeneration conditions of lab scale $CO_2$ absorption using 12 wt% aqueous $NH_3$ solution could estimate those of 20 wt% aqueous MEA solution and could be used for the design and operation of $CO_2$ absorption process using chemical absorbent.
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