Engineered Material Arresting System (EMAS) is a critical safety installation at the end of a runway toarrest an overrunning aircraft. Key parameters such as vertical load and wheel-EMAS interaction mode significantly influence arresting performance. Since aircraft overrun involves combinations of these parameters, understanding their coupled effect is essential for predicting arresting behavior. This study investigates the combined effects of loads and wheel-EMAS interaction modes, namely rolling, sliding, and combined rolling-sliding, on wheel velocity. A finite element model simulating the wheel’s translation across the EMAS bed was developed using LS-DYNA, a commercial software. The wheel was modeled as a rigid aluminum body, whereas the EMAS bed was represented as a glass foam. The simulation model was defined using comprehensive inputs, including geometry, material models, boundary conditions, and contact parameters, with the initial wheel entry velocity kept constant across all simulations. For each load, the various wheel-EMAS interaction modes were examined. Results indicate that both higher loads and sliding-dominated interaction significantly enhance velocity decay.Among the investigated cases, the greatest velocity decay occurs for pure sliding motion under the highest applied load, where the velocity is reduced by 99.43% of the initial velocity. In contrast, rolling motion under the reference load exhibits the least decay, with only a 29.27% of the initial velocity, while all other cases fall between these two extremes. This trend indicates that sliding-dominated motion dissipates a larger portion of kinetic energy, resultingin greater velocity decay. On the other hand, rolling motion limits energy loss, and the combined rolling-sliding mode exhibits transitional behavior between these two modes. This velocity decay is amplified under higher loads, where the increased normal force enhances energy dissipation. Hence, the combined effect of interaction mode and load is critical for the accurate evaluation and design of EMAS systems.

In response to global emission reduction goals set by the Paris Agreement (2015), the construction industry has adopted strategies to reduce cement consumption by using sustainable materials. Sugarcane bagasse ash (SCBA), an agro-waste by-product, has shown its potential for use as a sand or cement replacement in concrete. However, its nature and complex interactions across mixed designs make predicting its compressive strength challenging using conventional approaches. This study presents the use of k-nearest neighbors (KNN), a machine-learning model for predicting the compressive strength of concrete incorporating SCBA as a sand or cement replacement. Three databases, Web of Science, Scopus, and Google Scholar, were used in the collection of 844 experimental data points from published articles between 2015 and 2025. Independent variables include SCBA usage, SCBA replacement level, cement content, fine and coarse aggregate contents, water-to-binder ratio, superplasticizer dosage, and curing age, while compressive strength served as the dependent variable. Prior to model development, SCBA usage, the only categorical variable, was encoded using one-hot encoding. Feature scaling using StandardScaler was applied to ensure consistency in distance-based features. The dataset was split into 75%-25% train-test subsets, and 5-fold cross-validation was carried out to enhance model generalization and robustness. Hyperparameter tuning was optimized using Optuna to enhance predictive accuracy. The optimized KNN model achieved a coefficient of determination (R²), root mean square error (RMSE), and mean absolute error (MAE) values of 1, 0.329, and 0.063 in the training phase and 0.81, 7.378, and 5.674 in the testing phase, respectively. Optuna improved the result of the mean cross validated coefficient of determination from 0.78 to 0.84 upon hyperparameter tuning. While the results indicate KNN capability of capturing localized patterns in the heterogeneous SCBA concrete dataset, robust ML models such as eXtreme Gradient Boosting and Random Forest may be used to capture enhanced generalization of the dataset. KNN serves as a reliable baseline model for data-driven prediction of compressive strength, highlighting the potential of simple, interpretable machine-learning models in supporting sustainable concrete design aligned with global climate mitigation goals.

The use of hydrogen as an energy carrier has gained widespread adoption in warehouses and industrial environments. This increasing adoption necessitates the need for stringent safety evaluations specifically for enclosed fueling systems where the potential of accidental discharges may result in explosions or jet fires. This study demonstrates a quantitative risk assessment of an indoor hydrogen dispenser positioned in a warehouse facility using the Hydrogen Risk Assessment Models (HyRAM+) version 6.1 software developed by Sandia National Laboratories. A representative 120 m x 120 m x 10.62 m housing a 70 MPa gaseous hydrogen dispenser used in the refueling of hydrogen-powered vehicles in an enclosed space scenario was modeled Based on realistic industry standard assumptions system geometry conditions of operation and component inventory were defined. HyRAM+ was employed to evaluate deterministic and probabilistic models to determine potential loss of life (PLL), fatal accident rate (FAR), and average individual risk (AIR). The PLL, FAR, and AIR values of 1.05 x 10-4 fatalities per year 0.02 fatalities per 100 million working hours and 5.99 x 10-7, respectively indicate negligible individual risk under the modeled conditions. Additionally flame and leak analysis revealed smaller sizes of leaks being likely to result in no ignition and safe shutdown with larger leak size resulting in the probability of explosion or jet fire. Furthermore radiative heat flux analysis of a 6.223 mm leak also revealed the occurrence of peak heat flux along the jet axis with a decrease in distance demonstrating that thermal exposure is highly directional. These findings demonstrate that the assessed indoor hydrogen dispenser operates within acceptable safety limits and highlight the effectiveness of HyRAM+ as a tool for hydrogen safety designs.

The application of machine learning in concrete technology has expanded rapidly, yet its reliability is often constrained by limited experimental data, heterogeneous testing conditions, and inconsistencies across published studies. This study investigates the integration of machine learning and synthetic data augmentation to predict the compressive strength of concrete incorporating biochar as a partial replacement for cement. An experimental dataset was compiled from peer-reviewed journal articles indexed in Web of Science, focusing on biochar-modified concrete mixtures. Input variables included cement content, fine and coarse aggregates, biochar dosage, water to binder ratio, superplasticizer content, and curing age, with compressive strength as the target variable. Extreme Gradient Boosting was adopted due to its strong performance on nonlinear tabular data. Model performance was evaluated using the mean absolute error (MAE), mean squared error (MSE), and coefficient of determination (R²), alongside five-fold cross-validation. Hyperparameter optimization was performed using Optuna. To address data scarcity, a synthetic dataset of 1000 samples was generated using ChatGPT. the large language model approach relied solely on natural language prompts. Only feature definitions and the target variable were provided, without exposing the original data or implementing data generation algorithms. Three modeling strategies were examined. First, model trained and tested solely on experimental data achieved a testing R² of approximately 0.91. Second, model trained on synthetic data and evaluated exclusively on experimental data showed reduced generalization, achieving a testing R² of about 0.42, indicating pronounced domain shift effects. Third, synthetic and experimental data were combined through data augmentation and jointly modeled, a testing R² of 0.93 was achieved. The result showed that the use of LLMs for augmentation improved the performance of the model.

This study aims to evaluate the feasibility of cementless concrete using industrial byproducts as an eco-friendly alternative to conventional cement concrete. Ground-granulated blast-furnace slag (GGBFS), fly ash (FA), and silica fume (SF) were employed as binder materials, and the mechanical performance, plastic shrinkage behavior, and microstructural characteristics of cementless concrete were investigated to verify its applicability as a structural and shotcrete material capable of reducing CO₂ emissions. Cementless concrete mixtures were prepared using GGBFS, FA, and SF as binders, activated by sodium hydroxide and sodium silicate with water-to-binder (W/B) ratios of 0.40, 0.45, and 0.50. Conventional cement concrete with equivalent water ratios was used for comparison. Compressive strength tests were conducted at curing ages of 1, 3, 7, 14, and 28 days. Plastic shrinkage cracking was evaluated according to the ASTM C1579 standard. Microstructural development and reaction products were analyzed using scanning electron microscopy (SEM) and X-ray diffraction (XRD), respectively. Cementless concrete with W/B ratios of 0.45 and 0.50 exhibited compressive strength comparable to or higher than that of cement concrete from early ages and demonstrated superior 28-day strength performance. No plastic shrinkage cracking was observed for any mixture, indicating excellent early-age crack resistance. SEM analysis revealed progressive densification of the microstructure owing to the formation of C-(A)-S-H and N-A-S-H gel phases with increasing curing age. XRD results showed limited portlandite formation in cementless concrete, accompanied by an increased development of aluminosilicate reaction products after 7 days, resulting in reduced porosity and enhanced structural compactness. Experimental results confirmed that cementless concrete incorporating industrial byproducts can achieve mechanical performance and durability characteristics comparable to or exceeding those of conventional cement concrete when an appropriate W/B ratio is applied. Reduced portlandite formation and dominant alkali-activated reaction products contributed to the improved chemical stability and resistance to deterioration. Therefore, cementless concrete has a strong potential as a sustainable construction material capable of reducing CO₂ emissions while maintaining its structural performance, particularly for shotcrete applications.

일체식 교대 교량 공법은 1930년대부터 미국과 캐나다에서 적용되었으나, 국내에서는 공용 기간이 짧아 설계, 시공 및 유지관리 경 험이 부족하다. 또한, 장기 거동에 대한 추적 데이터가 부족해 설계 시 예측한 구조 거동의 안정성 검증이 필요하다. 본 연구는 국내 공 용 중인 일체식 교대 교량을 대상으로 장기 계측을 수행하고, 선행 연구에서 제안된 수치 해석 모델을 적용해 구조 안정성과 모델의 적용성을 검증하였다. 계절적 온도 변화에 따른 변위 값의 크기와 변화 형상을 정성적으로 평가하고, 실측과 수치 해석 변위 값을 t 검 정으로 비교해 정량적 검증을 수행하였다. 분석 결과, 대상 교량들은 예측 값과 실측 값이 큰 오차 없이 안정적인 구조 거동을 보였다. 일부 교량에서는 교대 밀림으로 인한 신축 이음 축소와 교대 벽체 및 거더부 협착이 관찰되었다. 모델링 정확도를 높이기 위해 지반- 교대 스프링 강성과 교좌 전단 강성을 설계 값보다 높게 반영하는 것이 필요하다.

본 연구는 중국의 BL 콘텐츠 규제를 통해 드러난 국가의 규율 권력과 이에 대응하 는 중국 BL 팬덤의 전술적 대응을 분석한다. 푸코의 ‘규율 권력’과 버틀러의 ‘젠더 수 행성’ 개념은 국가가 남성에게 요구하는 수행 양식을 표준화하고, ‘정상성’에 부합하는 표현만을 승인하는 통치 전략을 설명한다. 이에 맞서 중국 BL 팬덤은 세르토의 ‘전술’ 개념을 통해 규제의 틈을 점유하고, 프레이저의 ‘하위 공론장’ 개념을 바탕으로 독자 적인 자신들의 질서를 구성해 왔다. 본 연구는 이러한 BL 팬덤의 대응 양상을 분석 함으로써, 현대 중국 사회에서 하위 주체가 규범 통치에 맞서는 방식을 이론적으로 조명한다. 나아가 이러한 대응은 국가 규범 권력에 대한 전술적 대응을 넘어, 표현의 자율성과 젠더 수행을 둘러싼 새로운 질서 형성의 계기로 작동함을 드러낸다.

이 연구는 해조류에서 추출된 알긴산을 혼입하여 라텍스 콘크리트의 경제성을 개선하고, X선 회절 분석(XRD)을 통해 미세구조 변화 를 분석하는 것을 목표로 한다. 기존 라텍스 콘크리트(LMC)의 높은 비용을 보완하기 위해 라텍스 혼입량을 줄이고 알긴산을 추가한 콘크리트를 제작하여 재령 4시간, 7일, 28일에 따른 미세구조 및 강도 발현 특성을 분석하였다. XRD 분석 결과, 재령 증가에 따라 Ettringite는 감소하고 일부 Monosulfate(AFm 상)로 변환되었으며, Ye’elimite는 C-S-H 및 Monosulfate로 변환되면서 초기 강도 발현이 감 소하고 장기 강도가 증가하는 경향을 나타내었다. 압축강도 실험에서는 재령 28일 기준 case 2의 강도가 기존 LMC와 유사한 수준을 나타내었다. 알긴산 혼입 라텍스 콘크리트에서 Larnite(C2S) 증가와 Hatrurite(C3S) 감소가 관찰되었다. 이는 알긴산이 C3S의 조기 수화 를 촉진하고 후반 수화 반응을 활성화시켜 장기 강도 발현에 긍정적인 영향을 미친 것으로 판단된다. 결과적으로, 알긴산 혼입 라텍스 콘크리트는 초기 강도보다는 장기 강도 발현에 유리하며, 최적 혼입량 설정과 내구성 평가를 위한 추가 연구가 필요할 것으로 판단된 다.

이 연구는 산업 부산물을 활용한 무시멘트 숏크리트의 압축강도를 분석하고, 기존 숏크리트와 비교하여 최적 배합설계를 도출하였다. KS F 2403 및 KS F 2405에 따라 시험을 진행한 결과, 일반 숏크리트 및 무시멘트 숏크리트 모두 숏크리트 품질기준에서 제시하고 있 는 압축강도 기준을 만족하였다. 무시멘트 숏크리트 W/B 0.45 변수의 경우 초기강도가 가장 높게 나타났다. 28일 강도는 W/B 0.45 및 W/B 0.50 변수가 일반 숏크리트 대비 동등하거나 우수한 성능을 나타냈다.이러한 친환경 무시멘트 숏크리트 현장 적용을 위해서는 급 결제를 혼입한 배합에 대한 추가 검토가 필요할 것으로 판단되고, 또한 내구성능에 대한 추가적인 실험적 연구가 필요할 것으로 판단 된다.

이 연구는 라텍스 콘크리트(LMC)의 대체재로 해조류에서 추출한 알긴산을 활용한 콘크리트를 개발하고, 이에 따른 압축 강도 및 미 세구조 변화를 분석하였다. LMC는 공극 구조 개선으로 내구성과 강도가 향상되지만, 높은 원자재 비용이 단점이다. 이를 보완하기 위 해 라텍스 대신 알긴산을 혼합한 콘크리트를 제작하고, 주사전자현미경(SEM) 분석 및 압축 강도 실험을 수행하였다. 재령 4시간 및 1일 후의 압축 강도와 10000배율 SEM 분석을 진행하였다. 알긴산 0.05% 혼입 시 가장 높은 강도를 보였으며, 0.2% 혼 입 시 강도가 감소하였다. SEM 분석에서는 LMC가 균일한 표면과 미세한 입자 분포를 보인 반면, 알긴산 혼합 콘크리트는 섬유 및 막대 구조가 형성되었으며, 알긴산 함량이 증가할수록 기공이 증가하여 강도발현이 저하되었다. 재령이 증가하면서 C-S-H 구조가 조 밀해지고 결합력이 향상되어 강도가 증가하는 양상이 관찰되었다. 보다 정확한 결과를 얻기 위해서는 에너지 분산형 X선 분광법 (Energy Dispersive Spectroscopy, EDS)등 추가적인 실험이 필요할 것으로 사료된다.

Tunnel fires have significant social and economic impacts, causing extensive damage to concrete and steel reinforcements at high temperatures. Despite international advancements in fire-resistant designs, the safety measures for tunnel fires in South Korea remain insufficient. This study aimed to evaluate the fire resistance of fiber-reinforced concrete incorporating fire-resistant fibers with a focus on preventing spalling and enhancing structural safety. These findings are expected to contribute to the development of fire-resistant tunnel-design standards. Concrete mixtures with compressive strengths of 27 MPa were prepared according to highway construction material standards. Fiberreinforced concrete samples were produced with fire-resistant fiber dosages of 0.0, 0.6, 0.8, and 1.0 kg per cubic meter. Fresh concrete tests, including air content (KS F 2421) and slump (KS F 2402) tests, were conducted along with compressive strength tests (KS F 2405) on the hardened concrete. The fire resistance was assessed using an electric furnace to simulate the fire curve conditions specified in the Road Tunnel Fire Safety Guidelines based on KS F 2257. Increasing the fiber content led to a slight reduction in slump, likely owing to fiber agglomeration, with minimal effect on workability within the tested range. The air content exhibited negligible variation, indicating that there was no major impact on the air-void system. The compressive strength before the fire resistance test fluctuated but consistently met the design target of 27 MPa. The compressive strength after the fire resistance test across all samples decreased to approximately 2.0 MPa. The fiber-reinforced concrete exhibited reduced internal temperatures compared to the control, which was attributed to heat transfer disruption and the formation of micropores by the fibers. In this study, fiber-reinforced concrete demonstrated improved thermal resistance under fire conditions with minimal impact on the workability and air content within the tested range. Although the compressive strength before the fire resistance test remained adequate, the sharp decline in the post-fire strength highlights the need for further optimization. These findings emphasize the potential of fiber-reinforced concrete as a cost-effective solution for enhancing tunnel fire resistance, thereby supporting the development of safer and more resilient infrastructures.

The addition of fiber sto concrete matrix has been a norm to enhance the mechanical strength of concrete. However, the use ot synthetic fibers (artificial fibers) is rampant compared to natural fibers due to a low mechanical strength of some natural fibers. The study added cellulose fiber made from jute at 0.2%, 0.25, and 0.3% of cement weight to concrete matrix to determine their influence on the early strength development. It was observed that compressive strength and flexural strength increases as the proportion of fiber added to the concrete increased. Further observation showed that the compressive strength had its optimum point at 0.3% fiber addition. However, the optimum point of the flexural strength lied at 0.25% fiber addition. It was concluded that cellulose fiber is capable of enhancing the mechanical strengths of concrete matrix.

이 연구에서는 해양폐기물인 해조류에서 추출된 알긴산을 혼입하여 모르타르의 압축강도 특성을 분석하였다. 알긴산은 해양폐기물 중 해조류의 성분 중 하나로 라텍스와 비슷한 성분을 띄고 있으며, 방수성 성질이 있어 포장용 콘크리트에 활용 시 콘크리트의 수명 을 연장하고 파손 방지에 도움이 된다. 따라서 이 연구에서는 기존에 널리 사용되고 있는 라텍스 콘크리트에 알긴산을 혼입한 라텍스 콘크리트 개발의 일환으로 알긴산 혼입 라텍스 모르타르의 역학적 특성에 대한 실험적 연구를 수행하였다. 실험결과, 알긴산 혼입량 증가에 따른 응결은 빨라지는 경향을 나타내었으며, 압축강도는 저하하는 경향을 나타내었다.

도로터널의 연장과 대형화로 인해 화재 발생 시 터널 구조물의 안전확보가 중요한 과제가 되고 있다. 터널에서 화재가 발생할 경우, 콘크리트 라이닝이 고온에 노출되면서 강도저하 및 폭렬에 의한 구조적 손상을 초래할 수 있으며, 이를 방지하기 위해 다양한 내화공 법이 연구되고 있다. 이 연구에서는 폭렬을 억제하기 위한 내화공법으로 고온 노출에 따른 섬유혼입콘크리트의 온도전이 특성에 대한 실험적 연구를 수행하였다. 온도전이 특성 실험은 200×200×200mm 크기의 큐브 형태의 시험체에 0.6, 0.8, 1.0kg/m3의 섬유를 혼입하여 시험체를 제작하였다. 섬유혼입콘크리트 내부온도를 측정하기 위하여 표면에서부터 20mm 간격으로 100mm까지 총 6개의 K타입 열전 대를 설치하였고, 전기 내화로를 사용하여 RWS 화재곡선을 모사하여 시험체를 가열하였다. 실험결과, 섬유를 혼입한 콘크리트는 섬유 를 혼입하지 않은 Control 변수에 비해 내부온도가 낮아지는 경향을 보였다. 이는 고온에서 내화섬유가 용융되면서 콘크리트 내부의 수증기압을 감소시켜 효과적으로 억제된 것으로 보인다. 특히 내화섬유 0.8kg/m3을 혼입한 경우 60mm 이상에서 효과적으로 콘크리트 내부 온도 상승을 억제한 것으로 나타났으며, 폭렬에 의한 구조적 손상을 방지하기 위한 적정 수준의 내화섬유 혼입량은 필요할 것으 로 판단된다. 그러나 많은 양의 섬유 혼입은 고온에 따른 섬유 용융으로 인해 내부에 다량의 공극이 형성되어 폭렬 억제에는 효과적 일 수 있으나, 다량으로 형성된 공극에 따른 온도 확산이 더 빠르게 진행되어 적절한 피복두께 확보가 필요할 것으로 판단된다. 따라 서 도로터널 내화 지침(국토교통부, 2021)의 콘크리트(380℃) 및 철근(250℃)의 한계온도 이내를 만족하기 위해서는 피복두께는 최소 100mm 이상을 확보해야 할 것으로 판단된다. 이는 터널 구조물의 내화성능을 개선하기 위한 기준을 제시하며, 향후 도로터널의 안전 성을 강화하기 위해 섬유혼입량과 철근 피복두께 간의 상관관계에 대한 추가적인 실험 및 해석적 검토가 필요할 것으로 판단된다.

급격한 과학기술의 발전으로 미세먼지 배출량이 증가함에 따라 대기오염은 심각한 환경·사회 문제로 꾸준히 대두되고 있고, 이에 따 라 미세먼지 증가로 인한 질병 및 이상기후 증가로 인한 도로이동원에서의 교통사고 발생률 등의 문제점이 증가할 수 있다. 이를 해 결하기 위해 미세먼지 저감을 목적으로 건설분야에서 널리 사용되고 있는 광촉매 물질인 TiO2를 콘크리트의 광촉매 반응을 증가시키 고 광원의 효율적 이용을 위한 방안으로 투수콘크리트에 적용한 TiO2를 혼입한 투수콘크리트 포장 기술개발 기초 연구를 진행하였다. 실험결과, TiO2\혼입에 따른 투수콘크리트의 압축강도의 변화는 영향을 미치지 않는 미미한 수준으로 나타났다. TiO2를 혼입한 투수 콘크리트를 도로이동원에 적용하기 위해서는 동결융해 저항성 등 내구특성 및 미세먼지 저감 성능 등의 추가적인 실험이 필요할 것으 로 판단된다.

콘크리트 도로포장의 보강재로 사용된 철근은 염해나 중성화 등으로 인하여 지속적인 손상이 발생하고 있으며, 이에 따른 유지관리 비용의 증대가 사회적 관심으로 대두되고 있다. 이를 해결하기 위하여 건설분야에서는 철근보다 내부식성 및 내알칼리성이 뛰어난 유 리섬유강화폴리머(Glass Fiber Reinforced Polymer, GFRP)가 사용되고 있다. 하지만, 수분 및 염해 등의 환경에 대한 내구성 검증은 충분히 이루어지지 않고 있는 실정이다. 따라서, 이 연구에서는 국내외에서 생산하는 직경 22mm GFRP 보강근을 ASTM D570에 의 거하여 흡수율 품질기준을 평가하였다. 흡수율 실험결과, 국내에서 생산된 GFRP의 경우 가장 높은 0.15% 수준의 흡수율을 나타내었으며, 해외에서 생산된 GFRP의 경우 0.03% 이내 수준의 흡수율을 나타내었다. 이는 KCI-GFRP 101 : 2024 및 ASTM D7957에서 제시하고 있는 GFRP 보강근 흡수율 품 질기준은 0.25% 이하를 모두 만족하는 것으로 분석되었다. 철근대체제로써 활용을 위해서는 장기침지 및 특수한 환경 등에 대한 내구 특성에 대한 추가적인 실험적 검토가 필요할 것으로 판단된다.

The purpose of this study is to review the available literature on the effectiveness of fibers in preventing early-age shrinkage cracking on cementitious concrete. The overview describes the widely used ASTM C1579 (Standard Test Method for Evaluating Plastic Shrinkage Cracking of Restrained Fiber Reinforced Concrete (Using a Steel Form Insert) for plastic shrinkage cracking. The past literature used crack length, width, or area to describe and quantify cracks on concrete specimens. To keep things simple, this review expresses the length, width or area as a percentage of the control specimen. Finally, the study establishes a relationship between fiber volume and aspect ratio on plastic shrinkage and compressive strength of concrete. It was concluded that fiber is sufficient enough to mitigate plastic shrinkage cracking. An increase in fiber volume and aspect ratio reduces the early-age cracking of concrete but harm its compressive strength.

Membrane bioreactor (MBR) provides the benefits on high effluent quality and construction cost without the secondary clarification. Despite of these advantages, fouling, which clogs the pore in membrane modules, affects the membrane life span and effluent quality. Studies on the laboratory scale MBR were focused on the control of particulate fouling, organic fouling and inorganic fouling. However, less studies were focused on the control of biofouling and microbial aspect of membrane. In the full scale operation, most MBR produces high effluent quality to meet the national permit of discharge regulation. In this study, the performance and microbial community analysis were investigated in two MBRs. As the results, the performance of organic removal, nitrogen removal, and phosphorus removal was similar both MBRs. Microbial community analysis, however, showed that Azonexus sp. and Propionivibrio sp. contributed to indirect fouling to cause the chemical cleaning in the DX MBR.

PURPOSES : This study provides fundamental information on the temperature variations in tunnel structures during severe fire events. A fire event in a tunnel can drastically increase the internal temperature, which can significantly affect its structural safety. METHODS : Numerical simulations that consider various fire conditions are more efficient than experimental tests. The fire dynamic simulator (FDS) software, based on computational fluid dynamics (CFD) and developed by the National Institute of Standards and Technology, was used for the simulations. The variables included single and multiple accidents involving heavy goods vehicles carrying 27,000 liters of diesel fuel. Additionally, the concrete material characteristics of heat conductivity and specific heat were included in the analysis. The temperatures of concrete were investigated at various locations, surfaces, and inside the concrete at different depths. The obtained temperatures were verified to determine whether they reached the limits provided by the Fire Resistance Design for Road Tunnel (MOLIT 2021). RESULTS : For a fire caused by 27,000 liters of diesel, the fire intensity, expressed as the heat release rate, was approximately 160 MW. The increase in the carrying capacity of the fire source did not significantly affect the fire intensity; however, it affected the duration of the fire. The maximum temperature of concrete surface in the tunnel was approximately 1400 ℃ at some distance away in a longitudinal direction from the location of fire (not directly above). The temperature inside the concrete was successfully analyzed using FDS. The temperature inside the concrete decreased as the conductivity decreased and the specific heat increased. According to the Fire Resistance Design for Road Tunnel (MOLIT 2021), the internal temperatures should be within 380 ℃ and 250 ℃ for concrete and reinforcing steel, respectively. The temperatures were found to be approximately 380 ℃ and 100 ℃ in mist cases at depths of 5 cm and 10 cm, respectively, inside the concrete. CONCLUSIONS : The fire simulation studies indicated that the location of the maximum temperature was not directly above the fire, possibly because of fire-frame movements. During the final stage of the fire, the location of the highest temperature was immediately above the fire. During the fire in a tunnel with 27,000 liters of diesel, the maximum fire intensity was approximately 160 MW. The capacity of the fire source did not significantly affect the fire intensity, but affected the duration. Provided the concrete cover about 6 cm and 10 cm, both concrete and reinforcing steel can meet the required temperature limits of the Fire Resistance Design for Road Tunnel (MOLIT 2021). However, the results from this study are based on a few assumptions. Therefore, further studies should be conducted to include more specific numerical simulations and experimental tests that consider other variables, including tunnel shapes, fire sources, and locations.