Nuclear Energy Agency

Truck-involved accidents often result in severe consequences due to the vehicle's size and mass, making driver fatigue and cognitive overload critical risk factors.Mental workload reflects real-time cognitive demands during driving, where excessive levels accelerate fatigue, impair response time, and increase accident risk.This research investigates the effects of four driving scenarios (rural daytime, rural nighttime, urban daytime, urban nighttime) on the mental workload of 50 professional male truck drivers, using NASA Task Load Index (NASA-TLX) assessment and Heart Rate Variability (HRV) metrics (aLF, aHF, ln-aLF, ln-aHF, nLF, nHF, and HR in bpm).Performance was measured through response time, hit rate, and error rate.The NASA-TLX results indicate a proportional increase in mental workload from rural daytime to urban nighttime.Mental Demand (p = 0.025) and Temporal Demand (p = 0.047) are significantly higher in urban nighttime compared to rural daytime, while other dimensions, though not significant, show a general pattern of increasing mean scores, with Performance showing the opposite pattern.Heart rate (bpm) significantly increases, and nLF power shows a significant reduction during urban nighttime scenario compared to rural daytime (p < 0.03), indicating increased mental workload.Two-way ANOVA further revealed that road condition (urban vs. rural) significantly affected HRV indices (nLF, nHF, and HR), while driving time (nighttime vs. daytime) significantly elevated Mental Demand and Frustration, highlighting the distinct contribution of environmental and temporal factors to driver workload.Significantly, response times were slowest in rural nighttime scenarios, hit rates were higher at night than during the day, and error rate peaked in urban nighttime driving, suggesting that reduced visibility and traffic density contribute to increased mental workload.These findings provide a more structured and advanced methods for measuring truck drivers' mental workload, benefiting company management in optimizing driver performance and safety.

The demand for energy-efficient construction in agriculture calls for a reassessment of materials used in livestock buildings. This study evaluated the use of timber as an alternative to traditional materials, with a focus on embodied energy (EE) and carbon footprint (CFP) Eight EU countries (Germany, Poland, Spain, Italy, Denmark, France, Sweden, and Finland), were analyzed considering both forest resources and livestock populations. The forest area varied from more than 310,000 km2 in Sweden to just 6464 km2 in Denmark. Meanwhile, livestock populations varied significantly, with Germany reporting over 8.2 million LSU (livestock unit, 500 kg) in cattle alone. The number of livestock buildings was estimated assuming 100 LSU per building, allowing for a comparison between timber and conventional designs. Timber-based cowsheds were found to lower embodied carbon by up to 10,433 kg CO2e per barn compared with 17,450 kg CO2e for conventional structures. Embodied energy for a single wooden cowshed was around 151 GJ versus more than 246 GJ for a traditional counterpart. Scaled up to the national level, this represents a 35–40% reduction in total embodied energy. In addition to environmental outcomes, the analysis considered economic, technical, and regulatory aspects influencing adoption. The results suggest that substituting conventional materials with timber can contribute to emission reductions in agricultural construction, while further research is needed on fire safety, prefabrication, and policy harmonizations.

The development of small modular reactors (SMRs) at Pantai Gosong, Indonesia, requires careful attention to personnel health and safety, especially during the construction stage. The geological conditions at Pantai Gosong pose significant challenges, as unstable sandstone and igneous rocks necessitate specialized techniques to avoid increasing occupational health and safety (OHS) risks. To address these challenges, effective OHS risk management is crucial, requiring the creation of a modeling framework to identify, analyze, and control potential risks during construction. This study adopts a mixed-methods approach, following the Hazard Identification Risk Assessment and Determining Control method and international standards. It combines the quantitative analysis of risk probabilities and incident frequencies with qualitative methods, including field observations and expert interviews. Key risk analysis encompasses hazard identification, risk probability assessment, and consequence analysis. The findings identified significant potential hazards, primarily crane accidents caused by structural failure factors and transportation accidents caused by dock structural failure (foundation) or corrosion. The proposed model aims to enhance safety standards and support the sustainable deployment of SMRs in Indonesia.

An analysis of a target system on a small-scale electron accelerator-driven system (e-ADS) for experimental purposes has been conducted. The methodology employed includes particle transport simulations using the Particle and Heavy Ion Transport System (PHITS) code and Response Surface Methodology (RSM) analysis performed with Minitab software. The independent variables reviewed are the energy and radius of the electron beam, as well as the thickness and radius of both the pitcher and the catcher. The dependent variable observed is the neutron yield. Tungsten is used as the pitcher material, while the catcher material is varied among iridium, platinum, tungsten, uranium, thorium, and lead. The RSM analysis indicates that the most optimal target system configuration is tungsten-tungsten, with a pitcher thickness and radius of 1.7 and 3.4 cm, respectively, and a catcher thickness and radius of 1.0 and 2.7 cm, respectively. To achieve the desired neutron output, the required beam parameters are a radius of 0.4071 cm, a current of 1 µA, and an electron energy of 100 MeV, respectively. This configuration produces a neutron yield of 5.764 × 1011 n/s, with a simulation deviation of 0.85%, which is considered acceptable for experimental purposes.