Hasil untuk "Fuel"

Q. Nguyen, 高橋 武彦

V. Neburchilov, Jonathan Martin, Haijiang Wang et al.

Wolfgang Schmittinger, A. Vahidi

D. Fullerton, N. Bruce, S. Gordon

Summary One-third of the world's population burn organic material such as wood, dung or charcoal (biomass fuel) for cooking, heating and lighting. This form of energy usage is associated with high levels of indoor air pollution and an increase in the incidence of respiratory infections, including pneumonia, tuberculosis and chronic obstructive pulmonary disease, low birthweight, cataracts, cardiovascular events and all-cause mortality both in adults and children. The mechanisms behind these associations are not fully understood. This review summarises the available information on biomass fuel use and health, highlighting the current gaps in knowledge.

A. Burke

N. Minh

K. Ahn, Hesham A Rakha, A. Trani et al.

S. McIntosh, R. Gorte

Peter Clauwaert, K. Rabaey, P. Aelterman et al.

A. Murugesan, C. Umarani, R. Subramanian et al.

Sandys J. Thomas

G. Scheffknecht, Leema A. Al-Makhadmeh, U. Schnell et al.

J. Janaun, N. Ellis

Shengsheng Zhang, Xiao‐Zi Yuan, J. N. C. Hin et al.

Xingcai Lu, D. Han, Zhen Huang

R. Williamson, J. Hales, S. Novascone et al.

Jingyi Li, Minghui Guo, Ju Wang et al.

Self-propelled liquid metal-aluminum hybrid machines represent a promising class of autonomous motion systems capable of sustained movement without external power sources. While interactions between machines and their environment inevitably occur, the fundamental question of how spatial confinement affects the motion dynamics and the controllability of speed, direction, and lifetime of such liquid metal machines (LMMs) remains underexplored. Understanding these confined dynamics is essential for practical applications. Here, we present a comprehensive investigation of the non-symmetrical fueling principle governing the direction-tuning effect in LMMs. By confining LMMs within one-dimensional semi-open channels, we thoroughly disclose their impact and turning dynamics with different end obstacles throughout their lifecycle, with particular focus on fuel region morphological evolution, overall motion, and local flow characteristics after reaction times exceeding one hour. Utilizing ultra-high-speed imaging techniques, we systematically clarify how fuel region evolution and end-obstacle interactions influence symmetry-breaking mechanisms and reciprocating dynamics. Our findings reveal complex interactions between material properties, charge transfer processes, and fluid dynamics during end-turning processes, establishing a theoretical foundation for LMM driving dynamics. Beyond the theoretical mechanisms, we further demonstrate that LMM exhibits efficient heat and mass transfer capabilities, paving the way for applications in controlled transport systems and autonomous robotics.

Monica Ferraris, Stefano De la Pierre, Valentina Casalegno et al.

Silicon carbide fiber-reinforced composites (SiC/SiC) are leading candidates to replace zirconium-based alloys as cladding in light water reactors (LWR), owing to their exceptional oxidation resistance and mechanical performance under accident conditions.However, pressure-less joining methods compatible with the extreme chemical and thermal environment of LWRs remain a major technological hurdle.This work evaluates two promising joining materials—Mo-wrap (a MoSi₂/Si composite) and SAY (a silica–alumina–yttria glass-ceramic)—under simulated LWR conditions.Joining was performed using both conventional furnaces and laser-assisted techniques.Joint integrity and microstructure were assessed by SEM/EDS and X-ray computed tomography. Hydrothermal stability was evaluated in static and flowing-water (loop) autoclaves up to 30 days at 330 °C and 150–155 bar.Mo-wrap joints showed partial degradation due to silicon dissolution, while SAY joints retained good structural integrity in static tests but suffered phase-selective corrosion under flowing conditions, with keivite emerging as the most stable crystalline phase.Laser-processed amorphous SAY joints exhibited improved corrosion resistance, though still limited under prolonged exposure.These findings advance the understanding of joining performance in nuclear-relevant environments and support the development of accident-tolerant fuel cladding.

Mohammad Ful Hossain Seikh, Victor Grachev, Ilya Kravchenko et al.

We summarize the motivation for (as well as the presentations from) the April, 2024 workshop held in India and focused on radiowave techniques for cosmic ray and neutrino detection.

Wafeeq Jaleel, Md Ragib Rownak, Athar Hanif et al.

As hybrid electric vehicles (HEVs) gain traction in heavy-duty trucks, adaptive and efficient energy management is critical for reducing fuel consumption while maintaining battery charge for long operation times. We present a new reinforcement learning (RL) framework based on the Soft Actor-Critic (SAC) algorithm to optimize engine control in series HEVs. We reformulate the control task as a sequential decision-making problem and enhance SAC by incorporating Gated Recurrent Units (GRUs) and Decision Transformers (DTs) into both actor and critic networks to capture temporal dependencies and improve planning over time. To evaluate robustness and generalization, we train the models under diverse initial battery states, drive cycle durations, power demands, and input sequence lengths. Experiments show that the SAC agent with a DT-based actor and GRU-based critic was within 1.8% of Dynamic Programming (DP) in fuel savings on the Highway Fuel Economy Test (HFET) cycle, while the SAC agent with GRUs in both actor and critic networks, and FFN actor-critic agent were within 3.16% and 3.43%, respectively. On unseen drive cycles (US06 and Heavy Heavy-Duty Diesel Truck (HHDDT) cruise segment), generalized sequence-aware agents consistently outperformed feedforward network (FFN)-based agents, highlighting their adaptability and robustness in real-world settings.