In the context of large-scale energy storage applications, the triggering mechanisms for thermal runaway (TR) are highly diverse, with various TR triggering modes interrelated and the factors contributing to TR being extremely complex. However, there have been no reported studies on the coupling of different TR triggering modes. In this paper, based on three typical TR triggering modes: heating, overcharge, and external short circuit, we conducted a comparative study of TR and combustion characteristics under the following conditions: heating, overcharge, external short circuit, heating + overcharge, and heating + short circuit at different moments. The research results indicate that under the condition of heating + short circuit, the external short circuit increases the saturated vapor pressure of the electrolyte, shortens the valve opening time, and results in the highest peak heat release rate (HRR) increase of 28.26%. The coupling of heating and overcharge accelerates internal chemical reactions within the lithium-ion batteries (LIBs), leading to a maximum reduction of 21.01% in the initial temperature of thermal runaway (Tr). The total heat release (THR), and the peak temperature change rate (T') are positively correlated with TR state of charge (SOC) and combustion time. The presence of flames expedites the TR process, with the highest peak temperature increasing by 9.37%. Based on TR behavior and combustion characteristics, a risk and hazard evaluation method for TR and combustion is proposed using the Analytic Hierarchy Process (AHP). It is found that the coupling of different TR triggering modes increases the risk and hazard of TR and combustion, with heating + overcharge posing the greatest risk and hazard. The research findings can provide valuable guidance for the safety and prevention of energy storage LIBs.
The transient cooling process of an underground water pit thermal storage with inclined sidewalls is investigated in this paper. An experimental device was designed in order to validate the mathematical model proposed. Materials properties have been assumed constant with temperature, except for the water’s density that has been treated using the Boussinesq approximation. The simulations of temperature distributions are proved well by comparison with the experimental results. Results show that the water temperature decreasing next to the tank walls by the heat losses from the top and sidewalls of the tank, which creates a downward flow along the tank wall. At the center of the tank, a slight upward flow is generated, which lifts the warmer water at the bulk of the tank to a higher level. In this way, the buoyancy-driven flow gradually builds up the thermal stratification in the tank. The Nusselt number values show that comparing with the upper surface of the storage tank, there is more radical heat exchange at the bottom and inclined sidewalls. The maximum velocity appears near the top part of the inclined sidewalls, and its value decreases as the cooling continues.
Diesel traction Locomotives are widely used in railway tunnels in the plateau of China. Harmful gases given out by internal combustion engines must be excluded from the tunnel for human safety on railway. In the present study, nitrogen dioxide (NO 2 ) was taken into account as a representative harmful pollutant of the investigation object. Natural ventilation of diluting the concentration of NO 2 pollutant in the long railway tunnels was discussed according to real engineering on Lhasa-Rikaze line of China. One-dimensional unsteady flow models of tunnel ventilation were set up. The transient differential equations of the air velocity in the tunnel were solved by Runge-Kutta method and discrete convection-diffusion equations of scalar NO 2 concentration were discretized by controlling volume method and solved by first order upwind scheme. Cases with and without service gallery were discussed in terms of piston wind speed and elapsed time of diluting NO 2 concentration. Both positive and negative winds were considered. Based on the feasibility analysis of natural ventilation conditions, it is suggested that natural ventilation can settle for diluting harmful gases in tunnels with tunnel length less than 3 km on Lhasa-Rikaze line. Whereas the tunnel length is larger than 3 km, piecemeal natural ventilation with service gallery isn't recommended because it can't efficiently shorten the time of removing pollutants.
Abstract The activation of persulfates to degrade refractory organic pollutants is a hot issue in advanced oxidation right now. Here, it is reported that single‐atom Fe‐incorporated carbon nitride (Fe‐CN‐650) can effectively activate peroxymonosulfate (PMS) for sulfamethoxazole (SMX) removal. Through some characterization techniques and DFT calculation, it is proved that Fe single atoms in Fe‐CN‐650 exist mainly in the form of Fe‐N 3 O 1 coordination, and Fe‐N 3 O 1 exhibited better affinity for PMS than the traditional Fe‐N 4 structure. The degradation rate constant of SMX in the Fe‐CN‐650/PMS system reached 0.472 min −1 , and 90.80% of SMX can still be effectively degraded within 10 min after five consecutive recovery cycles. The radical quenching experiment and electrochemical analysis confirm that the pollutants are mainly degraded by two non‐radical pathways through 1 O 2 and Fe(IV)═O induced at the Fe‐N 3 O 1 sites. In addition, the intermediate products of SMX degradation in the Fe‐CN‐650/PMS system show toxicity attenuation or non‐toxicity. This study offers valuable insights into the design of carbon‐based single‐atom catalysts and provides a potential remediation technology for the optimum activation of PMS to disintegrate organic pollutants.
Speciation in nature is a fundamental process driving the formation of the vast microbial diversity on Earth. In the central Baltic Sea, the long-term stratification of water led to formation of a large-scale vertical redoxcline that provided a gradient of environmental niches with respect to the availability of electron acceptors and donors. The region was home to Shewanella baltica populations, which composed the dominant culturable nitrate-reducing bacteria, particularly in the oxic-anoxic transition zone. Using the collection of S. baltica isolates as a model system, genomic variations showed contrasting gene-sharing patterns within versus among S. baltica clades and revealed genomic signatures of S. baltica clades related to redox niche specialization as well as particle association. This study provides important insights into genomic mechanisms underlying bacterial speciation within this unique natural redoxcline.
The protozoan parasite Bonamia ostreae is a destructive pathogen of flat oysters and has been reported to be widespread in Europe and North America. The biological characteristics of this unicellular parasite are still not fully understood. In this study, 104 Ostrea edulis imported from the USA to the Guangdong province of China for consumption were examined for Bonamia infection. PCR assay, combined with restriction fragment length polymorphism, sequencing and BLAST analysis, showed that B. ostreae DNA could be detected in 1 of the 104 oyster samples. Light microscopy revealed Bonamia-like organisms in the oyster. PCR assay and fluorescent in situ hybridization showed that B. ostreae organisms were present and retained their integrity after 4 wk in culture. Acridine orange-ethidium bromide staining indicated that the B. ostreae were still alive. In conclusion, B. ostreae was present in oysters imported to China. More importantly, the parasite was able to survive for at least 4 wk of in vitro culture at 4°C, which further implied a long-term transmission risk of B. ostreae. Considering the wide culture beds of Crassostrea ariakensis and C. gigas in China, and that C. ariakensis and C. gigas are susceptible hosts or reservoirs of B. ostreae, our study highlights the potential risk of introducing B. ostreae by importing O. edulis from a Bonamia endemic area.
Currently, both manual and automatic evaluation technology can evaluate the translation quality of unreferenced English articles, playing a particular role in detecting translation results. Still, their deficiency is the lack of a close or noticeable relationship between evaluation time and evaluation theory. Thereupon, to realize the automatic Translation Quality Assessment (TQA) of unreferenced English articles, this paper proposes an automatic TQA model based on Sparse AutoEncoder (SAE) under the background of Deep Learning (DL). Meanwhile, the DL-based information extraction method employs AutoEncoder (AE) in the bilingual words’ unsupervised learning stage to reconstruct the translation language vector features. Then, it imports the translation information of unreferenced English articles into Bilingual words and optimizes the extraction effect of language vector features. Meantime, the translation language vector feature is introduced into the automatic DL-based TQA. The experimental findings corroborate that when the number of sentences increases, the number of actual translation errors and the evaluation scores of the proposed model increase, but the Bilingual Evaluation Understudy (BLEU) score is not significantly affected. When the number of sentences increases from 1,000 to 6,000, the BLEU increases from 96 to 98, which shows that the proposed model has good performance. Finally, the proposed model can realize the high-precision TQA of unreferenced English articles.
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