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Robust calorimetric data for highly exothermic organolithium reactions are obtained within a modular 3D printed continuous flow calorimeter.

An exothermic reaction in a semibatch reactor can potentially cause thermal runaway due to evolved energy accumulation or a secondary reaction. This research aims to propose safety criteria for solid-liquid reactions in semibatch reactors. Simulation modeling was carried out to build thermal runaway criteria for solid-liquid reactions in semibatch reactors. A new model for the energy and mass balance of solid-liquid reactions was successfully established. Criteria for the safety boundary diagram and the temperature diagram were ameliorated for solid-liquid reactions. The results showed that the dissolution heat has a great influence on the thermal behavior of the reaction. Experiments to neutralize citric acid and sodium hydroxide were carried out to determine the critical parameters for the neutralization reaction using the temperature diagram criterion. The proposed criteria would be reasonably expected to provide some guidance for chemical process optimization and safety design for engineering.

The emergency response process will not start immediately in the initial stage of a subway accident, and information will not fully spread temporarily. Crowds in different regions receive different comprehensiveness of accident information. They will start evacuating at different times and at different desired speed states. Depending on this phenomenon, pedestrians were classified in simulation modeling. In addition, the different states of emergency gates, escalators, and automatic gate machines before and after the emergency response instruction were set up in the simulation. The impact of different emergency response times on evacuations was studied. The emergency response in advance did not make a significant promotion to evacuation efficiency, but delayed emergency response reduced it greatly. This work proposed an evacuation risk index (ERI) and maximum safe evacuation capacity in metro stations. The worst accident evacuation scenario can be obtained by calculating the ERI, and a metro station was evaluated as a case study. The comparison of the evaluation results of ERI and other methods shows that the conclusion is consistent, but ERI considers the accident location factor.

In this paper, highly flame retardant C60/PMMA composites were prepared using an in situ polymerization method by introducing fullerene (C60) into polymethyl methacrylate (PMMA) to improve its combustion characteristics.

Due to the complex effects of combined loadings on complete steel structures, the combined effects of high-velocity projectile impact and heat radiation due to a pool-fire on a vertical Q345 steel tank have not been generally considered. In this study, a consecutive coupling approach is established. The combined effects of projectile perforation and heat radiation on the failure modes and fire resistance of a vertical steel tank are investigated. Additionally, the effects of the projectile size, projectile shape, and separation distance are analyzed. The results indicate that compared with a fixed-roof tank without impact, the perforation results in stress concentrations in the plastic deformation zone. The stress level of the perforated tank is higher, and the fire resistance of the perforated tank is lower. Additionally, as the perforation size increases, the stress level triggering the thermal buckling of the perforated tank decreases outside of the plastic deformation zone. Additionally, the fire resistance decreases. Moreover, as the separation distance decreases, the stress level of the cylindrical shell increases. The fire resistance of the perforated tank decreases dramatically. By understanding the failure mode, this study is able to suggest fire and explosion protection measures in petrochemical industries to decrease or eliminate the domino effect risk and incident damage. Additionally, the fire resistance data can help improve guidelines and understanding for fire and rescue services, which would undoubtedly play a vital part in emergency response and rescue, and enhance the process safety level overall.

Knowledge of flammability limits values, including both the lower flammability limit (LFL) and upper flammability limit (UFL), is essential to maximise safety in process design and operational procedures. This study aims to develop theoretical models for predicting both lower and upper flammability limits for fuel mixtures from molecular structures with the same molecular descriptors. All samples were collected from a single reference and the “compounds out” strategy was employed to divide the training and the test set. Descriptors for pure compounds were calculated by Gaussian 16 and Multiwfn package. The developed LFL and UFL models were validated with rigorous internal and external validations. The results indicated the robustness, validity, and satisfactory predictivity of the established models. The applicability domain (AD) of the model was also defined. The established LFL and UFL models demonstrated that the higher dipole moment and van der Waals volume are, the higher LFL and lower UFL values are. The proposed models can be expected to predict the LFL and UFL values for other fuel mixtures for which experiment values are unknown, only based on molecular structures.

Energetic materials (EMs) are the core materials of weapons and equipment. Achieving precise molecular design and efficient green synthesis of EMs has long been one of the primary concerns of researchers around the world. Traditionally, advanced materials were discovered through a trial-and-error processes, which required long research and development (R&D) cycles and high costs. In recent years, the machine learning (ML) method has matured into a tool that compliments and aids experimental studies for predicting and designing advanced EMs. This paper reviews the critical process of ML methods to discover and predict EMs, including data preparation, feature extraction, model construction, and model performance evaluation. The main ideas and basic steps of applying ML methods are analyzed and outlined. The state-of-the-art research about ML applications in property prediction and inverse material design of EMs is further summarized. Finally, the existing challenges and the strategies for coping with challenges in the further applications of the ML methods are proposed.

To improve the properties of Zr powder for specific applications in aerospace and military fields, Zr powders were coated with ferrite nanoparticles, namely FeOOH, Fe2O3, and Fe3O4. An instantaneous flame propagation system and scanning electron microscopy, X-ray diffraction, thermogravimetry, and differential scanning calorimetry techniques was used to characterized the flame propagation characteristics, micromorphology, phase composition, crystal structure, thermal stability, and reactivity of the three types of nano ferrite-coated Zr particles. The results showed that, the flame propagation velocity and maximal temperature exhibited the following order: Fe2O3-coated > FeOOH-coated > Fe3O4-coated Zr dust cloud. With an increase in the proportion of coating materials, the combustion characteristics all decreased. The contrastive analysis of surface, ingredient and heating process revealed that, during combustion, in addition to inducing oxidation–reduction, inner Zr led to a replacement reaction with the outside ferrite coating layer, and then, Fe generated was oxidized at a high temperature.

Adiabatic calorimeters (ARCs) are critical in thermal analysis and thermal hazard assessment. As testing equipment continually improves, analyzing changes in physical fields in sample pools during thermal decomposition reactions is increasingly essential. Therefore, this study analyzed the thermal decomposition of tert-butyl peroxyacetate (TBPA). On the basis of the computational fluid dynamics (CFD) numerical simulation method and the kinetic model of TBPA thermal decomposition, a full-scale model of an adiabatic reactor for the thermal decomposition of TBPA was constructed. The temperature rise curve obtained after monitoring the temperature of the system during thermal decomposition was compared with that obtained during the experiment; thus, the rationality of the CFD model was verified. Accordingly, the temperature field, temperature rate, and velocity field in the reactor were analyzed. The temperature distribution of the system was relatively uniform during thermal decomposition under completely adiabatic conditions, resulting in an effectively nonexistent temperature gradient. At the same time, the self-heat rate (dT/dt) of the system in the process of thermal decomposition was analyzed. It was found that self-heat rate (dT/dt) of the system in the full sensing state was much larger than that in the experimental process, maximum self-heat rate ((dT/dt)max) reaching 15℃/min, while in the experimental process was only 1.074℃/min.