煤矿岗前人员不安全状态智能检测系统研究——以红柳林煤矿为例

为从根本上降低煤矿从业人员实施不安全行为的概率,在充分考虑煤矿从业人员不安全个体状态是诱发其不安全行为的主要原因的基础上,设计开发一套矿工不安全状态智能检测系统。首先,对2007—2022年期间各高危行业安全事故调查报告和专家研究进行归纳,总结得出煤矿从业人员不安全状态的影响因素,构建包括生理状态、心理状态以及个体能力状态在内的3个一级指标和15个二级指标体系;其次,通过相应的表征模型对不安全状态影响因素进行深入剖析;最后,基于构建的从业人员不安全状态倾向数据库,建立煤矿岗前不安全状态智能检测系统。研究结果表明：在下井工作前对从业人员个体状态进行智能检测,能够实现矿工不安全状态“早发现、早干预”,能够有效地降低人因事故发生率,研究结果对煤炭行业安全管理具有重要的参考价值。     

爆炸超压场景下危化品社会风险对允许规划人口密度的影响分析*

为研究危化品重大危险源基于社会风险基准的规划管控影响,采用我国标准规定的定量风险评价方法,TNT当量炸药简化方法,针对最大TNT当量炸药、事故发生总累计频率、人口密度分布控制参数等不同工况条件,对比分析国土开发强度的允许人口密度受社会风险约束影响的变化规律。研究结果表明:人口密度指数分布控制参数Nk与Nb的允许取值随最大TNT当量炸药和事故发生总累计频率降低而提高;确定工况下,允许总人口规模受最大TNT当量炸药影响很小;在最大TNT当量炸药大于100 t或事故发生总累计频率小于1×10-8次/a时可按最大事故场景进行规划控制分析。     

Cybersecurity and dynamic operation in practice: Equipment impacts and safety guarantees

Though dynamic operation of chemical processes has been extensively explored theoretically in contexts such as economic model predictive control or even considering the potential for cyberattacks on control systems creating non-standard operating policies, important practical questions remain regarding dynamic operation. In this work, we look at two of these with particular relevance to process safety: (1) evaluating dynamic operating policies with respect to process equipment fidelity and (2) evaluating procedures for determining the parameters of an advanced control law that can promote both dynamic operation as well as safety if appropriately designed. Regarding the first topic, we utilize computational fluid dynamics and finite element analysis simulations to analyze how cyberattacks on control systems could impact a metric for stress in equipment (maximum Von Mises stress) over time. Subsequently, we develop reduced-order models showing how both a process variable and maximum Von Mises stress vary over time in response to temperature variations at the boundary of the equipment, to use in evaluating how advanced control frameworks might impact and consider the stress. We close by investigating options for obtaining parameters of an economic model predictive control design that would need to meet a variety of theoretical requirements for safety guarantees to hold. This provides insights on practical safety aspects of control theory, and also indicates relationships between control and design from a safety perspective that highlight further relationships between design and control under dynamic operation to deepen perspectives from the computational fluid dynamics and finite element analysis discussions.     

Dynamic risk assessment for underground gas storage facilities based on Bayesian network

Loss of the underground gas storage process can have significant effects, and risk analysis is critical for maintaining the integrity of the underground gas storage process and reducing potential accidents. This paper focuses on the dynamic risk assessment method for the underground gas storage process. First, the underground gas storage process data is combined to create a database, and the fault tree of the underground gas storage facility is built by identifying the risk factors of the underground gas storage facility and mapping them into a Bayesian network. To eliminate the subjectivity in the process of determining the failure probability level of basic events, fuzzy numbers are introduced to determine the prior probability of the Bayesian network. Then, causal and diagnostic reasoning is performed on the Bayesian network to determine the failure level of the underground gas storage facilities. Based on the rate of change of prior and posterior probabilities, sensitivity and impact analysis are combined to determine the significant risk factors and possible failure paths. In addition, the time factor is introduced to build a dynamic Bayesian network to perform dynamic assessment and analysis of underground gas storage facilities. Finally, the dynamic risk assessment method is applied to underground gas storage facilities in depleted oil and gas reservoirs. A dynamic risk evaluation model for underground gas storage facilities is built to simulate and validate the dynamic risk evaluation method based on the Bayesian network. The results show that the proposed method has practical value for improving underground gas storage process safety.     

Effects of typical additives on the thermal stability of ammonium peroxydisulfate

Ammonium peroxydisulfate (APS), one of the most widely used inorganic peroxides in the process industries, is a thermally unstable peroxide and potent oxidizer due to the presence of peroxy bond in the molecule and is incompatible with most substances. To investigate the effect of typical additives on the thermal decomposition of APS, in this paper, diamine phosphate (DAP), monoamine phosphate (MAP), and aluminum hydroxide (AH) were selected as additives; pure APS and samples with 10 wt% and 20 wt% of additives were first tested by differential scanning calorimetry (DSC). The experiments and analysis showed that the samples with 10 wt% of additive had better thermal stability than those with 20 wt% of additive. After screening, the three groups of 10 wt% AH, 10 wt% MAP, and 20 wt% MAP additive conditions could be considered to have a better thermal stability effect on the thermal decomposition of APS. Four groups of samples were, in turn, tested by Phi-Tec II. The adiabatic results showed two discontinuous exothermic processes; 10 wt% AH promoted the weak exothermic effect in the first stage. In contrast, the three groups of additives in the main exothermic stage showed different degrees of inhibition, and the inhibiting effect was ranked as 10 wt% AH, 10 wt% MAP, and 20 wt% MAP in order. Finally, the self-accelerated decomposition temperature (SADT) was calculated under the 25 kg standard package. The adiabatic results, including SADT, were combined to render feasible recommendations for the use of additives, which provides references for the packaging and transportation of additives and their applications.     

A thermal hazard risk evaluation of emulsion polymerisation and vinyl acetate monomers in the latex manufacturing process

Latex is extensively used in industrial products. However, completing some processes at scale leads to unacceptable levels of risk that need to be quantified and mitigated. Systemic risks must be eliminated wherever possible, and safety takes priority over efficiency and quality. To assess the process risks accurately, four raw materials were examined in this study: polyvinyl acetate (PVA), latex process-initiator-ammonium persulfate (APS) and hydrogen peroxide (H₂O₂), and vinyl acetate monomer (VAM). The physicochemical composition of the PVA latex process was determined via calorimeters, including differential scanning calorimetry (DSC) and vent sizing package 2 (VSP2). The calorimetry results showed that the protective colloid was a critical component in the polymerisation reaction. In addition, when adding initiators to the system, it is vital to observe the normal ratio of materials and keep the stirring system operating. The scenario system also simulated the effects of shutting down various inhibitory programs, including the build-up of free radicals that could result in a runaway reaction when the initiator was added in excess. On the other hand, the result of the risk matrix displayed as a medium level, indicating that although the probability of an accident is low, the resulting severity is at disaster level. As a result, this study provides process safety engineers with a reliable frame of reference for assessing the potential dangers in the PVA latex manufacturing process.     

A bayesian network-based safety assessment method for solid propellant granule-casting molding process

The safety of the solid propellant molding process is vital for the stable production of high-quality propellants. Failure events caused by abnormal parameters in the molding process may have catastrophic consequences. In this paper, a Bayesian network (BN) model is proposed to assess the safety of the solid propellant granule-casting molding process. Fault tree analysis (FTA) is developed to construct a causal link between process variables and process failures. Subsequently, expert experience and fuzzy set theory (FST) are used to obtain failure probabilities of the basic events (BEs). Based on the mapping rules, FTA provides BN with reliable prior knowledge and a network structure with interpretability. Finally, when new evidence is obtained, the probability is updated with the diagnostic reasoning capability of BN. The results of the sensitivity analysis and diagnostic inference were combined to identify key parameters in the granule-casting molding process, including curing temperature, vacuum degree, extrusion, calendering roll distance, length setting value, holding time, and polish time. The results of this paper can provide effective supporting information for managers to conduct process safety analysis.     

Experimental investigation of the performance of modified expanded graphite powder doped with zinc borate in extinguishing sodium fires

Sodium is the main cooling medium in the circuit of fourth-generation nuclear reactors, and its leakage constitutes a severe fire hazard because of its high chemical activity. In this study, expandable graphite (EG), which is a traditional sodium fire-extinguishing agent, was modified with zinc borate (ZB) as an intercalator, and the modified EG_ZB was characterized. Moreover, the effectiveness of the modified EG_ZB in extinguishing sodium fires was tested using a self-developed fire-extinguishing experimental device. This study's results indicated that EG, EG_ZB had a smaller particle size, higher thermal stability, higher fire-extinguishing speed, and lower powder mass consumption than EG. During the fire-extinguishing process, ZnO decomposed by ZB captured free radicals and inhibited the combustion reaction. Furthermore, B₂O₃ was adsorbed on the surface of the EG layer, which strengthened covering and asphyxiation. The findings of this study provide crucial information for effectively controlling fires caused by active metals and metallo-organic compounds.     

Effect of particle size on CO adsorption and thermodynamic analysis

The liquid nitrogen adsorption method was used to characterize the pore structure of non-cohesive coal in the 061,404 working face of the Lingxin coal mine. The amount of specific surface area of micropores in the sample continuously rose as particle sizes reduced. The volumetric method was used to measure the CO isothermal adsorption curves of three samples (sample I, 0.425–0.25 mm, sample II, 0.18–0.25 mm, and sample III, 0.15–0.18 mm). The experimental results were fitted by the Langmuir model. According to the experimental results, it was conducive to CO adsorption with the conditions of high pressure and low-temperature. The decrease in grain diameter increased the number and volume of micropores in the sample, which improved the adsorption capacity of the sample. In addition, according to the adsorption data, the CO adsorption thermodynamics of three samples were analyzed, including surface potential (Ω), Gibbs free energy change (ΔG) and entropy change (ΔS). The results demonstrated that CO adsorption by coal was a spontaneous process. Sample III has the most substantial adsorption capacity, whereas the sample I has the weakest adsorption capacity.     

O3-BAC深度处理工艺中细菌群落时空分布及动态变化规律

为弄清饮用水O₃-BAC深度处理工艺过程中细菌群落的时空分布和动态变化规律,本研究以我国南方某O₃-BAC深度处理工艺水厂为研究对象,采用NovaSeq6000高通量测序技术对夏季和冬季各工艺单元出水及滤砂和活性炭生物膜等细菌群落进行解析.结果表明,出厂水pH、浊度、COD_Mn、菌落总数等指标均满足《生活饮用水卫生标准》(GB5749-2006)的要求.夏季细菌群落多样性明显高于冬季,活性炭生物膜的细菌群落多样性高于滤砂生物膜;混凝沉淀、臭氧化和消毒是影响细菌群落多样性的主要工艺单元.水样和生物膜样品绝对优势菌门均为变形菌门(Proteobacteria),且主要菌门组成大体相同,但细菌群落门水平相对丰度存在一定的时空差异,属水平上差异则更为明显.此外,检测到的条件致病菌属主要包括芽孢杆菌属(Bacillus)、不动杆菌属(Acinetobacter)、假单胞菌属(Pseudomonas)和分支杆菌属(Mycobacterium),且其所占核心微生物OTUs数目不受季节性影响.水温和生物可降解溶解性有机碳(BDOC)是显...