桥梁施工过程的布拉格光纤光栅安全监测技术

为了安全可靠地建好每座大跨桥梁,就要对每座桥的施工过程进行安全监测,传统的安全监测方法是采用电测技术,由于抗电磁干扰性差等原因,测试的数据真实性差。笔者在布拉格光纤光栅的传感原理、室内悬臂梁试验和埋设工艺的研究基础上,成功地在黑大公路牛头山大桥上布设了布拉格光纤光栅应变传感器,为对比布拉格光纤光栅的监测结果,埋设了应变砖测试混凝土的应变,监测了该桥预应力混凝土连续梁先简支后连续施工的全过程,施工监测结果表明:布拉格光纤光栅监测大桥施工结果准确、稳定和可靠,同时证明该光纤光栅测试技术可以用于桥梁施工过程的安全监测且结果明显好于传统的电测技术。     

两相厌氧工艺的研究进展

为了了解两相厌氧工艺的研究状况,对两相厌氧反应器及相分离方法进行了综述,并指出了今后两相厌氧工艺的研究方向.     

倍福Profibus现场总线端子模块在炼钢电炉除尘系统中的应用

通过90 t炼钢电炉除尘工程控制系统的具体的工程项目实例,简略介绍了倍福(Beckhoff)现场总线端子模块及其在工程项目中的应用.     

A/DAT-IAT生物膜法处理高含盐废水

以含盐量为60 000mg/L(以NaCl计)的模拟工业废水为研究对象,利用A/DAT-IAT生物膜反应器,研究A/DAT-IAT工艺对投加悬浮填料后高含盐废水的处理,并以CODCr、NH4 -N、PO43--P等作为指标评价处理效果.试验结果表明,在总水力停留时间(HRT)为13 h、pH=7,5、25℃条件下,进水ρ(CODCr)、ρ(NH4 -N)和ρ(PO43--P)分别为907.4～1 210.0 mg/L、86.2～99.7 mg/L和3.6～5.1 mg/L.CODCr、NH4 -N和PO43--P的平均去除率分别为73.9%、38.6%和93.5%,平均出水SS为198 mg/L,其中CODCr和PO43--P的去除效果较好.研究表明,A/DAT-IAT生物膜法较其他活性污泥法有了较大的提高.     

生物燃气制气供气装置选型计算

根据生物质热解及其干燥所需能量计算,选择一种生物质燃气制气供气装置作为生物燃油生产过程中用于生物质干燥和热载体加热的能量来源,对降低生物燃油规模化生产能耗和生产成本具有重要的研究实践价值和经济意义.     

再生铜冶炼过程中重金属排放特征和控制

再生铜冶炼是重要的重金属排放源,为掌握再生铜冶炼过程中重金属的排放特征和控制效果,通过固定源等速采样装置采集不同冶炼阶段的烟气样品,利用电感耦合等离子体质谱仪测定烟气和飞灰中重金属的浓度,并估算重金属的排放因子.结果表明,在冷却阶段烟气中重金属和颗粒物的浓度较高,经过布袋除尘器和吸附塔等污染控制装置后,重金属和颗粒物被协同脱除,脱除效率达80%～99%.排放烟气中重金属的浓度在阳极炉不同工艺段中的排序为：加料熔融段>氧化段≈还原段,且As、 Pb、 Cr、 Sn、 Sb和Cd的平均排放因子分别为2.6×10³、2.4×10³、2.7×10³、5.6×10²、34.1和9.8 mg·t^-1,烟气中重金属和颗粒物的浓度均满足行业排放标准.飞灰中Cu和Zn的浓度较高,具有回收利用价值.     

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.