Application of a hydroxylamine nitrate stability model to plutonium purification process equipment

A mathematical model that predicts hydroxylamine nitrate (HAN) (NH₂OH·HNO₃) stability is applied to aqueous solutions containing HAN, nitric acid and plutonium that are used in plutonium purification processes. The model estimates the stability of these solutions with respect to the rapid, hazardous, autocatalytic reaction of HAN with nitric acid that generates heat and gas. It also accounts for reaction kinetics, temperature changes, gas generation rates, solution volumes and flow rates, and distribution of plutonium and nitric acid between aqueous and organic phases. The model is applied to three typical process vessels used in solvent extraction purification of plutonium – a countercurrent aqueous/organic plutonium stripping column, an oxidation column used for HAN and hydrazine destruction, and a plutonium rework tank. Both normal and off-normal process scenarios are modeled. Two of the off-normal scenarios lead to the rapid autocatalytic reaction of HAN with nitric acid where heat and gas are generated and that could lead to damage of the process equipment and/or release of hazardous plutonium solution from the vessel. In these two cases, stationary aqueous solutions containing HAN, Pu(III), and nitric acid were allowed to slowly react until conditions for the autocatalytic reaction were reached.     

一株产电菌嗜根考克氏菌(Kocuria rhizophila)的分离及其产电性能优化

本研究以天津泰达污水处理厂污泥浓缩间的污泥为接种物,启动并运行了微生物燃料电池(MFCs).从富集的阳极生物膜上分离得到了一株纯培养的微生物菌种,命名为P2-A-5.研究发现,菌株P2-A-5的16S rDNA序列与菌株Kocuria rhizophila DC2201具有100%的同源性,结合该菌的形态特征和生理生化实验,将其归属为嗜根考克氏菌(Kocuria rhizophila).通过化学剂处理、底物种类和浓度的优化,进一步提高其在微生物燃料电池中的产电性能.结果表明,菌株K.rhizophila P2-A-5经0.5 mg·L-1溶菌酶处理45 min后,接种到以2.0 g·L-1海藻糖为底物的阳极液中运行MFCs,其功率密度达到314.8 m W·m-2,比优化前(74.9 m W·m-2)提高了320.3%.这是首次对K.rhizophila种内微生物产电性能及其在微生物燃料电池中应用的报道,其成果对于丰富产电微生物的多样性,挖掘更多具有高电化学活性的微生物菌种,提高其产电性能具有重要的理论意义.     

阜新市空气监测点位优化的聚类分析

基于聚类分析法利用数据之间距离系数进行分类的原理,建立空气监测点位聚类分析优化模型,结合阜新市地形、气象及历史监测数据,进行阜新市空气监测点位布设优化应用,优化结果表明:距离相似水平取d=0.3时,环保局(B点)与人民公园(C点)监测点空气污染物浓度分布相似性最高,合并为1点,增设气象台监测点位作为清洁背景点,4个点位构成阜新市空气监测新网络;利用CALPUFF模型模拟对优化后监测点位进行相关性检验。检验结果表明:监测点位优化后SO2浓度与实测值相关系数为0.984,PM10相关系数为0.968,NO2相关系数为0.973。CALPUFF模型模拟值与实际监测值之间相关系数均大于0.75,表明优化后的阜新市空气监测点位具有客观环境代表性;监测点位优化与检验方法具有一定应用价值。     

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.     

A new pre-assessment model for failure-probability-based-planning by neural network

At present, the prediction of failure probability is based on the operation period for laid pipelines, and the method is complicated and time-consuming. If the failure probability can be predicted in the planning stage, the risk assessment system of gas pipeline will be greatly improved. In this paper, the pre-laying assessment model is established to minimize risk of leakage due to piping layout. Firstly, Fault Tree Analysis (FTA) modeling is carried out for urban natural gas pipeline network. According to expert evaluation, 84 failure factors, which can be determined in the planning stage, are selected as the input variables of the training network. Then the FTA model is used to calculate the theoretical failure probability value, and the failure probability prediction model is determined through repeated trial calculation based on BP (Back Propagation Neural Network) and RBF (Radial Basis Function), for obtaining the optimal network parameter combination. Finally, two prediction models are used to calculate the same example. By comparing our pre-assessment model with the theoretical prediction consequences of the fault tree, the results show that the error of RBF prediction model can be close to 3%, which proves the validity and correctness of the method.     

Multi-objective transportation route optimization for hazardous materials based on GIS

Safety and security are of paramount importance, it is important to optimize and improve the routes of trucks that carry hazardous materials. In this study, we not only ensure the risk in the network, but also consider the transportation cost and the factors such as buildings and emergency facilities around the routes. The Geographic Information System (GIS) is used to quantify the factors on each section in the network. We present an epsilon constrained multi-objective mixed-integer linear programming optimization model to find the robust and stable transportation optimization solutions. At the end, we complete a case analysis of the proposed methodology to determine the motorway segments in Jiangsu province, China and test the above algorithm on the network, which has 144 nodes and 388 sections. The results we get show that the factors of buildings play a very important role in the model, and the multi-objective mixed-integer linear optimization model is reasonable and performs good quality.     

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.     

山区农村居民点时空格局演变特征及蚁群仿真优化——以重庆澄江镇为例

山地农村居民点系统因受自然因素及人类活动等多重扰动而处于深刻转型中,探索山区农村居民点时空格局特征及其优化策略,对于优化山区国土空间格局、推进山区国土空间综合治理与乡村振兴具有重要意义。基于构建理论框架,集成运用景观格局指数法、栅格权重叠加评价法、改进蚁群算法（ACO）等,以重庆澄江镇为例,探索山区农村居民点时空格局演变特征及优化过程,提出优化调控策略。结果表明：（1）研究区农村居民点空间格局演变特征呈现集中、靠拢的演化发展趋势,总体呈现匀质、线状、向心、院落四种分布形态;同时高程、坡度、水域、城镇、道路、基础设施等自然—经济社会因素均对山区农村居民点时空格局演化产生重要影响。（2）改进蚁群算法优化后,研究区农村居民点斑块面积（CA）减少10.07%,居民点斑块数量（NP）和密度（PD）分别减少83.12%和81.16%,平均斑块面积（MPS）增加了4.3倍,平均最近邻体距离（MENN）增加了42.82%。优化后69.1%的农村居民点斑块都集中在适宜区和较适宜区内,且重点向交通便利、公共设施完善、生产便利和中心村庄集中。优化后的农村居民点空间格局更加紧凑有序,土地集约节约效率更高。（3）基于仿真优化结果,综合考虑村庄振兴“产业—人口—土地”互动耦合机制,提出城郊融合、产业集聚、景村融合、搬迁撤并四类农村居民点格局优化方案,助推山区乡村振兴。（4）优化结果同时表明改进的蚁群算法非常适用于复杂环境条件下的较小尺度要素空间布局优化,能够为山区国土空间规划编制提供技术支撑。     

碳中和趋势下数学模拟在污水处理系统中的发展与综合应用

数学模拟技术在污水处理方面被广泛应用,为了系统总结相关技术,本文回顾了污水处理系统中数学模拟技术的发展历程;综述了活性污泥模型(ASM)与机器学习(ML)在水质预测及参数工况优化领域中的应用;重点探究了污水处理系统中温室气体排放模型,以及多目标优化模型在污水处理系统中温室气体排放(GHG)、出水质量(EQI)和运行成本(OCI)的权衡问题;归纳了数学模拟技术在实现污水厂能量自给与资源回收的应用发展.研究结果表明数学模拟技术能准确预测出水水质、快速优化工艺参数、权衡温室气体排放、出水水质与运行成本之间的关系、以及提高资源回收效率等.因此,数值模拟技术可有效指导污水处理工艺的运行优化以及管理,为污水处理行业减污降碳协同增效提供技术支撑.     

浅谈秦皇岛外语语言软环境的优化策略

秦皇岛作为著名的沿海旅游城市,外语语言环境作为旅游软环境的一个重要因素直接影响着整个旅游产业的综合竞争力。鉴于此,对秦皇岛市外语语言软环境进行调查摸底。调查结果表明,旅游景区标示语及城市公示语的翻译存在不同程度的问题,旅游从业人员总体素质不高,市民的外语能力普遍偏低。以调查结果为依托,从政府导向、行业把关、全民参与三方面提出了优化秦皇岛市旅游业外语语言软环境的建议。