基于多主体行为决策的城市居住用地利用效用情景分析

构建包含智能主体和环境主体的城市居住空间演化情景模型,旨在探讨土地利用主体的行为决策与居住空间演化形态和土地利用效用之间的关系。调整城市政府主体的土地利用政策设定紧凑型、松散型和适度型三种居住空间演化情景类型,通过综合分析城市居民、住宅开发商和城市政府三类微观主体的相互作用求取每种情景下住宅用地开发的综合优先级函数。在VC和ArcGIS的实验环境下,以武汉市洪山和武昌区为实验区模拟了三种规定情景下实验区在1998年至2008年期间的居住空间演化情况,并与实际演化情况进行扩张形态和土地利用社会效用的概略对比,对比结果表明,多主体模型能有效比对不同主体空间决策情景下土地利用的效用,在表现土地利用主体的意愿方面更有优势,更能反映城市土地利用结构演变的内在规律。     

Prediction of methanol loss in liquid hydrocarbon phase during natural gas hydrate inhibition using rigorous models

Methanol is the most widely used natural gas hydrate inhibitor and it is only effective as a hydrate inhibitor in the aqueous phase. Methanol is not regenerated in natural gas inhibition process due to its intermittent application in most cases. However, a significant cost is associated with the process because of methanol loss while utilizing this inhibitor. In this work, several intelligent models along with a new mathematical correlation are presented in terms of methanol concentration in aqueous phase and temperature to precisely forecast the methanol loss in the saturated hydrocarbons phase. An excellent match was noticed between the calculated results and literature data.     

鄱阳湖发展演变及江湖关系变化影响

鄱阳湖为长江流域最大的通江湖泊,江湖关系独特.现代鄱阳湖的形成及其演变是多种因素长期综合作用与发展的结果,且经历了几个不同的阶段.各种影响因素在鄱阳湖演变的不同阶段所发挥的作用也不尽相同.自然因素的影响过程较为缓慢,而人为因素的作用则较为明显,也更为直接.随着湖区人类社会经济的发展,人类对鄱阳湖的依存大大凸显其生态系统的重要性、脆弱性和敏感性.这必将对湖泊的演化,尤其是对冲积平原浅水湖泊的演变发挥决定性作用.特别是近年来面临着江湖关系、河湖关系和人湖关系的改变所带来的重大影响,未来鄱阳湖的发展和演变存在诸多变数和不确定性,面临着许多挑战.科学认识和预测江湖关系变化趋势及其对鄱阳湖的影响,并提出应对鄱阳湖演变与发展对策,对保障鄱阳湖生态安全尤为重要和迫切.     

Detection of incipient self-ignition process in solid fuels through gas emissions methodology

The aim of this study is to propose an experimental methodology to detect incipient self-ignition processes in solid fuels. This methodology is based on the gases emissions of different solid fuels, varying the degree of compaction and the grain size of the materials. To achieve this goal, a procedure for the collection and analysis of the gases emitted by samples of various fuels has been developed, analysing the temperatures at which these emissions begin. The results obtained for different materials show that it is possible to detect incipient spontaneous combustion processes using measurements of CO and CO₂ emissions during heating process, and then to set alarm thresholds based on the concentrations of these gases. Those results have been compared with results from conventional thermogravimetry and differential scanning calorimetry tests and it is shown that the proposed methodology detect the self-ignition process start point in advance.     

Lower explosion limit of hybrid mixtures of burnable gas and dust

Hybrid mixtures – mixtures of burnable dusts and burnable gases – pose special problems to industries, as their combined Lower Explosion Limit (LEL) can lie below the LEL of the single substances. Different mathematical relations have been proposed by various authors in literature to predict the Lower Explosion Limit of hybrid mixtures (LEL_hybrid). The aim of this work is to prove the validity or limitations of these formulas for various combinations of dusts and gases. The experiments were executed in a standard 20 L vessel apparatus used for dust explosion testing. Permanent spark with an ignition energy of 10 J was used as ignition source. The results obtained so far show that, there are some combinations of dust and gas where the proposed mathematical formulas to predict the lower explosible limits of hybrid mixtures are not safe enough.     

Analysis of dust distribution in silo during axial filling using computational fluid dynamics: Assessment on dust explosion likelihood

In this study, the dust distribution in a silo during axial filling was modelled using a commercial computational fluid dynamics (CFD) code. The work focused on the dust concentration distribution in the silo, for evaluating the likelihood of a dust explosion in the silo. The simulation was conducted using a combination of renormalized (RNG) k-epsilon and discrete phase models, with standard pressure interpolation and a second order upwind scheme. The predicted dust concentration distribution showed a good agreement with experimental data adopted from the literature. It was found that the dust concentration distribution was influenced by mean velocity and turbulence flow. The simulation results suggest that the cornstarch concentration inside the silo was always above the lower explosion limit (LEL), hence requiring a mitigating action or a control system to reduce the explosion risk.     

Dynamic response characteristics and structural optimization of isolation seal under the impact of gas explosion

Either in the chemical process plants or in the underground infrastructures, the isolation seal is regularly used to separate the working sections and inactive sections, or to isolate the possible explosion sites in order to avoid any domino effects. Due to differences in accumulation space or ignition point locations, pressure on the seal can vary when an explosion occurs. Thus, the safety and reliability of seals are crucial to maintaining safety in process industry. This paper focuses on seals constructed with concrete and loess materials, and examines the dynamic response characteristics of the gas explosion wave on the seal through sample experiments and numerical simulation metods. The study proposes an optimized design for the explosion-proof structure of the wedge-shaped and spherical seal, which can provide a technical basis for the explosion-proof and anti-explosion measures of various sealed walls. These research findings can also serve as a basis for improving the construction quality of seals.     

Prediction of gas explosion pressures: A machine learning algorithm based on KPCA and an optimized LSSVM

A gas explosion, as a common accident in public life and industry, poses a great threat to the safety of life and property. The determination and prediction of gas explosion pressures are greatly important for safety issues and emergency rescue after an accident occurs. Compared with traditional empirical and numerical models, machine learning models are definitely a superior approach. However, the application of machine learning in gas explosion pressure prediction has not reached its full potential. In this study, a hybrid gas explosion pressure prediction model based on kernel principal component analysis (KPCA), a least square support vector machine (LSSVM), and a gray wolf optimization (GWO) algorithm is proposed. A dataset consisting of 12 influencing factors of gas explosion pressures and 317 groups of data is constructed for developing and evaluating the KPCA-GWO-LSSVM model. The results show that the correlations among the 12 influencing factors are eliminated and dimensioned down by the KPCA method, and 5 composite indicators are obtained. The proposed KPCA-GWO-LSSVM hybrid model performs well in predicting gas explosion pressures, with coefficient of determination (R²), root mean square error (RMSE), and mean absolute error (MAE) values of 0.928, 26.234, and 12.494, respectively, for the training set; and 0.826, 25.951, and 13.964, respectively, for the test set. The proposed model outperforms the LSSVM, GWO-LSSVM, KPCA-LSSVM, beetle antennae search improved BP neural network (BAS-BPNN) models and reported empirical models. In addition, the sensitivity of influencing factors to the model is evaluated based on the constructed database, and the geometric parameters X1 and X2 of the confined structure are the most critical variables for gas explosion pressure prediction. The findings of this study can help expand the application of machine learning in gas explosion prediction and can truly benefit the treatment of gas explosion accidents.     

原油储罐火灾事故环境风险评价分析

通过运用ADMS模型,对2万m3原油储罐发生火灾爆炸事故时有毒有害气体及燃烧次生污染物的环境影响进行预测。结果表明,其产生的废气污染物对环境影响较大;在火灾持续6h的情况下,产生的主要废气污染物在距离事故中心120m范围内的人员将有半数死亡;距120～240m范围内造成组织缺氧;距240～4725m人员不会有生命危险;距离4725m范围内污染物的浓度超出车间最高允许浓度要求。同时提出了相应的环境风险管理措施,为今后类似事故环境影响评价作借鉴,为环保部门环境管理提供参考。     

浙江省环境质量演变趋势分析及预测研究

选择2011—2020年浙江省地表水、空气和酸雨监测数据,结合社会经济发展统计数据,从社会经济与环境质量间协调性角度探讨“十二五”及“十三五”浙江省环境质量演变趋势,并在此基础上对“十四五”期间环境质量进行科学合理的预测。分析结果表明,2011—2020年环境质量不断向良好状态发展,通过动态耦合模型得到的耦合度由2011年的34.6°上升到2020年的55.4°,社会经济发展与环境质量协调发展水平呈现上升态势。采用灰色预测法和时间序列模型对环境质量进行预测,模拟结果显示,预计到2025年地表水优良率将达到92%,满足功能要求断面比例达到95%,设区城市空气质量优良天数比例达到92%,酸雨率平均为40%。正确认识社会经济发展与环境质量变化之间的耦合规律,并对环境质量进行合理预测,能够为促进社会经济与生态环境的协调发展提供理论依据,为深入打好污染防治攻坚战提供有力支撑。