近距双线盾构隧道开挖诱发地层变形演变规律及数值模拟

双线平行隧道盾构施工相互扰动作用对其诱发的地层变形分布特征和演变规律影响显著。以某地铁双线盾构隧道工程为例,考虑双线平行隧道间距与盾构施工相互作用影响,采用数值模拟和现场实测相结合的方法对双线平行隧道盾构施工引起的地层变形演变规律进行了对比分析,并提出了考虑近远距状态的双线平行隧道盾构施工地层变形预测模型。研究结果表明,双线盾构隧道施工地层竖向变形曲线由“V”形发展为非对称“W”形分布,沉降槽宽度由6D扩大为10D,地层深度越深非对称“双峰”特征越明显;地层水平变形曲线以两隧道中线为轴线呈反对称分布,两隧道间区域土体变形受施工扰动影响显著;地表沉降曲线分布随双线隧道近远距变化由深“V”形—浅“V”形—“U”形—浅“W”形—深“W”形—两独立“V”形演变,采用L cr=2CKH可作为双线平行盾构隧道近远距状态临界判据,本文提出的预测模型能较好地反映近远距状态及施工相互扰动对双线平行隧道盾构施工地层变形的影响规律。研究成果可为类似地铁隧道盾构施工变形预测与精细化控制提供科学参考。     

一体化A_mO_n工艺BP神经网络数学模型研究

讨论基于BP神经网络一体化AmOn污水处理工艺数学模型的构建。在分析神经网络和一体化AmOn污水处理工艺各自特点的基础上,建立了具有11个输入层节点、5个输出层节点以及包含两层隐含层的BP神经网络,并确定了各隐含层的节点数、网络的权值和阈值。对模型的验证结果表明:BP神经网络模型基本反映了AmOn一体化工艺的主要特点,网络预测出水结果与实测结果相差不大,神经网络模型具有较好的泛化能力。     

运用回归分析与人工神经网络预测含硫芳香族化合物好氧生物降解速率常数

为了研究人工神经网络预测有机化合物生物降解的性能,运用多元线性回归方法和误差反向传递人工神经网络模型以基团代码作为结构描述符,分别拟合、预测了一批含硫芳香族化合物的一级好氧生物降解速率常数．结果表明,由于神经网络自动考虑了基团间的交互作用,它对生物降解这类复杂问题有极高的求解能力,预测的均方误差为０．００１０２,远低于线性回归模型的预测误差０．０１５９１     

基于BP网络理论的岩爆预测方法

选取影响岩爆的一些主要因素,如地应力大小、岩石抗压和抗拉强度、岩石弹性能量指数,采用人工神经网络理论,根据国内外一些岩石地下工程实例构造样本集,建立了一种新的岩爆预测模型.此模型可以直接应用于岩石地下工程,对岩爆的发生与否及烈度大小进行预测.实例表明,预测结果与实际情况符合得很好,说明了此模型的有效性.     

Hydrogen explosion incident mitigation in steam reforming units through enhanced inspection and forecasting corrosion tools implementation

Hydrogen (H₂) explosion effects recently examined, are confirming the devastating loss scenarios to humans, environment, assets, and associated business interruption. H₂ production is a core process in refineries used in further process steps. Steam reforming of natural gas or a mix with naphtha or LPG is a common hydrogen production technique, where the latest technologies have adopted enhanced metallurgies to minimize explosion risk and the associated maintenance cost following plant degradation owing to corrosion effects. However, corrosion rates are still high in specific areas of piping and process equipment. The aim of this paper is to present a methodology based on semi-quantitative RBI modeling according to regulations by API and recent EN standards, adopting a family of linear regression forecasting models that depict the yearly corrosion rate (per corrosion loop) of a hydrogen production steam reforming unit; this is done under different operating conditions (e.g., temperature, pressure, and fluid speed), metallurgy and other related physicochemical variables. The model is based on the examination of both ultrasonic wall thinning measurements and the examination of quantitative crosslinking total corrosion effects along with the physicochemical properties prevailing in different plant corrosion loops. The outcome of the regression analysis is an expansive family of multivariable equations describing, with a defined accuracy, the yearly corrosion rate and associated lifespan forecast per corrosion loop, and per examined part. These equations were further utilized in a custom-made database that can be used as an additional loss prevention tool by the hydrogen production unit management team. Evaluation results regarding the tool efficiency are presented in the following of this paper.     

Fused CFD-interpolation model for real-time prediction of hazardous gas dispersion in emergency rescue

Accidental releases of hazardous gases in chemical industries can pose great threats to public security. The computational fluid dynamics (CFD) model is commonly applied to predict gas dispersion in complex structured areas. It can provide good accuracy but it is too time-consuming to be used in emergency response. To reduce computation time while keep acceptable accuracy, this paper proposes several fused CFD-interpolation models which combine CFD model with different interpolation methods. Spline, linear and nearest interpolation methods are used. A CFD simulations database is created ahead of time which can be quickly recalled for emergency usage and unknown situations can be predicted instantly by interpolation methods instead of time-consuming CFD model. Fused models were applied to a case study involving a hypothetical propane release with varying conditions and validated against CFD model. The validation shows that prediction accuracy of these fusion models is acceptable. Among these models, CFD-Spline interpolation model performs best. It is faster than CFD model by a factor of 75 and is potentially a good method to be applied to real-time prediction.     

A spatial-temporal approach for corrosion prediction in time-varying marine environment

Corrosion in seawater is simultaneously influenced by multiple environmental factors including dissolved oxygen (DO), temperature, salinity, pH, and so on. These factors vary along with time and are different in different locations. The spatial-temporal variation of the actual marine environment cannot be ignored in corrosion prediction models. This paper proposes a new method for corrosion prediction in the actual time-varying marine environment which includes the design of experiments, calibration of acceleration models, and the modeling of marine environment. Acceleration models capture the effects of environmental factors and acts as the link between the environment and the corrosion process. The marine environment is described with the Kriging spatial-temporal model. Then the proposed method is used to give corrosion predictions for metals in different locations and vessels travel in different waters. This method could be helpful for corrosion resistance evaluation and environment corrosivity assessment.     

Emergency evacuation model assuming leakage of toxic substances in a chemical plant

Preparedness of emergency evacuation for the leakage of toxic substances in chemical plants is very important in order to reduce damage. In order to implement an emergency evacuation properly, it is necessary to comprehensively and concretely determine the conditions of the leakage and atmospheric conditions and predict the consequences of the dispersed gases. Repeated training for emergencies is also essential. In order to realize effective evacuation, a prediction model of the evacuation area that anyone can use to obtain the same results both accurately and promptly is developed in the present study. The prediction model is designed such that the wind speed and atmospheric conditions are automatically set, and the leakage rate is the only input parameter, so that anyone can use the model easily. In addition, the model can also predict the atmospheric parameters for up to 3 h and can calculate the evacuation distance so that smooth evacuation can be achieved for changing atmospheric conditions. Finally, the evacuation area is defined by statistically analysed wind fluctuations, and a series of emergency evacuation measures is implemented.     

A review of research on China’s carbon emission peak and its forcing mechanism

In order to make further steps in dealing with climate change, China proposed to peak carbon dioxide emissions by about 2030 and to make best efforts for the peaking early. The carbon emission peak target (CEPT) must result in a forcing mechanism on China’s economic transition. This paper, by following the logical order from “research on carbon emission history” to “carbon emission trend prediction,” from “research on paths of realizing peak” to “peak restraint research,” provides a general review of current status and development trend of researches on China’s carbon emission and its peak value. Furthermore, this paper also reviews the basic theories and specific cases of the forcing mechanism. Based on the existing achievements and development trends in this field, the following research directions that can be further expanded are put forward. First, from the perspective of long-term strategy of sustainable development, we should analyze and construct the forcing mechanism of CEPT in a reverse thinking way. Second, economic transition paths under the forcing mechanism should be systematically studied. Third, by constructing a large-scale policy evaluation model, the emission reduction performance and economic impact of a series of policy measures adopted during the transition process should be quantitatively evaluated.     

长江中游荆南三口河系径流演变特征及趋势预测

以荆南三口五站1951~2015年实测径流数据,利用Mark-Kendall趋势突变检验法、累计距平、Morlet复小波等方法分析三口河系径流演变特征;选用ARIMA模型和时间序列模型预测荆南三口河系径流演变趋势。结果表明:(1)荆南三口径流年际变化较大,径流年内分配不均匀,5~10月为丰水期,11月~次年4月为枯水期,呈现出明显季节差异;(2)三口径流总体上呈下降趋势,其中以1959~1980年径流下降趋势最为明显,其趋势幅度p的绝对值达到了698.313,2003~2015年径流下降趋势较为缓慢,无明显趋势,但其p的绝对值仍达到了166.524;(3)运用Mark-Kendall突变检验及累计距平法共同检验,三口径流突变年份为1970年、1985年;(4)1951~2015年间三口径流变化过程主要存在48~58 a、20~28 a、10~18 a 3个尺度的周期变化,以55 a、24 a、14 a为周期中心,其小波方差显示三口径流序列第一、第二、第三主周期分别为55 a、24 a、14 a;(5)三口径流在2016~2030年呈现出先减小后增大的趋势,即2016~2018年为波动增减期,2019~2026年前后为枯水期,2026~2030年为丰水期。