Robust optimal operation of continuous catalytic reforming process under feedstock uncertainty

The continuous catalytic regenerative (CCR) reforming process is one of the most significant sources of hydrogen production in the petroleum refining process. However, the fluctuations in feedstock composition and flow rate could significantly affect both product distribution and energy consumption. In this study, a robust deviation criterion based multi-objective optimization approach is proposed to perform the optimal operation of CCR reformer under feedstock uncertainty, with simultaneous maximization of product yields and minimization of energy consumption. Minimax approach is adopted to handle these uncertain objectives, and the Latin hypercube sampling method is then used to calculate these robust deviation criteria. Multi-objective surrogate-based optimization methods are next introduced to effectively solve the robust operational problem with high computational cost. The level diagram method is finally utilized to assist in multi-criteria decision-making. Two robust operational optimization problems with different objectives are solved to demonstrate the effectiveness of the proposed method for robust optimal operation of the CCR reforming process under feedstock uncertainty.     

基准平面垂直断面法在爆破漏斗试验中的应用

系统阐述了基准平面垂直断面法在爆破漏斗试验中测量爆破漏斗体积的基本原理,并将隧道激光断面仪应用于金厂河矿1 750 m水平15^#采场底部切割巷道爆破漏斗试验爆破漏斗体积测量中。通过与传统体重法等计算法所得漏斗体积分析比较,结果表明基于隧道激光断面仪与3D Mine软件分析的基准平面垂直断面法实用性强、操作方便、结果直观可靠,达到试验预期目的。     

水压爆破拆除超大容积水池

简要介绍了组合式超大容积（８５０ｍ３）水池在水压爆破拆除过程中爆破方案选择、参数选取等方面的经验，并对爆破效果进行了分析，为同类工程施工提供了可借鉴的经验。     

Identifying catalyst layer compositions of proton exchange membrane fuel cells through machine-learning-based approach

Membrane electrode assembly (MEA) is considered a key component of a proton exchange membrane fuel cell (PEMFC). However, developing a new MEA to meet desired properties, such as operation under low-humidity conditions without a humidifier, is a time- and cost-consuming process. This study employs a machine-learning-based approach using K-nearest neighbor (KNN) and neural networks (NN) in the MEA development process by identifying a suitable catalyst layer (CL) recipe in MEA. Minimum redundancy maximum relevance and principal component analysis were implemented to specify the most important predictor and reduce the data dimension. The number of predictors was found to play an essential role in the accuracy of the KNN and NN models although the predictors have self-correlations. The KNN model with a K of 7 was found to minimize the model loss with a loss of 11.9%. The NN model constructed by three corresponding hidden layers with nine, eight, and nine nodes can achieve the lowest error of 0.1293 for the Pt catalyst and 0.031 for PVA as a good additive blending in the CL of the MEA. However, even if the error is low, the prediction of PVA seems to be inaccurate, regardless of the model structure. Therefore, the KNN model is more appropriate for CL recipe prediction.     

Mixing enhancement mechanism of combined H2–Water jets in supersonic crossflows in a combustor with an expanded section

To obtain the mixing enhancement mechanism of H₂–Water combined jets in supersonic crossflows in a combustor with expanded section for rotating detonation ramjet, the flow field shape and spray structure were studied by experimental and numerical methods. The Eulerian–Lagrangian method was used to investigate the diffusion mechanism and H₂–Water interaction law of combined jets with different sequences. At the same time, high-speed photography and the schlieren technique were used to capture the flow field. The effects of jet pressure drop, orifice diameter, orifice spacing, incoming Mach number, and other parameters on the penetration depth of water jets were studied. The results of experiment and simulation show that using H₂–Water combined jets, the penetration depth of the jet spray can be greatly increased and the jet mixing effect can be significantly improved, which will contribute to the engine's ignition and stable combustion. In the case of pre-water/post-H₂, the penetration depth of the hydrogen jet is greater. In the case of pre-H₂/post-water, the hydrogen jet raises the water spray mainly by protecting the integrity of the water column.     

炼油废白土在水泥厂燃煤自备电厂中再利用的实践

本项目主要研究和实现了工业废白土在BAYAH燃煤自备电厂中的再利用,实现变废为宝,减少了环境污染,同时为企业创造了一定的经济效益。针对废白土的特性,对燃料输送系统给煤机、皮带机、煤仓、下料溜子和排渣系统进行了改造。通过修改操作规程消除废白土对锅炉运行的影响。     

NNI-1型C_5/C_6烷烃异构化催化剂长周期运行分析及建议

中国石化海南炼油化工有限公司0.2 Mt/a C5/C6烷烃异构化装置以连续重整装置的拔头油为原料,使用NNI-1催化剂,采用一次通过流程,不设脱异戊烷塔和稳定塔,经设在连续重整装置内的脱丁烷塔稳定处理后作为汽油调合组分。该装置于2006年9月开工投产,截至2015年3月已连续运行3个周期。长周期运行分析结果表明:前两个周期中NNI-1催化剂具有较高的异构化活性及选择性,C5异构化率为60%左右,C6异构化率为80%左右,C6选择性为15%左右,产品辛烷值基本达到技术指标要求(RON≥78);而在第三周期运行中,催化剂积炭增加等原因导致其异构化活性及选择性降低,异构化产品辛烷值提升能力呈现逐步衰减的趋势,提高反应苛刻度已不能弥补催化剂活性下降造成的产品辛烷值降低。为保证装置长周期运行,建议择机停工对催化剂进行再生,或是直接换用与装置原料性质匹配的异构化催化剂。     

钢管套筒灌浆连接轴向受拉性能模拟试验研究

为研究钢管套筒灌浆连接轴向受拉破坏过程及破坏机理，试验中设计了16组48个钢管套筒灌浆连接试件，试件采用钢板代替圆钢管，并进行静载试验。分析了灌浆料裂缝扩展过程、荷载-相对位移曲线，并对抗剪键高距比、灌浆料厚度、侧向力等因素对破坏过程及承载力的影响进行分析。结果表明：对于不设置抗剪键的套筒灌浆连接试件，斜裂缝随机产生，裂缝分布不均匀；对于设置抗剪键的套筒灌浆连接试件，裂缝首先出现在底部抗剪键位置处，与水平方向夹角约为30°，随后在中部和上部抗剪键位置处分别出现斜裂缝。由于每个抗剪键上荷载分担并不均匀，与抗剪键接触的灌浆料逐渐达到极限压应力，达到极限状态时，承载力全部由抗剪键间的机械咬合力承担，在连接承载力中，可忽略摩擦力和胶结力作用。随着抗剪键高距比h/s增大，各试件初始剪切刚度相差不大，承载力增大，但增幅逐渐减小，建议抗剪键高距比0.06g/s>0.3，同时需要满足灌浆料灌注的施工要求。     

Improved error performance for generalised spatial modulation with enhanced spectral efficiency

The existing analytical average bit error rate (ABER) expression of conventional generalised spatial modulation (CGSM) does not agree well with the Monte Carlo simulation results in the low signal‐to‐noise ratio (SNR) region. Hence, the first contribution of this paper is to derive a new and easy way to evaluate analytical ABER expression that improves the validation of the simulation results at low SNRs. Secondly, a novel system termed CGSM with enhanced spectral efficiency (CGSM‐ESE) is presented. This system is realised by applying a rotation angle to one of the two active transmit antennas. As a result, the overall spectral efficiency is increased by 1 bit/s/Hz when compared with the equivalent CGSM system. In order to validate the simulation results of CGSM‐ESE, the third contribution is to derive an analytical ABER expression. Finally, to improve the ABER performance of CGSM‐ESE, three link adaptation algorithms are developed. By assuming full knowledge of the channel at the receiver, the proposed algorithms select a subset of channel gain vector (CGV) pairs based on the Euclidean distance between all CGV pairs, CGV splitting, CGV amplitudes, or a combination of these.