RPMS在大连石化催化料调合优化测算中的应用

RPMS模型优化原理是用线性规划方法,在满足设置的约束条件下求取目标函数最优值。利用RPMS模型对催化料调合进行优化测算,通过模型优化求解得到各方案的最优二次装置负荷、最优产品分布,并选出了效益最好的调合方案,为生产优化提供了决策支持。     

基于软PLC的电气控制器设计

针对以传统PLC为核心设计的控制器存在的电路和控制方式复杂的问题,选用具有可靠性高、抗干扰能力强、易在线修改、易调试操作,具有CAN通信模块的新型软PLC作为电气控制器的控制核心,实现对外部信号的采集、转换、控制,达到了对系统精确控制的目的。实践表明,以软PLC为核心的电气控制器的成功应用,不仅提高了电气控制系统的稳定性和可靠性,且为其他控制系统提供了技术支持和应用依据。     

余热锅炉蒸汽流量的温度压力补偿及在DCS系统中的实现方法

将"IFC-1967公式"用于水蒸汽流量的温度压力补偿,可以保证企业精确测量及统计蒸汽流量和累计用量。利用DCS系统提供的结构化文本编程组态方式,将IFC-1967公式写入到系统,并封装成通用功能块,在DCS系统中实现了对余热锅炉过热蒸汽流量的准确测量。     

Optimization models for shale gas water management

There are four key aspects for water use in hydraulic fracturing, including source water acquisition, wastewater production, reuse and recycle, and subsequent transportation, storage, and disposal. Water use life cycle is optimized for wellpads through a discrete‐time two‐stage stochastic mixed‐integer linear programming model under uncertain availability of water. The objective is to minimize expected transportation, treatment, storage, and disposal cost while accounting for the revenue from gas production. Assuming freshwater sources, river withdrawal data, location of wellpads, and treatment facilities are given, the goal is to determine an optimal fracturing schedule in coordination with water transportation, and its treatment and reuse. The proposed models consider a long‐time horizon and multiple scenarios from historical data. Two examples representative of the Marcellus Shale play are presented to illustrate the effectiveness of the formulation, and to identify optimization opportunities that can improve both the environmental impact and economical use of water. © 2014 American Institute of Chemical Engineers AIChE J, 60: 3490–3501, 2014     

Optimal maintenance scheduling of a gas engine power plant using generalized disjunctive programming

A new continuous‐time model for long‐term scheduling of a gas engine power plant with parallel units is presented. Gas engines are shut down according to a regular maintenance plan that limits the number of hours spent online. To minimize salary expenditure with skilled labor, a single maintenance team is considered which is unavailable during certain periods of time. Other challenging constraints involve constant minimum and variable maximum power demands. The objective is to maximize the revenue from electricity sales assuming seasonal variations in electricity pricing by reducing idle times and shutdowns in high‐tariff periods. By first developing a generalized disjunctive programming model and then applying both big‐M and hull reformulation techniques, we reduce the burden of finding the appropriate set of mixed‐integer linear constraints. Through the solution of a real‐life problem, we show that the proposed formulations are very efficient computationally, while gaining valuable insights about the system. © 2014 American Institute of Chemical Engineers AIChE J, 60: 2083–2097, 2014     

Integration of scheduling and control for batch processes using multi‐parametric model predictive control

Integration of scheduling and control results in Mixed Integer Nonlinear Programming (MINLP) which is computationally expensive. The online implementation of integrated scheduling and control requires repetitively solving the resulting MINLP at each time interval. (Zhuge and Ierapetritou, Ind Eng Chem Res. 2012;51:8550–8565) To address the online computation burden, we incorporare multi‐parametric Model Predictive Control (mp‐MPC) in the integration of scheduling and control. The proposed methodology involves the development of an integrated model using continuous‐time event‐point formulation for the scheduling level and the derived constraints from explicit MPC for the control level. Results of case studies of batch processes prove that the proposed approach guarantees efficient computation and thus facilitates the online implementation. © 2014 American Institute of Chemical Engineers AIChE J, 60: 3169–3183, 2014     

Transcriptional Regulation of Programmed Hypertension by Melatonin: An Epigenetic Perspective

Melatonin is an endogenously produced indoleamine and secreted by the pineal gland. Melatonin has pleiotropic bioactivities and is involved in epigenetic regulation. Suboptimal conditions during maternal and perinatal phases can elicit epigenetic regulation of genes for nephrogenesis and reset physiological responses to develop programmed hypertension. This review discusses the early utility of melatonin to prevent programmed hypertension in later life by epigenetic regulation in the kidney, with an emphasis on: (1) the role of melatonin in epigenetic regulation; (2) the beneficial effects of melatonin on programmed hypertension; (3) epigenetic regulation of maternal melatonin therapy in different developmental windows of offspring kidneys analyzed by whole-genome RNA next-generation sequencing; and (4) current blocks in the application of melatonin in preventing programmed hypertension.     

基于Matlab编程的含缺陷长输管道安全评定

分析各种管道评定标准给出不同裂纹情况相应的评价方法,采用GB/T 19624-2004对壁厚为18mm的X80管段长输管道工程实测裂纹进行简化评定,绘制出失效评定图,得出该管道可以安全运行,并给出了最大容许等效裂纹尺寸。对评定过程中的复杂汁算公式进行Matlab软件编程,使得计算过程程序化,提高计算准确率,降低评定难度。     

A dynamic programming approach for economic optimisation of lifetime-extending maintenance,renovation, and replacement of public infrastructure assets under differential inflation

In the next decades, many public infrastructure assets will reach the end of their life that they were originally designed for. Replacement costs are high, and therefore increasing effort is put into lifetime-extending maintenance, including major overhauls and renovations. A key question is whether the investments in lifetime-extending maintenance justify the postponement of a full replacement. This question becomes more complicated when future life cycle cash flows are non-repeatable. Differential inflation and technological change, including multiple intervention strategies to maintain a desired functionality, cause such non-repeatability. In this case, classic replacement analysis techniques will not suffice in answering this question. Literature demonstrates that case-specific modelling with dynamic or linear programming techniques is required to find economic optimisation. However, such literature primarily addresses replacement interval optimisation of new investments within relative short time horizons, whereas the current research develops a nested dynamic programming (DP) approach for typical ageing infrastructure assets over long service life periods. The model can deal with multiple and various successive intervention strategies and addresses differential inflation and age-related cost increases. Finally, it is shown in an infrastructure case study that this DP approach leads to a better decision in comparison to the application of classical replacement techniques.