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.     

Generation,validation and application of dynamic load profiles in flow measurement using cavitating Herschel–Venturi nozzles

Today, utility meters for water are tested for measurement behavior at stable operating conditions at specified flow rates as part of the approval process. The measurement error that occurs during start and stop or when changing between flow rates may not be taken into account. In addition, there are new technologies whose measuring behavior under real-world conditions is only known to a limited extend. To take these facts into account, a new method has been developed and tested to determine the measurement behavior of water meters under dynamic load profiles as they occur in the real application. For this purpose, a test rig for flow rate measurement was extended by a cavitation nozzle apparatus and the generation of dynamic load profiles was validated. For the cavitation nozzles used, possible factors influencing the flow rate, such as temperature and purity of the water as well as the upstream pressure were investigated. Using different types of domestic water meters, the applicability of the dynamic test procedure was demonstrated and the measurement behavior of the meters was characterised.     

Green Measurements for Software Product Based on Sustainability Dimensions

Software is a central component in the modern world and vastly affects the environment’s sustainability. The demand for energy and resource requirements is rising when producing hardware and software units. Literature study reveals that many studies focused on green hardware; however, limited efforts were made in the greenness of software products. Green software products are necessary to solve the issues and problems related to the long-term use of software, especially from a sustainability perspective. Without a proper mechanism for measuring the greenness of a particular software product executed in a specific environment, the mentioned benefits will not be attained. Currently, there are not enough works to address this problem, and the green status of software products is uncertain and unsure. This paper aims to identify the green measurements based on sustainable dimensions in a software product. The second objective is to reveal the relationships between the elements and measurements through empirical study. The study is conducted in two phases. The first phase is the theoretical phase, where the main components, measurements and practices that influence the sustainability of a software product are identified. The second phase is the empirical study that involved 103 respondents in Malaysia investigating current practices of green software in the industrial environment and further identifying the main sustainability dimensions and measurements and their impact on achieving green software products. This study has revealed seven green measurements of software product: Productivity, Usability, Cost Reduction, Employee Support, Energy Efficiency, Resource Efficiency and Tool Support. The relationships are statistically significant, with a significance level of less than 0.01 (p = 0.000). Thus, the hypothesised relationships were all accepted. The contributions of this study revolve around the research perspectives of the measurements to attain a green software product.     

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.     

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。     

Physicochemical and technological properties of beef burger as influenced by the addition of pea fibre

This study aimed to evaluate the physicochemical characteristics and sensory attributes of beef burgers with the addition of pea fibre as a partial substitute of meat or fat. Three formulations were prepared: control (CON) – similar to the commercial formulation; fibre/less meat (FLM)—5% meat reduction and addition of 1% pea fibre; fibre/less fat (FLF)—7% fat reduction and addition of 1% pea fibre. Non-significant differences were obtained for pH, colour parameters (L* and b*), texture profile, cooking loss and size reduction among formulations. Moreover, sensory analysis with consumers of beef burgers did not indicate differences among the formulations for all the analysed attributes. Therefore, pea fibre is a promising partial replacer for meat and fat in beef burgers due to the preservation of technological parameters and sensory acceptance.     

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。     

无人机在输电线路巡检中的多种应用

无人机技术目前的快速发展使得我们国家输电线路自身的巡检能力得到了持续的提升,基于此本文在对无人机技术给予认识的情况下,在了解了输电线路巡检过程中的使用优势之后,还总结了无人机技术在当前我国线路巡检过程中的应用路径以及应用方法;之后使用案例分析的方式分析了无人机技术在当前输电线路巡检过程中的应用方法。     

An industrial case study on variability handling in large enterprise software systems

ContextEnterprise software systems (e.g., enterprise resource planning software) are often deployed in different contexts (e.g., different organizations or different business units or branches of one organization). However, even though organizations, business units or branches have the same or similar business goals, they may differ in how they achieve these goals. Thus, many enterprise software systems are subject to variability and adapted depending on the context in which they are used.ObjectiveOur goal is to provide a snapshot of variability in large scale enterprise software systems. We aim at understanding the types of variability that occur in large industrial enterprise software systems. Furthermore, we aim at identifying how variability is handled in such systems.MethodWe performed an exploratory case study in two large software organizations, involving two large enterprise software systems. Data were collected through interviews and document analysis. Data were analyzed following a grounded theory approach.ResultsWe identified seven types of variability (e.g., functionality, infrastructure) and eight mechanisms to handle variability (e.g., add-ons, code switches).ConclusionsWe provide generic types for classifying variability in enterprise software systems, and reusable mechanisms for handling such variability. Some variability types and handling mechanisms for enterprise software systems found in the real world extend existing concepts and theories. Others confirm findings from previous research literature on variability in software in general and are therefore not specific to enterprise software systems. Our findings also offer a theoretical foundation for describing variability handling in practice. Future work needs to provide more evaluations of the theoretical foundations, and refine variability handling mechanisms into more detailed practices.