加热炉换热工艺特性分析软件进展

为便于对目前各类化工加热炉工艺特性设计技术软件技术进展的了解,通过7个换热特性专题分析软件的内容简介,综述了特性分析技术软件在工业炉工艺设计专业的应用,提出了当前加热炉软件技术发展中,设备结构和工艺两者结合发展面临的3个工程课题,分别是加热炉预热段、辐射段和对流段整体一体化、炉管振动计算、新智能技术的引入。     

Comparative studies of grain refinement of commercial purity Mg by CaO and Ca addition

ABSTRACT

The comparative studies of grain refinement of commercial purity Mg by CaO/Ca addition have been investigated by using TP-1 tests, optical microscope, XRD characterisation and TEM (STEM) observation along with EDX analysis. Experimental results showed that Ca/CaO addition significantly refines the grain structure of commercial purity Mg. Compared with Ca addition, CaO exhibits finer grain size and the average grain size remains invariable with further CaO addition. CaO addition is readily reduced to Ca by Mg melt and forms Mg₂Ca on the surface of MgO particles. First-principle calculations were used to understand the nucleation of Mg₂Ca layer by a coherent interface model calculating the work of adhesion and the interface energy between Mg₂Ca and α-Mg. The combination of experiments and calculations showed that the formation of Mg₂Ca layer on MgO facilitates the nucleation of α-Mg and then refines the grain structure by Ca or CaO addition.     

Ethanolysis of waste cottonseed oil over lithium impregnated calcium oxide: Kinetics and reusability studies

A series of Li/CaO catalysts has been prepared by impregnating 0.5–5.0 wt% Li in CaO by wet chemical method. Prepared Li/CaO catalysts have been characterized by powder X-ray diffraction, scanning electron and transmission electron microscopy and Brunauer–Emmett–Teller (BET) surface area studies, in order to establish the structure and surface morphology of the catalyst. Hammett indicator test study was performed to determine the basic strength of the Li/CaO catalysts. The prepared Li/CaO catalysts have been employed as a heterogeneous catalyst for the transesterification of waste cottonseed oil (having 2.8 wt% free fatty acid contents) with ethanol. Under optimal reaction conditions viz., ethanol/oil molar ratio of 12:1, catalyst to oil weight fraction of 5% and 65 °C reaction temperature, 98% fatty acid ethyl ester yield was obtained in 2.5 h of reaction duration. Under the optimized reaction conditions, the pseudo first order constant and Arrhenius activation energy were found to be 0.03 min⁻¹ and 70.0 kJ mol⁻¹, respectively. Further Li/CaO catalyst was also found to be effective for the ethanolysis and methanolysis of vegetable oils having up to 3.4 wt% free fatty acids. The use of 3-Li/CaO catalyst is advantageous considering that it not only utilizes waste cottonseed oil as a feedstock, but also renewable and nontoxic alcohol, ethanol, for the biodiesel production.     

A learning-based module extraction method for object-oriented systems

Developers apply object-oriented (OO) design principles to produce modular, reusable software. Therefore, service-specific groups of related software classes called modules arise in OO systems. Extracting the modules is critical for better software comprehension, efficient architecture recovery, determination of service candidates to migrate legacy software to a service-oriented architecture, and transportation of such services to cloud-based distributed systems. In this study, we propose a novel approach to automatic module extraction to identify services in OO software systems. In our approach, first we create a weighted and directed graph of the software system in which vertices and edges represent the classes and their relations, respectively. Then, we apply a clustering algorithm over the graph to extract the modules. We calculate the weight of an edge by considering its probability of being within a module or between modules. To estimate these positional probabilities, we propose a machine-learning-based classification system that we train with data gathered from a real-world OO reference system. We have implemented an automatic module extraction tool and evaluated the proposed approach on several open-source and industrial projects. The experimental results show that the proposed approach generates highly accurate decompositions that are close to authoritative module structures and outperforms existing methods.     

Political disagreement and ambivalence in new information environment: Exploring conditional indirect effects of partisan news use and heterogeneous discussion networks on SNSs on political participation

This study investigates the (de)mobilizing influences of political (dis)agreement in the news and in political discussion on political attitudes and participation in new information environments. Results demonstrate the mediating functions of political ambivalence in that exposure to proattitudinal news reduces ambivalence and thereby promotes political participation, whereas exposure to counter-attitudinal news increases ambivalence and thereby discourages participation. Importantly, the effect of exposure to counter-attitudinal news on ambivalence was moderated by heterogeneous discussion networks on social network sites, such that the combination of exposure to counter-attitudinal news and to heterogeneous discussion networks amplifies ambivalence additively, and thereby augments the tendency toward demobilization. These results are interpreted as suggesting that changing media contexts may lead to complex roles of news and political discussion.     

Synthesis of biodiesel from Scenedesmus sp. by microwave and ultrasound assisted in situ transesterification using tungstated zirconia as a solid acid catalyst

Oleaginous Scenedesmus sp. was cultivated phototrophically in an open pond for biofuels production. The culture was harvested and subsequently dewatered and dried. The chemical properties of the Scenedesmus sp. lipids were determined as per standard ASTM methods. Biodiesel was synthesized by in situ transesterification from dried biomass using microwave and sonication techniques with tungstated zirconia (WO₃/ZrO₂) as a solid acid catalyst. In situ transesterification allowed minimizing the requirement of solvents by merging the two steps (i.e. extraction of lipid and conversion to biodiesel) to a single step. The use of a solid catalyst effectively reduces the purification cost of biodiesel due to ease of separation and potential for reuse. The conversion of Scenedesmus sp. lipids to biodiesel was determined by GC. Box–Behnken design was used for optimization of the variables to optimize the biodiesel yield and conversion. The efficiency of the two processes was compared.     

An overview of Dynamic Software Product Line architectures and techniques: Observations from research and industry

Over the last two decades, software product lines have been used successfully in industry for building families of systems of related products, maximizing reuse, and exploiting their variable and configurable options. In a changing world, modern software demands more and more adaptive features, many of them performed dynamically, and the requirements on the software architecture to support adaptation capabilities of systems are increasing in importance. Today, many embedded system families and application domains such as ecosystems, service-based applications, and self-adaptive systems demand runtime capabilities for flexible adaptation, reconfiguration, and post-deployment activities. However, as traditional software product line architectures fail to provide mechanisms for runtime adaptation and behavior of products, there is a shift toward designing more dynamic software architectures and building more adaptable software able to handle autonomous decision-making, according to varying conditions. Recent development approaches such as Dynamic Software Product Lines (DSPLs) attempt to face the challenges of the dynamic conditions of such systems but the state of these solution architectures is still immature. In order to provide a more comprehensive treatment of DSPL models and their solution architectures, in this research work we provide an overview of the state of the art and current techniques that, partially, attempt to face the many challenges of runtime variability mechanisms in the context of Dynamic Software Product Lines. We also provide an integrated view of the challenges and solutions that are necessary to support runtime variability mechanisms in DSPL models and software architectures.     

Automated generation of computationally hard feature models using evolutionary algorithms

A feature model is a compact representation of the products of a software product line. The automated extraction of information from feature models is a thriving topic involving numerous analysis operations, techniques and tools. Performance evaluations in this domain mainly rely on the use of random feature models. However, these only provide a rough idea of the behaviour of the tools with average problems and are not sufficient to reveal their real strengths and weaknesses. In this article, we propose to model the problem of finding computationally hard feature models as an optimization problem and we solve it using a novel evolutionary algorithm for optimized feature models (ETHOM). Given a tool and an analysis operation, ETHOM generates input models of a predefined size maximizing aspects such as the execution time or the memory consumption of the tool when performing the operation over the model. This allows users and developers to know the performance of tools in pessimistic cases providing a better idea of their real power and revealing performance bugs. Experiments using ETHOM on a number of analyses and tools have successfully identified models producing much longer executions times and higher memory consumption than those obtained with random models of identical or even larger size.     

Optimal conditions of isobutane dehydrogenation in radial flow moving bed hydrogen-permselective membrane reactors to enhance isobutene and hydrogen production

In the isobutane dehydrogenation process, coupling reaction and separation and optimization of the intensified process can improve the isobutane conversion and selectivity, reduce operational costs and lets to produce pure hydrogen. In this research, the radial flow moving bed reactors in the Olefex technology have been supported by Pd–Ag membrane plate to remove hydrogen from the reaction zone. The reactions occur in the tube side and the hydrogen is permeated from the reaction zone to the sweep gas stream. The proposed configuration has been modeled heterogeneously based on the mass and energy conservation laws considering reaction networks. To prove the accuracy of the considered model, the simulation results of the conventional process have been compared against available plant data. The Genetic algorithm as an effective method in the global optimization has been considered to optimize the operating condition of membrane reactors to enhance isobutene productivity. In this optimal configuration, the isobutene production has been enhanced about 3.7%.     

Transesterification of Canola Oil to Biodiesel Using CaO/Talc Nanopowder as a Mixed Oxide Catalyst

A series of heterogeneous catalysts including different molar ratios of CaO/talc was synthesized to study the transesterification reaction of canola oil and methanol under different reaction conditions. Characterization and kinetic results revealed that the activity of this catalyst was enhanced due to the increase of CaO/talc molar ratio value leading to an improvement in the biodiesel production. Moreover, the effect of various parameters on the activity of the undertaken catalysts was studied in order to determine the optimum process conditions. Leaching measurements and the durability of the CaO/talc catalyst under several reaction cycles were evaluated and proved it to be a stable catalyst.