Knowledge expression,numerical modeling and optimization application of ethylene thermal cracking:From the perspective of intelligent manufacturing

Applications of process systems engineering(PSE)in plants and enterprises are boosting industrial reform from automation to digitization and intelligence.For ethylene thermal cracking,knowledge expression,numerical modeling and intelligent optimization are key steps for intelligent manufacturing.This paper provides an overview of progress and contributions to the PSE-aided production of thermal cracking;introduces the frameworks,methods and algorithms that have been proposed over the past10 years and discusses the advantages,limitations and applications in industrial practice.An entire set of molecular-level modeling approaches from feedstocks to products,including feedstock molecular reconstruction,reaction-network auto-generation and cracking unit simulation are described.Multilevel control and optimization methods are exhibited,including at the operational,cycle,plant and enterprise level.Relevant software packages are introduced.Finally,an outlook in terms of future directions is presented.

Modeling and Optimization of Surface Roughness of Epoxy/Nanoparticles Composite Coating

In power plants,flue gases can cause severe corrosion damage in metallic parts such as flue ducts,heat exchangers,and boilers.Coating is an effective technique to prevent this damage.A robust fuzzy model of the surface roughness(Ra and Rz)of flue gas ducts coated by protective composite coating from epoxy and nanoparticles was constructed based on the experimental dataset.The proposed model consists of four nanoparticles(ZnO,ZrO2,SiO2,and NiO)with 2%,4%,6%,and 8%,respectively.Response surface methodology(RSM)was used to optimize the process parameters and identify the optimal conditions for minimum surface roughness of this coated duct.To prove the superiority of the proposed fuzzy model,the model results were compared with those obtained by ANOVA,with the coefficient of determination and the root-mean-square error(RMSE)used as metrics.For Ra,for the first output response,using ANOVA,the coefficient-of-determination values were 0.9137 and 0.4037,respectively,for training and prediction.Similarly,for Rz,the second output response,the coefficient-of-determination results were 0.9695 and 0.4037,respectively,for training and prediction.In the fuzzy modeling of Ra,for the first output response,the RMSE values were 0.0 and 0.1455,respectively,for training and testing.The values for the coefficient of determination were 1.00 and 0.9807,respectively,for training and testing.The results prove the superiority of fuzzy modeling.For modeling the second output response Rz,the RMSE values were 0.0 and 0.0421,respectively,for training and testing,and the coefficient-of-determination values were 1.00 and 0.9959,respectively,for training and testing.

Modeling and optimization of a spherical triboelectric generator

A detailed geometric analysis of spherical triboelectric nanogenerators is presented.In comparison with earlier works on spherical triboelectric generators,the general case where the moving dielectric rolls on the inside surface of the larger sphere of the TENG is discussed in terms of maximum energy harvesting.An optimization analysis of geometrical parameters allows various cases of electrode geometry,either in the form of a spherical circle,spherical ellipse,spherical rectangle,or spherical isosceles trapezium,to be solved.The analytical insight and computational effective models provided by differential geometry make the mathematical model superior compared to standard three-dimensional(3D)numerical methods.

Modeling and optimization of a single-drive push–pull silicon Mach–Zehnder modulator

We present an equivalent circuit model for a silicon carrier-depletion single-drive push–pull Mach–Zehnder modulator(MZM)with its traveling wave electrode made of coplanar strip lines.In particular,the partialcapacitance technique and conformal mapping are used to derive the capacitance associated with each layer.The PN junction is accurately modeled with the fringe capacitances taken into consideration.The circuit model is validated by comparing the calculations with the simulation results.Using this model,we analyze the effect of several key parameters on the modulator performance to optimize the design.Experimental results of MZMs confirm the theoretical analysis.A 56 Gb/s on–off keying modulation and a 40 Gb/s binary phase-shift keying modulation are achieved using the optimized modulator.

The Memory-Bounded Speedup Model and Its Impacts in Computing

With the surge of big data applications and the worsening of the memory-wall problem,the memory system,instead of the computing unit,becomes the commonly recognized major concern of computing.However,this“memorycentric”common understanding has a humble beginning.More than three decades ago,the memory-bounded speedup model is the first model recognizing memory as the bound of computing and provided a general bound of speedup and a computing-memory trade-off formulation.The memory-bounded model was well received even by then.It was immediately introduced in several advanced computer architecture and parallel computing textbooks in the 1990’s as a must-know for scalable computing.These include Prof.Kai Hwang’s book“Scalable Parallel Computing”in which he introduced the memory-bounded speedup model as the Sun-Ni’s Law,parallel with the Amdahl’s Law and the Gustafson’s Law.Through the years,the impacts of this model have grown far beyond parallel processing and into the fundamental of computing.In this article,we revisit the memory-bounded speedup model and discuss its progress and impacts in depth to make a unique contribution to this special issue,to stimulate new solutions for big data applications,and to promote data-centric thinking and rethinking.

A bibliometric analysis of Stirling engine and in-depth review of its application for energy supply systems

With the great advantages and continuous innovations,prolific research efforts have been devoted to the Stirling engine(SE)domain driven by the sustainability development.In this study,a bibliometric analysis is conducted to explore the research tend and hotspots of SE.The country co-authorship,institute co-authorship and keyword networks are engendered from the visual map using VOSviewer,showing China ranks the first with the total number of published articles and the majority publications are presented by Chinese Academy of Sciences.Owing to the highest node centrality,the research findings in USA can be considered the most influential and greatly worthy being referred,particularly represented by the early contribution for thermo-acoustic SE.The total 7 keyword clusters are classified through the top terms in Citespace and 4 of them are related to its energy supply system,demonstrating the typical application of SE-based combined heat and power(CHP)and integrated multi-energy complementary system have gained much attention.Based on this,a detailed review of SE-based energy supply systems is further conducted through the system forms,4E performance evaluation and soft model combing optimization solutions.Several relevant issues hindering the improvement of these terms are summa-rized,providing the potential guides to help develop the SE-based energy supply system.

Distributed Scheduling Problems in Intelligent Manufacturing Systems

Currently,manufacturing enterprises face increasingly fierce market competition due to the various demands of customers and the rapid development of economic globalization.Hence,they have to extend their production mode into distributed environments and establish multiple factories in various geographical locations.Nowadays,distributed manufacturing systems have been widely adopted in industrial production processes.In recent years,many studies have been done on the modeling and optimization of distributed scheduling problems.This work provides a literature review on distributed scheduling problems in intelligent manufacturing systems.By summarizing and evaluating existing studies on distributed scheduling problems,we analyze the achievements and current research status in this field and discuss ongoing studies.Insights regarding prior works are discussed to uncover future research directions,particularly swarm intelligence and evolutionary algorithms,which are used for managing distributed scheduling problems in manufacturing systems.This work focuses on journal papers discovered using Google Scholar.After reviewing the papers,in this work,we discuss the research trends of distributed scheduling problems and point out some directions for future studies.

Design of large mode area all-solid anti-resonant fiber for high-power lasers

High-power fiber lasers have experienced a dramatic development over the last decade.Further increasing the output power needs an upscaling of the fiber mode area,while maintaining a single-mode output.Here,we propose an all-solid anti-resonant fiber(ARF)structure,which ensures single-mode operation in broadband by resonantly coupling higherorder modes into the cladding.A series of fibers with core sizes ranging from 40 to 100µm are proposed exhibiting maximum mode area exceeding 5000µm2.Numerical simulations show this resonant coupling scheme provides a higher-order mode(mainly TE01,TM01,and HE21)suppression ratio of more than 20 dB,while keeping the fundamental mode loss lower than 1 dB/m.The proposed structure also exhibits high tolerance for core index depression.