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Numerical Study on the Thermal and Optical Performances of an Aerogel Glazing System with the Multivariable optimization Using an Advanced Machine Learning Algorithm

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ADVANCED THEORY AND SIMULATIONS 2019年第9期2卷

作者： Zheng, Siqian Zhou, Yuekuan City Univ Hong Kong Dept Architecture & Civil Engn Hong Kong 999077 Peoples R China Hunan Univ Coll Civil Engn Key Lab Bldg Safety & Energy Efficiency Minist Educ Changsha 410082 Hunan Peoples R China Hong Kong Polytech Univ Fac Construct & Environm Dept Bldg Serv Engn Hong Kong 999077 Peoples R China

The implementation of advanced materials in high-efficient glazing system is important for green buildings. In this study, aerogel granules are implemented in the glazing system to form a translucent window with super-insulating performance. An experimentally validated numerical modeling integrating both heat transfer model and optical model is developed to characterize the sophisticated heat transfer and solar radiation transmission mechanisms. Sensitivity analysis is presented with quantifiable contribution ratio of each parameter to the total heat gain. Instead of returning back to numerical modeling repeatedly, an advanced optimization engine implemented with a generic optimization methodology with competitive computational efficiency and accuracy is proposed by implementing the supervised machine learning and advanced optimization algorithms. The research results show that the developed artificial neural network modeling is more accurate and computational-efficient than the traditional lsqcurvefit fitting methodology. In addition, the optimal case through the teaching-learning-based optimization is more robust and competitive than the optimal case through the particle swarm optimization in terms of the total heat gain. This study presents an in-depth understanding of heat transfer and solar radiation transmission of nanoporous aerogel granules together with a robust optimal design, which is important for the promotion of green buildings with high-energy performance.

关键词： aerogel machine learning optimization function particle swarm optimization teaching-learning-based optimization transmittance

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Blind recover conditions for images with side informationl

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 2007年第9期E90D卷 1469-1473页

作者： Takeuchi, Yoshinobu Ooyagi, Akira Iwaki Meisei Univ Iwaki Fukushima 9708551 Japan

We consider the blind recovery problem such that images embedded with side information are given, and we want to obtain the side information under some prescribed constraints. In this case, the system equation becomes y = Ax + b where in addition to the unknown A and x, b also is an unknown quantity and but clearly not a noise component. We assume that several images with the same embedding side information are given, and the image processing to b is described as the perturbation of A. We formulate the optimization function to obtain A, b and x, under the constraint of some finite brightness levels i.e. finite alphabets.

关键词： image restoration blind recovery side information optimization function finite alphabet

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Method for an Effective Selection of Tools and Cutting Conditions during Precise Turning of Non-Alloy Quality Steel C45

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MATERIALS 2022年第2期15卷 505页

作者： Ivchenko, Oleksandr Ivanov, Vitalii Trojanowska, Justyna Zhyhylii, Dmytro Ciszak, Olaf Zaloha, Olha Pavlenko, Ivan Hladyshev, Dmytro Sumy State Univ Dept Mfg Engn Machines & Tools 2 Rymskogo Korsakova Str UA-40007 Sumy Ukraine Poznan Univ Tech Fac Mech Engn Piotrowo 3 PL-60965 Poznan Poland Sumy State Univ Dept Computat Mech 2 Rymskogo Korsakova Str UA-40007 Sumy Ukraine

The paper presents a constructing methodology for a modern approach to tools selection and solving the problem of assigning optimal cutting parameters for specific production conditions. The mathematical formulation determining the extreme values of the technological process optimality criteria is obtained. A system of technical and economic quality indicators for cutting tools is proposed. This system allows principles' implementation of decentralization and interoperability "Industry 4.0" via finite element modeling of the cutting process based on solving the problem of orthogonal free cutting modeling. The proposed methodology further usage is possible by creating a standardized database on the parameters of the tool: the adhesive component of the friction cutting coefficient for processing of a specific pair of cutting and tool materials (or tool coating material) and the impacts of the cutting-edge radius on cutting efficiency of a particular material.

关键词： edge cutting tool finite element model precision machining cutting process industrial growth simulation design optimization function friction coefficient

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Multiple-objective optimization of a reconfigurable assembly system via equipment selection and sequence planning

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COMPUTERS & INDUSTRIAL ENGINEERING 2022年第PartA期172卷

作者： Yang, Jiangxin Liu, Fan Dong, Yafei Cao, Yanlong Cao, Yanpeng Zhejiang Univ Sch Mech Engn State Key Lab Fluid Power & Mechatron Syst Hangzhou 310027 Peoples R China Zhejiang Univ Sch Mech Engn Key Lab Adv Mfg Technol Zhejiang Prov Hangzhou 310027 Peoples R China

With the development of society and technology, the modern manufacturing system is required to handle unpredictable and rapidly changing market demands during various demand periods. This is a new challenge to the production scheduling of the production line, which requires a faster and smarter response to changes in production demand. To meet the challenge, the reconfigurable manufacturing system (RMS) has emerged as a competitive and promising manufacturing model. The reconfigurable assembly system (RAS), a critical feature of RMS, can be seamlessly incorporated into multi-variety, variable-batch, multi-functional, and fast -delivery manufacturing modes, opening up the possibility of rapid changes for production scheduling. In this paper, we first build a RAS model that can more accurately represent scheduling problems that may occur in real-world industrial operations. More specifically, we consider the assembly process of products could be divided into a number of major steps which are performed in different stations and optimize the assembly sequence of products and the equipment selection within individual assembly stations. After that, three objective functions corresponding to the workload balance, reconfiguration/assembly cost, and lead time are proposed to jointly optimize the assembly sequence and the equipment selection in individual assembly stations. Finally, a hybrid particle swarm optimization (MOHPSO) method is utilized to solve the multiple -objective optimization problem, which combines the advantages of particle swarm optimization and the hybrid method. Experimental results show the superiority of the proposed MOHPSO method over other alternatives including MOPSO and NSGA-II, achieving lower Spacing Metric (SM) and Mean Ideal Distance (MID) indexes and is suitable for solving production scheduling problems.

关键词： Reconfigurable manufacturing system (RMS) Reconfigurable assembly system (RAS) optimization function Multiple-objective hybrid particle swarm optimization (MOHPSO)

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Reliability-based calibration of partial factors for the design of membrane structures

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ENGINEERING STRUCTURES 2020年 214卷 110632-110632页

作者： De Smedt, Elien Mollaert, Marijke Caspeele, Robby Botte, Wouter Pyl, Lincy Vrije Univ Brussel Pleinlaan 2 B-1050 Brussels Belgium Univ Ghent Technol Pk Zwijnaarde 60 B-9052 Ghent Belgium

Membrane structures are widely used because of their lightweight properties and expressive architectural shapes. However, there does not yet exist a unified design approach for membrane structures as is available for conventional buildings. Because of their flexibility, membrane structures exhibit a different structural behaviour than conventional buildings. Membrane structures are doubly curved, prestressed and the prestress contributes to the stiffness. The structural response of these structures is non-linear, and the hanging and arching directions interact. A probabilistic framework for tensioned membrane structures is developed herein. Using this tool, partial factors are calibrated for a representative tensioned hypar membrane structure made of PVC-coated polyester fabric. Reliability analyses are performed using a First Order Reliability Method in combination with Latin Hypercube Sampling. The approach is illustrated for two load cases, i.e. considering snow load and wind uplift load, respectively. Three hypars are investigated, each with a different rise to span ratio. The partial factors are determined through a minimisation process. As a result of the performed process, the recommended partial factor for prestress is 1.0, for snow load is 2.0 and for wind uplift load is 2.0 for the investigated membrane structure. In this study, the hanging direction under snow load proves to be decisive for the calibration of the partial factors. The obtained partial factors are not in line with the partial factors found in the Eurocode (1.5 for variable loads). Alternatively, when considering a partial factor for snow load and wind uplift load of 1.5, partial factor for prestress should be increased to 1.2 for the structural type which have been investigated. The application of Latin Hypercube Sampling in combination with the structural analysis of membrane structures enables to perform the reliability analysis calculations in a more computationally efficient way. Moreov

关键词： Membrane structures Reliability analysis optimization function First order reliability method Latin hyper cube sampling

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A unified total variation method for underwater image enhancement

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KNOWLEDGE-BASED SYSTEMS 2022年 255卷

作者： Ding, Xueyan Wang, Yafei Liang, Zheng Fu, Xianping Dalian Maritime Univ Informat Sci & Technol Sch Dalian 116026 Peoples R China Pengcheng Lab Shenzhen 518055 Guangdong Peoples R China

Underwater images usually suffer from color casts and low contrast due to the absorption and scattering of light by the water medium. The degradation is caused not only by the light attenuation on the scene-sensor path but also by the light attenuation on the water surface-scene path. To eliminate the dual-path light attenuation, we propose a novel unified total variation method based on an extended underwater imaging model. Unlike previous variation-based methods that only consider light propagation along the scene-sensor path, we additionally include light propagation along the water surface-scene path in the underwater imaging model. In the proposed variational framework, we transform underwater image enhancement into two subproblems and construct different prior knowledge-guided optimization functions for them. The two subproblems aim to remove the light attenuation along the scene-sensor and surface-scene paths. Moreover, we present an alternating direction minimization algorithm based on an augmented Lagrange multiplier to address the opti-mization problems. The subjective and objective experimental results on underwater images with different attenuation characteristics demonstrate that the proposed method achieves good performance in underwater image enhancement. (c) 2022 Elsevier B.V. All rights reserved.

关键词： Underwater image enhancement Unified total variation Light propagation optimization function

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Spam message detection using Danger theory and Krill herd optimization

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COMPUTER NETWORKS 2021年 199卷 108453-108453页

作者： Sharaff, Aakanksha Kamal, Chandramani Porwal, Siddhartha Bhatia, Surbhi Kaur, Kuljeet Hassan, Mohammad Mehendi Natl Inst Technol Dept Comp Sci & Engn Raipur Madhya Pradesh India Manav Rachna Int Inst Res & Studies Faridabad India Univ Quebec Ecole Technol Super Montreal PQ Canada King Saud Univ Coll Comp & Informat Sci Dept Informat Syst Riyadh Saudi Arabia King Saud Univ Res Chair Smart Technol Riyadh Saudi Arabia

Due to proliferation of online posts and rise in the active social media users, fraudulent activities related with spam messages have taken a spike drift. Spam is an activity by which hackers use electronic messaging system to unsolicited messages in mass content to unknown users. It can be also taken as one of the major attraction of attackers in the form of short message service (SMS) messages. Spam messages can be categorized in different categories such as business opportunity spam, trending topic spam, banking services spam etc. These problems can be tackled by confirming to the actions taken by users towards these messages. There is an urgent explicit need of practical medium in order to assist the users against these spam messages. This paper proposes a novel SMS spam filtering model based on Danger theory of Artificial Immune System (AIS). Several feature extraction and selection techniques have been applied for optimizing the algorithm and claiming an admissible accuracy. This paper uses a biologically inspired algorithm named Krill herd optimization (KHO) for the task of feature selection and various optimization functions like Quing function, Sumsquare function, Levy function etc. are applied for enhancing its performance. The Dendritic Cell Algorithm (DCA) is also incorporated with KHA as an added advantage towards achieving efficiency. Comparative results between Dendritic Cell Algorithm (DCA) with KHA and other spam filtering models have been shown in comparison with several state-of-the-art machine learning classifiers. The algorithms have been experimented by using varied optimization functions illustrated using visualization tools and results have been validated in the paper. The obtained results demonstrate an admissible accuracy of 96% that is calculated using different information retrieval metrics using recall, F -measure and precision.

关键词： Danger theory Dendritic cells Krill herd optimization (KHO) Antigen Mature context antigen value (MCAV) Co-stimulated molecules (CSM) Semi mature dendritic cells (smDC) Mature dendritic cells (mDC) Pathogen associated molecular patterns (PAMP) Neighboring motion Foraging motion Physical diffusion Crossover Mutation optimization function

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Parametric optimization of a Reactive Distillation Column for the Ethyl Tert-Butyl Ether Production

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PERIODICA POLYTECHNICA-CHEMICAL ENGINEERING 2024年第1期68卷 116-123页

作者： Serpas, Carlos E. Garcia Samborskaya, Marina A. Mityanina, Olga E. Engn Chem Technol Ctr LLC Alekseya Belentza Str 9-1 Tomsk 634050 Russia Tomsk Polytech Univ Sch Earth Sci & Engn Dept Chem Engn Lenina Ave 30 Tomsk 634050 Russia

Combined processes in chemical industry are of current increasing interest, since they present a feasible solution for capital and operating expenses optimization. Multiplicities, which are specific to combined processes, cause certain control and design difficulties, thus, parametric sensitivity analysis and defining the range of existing multiplicities are the necessary part of the sustainable design and development of the combined process. Parametric and design optimization is the way of decreasing capital and operational costs. The paper discusses optimization of the design and operating parameters of an ethyl-tert-butyl ether synthesis reactive distillation column. The research aims to perform a parametric sensitivity analysis and explore existent multiple steady states of the process. The areas of multiple steady states are established, the optimal column design is developed, the optimal operation modes are determined. The procedure suggested in the study is universally applicable for design and optimization of other reactive distillation processes.

关键词： mathematical model optimization function parametric sensitivity reactive distillation synthesis ethyl tert -butyl ether

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The Problem of Steel Cutting in the Steel Manufacturing Industry

International Core Journal of Engineering

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International Core Journal of Engineering 2021年第8期7卷 172-177页

作者： Yongyuan Wang Hangyu Meng Linqing Fei Xiaoran Liu Feiteng Li

With the continuous improvement of social productivity, steel production is increasing day by day. The consumption of raw materials is increasing, and the impact on the environment is also getting worse. The sharp rise in steel prices has led to a sharp increase in production costs and a decline in profits for all steel companies in the world. Some companies even suffered losses. Therefore, improving the utilization rate of steel plate raw materials is an urgent problem that steel companies need to solve. In the steel plate cutting problem, a perfect cutting plan can greatly increase the utilization rate of the steel plate. This method can reduce the waste of raw materials, which not only saves costs, but also helps protect the environment. According to the steel plate cutting problem encountered at this stage, this paper establishes a dynamic programming discrete set mathematical model. While considering the cost of lossy steel plate and cutting cost, we establish an optimized layout function. This function can provide a high-quality layout plan and reduce product costs.

关键词： Dynamic Programming Discrete Set Permutation and Combination optimization function

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Joint Mobile Data Collection and Wireless Energy Transfer in Wireless Rechargeable Sensor Networks

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SENSORS 2017年第8期17卷 1881-1881页

作者： Zhong, Ping Li, Ya-Ting Liu, Wei-Rong Duan, Gui-Hua Chen, Ying-Wen Xiong, Neal Cent S Univ Sch Informat Sci & Engn Changsha 410083 Peoples R China Natl Univ Def Technol Coll Comp Changsha 410073 Hunan Peoples R China Northeastern State Univ Dept Math & Comp Sci Tahlequah OK 74464 USA

In wireless rechargeable sensor networks (WRSNs), there is a way to use mobile vehicles to charge node and collect data. It is a rational pattern to use two types of vehicles, one is for energy charging, and the other is for data collecting. These two types of vehicles, data collection vehicles (DCVs) and wireless charging vehicles (WCVs), are employed to achieve high efficiency in both data gathering and energy consumption. To handle the complex scheduling problem of multiple vehicles in large-scale networks, a twice-partition algorithm based on center points is proposed to divide the network into several parts. In addition, an anchor selection algorithm based on the tradeoff between neighbor amount and residual energy, named AS-NAE, is proposed to collect the zonal data. It can reduce the data transmission delay and the energy consumption for DCVs' movement in the zonal. Besides, we design an optimization function to achieve maximum data throughput by adjusting data rate and link rate of each node. Finally, the effectiveness of proposed algorithm is validated by numerical simulation results in WRSNs.

关键词： data collection wireless charging network partition adaptive anchor selection algorithm optimization function

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