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SSRN 2022年

作者： Hu, Yanglin Chen, Chuanmin Liu, Songtao Zhou, Yingran Jia, Wenbo Cao, Yue Hebei Key Lab of Power Plant Flue Gas Multi-Pollutants Control Department of Environmental Science and Engineering North China Electric Power University Baoding071003 China MOE Key Laboratory of Resources and Environmental Systems Optimization College of Environmental Science and Engineering North China Electric Power University Beijing102206 China

In this study, corrosion behavior of Q235 carbon steel (CS) under B. cereus agent in simulated cooling water was evaluated. Weight loss study proved B. cereus agent possessed anti-corrosion efficiencies of 92.84% and 73.88% for 3d and 14d rotation tests respectively. Electrochemical measurements indicated added B. cereus agent increased the charge transfer resistance and reduced corrosion current density. The corrosion inhibition mechanisms of B. cereus agent involves forming biofilm, consuming dissolved oxygen, and generating biomineralized layer to prevent corrosive medium contact. Thus, B. cereus agent provided a biological strategy for the industrial cooling water anti-corrosion application. © 2022, The Authors. All rights reserved.

关键词： Corrosion inhibitors

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A Modified Asynchronous PSO Algorithm

A Modified Asynchronous PSO Algorithm

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Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC

作者： Daxin Tian Junjie Hu Haiying Xia He Liu The Ministry of Public Security of China Key Lab of Urban ITS Technology Optimization and Integration Hefei Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beihang University Beijing China Research Institute of Highway Ministry Transport Beijing China Department of CPLA The Quartermaster Equipment Institute of the General Logistics Beijing China

ISBN: (纸本)9781467372121

To analyze the convergence of PSO algorithm, a method based on two order constant coefficient recursive method is proposed in this paper. A new way to modify PSO and APSO algorithm achieved by adjusting the progress of algorithm is also proposed, thus forming MPSO and MAPSO algorithm, and this paper also presents Auto-regulative PSO algorithm which can automatically adjust parameters in the iterations. Ten basic functions are used for experiments to study the performance of the algorithms, and the results of experiments prove that Auto-regulative PSO algorithm and MAPSO are superior to MPSO and APSO respectively.

关键词： particle swarm optimisation iterative methods iterative methods Particle swarm optimization parametric subharmonic oscillator Methylprednisolone Suleptanate algorithms

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Inverse Design of a Nurbs-Based Chiral Metamaterial Via Machine Learning for Programmable Mechanical Deformation

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SSRN 2024年

作者： Hou, Xiuhui Zhao, Wenhao Zhang, Kai Deng, Zichen School of Mechanics Civil Engineering and Architecture Northwestern Polytechnical University Xi’an710072 China MIIT Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical University Xi’an710072 China School of Aeronautics Northwestern Polytechnical University Xi’an710072 China State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial Equipment Dalian University of Technology Liaoning Dalian116024 China

Chiral metamaterials are manmade structures with extraordinary mechanical properties derived from their special geometrical design instead of the chemical composition. To make the mechanical deformation programmable, the Non-Uniform Rational B-Spline (NURBS) curves are taken to replace the traditional ligament boundaries of the chiral structure. The Neural Networks are innovatively inserted into the calculation of mechanical properties of the chiral structure instead of finite element methods to improve computational efficiency. For the problem of finding structure configuration with specified mechanical properties, such as Young’s modulus, Poisson’s ratio or deformation, an inverse design method using the Neural Network-based proxy model is proposed to build the relationship between mechanical properties and geometric configuration. To satisfy some more complex deformation requirements, a non-homogeneous inverse design method is proposed and verified through simulation and experiments. Numerical and test results reveal the high computational efficiency and accuracy of the proposed method in the design of chiral metamaterials. © 2024, The Authors. All rights reserved.

关键词： Numerical methods

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Inverse Design of a Nurbs-Based Chiral Metamaterial Via Machine Learning for Programmable Mechanical Deformation

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SSRN 2023年

Chiral metamaterials are manmade structures with extraordinary mechanical properties derived from their special geometrical design instead of the chemical composition. To make the mechanical deformation programmable, the Non-Uniform Rational B-Spline (NURBS) curves are taken to replace the traditional ligament boundaries of the chiral structure. The Neural Networks are innovatively inserted into the calculation of mechanical properties of the chiral structure instead of finite element methods to improve computational efficiency. For the general problem of structure configuration determination with specified mechanical properties, such as Young’s modulus, Poisson’s ratio or deformation, an inverse design method using the Neural Network-based surrogate model is proposed to build the relationship between local geometric configuration and overall deformation. To satisfy some more complex deformation requirements, a non-homogeneous inverse design method is proposed and verified through simulation and experiments. Numerical and test results reveal the high computational efficiency and accuracy of the proposed method in the device design of chiral metamaterials. © 2023, The Authors. All rights reserved.

关键词： Numerical methods

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An Evaluation Model for Epidemic Routing in VANETs

An Evaluation Model for Epidemic Routing in VANETs

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Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC

作者： Daxin Tian Yue Yang Haiying Xia Guohui Zhang Ministry of Public Security of China Key Lab of Urban ITS Technology Optimization and Integration Hefei China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beihang University Beijing China Research Institute of Highway Ministry Transport Beijing China School of Information Engineering Academy of Armored Forces Engineering Beijing China

ISBN: (纸本)9781467372121

Epidemic routing has emerged as a promising candidate for providing message dissemination method in vehicular ad hoc networks. In this paper, we present a novel model to evaluate the capacity of epidemic routing in vehicular networks with considering the traffic signal control as a significant factor in urban area. Our study reveal that epidemic routing can behave differently in various traffic signal control situations where messages can be forwarded by vehicles passing through the intersections from other directions. The simulation results prove the accuracy of the model.

关键词： Roads Vehicles Delays Routing Turning Simulation Dynamic programming

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Received Power Prediction for Suburban Environment based on Neural Network

Received Power Prediction for Suburban Environment based on ...

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International Conference on Information Networking

作者： Lina Wu Danping He Ke Guan Bo Ai César Briso-Rodríguez Tianyun Shui Chenji Liu Liju Zhu Xiaopeng Shen State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China School of Systems and Telecommunications Engineering Technical University of Madrid Madrid Spain Radio Network Optimization Center Jiangxi Mobile Communication Company Limited China Overseas consulting co. ltd China international engineering consulting corporation Beijing China

ISBN: (数字)9781728141992

ISBN: (纸本)9781728142005

Accurate received power prediction is important to wireless network planning and optimization, and appropriate channel modeling approach is highly demanded. The existing channel modeling approaches mainly include deterministic models and stochastic models. The deterministic models usually require detailed three-dimensional (3D) environment model including geometry and material information. The stochastic models are based on mathematical expressions which are difficult in describing complex environments. For mountaineous and suburban scenarios, where the environment is complex and difficult to reconstructed, both channel modeling approaches are limited. In this work, back propagation (BP) neural network which is the most widely used artificial neural network (ANN), is employed to accurately predict received power in the suburban scenario. An environmental feature is defined, which can describe the propagation environment only by using limited environmental types instead of complex 3D environment reconstruction. Furthermore, the low-dimensional environmental feature is generated by principal component analysis (PCA). From the measurements, the information of base station (BS) and the receiver (Rx), including 3D locations, frequency, transmitted power, angle information of antenna, and the received power of all the locations are obtained. The information of BS and Rx is combined with environmental features to form datasets for ANN training and testing. The training samples are randomly selected with different percentage from the formed datasets. The mean error, standard deviation and the prediction accuracy of BP networks are explored in the work, which will help researchers to carry out network planning and communication system design.

关键词： Mathematical model Feature extraction Training Predictive models Principal component analysis Neural networks Three-dimensional displays

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Peak Estimation of Time Delay systems Using Occupation Measures

Peak Estimation of Time Delay Systems Using Occupation Measu...

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IEEE Conference on Decision and control

作者： Jared Miller Milan Korda Victor Magron Mario Sznaier Automatic Control Laboratory (IfA) ETH Zürich Zürich Switzerland ECE Department Robust Systems Lab Northeastern University Boston MA Polynomial OPtimization Team LAAS-CNRS Toulouse France Faculty of Electrical Engineering Czech Technical University in Prague Prague Czech Republic Institut de Mathématiques de Toulouse France

This work proposes a method to compute the maximum value obtained by a state function along trajectories of a Delay Differential Equation (DDE). An example of this task is finding the maximum number of infected people in an epidemic model with a nonzero incubation period. The variables of this peak estimation problem include the stopping time and the original history (restricted to a class of admissible histories). The original nonconvex DDE peak estimation problem is approximated by an infinite-dimensional Linear Program (LP) in occupation measures, inspired by existing measure-based methods in peak estimation and optimal control. This LP is approximated from above by a sequence of Semidefinite Programs (SDPs) through the moment-Sum of Squares (SOS) hierarchy. Effectiveness of this scheme in providing peak estimates for DDEs is demonstrated with provided examples.

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Outlier-resistant distributed fusion filtering for nonlinear discrete-time singular systems under a dynamic event-triggered scheme

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Frontiers of Information Technology & Electronic Engineering 2024年第2期25卷 237-249页

作者： Zhibin HU Jun HU Cai CHEN Hongjian LIU Xiaojian YI Department of Applied Mathematics Harbin University of Science and TechnologyHarbin150080China Heilongjiang Provincial Key Laboratory of Optimization Control and Intelligent Analysis for Complex Systems Harbin University of Science and TechnologyHarbin150080China School of Automation Harbin University of Science and TechnologyHarbin150080China School of Mathematics and Physics Anhui Polytechnic UniversityWuhu241000China School of Mechatronical Engineering Beijing Institute of TechnologyBeijing100081China Yangtze Delta Region Academy of Beijing Institute of Technology Jiaxing314003China Tangshan Research Institute Beijing Institute of TechnologyTangshan063099China

This paper investigates the problem of outlier-resistant distributed fusion filtering(DFF)for a class of multi-sensor nonlinear singular systems(MSNSSs)under a dynamic event-triggered scheme(DETS).To relieve the effect of measurement outliers in data transmission,a self-adaptive saturation function is ***,to further reduce the energy consumption of each sensor node and improve the efficiency of resource utilization,a DETS is adopted to regulate the frequency of data *** the addressed MSNSSs,our purpose is to construct the local outlier-resistant filter under the effects of the measurement outliers and the DETS;the local upper bound(UB)on the filtering error covariance(FEC)is derived by solving the difference equations and minimized by designing proper filter ***,according to the local filters and their UBs,a DFF algorithm is presented in terms of the inverse covariance intersection fusion *** such,the proposed DFF algorithm has the advantages of reducing the frequency of data transmission and the impact of measurement outliers,thereby improving the estimation ***,the uniform boundedness of the filtering error is discussed and a corresponding sufficient condition is ***,the validity of the developed algorithm is checked using a simulation example.

关键词： Distributed fusion filtering Multi-sensor nonlinear singular systems Dynamic event-triggered scheme Outlier-resistant filter Uniform boundedness

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Towards Constraint-Based Burden-Aware Models for Metabolic Engineering

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IFAC-PapersOnLine 2024年第14期58卷 247-252页

作者： M. Maton F.N. Santos-Navarro J. Picó Ph. Bogaerts A. Vande Wouwer Systems Estimation Control and Optimization (SECO) Laboratory University of Mons Mons 7000 Belgium 3BIO-BioControl Université Libre de Bruxelles. Av. F.D. Roosevelt 50 C.P. 165/61 Brussels 1050 Belgium Synthetic Biology and Biosystems Control Lab I.U. de Automática e Informática Industrial (ai2) Universitat Politècnica de Valencia. 46022 Camino de Vera S/N Valencia Spain

Over the years, hundreds of applications have proved the effectiveness of constraint-based methods to validate the definition of metabolic networks, determine the robustness of metabolic models, and analyze the flow of metabolites through a network. However, stoichiometric models do not include information on flux capacity via enzymatic activity. Methods combining biological data from genome to metabolome have been developed to obtain improved flux predictions and constrain the range of possible flux distributions. Yet, these models still lack relevant information to design de novo metabolic pathways. Expressing the exogenous enzymes induces a cell burden due to competition for cell resources between the exogenous genes and the endogenous host ones, compromising the performance of the designed pathway. Thus, optimal selection of the expression strength of the pathway enzymes is still a challenge. Host-aware models have been developed to tackle cell burden in the context of designing increasingly complex synthetic genetic circuits in synthetic biology. This paper suggests a method to integrate host-aware gene expression models with constraint-based modeling to maximize the flux through an exogenous pathway by optimizing promoter and ribosome binding site strengths, crucial parameters that define the required transcription and translation strengths of the pathway enzymes’ genes. This study considers the formation of p-coumaric acid, shows promising results, and paves the way for further investigations.

关键词： Metabolic flux analysis burden-aware modeling synthetic-gene circuit multi-scale modeling enzymatic activity synthetic biology

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Rational design of MOF@COF composites with multi-site functional groups for enhanced elimination of U(VI) from aqueous solution

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Chemosphere 2023年第1期341卷 140086页

作者： Liu, Lijie Zhao, Bing Wu, Dedong Wang, Xiangxue Yao, Wen Ma, Zixuan Hou, Hairui Yu, Shujun MOE Key Laboratory of Resources and Environmental Systems Optimization College of Environmental Science and Engineering North China Electric Power University Beijing102206 China Hebei Key Lab of Power Plant Flue Gas Multi-Pollutants Control Department of Environmental Science and Engineering North China Electric Power University Baoding071003 China School of Public Health Guangdong Medical University Dongguan523808 China

Both environment and human beings were menaced by the widespread application of radioactive uranium, high-performance and effective elimination of uranium from wastewater is of important meaning for development of environmental sustainability in the future. In this study, the water-stable MOF material and the highly crystalline COF were compounded by a mild hydrothermal strategy, which achieved efficient removal of U(VI) through the synergistic effect. The composites showed the characteristics of both COFs and MOFs, which will possess higher stability, larger surface area and faster adsorption efficiency that cannot be carried out by a single component. Batch experiments and characterizations (SEM, TEM, XRD, FT-IR, BET, XPS, etc.) indicated that UiO-66-NH2@LZU1 had more stable and multi-layer pore structure and rich active functional groups. The Langmuir model and the pseudo-second-order kinetics fitting was more suitable for the U(VI) elimination process. The greatest uranium adsorbing capacity of UiO-66-NH2@LZU1 (180.4 mg g−1) was observed to exceed the UiO-66-NH2 (108.8 mg g−1) and COF-LZU1 (65.8 mg g−1), which reached the excellent hybrid effects. Furthermore, FT-IR and XPS analyses confirmed that the most nitrogen-containing group from COF-LZU1 and oxygen-containing group of UiO-66-NH2 could be combined with U(VI). In addition, electrostatic interaction was also a mechanism during the removal process. This work displayed that UiO-66-NH2@LZU1 was a prospective hybrid material for radioactive waste remediation. The compound method and application mentioned in this work had provided a theoretical basis for designing and developing multi-functional composite adsorbents, which contributed to the development of new materials for radioactive wastewater treatment technologies. © 2023 Elsevier Ltd

关键词： Wastewater treatment

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