For the digitization of turbocharger, the prediction of compressor working state is essential. How to build a model with accurate prediction and less time-consuming is the premise of studying the digitization of turbo...
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For the digitization of turbocharger, the prediction of compressor working state is essential. How to build a model with accurate prediction and less time-consuming is the premise of studying the digitization of turbochargers. As the relationship between compressor parameters is obtained through experiments, it cannot be expressed by simple functional equations, so the surrogate model is often used for fitting the curve. Five surrogate models, the Kriging model, Response Surface Methodology, Artificial Neural Networks, Radial Basis Function, and Support vector machines, were used to fit and regression compressor characteristic curves. And four optimization algorithms, Particle Swarm optimization, Genetic algorithm, Gray Wolf algorithm, and Firefly algorithm, were used to optimize the model. A method to construct a hybrid surrogate model is proposed. The results show that the influencing factors of the modeling pressure ratio and efficiency at all speed groups were confirmed; Different optimization algorithms have different optimization degrees for the five surrogate models; The prediction accuracy of the hybrid surrogate model is better than the optimized model and the single model. The constructed model can be applied in the digital twins system to predict the working state of the compressor in time to achieve the purpose of rapid response.
In the last years, the carbon footprint reduction has gained great relevance in the energy industry. Thus, it is necessary to choose approaches that weight the results not only evaluating economic benefits but also em...
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In the last years, the carbon footprint reduction has gained great relevance in the energy industry. Thus, it is necessary to choose approaches that weight the results not only evaluating economic benefits but also emphasizing the environmental impact. In order to measure this impact, the key parameter is the CO 2 emission in the atmosphere. The most powerful mean to satisfy this compromise between economic benefits and emission decrease is represented by the concept of Smart Grid. A Smart Grid implies a joint participation between information network and electric grid. In order to acquire the data from the electric grid, transmit them through the IT network, compute and translate them into commands to the plant devices, an ‘intelligent brain’ is necessary. In order to embed a small local network in the larger VPP a delocalized intelligent device is necessary, able to interface with the Smart Grid. An optimization algorithm performs this function of intelligent delocalized brain by setting different set-points for the energy devices on field. In this paper a purposefully developed optimization algorithm is described, with the aim of optimizing the operations of an existent trigeneration plant managing both RES and fossil energy sources. The plant analysed is a real plant located in central Italy, provided by several generators (PV, CHP, absorption chiller, electric chiller, gas boiler and a wind turbine). The results are yielded by a MATLAB/Simulink simulation tool, where all plant devices are characterized by datasheet information and on-field measurements. The benefits evaluation of the algorithm optimized management is obtained by embedding inside Simulink the optimization logic and executing it during the simulation runtime. The performance is compared with conventional thermal led management operations simulated in the same platform. The comparison is mainly based on economic costs but also considers CO 2 emissions and primary energy consumption. The analysis t
作者:
Li, JunzhiTan, YingPeking Univ
Sch Artificial Intelligence Key Lab Machine Percept MOE Beijing 100871 Peoples R China
Heuristic algorithms are able to optimize objective functions efficiently because they use intelligently the information about the objective functions. Thus, information utilization is critical to the performance of h...
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ISBN:
(纸本)9783031096778;9783031096761
Heuristic algorithms are able to optimize objective functions efficiently because they use intelligently the information about the objective functions. Thus, information utilization is critical to the performance of heuristics. However, the concept of information utilization has remained vague and abstract because there is no reliable metric to reflect the extent to which the information about the objective function is utilized by heuristic algorithms. In this paper, the metric of information utilization ratio (IUR) is defined, which is the ratio of the utilized information quantity over the acquired information quantity in the search process. The IUR proves to be well-defined. Several examples of typical heuristic algorithms are given to demonstrate the procedure of calculating the IUR. Empirical evidences on the correlation between the IUR and the performance of a heuristic are also provided. The IUR can be an index of how sophisticated an algorithm is designed and guide the invention of new heuristics and the improvement of existing ones.
optimization of the intelligent student educational intelligent cloud architecture based on computer topic generation algorithm is studied in the paper. There is no conflict between reverse proxy mode and packet filte...
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ISBN:
(数字)9781665408370
ISBN:
(纸本)9781665408387;9781665408370
optimization of the intelligent student educational intelligent cloud architecture based on computer topic generation algorithm is studied in the paper. There is no conflict between reverse proxy mode and packet filtering mode or ordinary proxy mode. These two modes can be used in firewall devices at the same time. The reverse proxy mode is used when the external network accesses the internal network. The forward proxy or packet filtering mode is used to reject other external access. Hence, for the designed model, this will be used as the cloud basis architecture. According to the regulatory cloud architecture design, its network can be divided into front-end service network and back-end resource high-speed synchronization network. This type of layered model is used to implement the intelligent student educational smart cloud architecture based on computer topic generation algorithm. Through the testing and implementation, the overall performance is presented.
The application of optimization algorithms to adaptive motion control is proposed in this paper. In order to provide optimal system response, optimization algorithm is used as adjustment mechanism of controller coeffi...
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The application of optimization algorithms to adaptive motion control is proposed in this paper. In order to provide optimal system response, optimization algorithm is used as adjustment mechanism of controller coefficients. Most of optimization algorithms are not able to work in continuous optimization mode and with non-constant search space (i.e. dataset). For this reason, the introduction of a novel approach, Adaptive Procedure for optimization algorithms (APOA), that allows to apply most of optimization algorithms to adaptation process seems to be necessary. Such an algorithm is innovative, due to its universality in terms of applied optimization algorithm. Its application allows to obtain optimal motion control in modern electric drives. The proposed APOA is presented together with the novel desired-response adaptive system (DRAS) approach for repetitive processes. This solution provides unchanged system response regardless of plant parameters variation or external disturbances. The developed adaptive approach based on optimization algorithm is implemented in permanent magnet synchronous motor (PMSM) drive to adapt state feedback speed controller during moment of inertia variations. Since the proposed DRAS is model-free approach, the adaptation procedure is immune to issues related to plant parameters mismatch. The obtained results prove that proposed adaptive speed controller for PMSM assures desired system response regardless of the moment of inertia variation. (C) 2021 ISA. Published by Elsevier Ltd. All rights reserved.
Electric tractors driven by dual motors have become a critical research topic in the field of pure electric tractor *** a key component of the transmission system,the optimization of the internal parameters of the pow...
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Electric tractors driven by dual motors have become a critical research topic in the field of pure electric tractor *** a key component of the transmission system,the optimization of the internal parameters of the power-coupled transmission gearbox has a crucial impact on the power transmission of the whole *** work combines the characteristics of low speed and high torque during tractor operation,and adopts the transmission form of double motor input and double planetary group coupling output to design the transmission structure of the ***,this paper proposes a dynamic optimization method of the transmission system based on the Improved Deep Deterministic Policy Gradient(IDDPG)algorithm,which realizes the optimization of the gear ratio of the transmission system by constructing a virtual prototype and hardware-in-the-loop simulation *** transport mode,the optimized gear ratios shorten the acceleration time of the tractor from 0-20 km/h by 13.6%and increase the motor efficiency by 10%;in rotary mode,the acceleration performance is improved by 28.5%and the motor efficiency is increased by 5%.The study shows that the proposed method is significantly better than the traditional static design and provides a new technical path for the intelligent optimization of the electric tractor drive train,while promoting the efficient and sustainable development of agricultural machinery.
A self-adaptive algorithm is proposed in this study to optimize optical parameters, such as correlated color temperature (CCT), color rendering index (CRI), and synthesized spectra, in a trichromatic white light-emitt...
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ISBN:
(数字)9781510652095
ISBN:
(纸本)9781510652095;9781510652088
A self-adaptive algorithm is proposed in this study to optimize optical parameters, such as correlated color temperature (CCT), color rendering index (CRI), and synthesized spectra, in a trichromatic white light-emitting diode (WLED) system. The key contributions of this algorithm include automatically finding target CCT values in different seasons and time periods, and optimizing the CRI values simultaneously under various CCT values. Comparing with the conventionally used algorithm for spectrum optimization, the realization of target values and running time of the proposed algorithm behaves excellent, which are significant in realization of real-time and automatic control in intelligent lighting.
The employment of Low Impact Development (LID) facilities is an effective means to alleviate urban flood in the context of climate change and urbanization. Existing methods for evaluating the hydrological reduction an...
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The employment of Low Impact Development (LID) facilities is an effective means to alleviate urban flood in the context of climate change and urbanization. Existing methods for evaluating the hydrological reduction and control effect of LID facilities are mostly based on hydrological models, which have inherent shortages in accurate flood process simulation. In this study, a fully-distributed bidirectional-coupled hydrodynamic model based on the Finite Volume Coastal Ocean Model (FVCOM) and a one-dimensional drainage pipe model is used to evaluate the effectiveness of LID facilities combining the Coevolutionary Constrained Multi-objective optimization (CCMO) algorithm. The proposed method is applied to investigate the responses of LID facilities effectiveness in hydrological reduction and control to rainfall patterns in the Yuelai New City, Chongqing, China. Results show that the overflow volume and peak overflow under unimodal rainfall are larger than those under other rainfall patterns. The time lag between initial and peak overflow under unimodal rainfall is the shortest, and it is shorter under small rainfall return period. The flood reduction and delay effect of LID facilities under unimodal rainfall is lower than that under bimodal rainfall, and it is the best under uniform rainfall. At low costs, the peak flood reduction effect of combined LID facilities may be lower than that of a single LID facility with strong permeability, but as costs continue to increase, combined LID facilities show its superiority. The proposed optimization-simulation method is of great significance for environmental managers to seek best solutions in urban flood control.
Effective management for the maintenance of water dispensers dispersed throughout an academic campus is essential for ensuring the quality of drinking water. Conventionally, water dispenser maintenance is conducted ap...
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Effective management for the maintenance of water dispensers dispersed throughout an academic campus is essential for ensuring the quality of drinking water. Conventionally, water dispenser maintenance is conducted approximately bimonthly or when a passive fault notice is obtained. This maintenance frequency usually results in ineffective allocation of maintenance staff and poor maintenance quality. This study proposes a new model for campus facility maintenance management that enables maintenance staff to maintain water dispensers at the optimal time and select the shortest maintenance path. The proposed model was developed using the maintenance information of the Construction Operations Building Information Exchange obtained from building information models of multiple buildings, water dispenser operation data from a water dispenser monitoring module, and an optimization algorithm developed by integrating Dijkstra's algorithm, simulated annealing, and a genetic algorithm to identify the shortest maintenance path. The proposed model was tested on a campus in Northern Taiwan. The application results revealed that maintenance strategies could be systematically established to determine the optimal time to dispatch maintenance staff based on the lowest unit cost criterion;this approach was also used to identify the shortest maintenance path through multiple buildings.
We propose the concept of thermal demultiplexer, which can split the heat flux in different frequency ranges intodifferent directions. We demonstrate this device concept in a honeycomb lattice with dangling atoms. Fro...
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We propose the concept of thermal demultiplexer, which can split the heat flux in different frequency ranges intodifferent directions. We demonstrate this device concept in a honeycomb lattice with dangling atoms. From the view ofeffective negative mass, we give a qualitative explanation of how the dangling atoms change the original transport *** first design a two-mass configuration thermal demultiplexer, and find that the heat flux can flow into different ports incorresponding frequency ranges roughly. Then, to improve the performance, we choose the suitable masses of danglingatoms and optimize the four-mass configuration with genetic algorithm. Finally, we give out the optimal configuration witha remarkable effect. Our study finds a way to selectively split spectrum-resolved heat to different ports as phonon splitter,which would provide a new means to manipulate phonons and heat, and to guide the design of phononic thermal devices inthe future.
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