• Nuclear Engineering and Technology
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• 제54권8호
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• pp.2852-2858
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• 2022

A proton therapy facility is under development at Huazhong University of Science and Technology (HUST). To meet the need for fast energy changes during treatments, a beamline control system (BCS) has been designed and implemented. The BCS coordinates and controls various beamline devices by adopting a distributed architecture divided into three layers: the client, server, and device layers. Among these, the design of the server layer is the key to realize fast energy changes. The server layer adopts the submodule programming paradigm and optimizes the data interface among modules, allowing the main workflow to be separated from the device workflow and data. Furthermore, this layer uses asynchronous, multithreaded, and thread-locking methods to improve the system's ability to operation efficiently and securely. Notably, to evaluate the changing energy status over time, a dynamic node update method is adopted, which can dynamically adjust the update frequency of variable nodes. This method not only meets the demand for fast updates on energy changes but also reduces the server's communication load in the steady state. This method is tested on a virtual platform, and the results are as expected.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권3호
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• pp.980-998
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• 2023

In Low Earth Orbit (LEO) satellite networks, satellites operate fast and the inter-satellite link change period is short. In order to sense the spectrum state in LEO satellite networks in real-time, a space-based satellite network intelligent spectrum sensing algorithm based on artificial neural network (ANN) is proposed, while Geosynchronous Earth Orbit (GEO) satellites are introduced to make fast and effective judgments on the spectrum state of LEO satellites by using their stronger arithmetic power. Firstly, the visibility constraints between LEO satellites and GEO satellites are analyzed to derive the inter-satellite link building matrix and complete the inter-satellite link situational awareness. Secondly, an ANN-based energy detection (ANN-ED) algorithm is proposed based on the traditional energy detection algorithm and artificial neural network. The ANN module is used to determine the spectrum state and optimize the traditional energy detection algorithm. GEO satellites are used to fuse the information sensed by LEO satellites and then give the spectrum decision, thereby realizing the inter-satellite spectrum state sensing. Finally, the sensing quality is evaluated by the analysis of sensing delay and sensing energy consumption. The simulation results show that our proposed algorithm has lower complexity, the sensing delay and sensing energy consumption compared with the traditional energy detection method.

• Advances in Energy Research
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• 제6권2호
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• pp.103-129
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• 2019

While global demand for energy increases annually, at the same time the demand for carbon-free, sulphur-free and NO_x-free energy sources grows considerably. This state poses a challenge in the research for newer sources like biomass and shale gas as well as renewable energy resources such as solar, wind, geothermal and hydraulic energy. Although wave energy also is a form of renewable energy it has not fully been exploited technically and economically so far. This study tries to explain those reasons in which it is beyond doubt that the demand for wave energy will soon increase as fossil energy resources are depleted and environmental concerns gain more importance. The electrical energy supplied to the grid shall be produced from wave energy whose conversion devices can basically work according to three different systems. i. Systems that exploit the motions or shape deformations of their mechanisms involved, being driven by the energy of passing waves. ii. Systems that exploit the weight of the seawater stored in a reservoir or the changes of water pressure by the oscillations of wave height, iii. Systems that convert the wave motions into air flow. One of the aims of this study is to present the classification deficits of the wave energy converters (WECs) of the "wave developers" prepared by the European Marine Energy Center, which were to be reclassified. Furthermore, a new classification of all WECs listed by the European Marine Energy Center was arranged independently. The other aim of the study is to assess the technological state of the art of these WECs designed and/or produced, to obtain an overview on them.

• Structural Engineering and Mechanics
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• 제76권6호
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• pp.709-724
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• 2020

The typical inerter system, the tuned viscous mass damper (TVMD), has been proven to be efficient. It is characterized by an energy-dissipation-enhancement effect, whereby the dashpot deformation of TVMD can be amplified for enhanced energy dissipation efficiency. However, existing studies related to TVMD have mainly been performed on elastic structures, so the working mechanism remains unclear for nonlinear structures. To deal with this, an energy-spectrum analysis framework is developed systematically for classic bilinear hysteretic structures with TVMD. Considering the soil effect, typical bedrock records are propagated through the soil deposit, for which the designed input energy spectra are proposed by considering the TVMD parameters and structural nonlinear properties. Furthermore, the energy-dissipation-enhancement effect of TVMD is quantitatively evaluated for bilinear hysteretic structures. The results show that the established designed input energy spectra can be employed to evaluate the total energy-dissipation burden for a nonlinear TVMD structure. Particularly, the stiffness of TVMD is the dominant factor in adjusting the total input energy. Compared with the case of elastic structures, the energy-dissipation-enhancement effect of TVMD for nonlinear structures is weakened so that the expected energy-dissipation effect of TVMD is replaced by the accumulated energy dissipation of the primary structure.

• 조명전기설비학회논문지
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• 제28권10호
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• pp.27-36
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• 2014

Network analysis applications in energy management systems play a key role in the economic and reliable operation of power systems. In order to provide operators with useful network information, the accurate results of topology processing, state estimation, power flow, and contingency analysis must be simulated. This paper proposes a validation methodology of network analysis applications in energy management systems. The energy management systems was checked to ensure that it meets the originally specified functions based on the proposed methodology. In addition, the performance of state estimation is evaluated with the reference of the proposed methodology. The proposed methodology is being conducted by energy management systems and the Korean power systems have been utilized for the test systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권9호
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• pp.4320-4333
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• 2017

Energy-efficient virtual resource allocation algorithm has become a hot research topic in cloud computing. However, most of the existing allocation schemes cannot ensure each type of resource be fully utilized. To solve the problem, this paper proposes a virtual machine (VM) allocation algorithm on the basis of multi-dimensional resource, considering the diversity of user's requests. First, we analyze the usage of each dimension resource of physical machines (PMs) and build a D-dimensional resource state model. Second, we introduce an energy-resource state metric (PAR) and then propose an energy-aware multi-dimensional resource allocation algorithm called MRBEA to allocate resources according to the resource state and energy consumption of PMs. Third, we validate the effectiveness of the proposed algorithm by real-world datasets. Experimental results show that MRBEA has a better performance in terms of energy consumption, SLA violations and the number of VM migrations.

• 한국태양에너지학회 논문집
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• 제34권4호
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• pp.23-29
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• 2014

Recently, in power system studies, Multiple Energy Carriers (MECs) such as Energy Hub has been broadly utilized in power system planners and operators. Particularly, Energy Hub performs one of the most important role as the intermediate in implementing the MECs. However, it still needs to be put under examination in both modeling and operating concerns. For instance, a probabilistic optimization model is treated by a robust global optimization technique such as multi-agent genetic algorithm (MAGA) which can support the online economic dispatch of MECs. MAGA also reduces the inevitable uncertainty caused by the integration of selected input energy carriers. However, MAGA only considers current state of the integration of selected input energy carriers in conjunctive with the condition of smart grid environments for decision making in Energy Hub. Thus, in this paper, we propose an immune algorithm based Multiple Energy Carriers System which can adopt the learning process in order to make a self decision making in Energy Hub. In particular, the proposed immune algorithm considers the previous state, the current state, and the future state of the selected input energy carriers in order to predict the next decision making of Energy Hub based on the probabilistic optimization model. The below figure shows the proposed immune algorithm based Multiple Energy Carriers System. Finally, we will compare the online economic dispatch of MECs of two algorithms such as MAGA and immune algorithm based MECs by using Real Time Digital Simulator (RTDS).

• Geomechanics and Engineering
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• 제20권1호
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• pp.55-66
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• 2020

The damage or failure of coal rock is accompanied by energy accumulation, dissipation and release. It is crucial to study the energy evolution characteristics of coal rock for rock mechanics and mining engineering applications. In this paper, coal specimens sourced from the Xinhe mine located in the Jining mining area of China were initially subjected to uniaxial compression, and the micro-parameters of the two-dimensional particle flow code (PFC^2D) model were calibrated according to the experimental test results. Then, the PFC^2D model was used to subject the specimens to substantial uniaxial compression, and the energy evolution laws of coal specimens with various schemes were presented. Finally, the elastic energy storage ratio m was investigated for coal rock, which described the energy conversion in coal specimens with various arrangements of preformed holes. The arrangement of the preformed holes significantly influenced the characteristics of the crack initiation stress and energy in the prepeak stage, whereas the characteristics of the cumulative crack number, failure pattern and elastic strain energy during the loading process were similar. Additionally, the arrangement of the preformed holes altered the proportion of elastic strain energy U_e in the total energy in the prepeak stage, and the probability of rock bursts can be qualitatively predicted.

• 대한방사선방어학회:학술대회논문집
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• 대한방사선방어학회 2009년도 추계 학술발표
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• pp.108-109
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• 2009

• Asian-Australasian Journal of Animal Sciences
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• 제25권10호
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• pp.1430-1438
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• 2012

The present experiment was conducted to determine the digestible energy (DE), metabolizable energy (ME) content, and the apparent total tract digestibility (ATTD) of energy in growing pigs fed diets containing one of ten cottonseed meals (CSM) collected from different provinces of China and to develop in vitro prediction equations for DE and ME content from chemical composition of the CSM samples. Twelve growing barrows with an initial body weight of $35.2{\pm}1.7$ kg were allotted to two $6{\times}6$ Latin square designs, with six barrows and six periods and six diets for each. A corn-dehulled soybean meal diet was used as the basal diet, and the other ten diets were formulated with corn, dehulled soybean meal and 19.20% CSM. The DE, ME and ATTD of gross energy among different CSM sources varied largely and ranged from 1,856 to 2,730 kcal/kg dry matter (DM), 1,778 to 2,534 kcal/kg DM, and 42.08 to 60.47%, respectively. Several chemical parameters were identified to predict the DE and ME values of CSM, and the accuracy of prediction models were also tested. The best fit equations were: DE, kcal/kg DM = 670.14+31.12 CP+659.15 EE with $R^2$ = 0.82, RSD = 172.02, p<0.05; and ME, kcal/kg DM = 843.98+25.03 CP+673.97 EE with $R^2$ = 0.84, RSD = 144.79, p<0.05. These results indicate that DE, ME values and ATTD of gross energy varied substantially among different CSM sources, and that some prediction equations can be applied to predict DE and ME in CSM with an acceptable accuracy.