• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.376-382
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• 1991

In the analysis of constrained holonomic systems, the Lagange multiplier method yields a system of second-order ordinary differential equations of motion and algebraic constraint equations. Conventional holonomic or nonholonomic constraints are defined as geometric constraints in this paper. Previous works concentrate on the geometric constraints. However, if the total energy of a dynamic system can be computed from the initial energy plus the time integral of the energy input rate due to external or internal forces, then the total energy can be artificially treated as a constraint. The violation of the total energy constraint due to numerical errors can be used as information to control these errors. It is a necessary condition for accurate simulation that both geometric and energy constraints be satisfied. When geometric constraint control is combined with energy constraint control, numerical simulation of a constrained dynamic system becomes more accurate. A new convenient and effective method to implement energy constraint control in numerical simulation is developed based on the geometric interpretation of the relation between constraints in the phase space. Several combinations of energy constraint control with either Baumgarte's Constraint Violation Stabilization Method (CVSM) are also addressed.

• KIEAE Journal
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• v.2 no.4
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• pp.65-72
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• 2002

In this study, the evaluation of environmental performance of the building energy system of domestic commercial sector was carried out. Based on the theory of linear programming model, we established an evaluation model satisfying object functions and constraint conditions. Employing the model, the evaluation of building energy system was performed under the consideration of cost and environmental constraint conditions. As an evaluation tool, MARKAL (MARKet Allocation) known as a market distribution model was employed. We analyzed scenarios of Case I (Base Scenarios) through Case IX established by the combination of the components of building energy system such as glazing, building skin, core, and heat source system. According to the results of the evaluation, highest contribution on the useful energy demand was obtained from the building energy system combined with solar heat source system, when the total amounts of $CO_2$ exhaust as an environmental constraint condition is assumed to be the level of 1995.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.3
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• pp.419-429
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• 1992

본 연구에서는 면외 변형이 가능한 평면 곡선보에 수정 형상함수를 적용하여 탈락성 및 지속성 에너지에 포함된 가성구속에 의한 수치해의 거동을 고찰함과 동시에, 가성구속에 의한 오차 발생 요인이 제거된, 면외 변형이 가능한 평면 곡선보의 선형 요소를 제안하고자 한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.2873-2892
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• 2019

Reducing the interference to the licensed mobile users and obtaining the energy efficiency are key issues in cognitive heterogeneous networks. A corresponding rate loss constraint is proposed to be used for the sensing-based spectrum sharing (SBSS) model in cognitive heterogeneous networks in this paper. Resource allocation optimization strategy is designed for the maximum energy efficiency under the proposed interference constraint together with average transmission power constraint. An efficiency algorithm is studied to maximize energy efficiency due to the nonconvex optimal problem. Furthermore, the relationship between the proposed protection criterion and the conventional interference constraint strategy under imperfect sensing condition for the SBSS model is also investigated, and we found that the conventional interference threshold can be regarded as the upper bound of the maximum rate loss that the primary user could tolerate. Simulation results have shown the effectiveness of the proposed protection criterion overcome the conventional interference power constraint.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.371-372
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• 2008

In this paper, we consider wireless sensor networks with hard energy constraint, where each node is powered by a small battery. Under this hard constraint, reducing energy consumption is the most important design consideration for wireless sensor networks. Energy saving and control is an important issue, involved in the design of most sensor nodes. In this context, we focus on physical layer design where energy constraint problem can be modeled as an optimization of transmission modulation scheme[1]. Specifically, our analyses are based on energy control schemes that are relative to physical layer design on upper bound SEP MPSK in AWGN channels.

• Earthquakes and Structures
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• v.18 no.1
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• pp.45-56
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• 2020

The application of critical excitation method with displacement-based objective function for multi degree of freedom (MDOF) systems is investigated. To this end, a new critical excitation method is developed to find the critical input motion of a MDOF system as a synthetic accelerogram. The upper bound of earthquake input energy per unit mass is considered as a new constraint for the problem, and its advantages are discussed. Considering this constraint, the critical excitation method is then used to generate synthetic accelerograms for MDOF models corresponding to three shear buildings of 10, 16, and 22 stories. In order to demonstrate the reliability of generated accelerograms to estimate dynamic response of the structures, three target ground motions with considerable level of energy contents are selected to represent "real critical excitation" of each model, and the method is used to re-generate these ground motions. Afterwards, linear dynamic analyses are conducted using these accelerograms along with the generated critical excitations, to investigate the key parameters of response including maximum displacement, maximum interstory drift, and maximum absolute acceleration of stories. The results show that the generated critical excitations can make an acceptable estimate of the structural behavior compared to the target ground motions. Therefore, the method can be reliably implemented to generate critical excitation of the structure when real one is not available.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.23 no.1
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• pp.1-18
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• 2019

In contrast to the well-developed convex splitting schemes for gradient flows of two-component system, there were few efforts on applying the convex splitting idea to gradient flows of multi-component system, such as the vector-valued Cahn-Hilliard (vCH) equation. In the case of the vCH equation, one need to consider not only the convex splitting idea but also a specific method to manage the partition of unity constraint to design an unconditionally energy stable scheme. In this paper, we propose a constrained Convex Splitting (cCS) scheme for the vCH equation, which is based on a convex splitting of the energy functional for the vCH equation under the constraint. We show analytically that the cCS scheme is mass conserving and unconditionally uniquely solvable. And it satisfies the constraint at the next time level for any time step thus is unconditionally energy stable. Numerical experiments are presented demonstrating the accuracy, energy stability, and efficiency of the proposed cCS scheme.

• Environmental Engineering Research
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• v.21 no.4
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• pp.409-419
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• 2016

As a major energy consumption province, the issue about the carbon emissions in Hebei Province, China has been concerned by the government. The carbon emissions can be effectively reduced due to a more rational energy consumption structure. Thus, in this paper the constraint of low carbon emissions is considered as a foundation and four energies--coal, petroleum, natural gas and electricity including wind power, nuclear power and hydro-power etc are selected as the main analysis objects of the adjustment of energy structure. This paper takes energy cost minimum and carbon trading cost minimum as the objective functions based on the economic growth, energy saving and emission reduction targets and constructs an optimization model of energy consumption structure. And empirical research about energy consumption structure optimization in 2015 and 2020 is carried out based on the energy consumption data in Hebei Province, China during the period 1995-2013, which indicates that the energy consumption in Hebei dominated by coal cannot be replaced in the next seven years, from 2014 to 2020, when the coal consumption proportion is still up to 85.93%. Finally, the corresponding policy suggestions are put forward, according to the results of the energy structure optimization in Hebei Province.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.219-227
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• 2008

As found in research on constraint satisfaction problems, the choice of variable ordering heuristics is crucial for effective solving of constraint optimization problems. For the special problems such as energy-efficient clustering in heterogeneous wireless sensor networks, in which cluster heads have an inclination to be near a base station, we propose a new approach based on the static preferences variable orderings and provide a pnode heuristic algorithm for a specific application. The pnode algorithm selects the next variable with the highest Preference. In our problem, the preference becomes higher when the cluster heads are closer to the optimal region, which can be obtained a Priori due to the characteristic of the problem. Since cluster heads are the most dominant sources of Power consumption in the cluster-based sensor networks, we seek to minimize energy consumption by minimizing the maximum energy dissipation at each cluster heads as well as sensor nodes. Simulation results indicate that the proposed approach is more efficient than other methods for solving constraint optimization problems with static preferences.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.2914-2935
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• 2016

With the increasing popularization of cloud computing, how to reduce physical energy consumption and increase resource utilization while maintaining system performance has become a research hotspot of virtual machine deployment in cloud platform. Although some related researches have been reported to solve this problem, most of them used the traditional heuristic algorithm based on greedy algorithm and only considered effect of single-dimensional resource (CPU or Memory) on energy consumption. With considerations to multi-dimensional resource utilization, this paper analyzed impact of multi-dimensional resources on energy consumption of cloud computation. A multi-dimensional resource constraint that could maintain normal system operation was proposed. Later, a novel virtual machine deployment method (NVMDM) based on improved particle swarm optimization (IPSO) and Euclidean distance was put forward. It deals with problems like how to generate the initial particle swarm through the improved first-fit algorithm based on resource constraint (IFFABRC), how to define measure standard of credibility of individual and global optimal solutions of particles by combining with Bayesian transform, and how to define fitness function of particle swarm according to the multi-dimensional resource constraint relationship. The proposed NVMDM was proved superior to existing heuristic algorithm in developing performances of physical machines. It could improve utilization of CPU, memory, disk and bandwidth effectively and control task execution time of users within the range of resource constraint.