• Title/Summary/Keyword: Energy optimization

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A many-objective optimization WSN energy balance model

  • Wu, Di;Geng, Shaojin;Cai, Xingjuan;Zhang, Guoyou;Xue, Fei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.2
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    • pp.514-537
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    • 2020
  • Wireless sensor network (WSN) is a distributed network composed of many sensory nodes. It is precisely due to the clustering unevenness and cluster head election randomness that the energy consumption of WSN is excessive. Therefore, a many-objective optimization WSN energy balance model is proposed for the first time in the clustering stage of LEACH protocol. The four objective is considered that the cluster distance, the sink node distance, the overall energy consumption of the network and the network energy consumption balance to select the cluster head, which to better balance the energy consumption of the WSN network and extend the network lifetime. A many-objective optimization algorithm to optimize the model (LEACH-ABF) is designed, which combines adaptive balanced function strategy with penalty-based boundary selection intersection strategy to optimize the clustering method of LEACH. The experimental results show that LEACH-ABF can balance network energy consumption effectively and extend the network lifetime when compared with other algorithms.

Bayesian Optimization Analysis of Containment-Venting Operation in a Boiling Water Reactor Severe Accident

  • Zheng, Xiaoyu;Ishikawa, Jun;Sugiyama, Tomoyuki;Maruyama, Yu
    • Nuclear Engineering and Technology
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    • v.49 no.2
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    • pp.434-441
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    • 2017
  • Containment venting is one of several essential measures to protect the integrity of the final barrier of a nuclear reactor during severe accidents, by which the uncontrollable release of fission products can be avoided. The authors seek to develop an optimization approach to venting operations, from a simulation-based perspective, using an integrated severe accident code, THALES2/KICHE. The effectiveness of the containment-venting strategies needs to be verified via numerical simulations based on various settings of the venting conditions. The number of iterations, however, needs to be controlled to avoid cumbersome computational burden of integrated codes. Bayesian optimization is an efficient global optimization approach. By using a Gaussian process regression, a surrogate model of the "black-box" code is constructed. It can be updated simultaneously whenever new simulation results are acquired. With predictions via the surrogate model, upcoming locations of the most probable optimum can be revealed. The sampling procedure is adaptive. Compared with the case of pure random searches, the number of code queries is largely reduced for the optimum finding. One typical severe accident scenario of a boiling water reactor is chosen as an example. The research demonstrates the applicability of the Bayesian optimization approach to the design and establishment of containment-venting strategies during severe accidents.

Shape optimization of blended-wing-body underwater glider by using gliding range as the optimization target

  • Sun, Chunya;Song, Baowei;Wang, Peng;Wang, Xinjing
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.9 no.6
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    • pp.693-704
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    • 2017
  • Blended-Wing-Body Underwater Glider (BWBUG), which has excellent hydrodynamic performance, is a new kind of underwater glider in recent years. In the shape optimization of BWBUG, the lift to drag ratio is often used as the optimization target. However this results in lose of internal space. In this paper, the energy reserve is defined as the direct proportional function of the internal space of BWBUG. A motion model, which relates gliding range to steady gliding motion parameters as well as energy consumption, is established by analyzing the steady-state gliding motion. The maximum gliding range is used as the optimization target instead of the lift to drag ratio to optimizing the shape of BWBUG. The result of optimization shows that the maximum gliding range of initial design is increased by 32.1% though an Efficient Global Optimization (EGO) process.

Topology optimization of the photovoltaic panel connector in high-rise buildings

  • Lu, Xilin;Xu, Jiaqi;Zhang, Hongmei;Wei, Peng
    • Structural Engineering and Mechanics
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    • v.62 no.4
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    • pp.465-475
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    • 2017
  • Photovoltaic (PV) panels are used in high-rise buildings to convert solar energy to electricity. Due to the considerable energy consumption of high-rise buildings, applying PV technology is of great significance to energy saving. In the application of PV panels, one of the most important construction issues is the connection of the PV panel with the main structures. One major difficulty of the connection design is that the PV panel connection consists of two separate components with coupling and indeterminate dimension. In this paper, the gap element is employed in these two separated but coupled components, i.e., hook and catch. Topology optimization is applied to optimize and design the cross-section of the PV panel connection. Pareto optimization is conducted to operate the optimization subject to multiple load scenarios. The initial design for the topology optimization is determined by the common design specified by the Technical Code for Glass Curtain Wall Engineering (JGJ 102-2003). Gravity and wind load scenarios are considered for the optimization and numerical analysis. Post analysis is conducted for the optimal design obtained by the topology optimization due to the manufactory requirements. Generally, compared with the conventional design, the optimized connector reduces material use with improved structural characteristics.

Recurrent Ant Colony Optimization for Optimal Path Convergence in Mobile Ad Hoc Networks

  • Karmel, A;Jayakumar, C
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.9
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    • pp.3496-3514
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    • 2015
  • One of the challenging tasks in Mobile Ad hoc Network is to discover precise optimal routing solution due to the infrastructure-less dynamic behavior of wireless mobile nodes. Ant Colony Optimization, a swarm Intelligence technique, inspired by the foraging behaviour of ants in colonies was used in the past research works to compute the optimal path. In this paper, we propose a Recurrent Ant Colony Optimization (RECACO) that executes the actual Ant Colony Optimization iteratively based on recurrent value in order to obtain an optimal path convergence. Each iteration involves three steps: Pheromone tracking, Pheromone renewal and Node selection based on the residual energy in the mobile nodes. The novelty of our approach is the inclusion of new pheromone updating strategy in both online step-by-step pheromone renewal mode and online delayed pheromone renewal mode with the use of newly proposed metric named ELD (Energy Load Delay) based on energy, Load balancing and end-to-end delay metrics to measure the performance. RECACO is implemented using network simulator NS2.34. The implementation results show that the proposed algorithm outperforms the existing algorithms like AODV, ACO, LBE-ARAMA in terms of Energy, Delay, Packet Delivery Ratio and Network life time.

Structure Optimization of Solute Molecules via Free Energy Gradient Method

  • Nagaoka, Masataka
    • Bulletin of the Korean Chemical Society
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    • v.24 no.6
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    • pp.805-808
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    • 2003
  • Fundamental ideas of the free energy gradient method are briefly reviewed with three applications: the stable structures of glycine and ammonia-water molecule pair in aqueous solution and the transition state (TS) structure of a Menshutkin reaction $NH_3 + CH_3Cl → CH_3NH_3^+ + Cl^-$ in aqueous solution, which is the first example of full TS optimization of all internal degrees of freedom.

Prolonging Network Lifetime by Optimizing Actuators Deployment with Probabilistic Mutation Multi-layer Particle Swarm Optimization

  • Han, Yamin;Byun, Heejung;Zhang, Liangliang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.8
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    • pp.2959-2973
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    • 2021
  • In wireless sensor and actuator networks (WSANs), the network lifetime is an important criterion to measure the performance of the WSAN system. Generally, the network lifetime is mainly affected by the energy of sensors. However, the energy of sensors is limited, and the batteries of sensors cannot be replaced and charged. So, it is crucial to make energy consumption efficient. WSAN introduces multiple actuators that can be regarded as multiple collectors to gather data from their respective surrounding sensors. But how to deploy actuators to reduce the energy consumption of sensors and increase the manageability of the network is an important challenge. This research optimizes actuators deployment by a proposed probabilistic mutation multi-layer particle swarm optimization algorithm to maximize the coverage of actuators to sensors and reduce the energy consumption of sensors. Simulation results show that this method is effective for improving the coverage rate and reducing the energy consumption.

Design of an Active Damping Layer Using Topology Optimization (위상 최적화를 이용한 능동 감쇠층의 설계)

  • 김태우;김지환
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2003.11a
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    • pp.660-664
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    • 2003
  • The optimal thickness distribution of an active damping layer is sought so that it satisfies a certain constraint on the dynamic performance of a system minimizing control efforts. To obtain a topologically optimized configuration, which includes size and shape optimization, thickness of the active damping layer is interpolated using linear functions. With the control energy as the objective function to be minimized, the state error energy is introduced as the dynamic performance criterion for the system and used lot a constraint. The optimal control gains are evaluated from LQR simultaneously as the optimization of the layer position proceeds. From numerical simulation, the topologically optimized distribution of the active damping layer shows the same dynamic performance and cost as the Idly covered counterpart, which is optimized only in terms of control gains, with less amount of the layer.

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Sizing, geometry and topology optimization of trusses using force method and supervised charged system search

  • Kaveh, A.;Ahmadi, B.
    • Structural Engineering and Mechanics
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    • v.50 no.3
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    • pp.365-382
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    • 2014
  • In this article, the force method and Charged System Search (CSS) algorithm are used for the analysis and optimal design of truss structures. The CSS algorithm is employed as the optimization tool and the force method is utilized for analysis. In this paper in addition to member's cross sections, redundant forces, geometry and topology variables are considered as the optimization variables. Minimum complementary energy principle is used directly to analyze the structure. In the presented method, redundant forces are calculated by the CSS in order to minimize the energy function. Combination of the CSS and force method leads to an efficient algorithm in comparison to some of the optimization algorithms.

Design Optimization of Ball Grid Array Packaging by the Taguchi Method

  • Kim, Yeong-K.;Kim, Jae-chang;Choi, Joo-Ho
    • Journal of the Microelectronics and Packaging Society
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    • v.17 no.4
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    • pp.67-72
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    • 2010
  • In this paper, a design optimization of ball grid array packaging geometry is studied based on the Taguchi method, which allowed robust design by considering the variance of the input parameters during the optimization process. Molding compound and substrate were modeled as viscoelastic, and finite element analyses were performed to calculate the strain energy densities of the eutectic solder balls. Six quality factors of the dimensions of the packaging geometry were chosen as control factors. After performing noise experiments to determine the dominant factors, main experiments were conducted to find the optimum packaging geometry. Then the strain energy densities between the original and optimized geometries were compared. It was found that the effects of the packaging geometry on the solder ball reliability were significant, and more than 40% of the strain energy density was reduced by the geometry optimization.