• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• 2008.03a
• /
• pp.130-135
• /
• 2008

An aerodynamic optimization design process of multistage axial turbine is presented in this article: first, applying quasi-three dimensional(Q3D) design methods to conduct preliminary design and then adopting modern optimization design methods to implement multistage local optimization. Quasi-three dimensional(Q3D) design methods, which mainly refer to S2 flow surface direct problem calculation, adopt the S2 flow surface direct problem calculation program of Harbin Institute of Technology. Multistage local optimization adopts the software of Numeca/Design3D, which jointly adopts genetic algorithm and artificial neural network. The major principle of the methodology is that the successive design evaluation is performed by using an artificial neural network instead of a flow solver and the genetic algorithms may be used in an efficient way. Flow computation applies three-dimensional viscosity Navier Stokes(N-S) equation solver. Such optimization process has three features: (i) local optimization based on aerodynamic performance of every cascade; (ii) several times of optimizations being performed to every cascade; and (iii) alternate use of coarse grid and fine grid. Such process was applied to optimize a three-stage axial turbine. During the optimization, blade shape and meridional channel were respectively optimized. Through optimization, the total efficiency increased 1.3% and total power increased 2.4% while total flow rate only slightly changed. Therefore, the total performance was improved and the design objective was achieved. The preliminary design makes use of quasi-three dimensional(Q3D) design methods to achieve most reasonable parameter distribution so as to preliminarily enhance total performance. Then total performance will be further improved by adopting multistage local optimization design. Thus the design objective will be successfully achieved without huge expenditure of manpower and calculation time. Therefore, such optimization design process may be efficiently applied to the aerodynamic design optimization of multistage axial turbine.

• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.21 no.1
• /
• pp.30-38
• /
• 2013

This paper describes the design optimization of Unmanned Aerial Vehicles(UAVs). An optimization framework has been developed and implemented for the conceptual design of UAVs. An integrated design analysis program was developed with several analysis modules such as propulsion, performance, mission, weight, and stability and control. A UAV configuration design optimization was performed by implementing the integrated analysis to enhance the endurance of UAVs. A SQP optimizer was utilized to build an optimization module for this program and sensitivity analysis was performed to determine the trends of shape variables for developing optimization objective. In conclusion, the results indicate that the resulting optimized UAVs configurations show performance improvements over the baseline design and reliable analysis results.

• Proceedings of the IEEK Conference
• /
• 2003.11a
• /
• pp.99-102
• /
• 2003

Computing environments of Embedded Systems are different from those of desktop computers so that they have resource constraints such as CPU processing, memory capacity, power, and etc.. Thus, when a desktop S/W is ported into embedded systems, optimization should be seriously considered. In this paper, we investigate several S/W optimization techniques to be considered for porting H.263 encoder into a high performance DSP, TMS320C6711. Through experiments, it is found that optimization techniques employed can make a big performance improvement.

• Structural Engineering and Mechanics
• /
• v.53 no.4
• /
• pp.833-845
• /
• 2015

Natural frequencies of the structural systems should be far away from the excitation frequency in order to avoid or reduce the destructive effects of dynamic loads on structures. To accomplish this goal, a structural optimization on size and shape has been performed considering frequency constraints. Such an optimization problem has highly nonlinear property. Thus, the quality of the solution is not independent of the optimization technique to be applied. This study presents the performance evaluation of the recently proposed meta-heuristic algorithm called Teaching Learning Based Optimization (TLBO) as an optimization engine in the weight optimization of the truss structures under frequency constraints. Some examples regarding the optimization of trusses on shape and size with frequency constraints are solved. Also, the results obtained are tabulated for comparison. The results demonstrated that the performance of the TLBO is satisfactory. Additionally, TLBO is better than other methods in some cases.

• Structural Engineering and Mechanics
• /
• v.37 no.5
• /
• pp.543-560
• /
• 2011

In structural engineering there are randomness inherently exist on determination of the loads, strength, geometry, and so on, and the manufacturing of the structural members, workmanship etc. Thus, objective and constraint functions of the optimization problem are functions that depend on those randomly natured components. The constraints being the function of the random variables are evaluated by using reliability index or performance measure approaches in the optimization process. In this study, the minimum weight of a space truss is obtained under the uncertainties on the load, material and cross-section areas with harmony search using reliability index and performance measure approaches. Consequently, optimization algorithm produces the same result when both the approaches converge. Performance measure approach, however, is more efficient compare to reliability index approach in terms of the convergence rate and iterations needed.

• ETRI Journal
• /
• v.42 no.4
• /
• pp.505-517
• /
• 2020

The increasing size and complexity of deep neural networks (DNNs) necessitate the development of efficient high-performance accelerators. An efficient memory structure and operating scheme provide an intuitive solution for high-performance accelerators along with dataflow control. Furthermore, the processing of various neural networks (NNs) requires a flexible memory architecture, programmable control scheme, and automated optimizations. We first propose an efficient architecture with flexibility while operating at a high frequency despite the large memory and PE-array sizes. We then improve the efficiency and usability of our architecture by automating the optimization algorithm. The experimental results show that the architecture increases the data reuse; a diagonal write path improves the performance by 1.44× on average across a wide range of NNs. The automated optimizations significantly enhance the performance from 3.8× to 14.79× and further provide usability. Therefore, automating the optimization as well as designing an efficient architecture is critical to realizing high-performance DNN accelerators.

• Journal of applied mathematics & informatics
• /
• v.15 no.1_2
• /
• pp.313-321
• /
• 2004

In this paper we study the problem of three-dimensional layout optimization on the simplified rotating vessel of satellite. The layout optimization model with behavioral constraints is established and some effective and convenient conditions of performance optimization are presented. Moreover, we prove that the performance objective function is locally Lipschitz continuous and the results on the relations between the local optimal solution and the global optimal solution are derived.

• International Journal of Advanced Culture Technology
• /
• v.7 no.4
• /
• pp.56-62
• /
• 2019

Recently, research using artificial neural networks has further expanded the field of neural network optimization and automatic structuring from improving inference accuracy. The performance of the machine learning algorithm depends on how the hyperparameters are configured. Open-source hyperparameter optimization software can be an important step forward in improving the performance of machine learning algorithms. In this paper, we review open-source hyperparameter optimization softwares.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.67 no.3
• /
• pp.143-148
• /
• 2018

In this paper, the optimal fuzzy logic controller(FLC) for a hybrid renewable energy system(HRES) is proposed. Generally, hybrid renewable energy systems can consist of wind power, solar power, fuel cells and storage devices. The proposed FLC can effectively control the entire HRES by determining the output power of the fuel cell or the absorption power of the electrolyzer. In general, fuzzy logic controllers can be optimized by classical optimization algorithms such as genetic algorithms(GA) or particle swarm optimization(PSO). However, these FLC have a disadvantage in that their performance varies greatly depending on the control parameters of the optimization algorithms. Therefore, we propose a method to optimize the fuzzy logic controller using the teaching-learning based optimization(TLBO) algorithm which does not have the control parameters of the algorithm. The TLBO algorithm is an optimization algorithm that mimics the knowledge transfer mechanism in a class. To verify the performance of the proposed algorithm, we modeled the hybrid system using Matlab Tool and compare and analyze the performance with other classical optimization algorithms. The simulation results show that the proposed method shows better performance than the other methods.

• Journal of Digital Convergence
• /
• v.10 no.4
• /
• pp.207-215
• /
• 2012

This paper proposes a proxy-based caching optimization scheme for improving the streaming media services in wireless mobile ad hoc networks. The proposed scheme utilizes the proxy for data packet transmission between media server and nodes in WLANs, and the proxy locates near the wireless access pointer. For caching optimization, this paper proposes NFCO (non-full cache optimization) and CFO (cache full optimization) scheme. When performs the streaming in the proxy, the NFCO and CFO is to optimize the caching performance. This paper compared the performance for optimization between the proposed scheme and the server-based scheme and rate-distortion scheme. Simulation results show that the proposed scheme has better performance than the existing server-only scheme and rate distortion scheme.