• Transactions of The Korea Fluid Power Systems Society
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• v.7 no.1
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• pp.11-19
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• 2010

A gas-assisted hydraulic breaker uses both hydraulic and pneumatic energies and the appropriate balance between them mostly effects its performance. Mathematical modeling of the breaker is established and verified by experiment. Through sensitivity analysis using AMESim, the key design parameters are selected, which mostly affect the performance of the breaker. Taguchi method is used to optimize the key design parameters to maximize the output power for long and short strokes through simulation. As the result, the output power as well as the impact energy are increased significantly compared with the existing design. The pressure pulsation in the supply line is reduced to a tolerable level and the dynamic characteristics of the piston displacement is also improved by the optimization.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.11
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• pp.1179-1185
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• 2013

In this study, the design optimization of the automotive side member is performed to maximize the crash energy absorption efficiency per unit weight. Design parameters which seriously influence on the frontal crash performance are selected through the sensitivity analysis using the Plackett-Burman design method. And also the design variables, which are determined from the sensitivity analysis, are optimized by two methods. One is conventional approximate optimization method which uses the statistical design of experiments (DOE) and response surface method (RSM). The other is a methodology derived from previous work by the authors, which is called sequential design of experiments (SDOE), to reduce a trial and error procedure and to find an appropriate condition for using micro-genetic algorithm. The proposed optimization technique shows that the automotive side member structure can be designed considering the frontal crash performance.

• KIEAE Journal
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• v.3 no.2
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• pp.51-58
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• 2003

The purpose of this study is to present rational methods of multi-criteria optimization of the shape of energy saving buildings. The object is to determine the optimum dimension of the shape of a building, based on the following criteria: minimum building costs (including the cost of materials and construction) and yearly heating costs. Mathematical model described heat losses and gains in a building during the heating season. It takes into consideration heat losses through wall, roof, floor and windows. Particular attention was paid to have a more detailed description of heat gains due to solar radiation. On the assumption that shape of building is rectangle in order to solve the problem, the proportions of wall length and building height are determined by using non-linear programing methods(Kuhn-Tucker Conditions). The results constitute information for designers on the optimum proportions of wall lengths, height, and the ratios of window to wall areas for energy saving buildings.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.3
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• pp.1235-1242
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• 2013

This study deals with the BIM (Building Information Modeling)-based energy performance analysis implemented in EnergyPlus. The BIM model constructed at Revit is updated at Design Builder, adding HVAC models and converted compatibly with the EnergyPlus. We can obtain the input values about HVAC system and building environment such as HVAC system efficient, the number of air changes and energy consumption of equipment on applying GAs (Genetic algorithms). After modification about HVAC system, Optimization about HVAC system energy consumption can be analyzed. In order to maximize the building energy performance, a genetic algorithm (GA)-based optimization technique is applied to the modified HVAC models. Throughout the proposed building energy simulation, finally, the best optimized HVAC control schedule for the target building can be obtained in the form of "supply air temperature schedule". Throughout the supply air temperature schedule is applied to energy performance simulation, we obtained energy saving effect result on simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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• pp.3071-3095
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• 2013

Configuring optimization of wireless sensor networks, which can improve the network performance such as utilization efficiency and network lifetime with minimal energy, has received considerable attention in recent years. In this paper, a cross layer optimal approach is proposed for multi-source linear network and grid network under Rayleigh block-fading channels, which not only achieves an optimal utility but also guarantees the end-to-end reliability. Specifically, in this paper, we first strictly present the optimization method for optimal nodal number $N^*$, nodal placement $d^*$ and nodal transmission structure $p^*$ under constraints of minimum total energy consumption and minimum unit data transmitting energy consumption. Then, based on the facts that nodal energy consumption is higher for those nodes near the sink and those nodes far from the sink may have remaining energy, a cross layer optimal design is proposed to achieve balanced network energy consumption. The design adopts lower reliability requirement and shorter transmission distance for nodes near the sink, and adopts higher reliability requirement and farther transmission distance for nodes far from the sink, the solvability conditions is given as well. In the end, both the theoretical analysis and experimental results for performance evaluation show that the optimal design indeed can improve the network lifetime by 20-50%, network utility by 20% and guarantee desire level of reliability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.3090-3102
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• 2015

The accuracy of an augmented reality (AR) application is highly dependent on the resolution of the object's image and the device's computational processing capability. Naturally, a mobile smart device equipped with a high-resolution camera becomes the best platform for portable AR services. AR applications require significant energy consumption and very fast response time, which are big burdens to the smart device. However, there are very few ways to overcome these burdens. Computation offloading via mobile cloud computing has the potential to provide energy savings and enhance the performance of applications executed on smart devices. Therefore, in this paper, adaptive mobile computation offloading of mobile AR applications is considered in order to determine optimal offloading points that satisfy the required quality of experience (QoE) while consuming minimum energy of the smart device. AR feature extraction based on SURF algorithm is partitioned into sub-stages in order to determine the optimal AR cloud computational offloading point based on conditions of the smart device, wireless and wired networks, and AR service cloud servers. Tradeoffs in energy savings and processing time are explored also taking network congestion and server load conditions into account.

• Smart Structures and Systems
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• v.23 no.5
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• pp.421-428
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• 2019

The development of the low power application such as wireless sensors and health monitoring systems, attract a great attention to low power vibration energy harvesters. The recent vibration energy harvesters use smart materials in their structures to convert ambient mechanical energy into electricity. The frequent model of this harvesters is cantilevered beam. In the literature, the base excitation cantilevered harvesters are mainly investigated, and the related models are presented. This paper investigates a tip excitation cantilevered beam energy harvester with permendur. In the first section, the mechanical model of the harvester and magneto-mechanical model of the permendur are presented. Later, to find the maximum output of the harvester, based on the response surface method (RSM), some experiments are done, and the results are analyzed. Finally, to verify the results of RSM, a harvester with optimum design variables is made, and its output power is compared. The last comparison verifies the estimation of the RSM method which was about $381{\mu}W/cm^3$.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.44-50
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• 2023

For Wi-Fi and IoT wireless systems, high-capacity wireless communication technology is being applied using MIMO OFDM. Because of virtu0al subcarriers in the practical MIMO OFDM system, the pilot subcarriers cannot be spaced equally. Thus, it is difficult to obtain a good mean square error (MSE) performance of the channel estimate. This paper proposes applicable methods and the newly discovered locations of pilot subcarriers in four transmitted antennas resulting in a good MSE performance with proposed optimization algorithms.

• International Journal of Railway
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• v.2 no.3
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• pp.124-126
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• 2009

Energy savings can be achieved with optimum energy consumptions, brake energy regeneration, efficient energy storage (onboard, line side), and primarily with light weight vehicles. Over the last few years, the rolling stock industry has experienced a marked increase in eco-awareness and needs for lower life cycle energy consumption costs. For rolling stock vehicle designers and engineers, weight has always been a critical design parameter. It is often specified directly or indirectly as contractual requirements. These requirements are usually expressed in terms of specified axle load limits, braking deceleration levels and/or demands for optimum energy consumptions. The contractual requirements for lower weights are becoming increasingly more stringent. Light weight vehicles with optimized strength to weight ratios are achievable through proven design processes. The primary driving processes consist of: $\bullet$ material selection to best contribute to the intended functionality and performance $\bullet$ design and design optimization to secure the intended functionality and performance $\bullet$ weight control processes to deliver the intended functionality and performance Aluminium has become the material of choice for modern light weight bodyshells. Steel sub-structures and in particular high strength steels are also used where high strength - high elongation characteristics out way the use of aluminium. With the improved characteristics and responses of composites against tire and smoke, small and large composite materials made components are also found in greater quantities in today's railway vehicles. Full scale hybrid composite rolling stock vehicles are being developed and tested. While an "overdesigned" bodyshell may be deemed as acceptable from a structural point of view, it can, in reality, be a weight saving missed opportunity. The conventional pass/fail structural criteria and existing passenger payload definitions promote conservative designs but they do not necessarily imply optimum lightweight designs. The weight to strength design optimization should be a fundamental design driving factor rather than a feeble post design activity. It should be more than a belated attempt to mitigate against contractual weight penalties. The weight control process must be rigorous, responsible, with achievable goals and above all must be integral to the design process. It should not be a mere tabulation of weights for the sole-purpose of predicting the axle loads and wheel balances compliance. The present paper explores and discusses the topics quoted above with a view to strengthen the recommendations and needs for the weight optimization by design approach as a pro-active design activity for the rolling stock industry at large.

• Tunnel and Underground Space
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• v.28 no.6
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• pp.651-669
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• 2018

This study suggests the prediction model to estimate the specific energy of a pick cutter using a gene expression programming (GEP) and particle swarm optimization (PSO). Estimating the performance of mechanical excavators is of crucial importance in early design stage of tunnelling projects, and the specific energy (SE) based approach serves as a standard performance prediction procedure that is applicable to all excavation machines. The purpose of this research, is to investigate the relationship between UCS and BTS, penetration depth, cut spacing, and SE. A total of 46 full-scale linear cutting test results using pick cutters and different values of depth of cut and cut spacing on various rock types was collected from the previous study for the analysis. The Mean Squared Error (MSE) associated with the conventional Multiple Linear Regression (MLR) method is more than two times larger than the MSE generated by GEP-PSO algorithm. The $R^2$ value associated with the GEP-PSO algorithm, is about 0.13 higher than the $R^2$ associated with MLR.