• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.05a
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• pp.47-47
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• 2010

Over the past 20 years, constant progress in noise and vibration (NVH) engineering has enabled to constantly advance quality and comfort of operation and use of really any products - from automobiles to aircraft, to all kinds of industrial vehicles and machines - to the extend that for many products, supreme NVH performance has becomes part of its brand image in the market. At the same time, the product innovation agenda in the automotive, aircraft and really many other industries, has been extended very much in recent years by meeting ever more strict environmental regulations. Like in the automotive industry, the drive towards meeting emission and CO2 targets leads to very much accelerated adoption of new powertrain concepts (downsizing of ICE, hybrid-electrical...), and to new vehicle architectures and the application of new materials to reduce weight, which bring new challenges for not only maintaining but further improving NVH performance. This drives for innovation in NVH engineering, so as to succeed in meeting a product brand performance for NVH, while as the same time satisfying eco-constraints. Product innovation has also become increasingly dependent on the adoption of electronics and software, which drives for new solutions for NVH engineering that can be applied for NVH performance optimization of mechatronic products. Finally, relentless pressure to shorten time to market while maintaining overall product quality and reliability, mandates that the practice and solutions for NVH engineering can be optimally applied in all phases of product development. The presentation will first review the afore trends for product and process innovation, and discuss the challenges they represent for NVH engineering. Next, the presentation discusses new solutions for NVH engineering of products, so as to meet target brand values, while at the same time meeting ever more strict eco constraints, and this within a context of increasing adoption of electronics and controls to drive product innovation. NVH being very much defined by system level performance, these solutions implement the approach of "Model Based System Engineering" to increase the impact of system level analysis for NVH in all phases of product development: - At the Concept Phase, to be able to do business case analysis of new product concepts; to arrive at an optimized and robust product architecture (e.g. to hybrid powertrain lay-out, to optimize fuel economy); to enable target cascading, to subsystem and component level. - In Development Phase, to increase realism and productivity of simulation, so as to frontload virtual validation of components and subsystems and to further reduce reliance on physical testing. - During the final System Testing Phase, to enable subsystem testing by a combination of physical testing and simulation: using simulation models to simulate the final integration context when testing a subsystem, enabling to frontload subsystem testing before final system integration is possible. - To interconnect Mechanical, Electronical and Controls engineering, in all phases of development, by supporting model driven controls engineering (MIL, SIL, HIL). Finally, the presentation reviews examples of how LMS is implementing such new applications for NVH engineering with lead customers in Europe, Asia and US, with demonstrated benefits both in terms of shortening development cycles, and/or enabling a simulation based approach to reduce reliance on physical testing.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.164-170
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• 2006

This paper proposes a RSM-based hybrid evolutionary algorithm (RHEA) which combines the merits of the popular programs such as genetic algorithm (GA), tabu search method, response surface methodology (RSM). This algorithm, for improving the convergent speed that is thought to be the demerit of genetic algorithm, uses response surface methodology and simplex method. The mutation of GA offers random variety to finding the optimum solution. In this study, however, systematic variety can be secured through the use of tabu list. Efficiency of this method has been proven by applying traditional test functions and comparing the results to GA. And it was also proved that the newly suggested algorithm is very effective to find the global optimum solution to minimize the weight for avoiding the resonance of fresh water tank that is placed in the rear of ship. According to the study, GA's convergent speed in initial stages is improved by using RSM method. An optimized solution is calculated without the evaluation of additional actual objective function. In a summary, it is concluded that RHEA is a very powerful global optimization algorithm from the view point of convergent speed and global search ability.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.45-51
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• 2011

This paper proposes a method to accelerate the evolution speed of individuals through hybrid reproduction of monogenesis and gamogenesis. Monogenesis as a reproduction method that bacteria or monad without sexual distinction divide into two individuals has an advantage for local search and gamogenesis as a reproduction method that individuals with sexual distinction mate and breed the offsprings has an advantages for keeping the diversity of individuals. These properties can be properly used for improvement of evolution speed of individuals in genetic algorithms. In this paper, we made relatively good individuals among selected parents to do monogenesis for local search and forced relatively bad individuals among selected parents to do gamogenesis for global search by increasing the diversity of chromosomes. The mutation probability for monogenesis was set to a lower value than that of original genetic algorithm for local search and the mutation probability for gamogenesis was set to a higher value than that of original genetic algorithm for global search. Experimental results with four function optimization problems showed that the performances of three functions were very good, but the performances of fourth function with distributed global optima were not good. This was because distributed global optima prevented individuals from steady evolution.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.6 s.111
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• pp.665-673
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• 2006

This paper proposes a RSM-based hybrid evolutionary Algorithm (RHEA) which combines the merits of the popular programs such as genetic algorithm (GA), tabu search method and response surface methodology (RSM). This algorithm, for improving the convergent speed that is thought to be the demerit of genetic algorithm, uses response surface methodology and simplex method. The mutation of GA offers random variety to finding the optimum solution. In this study, however, systematic variety can be secured through the use of tabu list. Efficiency of this method has been proven by applying traditional left functions and comparing the results to GA. It was also proved that the newly suggested algorithm is very effective to find the global optimum solution to minimize the weight for avoiding the resonance of fresh water tank that is placed in the after body area of ship. According to the study, GA's convergent speed in initial stages is improved by using RSM method. An optimized solution is calculated without the evaluation of additional actual objective function. In a summary, it is concluded that RHEA is a very powerful global optimization algorithm from the view point of convergent speed and global search ability.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.05a
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• pp.48-48
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• 2010

Sound quality and NVH-issues(Noise, Vibration and Harshness) of vehicles has become very important for car manufacturers. It is interpreted as among the most relevant factors regarding perceived product quality, and is important in gaining market advantage. The general sound quality of vehicles was gradually improved over the years. However, today the development cycles in the automotive industry are constantly reduced to meet the customers' demands and to react quickly to market needs. In addition, new drive and fuel concepts, tightened ecological specifications, increase of vehicle classes and increasing diversification(increasing market for niche vehicles), etc. challenge the acoustic engineers trying to develop a pleasant, adequate, harmonious passenger cabin sound. Another aspect concerns the general pressure for reducing emission and fuel consumption, which lead to vehicle weight reductions through material changes also resulting in new noise and vibration conflicts. Furthermore, in the context of alternative powertrains and engine concepts, the new objective is to detect and implement the vehicle sound, tailored to suit the auditory expectations and needs of the target group. New questions must be answered: What are appropriate sounds for hybrid or electric vehicles? How are new vehicle sounds perceived and judged? How can customer-oriented, client-specific target sounds be determined? Which sounds are needed to fulfil the driving task, and so on? Thus, advanced methods and tools are necessary which cope with the increasing complexity of NVH-problems and conflicts and at the same time which cope with the growing expectations regarding the acoustical comfort. Moreover, it is exceedingly important to have already detailed and reliable information about NVH-issues in early design phases to guarantee high quality standards. This requires the use of sophisticated simulation techniques, which allow for the virtual construction and testing of subsystems and/or the whole car in early development stages. The virtual, testing is very important especially with respect to alternative drive concepts(hybrid cars, electric cars, hydrogen fuel cell cars), where complete new NVH-problems and challenges occur which have to be adequately managed right from the beginning. In this context, it is important to mention that the challenge is that all noise contributions from different sources lead to a harmonious, well-balanced overall sound. The optimization of single sources alone does not automatically result in an ideal overall vehicle sound. The paper highlights modern and innovative NVH measurement technologies as well as presents solutions of recent NVH tasks and challenges. Furthermore, future prospects and developments in the field of automotive acoustics are considered and discussed.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.5 no.6
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• pp.583-591
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• 2015

In order to evaluate the performance of TAS applied to the hybrid vehicle of the soft belt driven, acceleration performance and fuel consumption performance is to be superior to the existing vehicle. The key components of belt driven TAS(Torque Assist System), such as the engine, the motor and the battery, The key components of the driven belt TAS, such as the engine, the motor, and the battery, have a significant impact on fuel consumption performance of the vehicle. Therefore, in order to improve the efficiency at the point of view based on the overall system, the study of the power distribution algorithm for controlling the main source powers is necessary. In this paper, we propose the power distribution algorithm, applied the homogeneous analysis method in terms of fuel equivalent, for minimizing the fuel consumption. We have confirmed that the proposed algorithm is contribute to improving the fuel consumption performance satisfied the constraints considering the vehicle status information and the required power through the control parameters to minimize the fuel consumption of the engine. The optimization process of the proposed driving strategy can reduce the trial and error in the research and development process and monitor the characteristics of the control parameter quickly and accurately. Therefore, it can be utilized as a way to derive the operational strategy to minimize the fuel consumption.

• Composites Research
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• v.34 no.1
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• pp.35-46
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• 2021

This paper aims to reduce weight by replacing the reinforcements of the B-pillar used in vehicles with CFRP(Carbon Fiber Reinforced Plastics) and GFRP(Glass Fiber Reinforced Plastics) from the existing steel materials. For this, it is necessary to secure structural stability that can replace the existing B-pillar while reducing the weight. Existing B-pillar are composed of steel reinforcements of various shapes, including a steel outer. Among these steel reinforcements, two steel reinforcements are to be replaced with composite materials. Each steel reinforcement is manufactured separately and bonded to the B-pillar outer by welding. However, the composite reinforcements presented in this paper are manufactured at once through compression and injection processes using patch-type CFRP and rib-structured GFRP. CFRP is attached to the high-strength part of the B-pillar to resist side loads, and the GFRP ribs are designed to resist torsion and side loads through a topology optimization technique. Through structural analysis, the designed composite B-pillar was compared with the existing B-pillar, and the weight reduction ratio was calculated.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.55-62
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• 2022

The perovskite solar cell is an active part of research in renewable energy fields such as solar energy, wind, hydroelectric power, marine energy, bioenergy, and hydrogen energy to replace fossil fuels such as oil, coal, and natural gas, which will gradually disappear as power demand increases due to the increase in use of the Internet of Things and Virtual environments due to the 4th industrial revolution. The perovskite solar cell is a solar cell device using an organic-inorganic hybrid material having a perovskite structure, and has advantages of replacing existing silicon solar cells with high efficiency, low cost solutions, and low temperature processes. In order to optimize the light absorption layer thin film predicted by the existing empirical method, reliability must be verified through device characteristics evaluation. However, since it costs a lot to evaluate the characteristics of the light-absorbing layer thin film device, the number of tests is limited. In order to solve this problem, the development and applicability of a clear and valid model using machine learning or artificial intelligence model as an auxiliary means for optimizing the light absorption layer thin film are considered infinite. In this study, to estimate the light absorption layer thin-film optimization of perovskite solar cells, the regression models of the support vector machine's linear kernel, R.B.F kernel, polynomial kernel, and sigmoid kernel were compared to verify the accuracy difference for each kernel function.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.31-43
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• 2022

Traditional video compression has developed so far based on hybrid compression methods through motion prediction, residual coding, and quantization. With the rapid development of technology through artificial neural networks in recent years, research on image compression and video compression based on artificial neural networks is also progressing rapidly, showing competitiveness compared to the performance of traditional video compression codecs. In this paper, a new method capable of improving the performance of such an artificial neural network-based video compression model is presented. Basically, we take the rate-distortion optimization method using the auto-encoder and entropy model adopted by the existing learned video compression model and shifts some components of the latent information that are difficult for entropy model to estimate when transmitting compressed latent representation to the decoder side from the encoder side, and finally compensates the distortion of lost information. In this way, the existing neural network based video compression framework, MFVC (Motion Free Video Compression) is improved and the BDBR (Bjøntegaard Delta-Rate) calculated based on H.264 is nearly twice the amount of bits (-27%) of MFVC (-14%). The proposed method has the advantage of being widely applicable to neural network based image or video compression technologies, not only to MFVC, but also to models using latent information and entropy model.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.2
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• pp.123-130
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• 2013

In this paper, the delamination and failures in frequency selected surface(FSS) caused by residual stresses in the FSS embedded hybrid composites due to the difference between the coefficients of thermal expansion of components and the transmission characteristic changes due to deformation of FSS patterns by residual stresses were studied. FSS may have different electromagnetic characteristics depending on the type of element, design variables, and arrangement. Design variables of dipole FSS were determined using PSO(Particle Swarm Optimization) to obtain the transmission characteristic for the target resonant frequency. Subsequently, the design variables of other types of N-pole(tripole, cross dipole, and Jerusalem cross) were determined based on the dimensions of the dipole for the comparisons of residual stresses of FSS embedded composite structures and transmission characteristics. In addition, effects of FSS pattern, and stacking sequence of composite laminates were considered.