• Title/Summary/Keyword: Process parameter window

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The Effect of Shielding Gas Composition on High Power Laser Welding Characteristics (보호가스 종류에 따른 고출력 레이저 용접특성)

  • Ahn, Young-Nam;Kim, Cheolhee
    • Journal of Welding and Joining
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    • v.33 no.4
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    • pp.17-23
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    • 2015
  • Laser-gas metal arc hybrid welding has been considered as an alternative process of gas metal arc welding for offshore pipe laying. Fiber delivered high power lasers which enable deep penetration welding were recently developed but high power welding characteristics were not fully understood yet. In this study, the influence of shielding gas composition on welding phenomena in high power laser welding was investigated. Bead shapes, melt ejection and dropping were observed after autogenous laser welding with 100% Ar, Ar-20% $CO_2$, Ar-50% $CO_2$, and 100% $CO_2$ shielding gas. Process parameter window was widest with Ar-50% $CO_2$ shielding gas and the penetration was deepest with 100% $CO_2$ shielding gas. The melt dropping was not observed when Ar-50% $CO_2$ or 100% $CO_2$ shielding gas was supplied.

Data-driven Approach to Explore the Contribution of Process Parameters for Laser Powder Bed Fusion of a Ti-6Al-4V Alloy

  • Jeong Min Park;Jaimyun Jung;Seungyeon Lee;Haeum Park;Yeon Woo Kim;Ji-Hun Yu
    • Journal of Powder Materials
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    • v.31 no.2
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    • pp.137-145
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    • 2024
  • In order to predict the process window of laser powder bed fusion (LPBF) for printing metallic components, the calculation of volumetric energy density (VED) has been widely calculated for controlling process parameters. However, because it is assumed that the process parameters contribute equally to heat input, the VED still has limitation for predicting the process window of LPBF-processed materials. In this study, an explainable machine learning (xML) approach was adopted to predict and understand the contribution of each process parameter to defect evolution in Ti alloys in the LPBF process. Various ML models were trained, and the Shapley additive explanation method was adopted to quantify the importance of each process parameter. This study can offer effective guidelines for fine-tuning process parameters to fabricate high-quality products using LPBF.

Comparison of Powder Feeding and Wire Feeding in Laser Cladding (분말송급 및 와이어송급을 이용한 레이저 클래딩 특성)

  • Ahn, Young-Nam;Kim, Cheolhee
    • Journal of Welding and Joining
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    • v.31 no.4
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    • pp.13-16
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    • 2013
  • In this research, laser cladding characteristics were investigated for various filler metal feeding methods such as powder, cold wire, and hot wire feeding. Appropriate parameter window, deposition rate, material efficiency and dilution for each filler feeding method were evaluated with same laser power and cladding speed range. Laser powder cladding has wider process parameter window but higher material efficiency and lower dilution were achieved by laser wire cladding. Among these feeding methods, laser hot-wire cladding showed best efficiency in material usage and deposition rate.

A Study on the FIR Digital Filter using Modified Window Function (변형된 창함수를 사용한 FIR 디지털 필터에 관한 연구)

  • 강경덕;배상범;김남호;류지구
    • Journal of the Institute of Convergence Signal Processing
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    • v.4 no.1
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    • pp.49-55
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    • 2003
  • The use of digital filters in the signal process field is increasing rapidly with development of the modern industrial society. Especially, detail processors, Y/C separators, ghost removing filters, standard converters (NTSC to PAL or PAL to NTSC) and noise reducers, all of which use digital filters, tend to be used in digital video and audio processing, CATV and various communication fields. Generally, there are two different digital filters, the Rf (infinite impulse response) filter and the FIR (finite impulse response) filter in digital filter. In this paper, we have designed FIR filter which has the phase linearity and the easiness of creation. In the design of the FIR digital filter, the window function is used to alleviate the ripples caused by Gibbs Phenomenon around the cut off frequency of the band pass. But there're some problems to choose proper window function for the design destination due to its fixed values. Therefore, in this paper, we designed a modified Hanning window with new parameter which is adaptively chosen corresponding to design objectives. The digital filter was simulated to prove the validity of the model and it was compared with the Hamming, the Manning, the Blacknan and the Kaiser window function. And we have used peak side-lobe and transient characteristics as standard of judgement.

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Analytic Throughput Model for Network Coded TCP in Wireless Mesh Networks

  • Zhang, Sanfeng;Lan, Xiang;Li, Shuang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.9
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    • pp.3110-3125
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    • 2014
  • Network coding improves TCP's performance in lossy wireless networks. However, the complex congestion window evolution of network coded TCP (TCP-NC) makes the analysis of end-to-end throughput challenging. This paper analyzes the evolutionary process of TCP-NC against lossy links. An analytic model is established by applying a two-dimensional Markov chain. With maximum window size, end-to-end erasure rate and redundancy parameter as input parameters, the analytic model can reflect window evolution and calculate end-to-end throughput of TCP-NC precisely. The key point of our model is that by the novel definition of the states of Markov chain, both the number of related states and the computation complexity are substantially reduced. Our work helps to understand the factors that affect TCP-NC's performance and lay the foundation of its optimization. Extensive simulations on NS2 show that the analytic model features fairly high accuracy.

Development of Analysis Method of Ordered Categorical Data for Optimal Parameter Design (순차 범주형 데이타의 최적 모수 설계를 위한 분석법 개발)

  • Jeon, Tae-Jun;Park, Ho-Il;Hong, Nam-Pyo;Choe, Seong-Jo
    • Journal of Korean Institute of Industrial Engineers
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    • v.20 no.1
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    • pp.27-38
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    • 1994
  • Accumulation analysis is difficult to analyze the ordered categorical data except smaller-the-better type problem. The purpose of this paper is to develop the statistic and method that can be easily applied to general type of problem, including nominal-the-best type problem. The experimental data of contact window process is analyzed and new procedure is compared with accumulation analysis.

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A Systems Engineering Approach to Predict the Success Window of FLEX Strategy under Extended SBO Using Artificial Intelligence

  • Alketbi, Salama Obaid;Diab, Aya
    • Journal of the Korean Society of Systems Engineering
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    • v.16 no.2
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    • pp.97-109
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    • 2020
  • On March 11, 2011, an earthquake followed by a tsunami caused an extended station blackout (SBO) at the Fukushima Dai-ichi NPP Units. The accident was initiated by a total loss of both onsite and offsite electrical power resulting in the loss of the ultimate heat sink for several days, and a consequent core melt in some units where proper mitigation strategies could not be implemented in a timely fashion. To enhance the plant's coping capability, the Diverse and Flexible Strategies (FLEX) were proposed to append the Emergency Operation Procedures (EOPs) by relying on portable equipment as an additional line of defense. To assess the success window of FLEX strategies, all sources of uncertainties need to be considered, using a physics-based model or system code. This necessitates conducting a large number of simulations to reflect all potential variations in initial, boundary, and design conditions as well as thermophysical properties, empirical models, and scenario uncertainties. Alternatively, data-driven models may provide a fast tool to predict the success window of FLEX strategies given the underlying uncertainties. This paper explores the applicability of Artificial Intelligence (AI) to identify the success window of FLEX strategy for extended SBO. The developed model can be trained and validated using data produced by the lumped parameter thermal-hydraulic code, MARS-KS, as best estimate system code loosely coupled with Dakota for uncertainty quantification. A Systems Engineering (SE) approach is used to plan and manage the process of using AI to predict the success window of FLEX strategies under extended SBO conditions.

Region-Segmental Scheme in Local Normalization Process of Digital Image (디지털영상 국부정규화처리의 영역분할 구도)

  • Hwang, Jung-Won;Hwang, Jae-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.44 no.4 s.316
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    • pp.78-85
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    • 2007
  • This paper presents a segmental scheme for regions-composed images in local normalization process. The scheme is based on local statistics computed through a moving window. The normalization algorithm uses linear or nonlinear functions to transfer the pixel distribution and the homogeneous affine of regions which is corrupted by additive noise. It adjusts the mean and standard deviation for nearest-neighbor interpoint distance between current and the normalized image signals and changes the segmentation performance according to local statistics and parameter variation adaptively. The performance of newly advanced local normalization algorithm is evaluated and compared to the performance of conventional normalization methods. Experimental results are presented to show the region segmentation properties of these approaches.

Development of a vision sensor for measuring the weld groove parameters in arc welding process (자동 아크 용접공정의 용접개선변수 측정을 위한 시각 시스템)

  • 김호학;부광석;조형석
    • Journal of Welding and Joining
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    • v.8 no.2
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    • pp.58-69
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    • 1990
  • In conventional arc welding, position error of the weld torch with respect to the weld seam and variation of groove dimension are induced by inaccurate fitup and fixturing. In this study, a vision system has been developed to recognize and compensate the position error and dimensional inaccuracy. The system uses a structured laser light illuminated on the weld groove and perceived by a C.C.D camera. A new algorithm to detect the edge of the reflected laser light is introduced for real time processing. The developed system was applied to arbitarary weld paths with various types of joint in arc welding process. The experimental results show that the proposed system can detect the weld groove parameters within good accuracy and yield good tracking performance.

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Supervised learning and frequency domain averaging-based adaptive channel estimation scheme for filterbank multicarrier with offset quadrature amplitude modulation

  • Singh, Vibhutesh Kumar;Upadhyay, Nidhi;Flanagan, Mark;Cardiff, Barry
    • ETRI Journal
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    • v.43 no.6
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    • pp.966-977
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    • 2021
  • Filterbank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) is an attractive alternative to the orthogonal frequency division multiplexing (OFDM) modulation technique. In comparison with OFDM, the FBMC-OQAM signal has better spectral confinement and higher spectral efficiency and tolerance to synchronization errors, primarily due to per-subcarrier filtering using a frequency-time localized prototype filter. However, the filtering process introduces intrinsic interference among the symbols and complicates channel estimation (CE). An efficient way to improve the CE in FBMC-OQAM is using a technique known as windowed frequency domain averaging (FDA); however, it requires a priori knowledge of the window length parameter which is set based on the channel's frequency selectivity (FS). As the channel's FS is not fixed and not a priori known, we propose a k-nearest neighbor-based machine learning algorithm to classify the FS and decide on the FDA's window length. A comparative theoretical analysis of the mean-squared error (MSE) is performed to prove the proposed CE scheme's effectiveness, validated through extensive simulations. The adaptive CE scheme is shown to yield a reduction in CE-MSE and improved bit error rates compared with the popular preamble-based CE schemes for FBMC-OQAM, without a priori knowledge of channel's frequency selectivity.