• Title/Summary/Keyword: Time-Domain Analysis

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Prediction of Unsteady Performance of a Propeller by Using Potential-Based Panel Method (포텐셜을 기저로 한 패널법에 의한 프로펠러의 비정상유동해석)

  • I.S. Moon;Y.G. Kim;C.S. Lee
    • Journal of the Society of Naval Architects of Korea
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    • v.33 no.1
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    • pp.9-18
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    • 1996
  • This paper describes a potential-based panel method for the prediction of unsteady performance of a marine propeller operating in a non-uniform flow field. Boundary-value problem, formulated by distributing the normal dipoles and sources on the blade, the hub and the shed wake, is descretized and numerically analyzed in a discretized time domain. Through an extensive test and comparison with the analytic solution, the convergence in time step is verified for a two-dimensional foil. Unsteaty analysis is then carried out for the DTRC 4118 propeller operating in a harmonic wake, and compared favorably with the experimental result. The present method is shown applicable to the analysis of unsteady performance of the propellers.

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An Identification of Dynamic Characteristics by Spectral Analysis Technique of Linear Autoregressive Model Using Lattice Filter (Lattice Filter 이용한 선형 AR 모델의 스펙트럼 분석기법에 의한 동특성 해석)

  • Lee, Tae-Yeon;Shin, Jun;Oh, Jae-Eung
    • Journal of the Korean Society of Safety
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    • v.7 no.2
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    • pp.71-79
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    • 1992
  • This paper presents a least-square algorithms of lattice structures and their use for adaptive prediction of time series generated from the dynamic system. As the view point of adaptive prediction, a new method of Identification of dynamic characteristics by means of estimating the parameters of linear auto regressive model is proposed. The fast convergence of adaptive lattice algorithms is seen to be due to the orthogonalization and decoupling properties of the lattice. The superiority of the least-square lattice is verified by computer simulation, then predictor coefficients are computed from the linear sequential time data. For the application to the dynamic characteristic analysis of unknown system, the transfer function of ideal system represented in frquency domain and the estimated one obtained by predicted coefficients are compared. Using the proposed method, the damping ratio and the natural frequency of a dynamic structure subjected to random excitations can be estimated. It is expected that this method will be widely applicable to other technical dynamic problem in which estimation of damping ratio and fundamental vibration modes are required.

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A Coherent Algorithm for Noise Revocation of Multispectral Images by Fast HD-NLM and its Method Noise Abatement

  • Hegde, Vijayalaxmi;Jagadale, Basavaraj N.;Naragund, Mukund N.
    • International Journal of Computer Science & Network Security
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    • v.21 no.12spc
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    • pp.556-564
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    • 2021
  • Numerous spatial and transform-domain-based conventional denoising algorithms struggle to keep critical and minute structural features of the image, especially at high noise levels. Although neural network approaches are effective, they are not always reliable since they demand a large quantity of training data, are computationally complicated, and take a long time to construct the model. A new framework of enhanced hybrid filtering is developed for denoising color images tainted by additive white Gaussian Noise with the goal of reducing algorithmic complexity and improving performance. In the first stage of the proposed approach, the noisy image is refined using a high-dimensional non-local means filter based on Principal Component Analysis, followed by the extraction of the method noise. The wavelet transform and SURE Shrink techniques are used to further culture this method noise. The final denoised image is created by combining the results of these two steps. Experiments were carried out on a set of standard color images corrupted by Gaussian noise with multiple standard deviations. Comparative analysis of empirical outcome indicates that the proposed method outperforms leading-edge denoising strategies in terms of consistency and performance while maintaining the visual quality. This algorithm ensures homogeneous noise reduction, which is almost independent of noise variations. The power of both the spatial and transform domains is harnessed in this multi realm consolidation technique. Rather than processing individual colors, it works directly on the multispectral image. Uses minimal resources and produces superior quality output in the optimal execution time.

Development of diagnosis index for tick/click and tone noise of blower motor using vibration signals (진동 신호를 이용한 블로워 모터 틱/클릭과 톤 소음의 진단 지수 개발)

  • Lee, Songjune;Cheong, Cheolung;Lee, In-Hyuk
    • The Journal of the Acoustical Society of Korea
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    • v.38 no.3
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    • pp.363-369
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    • 2019
  • Various studies have been conducted for the diagnosis of noise condition of complex rotary machines. In this study, diagnosis index using vibration signal is developed for the efficient and objective assessment of noise condition of a blower motor. The noise most commonly caused by the abnormal blower motor are Tick/Click noise and Tone noise. According to cause and noise characteristics, time-frequency analysis is used to diagnose Tick/Click noise, and smoothing in frequency domain is used to diagnose tone noise condition. The noise condition of the blower motors were diagnosed using the developed index and these results are compared with the diagnostic results by the experts. As a result, the agreement rate was about 95 %.

Predicting Oxynitrification layer using AI-based Varying Coefficient Regression model (AI 기반의 Varying Coefficient Regression 모델을 이용한 산질화층 예측)

  • Hye Jung Park;Joo Yong Shim;Kyong Jun An;Chang Ha Hwang;Je Hyun Han
    • Journal of the Korean Society for Heat Treatment
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    • v.36 no.6
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    • pp.374-381
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    • 2023
  • This study develops and evaluates a deep learning model for predicting oxide and nitride layers based on plasma process data. We introduce a novel deep learning-based Varying Coefficient Regressor (VCR) by adapting the VCR, which previously relied on an existing unique function. This model is employed to forecast the oxide and nitride layers within the plasma. Through comparative experiments, the proposed VCR-based model exhibits superior performance compared to Long Short-Term Memory, Random Forest, and other methods, showcasing its excellence in predicting time series data. This study indicates the potential for advancing prediction models through deep learning in the domain of plasma processing and highlights its application prospects in industrial settings.

A Study on Detection of Abnormal Patterns Based on AI·IoT to Support Environmental Management of Architectural Spaces (건축공간 환경관리 지원을 위한 AI·IoT 기반 이상패턴 검출에 관한 연구)

  • Kang, Tae-Wook
    • Journal of KIBIM
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    • v.13 no.3
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    • pp.12-20
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    • 2023
  • Deep learning-based anomaly detection technology is used in various fields such as computer vision, speech recognition, and natural language processing. In particular, this technology is applied in various fields such as monitoring manufacturing equipment abnormalities, detecting financial fraud, detecting network hacking, and detecting anomalies in medical images. However, in the field of construction and architecture, research on deep learning-based data anomaly detection technology is difficult due to the lack of digitization of domain knowledge due to late digital conversion, lack of learning data, and difficulties in collecting and processing field data in real time. This study acquires necessary data through IoT (Internet of Things) from the viewpoint of monitoring for environmental management of architectural spaces, converts them into a database, learns deep learning, and then supports anomaly patterns using AI (Artificial Infelligence) deep learning-based anomaly detection. We propose an implementation process. The results of this study suggest an effective environmental anomaly pattern detection solution architecture for environmental management of architectural spaces, proving its feasibility. The proposed method enables quick response through real-time data processing and analysis collected from IoT. In order to confirm the effectiveness of the proposed method, performance analysis is performed through prototype implementation to derive the results.

Stochastic System Reduction and Control via Component Cost Analysis (구성요소치 해석을 이용한 확률계의 축소와 제어)

  • Chae, Kyo-Soon;Lee, Dong-Hee;Park, Sung-Man;Yeo, Un-Kyung;Cho, Yun-Hyun;Heo, Hoon
    • Proceedings of the KSME Conference
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    • 2007.05a
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    • pp.921-926
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    • 2007
  • A dynamic system under random disturbance is considered in the study. In order to control the system efficiently, proper reduction of system dimension is indispensible in design stage. The reduction method using component cost analysis in conjunction with stochastic analysis is proposed for the control of a system. System response is obtained in terms of dynamic moment equation via Fokker-Plank-Kolmogorov(F-P-K) equation. The dynamic moment response of the system under random disturbance are reduced by using of deterministic version of component cost analysis. The reduced system via proposed "stochastic component cost analysis" is successfully implemented for dynamic response and shows remarkable control performance effectively utilizing "stochastic controller" in physical time domain.

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Study on Effective Arrangement of Main Engine Top-Bracing (메인 엔진 탑-브레이싱의 효과적 배치에 관한 연구)

  • Choung, Joon-Mo;Min, Dug-Ki
    • Journal of the Society of Naval Architects of Korea
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    • v.48 no.4
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    • pp.289-298
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    • 2011
  • This paper provides procedures to effectively determine arrangement of hydraulic type top-bracings, which are popular for the main engine of the mid and large sized commercial vessels. Analyzing the operation mechanism of hydraulic top-bracing, ideal unified nonlinear stiffness curve is presented for linear frequency response analysis and nonlinear transient response analysis. Nonlinear stiffnesses of the curve are determined based on the regression analysis of test results. It is noted from linear frequency response analysis, initial setting pressure is most important among the setting values of the other stiffness intervals. From transient response analyses for two top-bracing arrangement scenarios, it is recognized that, as far as initial setting pressure is well controlled for the concerning vessels, only two top-bracings are enough to suppress H-mode excitation forces from main engine.

New GPU computing algorithm for wind load uncertainty analysis on high-rise systems

  • Wei, Cui;Luca, Caracoglia
    • Wind and Structures
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    • v.21 no.5
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    • pp.461-487
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    • 2015
  • In recent years, the Graphics Processing Unit (GPU) has become a competitive computing technology in comparison with the standard Central Processing Unit (CPU) technology due to reduced unit cost, energy and computing time. This paper describes the derivation and implementation of GPU-based algorithms for the analysis of wind loading uncertainty on high-rise systems, in line with the research field of probability-based wind engineering. The study begins by presenting an application of the GPU technology to basic linear algebra problems to demonstrate advantages and limitations. Subsequently, Monte-Carlo integration and synthetic generation of wind turbulence are examined. Finally, the GPU architecture is used for the dynamic analysis of three high-rise structural systems under uncertain wind loads. In the first example the fragility analysis of a single degree-of-freedom structure is illustrated. Since fragility analysis employs sampling-based Monte Carlo simulation, it is feasible to distribute the evaluation of different random parameters among different GPU threads and to compute the results in parallel. In the second case the fragility analysis is carried out on a continuum structure, i.e., a tall building, in which double integration is required to evaluate the generalized turbulent wind load and the dynamic response in the frequency domain. The third example examines the computation of the generalized coupled wind load and response on a tall building in both along-wind and cross-wind directions. It is concluded that the GPU can perform computational tasks on average 10 times faster than the CPU.

Expression characterization and transcription regulation analysis of porcine Yip1 domain family member 3 gene

  • Ni, Dongjiao;Huang, Xiang;Wang, Zhibo;Deng, Lin;Zeng, Li;Zhang, Yiwei;Lu, Dongdong;Zou, Xinhua
    • Asian-Australasian Journal of Animal Sciences
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    • v.33 no.3
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    • pp.398-407
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    • 2020
  • Objective: The Yip1 domain family (YIPF) proteins were proposed to function in endoplasmic reticulum (ER) to Golgi transport and maintenance of the morphology of the Golgi, which were homologues of yeast Yip1p and Yif1p. YIPF3, the member 3 of YIPF family was a homolog of Yif1p. The aim of present study was to investigate the expression and regulation mechanism of porcine YIPF3. Methods: Quantitative realtime polymerase chain reaction (qPCR) was used to analyze porcine YIPF3 mRNA expression pattern in different tissues and pig kidney epithelial (PK15) cells stimulated by polyinosine-polycytidylic acid (poly [I:C]). Site-directed mutations combined with dual luciferase reporter assays and electrophoretic mobility shift assay (EMSA) were employed to reveal transcription regulation mechanism of porcine YIPF3. Results: Results showed that the mRNA of porcine YIPF3 (pYIPF3) was widely expressed with the highest levels in lymph and lung followed by spleen and liver, while weak in heart and skeletal muscle. Subcellular localization results indicated that it expressed in Golgi apparatus and plasma membranes. Upon stimulation with poly (I:C), the level of this gene was dramatically up-regulated in a time- and concentration-dependent manner. pYIPF3 core promoter region harbored three cis-acting elements which were bound by ETS proto-oncogene 2 (ETS2), zinc finger and BTB domain containing 4 (ZBTB4), and zinc finger and BTB domain containing 14 (ZBTB14), respectively. In which, ETS2 and ZBTB4 both promoted pYIPF3 transcription activity while ZBTB14 inhibited it, and these three transcription factors all played important regulation roles in tumorigenesis and apoptosis. Conclusion: The pYIPF3 mRNA expression was regulated by ETS2, ZBTB4, and ZBTB14, and its higher expression in immune organs might contribute to enhancing ER to Golgi transport of proteins, thus adapting to the immune response.