• Journal of the Korean Society of Propulsion Engineers
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• v.22 no.3
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• pp.72-80
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• 2018

Combustion instabilities are caused by the feedback relationship between heat release perturbations and acoustic pressure oscillations in the combustor. Studies on the combustion instability in an annular combustor have recently received great attention due to the enhanced NOx requirement in aero-engines. In this study, a thermoacoustic network model was developed in order to calculate the acoustic characteristics for various modes in the annular combustor. The network model is combined with flame transfer function(FTF) in order to calculate the stability of the combustor. Numerical results are compared with measurement data.

• Nuclear Engineering and Technology
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• v.48 no.4
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• pp.1047-1057
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• 2016

Design engineering process for field programmable gate array (FPGA)-based reactor trip functions are developed in this work. The process discussed in this work is based on the systems engineering approach. The overall design process is effectively implemented by combining with design and implementation processes. It transforms its overall development process from traditional V-model to Y-model. This approach gives the benefit of concurrent engineering of design work with software implementation. As a result, it reduces development time and effort. The design engineering process consisted of five activities, which are performed and discussed: needs/systems analysis; requirement analysis; functional analysis; design synthesis; and design verification and validation. Those activities are used to develop FPGA-based reactor bistable trip functions that trigger reactor trip when the process input value exceeds the setpoint. To implement design synthesis effectively, a model-based design technique is implied. The finite-state machine with data path structural modeling technique together with very high speed integrated circuit hardware description language and the Aldec Active-HDL tool are used to design, model, and verify the reactor bistable trip functions for nuclear power plants.

• Korean Journal of Remote Sensing
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• v.19 no.3
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• pp.255-261
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• 2003

Recently, the enormous increase in the volume of remotely sensed data is being acquired by an ever-growing number of earth observation satellites. The combining of diversely sourced imagery together is an important requirement in many applications such as data fusion, city modeling and object recognition. Aerial triangulation is a procedure to reconstruct object space from imagery. However, since the different kinds of imagery have their own sensor model, characteristics, and resolution, the previous approach in aerial triangulation (or georeferencing) is purformed on a sensor model separately. This study evaluated the advantages of aerial triangulation of large number of images from multi-sensors simultaneously. The incorporated multi-sensors are frame, push broom, and whisky broom cameras. The limits and problems of push-broom or whisky broom sensor models can be compensated by combined triangulation with other sensors The reconstructed object space from multi-sensor triangulation is more accurate than that from a single model. Experiments conducted in this study show the more accurately reconstructed object space from multi-sensor triangulation.

• International Journal of Railway
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• v.4 no.2
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• pp.42-49
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• 2011

Today, rolling stock has become a fast and convenient mode of transportation and has witnessed increased demand. But the speed improvement has resulted in increased aerodynamic noise and therefore residential districts near the railroad tracks are exposed to ever increasing noise level. A study on methodologies for measuring and appraising rolling stock's environmental noise has therefore become an important area of endeavor. In the case of the environmental noise, there are no changes in tone so prediction can be made by reducing areas around the railway. The present study explores estimation of the noise around the railway using scale model, and the source of the noise has been investigated as well. The scale model of rolling stock will have to be able to measure high frequency noise and it is required to be generated in a short amount of time. Since popping a balloon or firing a gun fits this requirement the present study analyzed the characteristics of these two different noise sources. Measurement was made in a large vacant lot and the reflection due to the ground was also examined. The method proposed here can be used in the future for predicting the environmental noise of railway vehicles.

• Journal of Korean Institute of Architectural Sustainable Environment and Building Systems
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• v.12 no.6
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• pp.579-590
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• 2018

Anomaly detection on building energy consumption has been regarded as an effective tool to reduce energy saving on building operation and maintenance. However, it requires energy model and FDD expert for quantitative model approach or large amount of training data for qualitative/history data approach. Both method needs additional time and labors. This study propose a machine learning and data science approach to define faulty conditions on hourly building energy consumption with reducing data amount and input requirement. It suggests an application of Support Vector Data Description (SVDD) method on training normal condition of hourly building energy consumption incorporated with hourly outdoor air temperature and time integer in a week, 168 data points and identifying hourly abnormal condition in the next day. The result shows the developed model has a better performance when the ${\nu}$ (probability of error in the training set) is 0.05 and ${\gamma}$ (radius of hyper plane) 0.2. The model accuracy to identify anomaly operation ranges from 70% (10% increase anomaly) to 95% (20% decrease anomaly) for daily total (24 hours) and from 80% (10% decrease anomaly) to 10%(15% increase anomaly) for occupied hours, respectively.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.83-93
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• 2021

COVID-19 poses a major risk to global health, highlighting the importance of faster and proper diagnosis. To handle the rise in the number of patients and eliminate redundant tests, healthcare information exchange and medical data are transmitted between healthcare centres. Medical data sharing helps speed up patient treatment; consequently, exchanging healthcare data is the requirement of the present era. Since healthcare professionals share data through the internet, security remains a critical challenge, which needs to be addressed. During the COVID-19 pandemic, computed tomography (CT) and X-ray images play a vital part in the diagnosis process, constituting information that needs to be shared among hospitals. Encryption and image steganography techniques can be employed to achieve secure data transmission of COVID-19 images. This study presents a new encryption with the image steganography model for secure data transmission (EIS-SDT) for COVID-19 diagnosis. The EIS-SDT model uses a multilevel discrete wavelet transform for image decomposition and Manta Ray Foraging Optimization algorithm for optimal pixel selection. The EIS-SDT method uses a double logistic chaotic map (DLCM) is employed for secret image encryption. The application of the DLCM-based encryption procedure provides an additional level of security to the image steganography technique. An extensive simulation results analysis ensures the effective performance of the EIS-SDT model and the results are investigated under several evaluation parameters. The outcome indicates that the EIS-SDT model has outperformed the existing methods considerably.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.4
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• pp.301-309
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• 2021

Pulse count method is the classical reaction wheel speed detection method. In this study, we represent the pulse count method as mathematical equations. Instead of rotation speed, we model the reaction wheel rotation through rotation angle during sampling periods. We verified the effectiveness of the proposed model by comparing the pulse counts variation and averaging method effects from the model and previous research results. Then, we add tacho pulse non-uniformity to this verified model, and examine the errors of pulse count method. We express the measurement error increasement due to non-uniformity as mathematical equations, and also shows the requirement of moving average numbers to offset the measurement errors.

• Coupled systems mechanics
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• v.12 no.1
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• pp.1-20
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• 2023

On the basis of the explicit time-domain method, an investigation is performed on the influence of the rotational stiffness and rotational damping of the vehicle body and front-rear bogies on the dynamic responses of the vehicle-bridge coupled systems. The equation of motion for the vehicle subsystem is derived employing rigid dynamical theories without considering the rotational stiffness and rotational damping of the vehicle body, as well as the front-rear bogies. The explicit expressions for the dynamic responses of the vehicle and bridge subsystems to contact forces are generated utilizing the explicit time-domain method. Due to the compact wheel-rail model, which reflects the compatibility requirement of the two subsystems, the explicit expression of the evolutionary statistical moment for the contact forces may be performed with relative ease. Then, the evolutionary statistical moments for the respective responses of the two subsystems can be determined. The numerical results indicate that the simplification of vehicle model has little effect on the responses of the bridge subsystem and the vehicle body, except for the responses of the rotational degrees of freedom for the vehicle subsystem, regardless of whether deterministic or random analyses are performed.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.301-312
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• 2017

Quality evaluation and control represent increasingly important concerns for construction quality management. There is an evident need for a standard data model to be used as the basis for computer-aided quality management. This study focuses on how to realize evaluation of construction quality based on BIM and database technology. In this paper, the reinforced concrete main structure is taken as an example, and the BP neural network evaluation model is established by inquiring current construction quality acceptance specification and evaluation standard. Furthermore, IFC standard is extended to integrate quality evaluation information and realize the mapping of evaluation information in BIM model, contributing to the visualization and transfer sharing of evaluation information. Furthermore, the conceptual entity model is designed to build quality evaluation database, and this paper select MySQL workbench system to achieve the establishment of the database. This study is organized to realize the requirement of visualization and data integration on construction quality evaluation which makes it more effective, convenient, intuitive, easy to find quality problems and provide more comprehensive and reliable data for the quality management of construction enterprises and official construction administratiors.

• Corrosion Science and Technology
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• v.23 no.3
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• pp.228-234
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• 2024

Zinc wiping is a phenomenon used to control zinc-coating thickness on steel substrate during hot dip galvanizing by equipment called air knife. Uniformity of zinc coating weight in length and width profile along with surface quality are most critical quality parameters of galvanized steel. Deviation from tolerance level of coating thickness causes issues like overcoating (excess consumption of costly zinc) or undercoating leading to rejections due to non-compliance of customer requirement. Main contributor of deviation from target coating weight is dynamic change in air knives equipment setup when thickness, width, and type of substrate changes. Additionally, cold coating measurement gauge measure coating weight after solidification but are installed down the line from air knife resulting in delayed feedback. This study presents a coating weight control model (Galvantage) predicting critical air knife parameters air pressure, knife distance from strip and line speed for coating control. A reverse engineering approach is adopted to design a predictive, prescriptive, and descriptive model recommending air knife setups that estimate air knife distance and expected coating weight in real time. Implementation of this model eliminates feedback lag experienced due to location of coating gauge and achieving setup without trial-error by operator.