• Title/Summary/Keyword: Air data

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Design and Integration of a Dual Redundancy Air Data System for Unmanned Air Vehicles (무인항공기 이중화 대기자료시스템 설계 및 통합 연구)

  • Won, Dae-Yeon;Yun, Seonghun;Lee, Hongju;Hong, Jin-Sung;Hwang, Sun-Yu;Lim, Heung-Sik;Kim, Taekyeum
    • Journal of the Korea Institute of Military Science and Technology
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    • v.23 no.6
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    • pp.639-649
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    • 2020
  • Air data systems measure airspeed, pressure altitude, angle of attack and angle of sideslip. These measurements are essential for operating flight control laws to ensure safe flights. Since the loss or corruption of air data measurements is considered as catastrophic, a high level of operational reliability needs to be achieved for air data systems. In the case of unmanned air vehicles, failure of any of air data sensors is more critical due to the absence of onboard pilot decision aid. This paper presents design of a dual redundancy air data system and the integration process for an unmanned air vehicle. The proposed dual-redundant architecture is based on two independent air data probes and redundancy management by central processing in two independent flight control computers. Starting from unit testing of single air data sensor, details are provided of system level tests used to meet overall requirements. Test results from system integration demonstrate the efficiency of the proposed process.

Design of Power Efficient Waveforms for Long Range Air-to-Air Data Links (장거리 공대공 데이터링크를 위한 저전력 웨이브폼 설계)

  • Haeuk Lee;Je Heo;Gijung Yang;Taehee Lim;Hyukjun Oh
    • Journal of Advanced Navigation Technology
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    • v.28 no.2
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    • pp.250-253
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    • 2024
  • This paper proposes a low-power waveform for a long-range air-to-air data link. In the case of an air-to-air data link, data communication is performed in the air and high Doppler shift may occur depending on the flight speed, so a waveform based on the non-coherent method is suitable. In addition, since it is mounted on an aircraft, it must have low power characteristics. This paper proposes a waveform that combines a modulation technique based on frequency modulation and pulse position modulation that can turn on/off the transmission signal. As a result of the performance analysis, it was shown that the performance was suitable for air-to-air operation while showing low power characteristics.

Analysis and Prediction of (Ultra) Air Pollution based on Meteorological Data and Atmospheric Environment Data (기상 데이터와 대기 환경 데이터 기반 (초)미세먼지 분석과 예측)

  • Park, Hong-Jin
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.14 no.4
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    • pp.328-337
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    • 2021
  • Air pollution, which is a class 1 carcinogen, such as asbestos and benzene, is the cause of various diseases. The spread of ultra-air pollution is one of the important causes of the spread of the corona virus. This paper analyzes and predicts fine dust and ultra-air pollution from 2015 to 2019 based on weather data such as average temperature, precipitation, and average wind speed in Seoul and atmospheric environment data such as SO2, NO2, and O3. Linear regression, SVM, and ensemble models among machine learning models were compared and analyzed to predict fine dust by grasping and analyzing the status of air pollution and ultra-air pollution by season and month. In addition, important features(attributes) that affect the generation of fine dust and ultra-air pollution are identified. The highest ultra-air pollution was found in March, and the lowest ultra-air pollution was observed from August to September. In the case of meteorological data, the data that has the most influence on ultra-air pollution is average temperature, and in the case of meteorological data and atmospheric environment data, NO2 has the greatest effect on ultra-air pollution generation.

A Low Power Wireless Communication-based Air Pollutants Measuring System (저전력 무선통신 기반 대기오염 측정시스템)

  • Kang, Jeong Gee;Lee, Bong Hwan
    • Journal of Information Technology Applications and Management
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    • v.28 no.6
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    • pp.87-95
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    • 2021
  • Recently interest for air pollution is gradually increasing. However, according to the environmental assessment of air quality, the level of air pollution in the nation is quite serious, and air pollutants measuring facilities are also not enough. In this paper, a secure air pollutants sensor system based low power wireless communication is designed and implemented. The proposed system is composed of three parts: air pollutants measuring sensors module, LoRa-based data transmission module, and monitoring module. In the air pollutants measuring module, the MSP430 board with six big air pollutants measuring sensors are used. The air pollutants sensing data is transmitted to the control server in the monitoring system using LoRa transmission module. The received sensing data is stored in the database of the monitoring system, and visualized in real-time on the map of the sensor locations. The implemented air pollutant sensor system can be used for measuring the level of air quality conveniently in our daily lives.

Air-Data Estimation for Air-Breathing Hypersonic Vehicles

  • Kang, Bryan-Heejin
    • Transactions on Control, Automation and Systems Engineering
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    • v.1 no.1
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    • pp.75-86
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    • 1999
  • An air-data estimator for generic air-breathing hypersonic vehicles (AHSVs) is developed and demonstrated with an example vehicle configuration. The AHSV air-data estimation strategy emphasized improvement of the angle of attack estimate accuracy to a degree necessitated by the stringent operational requirements of the air-breathing propulsion. the resulting estimation problem involves highly nonlinear diffusion process (propagation); consequently, significant distortion of a posteriori conditional density is suspected. A simulation based statistical analysis tool is developed to characterize the nonlinear diffusion process. The statistical analysis results indicate that the diffusion process preserves the symmetry and unimodality of initial probability density shape state variables, and provide the basis for applicability of an Extended Kalman Filter (EKF). An EKF is designed for the AHSV air-data system and the air data estimation capabilities are demonstrated.

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Review of Internet of Things-Based Artificial Intelligence Analysis Method through Real-Time Indoor Air Quality and Health Effect Monitoring: Focusing on Indoor Air Pollution That Are Harmful to the Respiratory Organ

  • Eunmi Mun;Jaehyuk Cho
    • Tuberculosis and Respiratory Diseases
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    • v.86 no.1
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    • pp.23-32
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    • 2023
  • Everyone is aware that air and environmental pollutants are harmful to health. Among them, indoor air quality directly affects physical health, such as respiratory rather than outdoor air. However, studies that have examined the correlation between environmental and health information have been conducted with public data targeting large cohorts, and studies with real-time data analysis are insufficient. Therefore, this research explores the research with an indoor air quality monitoring (AQM) system based on developing environmental detection sensors and the internet of things to collect, monitor, and analyze environmental and health data from various data sources in real-time. It explores the usage of wearable devices for health monitoring systems. In addition, the availability of big data and artificial intelligence analysis and prediction has increased, investigating algorithmic studies for accurate prediction of hazardous environments and health impacts. Regarding health effects, techniques to prevent respiratory and related diseases were reviewed.

Estimation of the air temperature over the sea using the satellite data

  • Kwon B. H.;Hong G. M.;Kim Y. S.
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.392-393
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    • 2005
  • Due to the temporal and spatial simultaneity and the high-frequency repetition, the data set retrieved from the satellite observation is considered to be the most desirable ones for the study of air-sea interaction. With rapidly developing sensor technology, satellite-retrieved data has experienced improvement in the accuracy and the number of parameters. Nevertheless, since it is still impossible to directly measure the heat fluxes between air and sea, the bulk method is an exclusive way for the evaluation of the heat fluxes at the sea surface. It was noted that the large deviation of air temperature in the winter season by the linear regression despite good correlation coefficients. We propose a new algorithm based on the Fourier series with which the SST and the air temperature. We found that the mean of air temperature is a function of the mean of SST with the monthly gradient of SST inferred from the latitudinal variation of SST and the spectral energy of air temperature is related linearly to that of SST. An algorithm to obtain the air temperature over the sea was completed with a proper analysis on the relation between of air temperature and of SST. This algorithm was examined by buoy data and therefore the air temperature over the sea can be retrieved based on just satellite data.

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An Analysis on Effects of the Initial Condition and Emission on PM10 Forecasting with Data Assimilation (초기조건과 배출량이 자료동화를 사용하는 미세먼지 예보에 미치는 영향 분석)

  • Park, Yun-Seo;Jang, Im-suk;Cho, Seog-yeon
    • Journal of Korean Society for Atmospheric Environment
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    • v.31 no.5
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    • pp.430-436
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    • 2015
  • Numerical air quality forecasting suffers from the large uncertainties of input data including emissions, boundary conditions, earth surface properties. Data assimilation has been widely used in the field of weather forecasting as a way to reduce the forecasting errors stemming from the uncertainties of input data. The present study aims at evaluating the effect of input data on the air quality forecasting results in Korea when data assimilation was invoked to generate the initial concentrations. The forecasting time was set to 36 hour and the emissions and initial conditions were chosen as tested input parameters. The air quality forecast model for Korea consisting of WRF and CMAQ was implemented for the test and the chosen test period ranged from November $2^{nd}$ to December $1^{st}$ of 2014. Halving the emission in China reduces the forecasted peak value of $PM_{10}$ and $SO_2$ in Seoul as much as 30% and 35% respectively due to the transport from China for the no-data assimilation case. As data assimilation was applied, halving the emissions in China has a negligible effect on air pollutant concentrations including $PM_{10}$ and $SO_2$ in Seoul. The emissions in Korea still maintain an effect on the forecasted air pollutant concentrations even after the data assimilation is applied. These emission sensitivity tests along with the initial condition sensitivity tests demonstrated that initial concentrations generated by data assimilation using field observation may minimize propagation of errors due to emission uncertainties in China. And the initial concentrations in China is more important than those in Korea for long-range transported air pollutants such as $PM_{10}$ and $SO_2$. And accurate estimation of the emissions in Korea are still necessary for further improvement of air quality forecasting in Korea even after the data assimilation is applied.

A Study on Air-distribution method for the Thermal Environmental Control in the Data Center (데이터센터의 합리적인 환경제어를 위한 공기분배 시스템에 대한 연구)

  • Cho, Jin-Kyun;Cha, Ji-Hyoung;Hong, Min-Ho;Yeon, Chang-Kun
    • Proceedings of the SAREK Conference
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    • 2008.11a
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    • pp.487-492
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    • 2008
  • The cooling of data centers has emerged as a significant challenge as the density of IT server increases. Server installations, along with the shrinking physical size of servers and storage systems, has resulted in high power density and high heat density. The introduction of high density enclosures into a data center creates the potential for "hot spots" within the room that the cooling system may not be able to address, since traditional designs assume relatively uniform cooling patterns within a data center. The cooling system for data center consists of a CRAC or CRAH unit and the associated air distribution system. It is the configuration of the distribution system that primarily distinguishes the different types of data center cooling systems, this is the main subject of this paper.

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Investigation of Natural Air Drying of Rough Rice Based on The Weather Data in Taegu Area (대구지방의 기상자료를 기초로한 벼의 상온통풍건조에 관한 조사연구)

  • 김재열;서승덕;금동혁;서석건
    • Journal of Biosystems Engineering
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    • v.5 no.1
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    • pp.15-23
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    • 1980
  • Natural-air drying systems have been extensively used for cereal grains, and many researches on the systems have been conducted in foreign countries. However, little research on drying rough rice with natural air has been done. Especially . little research on natural air drying of rough rice based on weather data has been done in Korean. The objective of this study was to present fundamental data for estimating optimum requirements and basic information available for natural air drying of rough rice based on the weather data . The weather data analyzed in this study were the 10-year (1969 to 1978) record of air temperatures, wet-bulb temperatures and relative humidities, which were three-hourly observations in Taegu area. The results of this study are summarized as follows ; 1 From the results of weather data analysis the average air temperature was about $14.8^\circ$and the average relative humidty 67.5% . Average equilibrium moisture content appeared to be 13.8 percent on wet basis, which showed great potential for natural air drying in Taegue area in October. 2. Possible fan operation time based on the equilibrium moisture content of 15% on wet basis was about 14 hours a day during October in Taegu area. Probabilities of possible drying days based on minimum time available for drying in a day were analyzed. 3. Minimum air flow requirements based on the worst year were determined for different fan operation methods and initial moisture contents.

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