인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
학술저널
DBpia Top 10%
오류 신고하기해당 페이지 내 제목·저자·목차·페이지정보가 잘못된 경우 알려주세요!
초록·키워드
The accuracy of gas turbine performance prediction depends on the precision of the performance map. An accurate performance map is crucial for maintaining the gas turbine compressor's efficiency and stability across diverse operating conditions. Traditionally, performance maps have been created by manufacturers based on experimental data. This study aims to generate a gas turbine compressor performance map using actual operational data from power plants instead of experimental data. To achieve this, Gas Path Analysis (GPA) was implemented to calculate and correcte performance parameters according to external conditions, resulting in a more accurate performance map. Our research consists of the following steps. First, a virtual performance map was used to construct a virtual dataset to validate the accuracy of the GPA was performed using the virtual dataset, and the results were compared with the virtual data to verify the accuracy of the GPA. Next, actual operational data from power plants were applied, and extensive filtering and GPA were used to calculate the gas turbine performance parameters. Based on these performance parameters, correction criteria for operating points were established, and fitting techniques were employed to generate the performance map. Finally, the accuracy of the generated performance map was evaluated through off-design analysis and compared with actual operational data. This validation confirmed that the performance map accurately reflects various operating conditions and effectively predicts performance variations.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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UCI(KEPA) : I410-151-25-02-092302049