인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
개인구독
소속 기관이 없으신 경우, 개인 정기구독을 하시면 저렴하게
논문을 무제한 열람 이용할 수 있어요.
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.
초록·키워드
Abstract Detecting buried active faults presents the challenge of precisely locating the upper breakpoint, the shallowest point in the Quaternary system where faults occur. Microtremor survey technology, unaffected by urban electromagnetic interference, offers an eco-friendly and efficient method for investigating buried faults and stratigraphic structures in urban areas. This research uses microtremor survey technology to identify the upper breakpoint of the buried Nankou-Sunhe Fault in Changping, Beijing. For data collection, 17 microtremor survey points were deployed across the northern section of the Nankou-Sunhe fault, employing a three-point nested circular array with a point spacing of approximately 200 m to form a profile spanning approximately 320 m. For data analysis, the spatial autocorrelation method was utilized. Each measurement point was divided into 9 sets of radii, ranging from a minimum of approximately 4 m to a maximum of 28 m. The correlation coefficients for each set were calculated, and the dispersion curve for each measurement point was generated by fitting the average coefficients with the Bessel function of the first kind of order zero. The apparent S-wave velocity was determined directly from the dispersion curve using empirical formulas and interpolated to generate the contour cross-section map. Integrating the section and inverted S-wave velocity data can significantly enhance interpretation accuracy, and based on these data, the spatial development characteristics and upper breakpoint locations of the Nankou-Sunhe fault zone were analyzed, and the strata shallower than 100 m were deduced. The results align well with known geological data, such as luminescence dating and 14 C dating from boreholes at nearby locations. Graphical Abstract
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.