BibTex Citation Data :
@article{BFIS3038, author = {Supriyadi Supriyadi}, title = {Membangun Filter Berdasarkan Model Amblesan dan Dinamika Muka Air Tanah Untuk Memisahkan Sumber Anomali Gaya Berat Mikro Antar Waktu}, journal = {BERKALA FISIKA}, volume = {13}, number = {2}, year = {2012}, keywords = {}, abstract = { Filter has been fabricated based on the model of microgravity two sources of anomalies over time, ie subsidence and groundwater level dynamics. Model adjusted for field conditions with several assumptions, one of which is the porosity of the aquifer consists of homogeneous sand and clay sand is 30% filled with water. Gravity response due to subsidence, soil water dynamics and combined the two done 2D FFT. FFT process is changing the data from the spatial region to region frekuensi. Furthermore, the filter is built by performing mathematical operations division, which is output divided by input. The output data of the gravity response due to subsidence or ground water dynamics, and input is combined response and the dynamics of gravity due to subsidence of ground water. Experimental results show that in order to create a filter that gives a small error when using filters subsidence dimensional (XY) of the same or greater dimension of subsidence are filtered. Differences dimensional subsidence subsidence filter with a filter at X = 100 m and Y = 100 m gives 1.744% error. Giving a small error when using filters subsidence dimension (Z) the same or smaller dimensions are filtered subsidence. Differences dimensional subsidence subsidence filter with a filter of 1 cm gives 7.322% error. For the case of subsidence of more than one location indicates that the smallest error occurs if you use the filters subsidence dimension equal to - average dimensions of subsidence to be filtered. Keywords: filter, subsidence, groundwater }, pages = {1--10} url = {https://ejournal.undip.ac.id/index.php/berkala_fisika/article/view/3038} }
Refworks Citation Data :
Filter has been fabricated based on the model of microgravity two sources of anomalies over time, ie subsidence and groundwater level dynamics. Model adjusted for field conditions with several assumptions, one of which is the porosity of the aquifer consists of homogeneous sand and clay sand is 30% filled with water. Gravity response due to subsidence, soil water dynamics and combined the two done 2D FFT. FFT process is changing the data from the spatial region to region frekuensi. Furthermore, the filter is built by performing mathematical operations division, which is output divided by input. The output data of the gravity response due to subsidence or ground water dynamics, and input is combined response and the dynamics of gravity due to subsidence of ground water. Experimental results show that in order to create a filter that gives a small error when using filters subsidence dimensional (XY) of the same or greater dimension of subsidence are filtered. Differences dimensional subsidence subsidence filter with a filter at X = 100 m and Y = 100 m gives 1.744% error. Giving a small error when using filters subsidence dimension (Z) the same or smaller dimensions are filtered subsidence. Differences dimensional subsidence subsidence filter with a filter of 1 cm gives 7.322% error. For the case of subsidence of more than one location indicates that the smallest error occurs if you use the filters subsidence dimension equal to - average dimensions of subsidence to be filtered.
Keywords: filter, subsidence, groundwater
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Last update: 2024-11-22 04:22:02
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