Репозиторий КазНИТУ

Dataset from Scintrex CG-5 gravity meters acquired at the Zhetygen calibration line in Kazakhstan

Авторы:

Kemerbayev, N (Соавтор)

Kosarev, N. (Соавтор)

Batalova, A. (Соавтор)

Sermiagin, R (Соавтор)

Kalen, Y (Соавтор)

Kassymkanova, K.-K (Соавтор)

Mussina, G (Соавтор)

Издательство:

Elsevier Inc.

Дата издания

12.11.2024

Область исследования

Инжиниринг и технологии

Тип исследования

Фундаментальное

Аннотация (краткое описание)

The article provides a dataset derived from Scintrex CG-5 gravity meter observation files collected during five years of annual measurements along the Zhetygen calibration line utilizing three meters. Geoken, a Kazakhstani enterprise, routinely conducts these measurements to calibrate its meters necessary for manufacturing operations. Researchers can use this constantly updated dataset to study the behavior of the CG-5 gravity meters' calibration function in time and the measurement range. The measurement range is 100,900 µGal. © 2024 The Author(s)

Соответствие целям устойчивого развития (ЦУР)

Индустриализация, инновации и инфраструктура

URI

https://www.scopus.com/record/display.url?eid=2-s2.0-85210681245&origin=resultslist

DOI

10.1016/j.dib.2024.111151

Тип публикаций

Статья

Сведения о финансировании

We extend our heartfelt appreciation to those who contributed to the execution of this research. Gratitude is extended to the scientific team involved in the project \u201CDevelopment of the Geoid Model of the Republic of Kazakhstan as the Basis of a Unified State Coordinate and Height System,\u201D including representatives from Satbayev University, the Institute of Ionosphere, and GEOID LLP for their significant contributions throughout all phases of the article's development. We express our gratitude to our colleagues at SPC Geoken LLP for granting access to essential resources and support in executing the experimental study. We like to recognize the significant contributions of our co-authors and colleagues who engaged in discussions regarding the results and assisted in refining the final version of the work. We express our gratitude to Kanat Samarkhanov, Senior Researcher at Al-Farabi Kazakh National University, for his invaluable recommendations. We express our gratitude to all anonymous reviewers for their helpful feedback and recommendations, which have greatly enhanced the quality of this publication. The authors declare that they have no known competing financial interests or personal relationships that have or could be perceived to have influenced the work reported in this article.

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