Rock Mass Characterization

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Kamajati Dhatu - One of the best experts on this subject based on the ideXlab platform.

  • Analisis Karakteristik Massa Batuan di Sektor Lemajung, Kalan, Kalimantan Barat
    'National Atomic Energy Agency of Indonesia (BATAN)', 2015
    Co-Authors: Syaeful Heri, Kamajati Dhatu
    Abstract:

    Karakterisasi Massa batuan diperlukan dalam suatu rancangan bukaan batuan, dimana perhitungan sifat-sifat teknis dari Massa batuan menjadi hal yang penting untuk diperhatikan. Sektor Lemajung merupakan salah satu area prospek untuk penambangan uranium di Kalan, Kalimantan Barat. Tujuan penelitian adalah mendapatkan data karakteristik Massa batuan yang merupakan data dasar bagi perencanaan pengembangan teknik penambangan cebakan bahan galian. Metodologi yang digunakan adalah dengan pengambilan contoh batuan untuk analisis laboratorium mekanika batuan, pengamatan rekahan, dan pengamatan kondisi airtanah. Parameter batuan yang dianalisis meliputi uniaxial compressive strength (UCS), Rock quality designation (RQD), jarak rekahan, kondisi rekahan, dan airtanah. Hasil analisis menyimpulkan bahwa metalanau sebagai litologi yang mengandung uranium di Sektor Lemajung mempunyai nilai Rock Mass rating (RMR) sebesar 56 atau kelas Massa batuan III: fair Rock pada kedalaman sekitar 60 m, dan pada kedalaman 280 m nilai RMR mencapai 82 atau kelas Massa batuan I: very good Rock. Data nilai RMR tersebut selanjutnya dapat digunakan dalam analisis pembuatan terowongan pada model tambang bawah tanah atau analisis kestabilan lereng pada model tambang terbuka. Rock Mass Characterization is required in design of Rock opening, which calculation of engineering characters of Rock Mass become one important parameter toconsider. Lemajung sector is one of prospect area for uranium mining in Kalan, West Kalimantan. Purpose of research is to acquire Rock Mass characteristicsas basic data for planning the development of mining technique of ore deposit. Methodology applied is Rock sampling for Rock mechanic laboratory analysis, observation of joints, and observation of groundwater condition. Rock parameters analyzed includes uniaxial compressive strength (UCS), Rock quality designation (RQD), joint spacing, joint condition, and groundwater. Analysis concluded that metasiltstonewhich is lithology contained uranium in Lemajung Sector has Rock Mass rating (RMR) value of 56 or Rock Mass class III: fair Rock in the depth of around 60 m, and in the depth of 280 m RMR value reach 82 or Rock Mass class I: very good Rock. RMR value data furthermore could be used for analysis of tunneling in the model of underground mine or slope stability analysis in the model of open pit mine

Dhatu Kamajati - One of the best experts on this subject based on the ideXlab platform.

  • Analisis Karakteristik Massa Batuan di Sektor Lemajung, Kalan, Kalimantan Barat
    Center for Nuclear Minerals Technology, 2015
    Co-Authors: Heri Syaeful, Dhatu Kamajati
    Abstract:

    Rock Mass Characterization is required in design of Rock opening, which calculation of engineering characters of Rock Mass become one important parameter toconsider. Lemajung sector is one of prospect area for uranium mining in Kalan, West Kalimantan. Purpose of research is to acquire Rock Mass characteristicsas basic data for planning the development of mining technique of ore deposit. Methodology applied is Rock sampling for Rock mechanic laboratory analysis, observation of joints, and observation of groundwater condition. Rock parameters analyzed includes uniaxial compressive strength (UCS), Rock quality designation (RQD), joint spacing, joint condition, and groundwater. Analysis concluded that metasiltstonewhich is lithology contained uranium in Lemajung Sector has Rock Mass rating (RMR) value of 56 or Rock Mass class III: fair Rock in the depth of around 60 m, and in the depth of 280 m RMR value reach 82 or Rock Mass class I: very good Rock. RMR value data furthermore could be used for analysis of tunneling in the model of underground mine or slope stability analysis in the model of open pit mine

Funehag Johan - One of the best experts on this subject based on the ideXlab platform.

  • Rock support prediction based on measurement while drilling technology
    'Springer Science and Business Media LLC', 2021
    Co-Authors: Van Eldert Jeroen, Saiang David, Funehag Johan, Schunnesson Håkan
    Abstract:

    In tunnelling, Rock Mass support is designed based on the observed Rock Mass conditions. These conditions are determined by Rock Mass Characterization. Measurement while drilling (MWD), one such Characterization method, acquires drill parameter data during drilling. These data can be used to predict Rock Mass conditions ahead of the face. In this study, grout-hole MWD data are collected at one of the main tunnels in the large infrastructural project Stockholm bypass tunnels. The normalized and filtered MWD data are correlated to the Rock Mass characteristics using multilinear regression and the Levenberg-Marquardt method. Although a strong numerical correlation cannot be obtained, the results are promising. As a result, a holistic visual approach, which linked the MWD parameters with the Rock Mass classification and Rock support requirements, was developed.Validerad;2021;Nivå 2;2021-02-09 (alebob)

  • Improved filtering and normalizing of Measurement-While-Drilling (MWD) data in tunnel excavation
    'Elsevier BV', 2020
    Co-Authors: Van Eldert Jeroen, Schunnesson Håkan, Saiang David, Funehag Johan
    Abstract:

    Measurement-While-Drilling (MWD) data are complex because of the drilling process and drilling system. Swift and accurate normalization and filtration processes are required if MWD data are to be used for Rock Mass Characterization. The current method for MWD data filtration does not consider all the effects of the drilling process, e.g., collaring or extension rod coupling. This paper presents a new method for MWD data filtration and normalization. The new method filters the operational parameters and normalizes the data on a stepwise algorithm, including production factors (collaring drill hole and rod extension coupling) and Rock drill settings. It shows reliable results for the normalization and filtration of MWD data gathered for drill hole collaring and coupled extension drill rods at grout holes and for different Rock drills.Validerad;2020;Nivå 2;2020-09-01 (johcin)

  • Improved filtering and normalizing of Measurement-While-Drilling (MWD) data in tunnel excavation
    2020
    Co-Authors: Van Eldert Jeroen, Schunnesson Håkan, Saiang David, Funehag Johan
    Abstract:

    Measurement-While-Drilling (MWD) data are complex because of the drilling process and drilling system. Swift and accurate normalization and filtration processes are required if MWD data are to be used for Rock Mass Characterization. The current method for MWD data filtration does not consider all the effects of the drilling process, e.g., collaring or extension rod coupling. This paper presents a new method for MWD data filtration and normalization. The new method filters the operational parameters and normalizes the data on a stepwise algorithm, including production factors (collaring drill hole and rod extension coupling) and Rock drill settings. It shows reliable results for the normalization and filtration of MWD data gathered for drill hole collaring and coupled extension drill rods at grout holes and for different Rock drills

  • Rock support prediction based on measurement while drilling technology
    'Springer Science and Business Media LLC', 2020
    Co-Authors: Van Eldert Jeroen, Saiang David, Funehag Johan, Schunnesson Håkan
    Abstract:

    In tunnelling, Rock Mass support is designed based on the observed Rock Mass conditions. These conditions are determined by Rock Mass Characterization. Measurement while drilling (MWD), one such Characterization method, acquires drill parameter data during drilling. These data can be used to predict Rock Mass conditions ahead of the face. In this study, grout-hole MWD data are collected at one of the main tunnels in the large infrastructural project Stockholm bypass tunnels. The normalized and filtered MWD data are correlated to the Rock Mass characteristics using multilinear regression and the Levenberg-Marquardt method. Although a strong numerical correlation cannot be obtained, the results are promising. As a result, a holistic visual approach, which linked the MWD parameters with the Rock Mass classification and Rock support requirements, was developed

Syaeful Heri - One of the best experts on this subject based on the ideXlab platform.

  • Analisis Karakteristik Massa Batuan di Sektor Lemajung, Kalan, Kalimantan Barat
    'National Atomic Energy Agency of Indonesia (BATAN)', 2015
    Co-Authors: Syaeful Heri, Kamajati Dhatu
    Abstract:

    Karakterisasi Massa batuan diperlukan dalam suatu rancangan bukaan batuan, dimana perhitungan sifat-sifat teknis dari Massa batuan menjadi hal yang penting untuk diperhatikan. Sektor Lemajung merupakan salah satu area prospek untuk penambangan uranium di Kalan, Kalimantan Barat. Tujuan penelitian adalah mendapatkan data karakteristik Massa batuan yang merupakan data dasar bagi perencanaan pengembangan teknik penambangan cebakan bahan galian. Metodologi yang digunakan adalah dengan pengambilan contoh batuan untuk analisis laboratorium mekanika batuan, pengamatan rekahan, dan pengamatan kondisi airtanah. Parameter batuan yang dianalisis meliputi uniaxial compressive strength (UCS), Rock quality designation (RQD), jarak rekahan, kondisi rekahan, dan airtanah. Hasil analisis menyimpulkan bahwa metalanau sebagai litologi yang mengandung uranium di Sektor Lemajung mempunyai nilai Rock Mass rating (RMR) sebesar 56 atau kelas Massa batuan III: fair Rock pada kedalaman sekitar 60 m, dan pada kedalaman 280 m nilai RMR mencapai 82 atau kelas Massa batuan I: very good Rock. Data nilai RMR tersebut selanjutnya dapat digunakan dalam analisis pembuatan terowongan pada model tambang bawah tanah atau analisis kestabilan lereng pada model tambang terbuka. Rock Mass Characterization is required in design of Rock opening, which calculation of engineering characters of Rock Mass become one important parameter toconsider. Lemajung sector is one of prospect area for uranium mining in Kalan, West Kalimantan. Purpose of research is to acquire Rock Mass characteristicsas basic data for planning the development of mining technique of ore deposit. Methodology applied is Rock sampling for Rock mechanic laboratory analysis, observation of joints, and observation of groundwater condition. Rock parameters analyzed includes uniaxial compressive strength (UCS), Rock quality designation (RQD), joint spacing, joint condition, and groundwater. Analysis concluded that metasiltstonewhich is lithology contained uranium in Lemajung Sector has Rock Mass rating (RMR) value of 56 or Rock Mass class III: fair Rock in the depth of around 60 m, and in the depth of 280 m RMR value reach 82 or Rock Mass class I: very good Rock. RMR value data furthermore could be used for analysis of tunneling in the model of underground mine or slope stability analysis in the model of open pit mine

Van Eldert Jeroen - One of the best experts on this subject based on the ideXlab platform.

  • Rock support prediction based on measurement while drilling technology
    'Springer Science and Business Media LLC', 2021
    Co-Authors: Van Eldert Jeroen, Saiang David, Funehag Johan, Schunnesson Håkan
    Abstract:

    In tunnelling, Rock Mass support is designed based on the observed Rock Mass conditions. These conditions are determined by Rock Mass Characterization. Measurement while drilling (MWD), one such Characterization method, acquires drill parameter data during drilling. These data can be used to predict Rock Mass conditions ahead of the face. In this study, grout-hole MWD data are collected at one of the main tunnels in the large infrastructural project Stockholm bypass tunnels. The normalized and filtered MWD data are correlated to the Rock Mass characteristics using multilinear regression and the Levenberg-Marquardt method. Although a strong numerical correlation cannot be obtained, the results are promising. As a result, a holistic visual approach, which linked the MWD parameters with the Rock Mass classification and Rock support requirements, was developed.Validerad;2021;Nivå 2;2021-02-09 (alebob)

  • Improved filtering and normalizing of Measurement-While-Drilling (MWD) data in tunnel excavation
    'Elsevier BV', 2020
    Co-Authors: Van Eldert Jeroen, Schunnesson Håkan, Saiang David, Funehag Johan
    Abstract:

    Measurement-While-Drilling (MWD) data are complex because of the drilling process and drilling system. Swift and accurate normalization and filtration processes are required if MWD data are to be used for Rock Mass Characterization. The current method for MWD data filtration does not consider all the effects of the drilling process, e.g., collaring or extension rod coupling. This paper presents a new method for MWD data filtration and normalization. The new method filters the operational parameters and normalizes the data on a stepwise algorithm, including production factors (collaring drill hole and rod extension coupling) and Rock drill settings. It shows reliable results for the normalization and filtration of MWD data gathered for drill hole collaring and coupled extension drill rods at grout holes and for different Rock drills.Validerad;2020;Nivå 2;2020-09-01 (johcin)

  • Improved filtering and normalizing of Measurement-While-Drilling (MWD) data in tunnel excavation
    2020
    Co-Authors: Van Eldert Jeroen, Schunnesson Håkan, Saiang David, Funehag Johan
    Abstract:

    Measurement-While-Drilling (MWD) data are complex because of the drilling process and drilling system. Swift and accurate normalization and filtration processes are required if MWD data are to be used for Rock Mass Characterization. The current method for MWD data filtration does not consider all the effects of the drilling process, e.g., collaring or extension rod coupling. This paper presents a new method for MWD data filtration and normalization. The new method filters the operational parameters and normalizes the data on a stepwise algorithm, including production factors (collaring drill hole and rod extension coupling) and Rock drill settings. It shows reliable results for the normalization and filtration of MWD data gathered for drill hole collaring and coupled extension drill rods at grout holes and for different Rock drills

  • Rock support prediction based on measurement while drilling technology
    'Springer Science and Business Media LLC', 2020
    Co-Authors: Van Eldert Jeroen, Saiang David, Funehag Johan, Schunnesson Håkan
    Abstract:

    In tunnelling, Rock Mass support is designed based on the observed Rock Mass conditions. These conditions are determined by Rock Mass Characterization. Measurement while drilling (MWD), one such Characterization method, acquires drill parameter data during drilling. These data can be used to predict Rock Mass conditions ahead of the face. In this study, grout-hole MWD data are collected at one of the main tunnels in the large infrastructural project Stockholm bypass tunnels. The normalized and filtered MWD data are correlated to the Rock Mass characteristics using multilinear regression and the Levenberg-Marquardt method. Although a strong numerical correlation cannot be obtained, the results are promising. As a result, a holistic visual approach, which linked the MWD parameters with the Rock Mass classification and Rock support requirements, was developed

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