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<article article-type="research-article" dtd-version="3.0" xml:lang="en" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">
<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">MC</journal-id>
<journal-title-group>
<journal-title>Materiales de Construcci&#x00F3;n</journal-title>
</journal-title-group>
<issn pub-type="epub">0465-2746</issn>
<publisher>
<publisher-name>Consejo Superior de Investigaciones Cientificas</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">MC2020_e230</article-id>
<article-id pub-id-type="doi">10.3989/mc.2020.15119</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Articles</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Assessing the uniaxial compressive strength and tangent Young&#x2019;s modulus of basalt rock using the Leeb rebound hardness test</article-title>
<trans-title-group xml:lang="es">
<trans-title>Evaluaci&#x00F3;n de la resistencia a compression uniaxial y de la tangente del m&#x00F3;dulo de Young de rocas bas&#x00E1;lticas utilizando la prueba de dureza de rebote Leeb</trans-title>
</trans-title-group>
<alt-title alt-title-type="running-head">Assessing the uniaxial compressive strength and tangent Young&#x2019;s modulus of basalt rock using the Leeb rebound hardness test</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Aldeeky</surname>
<given-names>H.</given-names>
</name>
<xref ref-type="aff" rid="aff0001">a</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Al Hattamleh</surname>
<given-names>O.</given-names>
</name>
<xref ref-type="aff" rid="aff0001">a</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Rababah</surname>
<given-names>S.</given-names>
</name>
<xref ref-type="aff" rid="aff0002">b</xref>
</contrib>
</contrib-group>
<aff id="aff0001"><label>a</label>Civil Engineering Department, College of Engineering, The Hashemite University, (Zarqa, Jordan)</aff>
<aff id="aff0002"><label>b</label>Civil Engineering Department, College of Engineering, Jordan University of Science &#x0026;Technology, (Irbid, Jordan)</aff>
<author-notes>
<corresp id="cor1"><label>&#x002A;</label>: <email xlink:href="aldeeky@hu.edu.jo">aldeeky@hu.edu.jo</email></corresp>
<fn><p>ORCID ID: H. Aldeeky (<ext-link ext-link-type="uri" xlink:href="https://orcid.org/0000-0003-0468-1678">https://orcid.org/0000-0003-0468-1678</ext-link>); O. Al Hattamleh (<ext-link ext-link-type="uri" xlink:href="https://orcid.org/0000-0001-9039-2850">https://orcid.org/0000-0001-9039-2850</ext-link>); S. Rababah (<ext-link ext-link-type="uri" xlink:href="https://orcid.org/0000-0002-4370-9007">https://orcid.org/0000-0002-4370-9007</ext-link>)</p></fn>
</author-notes>
<pub-date pub-type="epub">
<day>31</day>
<month>12</month>
<year>2020</year>
</pub-date>
<pub-date pub-type="collection">
<year>2020</year>
</pub-date>
<volume>70</volume>
<issue>340</issue>
<elocation-id content-type="doi">10.3989/mc.2020.15119</elocation-id>
<history>
<date date-type="received">
<day>12</day>
<month>11</month>
<year>2019</year>
</date>
<date date-type="accepted">
<day>06</day>
<month>04</month>
<year>2020</year>
</date>
<date date-type="Available on line">
<day>25</day>
<month>09</month>
<year>2020</year>
</date>
</history>
<permissions>
<copyright-statement>&#x00A9; 2020 CSIC</copyright-statement>
<copyright-year>2020</copyright-year>
<license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/">
<license-p>This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) License.</license-p>
</license>
</permissions>
<abstract>
<p>Basalt was used as an ornamental stone in many historic and ancient cities in Jordan. Measuring the uniaxial compressive strength (UCS) and the tangent Young&#x2019;s modulus (E<sub>t</sub>) in the laboratory requires premium quality specimens with special core dimensions. This research focuses on correlations both UCS and E<sub>t</sub> with Leeb Rebound Hardness Test (LRH). In the laboratory, UCS, E<sub>t</sub>, and LRH were performed on 90 core samples extracted from 30 different rock boulders collected from the neighboring area of Umm al-Jimal, a historic city in northeastern Jordan. A strong power correlation with (R<sup>2</sup> = 0.888, RMSE = 5.464) was found between non-destructive LRH value and UCS. On the other hand, a moderately strong linear regression with (R<sup>2</sup> = 0.792, RMSE = 4.661) was found between E<sub>t</sub> and LRH. In conclusion, non-destructive LRHs can be used as indictors for evaluating both UCS and E<sub>t</sub> during the restoration of the historic city Umm al-Jimal and the rehabilitation of other existing structures.</p>
</abstract>
<trans-abstract xml:lang="es">
<p><italic>Evaluaci&#x00F3;n de la resistencia a compression uniaxial y de la tangente del m&#x00F3;dulo de Young de rocas bas&#x00E1;lticas utilizando la prueba de dureza de rebote Leeb.</italic> El basalto como piedra ornamental se us&#x00F3; en muchas ciudades hist&#x00F3;ricas de Jordania. La medici&#x00F3;n de la resistencia a compresi&#x00F3;n uniaxial (UCS) y de la tangente del m&#x00F3;dulo de Young (Et) en el laboratorio requiere muestras de calidad superior con un n&#x00FA;cleo de dimensi&#x00F3;n especial. Esta investigaci&#x00F3;n se centra en correlacionar la UCS y el Et con la prueba de dureza de rebote Leeb (LRH). Se realizaron ensayos de laboratorio de UCS, Et y LRH en noventa muestras de n&#x00FA;cleos que se extrajeron de treinta rocas diferentes recogidas en el &#x00E1;rea vecina de la ciudad hist&#x00F3;rica de Um-Al Jimal, al noreste de Jordania. Se encontr&#x00F3; una fuerte correlaci&#x00F3;n (R<sup>2</sup> = 0.888, RMSE = 5.464) entre el valor de LRH no destructivo y la UCS. Por otro lado, se encontr&#x00F3; una regresi&#x00F3;n lineal moderada fuerte (R<sup>2</sup> = 0.792, RMSE = 4.661) entre Et y LRH. En conclusi&#x00F3;n, la LRH no destructiva puede emplearse como indicador para evaluar tanto UCS como Et durante la restauraci&#x00F3;n de la ciudad hist&#x00F3;rica (Um-Al Jimal) y otras rehabilitaciones de estructuras existentes.</p>
</trans-abstract>
<kwd-group>
<kwd>Ornamental stones</kwd>
<kwd>Mechanical properties</kwd>
<kwd>Compressive strength</kwd>
<kwd>Modulus of elasticity</kwd>
<kwd>Petrography</kwd>
</kwd-group>
<kwd-group>
<kwd>Piedras ornamentales</kwd>
<kwd>Propiedades mec&#x00E1;nicas</kwd>
<kwd>Resistencia a compresi&#x00F3;n</kwd>
<kwd>M&#x00F3;dulo de elasticidad</kwd>
<kwd>Petrograf&#x00ED;a</kwd>
</kwd-group>
</article-meta>
</front>
<body>
<sec id="sec1" sec-type="intro">
<title>1. INTRODUCTION</title>
<p>Restoration of historic buildings and monuments is a challenging task. In most cases, destructive tests are not allowed, therefore, non-destructive tests to evaluate mechanical behavior are required. Uniaxial compressive strength (UCS) and tangent Young&#x2019;s modulus (E<sub>t</sub>) are the main input parameters of the mechanical behavior of rock, especially in ascertaining rock shear strength, rock mass rating (RMR), classification, and earth structure design such as foundation and tunneling (<xref ref-type="bibr" rid="cit0001">1</xref>&#x2013;<xref ref-type="bibr" rid="cit0006">6</xref>).</p>
<p>Conducting a UCS test in the laboratory according to ISRM (<xref ref-type="bibr" rid="cit0007">7</xref>) and ASTM D7012 (<xref ref-type="bibr" rid="cit0008">8</xref>) requires a specified core of premium quality with certain dimensions. Sometimes a core sample is not possible, especially in foliated, soft, weathered, and fractured rock, or it is not allowed in historic buildings. In addition, the UCS test is a destructive, expensive, and time-consuming method as reported by many researchers (<xref ref-type="bibr" rid="cit0009">9</xref>&#x2013;<xref ref-type="bibr" rid="cit0014">14</xref>). For these reasons, the correlation between UCS and E<sub>t</sub> with the non-destructive or simple tests that require no sample preparation is more desired (<xref ref-type="bibr" rid="cit0015">15</xref>&#x2013;<xref ref-type="bibr" rid="cit0017">17</xref>). Different empirical models have been developed to estimate the UCS and E<sub>t</sub> depending on simple or non-destructive tests. These tests include porosity, dry density, Brazilian tensile strength test, point load, pulse velocity, slake durability index, Schmidt hammer hardness, Shore scleroscope hardness, and Brinell hardness tests (<xref ref-type="bibr" rid="cit0018">18</xref>&#x2013;<xref ref-type="bibr" rid="cit0024">24</xref>).</p>
<p>The Schmidt hammer procedure is a non-destructive and rapid test of hardness. Therefore, many researchers have developed numerous correlations between Schmidt hammer hardness, either linear or non-linear, and UCS and E<sub>t</sub> for diverse types of rocks (<xref ref-type="bibr" rid="cit0025">25</xref>&#x2013;<xref ref-type="bibr" rid="cit0035">35</xref>).</p>
<p>An Equotip hardness tester also was recommended for use in geological and rock mechanical applications (<xref ref-type="bibr" rid="cit0036">36</xref>, <xref ref-type="bibr" rid="cit0037">37</xref>). Hack et al. (<xref ref-type="bibr" rid="cit0036">36</xref>) used Equotip hardness type D to evaluate wall strength discontinuity. For this purpose, they used cubic samples with a 20 cm edge side from different rock types (granite, limestone, and sandstone). They found that the influence of layer thickness on Equotip hardness is very small compared to Schmidt hammer hardness and that Equotip is better at reflecting wall discontinuity. Also, they concluded that rock strength and surface roughness affected the Equotip hardness value more than rock density and elastic modulus. Verwaal and Mulder (<xref ref-type="bibr" rid="cit0038">38</xref>) studied the possibility of estimating UCS from the Equotip L-value test and the effect of size and roughness on Equotip L-value. Based on limestone cores with different diameters and lengths, they concluded that Equotip L-value increases with the increase in both diameter and length. On the other hand, they found the surface roughness presents no major influence on Equotip L-value. Meulenkamp and Grima (<xref ref-type="bibr" rid="cit0039">39</xref>) used neural networks to correlate UCS with Equotip L-value, porosity, density, rock texture, and rock type for sandstone, limestone, dolomite, granite, and granodiorites.</p>
<p>Okawa et al. (<xref ref-type="bibr" rid="cit0040">40</xref>) found that both surface roughness and curvature have no influence on Equotip L-value. Kawasaki et al. (<xref ref-type="bibr" rid="cit0041">41</xref>) conducted an Equotip hardness test on core rock samples for many rock types (sandstone, greenschist, hornfels, granite, shale), recommending a linear relationship between Equotip L-values and USC. This recommended equation depends on rock type and Equotip L-values. Aoki and Matsukura (<xref ref-type="bibr" rid="cit0037">37</xref>) found a good correlation between Equotip L-values, porosity, and USC for different rock types (tuff, sandstone, granite, gabbro, limestone). Using hybrid dynamic hardness (HDH) to investigate the effect of the test procedure on the UCS prediction on carbonate rocks, Ylimaz (<xref ref-type="bibr" rid="cit0042">42</xref>) found that the test procedure based on single impacts is more suitable for UCS prediction. Also, based on cubic samples with edge dimensions of 5, 9, 11, 13, and 15 cm, he concluded that there is no size effect on mean rebound values. Lee et al. (<xref ref-type="bibr" rid="cit0043">43</xref>) utilized Leeb rebound hardness to study the relation between Leeb rebound hardness number (RHN) and UCS for 24 shale samples; they found that UCS varies exponentially with RHN.</p>
<p>Siri et al. (<xref ref-type="bibr" rid="cit0044">44</xref>) presented a nonlinear relation between type D Leeb Hardness values (LRH) and UCS for sandstone rocks. They recommended that there is no size effect if the sample volume is greater than 100 cm<sup>3</sup>. Corkum et al. (<xref ref-type="bibr" rid="cit0045">45</xref>) studied the correlation between LRH test values and UCS for various rock types. Based on 213 sedimentary, 40 metamorphic, and 58 igneous rocks, they found a nonlinear power function between LRH and USC. They concluded that there is no scale effect on LRH value if the specimen&#x2019;s volume is at least 90 cm<sup>3</sup> for block or irregular block specimens, or with about L/D &#x003E; 0.4 for core specimens. Kovler et al. (<xref ref-type="bibr" rid="cit0046">46</xref>) used static Schmidt rebound test and dynamic LRH test to evaluate concrete compressive strength with different water-cement ratios. They found that the LRH could be applied in predicting concrete compressive strength within a 10 % margin of error for all water-cement ratios. On the other hand, they reported that the Schmidt rebound test can be considered a semi-destructive method since they found a significant strength reduction (on average by 10.5 MPa) after applying Schmidt hammer impact on specimens, while there was no damage in the concrete sample after applying LRH test. Yilmaz and Goktan (<xref ref-type="bibr" rid="cit0047">47</xref>) used two types of non-destructive hardness tests (L-type Schmidt hammer and the Equotip 3 hardness tester with D-probe) to evaluate UCS. They used 11 rock core samples with a diameter of 54 mm for basalt, limestone, andesite, tuff, travertine, and marble rocks. They proposed a power relation between Equotip hardness, Schmidt hammer, and USC. Also, they found a good prediction accuracy with R<sup>2</sup> = 0.87 between USC and Equotip hardness and an accuracy ratio = 0.60 compared to Schmidt hammer hardness<bold>.</bold></p>
<p>To study the effect of core holder type on LRH, Yilmaz and Goktan (<xref ref-type="bibr" rid="cit0048">48</xref>) used two different holders, a V-shape holder and an arch-shape holder. They found that the difference between LRH magnitudes in both holders is small and varies from one rock to another. Celik and Cobanoglu (<xref ref-type="bibr" rid="cit0049">49</xref>) predicted the physical and mechanical properties of different rock type, igneous, sedimentary, and metamorphic rock, using three types of non-destructive hardness tests. Based on their results, they concluded that Leeb hardness is more accurate in predicting mechanical and physical rock properties compared with shore scleroscope and Schmidt hammer type L.</p>
<p>Based on his results using Equotip (type D) hardness test to evaluate the mechanical properties of volcanic tuff building stone in Turkey, Y&#x00FC;ksek (<xref ref-type="bibr" rid="cit0050">50</xref>) found that there is a moderately good exponential correlation between LRH with UCS and dry unit weight; also, he found a fairly linear correlation with porosity and water absorption. Desarnaud et al. (<xref ref-type="bibr" rid="cit0051">51</xref>) studied the effect of sample size, moisture content, and surface roughness on the Equotip rebound hardness of sandstone rock samples. They recorded that Equotip rebound hardness is reduced by 26 % in the saturated cases compared with the dry cases and also that sample size has a significant effect on Equotip rebound hardness compared with surface roughness<bold>.</bold> <xref ref-type="table" rid="t0001">Table 1</xref> summarizes some of the previous correlations between UCS and LRH.</p>
<table-wrap id="t0001">
<label>Table 1</label>
<caption><p>Some previous correlations between UCS and LRH.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left">References</th>
<th align="left">Lithology</th>
<th align="left">Correlations</th>
<th align="center">R<sup>2</sup></th>
</tr>
</thead>
<tbody>
<tr>
<td align="left">Aoki and Matsukura (<xref ref-type="bibr" rid="cit0037">37</xref>)</td>
<td align="left">tuff, sandstone, granite, andesite, gabbro, and limestone</td>
<td align="left">UCS = 0.079 EXP (-0.039 n)(LRH1.1)</td>
<td align="center">0.88</td>
</tr>
<tr>
<td align="left">Verwaal and Mulder (<xref ref-type="bibr" rid="cit0038">38</xref>)</td>
<td align="left">limestone, granite, sandstone and man-made gypsum</td>
<td align="left">UCS = 8 X 10<sup>-6</sup>( LRH) <sup>2.5</sup></td>
<td align="center">0.77</td>
</tr>
<tr>
<td align="left">Meulenkamp and Grima (<xref ref-type="bibr" rid="cit0039">39</xref>)</td>
<td align="left">limestone, granite, sandstone, dolostone and granodiorite</td>
<td align="left">UCS = 1.75 X 10<sup>-9</sup>( LRH) <sup>3.8</sup></td>
<td align="center">0.806</td>
</tr>
<tr>
<td align="left">Lee et al. (<xref ref-type="bibr" rid="cit0043">43</xref>)</td>
<td align="left">shale</td>
<td align="left">UCS = 2.3007 EXP(0.0057LRH)</td>
<td align="center">0.823</td>
</tr>
<tr>
<td align="left">ASiri et al. (<xref ref-type="bibr" rid="cit0044">44</xref>)</td>
<td align="left">sandstone</td>
<td align="left">UCS =2.548EXP(0.00537LRH)</td>
<td align="center">0.72</td>
</tr>
<tr>
<td align="left">Corkum et al. (<xref ref-type="bibr" rid="cit0045">45</xref>)</td>
<td align="left">igneous</td>
<td align="left">UCS = 3.0&#x00D7;10<sup>-6</sup>(LRH)<sup>2.64</sup></td>
<td align="center">0.65</td>
</tr>
<tr>
<td align="left">Corkum et al. (<xref ref-type="bibr" rid="cit0045">45</xref>)</td>
<td align="left">Sandstone</td>
<td align="left">UCS = 0.9&#x00D7;10<sup>-6</sup>(LRH)<sup>2.84</sup></td>
<td align="center">0.75</td>
</tr>
<tr>
<td align="left">Corkum et al. (<xref ref-type="bibr" rid="cit0045">45</xref>)</td>
<td align="left">Sedimentary</td>
<td align="left">UCS = 0.1&#x00D7;10<sup>-6</sup>(LRH)<sup>3.18</sup></td>
<td align="center">0.71</td>
</tr>
<tr>
<td align="left">Corkum et al. (<xref ref-type="bibr" rid="cit0045">45</xref>)</td>
<td align="left">Metamorphic</td>
<td align="left">UCS = 0.3&#x00D7;10<sup>-6</sup>(LRH)<sup>2.98</sup></td>
<td align="center">0.75</td>
</tr>
<tr>
<td align="left">Kovler et al. (<xref ref-type="bibr" rid="cit0046">46</xref>)</td>
<td align="left">Concrete</td>
<td align="left">UCS = 0.18LRH-11</td>
<td align="center">0.92</td>
</tr>
<tr>
<td align="left">Yilmaz and Goktan(<xref ref-type="bibr" rid="cit0047">47</xref>)</td>
<td align="left">basalt, limestone, andesite, tuff, travertine and marble</td>
<td align="left">UCS = 2.0&#x00D7;10<sup>-8</sup>(LRH)<sup>3.3492</sup></td>
<td align="center">0.87</td>
</tr>
<tr>
<td align="left">Yilmaz and Goktan (<xref ref-type="bibr" rid="cit0048">48</xref>)</td>
<td align="left">16 different rock samples</td>
<td align="left">UCS = 0.229LRH-84.242</td>
<td align="center">0.87</td>
</tr>
<tr>
<td align="left">Celik and Cobanoglu (<xref ref-type="bibr" rid="cit0049">49</xref>)</td>
<td align="left">Travertine, limestone dolomite, Marble, schist, granite, syenite andesite gabbro, dunite, tuff, and ignimbrite</td>
<td align="left">UCS = 7.0&#x00D7;10<sup>-7</sup>(LRH)<sup>2.875</sup></td>
<td align="center">0.80</td>
</tr>
<tr>
<td align="left">Y&#x00FC;ksek(<xref ref-type="bibr" rid="cit0050">50</xref>)</td>
<td align="left">Volcanic tuff</td>
<td align="left">UCS = 2.359 EXP(0.0044LRH)</td>
<td align="center">0.657</td>
</tr>
<tr>
<td align="left">Kawasaki et al. (<xref ref-type="bibr" rid="cit0052">52</xref> )</td>
<td align="left">shale</td>
<td align="left">UCS = 156+0.309LRH</td>
<td align="center">0.818</td>
</tr>
<tr>
<td align="left">Kawasaki et al. (<xref ref-type="bibr" rid="cit0053">52</xref> )</td>
<td align="left">granite</td>
<td align="left">UCS = 271-0.38LRH</td>
<td align="center">0.356</td>
</tr>
<tr>
<td align="left">Kawasaki et al. (<xref ref-type="bibr" rid="cit0052">52</xref> )</td>
<td align="left">hornfels</td>
<td align="left">UCS = 64.6+0.122LRH</td>
<td align="center">0.339</td>
</tr>
<tr>
<td align="left">ASiri et al. (<xref ref-type="bibr" rid="cit0053">53</xref>)</td>
<td align="left">igneous rock</td>
<td align="left">UCS = 9.70X 10<sup>-5</sup>(LRH)<sup>2.14</sup></td>
<td align="center">0.65</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>LRHT was adopted in this research because it is a portable device, non-destructive, and a simple test that has a high testing rate with each test taking about 2 seconds. In addition to being low cost and suitable for hard and soft materials, it measures in any direction and can be directly converted to Rockwell, Brinell, and Vickers hardness. Few researchers have attempted to find a relationship between UCS and E<sub>t</sub> with LRHT.</p>
<p>The aim of this research was to acquire a correlation using the LRHT to predict the UCS and the E<sub>t</sub> of basalt rocks in Harrat al-Sham in eastern Jordan. The developed model might be useful in the restoration of the historic city Umm al-Jimal and in the rehabilitation of other existing structures. To achieve this target, the UCS and E<sub>t</sub> along with LRHT of basalt samples collected from the neighboring area of Umm al-Jimal were determined in the laboratory, then the power and linear relationship between UCS and E<sub>t</sub> with LRHT test was established respectively.</p>
</sec>
<sec id="sec2">
<title>2. BASALT IN JORDAN AND STUDY AREA</title>
<p>Basalt rock covers about 11 % of Jordan&#x2019;s area (<xref ref-type="bibr" rid="cit0054">54</xref>, <xref ref-type="bibr" rid="cit0055">55</xref>). As explained in <xref ref-type="fig" rid="f0001">Figure 1</xref>, basalt rock covers about 11400 km<sup>2</sup>, in both Harrat al-Shamin in the northeast and Harrat Irbid in the northwestern part of Jordan (<xref ref-type="bibr" rid="cit0057">57</xref>, <xref ref-type="bibr" rid="cit0058">58</xref>). As a building stone, basalt was used in many historic and ancient cities in Jordan such as Umm Qais located to the north of Jordan, Qasr al-Mashta and Umm al-Jimal (east of Al-Mafraq), Qasr al-Hallabat and Qastal (south of Jordan), and Qasr al-Azraq (<xref ref-type="bibr" rid="cit0059">59</xref>), as presented in <xref ref-type="fig" rid="f0002">Figure 2</xref>. During the Roman period, basalt stones were used as road pavement. Nowadays, basalt is used as aggregates, dimension stone, curbstone, paving stone, and in industrial applications due to it is wide availability in Jordan where basalt stone constitutes about 15 % of the country&#x2019;s economic rocks (<xref ref-type="bibr" rid="cit0060">60</xref>&#x2013;<xref ref-type="bibr" rid="cit0062">62</xref>).</p>
<fig id="f0001">
<label>Figure 1</label>
<caption><p>(a) Location of basalt rock distribution in Jordan; modified from Al Kuisi et al. (<xref ref-type="bibr" rid="cit0056">56</xref>); (b) Basalt boulders in Harrat al-Sham (northeast of Jordan).</p></caption>
<graphic xlink:href="MC2020_e230-g001.tif" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</fig>
<fig id="f0002">
<label>Figure 2</label>
<caption><p>Pictures of basalt historic buildings in Jordan. (a) Umm Qais located to the north of Jordan. (b) Qasr Al-Azraq. (c) Qaser al-Hallabat and Qastal. (d) Umm al-Jimal (east of Al-Mafraq).</p></caption>
<graphic xlink:href="MC2020_e230-g002.tif" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</fig>
<p>Thirty basalt boulders with dimensions of approximately 30 &#x00D7; 30 &#x00D7; 50 cm were collected from the neighboring area of the historic Umm al-Jimal village located in the northeast of Jordan; the study area is located at latitude 32&#x00B0; 19&#x2032; 36&#x2033; N<bold>,</bold> and longitude 36&#x00B0; 22&#x2032; 11&#x2033; E (<xref ref-type="fig" rid="f0003">Figure 3</xref>).</p>
<fig id="f0003">
<label>Figure 3</label>
<caption><p>(a) Study area. (b) Historic Umm al-Jimal village.</p></caption>
<graphic xlink:href="MC2020_e230-g003.tif" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</fig>
</sec>
<sec id="sec3">
<title>3. LEEB REBOUND HARDNESS TEST (LRH)</title>
<p>In 1975, Leeb and Brandestini developed LRH, a portable nondestructive device with dynamic impact energy, for the Proceq SA Company in Switzerland to test the hardness of metals (<xref ref-type="bibr" rid="cit0063">63</xref>). The Leeb rebound hardness was calculated based on the following <xref ref-type="disp-formula" rid="eq1">Equation [1</xref>]:</p>
<disp-formula id="eq1">
<alternatives>
<mml:math id="M1">
<mml:mrow>
<mml:mtext>LRH</mml:mtext>
<mml:mo>=</mml:mo>
<mml:mo stretchy='false'>(</mml:mo>
<mml:mi>V</mml:mi>
<mml:mi>r</mml:mi>
<mml:mo>/</mml:mo>
<mml:mi>V</mml:mi>
<mml:mi>i</mml:mi>
<mml:mo stretchy='false'>)</mml:mo>
<mml:mo>&#x00D7;</mml:mo>
<mml:mn>1000</mml:mn>
</mml:mrow>
</mml:math>
<graphic xlink:href="MC2020_e230-eq1.tif" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</alternatives>
<label>1</label>
</disp-formula>
<p>Where LRH: Leeb rebound hardness, Vr: impact speed, Vi: rebound speed.</p>
<p>LRH type D is a non-destructive test with low impact energy of about 11 N mm, about 1/200 of the rebound Schmidt hammer test type N and 1/66 type L (<xref ref-type="bibr" rid="cit0064">64</xref>). Because it is low energy, this test is suitable for soft and thin layers. LRH can be repeated on the same spot without affecting the rock sample, compared with Schmidt hammer as recommended by Aoki and Matsukura (<xref ref-type="bibr" rid="cit0065">65</xref>). <xref ref-type="table" rid="t0002">Table 2</xref> summarizes a compression between Schmidt hammer type N and LRH type D.</p>
<table-wrap id="t0002">
<label>Table 2</label>
<caption><p>Comparison between Leeb Hardness Tester Type D and Schmidt Hammer Tester type N.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left">Hardness tester</th>
<th align="left">Leeb Hardness Tester type D</th>
<th align="left">Schmidt Hammer type N</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left">Impact energy (Nm) (<xref ref-type="bibr" rid="cit0064">64</xref>)</td>
<td align="left">0.011</td>
<td align="left">2.207</td>
</tr>
<tr>
<td align="left">Length (cm)</td>
<td align="left">15.5</td>
<td align="left">30</td>
</tr>
<tr>
<td align="left">Weight (kg)</td>
<td align="left">0.166</td>
<td align="left">1.52</td>
</tr>
<tr>
<td align="left">Impact direction (<xref ref-type="bibr" rid="cit0042">42</xref>)</td>
<td align="left">360&#x00B0;</td>
<td align="left">90&#x00B0;</td>
</tr>
<tr>
<td align="left">Minimum thickness (mm)</td>
<td align="left">5</td>
<td align="left">100</td>
</tr>
<tr>
<td align="left">UCS (MPa) range</td>
<td align="left">3-285</td>
<td align="left">10-70</td>
</tr>
<tr>
<td align="left">Impact plunger diameter (cm)</td>
<td align="left">0.5</td>
<td align="left">1.5</td>
</tr>
<tr>
<td align="left">Type of energy</td>
<td align="left">Dynamic test</td>
<td align="left">Static test</td>
</tr>
<tr>
<td align="left">Layer thickness (<xref ref-type="bibr" rid="cit0065">65</xref>)</td>
<td align="left">Suitable for a thin layer</td>
<td align="left">Not suitable for a thin layer</td>
</tr>
<tr>
<td align="left">Effect of water content (<xref ref-type="bibr" rid="cit0064">64</xref>, <xref ref-type="bibr" rid="cit0065">65</xref>)</td>
<td align="left">Slightly not affected</td>
<td align="left">Significantly affected</td>
</tr>
<tr>
<td align="left">Standard test method</td>
<td align="left">No standard for rock</td>
<td align="left">ISRM (<xref ref-type="bibr" rid="cit0007">7</xref>)</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="sec4" sec-type="materials|methods">
<title>4. MATERIALS AND METHODS</title>
<p>Thirty basalt boulders with dimensions of approximately 30 &#x00D7; 30 &#x00D7; 50 cm were collected from the neighboring area of Umm al-Jimal in northeastern Jordan. Selected boulder samples had no joints or fractures. From each boulder, three NX cylindrical rock core specimens with a diameter of 64.0 mm and length of 130.0 mm were prepared according to ASTM D4543 (<xref ref-type="bibr" rid="cit0066">66</xref>) and ISRM (<xref ref-type="bibr" rid="cit0007">7</xref>). After coring, samples were cut to a 2:1 ratio of length to diameter. The specimens were polished using a suitable machine to ensure a smooth surface.</p>
<p>The ASTM A956 (<xref ref-type="bibr" rid="cit0067">67</xref>) testing procedure for LRH is standard for steel products only; therefore, the ASTM is not applicable for rock specimens. Since there is no international standard test procedure for LRH on rock materials regarding test procedure, data evaluation, or specimen preparation, a single impact method was adopted as recommended by Daniels et al. (<xref ref-type="bibr" rid="cit0068">68</xref>) and Corkum et al. (<xref ref-type="bibr" rid="cit0045">45</xref>). Using this method, an air-dry core specimen was fixed, and the device was pressed perpendicular to the specimen surface (<xref ref-type="fig" rid="f0004">Figure 4</xref>). Twelve impact values were conducted on each core specimen, then the average of the remaining 10 values was recorded as the LRH value after excluding the maximum and minimum value.</p>
<fig id="f0004">
<label>Figure 4</label>
<caption><p>(a) Core specimen. (b) Equo tip 2 devices. (c) Core specimen with holder under test.</p></caption>
<graphic xlink:href="MC2020_e230-g004.tif" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</fig>
<p>UCS and E<sub>t</sub> tests were performed according to ISRM (<xref ref-type="bibr" rid="cit0007">7</xref>) and ASTM D 7012 (<xref ref-type="bibr" rid="cit0069">69</xref>) using a computerized MTS compression machine (Matest&#x2013;Italy) with a maximum compression static load of 2000 kN. A stress rate of 0.5 MPa/s was applied to reach failure within 5&#x2013;10 min. The reported UCS was equal to the failure load divided by the cross-sectional area of the cylindrical specimen. The tests were conducted on the three prepared cylindrical specimens of each boulder sample and the average was reported.</p>
<p>E<sub>t</sub> is a key factor in evaluating rock deformation. E<sub>t</sub> can be determined from the stress-strain curve analysis, where E<sub>t</sub> is the slope of the tangent of the stress-strain curve at point represent 50 % of UCS as described by Bejarbaneh et al. (<xref ref-type="bibr" rid="cit0070">70</xref>) and Malkowskia et al. (<xref ref-type="bibr" rid="cit0071">71</xref>).</p>
<p>A Phillips X-ray florescence (XRF) Majex Pw-242 model, available from the Water, Environment, and Arid Regions Research Center at Al al-Bayt University in Jordan, was adopted to determine the major elements analyzed using fused glass discs. Of the basalt samples. A basalt sample was dried then crushed until it reached a size of 10 mm. The sample was then ground into powder using a ball mill with a tungsten carbide barrel at 400 RPM until the sample reached a size of about 0.075 mm. Two grams of the powder sample were mixed with 8 g of lithium tetraborate then fused in platinum crucibles over gas burners at 1000 <sup>o</sup>C for one hour, then the melted sample poured in a mold to create glass disks. The test results were analyzed using GEOS software calibration to international geological rock standards. The contents of the major oxides of Si, Ti, Al, Fe, Mg, Mn, Ca, Na, and K were analyzed. Loss on ignition was determined first by drying the powder sample at 110 <sup>o</sup>C for eight hours, then weighted before and after ignition at 1000 <sup>o</sup>C. The sample preparation and test were conducted according to ASTM E1621 (<xref ref-type="bibr" rid="cit0072">72</xref>).</p>
<p>An X-ray diffractometer (XRD) type XRD-7000 (CuK&#x03B1;1 radiation, &#x03BB; = 1.54060&#x00C5;), using 99 % silicon powder and 325 mesh (0.044 mm) for calibration was available through the geology department at Hashemite University. A randomly oriented powder mount was adopted in this test. The mounts are typically X-rayed between the angles of 5 and 65 degrees 2 theta using copper K alpha radiation at a scanning rate of 2 degrees per minute. First, the sample was crushed and powdered to reach a size 0.040 mm, then 1 g of the powder was used on the sample holder. The sample preparation and test were conducted according to &#x201C;A Laboratory Manual for X-Ray Powder Diffraction&#x201D; (<xref ref-type="bibr" rid="cit0073">73</xref>).</p>
<p><bold>A</bold> thin slab of a basalt core sample about 30 mm &#x00D7; 20 mm &#x00D7; 10 mm was cut and polished using silicon carbide powder, then stack with glass slide of 26 mm &#x00D7; 42 mm using a special adherent, then an automated multiplate grinder machine was used to make the slides about 0.030 mm thinner in thickness, following the procedure laid out by Grundmann and Scholz (<xref ref-type="bibr" rid="cit0074">74</xref>). A Nikon optical microscope was used particularly to identify mineral constituents of the studied basaltic rocks and to determine their mineralogical properties and textures. Modal analysis with five hundred points as recommended by ASTM E562 (<xref ref-type="bibr" rid="cit0075">75</xref>) was used to determine the mineral percentage as % of volume. The point-counting method depends on using a grid mesh with equally spaced points on the thin section slides, the grid distance, which is the distance between successive points on a grid mesh, should not exceed both grain size and texture. For the same mineral particle, the volume percentage was found by dividing the number of points by the total number of points counted.</p>
</sec>
<sec id="sec5" sec-type="results|discussions">
<title>5. RESULTS AND DISCUSSIONS</title>
<sec id="sec5.1">
<title>5.1. Petrography analysis</title>
<p>X-ray Fluorescence Spectrometry (XRF) was used to determine the dominant and minor oxides in rock samples (<xref ref-type="table" rid="t0003">Table 3</xref>). The XRF analysis shows that the majority of oxides are based on plotting the test results on the total alkali (Na<sub>2</sub>O + K<sub>2</sub>O) versus SiO<sub>2</sub> diagram (TAS) as shown in <xref ref-type="fig" rid="f0005">Figures 5a</xref> and <xref ref-type="fig" rid="f0005">5b</xref>. The basalt rock in this study is classified as mafic alkaline basalt rock. The basalt samples are considered non-weathered basalt since L.O.I is less than 2.64 wt. % (<xref ref-type="bibr" rid="cit0076">76</xref>).</p>
<table-wrap id="t0003">
<label>Table 3</label>
<caption><p>XRF analysis of studied basalt samples.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left">Mineral</th>
<th align="left">SiO<sub>2</sub></th>
<th align="left">Al<sub>2</sub>O<sub>3</sub></th>
<th align="left">Fe<sub>2</sub>O<sub>3</sub></th>
<th align="left">CaO</th>
<th align="left">MgO</th>
<th align="left">Na<sub>2</sub>O</th>
<th align="left">TiO<sub>2</sub></th>
<th align="left">K<sub>2</sub>O</th>
<th align="left">P<sub>2</sub>O<sub>5</sub></th>
<th align="left">MnO</th>
<th align="left">L.O.I</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left">Mean value, Wt. %</td>
<td align="left">45.08</td>
<td align="left">14.32</td>
<td align="left">12.39</td>
<td align="left">11.54</td>
<td align="left">8.42</td>
<td align="left">3.42</td>
<td align="left">1.67</td>
<td align="left">0.65</td>
<td align="left">0.30</td>
<td align="left">0.16</td>
<td align="left">2.31</td>
</tr>
<tr>
<td align="left">Standard Deviation</td>
<td align="left">0.56</td>
<td align="left">0.55</td>
<td align="left">0.34</td>
<td align="left">0.69</td>
<td align="left">0.38</td>
<td align="left">0.29</td>
<td align="left">0.05</td>
<td align="left">0.07</td>
<td align="left">0.05</td>
<td align="left">0.01</td>
<td align="left">0.40</td>
</tr>
</tbody>
</table>
</table-wrap>
<fig id="f0005">
<label>Figure 5</label>
<caption><p>Test results on TAS modified after (<xref ref-type="bibr" rid="cit0077">77</xref>). (b) Test result on total alkaline versus silica diagram modified after (<xref ref-type="bibr" rid="cit0078">78</xref>).</p></caption>
<graphic xlink:href="MC2020_e230-g005.tif" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</fig>
<p>XRD test results showed that plagioclase, pyroxene, magnetite, and olivine, are the major minerals in the studied samples (<xref ref-type="fig" rid="f0006">Figure 6</xref>)<bold>.</bold></p>
<fig id="f0006">
<label>Figure 6</label>
<caption><p>XRD analysis of studied basalt samples (PL: plagioclase, Py: pyroxene, OL: olivine, M: magnetite, Ca: calcite, Ch: Chlorite, Ser: Sericite).</p></caption>
<graphic xlink:href="MC2020_e230-g006.tif" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</fig>
<p>Based on the microphotographs of mineral components (<xref ref-type="fig" rid="f0007">Figure 7</xref>) and modal analysis, plagioclase is the most abundant mineral in the studied rock samples, forming approximately 50 % of the rock volume. Plagioclase was found to be subhedral to euhedral with a tabular shape, with length ranging between 0.5&#x2013;3.0 mm. Pyroxene, the second most abundant mineral, formed about 20 % of the rock volume. Pyroxene, which is mainly an augite mineral composition, had anhedral to subhedral crystals with a size range between 0.3&#x2013;1.0 mm [<xref ref-type="fig" rid="f0007">Figure 7 (c</xref>)]. Olivine composed about 13 % of the volume of the rock sample. Olivine crystals range in size between 0.05&#x2013;0.3 mm. Olivine minerals subjected to hydration and the oxidation process produced brownish iddingsite mineral [<xref ref-type="fig" rid="f0007">Figure 7 (d</xref>)]. Magnetite formed about 8 % of the rock volume, the size ranging from 0.03 mm to 0.5 m [<xref ref-type="fig" rid="f0007">Figure 7 (a</xref>)]. Basalt vascularity (voids) about 6 % by volume, some voids are filled with calcite and chloride minerals <xref ref-type="fig" rid="f0007">[Figure 7 (b</xref>)]. A secondary mineral-like sericite (weathered plagioclase), iddingsite (weathered olivine), chloride (weathered pyroxene) composed about 3 % by volume. Based on the Modal analysis with 500 points, the rock samples can be classified as plagioclase&#x2013;pyroxene&#x2013;olivine basalt, according to (<xref ref-type="bibr" rid="cit0079">79</xref>).</p>
<fig id="f0007">
<label>Figure 7</label>
<caption><p>Microphotograph of mineral components, Mag 10x. (PL: Plagioclase, PX: Pyroxene, OL: Olivine, Idd: Iddingsite, Ca: calcite, Op.M: Magnetite, Ves: vascularity).</p></caption>
<graphic xlink:href="MC2020_e230-g007.tif" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</fig>
</sec>
<sec id="sec5.2">
<title>5.2. Mechanical properties</title>
<p>The results of UCS, E<sub>t</sub>, and LRH tests conducted on 90 core rock specimens extracted from 30 rock boulders collected from the study area are shown in <xref ref-type="fig" rid="f0008">Figure 8</xref>. Statistical parameters values of maximum, minimum, mean, coefficient of variation, and standard deviation of the results are shown in <xref ref-type="table" rid="t0004">Table 4</xref>. As seen in <xref ref-type="table" rid="t0004">Table 4</xref><bold>,</bold> the mean UCS for the basalt rock samples used in this study was 83.82 MPa, with a range between 51.75 and 115.70 MPa. In addition, the mean of the E<sub>t</sub><sub>,</sub> about 50.78 GPa, varies between 31.77 and 68.39 GPa. This variation of test results might be due to the effect of non-isotropy, mineralogical composition, porosity, and grain boundaries. The current basalt rock was classified as strong to very strong rock based on the UCS results according to ISO 14689-1 (<xref ref-type="bibr" rid="cit0080">80</xref>) classification. On the other hand, the studied basalt rock was designated as medium strength (CH) to high strength (BH) according to Deere and Miller&#x2019;s (<xref ref-type="bibr" rid="cit0081">81</xref>) classification system.</p>
<fig id="f0008">
<label>Figure 8</label>
<caption><p>Test results distribution. (a) UCS. (b) E<sub>t</sub>. (c) LRH (each point is an average of the results of three cores).</p></caption>
<graphic xlink:href="MC2020_e230-g008.tif" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</fig>
<table-wrap id="t0004">
<label>Table 4</label>
<caption><p>Statistical parameters of tested samples.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left"/>
<th align="center">USC (MPa)</th>
<th align="center">E<sub>t</sub> (GPa)</th>
<th align="center">LRH</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left">Mean</td>
<td align="center">83.82</td>
<td align="center">50.78</td>
<td align="center">640.9</td>
</tr>
<tr>
<td align="left">Max</td>
<td align="center">115.70</td>
<td align="center">68.39</td>
<td align="center">980.0</td>
</tr>
<tr>
<td align="left">Min</td>
<td align="center">51.75</td>
<td align="center">31.77</td>
<td align="center">315.0</td>
</tr>
<tr>
<td align="left">SD</td>
<td align="center">16.4</td>
<td align="center">10.4</td>
<td align="center">186.3</td>
</tr>
<tr>
<td align="left">CV (%)</td>
<td align="center">19.5 %</td>
<td align="center">20.4 %</td>
<td align="center">29.06 %</td>
</tr>
<tr>
<td align="left">N<xref ref-type="table-fn" rid="tf4-1">&#x002A;</xref></td>
<td align="center">30</td>
<td align="center">30</td>
<td align="center">30</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="tf4-1"><label>&#x002A;</label><p>note: N is an average of the results of three cores</p></fn>
</table-wrap-foot>
</table-wrap>
<p>Stress&#x2013;strain curves for the first sample are shown in <xref ref-type="fig" rid="f0009">Figure 9</xref>. As illustrated in <xref ref-type="fig" rid="f0009">Figure 9</xref>, at initial loading there is a non-linear relationship between stress and strain because, at this stage, there is a closing of preexisting micro-cracks inside the specimen due to the stress history of the rock specimen including rock coring. As the loading increases, the stress&#x2013;strain curve becomes linear, and the rock behavior is more elastic. After the elastic range, the stress&#x2013;strain curve becomes nonlinear and large deformation occurs until the maximum stress is reached. The LRH shows an average value of 640.9 with a range between 315 and 980; these values indicate that the basalt rock in the study area has a high hardness. The high hardness can be explained by the fact that the basalt rock is composed of plagioclase, pyroxene, and olivine minerals that have a hardness on Mohs&#x2019; scale of 6, 6.6, and 6.5, respectively. The variation is due to micro-crack and small voids.</p>
<fig id="f0009">
<label>Figure 9</label>
<caption><p>Stress&#x2013;strain curves for the first sample.</p></caption>
<graphic xlink:href="MC2020_e230-g009.tif" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</fig>
</sec>
<sec id="sec5.3">
<title>5.3. Regression analysis</title>
<p>The prediction of UCS and E<sub>t</sub> using simple regression from non-destructive simple tests are widely used by many researchers (<xref ref-type="bibr" rid="cit0082">82</xref>-<xref ref-type="bibr" rid="cit0084">84</xref>)<bold>.</bold> In this research, simple regression equations such as linear, exponential, logarithm, and power were adapted to examine the relationship between UCS, E<sub>t</sub>, and LRH test values of basalt rock. Both UCS and E<sub>t</sub> increased with the increase LRH value (<xref ref-type="fig" rid="f0010">Figure 10</xref> and <xref ref-type="fig" rid="f0011">11</xref>).</p>
<fig id="f0010">
<label>Figure 10</label>
<caption><p>Correlation between USC and LRH.</p></caption>
<graphic xlink:href="MC2020_e230-g010.tif" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</fig>
<fig id="f0011">
<label>Figure 11</label>
<caption><p>Correlation between E<sub>t</sub> and LRH.</p></caption>
<graphic xlink:href="MC2020_e230-g011.tif" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</fig>
<p>Moreover, to evaluate the predicted simple regression equations (linear, power, logarithm, and polynomial) and to select the best equation to estimate both UCS and E<sub>t</sub> based on LRH value, the evaluation was conducted based on statistical performance indices, coefficient of determination (R<sup>2</sup>), and root mean square error (RMSE), which has been adapted by many researchers (<xref ref-type="bibr" rid="cit0085">85</xref>, <xref ref-type="bibr" rid="cit0086">86</xref>). A strong correlation model can be considered if R<sup>2</sup> equals 1.0 and RMSE are close to zero (<xref ref-type="bibr" rid="cit0029">29</xref>, <xref ref-type="bibr" rid="cit0033">33</xref>). The equations of these indices are listed below as <xref ref-type="disp-formula" rid="eq2">Equations [2</xref>] and [<xref ref-type="disp-formula" rid="eq3">3</xref>], and the results for each regression model are presented in <xref ref-type="table" rid="t0005">Table 5</xref>. The power equation is the best equation to predict UCS, while the linear is best to predict E<sub>t</sub>.</p>
<table-wrap id="t0005">
<label>Table 5</label>
<caption><p>Results of statistical regression models for UCS, E<sub>t</sub> predictions.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left">Mechanical properties</th>
<th align="left">Regression type</th>
<th align="center">Equation No.</th>
<th align="center">R<sup>2</sup></th>
<th align="center">RMSE</th>
</tr>
</thead>
<tbody>
<tr>
<td rowspan="5" align="left">UCS</td>
<td align="left">Linear</td>
<td align="left">UCS = 0.082(LRH) + 31.049</td>
<td align="center">0.878</td>
<td align="center">5.621</td>
</tr>
<tr>
<td align="left">Exponential</td>
<td align="left">UCS = 42.633 EXP (0.001LRH)</td>
<td align="center">0.855</td>
<td align="center">6.368</td>
</tr>
<tr>
<td align="left">Logarithmic</td>
<td align="left">UCS=49.553 Ln (LRH) - 234.24</td>
<td align="center">0.882</td>
<td align="center">5.512</td>
</tr>
<tr>
<td align="left">power</td>
<td align="left">UCS=1.475(LRH)<sup>0.6264</sup></td>
<td align="center">0.888</td>
<td align="center">5.464</td>
</tr>
<tr>
<td align="left">Linear</td>
<td align="left">E<sub>t</sub> = 0.0496(LRH) + 18.993</td>
<td align="center">0.792</td>
<td align="center">4.661</td>
</tr>
<tr>
<td rowspan="3">Et</td>
<td align="left">Exponential</td>
<td align="left">E<sub>t</sub> = 26.41 EXP (0.001LRH)</td>
<td align="center">0.777</td>
<td align="center">4.603</td>
</tr>
<tr>
<td align="left">Logarithmic</td>
<td align="left">E<sub>t</sub> = 28.976Ln(LRH) - 135.21</td>
<td align="center">0.750</td>
<td align="center">5.091</td>
</tr>
<tr>
<td align="left">power</td>
<td align="left">E<sub>t</sub> = 1.1645(LRH)<sup>0.5849</sup></td>
<td align="center">0.756</td>
<td align="center">4.80</td>
</tr>
</tbody>
</table>
</table-wrap>
<disp-formula id="eq2">
<alternatives>
<mml:math id="M2">
<mml:mrow>
<mml:msup>
<mml:mi>R</mml:mi>
<mml:mn>2</mml:mn>
</mml:msup>
<mml:mo>=</mml:mo>
<mml:mn>1</mml:mn>
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<p>Where ym: measured value, yp: predicted value, ya: an average of the measured value, n: total number of data.</p>
<p>To check the validity of these correlations, UCS and E<sub>t</sub> calculated from the adapted correlations were presented with the measured values (<xref ref-type="fig" rid="f0012">Figures 12</xref> and <xref ref-type="fig" rid="f0013">13</xref>). It can be concluded that these correlations are highly reliable in estimating both the UCS and the E<sub>t</sub> since the majority scattered around the quality line (y = x) lay within the range &#x00B1;20 %.</p>
<fig id="f0012">
<label>Figure 12</label>
<caption><p>Mapped experimental results and predicted UCS.</p></caption>
<graphic xlink:href="MC2020_e230-g012.tif" xmlns:xlink="http://www.w3.org/1999/xlink"/>
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<fig id="f0013">
<label>Figure 13</label>
<caption><p>Mapped experimental results and predicted E<sub>t</sub>.</p></caption>
<graphic xlink:href="MC2020_e230-g013.tif" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</fig>
<p>On the other hand, to check the validity of the power correlation proposed in this study to predict USC value for different rock types, the predicted values compared with measured values collected from previous literature (<xref ref-type="fig" rid="f0014">Figure 14</xref>). It can be concluded that for very low to low strength (class E and D) the predicted values are overestimated by the proposed correlations; for medium-strength (class C), the predicted value lays within &#x00B1; 20 % of the measured values; while for high and very high strength (class A and B) the predicted values are underestimated.</p>
<fig id="f0014">
<label>Figure 14</label>
<caption><p>Experimental and predicted UCS results using proposed linear correlation.</p></caption>
<graphic xlink:href="MC2020_e230-g014.tif" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</fig>
<p>However, the proposed power correlation to predict UCS in this study was compared with other researchers&#x2019; correlations presented in <xref ref-type="table" rid="t0001">Table 1</xref>. The majority of the previous relationship is power relations which agree with this study. However, the previous studies included different rock types with a wide range of strength varied between very weak to very strong rock, while in the current study the rock samples were collected from the same source with little variation in UCS (<xref ref-type="fig" rid="f0015">Figure 15</xref>).</p>
<fig id="f0015">
<label>Figure 15</label>
<caption><p>Comparison with some previous correlations to predict UCS from LRH.</p></caption>
<graphic xlink:href="MC2020_e230-g015.tif" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</fig>
</sec>
</sec>
<sec id="sec6" sec-type="conclusions">
<title>6. CONCLUSIONS</title>
<p>This research examined the correlation between LRH and the mechanical engineering properties for both UCS and E<sub>t</sub> for basalt rock. In this investigation, LRH value, UCS and E<sub>t</sub> were conducted on core specimens extracted from 30 different boulders collected from the neighboring area of Umm al-Jimal city. Linear regression was performed to correlate LRH value with both the UCS and the E<sub>t</sub> of basalt rock. From the analysis conducted, the following conclusions can be drawn:</p>
<list list-type="order">
<list-item><p>A strong to moderate strong correlation of power regression was found between Lee rebound hardness value (LRH) and UCS with (R<sup>2</sup> = 0.888, RMSE = 5.464) and moderate strong linear with the E<sub>t</sub> with (R<sup>2</sup> = 0.888, RMSE = 5.464). The results indicate that with the increase in LRH value, the value of both the UCS and the E<sub>t</sub> increases.</p></list-item>
<list-item><p>UCS and E<sub>t</sub> of basalt rock already utilized as a building stone in historic buildings can be estimated using simple, portable, non-destructive LRH tests rather than obtaining destructive core samples.</p></list-item>
<list-item><p>These proposed correlations are limited and only applicable for strong to very strong basalt rock with low porosity in the study area.</p></list-item>
</list>
</sec>
</body>
<back>
<ack>
<title>ACKNOWLEDGEMENT</title>
<p>The authors would like to thank Mr. Tareq Albeshety from the geology department at Al Hashemite University for his help in conducting XRD and thin section. Our great thanks to Prof. Ahmad al-Malabeh from the geology department at Al Hashemite University for reviewing and revising the petrography analysis part; his help is really appreciated.</p>
</ack>
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