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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Mater.</journal-id>
<journal-title-group>
<journal-title>Frontiers in Materials</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Mater.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2296-8016</issn>
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<publisher-name>Frontiers Media S.A.</publisher-name>
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<article-id pub-id-type="publisher-id">1788884</article-id>
<article-id pub-id-type="doi">10.3389/fmats.2026.1788884</article-id>
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<subj-group subj-group-type="heading">
<subject>Original Research</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Short-term performance optimization of steel fiber-reinforced concrete for roadway support</article-title>
<alt-title alt-title-type="left-running-head">Xu et al.</alt-title>
<alt-title alt-title-type="right-running-head">
<ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3389/fmats.2026.1788884">10.3389/fmats.2026.1788884</ext-link>
</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Xu</surname>
<given-names>Xiaowen</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
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</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Chen</surname>
<given-names>Junzhi</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
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<contrib contrib-type="author">
<name>
<surname>Zhang</surname>
<given-names>Yonggang</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
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<contrib contrib-type="author">
<name>
<surname>Shuai</surname>
<given-names>Ping</given-names>
</name>
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<sup>3</sup>
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<aff id="aff1">
<label>1</label>
<institution>Faculty of Land Resources Engineering, Kunming University of Science and Technology</institution>, <city>Kunming</city>, <country country="CN">China</country>
</aff>
<aff id="aff2">
<label>2</label>
<institution>College of Urban Construction, Zhejiang Shuren University</institution>, <city>Hangzhou</city>, <country country="CN">China</country>
</aff>
<aff id="aff3">
<label>3</label>
<institution>China Railway Resource Group Co., Ltd.</institution>, <city>Beijing</city>, <country country="CN">China</country>
</aff>
<author-notes>
<corresp id="c001">
<label>&#x2a;</label>Correspondence: Junzhi Chen, <email xlink:href="mailto:cjz1232025@163.com">cjz1232025@163.com</email>
</corresp>
</author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2026-02-24">
<day>24</day>
<month>02</month>
<year>2026</year>
</pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2026</year>
</pub-date>
<volume>13</volume>
<elocation-id>1788884</elocation-id>
<history>
<date date-type="received">
<day>15</day>
<month>01</month>
<year>2026</year>
</date>
<date date-type="rev-recd">
<day>04</day>
<month>02</month>
<year>2026</year>
</date>
<date date-type="accepted">
<day>09</day>
<month>02</month>
<year>2026</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2026 Xu, Chen, Zhang and Shuai.</copyright-statement>
<copyright-year>2026</copyright-year>
<copyright-holder>Xu, Chen, Zhang and Shuai</copyright-holder>
<license>
<ali:license_ref start_date="2026-02-24">https://creativecommons.org/licenses/by/4.0/</ali:license_ref>
<license-p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License (CC BY)</ext-link>. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</license-p>
</license>
</permissions>
<abstract>
<sec>
<title>Introduction</title>
<p>Steel fiber-reinforced concrete(SFRC) is widely used to mitigate early instability during mining because of its excellent toughness and crack resistance. However, its rapid early strength development requires chemical accelerators. Short-term support performance also depends on support thickness.</p>
</sec>
<sec>
<title>Methods</title>
<p>This study investigated the effects of accelerator dosage and support thickness on short-term SFRC performance using a 1363-m-level transport roadway in an iron ore mine in Yunnan Province as a case study. The analysis focused on two critical short-term time points-4 h and 7 h after mining-to identify the optimal support parameters. Laboratory specimens were prepared with accelerator dosages of 5%, 7.5% and 10%. Mechanical properties were measured at 4 and 7 h of curing. Numerical simulations evaluated displacement, maximum principal stress,and plastic zone development for SFRC supports of 30 mm, 60 mm, and 100 mm thicknesses at 4 and 7 h.</p>
</sec>
<sec>
<title>Results</title>
<p>The results indicated that decreasing accelerator dosage and extending curing age increase compressive strength and shear resistance but reduce elastic modulus. A lower accelerator dosage and greater support thickness reduced roadway displacement, plastic zone volume, and maximum principal stress. Support thickness was the dominant factor influencing SFRC support effectiveness. The optimal SFRC configuration was 5% accelerator dosage and a 100 mm support thickness.</p>
</sec>
<sec>
<title>Discussion</title>
<p>Field measurements confirmed that sidewall displacements stabilized at approximately 25 mm. This outcome indicated satisfactory performance of the adopted support system. These findings provide a scientific for optimizing short-term mechanical parameters of SFRC roadway supports.</p>
</sec>
</abstract>
<kwd-group>
<kwd>correlation analysis</kwd>
<kwd>numerical simulation</kwd>
<kwd>parameter optimization</kwd>
<kwd>roadway support</kwd>
<kwd>steel fiber-reinforced concrete</kwd>
</kwd-group>
<funding-group>
<funding-statement>The author(s) declared that financial support was received for this work and/or its publication. The author(s) declared that financial support was received for this work and/or its publication. This work was supported by the National Natural Science Foundation of China: Research on the Engineering Induced Mechanism and Monitoring and Early Warning of Rock Slope Disasters in Mountainous Areas (Grant No. U1602232).</funding-statement>
</funding-group>
<counts>
<fig-count count="7"/>
<table-count count="9"/>
<equation-count count="9"/>
<ref-count count="37"/>
<page-count count="00"/>
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<custom-meta-group>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Structural Materials</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="s1">
<label>1</label>
<title>Introduction</title>
<p>Roadways are the principal conduits for transport, ventilation, and operations in underground resource extraction, and their stability directly governs construction safety, production efficiency, and long-term operational outcomes (<xref ref-type="bibr" rid="B11">Jiang et al., 2026</xref>; <xref ref-type="bibr" rid="B23">Wang T et al., 2025</xref>). Excavation breaks the <italic>in-situ</italic> stress equilibrium and initiates a dynamic sequence of stress redistribution, deformation, and progressive failure in the surrounding rock (<xref ref-type="bibr" rid="B24">Wang Z et al., 2025</xref>). The initial post-excavation period is particularly critical due to rapid deformation rates and low stability (<xref ref-type="bibr" rid="B7">Gao et al., 2025</xref>; <xref ref-type="bibr" rid="B37">Zuo et al., 2025</xref>). Support systems must rapidly provide load-bearing capacity to counteract rock loads and restrain accelerating deformation; otherwise, roadway collapse, shotcrete delamination, and other failures that cause casualties and economic loss may occur (<xref ref-type="bibr" rid="B6">Chen Y et al., 2025</xref>). Consequently, developing materials and techniques tailored to short-term, high-intensity support and optimizing support-parameter combinations constitute a key unresolved technical challenge in underground engineering (<xref ref-type="bibr" rid="B3">Chen D et al., 2024</xref>; <xref ref-type="bibr" rid="B8">Gong et al., 2025</xref>; <xref ref-type="bibr" rid="B10">Jiang et al., 2025</xref>).</p>
<p>Steel fiber-reinforced concrete (SFRC) offers distinct advantages over traditional shotcrete for reducing rock deformation and extending support service life. It is increasingly used for underground roadway support (<xref ref-type="bibr" rid="B14">Li et al., 2019</xref>; <xref ref-type="bibr" rid="B32">Zhang et al., 2024</xref>) due to its superior toughness, crack resistance, and impact resistance (<xref ref-type="bibr" rid="B25">Wu et al., 2025</xref>; <xref ref-type="bibr" rid="B34">Zhao et al., 2025</xref>). The steel fibers form a three-dimensional, randomly oriented support network within the concrete matrix that effectively inhibits crack initiation and propagation (<xref ref-type="bibr" rid="B15">Li et al., 2021</xref>; <xref ref-type="bibr" rid="B18">Negi and Jain, 2022</xref>). Consequently, it increases material tensile (<xref ref-type="bibr" rid="B2">Bakhshi et al., 2025</xref>; <xref ref-type="bibr" rid="B20">Song et al., 2025</xref>) and shear strength (<xref ref-type="bibr" rid="B5">Chen Y et al., 2024</xref>; <xref ref-type="bibr" rid="B35">Zhi et al., 2026</xref>) and enhances support confinement of the surrounding rock. However, the short-term support performance of SFRC depends critically on rapid early-strength development. This development is determined not only by the material mix but also by support design parameters. The accelerator&#x2014;a critical additive in SFRC (<xref ref-type="bibr" rid="B16">Li et al., 2023</xref>)&#x2014;directly controls setting time and early strength gain. Consequently, appropriate accelerator use is essential for rapid tunnelling and timely support. Support thickness directly affects structural stiffness and load-bearing capacity. It should be selected according to rock mass mechanical properties and the loosened-zone dimensions to ensure effective support performance.</p>
<p>Extensive research has targeted these engineering issues. Laboratory studies have quantified how steel-fiber dosage (<xref ref-type="bibr" rid="B12">Koorikkattil et al., 2026</xref>; <xref ref-type="bibr" rid="B22">Wang L et al., 2025</xref>), fiber length (<xref ref-type="bibr" rid="B33">Zhang et al., 2025</xref>), diameter (<xref ref-type="bibr" rid="B1">Al-Shamasneh et al., 2025</xref>) and type (<xref ref-type="bibr" rid="B31">Yun et al., 2022</xref>) and dosage (<xref ref-type="bibr" rid="B13">Kos et al., 2023</xref>) of the accelerator influence concrete mechanical behavior. The results indicate that accelerators substantially reduce setting time and accelerate early strength gain, although excessive dosing can impair later strength. Steel fibers enhance toughness and crack control, but benefits depend on uniform fiber dispersion (<xref ref-type="bibr" rid="B36">Zhu et al., 2025</xref>). Numerical simulations (<xref ref-type="bibr" rid="B9">Jia et al., 2025</xref>), loosening-zone theory (<xref ref-type="bibr" rid="B26">Wu et al., 2026a</xref>), and principles of the New Austrian Tunnelling Method (NATM) have been applied to roadway support design. These methods have been used to assess the effects of support thickness (<xref ref-type="bibr" rid="B29">Xue et al., 2025</xref>), application timing (<xref ref-type="bibr" rid="B21">Sun et al., 2025</xref>), and anchor arrangement (<xref ref-type="bibr" rid="B4">Chen J et al., 2025</xref>; <xref ref-type="bibr" rid="B27">Wu et al., 2026b</xref>) on roadway stability. Nonetheless, most studies focus on single variables and do not systematically address the coupled effect of accelerator dosage and support thickness. Moreover, studies of SFRC supports have tended to emphasize long-term mechanical properties (<xref ref-type="bibr" rid="B28">Xu et al., 2024</xref>; <xref ref-type="bibr" rid="B30">Yuan et al., 2025</xref>), durability (<xref ref-type="bibr" rid="B19">Ortiz-Lozano et al., 2025</xref>), or macroscopic performance assessment. They create a gap in understanding the short-term (hours after excavation) coupling between material properties&#x2014;particularly those governed by accelerator dosage&#x2014;and support parameters such as thickness. Current designs rely heavily on engineering analogies and practitioner experience. They lack refined, quantitative analyses of short-term support effects. As a result, projects often suffer from poor early adhesion of shotcrete to rock surfaces, inadequate consolidation, and premature cracking or spalling. These defects undermine the immediate support of unstable surrounding rock.</p>
<p>To address this gap, the study used a 1363-m-level transport roadway in an iron mine in Yunnan Province as an engineering case to optimize SFRC support. First, SFRC specimens with accelerator dosages of 5%, 7.5%, and 10% were prepared. Their unconfined compressive strength (UCS), shear strength, and elastic modulus were measured after 4 and 7 h of curing to reveal how accelerator dosage and curing age affect SFRC short-term mechanical behavior. Then, numerical simulations were used to evaluate roadway displacements, stress distributions, and the evolution of plastic zones under different accelerator dosages and support thicknesses (30 mm, 60 mm, 100 mm). The analysis clarified the coupled influence of accelerator dosage and support thickness on short-term support performance. Finally, the optimal parameter combination was validated in the field. The research provides a scientifically grounded optimization protocol for SFRC roadway support.</p>
</sec>
<sec id="s2">
<label>2</label>
<title>Engineering background</title>
<sec id="s2-1">
<label>2.1</label>
<title>Geological conditions and support scheme</title>
<p>An iron mine in Yunnan Province primarily produces siderite. The mine is developed by horizontal adits and employs a segmented-caving mining method. The mining area is situated within a fault zone characterized by well-developed joints and fissures. The 1363-m-level haulage roadway is currently being excavated. The roadway is designed as a triple-centered arch with a width of 3 m, a sidewall height of 1.8 m, and an arch height of 1 m. Field geological survey indicated that the roadway surrounding rock is mainly fractured Grade III rock. Some sections are low-quality Grade IV rock. The surrounding rock is primarily sedimentary-metamorphic carbonate rock, and the exposed rock is predominantly limestone.</p>
<p>SFRC is used as support in the mined 1363-m-level roadway. The concrete is specified as grade C20. The specified support thicknesses are 30 mm and 60 mm. Field investigations identified two problems for this support strategy: short-term support performance was difficult to guarantee, and long-term durability in wet environments was inadequate. In the short term, SFRC slurry sprayed onto rock surfaces exhibits poor adhesion and inadequate consolidation. A significant amount of slurry falls downward or flows along the roadway sidewall. These deficiencies render it difficult to ensure adequate sprayed layer thickness and quality. The sprayed layer exhibits cracking and spalling upon water exposure within 3&#x2013;10 days of slurry set. The severity of these issues becomes increasingly pronounced over time.</p>
</sec>
<sec id="s2-2">
<label>2.2</label>
<title>Causes of original support failure</title>
<p>The application of SFRC support in the 1363-m-level roadway showed problems such as unreliable short-term support performance and detachment/cracking. These issues are primarily constrained by material properties and inadequate matching of support parameters.<list list-type="order">
<list-item>
<p>Influence of material properties</p>
</list-item>
</list>
</p>
<p>SFRC is produced by adding steel fibers, silica fume, and other constituents to ordinary concrete. The fibers form bridges that inhibit crack development and improve the matrix&#x2019;s impact resistance and durability. Accelerators are incorporated to accommodate rapid mining by shortening setting time and reducing rebound rate. However, varying accelerator dosages change concrete setting time, which in turn modifies short-term mechanical properties and reduces the immediate effectiveness of SFRC support.<list list-type="order">
<list-item>
<label>2.</label>
<p>Support parameter mismatch</p>
</list-item>
</list>
</p>
<p>The thickness of the loosened zone was calculated by applying the loosening-zone theory together with the Mohr-Coulomb and Hoek-Brown strength criteria using <xref ref-type="disp-formula" rid="e1">Equations 1</xref>&#x2013;<xref ref-type="disp-formula" rid="e4">4</xref>.<disp-formula id="e1">
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<mml:mi mathvariant="normal">P</mml:mi>
<mml:mi mathvariant="normal">i</mml:mi>
</mml:msub>
<mml:mo>&#x3d;</mml:mo>
<mml:msub>
<mml:mi mathvariant="normal">P</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
<mml:mrow>
<mml:mfenced open="(" close=")" separators="&#x7c;">
<mml:mrow>
<mml:mn>1</mml:mn>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>sin</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:mi mathvariant="normal">&#x3c6;</mml:mi>
</mml:mrow>
</mml:mfenced>
</mml:mrow>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>cos</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:mi mathvariant="normal">&#x3c6;</mml:mi>
</mml:mrow>
</mml:math>
<label>(3)</label>
</disp-formula>
<disp-formula id="e4">
<mml:math id="m4">
<mml:mrow>
<mml:msub>
<mml:mi mathvariant="normal">R</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
<mml:mo>&#x3d;</mml:mo>
<mml:msup>
<mml:mrow>
<mml:mi mathvariant="normal">R</mml:mi>
<mml:mtext> </mml:mtext>
<mml:mrow>
<mml:mfenced open="(" close=")" separators="&#x7c;">
<mml:mrow>
<mml:mfrac>
<mml:mn>1</mml:mn>
<mml:mrow>
<mml:mn>1</mml:mn>
<mml:mo>&#x2b;</mml:mo>
<mml:mi>sin</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:mi mathvariant="normal">&#x3c6;</mml:mi>
</mml:mrow>
</mml:mfrac>
</mml:mrow>
</mml:mfenced>
</mml:mrow>
</mml:mrow>
<mml:mfrac>
<mml:mrow>
<mml:mn>1</mml:mn>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>sin</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:mi mathvariant="normal">&#x3c6;</mml:mi>
</mml:mrow>
<mml:mrow>
<mml:mn>2</mml:mn>
<mml:mo>&#x2061;</mml:mo>
<mml:mi>sin</mml:mi>
<mml:mo>&#x2061;</mml:mo>
<mml:mi mathvariant="normal">&#x3c6;</mml:mi>
</mml:mrow>
</mml:mfrac>
</mml:msup>
</mml:mrow>
</mml:math>
<label>(4)</label>
</disp-formula>where <italic>R</italic> is the thickness of the loosened zone (m). <italic>R</italic>
<sub>0</sub> is the radius of the loosened zone (m). <italic>P</italic>
<sub>0</sub> is the initial <italic>in-situ</italic> stress (MPa) and was taken as the mean of <italic>in-situ</italic> measurements at the mining site. <italic>m</italic>
<sub>
<italic>b</italic>
</sub>, <italic>s</italic>, and <italic>&#x3b1;</italic> are the dimensionless empirical parameters of the Hoek-Brown criterion. Their values were taken as <italic>m</italic>
<sub>
<italic>b</italic>
</sub> &#x3d; 1.2, s &#x3d; 0.004, and <italic>&#x3b1;</italic> &#x3d; 0.5for a rock-mass quality of GIS &#x3d; 45. <italic>r</italic>
<sub>0</sub> is the roadway radius. The equivalent radius is <italic>r</italic>
<sub>0</sub> &#x3d; (<italic>b</italic> &#x2b; 2<italic>h</italic>
<sub>0</sub>)/4 for a triple-centered arch roadway, where <italic>b</italic> is the roadway width and <italic>h</italic>
<sub>0</sub>is the full roadway height. Substituting the roadway dimensions yields <inline-formula id="inf1">
<mml:math id="m5">
<mml:mrow>
<mml:msub>
<mml:mi mathvariant="normal">r</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
<mml:mo>&#x3d;</mml:mo>
<mml:mn>2.15</mml:mn>
<mml:mi mathvariant="normal">m</mml:mi>
</mml:mrow>
</mml:math>
</inline-formula>.<italic>P</italic>
<sub>
<italic>i</italic>
</sub> is the support pressure (kN). <inline-formula id="inf2">
<mml:math id="m6">
<mml:mrow>
<mml:msub>
<mml:mi mathvariant="normal">&#x3c3;</mml:mi>
<mml:mtext>ci</mml:mtext>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> is the uniaxial compressive strength (MPa). <inline-formula id="inf3">
<mml:math id="m7">
<mml:mrow>
<mml:mi mathvariant="normal">&#x3c6;</mml:mi>
</mml:mrow>
</mml:math>
</inline-formula> is the internal friction angle (&#xb0;). <italic>c</italic>is the cohesion (MPa). Their values are listed in <xref ref-type="table" rid="T1">Table 1</xref>.</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Physical and mechanical parameters of the surrounding rock.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Lithology</th>
<th align="left">Tensile strength (MPa)</th>
<th align="left">Modulus of elasticity (GPa)</th>
<th align="left">Cohesion (MPa)</th>
<th align="left">Internal angle of friction (&#xb0;)</th>
<th align="left">UCS (MPa)</th>
<th align="left">Poisson&#x2019;s ratio</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">Surrounding rock</td>
<td align="left">0.57</td>
<td align="left">4.40</td>
<td align="left">0.50</td>
<td align="left">30.4</td>
<td align="left">1.43</td>
<td align="left">0.28</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>The calculated loosened zone thickness for the roadway was 1.73 m. According to the loosened-zone theory, the loosened zone in this roadway is classified as large and forms beneath unstable rock masses. A common support method for this situation is bolt-mesh-shotcrete support. However, this method performs poorly in loose and fractured rock mass with well-developed joints and fissures. Moreover, it cannot provide timely support during mining operations and involves a relatively cumbersome construction process. Therefore, after comprehensive consideration of the geological characteristics, SFRC support was chosen for this roadway.</p>
<p>Although the roadway in this mine employed SFRC support, the selection of support parameters was primarily based on empirical analogy and lacks theoretical justification. The New Austrian Tunnelling Method (NATM) indicates that an inadequately designed SFRC thickness can result in insufficient strength and stiffness of the support. This prevents the support structure from effectively resisting surrounding rock pressure and water erosion, leading to cracking and spalling.</p>
</sec>
</sec>
<sec id="s3">
<label>3</label>
<title>Laboratory mechanical tests</title>
<sec id="s3-1">
<label>3.1</label>
<title>SFRC specimen preparation</title>
<p>The cement used was ordinary Portland cement (P.O.42.5). The mass ratio of fine to coarse aggregate was 1:1. The fine aggregate was sand with a particle size of 3&#x2013;5 mm. The coarse aggregate consisted of pea gravel with a particle size of 5&#x2013;15 mm. Steel fibers measured 30 mm in length and 0.5 mm in diameter. The accelerator was an HQ-240 alkali-free liquid accelerator. The effect of the alkali-free liquid accelerator on support performance is concentrated in the early support stage: it substantially increases early concrete strength, results in a slower mid-term strength gain rate, and has little effect on long-term concrete strength. The water-to-cement ratio was 0.45. <xref ref-type="table" rid="T2">Table 2</xref> lists the quantities of each raw material required for one cubic meter of SFRC.</p>
<table-wrap id="T2" position="float">
<label>TABLE 2</label>
<caption>
<p>Quantities of each raw materials per cubic meter of SFRC.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="center">Materials</th>
<th align="center">Mass</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="center">Water</td>
<td align="center">180 kg</td>
</tr>
<tr>
<td align="center">Cement</td>
<td align="center">400 kg</td>
</tr>
<tr>
<td align="center">Silicon powder</td>
<td align="center">25 kg</td>
</tr>
<tr>
<td align="center">Steel fiber</td>
<td align="center">40 kg</td>
</tr>
<tr>
<td align="center">Accelerator</td>
<td align="center">7.5%</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>
<xref ref-type="fig" rid="F1">Figure 1</xref> shows photographs of the raw materials used in this study, including cement, silicon powder, steel fibers, and accelerator.</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>Raw materials for steel fibre reinforced concrete. <bold>(a)</bold> Cement. <bold>(b)</bold> Silicon powder. <bold>(c)</bold> Steel fiber. <bold>(d)</bold> Accelerator.</p>
</caption>
<graphic xlink:href="fmats-13-1788884-g001.tif">
<alt-text content-type="machine-generated">Panel a shows a close-up of a pile of gray powder on a black surface. Panel b presents a finer light gray powder in a container. Panel c depicts a small pile of thin, metallic fibers scattered on a dark tabletop. Panel d displays a white plastic bottle with a handle and screw cap, placed behind a small transparent cup containing a beige liquid.</alt-text>
</graphic>
</fig>
<p>The tests primarily investigated the effects of different accelerator dosages and curing ages on the mechanical properties of SFRC. These results were then used to evaluate the short-term support performance of the material. The case mine used an accelerator dosage of 7.5%. Accordingly, the accelerator dosages were set to 5%, 7.5%, and 10%, respectively, while all other mix proportions were held constant. Field practice indicated that shotcrete sets in 2&#x2013;4 h and typically attains about 70% of design strength at 7 h. Therefore, curing ages of 4 h and 7 h were chosen to represent the post-spray strength-gain period and the pre-secondary-spray stability check, respectively. Six specimen groups (A&#x2013;F) were prepared (<xref ref-type="table" rid="T3">Table 3</xref>). Each group comprised six SFRC specimens prepared by hand rodding and tamping according to the Standard for test methods of concrete physical and mechanical properties (GB/T 50,081-2019) (<xref ref-type="bibr" rid="B17">Ministry of Housing and Urban-Rural Development of the People&#x2019;s Republic of China, 2019</xref>). Three specimens were used for uniaxial compression tests, while the other three were used for variable-angle shear tests.</p>
<table-wrap id="T3" position="float">
<label>TABLE 3</label>
<caption>
<p>Mix proportions for SFRC specimens.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="center">Group</th>
<th align="center">No.</th>
<th align="center">Accelerator dosage (%)</th>
<th align="center">Curing age (h)</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="center">A</td>
<td align="center">A-A50C4</td>
<td align="center">5</td>
<td align="center">4</td>
</tr>
<tr>
<td align="center">B</td>
<td align="center">B-A75C4</td>
<td align="center">7.5</td>
<td align="center">4</td>
</tr>
<tr>
<td align="center">C</td>
<td align="center">C-A10C4</td>
<td align="center">10</td>
<td align="center">4</td>
</tr>
<tr>
<td align="center">D</td>
<td align="center">D-A50C7</td>
<td align="center">5</td>
<td align="center">7</td>
</tr>
<tr>
<td align="center">E</td>
<td align="center">E-A75C7</td>
<td align="center">7.5</td>
<td align="center">7</td>
</tr>
<tr>
<td align="center">F</td>
<td align="center">F-A10C7</td>
<td align="center">10</td>
<td align="center">7</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="s3-2">
<label>3.2</label>
<title>Experimental setup and methods</title>
<p>SFRC specimens cured for 4 and 7 h were subjected to uniaxial compression and variable-angle shear tests. The uniaxial compression test directly provided UCS. Measured stress-strain curves also allowed for the calculation of the SFRC&#x2019;s Poisson&#x2019;s ratio and elastic modulus. The variable-angle shear tests yielded the failure load for each specimen, from which the corresponding normal and shear stresses were computed. The resulting normal-stress versus shear-stress envelope was used to determine cohesion and the internal friction angle.</p>
<p>The uniaxial compression specimens were non-standard in size, therefore, the raw measurements required correction. UCS and elastic modulus are subject to size effects. When specimen size is below the standard, the size effect tends to cause overestimation of both parameters. Poisson&#x2019;s ratio is largely size-independent and can be approximated as equal to that of a standard specimen. The UCS and elastic modulus were corrected using the <xref ref-type="disp-formula" rid="e5">Equations 5</xref>, <xref ref-type="disp-formula" rid="e6">6</xref>:<disp-formula id="e5">
<mml:math id="m8">
<mml:mrow>
<mml:msubsup>
<mml:mi>f</mml:mi>
<mml:mrow>
<mml:mi>c</mml:mi>
<mml:mi>u</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>k</mml:mi>
</mml:mrow>
<mml:mo>&#x2032;</mml:mo>
</mml:msubsup>
<mml:mo>&#x3d;</mml:mo>
<mml:mn>0.9</mml:mn>
<mml:msub>
<mml:mi>f</mml:mi>
<mml:mrow>
<mml:mi>c</mml:mi>
<mml:mi>u</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>k</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
<label>(5)</label>
</disp-formula>
<disp-formula id="e6">
<mml:math id="m9">
<mml:mrow>
<mml:msup>
<mml:mi>E</mml:mi>
<mml:mo>&#x2032;</mml:mo>
</mml:msup>
<mml:mo>&#x3d;</mml:mo>
<mml:mi>E</mml:mi>
<mml:mo>&#xd7;</mml:mo>
<mml:msup>
<mml:mrow>
<mml:mfenced open="(" close=")" separators="&#x7c;">
<mml:mrow>
<mml:mfrac>
<mml:mrow>
<mml:mn>150</mml:mn>
</mml:mrow>
<mml:mrow>
<mml:mi>a</mml:mi>
</mml:mrow>
</mml:mfrac>
</mml:mrow>
</mml:mfenced>
</mml:mrow>
<mml:mi>n</mml:mi>
</mml:msup>
</mml:mrow>
</mml:math>
<label>(6)</label>
</disp-formula>where <inline-formula id="inf4">
<mml:math id="m10">
<mml:mrow>
<mml:msubsup>
<mml:mi mathvariant="normal">f</mml:mi>
<mml:mrow>
<mml:mtext>cu</mml:mtext>
<mml:mo>,</mml:mo>
<mml:mi mathvariant="normal">k</mml:mi>
</mml:mrow>
<mml:mo>&#x2032;</mml:mo>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula> is the corrected unconfined compressive strength of the standard specimen. <inline-formula id="inf5">
<mml:math id="m11">
<mml:mrow>
<mml:msub>
<mml:mi mathvariant="normal">f</mml:mi>
<mml:mrow>
<mml:mtext>cu</mml:mtext>
<mml:mo>,</mml:mo>
<mml:mi mathvariant="normal">k</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> is the measured unconfined compressive strength of the non-standard specimen. <inline-formula id="inf6">
<mml:math id="m12">
<mml:mrow>
<mml:msup>
<mml:mi mathvariant="normal">E</mml:mi>
<mml:mo>&#x2032;</mml:mo>
</mml:msup>
</mml:mrow>
</mml:math>
</inline-formula> is the corrected elastic modulus of the standard specimen. E is the measured elastic modulus of the non-standard specimen. <inline-formula id="inf7">
<mml:math id="m13">
<mml:mrow>
<mml:mi>a</mml:mi>
</mml:mrow>
</mml:math>
</inline-formula> is the side length of the non-standard specimen. <inline-formula id="inf8">
<mml:math id="m14">
<mml:mrow>
<mml:mi>n</mml:mi>
</mml:mrow>
</mml:math>
</inline-formula> is an exponent related to concrete properties. The <inline-formula id="inf9">
<mml:math id="m15">
<mml:mrow>
<mml:mi>n</mml:mi>
</mml:mrow>
</mml:math>
</inline-formula> for converting the elastic modulus from nonstandard to standard SFRC specimens typically ranges from 0.4 to 0.6,this study adopts 0.5.</p>
</sec>
<sec id="s3-3">
<label>3.3</label>
<title>Results and analysis</title>
<p>The uniaxial compression and variable-angle shear test results for the SFRC specimens are listed in <xref ref-type="sec" rid="s13">Supplementary Tables S1, S2</xref>. The calculated mechanical test results for the standardized SFRC specimens are presented in <xref ref-type="sec" rid="s13">Supplementary Tables S3</xref>. <xref ref-type="fig" rid="F2">Figure 2</xref> display the resulting mechanical parameters for the specimens under different test conditions.</p>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption>
<p>Mechanical parameters for SFRC specimens under different curing ages and accelerator dosages. <bold>(a)</bold> UCS. <bold>(b)</bold> Elastic modulus. <bold>(c)</bold> Internal friction angle. <bold>(d)</bold> Cohesion.</p>
</caption>
<graphic xlink:href="fmats-13-1788884-g002.tif">
<alt-text content-type="machine-generated">Four grouped bar charts display the effects of accelerator dosage (five percent, seven point five percent, ten percent) and curing time (four hours, seven hours) on different properties: (a) Unconfined Compressive Strength (UCS) in megapascals, (b) Elastic Modulus in gigapascals, (c) Internal Friction Angle in degrees, and (d) Cohesion in megapascals, showing that property values generally vary with both accelerator percentage and curing duration.</alt-text>
</graphic>
</fig>
<p>
<xref ref-type="fig" rid="F2">Figure 2a</xref> showed that the UCS of the SFRC specimens decreases as accelerator dosage increases. Increasing the accelerator dosage from 5% to 10% reduced UCS by 1.0 MPa at 4 h and 1.4 MPa at 7 h. This effect is attributed to the use of a liquid accelerator. Higher dosages increased the mixture&#x2019;s free water content, which reduced short-term solidification and early UCS. UCS increased with curing age; specimens tested at 7 h exhibited higher strength than those tested at 4 h. Overall, the maximum UCS was observed at 5% accelerator dosage and 7-h curing age.</p>
<p>
<xref ref-type="fig" rid="F2">Figure 2b</xref> indicated a positive correlation between the accelerator dosage and the elastic modulus for SFRC specimens when the accelerator dosage was 5%&#x2013;7.5%. Increasing the accelerator dosage from 5% to 7.5% raised the 4-h elastic modulus from 2.5 GPa to 6.8 GPa. The elastic modulus dropped as accelerator dosage increased from 7.5% to 10%. Overall, the elastic modulus was higher at the 4-h curing age.</p>
<p>
<xref ref-type="fig" rid="F2">Figure 2c</xref> indicated a negative correlation between the accelerator dosage and the internal friction angle for SFRC specimens at 4 h. Higher accelerator dosage lowered the internal friction angle and therefore reduced the concrete&#x2019;s strength. In general, the internal friction angle was more favorable at the 4-h curing age.</p>
<p>
<xref ref-type="fig" rid="F2">Figure 2d</xref> showed that the cohesion of SFRC specimens cured for 4 h was little affected by the accelerator dosage and remained around 0.7 MPa. The cohesion of SFRC specimens cured for 7 h reached a maximum of 2.0 MPa at an accelerator dosage of 5%. Cohesion was positively correlated with curing age. Overall, within the tested mix-design range, lower accelerator dosage improved the shear resistance of SFRC.</p>
</sec>
</sec>
<sec id="s4">
<label>4</label>
<title>Numerical simulation of the support performance of SFRC</title>
<sec id="s4-1">
<label>4.1</label>
<title>Simulation scenario</title>
<p>The aforementioned theoretical analysis and laboratory tests indicated that short-term SFRC support performance is primarily governed by the accelerator dosage and the support thickness. This section performed numerical simulations to assess how SFRC cured for 4 h and 7 h affects roadway support performance and to determine optimal support parameters for practical application. The accelerator dosages were set to 5%, 7.5%, and 10%, respectively. Support thickness choices were based on rock mass quality guidance. Generally, roadways with Grade III-IV surrounding rock require a shotcrete thickness of 80&#x2013;100 mm, whereas those exhibiting heavily loosened zones generally call for 50&#x2013;100 mm. The mechanical properties of SFRC are superior to those of ordinary concrete. Therefore, support thicknesses were set to 30 mm, 60 mm, and 100 mm, respectively. Eighteen simulation scenarios were then established using a single-factor control variable method. These scenarios are summarized in <xref ref-type="table" rid="T4">Table 4</xref>.</p>
<table-wrap id="T4" position="float">
<label>TABLE 4</label>
<caption>
<p>Numerical simulation scenario.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="center">Scenario</th>
<th align="center">Accelerator dosage (%)</th>
<th align="center">Support duration (h)</th>
<th align="center">Support thickness (mm)</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="center">1</td>
<td align="center">5</td>
<td align="center">4</td>
<td align="center">30</td>
</tr>
<tr>
<td align="center">2</td>
<td align="center">7.5</td>
<td align="center">4</td>
<td align="center">30</td>
</tr>
<tr>
<td align="center">3</td>
<td align="center">10</td>
<td align="center">4</td>
<td align="center">30</td>
</tr>
<tr>
<td align="center">4</td>
<td align="center">5</td>
<td align="center">4</td>
<td align="center">60</td>
</tr>
<tr>
<td align="center">5</td>
<td align="center">7.5</td>
<td align="center">4</td>
<td align="center">60</td>
</tr>
<tr>
<td align="center">6</td>
<td align="center">10</td>
<td align="center">4</td>
<td align="center">60</td>
</tr>
<tr>
<td align="center">7</td>
<td align="center">5</td>
<td align="center">4</td>
<td align="center">100</td>
</tr>
<tr>
<td align="center">8</td>
<td align="center">7.5</td>
<td align="center">4</td>
<td align="center">100</td>
</tr>
<tr>
<td align="center">9</td>
<td align="center">10</td>
<td align="center">4</td>
<td align="center">100</td>
</tr>
<tr>
<td align="center">10</td>
<td align="center">5</td>
<td align="center">7</td>
<td align="center">30</td>
</tr>
<tr>
<td align="center">11</td>
<td align="center">7.5</td>
<td align="center">7</td>
<td align="center">30</td>
</tr>
<tr>
<td align="center">12</td>
<td align="center">10</td>
<td align="center">7</td>
<td align="center">30</td>
</tr>
<tr>
<td align="center">13</td>
<td align="center">5</td>
<td align="center">7</td>
<td align="center">60</td>
</tr>
<tr>
<td align="center">14</td>
<td align="center">7.5</td>
<td align="center">7</td>
<td align="center">60</td>
</tr>
<tr>
<td align="center">15</td>
<td align="center">10</td>
<td align="center">7</td>
<td align="center">60</td>
</tr>
<tr>
<td align="center">16</td>
<td align="center">5</td>
<td align="center">7</td>
<td align="center">100</td>
</tr>
<tr>
<td align="center">17</td>
<td align="center">7.5</td>
<td align="center">7</td>
<td align="center">100</td>
</tr>
<tr>
<td align="center">18</td>
<td align="center">10</td>
<td align="center">7</td>
<td align="center">100</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="s4-2">
<label>4.2</label>
<title>Model establishment</title>
<p>A 3D numerical model with dimensions of 30 m &#xd7; 30 m &#xd7; 30 m (length &#xd7; width &#xd7; height) was developed in Midas GTS NX. The model comprised 195,720 elements and 201,056 nodes. The numerical model is illustrated in <xref ref-type="fig" rid="F3">Figure 3</xref>. To assess the model&#x2019;s accuracy, conducted a mesh sensitivity analysis. The results indicate that displacement and stress outcomes stabilise when the number of mesh elements exceeds 150,000, with variations falling below 2%. Furthermore, the simulated displacements closely match the recorded field monitoring data, validating the numerical model. The established model was imported into FLAC3D for computational analysis. It should be noted that this study treats SFRC as an isotropic continuous medium with uniformly distributed fibres, disregarding environmental factors such as temperature and humidity. An ideal elastoplastic constitutive model with Mohr-Coulomb failure criteria was used. The magnitude of the load P<sub>0</sub> is determined by taking the average value from measured <italic>in-situ</italic> stress data within the mining area. The load is applied to the top of the model to simulate the self-weight stress of the overlying strata. The lateral pressure coefficient was computed as 0.43 according to the Heim-Kinnick theorem. Lateral boundary constraints normal displacement to simulate the confining effect of the infinite far-field surrounding rock. The model bottom boundary was fixed.</p>
<fig id="F3" position="float">
<label>FIGURE 3</label>
<caption>
<p>3D numerical models. <bold>(a)</bold> Overall view. <bold>(b)</bold> Detailed view.</p>
</caption>
<graphic xlink:href="fmats-13-1788884-g003.tif">
<alt-text content-type="machine-generated">Panel (a) shows a 3D mesh model of a tunnel environment with a red tunnel at the center surrounded by turquoise layers. Panel (b) presents a cross-sectional view labeling the tunnel, spray layer, and surrounding rock.</alt-text>
</graphic>
</fig>
<p>The SFRC support performance under different support durations was simulated by assigning the mechanical parameters listed in <xref ref-type="sec" rid="s13">Supplementary Table S2</xref> to the support elements. These parameters were measured for varying accelerator dosages at curing ages of 4 h and 7 h. SFRC sprayed onto the rock surface develops strength rapidly. Therefore, directly assigning the 4-h and 7-h material property sets to the support elements does not accurately capture the roadway&#x2019;s short-term response after support. Accordingly, a FISH-language script was developed to define the time-dependent short-term strength development of the SFRC. Strength development was modeled with an exponential function using a growth parameter of 2.5. This implementation reproduced the short-term change in support performance after shotcrete support application. The core computational steps can be expressed by <xref ref-type="disp-formula" rid="e7">Equations 7</xref>, <xref ref-type="disp-formula" rid="e8">8</xref>.<disp-formula id="e7">
<mml:math id="m16">
<mml:mrow>
<mml:mi>S</mml:mi>
<mml:mo>&#x3d;</mml:mo>
<mml:mn>1</mml:mn>
<mml:mo>&#x2212;</mml:mo>
<mml:mrow>
<mml:mfenced open="(" close=")" separators="&#x7c;">
<mml:mrow>
<mml:mn>1</mml:mn>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>s</mml:mi>
</mml:mrow>
</mml:mfenced>
</mml:mrow>
<mml:mi mathvariant="italic">exp</mml:mi>
<mml:mrow>
<mml:mfenced open="(" close=")" separators="&#x7c;">
<mml:mrow>
<mml:mfrac>
<mml:mrow>
<mml:mi>k</mml:mi>
<mml:mo>&#xb7;</mml:mo>
<mml:msub>
<mml:mi>t</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
</mml:mrow>
<mml:mi>T</mml:mi>
</mml:mfrac>
</mml:mrow>
</mml:mfenced>
</mml:mrow>
<mml:mo>,</mml:mo>
<mml:mi>S</mml:mi>
<mml:mo>&#x2264;</mml:mo>
<mml:mn>1</mml:mn>
</mml:mrow>
</mml:math>
<label>(7)</label>
</disp-formula>
<disp-formula id="e8">
<mml:math id="m17">
<mml:mrow>
<mml:msubsup>
<mml:mi>t</mml:mi>
<mml:mn>0</mml:mn>
<mml:mo>&#x2032;</mml:mo>
</mml:msubsup>
<mml:mo>&#x3d;</mml:mo>
<mml:mi>t</mml:mi>
<mml:mo>&#x2b;</mml:mo>
<mml:msub>
<mml:mi>t</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
<mml:mo>,</mml:mo>
<mml:msubsup>
<mml:mi>t</mml:mi>
<mml:mn>0</mml:mn>
<mml:mo>&#x2032;</mml:mo>
</mml:msubsup>
<mml:mo>&#x2264;</mml:mo>
<mml:mi>T</mml:mi>
</mml:mrow>
</mml:math>
<label>(8)</label>
</disp-formula>
<disp-formula id="e9">
<mml:math id="m18">
<mml:mrow>
<mml:mi>C</mml:mi>
<mml:mo>&#x3d;</mml:mo>
<mml:mi>S</mml:mi>
<mml:mo>&#xb7;</mml:mo>
<mml:mi>F</mml:mi>
</mml:mrow>
</mml:math>
<label>(9)</label>
</disp-formula>where s is the initial strength ratio of the SFRC sprayed onto the rock surface and was set to 5%. <italic>S</italic> is the actual strength ratio of the SFRC. <italic>k</italic> is the strength growth rate and was set to 2.5. <italic>T</italic> is the support duration (4 h and 7 h in this study). <inline-formula id="inf10">
<mml:math id="m19">
<mml:mrow>
<mml:msubsup>
<mml:mi mathvariant="normal">t</mml:mi>
<mml:mn>0</mml:mn>
<mml:mo>&#x2032;</mml:mo>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula> is the cumulative duration. The calculation terminates when <inline-formula id="inf11">
<mml:math id="m20">
<mml:mrow>
<mml:msubsup>
<mml:mi mathvariant="normal">t</mml:mi>
<mml:mn>0</mml:mn>
<mml:mo>&#x2032;</mml:mo>
</mml:msubsup>
</mml:mrow>
</mml:math>
</inline-formula> reaches the target support duration. t<sub>0</sub> is the cumulative duration from the previous calculation step, with an initial value of 0 s t is the time increment per calculation step and was set to 2 min. C is the calculated mechanical parameter value for SFRC. F is the target final mechanical parameter value for SFRC.</p>
<p>Time-dependent functions for strength ratio and mechanical parameters were implemented so that the sprayed SFRC&#x2019;s properties evolve with curing age. Strength increased from an initial 5% to the target value. These updates were executed within the support simulation cycles and ceased once the preset support duration was reached. This approach addresses the difficulty of prescribing support duration in numerical models and captures the time-dependent evolution of material strength and support performance. Poisson&#x2019;s ratio, however, was fixed at its final value and was not affected by the strength evolution function. The physical and mechanical parameters of the surrounding rock are listed in <xref ref-type="sec" rid="s13">Supplementary Table S2</xref>.</p>
</sec>
<sec id="s4-3">
<label>4.3</label>
<title>Results and analysis</title>
<sec id="s4-3-1">
<label>4.3.1</label>
<title>Rock mass displacement</title>
<p>
<xref ref-type="table" rid="T5">Table 5</xref> summarizes the simulated roadway displacement for different scenarios. Left sidewall displacement ranged from 22.324 to 26.052 mm, while roof subsidence ranged from 19.934 to 24.35 mm. The overall deformation magnitudes were relatively consistent. In general, left sidewall displacement was slightly larger than roof subsidence, and both parameters rose and fell synchronously. These results reflected coordinated deformation of the surrounding rock across scenarios.</p>
<table-wrap id="T5" position="float">
<label>TABLE 5</label>
<caption>
<p>Simulated roadway displacement.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="center">Scenario</th>
<th align="center">Left sidewall displacement (mm)</th>
<th align="center">Roof subsidence (mm)</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="center">1</td>
<td align="center">25.762</td>
<td align="center">24.134</td>
</tr>
<tr>
<td align="center">2</td>
<td align="center">25.596</td>
<td align="center">23.925</td>
</tr>
<tr>
<td align="center">3</td>
<td align="center">25.581</td>
<td align="center">23.848</td>
</tr>
<tr>
<td align="center">4</td>
<td align="center">24.056</td>
<td align="center">22.324</td>
</tr>
<tr>
<td align="center">5</td>
<td align="center">24.762</td>
<td align="center">22.460</td>
</tr>
<tr>
<td align="center">6</td>
<td align="center">24.424</td>
<td align="center">22.108</td>
</tr>
<tr>
<td align="center">7</td>
<td align="center">22.324</td>
<td align="center">19.934</td>
</tr>
<tr>
<td align="center">8</td>
<td align="center">23.459</td>
<td align="center">21.131</td>
</tr>
<tr>
<td align="center">9</td>
<td align="center">23.038</td>
<td align="center">20.818</td>
</tr>
<tr>
<td align="center">10</td>
<td align="center">25.635</td>
<td align="center">23.624</td>
</tr>
<tr>
<td align="center">11</td>
<td align="center">26.052</td>
<td align="center">24.35</td>
</tr>
<tr>
<td align="center">12</td>
<td align="center">25.894</td>
<td align="center">24.267</td>
</tr>
<tr>
<td align="center">13</td>
<td align="center">24.605</td>
<td align="center">22.085</td>
</tr>
<tr>
<td align="center">14</td>
<td align="center">25.034</td>
<td align="center">22.805</td>
</tr>
<tr>
<td align="center">15</td>
<td align="center">24.785</td>
<td align="center">22.489</td>
</tr>
<tr>
<td align="center">16</td>
<td align="center">23.356</td>
<td align="center">20.38</td>
</tr>
<tr>
<td align="center">17</td>
<td align="center">24.002</td>
<td align="center">21.305</td>
</tr>
<tr>
<td align="center">18</td>
<td align="center">23.637</td>
<td align="center">20.843</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>The simulated roadway displacements were compared with field monitoring data, which commenced immediately after the installation of the SFRC support. To facilitate meaningful comparison, particular attention was focused on the 4-h and 7-h intervals post-support installation.</p>
<p>Field displacements were contrasted with numerical simulations employing the optimal support parameter combination (5% accelerator, 100 mm support thickness). Field monitoring values were extracted from <xref ref-type="fig" rid="F6">Figure 6</xref> and are presented in <xref ref-type="table" rid="T6">Table 6</xref>. Although the numerical simulation results were lower than the field monitoring values, the error fell within a reasonable range.</p>
<table-wrap id="T6" position="float">
<label>TABLE 6</label>
<caption>
<p>Comparison of simulated and monitored displacement values for the two sides of the tunnel.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="center">Comparative indicators</th>
<th align="center">Simulated forecast values (mm)</th>
<th align="center">On-site monitoring values (mm)</th>
<th align="center">Absolute error (mm)</th>
<th align="center">Relative error (%)</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="center">Support for 4 h</td>
<td align="center">22.324</td>
<td align="center">27.874</td>
<td align="center">5.550</td>
<td align="center">19.91</td>
</tr>
<tr>
<td align="center">Support for 7 h</td>
<td align="center">23.356</td>
<td align="center">27.791</td>
<td align="center">4.435</td>
<td align="center">15.96</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>Further, we performed correlation analysis on the simulation results using Stata. This analysis produced correlation coefficients between three factors&#x2014;accelerator dosage, support duration, and support thickness&#x2014;and two responses: roof subsidence and left sidewall displacement. The results are presented in <xref ref-type="table" rid="T7">Table 7</xref>.</p>
<table-wrap id="T7" position="float">
<label>TABLE 7</label>
<caption>
<p>Correlation analysis.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Factors</th>
<th align="left">Accelerator dosage</th>
<th align="left">Support duration</th>
<th align="left">Support thickness</th>
<th align="left">Roof displacement</th>
<th align="left">Left sidewall displacement</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">Accelerator dosage</td>
<td align="left">1.000</td>
<td align="left">--</td>
<td align="left">--</td>
<td align="left">--</td>
<td align="left">--</td>
</tr>
<tr>
<td align="left">Support duration</td>
<td align="left">0.000</td>
<td align="left">1.000</td>
<td align="left">--</td>
<td align="left">--</td>
<td align="left">--</td>
</tr>
<tr>
<td align="left">Support thickness</td>
<td align="left">0.000</td>
<td align="left">0.000</td>
<td align="left">1.000</td>
<td align="left">--</td>
<td align="left">--</td>
</tr>
<tr>
<td align="left">Roof displacement</td>
<td align="left">0.093</td>
<td align="left">0.059</td>
<td align="left">&#x2212;0.967</td>
<td align="left">1.000</td>
<td align="left">--</td>
</tr>
<tr>
<td align="left">Left sidewall displacement</td>
<td align="left">0.104</td>
<td align="left">0.208</td>
<td align="left">&#x2212;0.938</td>
<td align="left">0.000</td>
<td align="left">1.000</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>The correlation coefficients between accelerator dosage and roof subsidence and left sidewall displacement were 0.093 and 0.104, respectively. This indicated a positive correlation. Higher accelerator dosage correlated with greater roadway displacement. The correlation coefficients between support thickness and roof subsidence and left sidewall displacement were &#x2212;0.967 and &#x2212;0.938, respectively. This indicated a negative correlation. Greater support thickness resulted in smaller roadway displacement. The correlation coefficients between support duration and roof subsidence and left sidewall displacement were 0.059 and 0.208, respectively. This indicated a positive correlation. Longer support duration correlated with greater roadway displacement. This developmental pattern aligns with the rock-mass creep behavior, wherein strain increases over time. The absolute magnitudes of the correlation coefficients characterize the strength of the relationships between each influencing factor and roadway displacement. Therefore, the support thickness exhibited the strongest correlation with short-term roadway deformation, followed by the accelerator dosage.</p>
</sec>
<sec id="s4-3-2">
<label>4.3.2</label>
<title>Maximum principal stress</title>
<p>
<xref ref-type="table" rid="T8">Table 8</xref> summarizes the simulated maximum principal stress for different scenarios. The maximum principal stress ranged from 6.15 to 6.27 MPa across the 18 scenarios. The values were tightly clustered with minor fluctuations. These results indicated a consistently stable mechanical response of the structure under the different simulated scenarios. Scenario 10 exhibited the highest maximum principal stress (6.27 MPa), while scenarios seven to nine recorded the lowest (6.15 MPa). The remaining values were relatively dispersed and showed no clear monotonic trend.</p>
<table-wrap id="T8" position="float">
<label>TABLE 8</label>
<caption>
<p>Simulated maximum principal stress for different scenarios.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="center">Scenario</th>
<th align="center">Maximum principal stress (MPa)</th>
<th align="center">Scenario</th>
<th align="center">Maximum principal stress (MPa)</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="center">1</td>
<td align="center">6.23</td>
<td align="center">10</td>
<td align="center">6.27</td>
</tr>
<tr>
<td align="center">2</td>
<td align="center">6.24</td>
<td align="center">11</td>
<td align="center">6.24</td>
</tr>
<tr>
<td align="center">3</td>
<td align="center">6.24</td>
<td align="center">12</td>
<td align="center">6.24</td>
</tr>
<tr>
<td align="center">4</td>
<td align="center">6.19</td>
<td align="center">13</td>
<td align="center">6.21</td>
</tr>
<tr>
<td align="center">5</td>
<td align="center">6.21</td>
<td align="center">14</td>
<td align="center">6.20</td>
</tr>
<tr>
<td align="center">6</td>
<td align="center">6.20</td>
<td align="center">15</td>
<td align="center">6.20</td>
</tr>
<tr>
<td align="center">7</td>
<td align="center">6.15</td>
<td align="center">16</td>
<td align="center">6.16</td>
</tr>
<tr>
<td align="center">8</td>
<td align="center">6.15</td>
<td align="center">17</td>
<td align="center">6.18</td>
</tr>
<tr>
<td align="center">9</td>
<td align="center">6.15</td>
<td align="center">18</td>
<td align="center">6.17</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>The overall behavior of the maximum principal stress was consistent across all simulated scenarios. Therefore, the maximum principal stress contour maps of Scenarios 7 and 12 were selected for detailed analysis. The results are presented in <xref ref-type="fig" rid="F4">Figure 4</xref>. A circular stress zone developed around the roadway. A concentration zone of maximum principal stress formed at approximately 3.5 m outward from the two sidewalls of the roadway. The average maximum principal stresses for support thicknesses of 30 mm, 60 mm, and 100 mm were 6.24 MPa, 6.20 MPa, and 6.16 MPa, respectively. These results indicated an inverse relationship between support thickness and maximum principal stress. The average maximum principal stresses for support durations of 4 h and 7 h were 6.20 MPa and 6.89 MPa, respectively. The stress redistribution in the surrounding rock following excavation intensified over time. This resulted in a higher surrounding rock stress.</p>
<fig id="F4" position="float">
<label>FIGURE 4</label>
<caption>
<p>Simulated maximum principal stress contour maps. <bold>(a)</bold> Scenario 7 <bold>(b)</bold> Scenario 12.</p>
</caption>
<graphic xlink:href="fmats-13-1788884-g004.tif">
<alt-text content-type="machine-generated">Two contour plots from FLAC3D software display zone minimum principal stress around a tunnel cross-section. Plot (a) on the left and plot (b) on the right use color gradients from red to blue, with corresponding stress values in the legend, to illustrate stress distribution patterns.</alt-text>
</graphic>
</fig>
</sec>
<sec id="s4-3-3">
<label>4.3.3</label>
<title>Plastic zone</title>
<p>
<xref ref-type="table" rid="T9">Table 9</xref> presents the simulated plastic zone for different scenarios. The plastic-zone volume ranged from 139.21 to 156.97 m<sup>3</sup> across 18 scenarios. Scenario seven produced the minimum volume (139.21 m<sup>3</sup>), while Scenario six produced the maximum volume (156.97 m<sup>3</sup>). Overall, the plastic-zone volumes showed a relatively stable distribution.</p>
<table-wrap id="T9" position="float">
<label>TABLE 9</label>
<caption>
<p>Simulated volume of the plastic zone for different scenarios.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="center">Scenario</th>
<th align="center">Volume of the plastic zone (m<sup>3</sup>)</th>
<th align="center">Scenario</th>
<th align="center">Volume of the plastic zone (m<sup>3</sup>)</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="center">1</td>
<td align="center">156.28</td>
<td align="center">10</td>
<td align="center">156.84</td>
</tr>
<tr>
<td align="center">2</td>
<td align="center">152.91</td>
<td align="center">11</td>
<td align="center">153.58</td>
</tr>
<tr>
<td align="center">3</td>
<td align="center">152.23</td>
<td align="center">12</td>
<td align="center">153.98</td>
</tr>
<tr>
<td align="center">4</td>
<td align="center">142.18</td>
<td align="center">13</td>
<td align="center">155.26</td>
</tr>
<tr>
<td align="center">5</td>
<td align="center">156.60</td>
<td align="center">14</td>
<td align="center">150.20</td>
</tr>
<tr>
<td align="center">6</td>
<td align="center">156.97</td>
<td align="center">15</td>
<td align="center">150.81</td>
</tr>
<tr>
<td align="center">7</td>
<td align="center">139.21</td>
<td align="center">16</td>
<td align="center">149.03</td>
</tr>
<tr>
<td align="center">8</td>
<td align="center">147.24</td>
<td align="center">17</td>
<td align="center">156.72</td>
</tr>
<tr>
<td align="center">9</td>
<td align="center">139.94</td>
<td align="center">18</td>
<td align="center">150.70</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>The overall trend of the plastic zone was consistent across all simulated scenarios. Therefore, the plastic zone contour maps of Scenarios 7 and 12 were selected for detailed analysis. The results are presented in <xref ref-type="fig" rid="F5">Figure 5</xref>. The poor rock mass produced extensive plastic zone, which concentrated around the roadway in a butterfly-shaped symmetric pattern. The average plastic-zone volumes for accelerator dosages of 5%, 7.5%, and 10% were 149.80 m<sup>3</sup>, 152.88 m<sup>3</sup>, and 150.88 m<sup>3</sup>. The smallest volume occurred at the 5% accelerator dosage. The average plastic-zone volumes for support thicknesses of 30 mm, 60 mm, and 100 mm were 154.30 m<sup>3</sup>, 152.00 m<sup>3</sup>, and 147.14 m<sup>3</sup>, respectively. These results indicated an inverse relationship between support thickness and plastic-zone volume. The average plastic-zone volumes for support durations of 4 h and 7 h were 149.28 m<sup>3</sup> and 153.01 m<sup>3</sup>, respectively. The plastic-zone volume at 7 h was slightly higher than that at 4 h.</p>
<fig id="F5" position="float">
<label>FIGURE 5</label>
<caption>
<p>Simulated plastic zone contour maps: (a) Scenario 7 (b) Scenario 12.</p>
</caption>
<graphic xlink:href="fmats-13-1788884-g005.tif">
<alt-text content-type="machine-generated">Two side-by-side simulation outputs labeled (a) and (b) display tunnel cross-sections colored by zone state using a five-color legend to indicate none, shear-n shear-p, shear-n shear-p tension-p, shear-p, and shear-p tension-p. Each diagram shows distinct color distributions around the tunnel opening, with variations between the two panels in the zones exhibiting shear and tension states.</alt-text>
</graphic>
</fig>
</sec>
</sec>
</sec>
<sec id="s5">
<label>5</label>
<title>Field application and validation</title>
<p>Monitoring began immediately following the installation of SFRC support within the 1363-m-level roadway. A monitoring point was installed on the left sidewall. Continuous 3-day measurements were performed to record the relative displacement between the left and right sidewalls. <xref ref-type="fig" rid="F6">Figure 6</xref> shows the relative displacement between the sidewalls. <xref ref-type="fig" rid="F7">Figure 7</xref> presents the deformation rate.</p>
<fig id="F6" position="float">
<label>FIGURE 6</label>
<caption>
<p>Monitored relative displacement between the roadway sidewalls.</p>
</caption>
<graphic xlink:href="fmats-13-1788884-g006.tif">
<alt-text content-type="machine-generated">Line graph showing the distance between two sides of a tunnel in millimeters versus the number of monitoring sessions. Actual measured distance is represented by blue dotted lines, while the moving average trend is shown by a solid black line, indicating mild fluctuations around a generally stable distance over time.</alt-text>
</graphic>
</fig>
<fig id="F7" position="float">
<label>FIGURE 7</label>
<caption>
<p>Statistical chart of deformation rate of roadway.</p>
</caption>
<graphic xlink:href="fmats-13-1788884-g007.tif">
<alt-text content-type="machine-generated">Line graph depicting deformation rate in millimeters per second versus number of monitoring sessions, with blue dotted lines for deformation rate variability and a solid black line showing the average trend near zero over time.</alt-text>
</graphic>
</fig>
<p>
<xref ref-type="fig" rid="F6">Figure 6</xref> indicated that the relative distance between the roadway sidewalls stably varied between approximately 2,760 mm and 2,780 mm. The actual measured values (blue dots) showed more frequent and significant fluctuations. Specifically, the fluctuations reached around 200 mm. However, these fluctuations did not cause the moving average to display a distinct upward or downward trend. Although the relative distance between the roadway sidewalls may vary in the short term, the overall stability remained favorable. The moving average trend line indicated that the distance between the roadway sidewalls decreased from 2,797.6 mm to 2,769.4 mm during the monitoring period. This corresponded to a deformation of 28.2 mm. The average relative displacement trend and the deformation rate showed that the SFRC support preserves the roadway&#x2019;s overall stability. Although significant fluctuations were observed in the measured distances, the stable average trend indicated that the SFRC support effectively controlled deformation of the roadway sidewalls. Consequently, the roadway remained relatively stable in the short term, with no clear evidence of sustained deformation or instability.</p>
<p>
<xref ref-type="fig" rid="F7">Figure 7</xref> showed that the deformation rates (blue points) exhibit significant fluctuations. Their values oscillated frequently between &#x2212;30 mm/s and 30 mm/s. This demonstrated considerable variation in the deformation rate between the roadway sidewalls over time. The average trend line (black curve) remained close to 0 mm/s (&#x2212;0.02&#x2013;0.03 mm/s), with typical fluctuations of approximately 1 mm/s. These observations indicated that the roadway sidewall deformation rate remained generally stable throughout the monitoring period, with no discernible sustained increase or decrease. Short-term fluctuations in deformation rates arose from transient disturbances associated with mining operations, such as blasting vibrations and mine car movements. Nevertheless, these disturbances did not substantially compromise the overall stability of the roadway. The results demonstrated that SFRC support is highly resilient to such perturbations and can provide effective support in complex mining environments.</p>
</sec>
<sec sec-type="conclusion" id="s6">
<label>6</label>
<title>Conclusion</title>
<p>This study used the 1363-m-level roadway of an iron mine in Yunnan as the case background to investigate the short-term mechanical response of SFRC support. Support parameters were optimized through a combination of theoretical analysis, laboratory experiments, numerical simulation, and field testing. This study focuses on the short-term performance (4 and 7 h) of SFRC support systems, though it does not address long-term durability under sustained loading and environmental exposure. The numerical simulations employed an ideal elastoplastic model, neglecting rock mass creep behaviour. Field monitoring was conducted for only 3 days; it is recommended that future research undertake longer-term performance monitoring. The principal conclusions are as follows:<list list-type="order">
<list-item>
<p>The core reasons for the failure of the original SFRC support in this roadway included two aspects. An unreasonable accelerator dosage caused a decline in the short-term setting and hardening performance of SFRC. This resulted in insufficient material bond and strength. Numerical simulations indicate that increasing the support thickness from 30 mm to 100 mm reduced road displacement by 13.4% (with a 4.2 mm decrease in roof settlement) and decreased the plastic zone volume by 10.9%. These findings indicate that the original support thicknesses (30 mm and 60 mm) proved inadequate for the extensive loosened zone (1.73 m) to effectively resist surrounding rock pressure and water erosion, ultimately leading to cracking and spalling within the support structure.</p>
</list-item>
<list-item>
<p>The accelerator dosage was significantly correlated with the short-term mechanical properties of SFRC. Reducing the accelerator dosage from 10% to 5% increased short-term UCS (by 1.0 MPa after 4-h curing) and shear strength, but decreased the elastic modulus (by 4.1 GPa after 4-h curing). Support thickness had the greatest effect on roadway stability. Increasing the thickness from 30 mm to 100 mm reduced roadway displacement by 13.4% (roof subsidence decreased by 4.2 mm after 4-h curing) and reduced the plastic-zone volume by 10.9%.</p>
</list-item>
<list-item>
<p>Numerical simulations indicated that 5% accelerator dosage combined with a 100 mm support thickness was the optimal configuration. This arrangement reduced the roadway&#x2019;s maximum principal stress by 1.3% (from 6.23 MPa to 6.15 MPa) and decreased the plastic-zone volume by 10.8%. Field monitoring indicated that the deformation 3 days after support installation was 28.2 mm. The deformation rate was close to zero (&#x2212;0.02&#x2013;0.03 mm/s), and no abnormal increase was observed. These observations further confirm the reliability of the support scheme.</p>
</list-item>
</list>
</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="s7">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="sec" rid="s13">Supplementary Material</xref>, further inquiries can be directed to the corresponding author.</p>
</sec>
<sec sec-type="author-contributions" id="s8">
<title>Author contributions</title>
<p>XX: Visualization, Data curation, Methodology, Investigation, Validation, Conceptualization, Writing &#x2013; original draft, Formal Analysis. JC: Writing &#x2013; review and editing, Supervision, Project administration, Funding acquisition. YZ: Writing &#x2013; review and editing, Supervision. PS: Supervision, Writing &#x2013; review and editing.</p>
</sec>
<sec sec-type="COI-statement" id="s10">
<title>Conflict of interest</title>
<p>Author PS was employed by China Railway Resource Group Co., Ltd.</p>
<p>The remaining author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="ai-statement" id="s11">
<title>Generative AI statement</title>
<p>The author(s) declared that generative AI was not used in the creation of this manuscript.</p>
<p>Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.</p>
</sec>
<sec sec-type="disclaimer" id="s12">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec sec-type="supplementary-material" id="s13">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fmats.2026.1788884/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fmats.2026.1788884/full&#x23;supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="Table1.docx" id="SM1" mimetype="application/docx" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
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<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1465856/overview">Jue Li</ext-link>, Chongqing Jiaotong University, China</p>
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<bold>Reviewed by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1079905/overview">Pavlo Maruschak</ext-link>, Ternopil Ivan Pului National Technical University, Ukraine</p>
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<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/3355742/overview">Jianwen Shao</ext-link>, Ludong University, China</p>
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