The soil–rock mixture (SRM) usually contains a large amount of gravels exceeding 40 mm in size, so the traditional laboratory method cannot directly test its maximum dry density (MD), making it difficult to evaluate the compaction degree of the SRM subgrade during construction. In this paper, a numerical simulation method of the vibration compaction method for the SRM (NSM-VCM) was developed based on a discrete element method (DEM) and CT scanning. Based on the established NSM-VCM, the MD of SRMs with a maximum particle size greater than 40 mm (SRM-G) was investigated comprehensively. Based on the results of laboratory tests and the NSM-VCM, a predictive model and determination method of the MD of SRM-G were developed. Finally, field measurements were conducted to validate the laboratory investigations. The results showed that the maximum error between the MD of the SRM obtained from the NSM-VCM and the laboratory test was 0.1%, indicating that the established NSM-VCM has high predictive accuracy. The MD of SRM-G increases with an increasing maximum particle size and dosage of giant granules. Only when the soil–rock ratio is appropriate can SRM-G form a better skeleton dense structure, which is important for improving the MD and mechanical strength. The maximum error between the estimated MD and the measured MD from the field site is 1.3%, which indicates that the prediction model and method for SRM-G established in this paper have high precision. These results address the issue that the MD of SRM-G cannot be determined in a laboratory.

土石混合料（SRM）通常含有大量超过40 mm的砾石，传统的实验室方法无法直接测试其最大干密度（MD），难以评价SRM路基的压实度。建造。本文基于离散元法（DEM）和CT扫描，开发了一种SRM（NSM-VCM）振动压实方法的数值模拟方法。基于已建立的NSM-VCM，全面研究了最大粒径大于40 mm（SRM-G）的SRM的MD。基于实验室测试结果和NSM-VCM，建立了SRM-G MD的预测模型和确定方法。最后，进行现场测量以验证实验室调查。结果表明，NSM-VCM得到的SRM的MD与实验室测试的最大误差为0.1%，表明所建立的NSM-VCM具有较高的预测精度。SRM-G 的 MD 随着最大粒径和大颗粒剂量的增加而增加。只有当土石比合适时，SRM-G才能形成较好的骨架致密结构，这对提高MD和力学强度具有重要意义。估计的MD与现场实测MD的最大误差为1.3%，表明本文建立的SRM-G预测模型和方法具有较高的精度。这些结果解决了无法在实验室确定 SRM-G 的 MD 的问题。表明建立的 NSM-VCM 具有较高的预测精度。SRM-G 的 MD 随着最大粒径和大颗粒剂量的增加而增加。只有当土石比合适时，SRM-G才能形成较好的骨架致密结构，这对提高MD和力学强度具有重要意义。估计的MD与现场实测MD的最大误差为1.3%，表明本文建立的SRM-G预测模型和方法具有较高的精度。这些结果解决了无法在实验室确定 SRM-G 的 MD 的问题。表明建立的 NSM-VCM 具有较高的预测精度。SRM-G 的 MD 随着最大粒径和大颗粒剂量的增加而增加。只有当土石比合适时，SRM-G才能形成较好的骨架致密结构，这对提高MD和力学强度具有重要意义。估计的MD与现场实测MD的最大误差为1.3%，表明本文建立的SRM-G预测模型和方法具有较高的精度。这些结果解决了无法在实验室确定 SRM-G 的 MD 的问题。这对于提高MD和机械强度很重要。估计的MD与现场实测MD的最大误差为1.3%，表明本文建立的SRM-G预测模型和方法具有较高的精度。这些结果解决了无法在实验室确定 SRM-G 的 MD 的问题。这对于提高MD和机械强度很重要。估计的MD与现场实测MD的最大误差为1.3%，表明本文建立的SRM-G预测模型和方法具有较高的精度。这些结果解决了无法在实验室确定 SRM-G 的 MD 的问题。