1. Introduction
In recent years, low-carbon sustainability has been a key focus of research in the construction industry [
1]. Many scholars have explored this direction, such as using recycled aggregates to replace natural aggregates in the production of recycled concrete [
2], using fly ash to partially replace cement as a binder in concrete [
3], incorporating straw fibers into concrete for modification [
4], and substituting natural river sand as fine aggregate in concrete with manufactured sand [
5]. The focus of this study is on the preparation of concrete using manufactured sand to investigate its impact on frost resistance. Natural river sand is an irreplaceable resource [
6]. However, the accelerated global urbanization process has led to the over-extraction of natural sand, causing significant environmental damage [
7]. From an economic perspective, the production cost of manufactured sand is typically lower than that of natural river sand. This is because the raw materials for manufactured sand primarily come from construction waste, which ensures a more stable supply and relatively lower prices. In contrast, the price of river sand continues to rise due to its gradual depletion, making the use of manufactured sand an effective way to reduce material costs in construction [
8]. Jadhav et al. found that replacing 60% of natural sand with manufactured sand not only achieved good strength but also reduced costs by approximately 10–15% in their study on the feasibility of using manufactured sand to replace natural river sand in concrete production [
9]. From an environmental protection perspective, the excessive extraction of natural river sand often leads to riverbed subsidence, resulting in a series of ecological issues [
10]. According to Gupta et al., using manufactured sand as a substitute for river sand in construction not only reduces pollution from waste accumulation but also decreases river sand extraction by approximately 30% to 50%, which is significant for protecting rivers and surrounding ecosystems [
11]. More importantly, the localized production of manufactured sand can reduce carbon emissions by 20% to 30% compared to the long-distance transportation of river sand [
12]. As a result, substituting natural sand with manufactured sand as fine aggregate in concrete has become a research focus [
13].
Manufactured sand particles are angular and rough, with a coarse and porous texture [
14]. Therefore, the angular shape and contour of manufactured sand can affect the compressive strength, flexural strength, and dynamic modulus of manufactured sand concrete [
15]. Many scholars have already conducted various studies on manufactured sand concrete. Jin et al. [
16] researched the fatigue life of manufactured sand concrete beams and found that their fatigue life is associated with the range of applied load or stress. Li et al. [
17] studied the abrasion resistance of manufactured sand cement concrete and found that the roughness and angularity of manufactured sand significantly enhance its abrasion resistance compared to conventional concrete. The optimal performance was achieved upon reaching 10% stone powder content in the manufactured sand. Shen et al. [
18] used sandstone-derived manufactured sand to prepare ultra-high-strength concrete. Their research found that the hydration products of manufactured sand were much finer than those in conventional concrete, resulting in higher strength compared to concrete made with river sand. Li et al. [
19] studied the effects of manufactured sand on the properties of both low-strength and high-strength concrete. The results indicated that when the stone powder content in the manufactured sand ranged from 0% to 20%, the chloride ion permeability and frost resistance of low-strength concrete decreased to varying extents, whereas high-strength concrete was almost unaffected. Riyadh et al. [
20] quantified the shape characteristics of manufactured sand, providing better control methods for the workability of manufactured sand cement concrete. Prakash et al. [
21] used manufactured sand to prepare self-compacting concrete. Due to the larger surface area of the manufactured sand particles, a higher volume of paste is required during preparation. Experimental verification showed that, although theoretically more paste is needed, the substantial amount of fines in the manufactured sand effectively fills the required paste volume. Therefore, using manufactured sand to produce self-compacting concrete is feasible. Cai et al. [
22] studied the fracture mechanics of manufactured sand cement concrete with the addition of steel fibers. The research found that adding steel fibers significantly improved its load-bearing capacity and post-peak behavior. As the volume fraction of steel fibers increased, the concrete’s post-peak behavior changed from quasi-brittle to ductile, and its residual strength also increased accordingly. Wang et al. [
23] prepared high-strength concrete (HMC) with manufactured sand from different sources and studied its bonding performance with steel reinforcement. The tests revealed that as the content of stone powder in the manufactured sand increased, the bond strength between the HMC and the steel reinforcement initially increased and then decreased. Finally, by fitting the experimental data, they obtained a bond-slip constitutive model for HMC and steel reinforcement. Zhu et al. [
24] determined the carbon emission factors for manufactured sand and manufactured sand gravel in their study and calculated the carbon emissions of manufactured sand concrete (MSC). They used the Gaussian distribution function to fit the variations in compressive strength and carbon reduction rate of MSC under different stone powder replacement rates and fly ash replacement rates. Wang et al. [
25] tested the performance of manufactured sand cement concrete at high temperatures and analyzed the factors affecting its performance under such conditions. They used measured stress–strain curves and existing high-temperature behavior constitutive models to conduct their analysis. Yang et al. [
26] tested the carbonation depth of reinforcement in MSC with different amounts of stone powder and used scanning electron microscopy (SEM) to analyze the carbonation mechanism of MSC. The test results showed that with the increase in stone powder content, the carbonation depth and corrosion probability of the reinforcement initially decreased and then increased. Zhao et al. [
27] prepared concrete of different strength grades using both basic and optimized dosages of water-reducing agents. The test results indicated that the optimized dosage of water-reducing agents significantly improved the flowability, peak stress, and elastic modulus of artificial sand concrete at the same strength grade, while reducing slump loss, peak strain, and porosity.
Although there has been extensive research on the strength of manufactured sand cement concrete, studies on its freeze–thaw resistance are still relatively scarce. Piotr et al. [
28] studied the freeze–thaw resistance of concrete prepared with waste foundry sand as a replacement for natural sand. Their experiments revealed that adding 5% waste foundry sand resulted in a mass loss of 6.31% after 180 freeze–thaw cycles, which is more than double that of ordinary concrete. However, when the waste foundry sand content was increased to 15%, the mass loss slightly decreased to 5.1%. Processing iron tailings into fine sand as a substitute for natural river sand holds considerable potential. Shi et al. [
29] employed the entropy weight method to develop a Weibull damage model to assess the freeze–thaw cycle performance of concrete made with iron tailings sand. The findings revealed that damage in the concrete progresses from the edges of the specimen toward the center, with damage levels ranging between 28% and 44%.
With the advancement of modern computing technology, artificial neural networks (ANNs) have found widespread application in traditional engineering fields, offering reliable connections between inputs and outputs [
30]. ANNs are a nonlinear data modeling approach inspired by the functioning of biological neural networks for processing information [
31]. These networks generally consist of three types of layers: an input layer, an output layer, and one or more hidden layers. Information is transmitted and processed through neurons, which, after weighted modifications, generate a nonlinear output [
32]. To date, neural network prediction models have seen extensive application in research on manufactured sand concrete [
33,
34,
35,
36,
37]. Himank et al. [
35] utilized artificial neural network technology to predict the mechanical properties of waste foundry sand concrete. Upon comparing the predicted results with experimental outcomes, they found that the reliability coefficients for compressive strength and tensile strength reached 0.9007 and 0.9022, respectively. This demonstrates the model’s high accuracy and practical value. Gottapu et al. [
38] developed a neural network prediction model based on the Levenberg–Marquardt (LM) algorithm and the Steepest Descent (SD) algorithm to assess the mechanical properties of fiber-reinforced concrete made with various fiber percentages and manufactured sand as a replacement for natural sand. The results indicated that the LM algorithm required fewer iterations and produced more accurate predictions than the SD algorithm, with an accuracy of up to 95%.
Since manufactured sand replaces natural river sand in manufactured sand cement concrete, various properties will change significantly. However, current research on the frost resistance of manufactured sand concrete is limited, and using neural networks to predict its frost resistance indicators is even rarer. This paper investigates the mass loss rate and relative dynamic modulus of elasticity of manufactured sand cement concrete following freeze–thaw cycles. We also developed a BP neural network prediction model to assess its effectiveness in forecasting the frost resistance of manufactured sand concrete.