Tempering Behavior of 420 MPa Grade Steel with Cu Alloying

Abstract

Nodes made from steel are widely applicable to the structure of pipe racks. In this paper, the Cu content and tempering temperature of 420 MPa grade (yield strength grade) steel alloyed with Cu were studied for their effect on strength and toughness. The precipitation behavior of different Cu contents during the normalizing cooling and tempering process of the steel, and the corresponding strength and toughness levels, were clarified. The research results showed that an experimental steel with ferrite as the matrix was prepared by the normalizing and tempering method. A strengthening method mainly based on Cu precipitation was proposed, which effectively promoted the steel to have a good toughness reserve while meeting the strength requirements. With the increase in Cu content, the contribution of Cu particle precipitation to strength gradually slowed down, mainly due to the weakening of the contribution of Cu particle growth and coarsening to precipitation strengthening.

1. Introduction

Recently, with the increasing demand for deepwater oil and gas extraction equipment and offshore wind power infrastructure construction, the long-term safety issues of jacket structures in marine service environments have become increasingly prominent [1,2]. The nodes and other such parts serve as stress-concentration areas and corrosion-sensitive zones of the structure. Their performance has a decisive impact on the fatigue life and service reliability of the entire platform. The traditional nodes constructed with welded steel pipes often encounter problems such as weld corrosion fatigue, micro-crack propagation, and tissue brittleness in the heat-affected zone in marine environments. These issues severely limit the extension of the service life of the pipe racks and the reduction in maintenance costs [3,4].

As an alternative to welded nodes, cast steel nodes have garnered increasing attention, as they can effectively eliminate weld-induced stress concentration, improve global mechanical continuity, and structural performance. To achieve the desired mechanical properties, this type of cast steel is usually made of low-carbon and microalloyed materials and combines heat-deformation methods such as forging and hot rolling [5,6]. Generally speaking, hot deformation is an effective method to enhance toughness and strength. However, this method inevitably leads to additional production processing steps, increasing energy consumption and production costs. If post-casting heat treatment or other modification methods are adopted to increase both toughness and strength to the level required by design, the above problems can be solved, and production costs can be reduced [7]. Therefore, the demand for developing cast steel components with excellent strength and toughness has prompted more researchers to focus on microalloying design of material composition and to carry out multi-objective optimization through appropriate heat treatment [8,9]. To ensure the alloy steel possesses an appropriate microstructure and fracture toughness to resist impact loads, while satisfying requirements for weldability and high strength, a low carbon content ranging from 0.03 wt.% to 0.15 wt.% is generally adopted [10,11]. In low-carbon steel, in order to enhance strength, the amount of pearlite within the structure can be increased by increasing the carbon content. However, this actually reduces the impact toughness [12]. Within the carbon content range from 0.03% to 0.15%, the amount of pearlite can be reduced, thereby achieving a simultaneous improvement in both strength and impact toughness. Based on low-carbon design, researchers investigated the effects of heat treatment combined with chemical composition adjustment on the properties of microalloyed cast steel. They found that quenching and tempering heat treatment, coupled with favorable toughness, can yield strength levels up to 690 MPa [13]. Jana et al. [14] reported that by controlling the heat treatment process, the tensile strength and elongation of cast steel microalloyed with V + Ti and Nb + V + Ti were significantly improved.

Furthermore, some studies [15,16,17] have demonstrated the simultaneous precipitation of multiple phases in steel, including simple carbides, complex carbides, and copper-rich precipitates, and have exploited the synergistic interactions between these phases to enhance mechanical properties. If Cu, Ti, and Mo are alloyed to the low-carbon ferritic steel, the yield strength can be increased from 267 MPa to 732 MPa, and the tensile strength can be raised from 401 MPa to 853 MPa. This increment significantly exceeds that of using only copper precipitation or only carbide precipitation [17]. Furthermore, the introduction of Ti element into high-strength low-carbon steel promotes the precipitation strengthening effect of Cu precipitates. When the Ti content is 0.05 wt%, the yield strength increases by 200 MPa. This is because Ti microalloying leads to an increase in the grain boundary density and the nucleation sites of dislocations, thereby promoting the refinement of the Cu-rich grains [18]. However, excellent low-temperature toughness is another required characteristic for marine engineering steel and jacket structures. The aforementioned precipitation strengthening is generally detrimental to the toughness of the steel. The changes in impact toughness of V, V-Nb, and V-Nb-Ti microalloyed steels are related to the characteristics of the precipitated particles [19]. It is worth noting that V–Ti steel with Nb exhibits inferior low-temperature toughness compared with V–Ti steel, since coarse particles such as (V, Nb, Ti)(C,N) act as local initiation sites for cleavage fracture [20]. However, precipitation can suppress austenite coarsening, leading to the refinement of martensite clusters while increasing the proportion of high-angle grain boundaries (HAGBs). HAGBs act as a natural barrier that hinders dislocation migration and crack propagation and have a positive effect on the toughness of the steel [21]. Compared with Nb steel and V-Ti steel, the addition of V-Ti has a refining and stabilizing effect on the microstructure of marine platform steel, enabling V-Ti steel to have excellent impact toughness at low temperatures [22].

Therefore, cast steels containing Cu alloying elements were prepared and subjected to different heat treatment tempering temperatures. Through microstructure characterization and mechanical property tests, the precipitation behavior of Cu in the Cu-alloyed cast steel and its influence on mechanical properties were understood. The relationship between the Cu-precipitated phase in the ferrite matrix and crack propagation was clarified, and the mechanism of its toughening effect was discussed. This provides a theoretical basis for ensuring the strength and toughness of this type of cast steel and realizing its industrial application in the future.

2. Experimental Procedure

A low-carbon-alloyed cast steel used in this study, with the chemical compositions in weight percentage, is shown in

Table 1. Chemical compositions of the studied steel (wt.%).

Sample	C	Mn	Si	Ni	Cu	Ti	P	S
0.8Cu	0.12	0.70	0.23	0.90	0.80	0.016	0.0058	0.0015
1.1Cu	0.12	0.71	0.23	0.91	1.10	0.016	0.0058	0.0016
1.4Cu	0.12	0.70	0.23	0.90	1.40	0.016	0.0057	0.0016

. The addition of the Ni element is to enhance its low-temperature toughness, while it can also enhance the hardenability. Ti is used to refine the structure during the solidification process. The experiment set up several sample blocks with 0.8, 1.1, and 1.4% Cu contents. Melting is carried out in a medium-frequency induction furnace. To ensure the metallurgical quality of the ingot, all alloying elements are added in the form of high-purity elementary substances. The pouring temperature is controlled at 1550 °C, and the molten metal is poured into a 200 kg cavity by sand casting. Rectangular samples with a size of 120 × 200 × 300 mm were cut from the cast steel. Heat treatment using an electric furnace was carried out in the laboratory. Block samples were first austenitized at 930 °C for 2 h and then air-cooled; some of the samples were subsequently tempered at 580, 610, and 640 °C. After heat treatment, standard Charpy impact and tensile specimens were prepared and tested according to GB/T 229 [23] and GB/T 228.1 [24], respectively, in which the Charpy V-notched specimens had a cross-section of 10 × 10 mm and a length of 55 mm. It was employed to study the impact resistance at −40 °C on an impact tester (HIT450, Zwick/Roell, Germany). Tensile tests were performed using a standard specimen (Gauge length 30 mm, gauge diameter 6 mm) on a tensile testing machine (8801, INSTRON, USA) at room temperature with a strain rate of 5 × 10³ s ⁻¹. The yield strength, tensile strength, and percent elongation displayed by the computer were directly recorded.

Samples for morphological observation were mechanically ground and polished, followed by etching in a 4~6% Nital solution. The microstructure information was characterized by a scanning electron microscope (SEM, model: Quanta650 FEG, FEI Company, Hillsboro, OR, USA) equipped with an Oxford electron backscattered diffraction (EBSD) detector. Microstructural morphology was characterized by an accelerating voltage of 5 kV. EBSD analysis was carried out at an accelerating voltage of 20 kV, with a scan area of 200 × 200 µm² and a step size of 0.2 µm. Samples for transmission electron microscope (TEM, JEM-F200, JEOL, Tokyo, Japan) were prepared after electropolishing with a twin-jet polishing machine in a solution containing 6% perchloric acid at −20 °C. X-ray diffraction (XRD) analysis was performed using an X-ray diffractometer (D/MAX 2550, RIGAKU, Tokyo, Japan) with Co-Kα radiation at 3°/min from 35° to 135° at room temperature. The mean lattice parameter $\alpha$ for the body-centered cubic (bcc) phase can be calculated by the experimental mean scattering angle $2{\theta }_i$ of the considered diffraction peak data of ferrite {hkl} reflections, including (200)_α, (211)_α, and (220)_α, using Equation (1). Relative mean bcc lattice (α) was calculated by the following Equation (2) [25,26]

$$\alpha ={\displaystyle \frac{1}{N}}{\displaystyle \sum _{i=1}^N\left(\frac{\lambda }{2}\right)}{\displaystyle \frac{\sqrt{h^2+k^2+l^2}}{\sin ({\theta }_i)}}$$

(1)

$$\alpha =2.8644+0.015\times X_{\mathrm{c}\text{-}\mathrm{bcc}}$$

(2)

where ${\alpha }_{\alpha }$ and $X_{\mathrm{c}\text{-}\mathrm{bcc}}$ are the lattice parameter (Å) and the carbon content (wt. %) of the bcc phase, respectively.

As detailed hereinafter, the approximate dislocation density in tested steels was systematically characterized and quantitatively analyzed using X-ray diffraction (XRD), with the modified Williamson–Hall (MWH) method adopted as the core analytical approach to enable an accurate assessment [27,28,29,30,31,32].

The volume fraction of particles V_f was calculated according to the McCall–Boyd method [33] as follows:

$$V_f=\left({\displaystyle \frac{1.4\pi }{6}}\right)\times \left({\displaystyle \frac{N{d}_{mean}^2}{A}}\right)$$

(3)

where N is the number of particles in the scanning area, d is the average size of particles, and A is the scanning area. In this work, several TEM morphologies of arbitrarily selected regions with dimensions of 12,750 × 12,750 nm were analyzed.

3. Experimental Results

3.1. Mechanical Property

The engineering stress–strain curves after testing with different Cu contents of untempered and 610 °C-tempered steels are shown in Figure 1a, and the corresponding strain-hardening rate and true strain curves are shown in Figure 1b. The strain-hardening rates of the specimens in the non-tempering state with different Cu contents all decreased with the increase in true strain. In the early stage of plastic deformation, the strain hardening rate of 0.8Cu without tempering is higher than that of 1.4Cu. With the increase in true strain, the difference in the non-tempered state gradually decreases. After tempering at 610 °C, the strain hardening rate between samples with 0.8Cu content increased, but with the increase in Cu content, the difference in values was not significant. In Figure 1c, as the content of Cu in the matrix increases, both the tensile strength and the yield strength also increase. This indicates that within the range of 0.8–1.4 for the Cu content, there is a positive correlation between the increase in strength and the Cu content. As the tempering temperature rises to 580 °C, its strength increases, but the impact is relatively the lowest at −40 °C, about 25 J. However, when the tempering temperature rises to 610 °C, although the strength decreases somewhat, at this temperature, the strength and toughness of Cu-alloyed steel reach their maximum, showing an excellent strength–toughness match (as shown in Figure 1d), which is 445 MPa at 1.1Cu content, and the impact value is approximately 105 J, satisfying the yield strength level of 420 MPa (yield strength grade).

3.2. Microstructure and Fractography

The SEM microstructures with different Cu contents under the condition of non-tempering and tempered at 610 °C are shown in Figure 2. As the Cu content increases, the microstructure is mainly composed of pearlite (P) + ferrite (F) + granular bainite (GB), and it is clearly observed that the content of GB islands increases in the untempered microstructure. At the same time, the content of pearlite decreases. This is reflected in the increase in yield strength under the non-tempering condition. As the tempering temperature rose to 610 °C, more carbide clusters appeared in the morphology, shown as the grayish–white part in Figure 2c,d. It can be reasonably inferred that these carbide clusters (CC) were formed via the spheroidization of pearlite and the decomposition of martensite/austenite (M/A) islands during tempering. Furthermore, by comparing and analyzing the “dark gray” and “gray” zones in microstructure morphologies, the results are presented in

Table 2. Phase proportion of the studied steel after being tempered at 610 °C. F: ferrite.

Fraction, %	0.8Cu, 610 °C	1.1Cu, 610 °C	1.4Cu, 610 °C
F	81.9	79.9	77.9
The remaining portion	18.1	20.1	22.1

. In the 0.8Cu sample, the F content is approximately 81.9% in the gray area. When the Cu content increases to 1.1 or even 1.4, the F content decreases to approximately 79.9% or 77.9%, respectively. Correspondingly, the “gray” portion increases with the increase in Cu content, being 18.1%, 20.1%, and 22.1%, respectively.

Furthermore, TEM morphologies following tempering at 610 °C were examined for samples with different Cu contents. In specimens with a Cu content ranging from 0.8 wt% to 1.4 wt%, particles of various sizes were observed, as shown in Figture 3. Combined with STEM elemental mapping analysis, these particles were confirmed to be Cu-rich precipitates. Nevertheless, the average size of Cu particles gradually increased with increasing Cu content. Following austenitization, in samples with a Cu content of 0.8–1.1 wt%, numerous Cu atoms are dissolved into the austenite lattice, rendering the matrix a Cu-bearing supersaturated solid solution (Figture 3a,c,e). With decreasing temperature during air cooling, the solubility of Cu in ferrite declines, placing the system in a thermodynamically unstable state and thereby promoting gradual Cu segregation and precipitation.

Tempering at 610 °C essentially falls within the over-aging regime. At this temperature, finer particles tend to re-dissolve, and Cu precipitates preferentially adopt an ellipsoidal or spherical morphology. Similarly, the number density of Cu particles increases significantly with increasing Cu content. To accurately quantify the number and size of these precipitates, statistical analyses were performed on 10–15 TEM images for each Cu content, covering both tempered and as-quenched (untempered) samples (Figure 3b,d,f).

Figure 4 shows the size distribution and volume fraction of Cu particles in the Cu-alloyed steel samples after non-tempering and tempering at 610 °C. Due to errors and other factors in the statistical process, there is a statistical deviation. However, it is reasonable to believe that the particle statistics are regular. The particles in the 0.8Cu sample under the normalizing state are mainly 11–20 nm. As the Cu content increases, the proportion of particles in this size range gradually decreases, and correspondingly, the number of particles with a diameter of 21–30 nm gradually increases, indicating the dynamic merging of Cu particles (Figure 4a). In addition, after being tempered at 610 °C, the number of particles with a diameter of 1–10 nm significantly increases, but still, with the increase in Cu content, Cu particles also merge, showing a relatively larger particle precipitation (Figure 4b). To further clarify the volume fraction of Cu precipitation, the Thermal-calc software (2021A) was used to calculate the volume fraction of Cu particles under different Cu contents, as shown in Figure 4c. Correspondingly, the average diameters of the Cu particles in these different Cu content samples are approximately 7.85 nm, 14.89 nm, and 14.52 nm without tempering, and approximately 13.54 nm, 9.86 nm, and 15.3 nm after tempering (Figure 4d). However, inevitably, the errors in this part of the results mainly come from the selection of TEM photos, the evaluation of the statistical process, etc.

Figure 5 shows the impact fracture morphology of the experimental steel with different Cu contents after tempering at 610 °C. The impact fracture surface consists of a fibrous zone and a shear lip zone, exhibiting typical ductile fracture characteristics. Zone 1 corresponds to the fibrous region with deep, large dimples, while Zone 2 with tear ridges represents the radial region. Clearly, the fibrous and shear lip zones absorb more energy than the radial zone. The promotion of ductile fracture is typically associated with the formation of tear ridges and dimples in the fibrous zone. In contrast, brittle fracture, characterized by cleavage planes and transgranular propagation, corresponds to poor low-temperature impact toughness.

Figure 6 illustrates the inverse pole figure (IPF) colored maps, the kernel average misorientation (KAM) maps, the band contrast (BC) maps and bainite micrographs with grain boundary misorientation distributions of 0.8Cu (Figure 6(a1)), 1.1Cu (Figure 6(b1)), 1.4Cu (Figure 6(c1)), and 0.8Cu-610 (Figure 6(d1)), 1.1Cu-610 (Figure 6(e1)), 1.4Cu-610 (Figure 6(f1)) samples, respectively. The KAM maps represent the accumulative plastic deformation and local strain distribution state by calculating the misorientation between the nearest two scanning points. In Figure 6(a3–f3), the black line delineates the HAGB, while the red line designates the LAGB. As discussed above, the microstructures of both the as-quenched (untempered) and 610 °C-tempered experimental steels consist of ferrite (F) and granular bainite (GB). Since it is well established that granular bainite possesses a higher dislocation density than ferrite, in the corresponding KAM maps, the blue regions correspond to ferrite with low dislocation density, whereas the green regions represent bainite with high dislocation density. According to the EBSD results about grain boundary misorientation distributions, the effective grain sizes are calculated as follows: 9.7 μm, 11.1 μm, 10.1 μm for 0.8Cu, 1.1Cu, 1.4Cu, and 9.2 μm, 11.1 μm, 9.9 μm for 0.8Cu-610, 1.1Cu-610, 1.4Cu-610, respectively, which are used for the calculation of strengthening mechanisms.

3.3. Dislocation Density

The dislocation density of 0.8Cu, 1.1Cu, and 1.4Cu samples under no tempering and tempering at 610 °C was calculated from the XRD profiles. Compared with the non-tempered samples, the dislocation densities of the 610 °C-tempered samples were all lower than those of the non-tempered samples. The dislocation densities are 4.13 × 10⁹, 5.32 × 10⁹, 3.33 × 10⁹ m² in the non-tempered condition, and 1.92 × 10⁹, 0.19 × 10⁹, 2.36 × 10⁹ m² after 610 °C tempering (Figure 7).

4. Discussion

4.1. Cu Precipitation and Microstructure Evolution

The cooling rate plays a crucial role in the formation of microstructure. During the slow normalizing cooling process, the austenite in Cu-alloyed steel undergoes a diffusion-controlled phase transformation. The proeutectoid ferrite nucleates at the austenite grain boundaries, expelling C atoms and enriching the Cu element in the remaining austenite. As the C-rich austenite continues to cool and approaches the eutectoid temperature, the untransformed pearlite undergoes a cooperative transformation. The slow cooling rate promotes the evolution of a near-equilibrium microstructure, resulting in pearlite with relatively coarse lamellar spacing. However, as the Cu content in steel increases, Cu, as an austenite-stabilizing element, significantly enhances the stability of austenite, causing the transformation of austenite to the aforementioned ferrite and pearlite phases to be markedly delayed under continuous cooling conditions. At a relatively low cooling rate, austenite cannot fully transform into ferrite and pearlite. Instead, some austenite undergoes a medium-temperature transformation within the interval between the pearlite and martensite transformation regions, ultimately forming granular bainite. Specifically, upon cooling into the bainitic transformation zone, austenite first precipitates carbon-enriched, island-like retained austenite or carbon-rich martensite/twinning martensite via local short-range carbon diffusion in the matrix [34]. Concurrently, Cu addition expands the austenite phase field and markedly impedes the long-range diffusion of Fe and C atoms, thereby restricting the full progression of high-temperature phase transformation [35]. This provides favorable kinetic conditions for the occurrence of bainitic transformation during subsequent cooling.

Further analysis shows that the higher the Cu content, the greater the supersaturation of Cu element, the larger the free-energy difference for precipitation; the precipitation driving force increases exponentially. Diffusion control is the key kinetic basis. Cu atoms diffuse and nucleate through defect channels such as vacancies, dislocations, and grain boundaries. A higher Cu content in the steel matrix gives rise to a much higher solute supersaturation, which substantially promotes both the nucleation rate and the subsequent growth rate of Cu-rich precipitates. Lattice defects such as vacancies, dislocations, and grain boundaries act as preferential heterogeneous nucleation sites and rapid diffusion pathways for Cu atoms, thereby serving as the core structural carriers for the cooperative nucleation and assembly of precipitate embryos [36]. Meanwhile, the morphological and structural evolution of Cu precipitates during growth is essentially governed by the dynamic equilibrium between interfacial energy and strain energy. The competition and mutual compensation between these two energetic contributions determine the critical transformation size, lattice stability of precipitates, and final crystal structure formed during coarsening, which in turn dominates the overall strengthening effect imparted by Cu precipitation [37]. Initially, the coherent BCC phase exhibits low interfacial energy but high strain energy. With increasing particle size, Cu-rich systems more readily surmount the associated energy barrier and transform toward a stable face-centered cubic (FCC) phase with lower strain energy, thereby establishing a balanced equilibrium between interfacial energy and strain energy.

Furthermore, the crystallographic characterization of Cu particles was carried out in the morphology of 1.1Cu after non-reheating treatment, in order to clarify the precipitation process of Cu particles, as shown in Figure 8. Figure 8a shows the typical Cu particle morphology at the boundary interface, and its facets are nearly in the edge-on direction. Two phases of ferrite and Cu particles are identified with an OR of ${\left(\stackrel{-}{2} 2 0\right)}_{\alpha }//{\left(2 \stackrel{-}{2} 0\right)}_{Cu}$ in the ${[1 1 1]}_{\mathsf{\alpha }}// {[1 1 1]}_{\mathrm{Cu}}$ direction of the incident beam, based on the HRTEM of the particle (Figure 8b), its FFT pattern (Figure 8c), and Figure 8e. The dominant habit planes (facets F1 and F2, as presented in Figure 8a) were formed during the precipitation reaction within the ferrite matrix. These distinct orientation relationships (OR) indicate that the near-coincidence site (NCS) lattice model is suitable for analyzing the interfacial structure between ferrite and copper precipitates (Figure 8d). To achieve a reliable description of such an interfacial structure, it is essential to specify the structural element that determines its periodicity. The two-dimensional NCS distribution of the two phases in real space is partially magnified in Figure 8f and exhibits a regular periodic arrangement as illustrated in Figure 8g. Crystallographic planes featuring a high planar density of periodically arranged NCS clusters act as preferential interfaces for the phase transformation from the α-ferrite matrix to the newly formed Cu precipitates, which are in good agreement with the F1 and F2 facets observed experimentally.

Accordingly, the microstructure of the habit plane is directly correlated with its macroscopic characteristics. It can be reasonably inferred that the directional growth selectivity of carbides is governed by multiple factors, including growth kinetics, and this growth mode acts primarily to minimize the overall interfacial energy.

4.2. Strengthening Mechanism Analysis Cu-Alloyed Steel Influenced by Cu Content and Tempering

The yield strength of the investigated steel is governed by its multiscale microstructure, encompassing solute elements, matrix morphology, dislocation density, and precipitated phases, among other microstructural features. On this basis, the yield stress can be quantitatively decomposed into the sum of four individual contributions:

$${\sigma }_{\mathrm{y}}={\sigma }_0+{\sigma }_{ss}+{\sigma }_{\mathrm{gb}}+{\sigma }_{\mathrm{p}}+{\sigma }_{\mathrm{d}}$$

(4)

where ${\sigma }_0$ is the friction stress of a pure iron single crystal, which is about 48 MPa [38], ${\sigma }_{ss}$, ${\sigma }_{\mathrm{gb}}$, ${\sigma }_{\mathrm{p}}$ and ${\sigma }_{\mathrm{d}}$ are the strengthening contributions of solid solution, grain boundary, precipitation, and dislocation, respectively. The calculated method is as follows [39,40,41,42]:

$${\sigma }_{ss}=4570[C]+37[Mn]+83[Si]+38[C\mathrm{u}]-30[Cr]$$

(5)

$${\sigma }_{\mathrm{gb}}=k\times d^{-1/2}$$

(6)

$${\sigma }_{\mathrm{p}}=8.955\times {10}^3\times \left({\displaystyle \frac{V_{\mathrm{f}} 1/2}{dp}}\right)\mathrm{l}\mathrm{n}\left(2.417dp\right)$$

(7)

$${\sigma }_{\mathrm{d}}=\alpha Gb\times \sqrt{\rho }$$

(8)

where [i] is the mass percentage of alloying elements (i = C, Mn, Si, Ni, Cu, and Cr in wt.%). For the solid solution, the carbon content of ferrite in the test sample is 0.0008 wt%. k is the Hall–Petch coefficient with a value of 9.33 MPa mm^1/2 [36]; d is effective grain size (μm); b is a Burgers vector with a value of 0.248 nm, f is the volume fraction of the Cu precipitates; d_p is the average diameter of the precipitates (nm); α is 0.435, G is 83,000 MPa, and ρ is dislocation density. The calculated σ_p values are 89.7 MPa, 96.9 MPa, 153.1 MPa for non-tempered samples, and 125.1 MPa, 184.4 MPa, 209.0 MPa for samples tempered at 610 °C, respectively.

As illustrated in Figure 9, the contributions of individual strengthening mechanisms to the yield strength of the experimental steel were quantitatively resolved, with the corresponding detailed parameters listed in

Table 3. Contribution of individual strengthening mechanisms.

	σ0/MPa	σss/MPa	σgb/MPa	σd/MPa	σp/MPa	σy	Measured
0.8Cu	48	76.0	92.5	57.5	87.9	361.9	355
1.1Cu	48	83.6	94.8	65.3	96.9	388.6	381
1.4Cu	48	94.2	88.2	32.7	153.1	416.2	415
0.8Cu-610	48	56.4	97.3	39.2	125.1	366.0	371
1.1Cu-610	48	59.6	91.9	15	184.4	398.9	412
1.4Cu-610	48	63.2	93.8	17	209.0	431.1	439

. The theoretically calculated values are in good agreement with the experimentally measured results, which verifies the reliability of the adopted strengthening mechanism analysis. Precipitation strengthening is recognized as the dominant strengthening mechanism in the present steel and is responsible for the significant differences in strengthening behavior under various Cu contents. This phenomenon is mainly attributed to the two-stage precipitation process of Cu particles during the initial slow cooling to room temperature and the subsequent tempering treatment.

5. Conclusions

The conclusions of this study highlight the significant progress made in improving the strength–toughness matching cast steel for nodes, specifically:

(1)

Experimental cast steel with a mostly ferritic matrix was prepared by normalizing and tempering. The strengthening method, mainly based on Cu precipitation, was proposed, which effectively promoted the cast steel to have good toughness reserve while meeting the strength requirements.

(2)

The precipitated phase in the experimental steel is mainly Cu particles, presenting spherical or ellipsoidal shapes. During the normalizing process, the precipitation amount of these precipitated phases increases with the increase in Cu element addition content in the alloy. During the subsequent tempering process, precipitation and growth are the main factors, which are manifested as a limited increase in strength.

(3)

The addition of Cu enhances the quenching toughness during normalizing, which is manifested by the appearance of granular bainite in the microstructure. As the content of Cu increases, the amount of granular bainite also increases. After 610 °C tempering, this structure decomposes, ensuring excellent strength and toughness matching.