Search Results (1,672)

Nickel-based single-crystal superalloys are key materials for manufacturing aero-engine turbine blades. Different grain boundaries are inevitably formed during the production of superalloys and weaken the fatigue performance of the alloys. Systematic exploration of the effect of grain boundary misorientation (GBM) on the fatigue properties of superalloys is of great significance. Available research cannot fully illustrate the influence of GBM on the high-cycle fatigue (HCF) damage mechanism of superalloys, especially its coupling with inherent casting defects. In this study, bicrystal specimens with misorientations of 4°, 8° and 12° were fabricated from a second-generation nickel-based single-crystal superalloy. The influence mechanism of misorientation variation on HCF performance was systematically investigated. The test results show that the HCF life of the alloy decreases obviously as GBM rises from 4° to 8° and then declines slowly. Fracture analysis indicates that fatigue damage is closely associated with GBM and casting defects. A 4° grain boundary promotes coordinated deformation and inhibits cracking, whereas misorientations over 8° cause dislocation pile-up and speed up crack propagation. Based on the significant effects of GBM and casting defects on fatigue damage behavior, as well as the analysis of the two key parameters in the Basquin model, a linear correlation is established between the fatigue strength coefficient (σ′_f) and misorientation; a coupling relationship is constructed among the fatigue strength exponent (b), misorientation, and defect size. Prediction results confirm that the model achieves higher accuracy by incorporating casting defect parameters. Full article

To investigate the corrosion resistance and deterioration mechanism of cast-in situ concrete incorporating iron ore tailings aggregate (IOT), specimens with IOT replacement ratios of 0%, 30%, and 50% were exposed to distilled water, endogenous Cl⁻-SO₄²⁻ corrosion, exogenous Mg²⁺-SO₄²⁻ corrosion, and endogenous-exogenous coupled corrosion. The evolution of mass, size, compressive strength, and flexural strength was evaluated, while Nuclear Magnetic Resonance (NMR), Scanning Electron Microscope-Energy Dispersive Spectroscopy (SEM-EDS), X-ray Diffraction (XRD), and Thermogravimetric Analysis/Derivative Thermogravimetry (TG/DTG) were used to characterize pore structure and phase transformation. Results show that distilled water causes limited variation, whereas exogenous and coupled corrosion accelerate product accumulation, size expansion, pore coarsening, and strength degradation. Under exogenous Mg²⁺-SO₄²⁻ corrosion, the peak compressive strengths of specimens with 0%, 30%, and 50% IOT reach 43.30 MPa, 45.60 MPa, and 46.93 MPa, respectively, with the 50% IOT specimen showing an 8.38% increase compared with the specimen without IOT. TG/DTG results show that the Ca(OH)₂ related mass loss decreases from 5.42% under distilled water immersion to 4.37% under exogenous Mg²⁺-SO₄²⁻ corrosion, confirming calcium consumption during sulfate–magnesium attack. Microstructural characterization reveals that sulfate reaction, chloride binding, and Mg²⁺-induced decalcification jointly promote the formation of gypsum, ettringite, Friedel’s salt, magnesium silicate hydrate (M-S-H), and magnesium-associated corrosion products. Overall, 30% IOT provides better pore refinement and mechanical stability under endogenous and exogenous corrosion, whereas 50% IOT improves residual skeleton support under coupled corrosion. These findings provide guidance for durability design and sustainable utilization of IOT aggregate in cast-in situ concrete. Full article

Polyhydroxyalkanoates (PHAs) are bio-based, biodegradable polyesters increasingly explored as sustainable biomaterials for regenerative medicine. This review summarizes recent advances in PHA-based bone substitute materials, highlighting their properties, fabrication methods, and biological performance. PHAs combine biocompatibility, tunable mechanical behavior, and degradation into non-toxic metabolites, while copolymerization and monomer selection modulate the stiffness, crystallinity, and resorption rate. Processing techniques such as solvent casting, electrospinning, and additive manufacturing allow the production of porous architectures that mimic bone extracellular matrix. Electrospinning is particularly suitable for nanoscale fibrous matrices, whereas 3D printing enables patient-specific scaffolds with controlled geometry and interconnected porosity. Scaffold performance can be further improved through the incorporation of osteoconductive fillers, including hydroxyapatite, β-tricalcium phosphate, bioactive glasses, graphene oxide, and carbon nanotubes, as well as through drug-delivery and pro-angiogenic functionalization. In vitro and in vivo studies consistently report favorable cytocompatibility, enhanced osteogenic differentiation, vascularization, and effective repair of bone defects in animal models. However, clinical translation remains limited by production costs, variability in polymer quality, thermal processing constraints, and regulatory challenges. Future progress will rely on more efficient biosynthesis, medical-grade purification, multifunctional scaffold design, and stronger collaboration between academia, industry, and clinicians to unlock the full potential of PHAs in regenerative bone therapies. Full article

An integrated building information model (BIM) was constructed based on embodied carbon emissions (CEs) and a cost assessment framework to evaluate the environmental and economic performance of prefabricated buildings (PBs) and traditional cast in situ buildings (TBs) during the materialization stage. BIMs and carbon emission factor (CEF) methods were combined to quantify material consumption, embodied CEs, and construction costs under identical building conditions. An eight-story residential shear wall structure was selected as a case study, and carbon was analyzed across different stages. Sensitivity and uncertainty analyses were incorporated to evaluate the robustness of the accounting results under different transportation, electricity emission, and regional production scenarios. The results indicated that prefabricated construction exhibited lower embodied carbon emissions and improved economic performance compared with traditional cast in situ construction. The material production stage was identified as the dominant carbon source, while electricity-related emission factors had the strongest influence on the accounting results. The proposed framework provides a transferable methodological pathway for low-carbon building assessment and sustainable decision making in prefabricated residential construction. Full article

Concrete construction is associated with high environmental impact and geometric limitations imposed by conventional formwork, which has led to growing interest in combining structural optimization with robotic fabrication. In this study, structural optimization refers to computational methods such as topology optimization, shape optimization, and form finding that aim to improve material efficiency and load-bearing performance by modifying the geometry of structural elements. This systematic review investigates how these optimization approaches are translated into fabrication-aware design workflows for robotic concrete construction. Following a PRISMA-based methodology, 90 peer-reviewed studies published between 2015 and 2025 were analyzed. The review focuses on fabrication routes including (i) 3D concrete printing, (ii) 3D-printed formwork, (iii) shotcrete-based additive manufacturing, and (iv) controlled casting systems, and examines how each route constrains geometry representation, design decisions, toolpath generation, and robotic execution. The review analyzes design-to-fabrication workflows that link optimized structural geometry to production logic and process control. Key findings indicate that incorporating fabrication constraints at early design stages can support buildability and potential material efficiency, while reinforcement integration and quality control remain critical challenges for structural reliability. The review also highlights the increasing role of in situ sensing and feedback-driven automation in improving process stability. Overall, the study clarifies current practices, limitations, and emerging directions for integrating structural optimization with robotic concrete fabrication. Full article

Koji production is a critical process that determines the flavor and quality of the final soy sauce product. However, the complex mechanisms underlying microbial metabolism and the evolution of the physicochemical environment still require further analysis. This study focuses on three parallel koji rooms in an industrialized koji fermentation process. This work tracked the dynamics of physicochemical indices, volatile flavor compounds, and microbial communities over a full 40 h cycle. Data integration and correlation analysis elucidated the close linkage between the microbial community, the fermentation environment, and flavor formation. Koji moisture declined gradually, with faster losses at later fermentation stages. This physiological dehydration arose from microbial metabolic heat, forced aeration and structural loosening of koji, not simple physical evaporation. System pH displayed a typical U-shaped trend across fermentation. Values dropped early, most likely driven by accumulating organic acids, before rising from mid to late fermentation. This pH rebound was tentatively attributed to ammonia release from proteolytic breakdown, which may neutralize acidic compounds. These observations cast doubt on the conventional assumption that organic acid levels may be reliably estimated solely from pH measurements. Physicochemical analysis showed continuous accumulation of amino acid nitrogen (0.6–0.9 g/100 g) and total acidity throughout fermentation. By contrast, reducing sugar concentrations differed across individual koji rooms, presumably owing to divergent microbial adaptation in early fermentation. A total of 77 common compounds were identified, among which 13 key odor-active compounds with OAV ≥ 1, such as 4-vinylguaiacol and 3-methylbutyraldehyde, constitute the characteristic flavor profile of soy sauce starter culture. High-throughput sequencing uncovered a distinct ecological pattern: eukaryotic communities, dominated by Aspergillus oryzae, converged under controlled regulation. While prokaryotic communities differentiated dynamically, driven by spatial heterogeneity in the semi-open fermentation environment. Spearman correlation analysis further indicated potential functional partitioning: high-abundance taxa (e.g., Aspergillus oryzae, Weissella) were predominantly associated with macromolecular substrate degradation, whereas rare low-abundance taxa (e.g., Alternaria) displayed significant correlations with the biosynthesis of key characteristic flavor compounds. This study clarifies the synergistic regulatory mechanisms linking physicochemical conditions, microbial metabolism, and flavor precursor formation during industrial koji production. The findings establish a scientific foundation for optimizing process parameters and achieving standardized quality control in soy sauce manufacturing. Full article

A 700 m pilot-scale cast iron pipeline reactor was operated for 120 days to investigate corrosion-stage evolution under reclaimed-water conveyance conditions. Sampling points were arranged at 50, 250, 450, and 650 m, and water-quality monitoring, coupon weight-loss tests, scanning electron microscopy (SEM), and high-throughput 16S rRNA sequencing were combined to characterize corrosion-rate variation, corrosion-product morphology, and microbial community succession. During transport, NH₄⁺ generally decreased while NO₃⁻ increased, indicating nitrification-related nitrogen transformation under aerobic conditions; meanwhile, PO₄³⁻ declined and DOC fluctuated, reflecting coupled physicochemical and biological processes. SEM observations showed a transition from loose porous deposits to relatively compact layered corrosion products, followed by local deterioration and renewed porous structures in the later period. The corrosion rate followed an increase–decrease–re-increase pattern rather than a monotonic trend. Therefore, corrosion acceleration (CA = dc/dt) was introduced as an auxiliary diagnostic indicator to identify whether corrosion activity was increasing, decreasing, or temporarily stabilizing. Microbial community analysis showed stage-associated variation in biofilm and nitrogen-transformation-related taxa, supporting the interpretation that corrosion evolution was jointly affected by water-quality change, corrosion-product development, and microbial succession. Overall, the combined interpretation of corrosion rate, CA, water quality, SEM morphology, and microbial succession provides a more informative basis for diagnosing corrosion-stage transitions in reclaimed-water cast iron pipelines. From a sustainability perspective, this diagnostic framework can support long-term operation, maintenance planning, and risk monitoring of urban reclaimed-water distribution infrastructure, thereby improving pipeline durability, reducing leakage and maintenance risks, and enhancing the reliability of reclaimed-water reuse systems. Full article

In CSP thin slab casting, high casting speeds promote excessive columnar grain growth, leading to low equiaxed grain ratios in non-oriented silicon steel and resulting in wrinkling defects. This study employs a box-type electromagnetic stirrer (B-EMS) to address this issue. A multiphysics model was established, in which grain transformation and its associated effects were neglected. The effects of B-EMS on the flow of molten steel, temperature distribution and evolution of solidified shell were analyzed, and industrial trials were conducted to verify the influence of B-EMS on grains. Results show that B-EMS generates asymmetric magnetic fields and electromagnetic forces, driving width-directional flow that enhances scouring of the solidification front. Compared with the experiment and simulation, the error in the magnetic field excited by B-EMS is within 5%. Under 800 A current, narrow-face center shell thickness increased from 22.88 mm (no stirring) to 23.62 mm (starting side) and 23.21 mm (pushing side). The central mushy zone area and liquid fraction decreased significantly, indicating accelerated solidification and more uniform shell growth. Industrial trials confirmed that the equiaxed grain ratio increased to approximately 30%, with significantly improved internal strand quality. This study demonstrates B-EMS’s metallurgical effects in regulating solidification structure, optimizing shell morphology, and improving continuous casting slab quality. The numerical simulation can be correlated with the industrial production process to better guide manufacturing practices. Full article

We present S2VDT, a two-party secure vertical decision tree framework built on a suite of matrix-level secure operators, including matrix multiplication, the Hadamard product, reciprocal, and vector comparison. These operators, constructed from additive secret sharing and masked matrices, provide two core advantages. First, inherent parallelism: by casting Gini impurity evaluation and split selection into matrix form, all candidate splits are evaluated simultaneously within a constant number of communication rounds, eliminating the per-split sequential interactions of prior schemes. Second, composable security: each operator is proven secure under the semihonest model via the universal composability framework, and the full training protocol achieves bounded privacy guarantees without relying on homomorphic encryption or an online trusted third party. Experiments on three real-world UCI datasets show that S2VDT matches non-private accuracy with negligible model-level precision loss while reducing communication overhead by $2.5\times$–$7.1\times$ and peak memory consumption by $19\times$–$68\times$ over Pivot. Full article

Hydrogenation reactor shells are safety-critical thick-section pressure-bearing components in petrochemical hydroprocessing equipment. Long-term exposure to elevated temperature, high pressure, and hydrogen-bearing media requires not only adequate strength, but also toughness, tempering stability, hydrogen-damage resistance, and through-thickness property uniformity. 12Cr2Mo1V steel, a Chinese Cr-Mo-V reactor steel closely related to vanadium-modified 2.25Cr-1Mo-0.25V steels, is widely used for large-shell forgings because its alloy design supports bainitic transformation, carbide stability, and elevated-temperature performance. This review critically synthesizes studies on 12Cr2Mo1V shell forgings, related Cr-Mo-V reactor steels, and heavy free-forged products. The discussion is organized around alloy design, ingot-derived defect inheritance, defect closure during free forging, bainite–grain–carbide evolution during forging and heat treatment, and the resulting strength, toughness, and hydrogen-service performance. Particular emphasis is placed on the process–defect–microstructure–property linkage in super-thick sections. The review shows that free forging is not merely a forming route, but a decisive metallurgical operation for densification, strain penetration, and precursor-structure conditioning. Future work should integrate casting, free forging, and heat treatment with multiscale characterization and data-enhanced predictive quality control. To further reduce descriptive comparison, this review summarizes standardized quantitative indicators for evaluating forging-route design, heat-treatment response, and prediction-method reliability. Full article

Driven by the increasing demand for material efficiency and reduced environmental impact in automotive foundry production, this study addresses the industrial problem of determining the allowable content of internal return material in high-pressure die casting of EN AC-47100 aluminum alloy while maintaining the required quality of automotive castings. The aim was to determine how return material content and selected process parameters affect ultimate tensile strength, Brinell hardness, and internal porosity. In the regression model with interaction terms, high explanatory ability was achieved for ultimate tensile strength and internal porosity, with R² values of 0.920 and 0.744, respectively. A full factorial experiment was performed using five levels of return material content, five levels of plunger velocity, and three levels of intensification pressure, resulting in 75 experimental settings. The data were analyzed using ANOVA, regression models with interaction terms, response surface methodology, and constrained multi-criteria optimization. Return material content was identified as the dominant factor affecting tensile strength and porosity. Increasing its proportion caused a systematic decrease in strength and an increase in internal porosity. Plunger velocity acted as a modifying factor, partially reducing porosity and improving strength response. The optimization showed that the maximum usable return material content was mainly limited by internal porosity. Under the most permissive scenario, a return material content of approximately 33.5% was achievable. The proposed scenario-based approach supports the selection of acceptable process settings that balance casting quality with return material utilization and provides a practical basis for increasing material circularity in industrial HPDC production without exceeding defined quality limits. Full article

This study introduces a greentelligent scheduling approach to enhance energy efficiency in the aluminum extrusions casting workshop (ACW), addressing the high energy consumption and low efficiency inherent in these processes. Global energy consumption is significantly attributed to the manufacturing sector, with aluminum extrusions being one of the most common products, particularly in energy-intensive casting workshops. Given the considerable demand and potential for energy savings in aluminum extrusions manufacturing (AEM), this study proposes an intelligent scheduling approach to minimize non-processing energy consumption (NPE) while also reducing average completion time (ACT). Utilizing industrial internet of things (IIoT) technologies, practical production data is acquired to support a bi-objective scheduling model. An empirical knowledge-based evolution algorithm (EBA) with an improvement strategy (SO-EBA) is developed to efficiently solve this complex, NP-hard problem. A production case in an ACW demonstrates the effectiveness of the SO-EBA. Compared to benchmark algorithms, the SO-EBA achieves significant reductions in optimal NPE by more than 39.41%, while maintaining production efficiency. This work advances greentelligent manufacturing by integrating IIoT and intelligent algorithms, offering a scalable solution for sustainable production in energy-intensive industries. Full article

Selecting a compact subgraph of a document graph while maximising a learned coherence function, subject to flow conservation and temporal ordering, is important in storyline detection, event threading, and Narrative Map extraction. Existing Narrative Map methods either recover a single optimal path (a Narrative Trail) or solve a linear program with an output size which grows with graph density (Narrative Maps). We propose a hybrid classical–quantum pipeline that casts the problem as a Quadratic Unconstrained Binary Optimisation (QUBO) problem and solves it both with the Quantum Approximate Optimisation Algorithm (QAOA) and with off-the-shelf classical QUBO solvers (simulated annealing, Tabu search) on the same Hamiltonian; this approach uses a classical mean field active space reduction and Matrix Product State tensor network simulation to scale beyond 16 qubits. We evaluate node- and edge-level qubit encodings under a range of QAOA circuit variants (transverse field and XY mixers; classical warm-start deeper circuits) on a 418-document news corpus across four graph densities and ten endpoint pairs, and audit their reproducibility across optimiser seeds. The QUBO formulations—whether solved by QAOA or by classical QUBO solvers on the same Hamiltonian—produce maps averaging $4.7$–$9.0$ nodes versus $26.6$ for Narrative Maps ($p<{10}^{-7}$) and they are far more focused on their main storyline (main path fraction $0.61$–$0.99$ versus $0.20$). The Hamming-weight-preserving XY mixer goes the furthest: the node-level XY mixer variant produces the most compact ($4.7$ nodes) and most spine-focused ($0.99$ main path fraction) maps of any method tested, and a multi-seed audit identifies it as the most reproducible of the eight QAOA variants we compared. Main path coherence is on par with Narrative Maps’ and $0.031$–$0.072$ below the bottleneck-optimising baselines—Narrative Trails ($0.770$) and Iterative Maximin ($0.758$). These results position QAOA not as a uniformly stronger alternative but as a distinct trade-off region favouring compactness and spine focus over raw bottleneck coherence and corpus topic breadth. Full article

Aluminum alloy A356 (Al-7Si-0.3Mg) is widely employed in automotive structural components due to its favorable strength-to-weight ratio, yet its mechanical performance is highly sensitive to T6 heat-treatment processes. Conventional heat-treatment schedules are typically based on uniform, empirically derived parameters and fail to consider variations in component size, geometry, or thermal mass. Consequently, applying a single schedule across all component sizes often leads to inconsistent microstructural development, energy inefficiency, and elevated scrap rates. Smaller components tend to be over-processed, while larger components may be under-processed, both resulting in suboptimal mechanical properties and increased production costs. To overcome these limitations, this study presents a scalable heat-treatment optimization framework that integrates physics-based thermal simulations with machine learning techniques. The framework combines a transient thermal simulator with Long Short-Term Memory (LSTM) networks to predict sample temperature evolution, Random Forest regressors to estimate mechanical properties such as yield strength, hardness, and modulus of toughness, and Bayesian optimization to generate size-dependent, property-compliant heat-treatment schedules. Unlike traditional methods, this approach dynamically adjusts furnace parameters to individual component characteristics, optimizing both processing time and energy consumption while minimizing scrap. Application of the framework to components ranging from 0.5 to 10 kg demonstrates internally consistent simulation-based predictions of temperature profiles, phase-fraction evolution, and mechanical-property trends within the assumed modelling framework. Optimized schedules achieved 15–25% reductions in cycle time while maintaining properties within T6 specifications. These findings underscore the potential of AI-assisted heat-treatment optimization to enhance energy efficiency, reduce material waste, and improve the consistency of mechanical performance in automotive casting operations. Full article

Using industrial by-product lithium slag (LS) as a raw material for ultra-high performance concrete (UHPC) is an important way to achieve low-carbon prefabricated structures. However, existing studies lack a constitutive model for LS-UHPC and its application in prefabricated beam connection nodes. To fill this gap, this paper first established a tensile-compressive constitutive model for LS-UHPC through mechanical tests; then it was embedded into the finite element model to simulate the bending performance of the connection nodes of the post-cast LS-UHPC prefabricated beams and verified by the test results. Finally, parameter analysis is carried out. The results show that moderately increasing the diameter of longitudinal reinforcement can significantly improve the flexural bearing capacity of the connection node, but when the diameter exceeds 18 mm and HRB500 high-strength steel bars are used, the node exhibits over-reinforced failure characteristics; increasing the strength grade of ordinary concrete has a limited effect on the improvement of flexural bearing capacity (<5%). This study clarified the mechanical constitutive relationship of LS-UHPC, revealed the failure mechanism and bearing capacity evolution law of its prefabricated connection nodes under parameter changes, and provided a theoretical basis and design suggestions for the application of low-carbon lithium slag UHPC in prefabricated assembly structures. Full article