The failure and stability of high arch dams under coupled actions of thermal-humidity-chemical conditions is an important research issue. The scaled model test is reliable to reveal the failure process and stability of arch dam, whilst 3D-DIC is a powerful tool to synchronously visualize and quantify the full-field deformation and micro-cracks. The synergistic work of these two methods is anticipated to solve the failure process and mechanism of high arch dam under environmental acts. Therefore, the artificial simulated environment (ASE) of the dam site was designed by the theory of micro-environment response in concrete. The overloading tests were carried out on the arch dam models treated by 0, 150 and 300 cycles of ASE. The failure modes and mechanism of high arch dam under environmental actions were elaborated by the visualized cracks results and quantified analysis of arch-ring interaction based on full field-deformation of 3D-DIC. The stability safety factors for the crack initiation, the nonlinear deformation (including prominent arching action), and the ultimate bearing capacity were identified. A theoretical model of ultimate bearing capacity for high arch dams under coupled environmental acts was proposed and validated. This study is valuable for the long-term safety of high arch dams under actual environmental actions.

Rubberized concrete exhibits excellent resistance to abrasion and provides a value-added method for recycling waste tires, thus demonstrating significant application potential in hydraulic engineering. To systematically study its fracture performance, this study used three-point bending beam specimens with span-depth ratios of 2.5, 3, 3.5, and 4 to characterize the fracture behavior of rubber concrete. The digital image correlation method was used to obtain full-field strain and displacement data on the specimen surfaces, enabling the observation of crack propagation paths. Subsequently, the fracture parameters of rubberized concrete beams with different span-depth ratios were calculated. The relationship between initial fracture toughness and span-depth ratio was established. The results indicate that the predominant fracture mode of rubberized concrete is Mode I fracture. The fracture performance of rubberized concrete is significantly affected by the span-depth ratio. As the span-depth ratio increases, the permissible damage scale decreases, the initial fracture toughness increases gradually, while the unstable fracture toughness decreases and gradually approaches a stable value. Furthermore, the ductility index increases significantly, indicating that an increase in the span-depth ratio effectively reduces the brittleness of rubberized concrete and enhances its toughness. These findings provide theoretical support and experimental evidence for the application of rubberized concrete in hydraulic engineering.

After closure, high arch dams often exhibit a noticeable temperature rise that significantly affects their stress state. This rise is driven by both environmental heat transfer and residual hydration heat of concrete, yet the dominant cause remains under debate. Using temperature monitoring data from the Baihetan arch dam, this study examines the evolution, causes, and structural effects of this process. By October 2024, the Baihetan dam shows a temperature rise of 4.5-9 degrees C. A detailed analysis reveals a 3-4 degrees C temperature gradient across the dam thickness at closure within the placement blocks. Previous studies assumed a uniform closure temperature field, which results in a systematic overestimation of residual hydration heat. On this basis, a Bayesian optimization-based inversion framework is employed to refine the estimation of residual hydration heat, yielding a value of approximately 2.5-3.0 degrees C. Using a factor-separation approach, the relative contributions of the influencing factors are quantified, showing that environmental effects contribute approximately 60% of the temperature rise, whereas residual hydration heat contributes around 40%. The temperature rise causes upstream deformation and induces local tensile stresses of 0.1-0.4 MPa. These findings offer quantitative insights into the temperature-rise mechanism and support the structural safety assessment of high arch dams.

Concrete placement scheduling in high arch dam construction is a long-horizon decision-making problem with complex spatiotemporal constraints and operational uncertainty. Existing scheduling optimization approaches mainly focus on pre-construction planning and often exhibit insufficient robustness. To address this challenge, this paper proposes a neuroevolution-based approach for dynamic optimization. A hybrid construction simulation environment integrating Discrete Event Simulation and Agent-Based Modeling is developed to evaluate scheduling performance. Within this environment, the Covariance Matrix Adaptation Evolution Strategy is used to evolve a decision neural network. The network dynamically scores feasible dam sections at each step to generate adaptive placement decisions. A case study of a high arch dam in Southwest China showed that the proposed approach outperformed the human-experience benchmark, Genetic Algorithms, and Proximal Policy Optimization. It reduced the average duration by 16.54 days relative to the human-experience benchmark and achieved the shortest duration and greatest stability among all compared methods.

This study develops and validates an integrated predictive framework for fracture failure assessment and fracture parameter evaluation of the Baihetan arch dam concrete. A four-season wedge-splitting test program was conducted on specimens cast with full-graded and wet-sieved concretes and naturally cured before testing at designated ages, covering the influences of specimen size, crack-to-depth ratio, age, and curing temperature-humidity history. The initial cracking and unstable fracture toughness values together with the fracture energy were determined, providing an experimental database for calibration and verification. The proposed framework synthesizes the Boundary Effect Model (BEM) with a maturity-based equivalent age to predict the initial cracking and peak loads, and employs the Fracture Extreme Theory (FET) to evaluate the corresponding fracture toughness values, comprehensively accounting for specimen size, crack ratio, curing temperature-humidity history, and concrete age. The material parameters were calibrated using the winter-cast specimens, which provided the most complete coverage of equivalent ages for regression of age-dependent development equations, and the framework was verified using data from the other seasons. The proposed framework demonstrated reliable predictive capability for fracture failure loads and fracture toughness of both concretes within the tested parameter range. Furthermore, two complementary conversion methods were developed to estimate the fracture toughness of full-graded concrete from wet-sieved test results, including a direct experimental conversion based on stable fracture parameters measured from large-size specimens and a prediction-based conversion using age-dependent development equations. These approaches provide a practical basis for fracture parameter conversion and fracture safety evaluation in dam engineering applications.

The stress and deformation analysis of concrete gravity dams is a core component of evaluating the structural safety of dam bodies. To obtain accurate and efficient solutions for the stress-deformation fields of gravity dams and fast inversion of material parameter, based on physics-informed neural networks (PINNs), we develop a residual minimization-based PINN model and a potential energy minimization-based EPINN model specifically targeted at gravity dams, which are grounded in the elasticity theory of solid mechanics. Through various case studies involving gravity dams, the computational accuracy and efficiency of different PINN models are compared. The results show the following: (1) The EPINN model demonstrates superior solving capability and computational efficiency-it is approximately 20 times faster than the PINN model-when dealing with complex geometries and boundary conditions. Conversely, the PINN model achieves higher computational accuracy for simpler geometries, with its precision being approximately twice that of the EPINN model. (2) Both models exhibit strong capabilities in material parameter inversion. In particular, the PINN model achieves accurate inversion of material properties via extremely limited data samples, with errors of only 0.46 % for the elastic modulus E and 2.32 % for Poisson's ratio mu. (3) The convergence performance of PINNs is influenced by factors such as the number of hidden layers, the number of neurons, and the test displacement functions. Overall, PINNs serve as a machine learning method that enables the direct construction of mechanistic models for gravity dams, contributing to the rapid and intelligent assessment of dam structural safety.

In arch dam engineering, transverse joint apertures often fail to meet grouting requirements due to limited understanding and consideration of joint interfacial tensile strength. Before opening, the transverse joint is essentially the interface between new and old concrete. This study experimentally investigated the effects of four key factors-curing temperature of the old concrete, casting interval, age of the new concrete, and curing temperature of the composite specimen-on the interfacial splitting and direct tensile strengths of new-to-old low-heat Portland cement concrete (LHPC-C) composite specimens using an orthogonal design, followed by analysis of variance (ANOVA). The results show that the curing temperature of the composite specimen and the age of the new concrete have highly significant influence (P < 0.001), whereas the casting interval and the curing temperature of the old concrete have no significant influence. Maturity-based predictive models for estimating the development of interfacial splitting and direct tensile strengths were developed with coefficients of determination (R-2) of 0.96 for both, and validated, achieving mean absolute percentage errors (MAPEs) of 4.15 % for splitting tensile strength and 1.02 % for direct tensile strength. To assess engineering applicability, the models were applied to predict interfacial splitting tensile strength under time-varying curing temperature histories and the opening temperatures of transverse joints in a certain arch dam, with relative errors below 5 % and 7 %, respectively. These results demonstrate that the proposed models accurately describe interfacial tensile strength development in response to variations in key influencing factors, and are applicable to engineering practice.

Thermal stress control is crucial for massive concrete structures during construction. The cooling strategies directly determine the safety of structures, material quality, construction efficiency, and project cost. However, precise spatiotemporal thermal stress regulation and management are difficult to achieve due to the lack of balanced discriminant criteria and multi-objective optimization methods for the selection of traditional strategies. Therefore, an intelligent optimization method for thermal stress management strategy in massive concrete structures, considering the balance of safety, quality, efficiency, and cost (SEQC-TSOM), is proposed. Initially, a Thermal Stress Simulation Mechanism Model (TSSM) is constructed to accurately evaluate the structural state throughout the entire process. Subsequently, a mechanism data-driven surrogate model (MD-SM) is constructed to quickly evaluate the structural response under different cooling strategies. Furthermore, a multi-objective intelligent optimization model and a multi-criteria decision-making model are proposed to filter the intelligent optimal strategy from the Pareto solution set. Finally, a case study based on the Baihetan arch dam project is conducted, and the results show that the safety, quality, efficiency, and cost (SEQC)-balanced strategy increases safety by 42%, improves cooling efficiency by 36%, and reduces cooling costs by 20.6% compared with traditional strategies.

The Wudongde arch dam is currently the thinnest 300-meter-class super-high arch dam in the world, and the risk of concrete cracking is a critical concern during its construction and operation. In this study, wedge-splitting fracture tests were conducted on full-graded and wet-sieved concrete specimens cast at the dam construction site, with varying test ages, specimen sizes, and crack lengths. A quantitative analysis was carried out to evaluate the impact of these factors on the fracture parameters of the dam concrete. Based on the test results, relevant theoretical models were used to predict the fracture loads and parameters of full-graded and wet-sieved concrete under different ages, sizes, and crack length conditions. The feasibility of predicting full-graded concrete fracture behavior using the results of wet-sieved concrete tests was also discussed. The findings indicate that age, size, and crack length all significantly affect the fracture parameters of dam concrete. When the ratio of ligament depth to maximum aggregate size reaches or exceeds 6, the initial fracture toughness, unstable fracture toughness, and fracture energy of both full-graded and wet-sieved concrete tend to stabilize. Using the boundary effect model, the size-independent fracture toughness, fracture strength, and scaling parameters of dam concrete can be determined, and the fracture loads, including initial cracking and maximum loads, can be accurately predicted under varying conditions of age, size, and crack length. In combination with the fracture extreme theory, accurate predictions of fracture toughness under different conditions can also be achieved. Validation results show that the absolute error between predicted and experimental values is generally within 15 %, indicating that this prediction method meets engineering requirements. By utilizing the results of wet-sieved concrete fracture tests, theoretical methods can effectively predict the fracture behavior of full-graded concrete. These findings can provide a scientific basis for crack risk analysis and control in the Wudongde arch dam.

ObjectiveAccurate assessment of concrete fatigue life under fatigue load is essential to ensure the safety and stability of structures, especially the fatigue failure behavior dominated by stress and strain.The fatigue loading surface function is established to describe the fatigue state of concrete based on the constraint relationship in the stress-strain fatigue criterion.The fatigue loading surface function of concrete exhibits a monotonic variation with fatigue cycles, enabling the establishment of an equivalent function to represent the concrete fatigue state.The fatigue loading surface function of concrete can be described as a linear equivalent expression, and the coefficients can be calibrated by the characteristic points in the fatigue loading process.MethodsBased on the constraint relationship between fatigue stress-strain and fatigue cycles, the equivalent fatigue cycles can be calculated from the fatigue stress-strain data.The equivalent fatigue cycles can effectively express the fatigue stress-strain state of the material, and the fatigue life indirectly represents the fatigue failure stress-strain state in the fatigue failure criterion of materials with the static constitutive curve as the limit value.The degree of fatigue accumulation of materials can be quantified by comparing the equivalent fatigue cycles and fatigue life.The evaluation method based on equivalent fatigue cycles overcomes the shortcomings of the current evaluation methods based on the classic fatigue criteria and fatigue envelope lines.Therefore, in this work, the fatigue loading surface function is constructed, and its evolution law is studied through the analogical form of the fatigue failure criterion of materials with a static constitutive curve as the limit value, thus proposing a description method for equivalent calibration and solving the equivalent fatigue cycles.The fatigue loading surface function is proposed to describe the fatigue state and determine the constraint relationship between fatigue stress and strain and fatigue cycles based on the fatigue failure criterion of materials with a static constitutive curve as the limit value.The equivalent fatigue loading surface function and coefficients can be obtained by the equivalent description method of feature point calibration.The R-square is introduced to ensure an equivalent description, and the maximum R-square directly relates to the optimal equivalent description results.Therefore, the maximum R-square algorithm is proposed based on the evolution law of the fatigue loading surface function.The linear equivalent form of the fatigue loading surface function is proposed to meet the equivalent description and practical application requirements.ResultsTherefore, equivalent calibration can be achieved by selecting the optimal maximum R-square, and the coefficients of the fatigue loading surface function can be determined from the experimental results of the fatigue loading process.The equivalent fatigue loading surface function, feature point calibration, and maximum determinable coefficient algorithms were developed to achieve the equivalent fatigue state description of materials.Through the equivalent calibration results, the equivalent fatigue cycles can be obtained using the corresponding fatigue stress-strain.Furthermore, the fatigue stress-strain state of concrete can be quantified by the equivalent fatigue cycles, and corresponding evaluation processes and indicators are obtained through further study.ConclusionsThe proposed method provides an effective approach for the fatigue life analysis of concrete.

Cracking-associated problems may occur in the construction and operation periods of dam galleries, necessitating attention to the fracture characteristics of gallery concrete. The fracture parameters of concrete exhibit size effects and also change with age. A correct evaluation of the cracking risk or crack stability of gallery structures at any given time requires a comprehensive understanding of both the size effect and time-variant characteristics of the gallery concrete fracture parameters. In the present study, 75 wedge-splitting specimens, with effective heights ranging from 200 mm to 600 mm, were cast using gallery concrete produced by the concrete mixing system at the Baihetan Dam construction site. Subsequently, fracture tests were conducted on these specimens at curing ages spanning from 7 days to 90 days. According to the test results, the fracture parameters of concrete with a specific size exhibited an increasing trend with age within 90 days, while the fracture parameters of concrete at specific ages show a significant size effect, tending to stabilize as the effective depth of specimens gradually increases. The boundary effect model was utilized for analyzing the fracture test results of concrete specimens at different ages, yielding the size-independent double-K fracture parameters and scale parameters for concrete at each age, along with their time-varying patterns. Subsequently, equations for predicting the failure loads of concrete specimens of any age and size were established. Based on the prediction results of failure loads, the double-K fracture parameters of concrete specimens of any age and size were solved by the fracture extreme theory. The predicted failure loads and fracture parameters were in good agreement with the experimental results. The findings of this study can be applied to the full lifecycle crack risk analysis or crack stability assessment of Baihetan Dam gallery structures.

This study developed a sustainable low-carbon sea sand engineered cementitious composites (LSECCs). The effect of FA/GGBS weight ratios (1, 0.5, 0), W/B ratios (0.16, 0.18, 0.20, 0.25) and PE fiber vol% (2 %, 1.8 %, 1.6 %) on the tensile and compressive properties of LSECCs was investigated. The formation mechanism of its high ductility was analyzed through fracture energy, single-crack testing, and SEM images. The results show that the compressive strength of LSECCs ranges from 60.0 MPa to 88.4 MPa, the ultimate tensile strength from 6.16 MPa to 8.38 MPa, and the ultimate tensile strain from 4.27 % to 8.49 %. Decreasing the FA/GGBS weight ratio, especially to 0.5, contributes to higher compressive strength, first-crack strength, and ultimate tensile strength of LSECCs, but reduces the ductility, while increasing the average crack width and crack spacing. Increasing the W/ B ratio enhances the ductility and crack width control ability of LSECCs. The optimal volume fraction of PE fibers is 1.8 %, at which the tensile failure process of LSECCs can be divided into three stages: linear elastic, hardening, and softening with considerable load-carrying capacity. Therefore, a trilinear tensile constitutive model is proposed to more accurately describe their tensile stress-strain relationship. This model is applicable not only to LSECCs with three-stage failure characteristics but also to ECCs with two-stage (elastic and strain hardening) failure characteristics. The findings of this study can provide experimental and theoretical references for the future design and application of sustainable low-carbon engineered cementitious composites.

This study presents an inverse analysis algorithm for deriving the softening relationship of concrete. The algo-rithm can not only reproduce the influence of local response on the a -w curve by introducing additional load criteria but also reduce the dependence of optimization results on the initial guesses by combining global best -fitting with the automatic parameter updating technique, improving the prediction accuracy and lowing the possibility of obtaining pseudo-solutions. Then, the fracture tests were carried out on the wedge splitting specimens. The validity and versatility of the algorithm were verified using experimental data. The findings show that the simulation responses agree well with the test ones in all regions of the load-CMOD curve, and the values of fracture energy determined by the load-CMOD and a -w curves are consistent. The derived a -w curve is in-dependent of the initial guesses of parameters. The widely used bi-linear a-w curve tends to overestimate the load in the post-peak of load-CMOD, and the tri-linear model is recommended after considering the accuracy, computation time, and convergence. The tensile strength evaluated by the inverse analysis method is 75% of the splitting tension test and 91% of the fracture theory method. Further, the proposed algorithm exhibits outstanding versatility, applying to various concrete materials and specimen configurations.

Herein, we propose a one-dimensional convolutional neural network (CNN) + long short-term memory (LSTM) model optimised by L1 regularisation and the dropout method to solve the problem of acquiring both computational speed and accuracy in a deformation prediction analysis model of a super-high arch dam’s first impoundment. The calculation results of one class (OC) + LSTM, traditional LSTM, optimised LSTM, CNN + LSTM and multilayer perceptron are compared with the actual measurement results using deformation monitoring data from the first impoundment of a super-high arch dam in southwest China. The results show that the proposed OC-LSTM model can reduce the computational time without sacrificing computational accuracy, providing a new computational model for super-high arch dam deformation prediction during the first impoundment.

A correction method is presented which can effectively improve the spurious oscillation phenomenon in impact problems. Based on the finite element method, the Lagrange multiplier method is introduced to impose contact constraints, and an unconditionally stable implicit combined time integration algorithm is combined to solve the frictionless dynamic contact problem. By introducing additional Lagrange multipliers, the velocity and acceleration obtained by the combined time integration algorithm are modified to meet the persistency conditions of the contact constraints in the form of velocity and acceleration. Numerical example results show that the correction method can effectively improve the spurious oscillation of velocity, contact force, etc. at the time of initial contact, and improve the solution accuracy of impact problems.

The fatigue failure problem actually can be explained by fatigue stress-strain envelope, and the fatigue evaluation based on fatigue stress-strain can avoid the uncertainty of selecting fatigue criteria in engineering applications. However, the application of experimental fatigue envelope criterion based on stress-strain curve is limited to concrete and rocks, and it also can not predict the fatigue failure time. To further develop the availability of fatigue stress-strain envelope criterion, the fatigue failure criterion of materials with static constitutive curve as the limit value is proposed to describe high-cycle and low-cycle fatigue failure through theoretical deduction of classic fatigue criteria and analysis of experimental results. The proposed criterion reveals the constraints mechanism that the fatigue life is dominated by fatigue failure stress-strain in the fatigue envelope surface. Finally, the comparison between calculated and experimental fatigue life indicates that the proposed criterion is suitable to. describe the fatigue failure well and has the comprehensive application prospect.

坝区高温低湿、大风等极端天气会使分层浇筑混凝土层间结合性能发生劣化.通过测定极端天气环境(如:高温低湿、大风)下混凝土的层面状态(含水量、贯入阻力)和层间劈裂抗拉强度,对3种施工措施(如表面不处理、覆盖保温被和界面凹槽)进行了研究.结果表明:碾压混凝土坝在极端环境下浇筑存在施工风险.在高温低湿条件下覆盖保温被并不能有效避免层间结合质量的下降,界面凹槽可以小幅度地提高坯层间结合强度;在大风条件下坯层表面覆盖保温被及采用界面凹槽处理是比较可行的措施,可以保证坯层间结合质量满足要求.在大风条件下覆盖保温被,一方面防止了水分的散失,另一方面延缓了混凝土的凝结速率,使得层间劈拉强度得到保证.

在高湿度地区,提高混凝土对水或者其他侵蚀溶液的抗渗性是十分必要的.添加疏水剂是提高混凝土抗渗性能的常用方法.介绍了一种新型的疏水外加剂YREC,在提高混凝土抗渗性的同时也增强了材料的强度.对掺入YREC混凝土的力学性能、抗渗性能、孔隙结构以及水泥水化程度进行了系统的研究.应用液氮吸附/解吸等温曲线和压汞法进一步分析了YREC对混凝土砂浆基体孔隙结构的影响.试验表明YREC的填充效应改善了孔隙分布,减少有害孔的含量,对提高混凝土材料的抗渗性能有一定的作用.由于YREC自身的疏水性,使得水化过程中的水体得到细化,CH晶体的发育受到抑制.伴随着更高密实度的C-S-H凝胶生成,混凝土的强度也得到了显著提高.

Existing tunnel boring machine (TBM) construction presents certain shortcomings. These include difficulty in comprehensive perception of information, poor timelines of information transmission and storage systems, significant effects of traditional data processing methods on the timeless of intelligent decision-making, and poor applicability of decision-making models and control strategies. In addition, the integration level of perception, decision-making, and control should be further improved. Therefore, a cross-platform deployable intelligent tunnelling robot system with closed-loop intelligent control functions of a "comprehensive perception, dual-driven decision-making, and composite intelligent control" is developed. Based on fieldbus, communication, database, cloud computing, and advanced exploration technologies, a multi-source information perception and integrated management platform based on a two-layer architecture is built to achieve the comprehensive perception of tunnelling information. In addition, an optimal decision-making method of the particle swarm optimisation (PSO) algorithm is simultaneously proposed for the minimum decision-making of tunnelling specific energy for scientific analyses and decision-making. A composite intelligent control strategy comprising multimodal and expert experienced learning control strategies is designed to achieve the control of conventional and unfavourable geological sections, respectively. Engineering cases verified the effectiveness and reliability of the intelligent tunnelling robot system. The research results not only provide new ideas and technical means for achieving the less-manned, unmanned, and intelligent tunnelling construction of deep-buried long tunnels but can also be promoted owing to its universality.

High dam construction is continuing to develop with new requirements for intelligent dam construction. New information technology capabilities are providing paths for improved intelligent dam construction. The key to achieving safe, quality, efficient, economic, green construction projects is to integrate these new information technology capabilities into intelligent construction methods. New systems enable intelligent construction of dams and the construction of intelligent dams. This article summarizes these two paths for intelligent construction, identifies three stages in the development of intelligent construction systems for dams, and analyzes the technical characteristics, goals, theory, methods, and management models with engineering examples for each stage of the intelligent construction process. The analysis shows the relationship between intelligent dam construction and intelligent dams, the three stages of intelligent dam construction, the changes in manager thinking for solving key problems in the intelligent era, and future developments in intelligent dam construction.