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Parameter identification is an important issue in structural health monitoring and damage identification for concrete dams. The purpose of this paper is to introduce a novel adaptive fireworks algorithm (AFWA) into inverse analysis of parameter identification.

Swarm intelligence algorithms and finite element analysis are integrated to identify parameters of hydraulic structures. Three swarm intelligence algorithms: AFWA, standard particle swarm optimization (SPSO) and artificial bee colony algorithm (ABC) are adopted to make a comparative study. These algorithms are introduced briefly and then tested by four standard benchmark functions. Inverse analysis methods based on AFWA, SPSO and ABC are adopted to identify Young’s modulus of a concrete gravity dam and a concrete arch dam.

Numerical results show that swarm intelligence algorithms are powerful tools for parameter identification of concrete structures. The proposed AFWA-based inverse analysis algorithm for concrete dams is promising in terms of accuracy and efficiency.

Fireworks algorithm is applied for inverse analysis of hydraulic structures for the first time, and the problem of parameter selection in AFWA is studied.

A large, uneven settlement that is unfavourable to dam safety can occur between a concrete cut-off wall and the high-plasticity clay of earth core dam built on alluviums. This issue has been often studied using the small-strain finite element (FE) method in previous research. This paper aims to research the interaction behaviour between a concrete cut-off wall and high-plasticity clay using large-deformation FE analyses.

The re-meshing and interpolation technique with a small-strain (RITSS) method was performed using an independently developed program and adopted for large-deformation FE analyses, and a suitable element size for the high-plasticity clay region was suggested. The layered construction process of an earth core dam built on thick alluviums was simulated using the RITSS method incorporating a hyperbolic model for soil.

The RITSS method is an effective technique for simulating the soil–structure interaction during dam construction. The RITSS analysis predicted a higher maximum principle stress of the concrete cut-off wall and higher stress levels in the high-plasticity clay region than small-strain FE analysis.

A practical method for large-deformation FE analysis was advised and was used for the first time to study the interaction between a concrete cut-off wall and high-plasticity clay in dam engineering. Large deformation in the high-plasticity clay was handled using the RITSS method. Moreover, the penetration process of the concrete cut-off wall into the high-plasticity clay was captured using a favourable element shape and mesh density.

Societal needs produce infrastructural demands that often, require innovative industrial solutions to optimally satisfy them. One such need is fresh clean water and this has been met in part, by a global infrastructure of dams and reservoirs. Dams have borne witness to their innovative construction design, technology and management (CDTM) over the years and the purpose of this paper is to examine an example of this, relating to Claerwen dam in Great Britain.

The study used historical case study method based on Busha and Harter's (1980) model, to accommodate synthesis of extant, historical and archive data. Subsequent archival data analysis is founded predominately on document synthesis and embraces a longitudinal character.

Benefiting incontrovertibly from industrial innovations, Claerwen was constructed in markedly different ways from its “sister” phase 1 Elan Valley dams built 50 years earlier, to uniquely combine vernacular aesthetic with contemporary CDTM of the time and create a reservoir with capacity almost equal to that of the entire phase 1 dams combined.

Findings offset a dearth of historical construction research more generally; and that relating to dam infrastructure, more specifically.

Minimal literature exists regarding innovations in British dam building so the study is especially original in that respect.

The purpose of this study is to develop and verify a methodology for a zoned deformation prediction model for super high arch dams, which is indeed a panel data-based regression model with the hierarchical clustering on principal components.

The hierarchical clustering method is used to highlight the main features of the time series. This method is used to select the typical points of the measured ambient and concrete temperatures as predictors and divide the deformation observation points into groups. Based on this, the panel data of each zone can be established, and its type can be judged using F and Hausman tests successively. Then hydrostatic–temperature–time–season models for zones can be constructed. Through the comparative analyses of the distributions and the fitted coefficients of these zones, the spatial deformation mechanism of a dam can be identified. A super high arch dam is taken as a case study.

According to the measured radial displacements during the initial operation period, the investigated pendulums are divided into four zones. After tests, fixed-effect regression models are established. The comparative analyses show that the dam deformation conforms to the natural condition. The factors such as the unstable temperature field and the nonlinear time-dependent effect have obvious effects on the dam deformation. The results show the efficiency of the proposed methodology in zoning and prediction modeling for deformation of super high arch dams and the potential to mining dam deformation mechanism.

A zoned deformation prediction model for super high arch dams is proposed where hierarchical clustering on principal component method and panel data model are combined.

Dams require high-volume of construction materials and operations over the life cycle. This paper aims to select a proper type of dam structure that can significantly contribute to the sustainability of dam projects.

This research proposes a complementary fuel consumption and carbon dioxide (CO₂) emission assessment method for the alternate dam structure types to assist decision-makers in selecting sustainable choices. Related equations are developed for two common earthen and rock-fill dam structures types in Iran. These equations are then successfully applied to two real dam project cases where the significance of the achieved results are assessed and discussed.

The achieved results of the case studies demonstrate a high deviation of up to 41.3% in CO₂ emissions comparing alternate dam structure scenarios of earthen and rock-fill dam structures. This high deviation represents an important potential for CO₂ emission reduction considering the high volume of the emission in large dam projects.

The life cycle emission assessment of the alternate dam structures, proposed in this research as a novel complementary factor, can be used in the decision-making process of dam projects. The results in this research identify high potential sustainability improvement of dam projects as a result of the proposed method.

To improve the efficiency, accuracy and adaptivity of the parameter inversion analysis method of a rockfill dam, this study aims to establish an adaptive model based on a harmony search algorithm (HS) and a mixed multi-output relevance vector machine (MMRVM).

By introducing the mixed kernel function, the MMRVM can accurately simulate the nonlinear relationship between the material parameters and dam settlement. Therefore, the finite element method with time consumption can be replaced by the MMRVM. Because of its excellent global search capability, the HS is used to optimize the kernel parameters of the MMRVM and the material parameters of a rockfill dam.

Because the parameters of the HS and the variation range of the MMRVM parameters are relatively fixed, the HS-MMRVM can imbue the inversion analysis with adaptivity; the number of observation points required and the robustness of the HS-MMRVM are analyzed. An application example involving a concrete-faced rockfill dam shows that the HS-MMRVM exhibits high accuracy and high speed in the parameter inversion analysis of static and creep constitutive models.

The applicability of the HS-MMRVM in hydraulic engineering is proved in this paper, which should further validate in inversion problems of other fields.

An adaptive inversion analysis model is established to avoid the parameters of traditional methods that need to be set by humans, which strongly affect the inversion analysis results. By introducing the mixed kernel function, the MMRVM can accurately simulate the nonlinear relationship between the material parameters and dam settlement. To reduce the data dimensions and verify the model’s robustness, the number of observation points required for inversion analysis and the acceptable degree of noise are determined. The confidence interval is built to monitor dam settlement and provide the foundation for dam monitoring and reservoir operation management.

The complexity of analysis of geotechnical behavior is due to multivariable dependencies of soil and rock responses. In order to cope with this complex behavior, traditional forms of engineering design solutions are reasonably simplified. Incorporating simplifying assumptions into the development of the traditional models may lead to very large errors. The purpose of this paper is to illustrate capabilities of promising variants of genetic programming (GP), namely linear genetic programming (LGP), gene expression programming (GEP), and multi‐expression programming (MEP) by applying them to the formulation of several complex geotechnical engineering problems.

LGP, GEP, and MEP are new variants of GP that make a clear distinction between the genotype and the phenotype of an individual. Compared with the traditional GP, the LGP, GEP, and MEP techniques are more compatible with computer architectures. This results in a significant speedup in their execution. These methods have a great ability to directly capture the knowledge contained in the experimental data without making assumptions about the underlying rules governing the system. This is one of their major advantages over most of the traditional constitutive modeling methods.

In order to demonstrate the simulation capabilities of LGP, GEP, and MEP, they were applied to the prediction of: relative crest settlement of concrete‐faced rockfill dams; slope stability; settlement around tunnels; and soil liquefaction. The results are compared with those obtained by other models presented in the literature and found to be more accurate. LGP has the best overall behavior for the analysis of the considered problems in comparison with GEP and MEP. The simple and straightforward constitutive models developed using LGP, GEP and MEP provide valuable analysis tools accessible to practicing engineers.

The LGP, GEP, and MEP approaches overcome the shortcomings of different methods previously presented in the literature for the analysis of geotechnical engineering systems. Contrary to artificial neural networks and many other soft computing tools, LGP, GEP, and MEP provide prediction equations that can readily be used for routine design practice. The constitutive models derived using these methods can efficiently be incorporated into the finite element or finite difference analyses as material models. They may also be used as a quick check on solutions developed by more time consuming and in‐depth deterministic analyses.

This paper presents a mathematical model for the analysis of cohesive fracture propagation through a non‐homogeneous porous medium. Governing equations are stated within the frame of Biot's theory, accounting for the flow through the solid skeleton, along the fracture and across its sides toward the surrounding medium. The numerical solution is obtained in a 2D context, exploiting the capabilities of an efficient mesh generator, and requires continuous updating of the domain as the fractures enucleate and propagate. It results that fracture paths and their velocity of propagation, usually assumed as known, are supplied directly by the model without introducing any simplifying assumption.

The main purpose of this paper is to present and use the particle simulation method to explicitly simulate the spontaneous crack initiation phenomenon in brittle materials, and to compare the particle simulation results with experimental ones on the laboratory scale.

Using the particle simulation method, the brittle material is simulated as an assembly of particles so that the microscopic mechanism of inter‐ and intra‐particle crack initiation can be straightforwardly considered on the microscopic scale. A laboratory test has been conducted using a gypsum sample model to validate the particle simulation method for explicitly simulating the spontaneous crack initiation phenomenon.

The paper finds that in terms of simulating the macroscopic sliding surface along or around the contact plane between a block and its foundation, both the laboratory test and the particle simulation have produced consistent results. This indicated that the particle simulation method is capable of simulating macroscopic cracks through simulating conglomerations and accumulations of microscopic crack initiation within the brittle material. Compared with other numerical methods, the particle simulation method is more suitable for explicitly and effectively simulating spontaneous crack initiation problems on the microscopic scale in brittle materials.

The particle simulation method can be used to explicitly and effectively simulate the spontaneous crack initiation on the microscopic scale in brittle materials. It can be also used to simulate the macroscopic sliding surface along or around the contact plane between a block and its foundation. The experimental results of simulating the spontaneous crack initiation on the laboratory scale in brittle materials are very valuable for validating the numerical simulation results obtained not only from the particle simulation method, but also from other numerical simulation methods.

Proposes a new approach for analysing the stationary random response of complex structures located in a non‐homogeneous stochastic field. The approach is a kind of complete CQC method because the cross‐correlation terms between both the participant modes and the ground joint excitations are included in the response calculations. Also takes into account the effect of the loss of coherency between ground joints.