Complex Engineering Structures Research Articles

New methods and applications of structural dynamics modeling for railway freight liquid tank

As railway freight technology advances towards heavy-load, high-speed capabilities, the design of liquid tank products is evolving to prioritize high load capacity, lightweight, high-strength materials, low structural rigidity, and thin-walled construction. These changes result in pronounced nonlinear low-frequency vibrations during rail operation. Addressing these complex liquid-solid coupled vibrations requires accurate dynamic modeling of the structural system. This paper introduces a novel dynamic modeling method for liquid tank products based on acousto-elastic coupling. This approach considers the swaying of the free liquid surface and liquid-solid interactions, enabling precise characterization of these dynamics in a unified model. Specifically, it tackles the challenge of uneven node swaying forces caused by non-uniform liquid surface meshing, presenting a technique and program to adjust swaying recovery forces based on nodes’ actual coverage area. This method’s liquid sway frequency calculations showed a 10% precision increase over traditional methods, more accurately reflecting liquid vibration states. The paper applies these techniques to a single tank container and an LNG tank container on a flatbed trailer. Through theoretical, simulation, and experimental comparisons, the model’s accuracy and reasonableness were validated. This low-dimensionality, high-precision dynamic model is universally applicable, especially valuable in modeling complex engineering structures.

Dynamic response of sandwich functionally graded nanoplate under thermal environments and elastic foundations using dynamic stiffness method

The present paper introduces the development of dynamic stiffness method for analyzing small-scale sandwich functionally graded nanoplates resting on elastic foundation in thermal environments. The mathematical formulation is based on classical plate theory in conjunction with nonlocal elasticity theory. The governing equation is derived using Hamilton’s principle. The dynamic stiffness matrix is obtained through the application of the Levy displacement approach and assembled to form the global stiffness matrix. The final matrix is solved for natural frequency of the plates using the Wittrick–Williams algorithm. The proposed methodology is validated against existing literature, demonstrating a strong agreement. Various parametric studies explore the effects of thermal environments, volume fraction index, sandwich configurations, elastic foundation characteristics, nonlocal parameter and boundary conditions. The results show the versatility of the proposed approach in addressing small scaled complex engineering structures. This research significantly contributes to the understanding and analysis of sandwich functionally graded nanoplates, providing valuable insights for applications in aerospace, structural systems, sensors, actuators, and energy harvesting devices.

Online numerical simulation method based on adaptive unscented Kalman filter for shear wall structures

Hybrid test method is an effective approach to evaluate the seismic performance of engineering structures. Particularly, online numerical simulation method (ONSM) based on unscented Kalman filter (UKF) model updating significantly improves the accuracy of the hybrid test results. However, the sensitivity of UKF to the initial values of the state vector, state covariance, and observation noise covariance may lead to the distortion of hybrid test results. To address these issues, one novel ONSM based on adaptive UKF (ONSM-AUKF) is proposed in this paper. The AUKF algorithm incorporates an adaptive variance module to maintain equilibrium. This not only reduces the sensitivity of UKF to the initial parameter settings, prevents filter divergence, but also enhances the accuracy and stability of estimation. The proposed ONSM-AUKF accurately identifies the constitutive model parameters by utilizing measured data from specimens through the AUKF algorithm, which improves the accuracy and the stability of parameter estimation. The simulation results indicate that AUKF algorithm has the capability to decrease the sensitivity of initial parameter settings, thus enhancing the stability and robustness of parameter estimation in comparison to the UKF algorithm. The experimental results validate the feasibility and effectiveness of the proposed ONSM-AUKF, as well as the advantages of the ONSM-AUKF over the ONSM-UKF. The results indicate that the proposed ONSM-AUKF may have broad application prospect in evaluating the seismic performance of various of complex engineering structures.

Quantile-based optimization under uncertainties for complex engineering structures using an active learning basis-adaptive PC-Kriging model

The Reliability-Based Design Optimization (RBDO) of complex engineering structures considering uncertainties has problems of being high-dimensional, highly nonlinear, and time-consuming, which requires a significant amount of sampling simulation computation. In this paper, a basis-adaptive Polynomial Chaos (PC)-Kriging surrogate model is proposed, in order to relieve the computational burden and enhance the predictive accuracy of a metamodel. The active learning basis-adaptive PC-Kriging model is combined with a quantile-based RBDO framework. Finally, five engineering cases have been implemented, including a benchmark RBDO problem, three high-dimensional explicit problems, and a high-dimensional implicit problem. Compared with Support Vector Regression (SVR), Kriging, and polynomial chaos expansion models, results show that the proposed basis-adaptive PC-Kriging model is more accurate and efficient for RBDO problems of complex engineering structures.

Nonlinear Seismic Analysis of Concrete Dams Using ABAQUS-Based Scaled Boundary Finite Element Method

ABSTRACT The scaled boundary finite element method (SBFEM) is implemented in ABAQUS through the user subroutine interface. The accuracy of the proposed method and computer program are verified by using two benchmark examples. With the coupled SBFEM and standard finite element method (FEM), the dynamic interaction model of concrete dam – reservoir – foundation considering the geometrical nonlinearity of transverse joints is established using the viscous-spring absorbing boundary conditions. The overlaying element technique is applied to define the contact interface of transverse joints. The dynamic characteristics and linear seismic response of the Koyna gravity dam have been analyzed using polyhedral elements. Finally, nonlinear seismic analysis of the NG5 arch dam has been conducted. The calculated results are in good agreement with those of ABAQUS built-in elements. Moreover, numerical examples demonstrate that proposed method has high computational accuracy and can be applied to the dynamic analysis of complex engineering structures.

Superhydrophobic Tensile Designability of Silicone Rubber Composites.

Silicone rubber has broad applications in the field of industrial engineering due to its stable physical and chemical properties. However, the superhydrophobic properties, of silicone rubber, especially large deformation superhydrophobic properties, were not satisfactory for many harsh application environments and complex engineering structures. Here, we report the preparation of superhydrophobic tensile designable silicone rubber composites by a mixed deposition process that included powder deposition and smoke deposition. The infrared test showed that the deposited powder from silicone rubber combustion was mainly composed of SiO2 and short chain siloxane. The mixed deposited surface with a rich micro-nanostructure, which was the key to the formation of superhydrophobic properties. The water contact angle (WCA) and sliding angle (SA) of coating surface could reach 157.6° and 5° ± 1°, respectively, and the tensile designability of superhydrophobic surface is closely related to the prestretched process. In addition, bounce tests, high temperature tests, and solvent resistance tests showed the application potential of modified silicone rubber composites in the field of engineering.

An adaptive multi-output Gaussian process surrogate model for large-scale parameter estimation problems

PurposeParameter estimation in complex engineering structures typically necessitates repeated calculations using simulation models, leading to significant computational costs. This paper aims to introduce an adaptive multi-output Gaussian process (MOGP) surrogate model for parameter estimation in time-consuming models.Design/methodology/approachThe MOGP surrogate model is established to replace the computationally expensive finite element method (FEM) analysis during the estimation process. We propose a novel adaptive sampling method for MOGP inspired by the traditional expected improvement (EI) method, aiming to reduce the number of required sample points for building the surrogate model. Two mathematical examples and an application in the back analysis of a concrete arch dam are tested to demonstrate the effectiveness of the proposed method.FindingsThe numerical results show that the proposed method requires a relatively small number of sample points to achieve accurate estimates. The proposed adaptive sampling method combined with the MOGP surrogate model shows an obvious advantage in parameter estimation problems involving expensive-to-evaluate models, particularly those with high-dimensional output.Originality/valueA novel adaptive sampling method for establishing the MOGP surrogate model is proposed to accelerate the procedure of solving large-scale parameter estimation problems. This modified adaptive sampling method, based on the traditional EI method, is better suited for multi-output problems, making it highly valuable for numerous practical engineering applications.

Time-dependent dynamical energy analysis via convolution quadrature

Dynamical Energy Analysis was introduced in 2009 as a novel method for predicting high-frequency acoustic and vibrational energy distributions in complex engineering structures. In this paper we introduce the first time-dependent Dynamical Energy Analysis method. Time-domain models are important in numerous applications including sound simulation in room acoustics, predicting shock-responses in structural mechanics and modelling electromagnetic scattering from conductors. The first step is to reformulate Dynamical Energy Analysis in the time-domain by means of a convolution integral operator. We are then able to employ the Convolution Quadrature method to provide a link between the previous frequency-domain implementations of Dynamical Energy Analysis and fully time-dependent solutions by means of the Z-transform. By combining a modified multistep Convolution Quadrature approach for the time discretisation, together with Galerkin and Petrov-Galerkin methods for the space and momentum discretisations, respectively, we are able to accurately track the propagation of high-frequency transient signals through phase-space. The implementation here is detailed for finite two-dimensional spatial domains and we demonstrate the versatility of our approach by performing a range of numerical experiments for regular, non-convex and irregular geometries as well as different types of wave source.

Electrical measurement method of static friction force on rough surface

Friction plays a key role in the assessment of the safety and stability of mechanical systems (such as superconducting magnet quench explosion, aerospace vehicle bearing wear, etc.). Due to the closeness of the interfaces in engineering structures and the randomness of the contact surfaces, existing methods for measuring static friction force are unable to measure it at the contact interfaces of engineering structures under service conditions. In this paper, a new method for measuring the static friction force at the interface based on electrical signals is proposed. This method enables the measurement of the static friction force at interfaces of complex engineering structures under service conditions solely through electrical signals. The results indicate that the contact resistance gradually decreases with the increase in tangential load during the static friction stage until a monotonic behavior of macroscopic sliding occurs. The evolution of contact resistance is linked to the evolution of the real contact area, and this monotonic behavior can be explained as the deformation form of contact points. The accuracy of the proposed electrical measurement method is verified by comparison with experimental results (with an error of less than 9%). The indirect measurement method of friction force proposed in this paper can effectively measure the static friction force at the interfaces of engineering structures under service conditions, and it is expected to be applied to the detection of friction performance at engineering structure interfaces in extreme service environments.

Complexity biomechanics: a case study of dragonfly wing design from constituting composite material to higher structural levels.

Presenting a novel framework for sustainable and regenerative design and development is a fundamental future need. Here we argue that a new framework, referred to as complexity biomechanics, which can be used for holistic analysis and understanding of natural mechanical systems, is key to fulfilling this need. We also present a roadmap for the design and development of intelligent and complex engineering materials, mechanisms, structures, systems, and processes capable of automatic adaptation and self-organization in response to ever-changing environments. We apply complexity biomechanics to elucidate how the different structural components of a complex biological system as dragonfly wings, from ultrastructure of the cuticle, the constituting bio-composite material of the wing, to higher structural levels, collaboratively contribute to the functionality of the entire wing system. This framework not only proposes a paradigm shift in understanding and drawing inspiration from natural systems but also holds potential applications in various domains, including materials science and engineering, biomechanics, biomimetics, bionics, and engineering biology.

A mixed uncertain structural reliability analysis method considering random and convex set variables with correlation

AbstractIn this paper, a mixed model reliability analysis method is put forward for the problem of assessing the reliability of complex engineering structures containing both random and convex aggregate variables. By integrating the ellipsoidal model with correlation and the interval model, the uncertainty region characterized by the ellipsoidal model with correlation is optimized with full consideration of the limited amount of engineering structure sample data, and the risk region represented by the reliability model is redefined, a new mixed reliability assessment criterion is established, and the minimum safe nonprobability reliability index of the structure is built. A key reference is offered by the safety limit diagram of constant reliability indexes set for the first time for the optimal design of engineering structure reliability. The proposed mixed reliability model is compared and analyzed with three classical models. The sensitivity of nonprobability reliability indexes, influenced by random variable parameters and correlation coefficients, is analyzed. This verification confirms that the new reliability model not only provides an accurate assessment of engineering structures' reliability but also lowers the computational demands of engineering design. In this paper, aero‐engine blades and wind turbine blades are taken as examples to expound the validity of the reliability model built using this method and its importance to the structural safety analysis of actual engineering.

Implementation of real-time hybrid simulation using a large shake table with onboard actuators

In recent decades, shake table real-time hybrid simulation (RTHS) has emerged as a promising seismic testing approach for complex engineering structures. However, the current shake table RTHS systems with actuators typically install the dynamic actuators on a reaction wall outside the table, which introduce interaction issues between the dynamic actuators and the shake table. This study proposes a potential improvement by developing a shake table RTHS platform with onboard actuators. The platform incorporates a 6 m × 9 m large-scale shake table where the physical substructure, two dynamic actuators, and the reaction frame are all positioned. To validate the effectiveness of the developed platform, a two-story steel frame is tested by both full structure shake table test and substructure shake table RTHS. In the shake table RTHS, the lower part of the frame serves as the physical substructure and is simultaneously loaded by the shake table and dynamic actuators, while the upper part is numerically analyzed in OpenSees, using OpenFresco and Simulink as intermediate softwares. The test results demonstrate that the developed shake table RTHS platform provides reasonable predictions to the structural seismic responses. In addition, time delay is optimized using both inner and outer loop compensators, highlighting the effectiveness of inverse compensation and adaptive time series (ATS) compensation schemes. This paper successfully develops a shake table RTHS platform using a large shake table with onboard dynamic actuators, providing a valuable seismic testing platform for RTHS of large-scale complex engineering structures.

High-rise building foundation design of the Lakhta Center

The foundation is the most significant element of buildings. The foundation structure closely relates to the general construction of the building frame and is largely determined by soil conditions. High-rise buildings are complex engineering structures with increased requirements for strength, stability and durability. Therefore, their safety and durability depend on strength, deformity and stability of foundation. These principles allow creating foundations of the higher quality, bearing capacity, reliability, and durability.Purpose: Optimization of production processes in the construction of foundation structures of super tall buildings and structures.Research findings: The structural design of the Lakhta Center 462 m high in Saint-Petersburg, which is the tallest building in Europe. A particular attention is paid to the design and construction of the foundation. Key results can prove operation and design of high-rise buildings designed for weak and unstable soils.Value: Determination of the most significant factors influencing the choice of production processes during the construction of super-tall buildings.

МІСЦЕ ІНЖИНІРИНГУ В ЖИТТЄВОМУ ЦИКЛІ ПРОМИСЛОВИХ ВИРОБІВ

In undertaking the exploration, the authors endeavored to disseminate to the readership a developed comprehension of the essence of engineering as a distinct form of economic endeavor and its positioning within the lifecycle of generating consumer value. Emphasis is placed on shipbuilding artifacts, considering their pivotal role in both the global and, by extension, national economies increasingly enmeshed within the international economic milieu. It is discerned that the upsurge in demand for Engineering services is attributable to the steep ascension in fleet size, notably within its most robust segment - the commercial sector. The doubling of the fleet size for transporting various types of cargo over the past twenty years has been confirmed by visualized statistics. This phenomenon is not merely a result of a surge in maritime freight transportation, which has increased by nearly three hundred percent over the analyzed period. Simultaneously, there is a growing interest among shipowners in extending the operational lifespan of vessels. In this context, they place hopes on vessel repair, modernization, and conversion. Furthermore, even the disposal of these complex engineering structures, in accordance with the requirements of the International Maritime Organization and the standards of the European Union and participating countries, should occur without causing harm to the personnel of specialized shipyards and the environment. It has been demonstrated that solving this problem is also impossible without engineering support. A model has been provided, defining the role of Engineering in the life cycle of industrial products (using shipbuilding as an example). It confirmed the working hypothesis regarding the parallel-sequential organization of relationships between Engineering and other stages of the life cycle of mechanical engineering products. Attention is focused on the fact that addressing the challenges that arise at each stage is facilitated by digital twins of physical objects. The "lives" of both are completely synchronized, as events occurring during the real-time operation of the offline object and their consequences are automatically reflected in the virtual "twin". This conclusion is of particular significance in the context of applying the concept and corresponding tools of Product Lifecycle Management in practice.

Introduction to the Special Issue on Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures

Introduction to the Special Issue on Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures

SEARCH OF OPTIMAL SPATIAL PARAMETERS FOR GEODETIC DELINEATION OF MOTORWAY INTERCHANGES WITH BRAKING TRANSITION CURVES

The most widespread grade-separated road junction — cloverleaf interchange — is a complex engineering structure, in which all the parameters and limitations of the plan and longitudinal profile must be coordinated with each other. The goals of the analysis: traffic safety, technical and economic indicators of the movement of transport units, the compactness of left-turn and right-turn exits and, as an additional, but extremely important aspect, the minimization of the area occupied by the entire transport structure, which is very important in tight urban conditions. 
 First, let's emphasize that the trajectories of cars at the intersection must correspond to their real variable speeds on left-turn exits, since this is traffic on curves of small radii. In our previous studies, it has been experimentally proven that cars entering a left-turning exit reduce their speed, and conversely, when leaving the exit, their speed increases. Therefore, it is necessary to use braking curves as transition curves of left-turn exits, and not clothoid curves, which are often used, and which are designed for constant speed of movement.
 Some braking transition curves designed for variable speed are also used in traffic junctions [4]. But, analyzing these curves, we came to the conclusion that they do not meet the classical purpose of the transition curve, namely, they do not provide the necessary radius at the end of the curve, which is equal to the radius of the circular insert for a smooth transition from a transition curve to a circular curve. This leads to dangerous moments of the car's movement at the junction of the transition and circular curves.
 Therefore, we previously derived the formulas of refined braking transition curves that meet the requirements of the radii of classical transition curves [1, 2]. In addition, it later turned out that these refined transition curves have, as an additional effect, the property of reducing the area occupied by the left-turn exit, as shown in Fig. 1.
 We offer a method for optimizing the spatial parameters of cloverleaf interchanges with refined braking transition curves.

Implementation of offline iterative hybrid simulation based on neural networks

AbstractReal‐time hybrid simulation (RTHS) is a testing method that combines numerical simulation and physical testing, enabling large‐scale or even full‐scale tests of large and complex engineering structures using the existing experimental facilities. At present, the accuracy and stability of RTHS are limited by the loading device and numerical solution efficiency. The experimental method was improved based on the neural network, and an off‐line iterative hybrid simulation method based on neural networks was implemented. Taking the tuned damping structure as examples, the dynamic metamodels of the tuned mass damper and tuned liquid damper were established based on the long‐short time memory (LSTM) neural network, and the model was iteratively simulated globally with the 9‐story benchmark model to calculate the response of the damping structure. The error of damper reaction predicted by LSTM neural network model is within 5.16%. The global iterative method can converge after a limited number of iterations, and the peak error of the structural response is within 7.85%.

A novel hybrid adaptive framework for support vector machine-based reliability analysis: A comparative study

This study presents an innovative hybrid Adaptive Support Vector Machine - Monte Carlo Simulation (ASVM-MCS) framework for reliability analysis in complex engineering structures. These structures often involve highly nonlinear implicit functions, making traditional gradient-based first or second order reliability algorithms and Monte Carlo Simulation (MCS) time-consuming. The application of surrogate models has proven effective in addressing computational challenges associated with a large number of simulations. Support Vector Machine (SVM), as an emerging machine learning method suitable for small-sample scenarios, offers a well-established theoretical foundation and presents an effective model substitution approach for reliability analysis in engineering structures. However, the existing literature lacks a comprehensive and thorough comparative analysis of SVM's hybrid adaptive modeling approach, encompassing initial sampling methods and learning functions, with regards to both computational efficiency and accuracy. Additionally, there is a gap in adaptive modeling methods capable of accommodating diverse types of input uncertainty, the nonlinearity of limit state functions, and various application scenarios. In response to these gaps, this article introduces the ASVM-MCS framework, which addresses these challenges by considering different types of input variables and various failure modes. Moreover, this study provides a comprehensive evaluation of the ASVM-MCS framework's performance, including its initial sampling methods and learning functions, across a range of application scenarios, such as scenarios involving only random variables, mixed variables, and the reliability of series-parallel systems.

Efficient inverse-designed structural infill for complex engineering structures

Inverse design of high-resolution and fine-detailed 3D lightweight mechanical structures is notoriously expensive due to the need for vast computational resources and the use of very fine-scaled complex meshes. Furthermore, in designing for additive manufacturing, infill is often neglected as a component of the optimized structure. In this paper, both concerns are addressed using a so-called de-homogenization topology optimization procedure on complex engineering structures discretized by 3D unstructured hexahedrals.Using a rectangular-hole microstructure (reminiscent to the stiffness optimal orthogonal rank-3 multi-scale) as a base material for the multi-scale optimization, a coarse-scale optimized geometry can be obtained using homogenization-based topology optimization. Due to the microstructure periodicity, this coarse-scale geometry can be up-sampled to a fine single-scale physical geometry with optimized infill, with only a minor loss in structural performance and at a fraction of the cost of a fine-scale solution. The upsampling on 3D unstructured grids is achieved through stream surface tracing, aligning with the optimized local orientations. The periodicity of the physical geometry can be tuned, such that the material serves as a structural component and also as an efficient infill for additive manufacturing designs.The method is demonstrated through three examples of varying geometrical complexity. It achieves comparable structural performance to “brute force” state-of-the-art methods but stands out for its significant computational time reduction. By allowing multiple active layers, the mapped solution becomes more mechanically stable, leading to an increased critical buckling load factor without additional computational expense. The control of active layers also provides direct control over the internal structure, i.e., infill, ensuring that the infill is incorporated as a structural component and enhancing the manufacturability of the de-homogenization procedure. Furthermore, the proposed approach exhibits promising results, achieving volume fractions and weighted compliance values within 5% of the large-scale SIMP model, while demonstrating a computational efficiency improvement ranging from 10 times to over 250 times.

Enhanced adaptive sequential Monte Carlo method for Bayesian model class selection by quantifying data fit and information gain

For complex engineering structures, it is important to systematically select a model class among various choices and search the complicated parameter space, while also quantifying uncertainties. This paper develops an enhanced adaptive sequential Monte Carlo (ASMC) method to solve Bayesian model updating and model class selection in a unified manner. Main contributions are: (1) Analysis of the sequential sampling process reveals difficulties of sampling from complex probability density functions (PDFs), which naturally leads to the PDF approximation using incremental weights of samples, and then the adaptive sampling scheme with this approximation. (2) Following ASMC framework, new formulations are derived to calculate model class evidence; these formulations enable the separate quantification of data fit and information gain of a model class. A simulated and a full-scale structure were used to demonstrate the proposed method. This work lays good foundation for downstream research such as automation in construction and structural health monitoring.