Hybrid Simulation Method Research Articles

A hybrid simulation method towards the gamma ray phase contrast imaging for metallic material

A high efficiency simulation method for propagation-based phase-contrast imaging, called directional macro-wavefront (DMWF), is developed with the aim of simulating high-energy phase-contrast imaging. This method takes both Monte Carlo and wave optical propagation into consideration. Traditional wave-optics-based simulation methods for phase-contrast imaging encounter unacceptable computational complexity when high-energy radiation is used. In contrast, this method effectively addresses this issue by using macro-wavefront integration. Several simulation examples using typical parameters of inverse Compton scattering sources are presented to illustrate the excellent energy adaptability and efficiency of the DMWF method. This method provides a more efficient approach for phase-contrast imaging simulations, which will drive the advancement of high-energy phase-contrast imaging.

Determination of diffuse field sound absorption of a porous absorber from Biot parameters using simulation

Porous sound absorbers are commonly assessed by their diffuse field sound absorption. In the test, a sample of the material, having a recommended surface area of 2.44 m by 2.74 m, is placed on the floor of a reverberation room. The average sound pressure level in the room is measured using a reference sound source and compared to the level in an empty room. Using room acoustic theory, the diffuse field sound absorption of the sample can be determined. This sound absorption is often much higher than the normal incidence sound absorption due to diffraction effects especially at lower frequencies. In this research, a hybrid simulation method is used to determine the diffuse field sound absorption from the Biot properties of the sound absorber. Statistical energy analysis is used to model the room and finite element analysis is used to simulate the material sample. Results from simulation are compared against measurement and agreement is acceptable.

An efficient yet accurate optimization algorithm for thermal systems integrating heat current method and generalized Benders decomposition

Thermal system optimization is critical for energy conservation but challenging due to highly complicated systems and nonlinear governing equations. Herein, an efficient yet accurate optimization algorithm based on generalized Benders decomposition (GBD) is developed to address this challenge. It decomposes the entire optimization into a subproblem and a master problem. The subproblem performs the system simulation by developing a hybrid simulation method, which uses GBD and fixed-point iteration sequentially for acceleration. The master problem is constructed based on the gradients of the objective with respect to decision variables, where the solution of every iteration gives an approximation of the optimal solution. The two generated problems are iteratively solved in an alternating manner to converge towards the optimal solution. Test results of a supercritical carbon dioxide recompression system indicate that the hybrid simulation method expands the convergence region to ∼167 % which is nearly 4 times larger than that of the fixed-point iteration, and consumes about 10 % calculation time compared with sequential modular method. The optimization algorithm reproduces the results obtained from the genetic algorithm but reduces the calculation time for an order-of-magnitude and has higher stability. The high efficiency and accuracy suggest the proposed algorithm as a powerful system optimization tool.

Unveiling the transition of tumbling and tank-treading dynamics of star-shaped polyelectrolytes in shear flow by modulating the solution's dielectric properties.

The effects of the solution's dielectric properties on the conformation and dynamics of star-shaped polyelectrolytes in shear flow are investigated using a hybrid simulation method coupling multi-particle collision dynamics and molecular dynamics. The simulation results showed that by modulating the dielectric properties of the solution, star-shaped polyelectrolytes showed a three-step dynamic behavior transition from tumbling to tank-treading to tumbling dynamics under shear flow. The analysis indicated that this distinct transition in dynamics could be attributed to the uneven distribution of counterions induced by shear on the chain, resulting in a change in the polyelectrolyte conformation and degree of segmental alignment in arms. These findings contribute to a comprehensive understanding of the non-equilibrium dynamics of star-shaped polyelectrolytes in shear flow and offer a viable approach for controlling the dynamic behavior of star-shaped polyelectrolytes by adjusting the dielectric properties of the solution.

Unscented Kalman Filter-Based Two-Stage Adaptive Compensation Method for Real-Time Hybrid Simulation

ABSTRACT In order to effectively solve the dynamic delay problem of the servo-hydraulic actuator, simplify the design of the compensator, and improve the robustness of the compensation, an unscented Kalman filter-based two-stage adaptive compensation (UKF-TAC) method is proposed for real-time hybrid simulation (RTHS) in this study. Theoretical analysis and numerical simulations are conducted to verify the performance of the proposed UKF-TAC method. The research results show that the proposed UKF-TAC method can significantly simplify the design of the compensator, effectively improve the compensation accuracy, and has the robustness to adapt to different partitioning cases and resist the interference of uncertain factors.

An EGO-based online model updating method for hybrid simulation

Hybrid simulation combines experimentally testing of physical substructures with computational simulation of numerical substructures to replicate structural responses under earthquakes. When numerical substructure involves parts that are similar to physical substructure, measured responses of physical substructure are often used to update similar parts within numerical substructure, aiming to improve accuracy of seismic assessment. This study proposes an efficient global optimization based approach for online model updating in hybrid simulation (HSMU-EGO) involving multiple key components yet with only one physically tested in laboratory. Kriging meta-model is constructed for the response error between the numerical model for updating and the experimental substructure, while efficient global optimization and optimal Latin hypercube design are integrated for parameter estimation to minimize the response error. Computational simulations are conducted for a simple steel braced frame and a complex concrete continuous bridge to comprehensively evaluate the performance of HSMU-EGO in the presence of constitutive parameter and model errors. The proposed method is demonstrated to effectively and efficiently improve the accuracy of hybrid simulation in almost all cases. Compared with Unscented Kalman Filter (UKF), this proposed HSMU-EGO provides more suitable alternative when prior information is limited for the physical substructure.

Hybrid genetic algorithm-simulated annealing based electric vehicle charging station placement for optimizing distribution network resilience

Rapid placement of electric vehicle charging stations (EVCSs) is essential for the transportation industry in response to the growing electric vehicle (EV) fleet. The widespread usage of EVs is an essential strategy for reducing greenhouse gas emissions from traditional vehicles. The focus of this study is the challenge of smoothly integrating Plug-in EV Charging Stations (PEVCS) into distribution networks, especially when distributed photovoltaic (PV) systems are involved. A hybrid Genetic Algorithm and Simulated Annealing method (GA-SAA) are used in the research to strategically find the optimal locations for PEVCS in order to overcome this integration difficulty. This paper investigates PV system situations, presenting the problem as a multicriteria task with two primary objectives: reducing power losses and maintaining acceptable voltage levels. By optimizing the placement of EVCS and balancing their integration with distributed generation, this approach enhances the sustainability and reliability of distribution networks.

Carbon structural evolution and interfacial reaction mechanism investigation of the green anode in kneading and baking via ReaxFF-MD and force-biased Monte Carlo

ABSTRACT Baking is the most costly and critical process in anode preparation, and the study from the microscopic scale is conducive to the optimisation of anode baking process. In this research, a hybrid simulation method of reactive force field molecular dynamics (ReaxFF-MD) and force-biased Monte Carlo (fbMC) was proposed to understand the interaction mechanism between coal tar pitch (CTP) and calcined petroleum coke (CPC) during kneading and baking processes, and to explore the optimal ratio of CTP from the molecular scale. Results showed that the CTP content of 14 wt.% was beneficial for anode production. The mechanism of anode coking behaviour at high temperatures was also analyzed. The carbonisation of CTP during high-temperature baking broke the carbon rings and formed straight chains, exposing active carbon atoms that can bond with the remaining layers. As the high-temperature simulation progresses, the carbon chains at the bonding sites became increasingly cyclized and aromatised, which made the layered structure of the baked block similar to that of graphite. The generation of various volatile hydrocarbons during the baking process was observed, namely CH4, C2H4, C2H2, C2H6, and C3H6. This work provides theoretical basis for process optimisation.

Accurate solution of the Index Tracking problem with a hybrid simulated annealing algorithm

An actively managed portfolio almost never beats the market in the long term. Thus, many investors often resort to passively managed portfolios whose aim is to follow a certain financial index. The task of building such passive portfolios aiming also to minimize the transaction costs is called Index Tracking (IT), where the goal is to track the index by holding only a small subset of assets in the index. As such, it is an NP-hard problem and becomes unfeasible to solve exactly for indices with more than 100 assets. In this work, we present a novel hybrid simulated annealing method that can efficiently solve the IT problem for large indices and is flexible enough to adapt to financially relevant constraints. By tracking the S&P-500 index between the years 2011 and 2018 we show that our algorithm is capable of finding optimal solutions in the in-sample period of past returns and can be tuned to provide optimal returns in the out-of-sample period of future returns. Finally, we focus on the task of holding an IT portfolio during one year and rebalancing the portfolio every month. Here, our hybrid simulated annealing algorithm is capable of producing financially optimal portfolios already for small subsets of assets and using reasonable computational resources, making it an appropriate tool for financial managers.

GA-BPNN Prediction Model of Broadband Ground Motion Parameters in Tianjin Area Driven by Synthetic Database Based on Hybrid Simulated Method

GA-BPNN Prediction Model of Broadband Ground Motion Parameters in Tianjin Area Driven by Synthetic Database Based on Hybrid Simulated Method

Distributed real-time hybrid simulation method for dynamic response evaluation of floating wind turbines

Limited land and near coast spaces led to the development of floating wind turbine (FWT) farms in unlimited space of deep water with steady winds. Experimental evaluation of dynamic responses of FWT is essential to ensure its safe operation. However, due to laboratory limitations and scaling issues, realistic FWT responses are difficult to be replicated on scaled-down test specimens. To facilitate larger-scale testing of FWT and apply realistic wind and wave loads, distributed real-time hybrid simulation (dRTHS) method is proposed which combines the testing of FWT substructures at geographically distributed laboratories using wind tunnels and wave tanks. In this research, dRTHS experimental method for FWT is developed and its feasibility is verified through a series of virtual dRTHS (vdRTHS) and proof-of-the-concept partial dRTHS tests. The equation of motion of a prototype FWT structure under coupled aerodynamic and hydrodynamic loads was partitioned to represent the wind turbine tower and platform substructures, based on which substructural formulation was derived. During the vdRTHS, two distributed real-time controllers were used to simulate the physical testing of the two substructures tested in the wind tunnel and water tank, respectively, with interfacing data being transferred in real-time through a network. FWT responses from vdRTHS match well with those obtained from numerical simulations of the whole FWT model and the substructured models, demonstrating that the feasibility of the proposed dRTHS method. In addition, the substructuring approach, the vdRTHS testing platform, and the method to overcome network communication delay are effective in the vdRTHS resulting in reliable FWT dynamic responses under coupled loading conditions. Furthermore, the proposed dRTHS concept was verified through a partial distributed physical tests during which the wind turbine substructure was tested physically, while the platform substructure and the hydrodynamic loads were simulated numerically.

The Assessment of Structural Damages by Potential M<sub>L</sub> 7.0 Changhua Earthquake in Taiwan Using Hybrid Simulation Method, Modal Analysis and Story Drift Ratio

The Assessment of Structural Damages by Potential M<sub>L</sub> 7.0 Changhua Earthquake in Taiwan Using Hybrid Simulation Method, Modal Analysis and Story Drift Ratio

A new 2D fluid-MC hybrid approach for simulating nonequilibrium atmospheric pressure plasmas: density distribution of atomic oxygen in radio-frequency plasma jets in He/O2 mixtures

A spatially two dimensional fluid-MC hybrid (fluid-kinetic) simulation method is developed and applied to the COST reference microplasma jet operated in helium with an oxygen admixture of 0.5%, excited by a single frequency voltage waveform with f = 13.56 MHz and ϕrms=275 V. The simulation approach is based on a fluid model augmented by a Monte Carlo module that generates electron impact rates for the continuity equations solved by the fluid module. This method is capable of providing the same level of accuracy as PIC/MCC simulations with an agreement within 5%–10% at atmospheric pressure, while being significantly faster (with a speedup factor of 30 for serial to 50 for parallel implementation). The simulation results are compared to previous measurements of atomic oxygen densities (Steuer et al 2021 J. Phys. D: Appl. Phys. 54 355204), and show a very good agreement. It is found that the buildup and saturation of the atomic oxygen density distribution along the jet are due to the interplay of chemical and electron impact reactions as well as of the gas flow. Comparing the simulation results to that of Liu et al 2021 J. Phys. D: Appl. Phys. 54 275204, it is inferred that fluid models where a 2-term BE solver is used, fail to describe the COST jet in an accurate manner due to the underestimation of the electron impact rates.

Thermal flow analysis of temperature-sensitive magnetic fluid around multiple heated bodies

When the system proposed by Resler and Rosensweig (1964) is used for heat transfer, it is necessary to efficiently inject heat into the temperature-sensitive magnetic fluid and generate an appropriate self-drive to transport heat. In this paper, assuming that a heat sink is used for heat injection, the heat flow that occurs when multiple heated bodies are arranged in the temperature-sensitive magnetic fluid. The thermal flows around nine heated objects were calculated using a two-dimensional hybrid simulation method based on the lattice Boltzmann method, the finite difference method, and the immersed boundary method. The nine square or circular cylinders were assumed as the heated bodies. The average Nusselt number of each heated object was calculated. From the simulation results, it is shown that the heat transfer performance is better from the downstream objects than that from the upstream objects in case of circular objects. The velocity of the wake is faster than in case of the circular objects than in the case of square objects. In the case of circular objects, heat is trapped between the objects aligned in the flow direction, thus the heat transfer characteristics of square objects are better than that of circular objects.

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 Real-Time Hybrid Simulation Method for Vehicle–Bridge Interaction Systems Considering Vehicle Jumping

The investigation on vehicle–bridge interaction systems (VBIS) plays an important role in evaluating the performance of bridges and/or vehicles. However, due to the limitations of traditional simulation methods and testing methods, the impact of vehicle jumping (VJ) on the VBIS has never been precisely disclosed. In order to accurately and comprehensively reveal the impact of VJ on the dynamic performance of VBIS, one real-time hybrid simulation method (RHSM) for VBIS considering the impact of VJ (VBIS-VJ) is proposed in this paper. In the proposed method, the vehicle system is chosen as the experimental substructure loaded by servo-hydraulic actuator loading system in real-time, whilst the bridge system is chosen as the numerical substructure numerically simulated in one computer. During the vehicle jumping, the vehicle and bridge vibrate freely respectively, otherwise, the experimental substructure and numerical substructure are synchronized at the coupling points in terms of force equilibrium and deformation compatibility in RHSM for VBIS-VJ. Firstly, the principle and numerical models of RHSM for VBIS-VJ are proposed. Furthermore, numerical simulations of RHSM for VBIS-VJ are conducted for verifying the feasibility of the proposed method. Finally, the influence of jumping position, jumping height, and driving speed on the VBIS is disclosed by hybrid simulations. It is shown that compared with the ever-known investigation methods, the proposed method could economically and accurately disclose the dynamic performance of VBIS-VJ. It is shown from the simulation results that compared with the referenced results, the quantitative errors of the proposed method with quarter vehicle model and half vehicle model are less than 2.5152% and 3.5599% respectively, which prove the effectiveness and accuracy of proposed RHSM for VBIS-VJ. The peak displacement of the bridge at a quarter-span and mid-span exceeds the three-quarters span by about 1.9–2.9[Formula: see text]mm. The influence of jumping position of a quarter span and midspan of bridge is much huger than that in the three-quarters span. The dynamic response of bridge increases with the increase the jumping height, but the deformation of the bridge is reduced when the jumping height is more than 0.05[Formula: see text]m. Meanwhile, the requirements for experimental loading equipment are acquired through the hybrid simulations, which could be used as a reference for selecting the loading system of the RHSM for VBIS-VJ.

Real-time hybrid simulation incorporating machine learning for deep-water bridges subjected to seismic ground motion with fluid-structure dynamic interaction

The investigation of fluid-structure dynamic interaction (FSI) of deep-water structures subjected to seismic events with underwater shaking table testing method has been restricted by similarity problems and limited experimental capabilities. To address this issue, the authors previously proposed a real-time hybrid simulation (RTHS) method for FSI under seismic loading. In this study, the proposed method is applied to a deep-water bridge to demonstrate the low-cost and high-efficiency features of the proposed method. A total of 100 sets of experimental samples were analyzed, providing details and statistical information of the structural responses with FSI effects during seismic events. In the proposed RTHS application, a machine learning surrogate model was established for real-time calculation of the complex numerical substructure, and data exchange for complex physical-numerical boundaries. Additionally, a solution for RTHS when complex physical substructure boundary conditions can only be partially satisfied has been proposed, further contributing to the versatility of the study. Through the utilization of such advanced computational methods, the authors were able to explore the intricate coupled effect between fluid and structure in a deep-water environment. Such efforts hold the promise of enhancing our understanding of this complex phenomenon and may ultimately inform the design and construction of more resilient structures in the future.

Analysis of the Effect of Lateral Collision on the Seismic Response of Bridges under Fault Misalignment

Mutual dislocation of seismogenic faults during strong earthquakes will result in a large relative displacement on both sides of the fault. It is of great significance to explore the influence of the collision effect between the main beam and the transverse shear key on the seismic response of the bridge under fault dislocation. In this paper, a series of cross-fault ground motions with different ground permanent displacements are artificially synthesized using a hybrid simulation method. Based on the contact element theory, the Kelvin–Voigt model is used to simulate the lateral collision effect. The effect of lateral collision on the seismic response of the continuous girder bridge is compared from the two aspects of fault dislocation position and fault dislocation degree. On this basis, the analysis of lateral collision parameters is carried out with the aim of reasonably regulating the seismic response of the structure. The results show that, compared with the near-fault bridge, the influence of lateral collision on the cross-fault bridge is stronger. The amplification of the bending moment of the central pier and the limitation of the bearing displacement are five times and two times, respectively, for the near-fault bridge. When the fault has a large dislocation, the weak point of the structural damage is the bending failure of the pier bottom and the residual torsion after the earthquake. The collision parameters of conventional bridges will aggravate the bending moment demand of the pier bottom of cross-fault bridges and limit their bearing displacement too much. Therefore, by appropriately reducing the collision stiffness and increasing the initial gap, the internal force and displacement response distribution of the cross-fault bridge structure can be more reasonable. The study in this paper has reference significance for seismic analysis of cross-fault bridges with transverse shear keys.

Using real-time hybrid simulation for active mass damper experimentation and validation

This paper proposes a novel real-time hybrid simulation (RTHS) method for advancing active mass driver (AMD) control techniques. A comprehensive derivation of the equations of motion are developed, where the tracking problem of absolute acceleration is addressed by transforming it into a displacement tracking problem, within the RTHS control loop. The simulated and experimental results demonstrate acceptable acceleration tracking using this methodology, enabling a seamless and effective option for controlling the shake table transfer system, within the RTHS framework. To demonstrate and validate the effectiveness of the proposed techniques, complete AMD shake table, and AMD-RTHS experiments are conducted. To address the effects of uncertainty, a series of tests are conducted to form an uncertainty response envelope. Comparisons between RTHS and shake table tests show that the responses lie within RTHS uncertainty regions, demonstrating that acceleration can be successfully tracked. This study shows that an AMD control experiment can be realized using RTHS techniques, thus offering an option to advance the development of AMD control techniques. Finally, an RTHS framework is proposed for performance evaluation of structural control methods using AMDs.

A real‐time hybrid simulation method based on multitasking loading

SummaryDue to the real‐time loading property and the limitation of available loading facilities, both of the refined numerical substructure simulations and multiple experimental substructure tests are impossible for traditional real‐time hybrid simulation method (RHSM). For improving the experimental accuracy under limited loading facilities, a RHSM based on multitasking loading (RHSM‐ML) is proposed in this paper. In the proposed method, an inner‐loop multitasking loading strategy is adopted for accurately reproducing the performance of multiple experimental substructures with limited available loading facilities, and an outer‐loop force correction‐based iteration strategy is adopted for further improving the experimental accuracy by allowing refined simulation of the numerical substructures while remaining real‐time loading on the experimental substructures. Firstly, the methodology of the proposed RHSM‐ML is presented. Furthermore, the numerical simulations were conducted for validating the effectiveness and accuracy of the proposed method. Finally, the influence of the structural model on the iterative convergence is analyzed. It is shown that the multitasking loading and the force correction‐based iteration strategy are feasible for RHSM. It is shown from numerical simulations that with the contribution of the multitasking loading strategy, the correlation coefficients under different simulation conditions can up to 0.9999 within five round iterations by the RHSM‐ML and the force correction‐based iteration strategy of the RHSM‐ML can significantly improve the iterative convergence accuracy. It is shown from iterative convergence analysis that under different structural models, the convergence of the RHSM‐ML can be achieved within five round iterations.