High-efficiency Simulation Research Articles

Research on the simulation method of a BP neural network PID control for stellar spectrum

This study investigated the multiple correlations among spectral simulation units based on digital micromirror device (DMD) spectral simulation, which leads to the problem that conventional spectral simulation methods such as PID control exhibit a low fitting accuracy or long fitting time in the spectral simulation of various targets. In this paper, a method of stellar spectrum simulation based on back propagation neural network-based PID (BP-PID) control is proposed to achieve high efficiency and high precision simulation of various spectral targets. The topology of the BP neural network was constructed based on the spectral modulation model of a DMD stellar spectrum simulation system, and the algorithm of the BP-PID control was designed. Finally, an experimental platform was built to verify the performance and spectral simulation accuracy of the BP-PID control algorithm. The results show that the overshoot and response time of the BP-PID control algorithm decreased by 79.01% and 30%, respectively compared with those of the PID control algorithm. The maximum spectral simulation accuracies of 2000K, 7000K, and 12000K color temperature increased by a factor of 2.311, 1.871, and 2.254, respectively, and the standard deviations of the spectral simulation error decreased by 56%, 41%, and 54%, respectively. In the range of 2000-12000K color temperature, the spectral simulation error of the BP-PID control algorithm is better than ±3.495%, and the standard deviation of the spectral simulation error is between 1.8255 and 2.2358. The proposed method can improve the spectral simulation accuracy and simulation efficiency of a star simulator, reduce the magnitude and spectrum calibration errors caused by the differential response, improve the star feature recognition accuracy of the orbiting star sensor, and hence, provide a theoretical and technical basis for the development of high-precision star sensors.

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.

High-Efficiency Simulation of Coherent Beam Combining Using Scaled Angular Spectrum Method with GPU Acceleration

High-Efficiency Simulation of Coherent Beam Combining Using Scaled Angular Spectrum Method with GPU Acceleration

Computable turbulence modeling of laminar-turbulent transition characterized boundary layer flows with the aid of artificial neural network

The continuous development of machine learning algorithms has stimulated the technological revolution on turbulence modeling for Reynolds-averaged Navier–Stokes (RANS) simulations. In this paper, a computable transition-enabled turbulence model is developed with the aid of an artificial neural network (ANN), which maps the relation between the mean flow variables from the shear stress transport (SST) model on coarse grid and the turbulent viscosity from SST-γ model on fine grid. It turns out that the ANN model can predict the aerodynamic integral quantities, transition onset location, laminar separation bubble structure, streamwise velocity distribution, etc. with superior accuracy and robustness for subsonic and moderate transonic airfoil flows. Meanwhile, the ANN model can significantly improve the convergence property with a much higher convergence speed of the model equation in comparison with traditional transition-enabled RANS model. Moreover, due to the lack of solving RANS model equations and use of grid interpolation technology, the computation speed of this ANN model is improved by a factor of about six over the conventional benchmark model. Therefore, the present computable ANN model provides a new perspective for high-efficiency simulation of transition-characterized flows in engineering applications.

Three-dimensional broadband simulation of near-fault seismic ground motion considering complete source-path-site effect: Modeled by fast multipole indirect boundary element method

Efficient and accurate numerical methods are essential for analyzing seismic wave propagation and amplification in near-fault complex sites. Understanding the complete process of ground motion simulation, including fault rupture, path propagation, and near-surface complex site response, is crucial for studying earthquake damage mechanisms, seismic zoning, and designing large-scale engineering structures. In this study, we propose a fast multipole indirect boundary element method (FMIBEM) to achieve broadband and high-efficiency simulation, enabling a comprehensive analysis of the complete process involving seismic ground motion. The FMIBEM significantly reduces the computational and storage costs associated with 3D near-fault complex site seismic wave scattering problems to O(N). We validate the accuracy of the method by comparing it with the analytical solution. Compared to the conventional indirect boundary element method (IBEM), our proposed method reduces computational time by over 95 % and storage costs by nearly 90 %. FMIBEM greatly enhances the efficiency of the boundary element method for simulating seismic wave scattering in near-fault complex sites. To demonstrate the effectiveness of our approach, we apply the FMIBEM method to two typical 3D near-fault complex site examples of seismic wave scattering. The simulation results successfully capture both the local site amplification effect and the characteristic near-fault seismic features, such as the hanging wall effect, permanent displacement effect, and large velocity pulse.

Research on the automatic modeling and performance prediction of plain-woven composites based on beam elements

This work presents an approach for the automatic modeling and high-efficiency simulation of the mechanical properties of plain-woven composites. For the beam element finite element model, a technical scheme for the automatic modeling of plain-woven fabrics is presented. Considering the constraint relationship between the matrix and the fibers, a method for creating matrix beam elements is proposed. Then, a beam element solver was compiled to simulate the tensile properties of the plain-woven composites. In addition, a method of rendering a three-dimensional model of yarn and the simulation results were presented, and a comparison between real fabric images and modeled fabric structure confirmed that the method proposed in this work could effectively model plain-weave fabric structures. Experimental results showed that the deviations of the tensile modulus and strength were 0.41% and −7.59% respectively, which verified the validity of the beam element model used in this study. Moreover, testing verification of the method used in this study could realize the automatic modeling and simulation of representative cells of plain-woven composites in a few seconds. The above results show that this work offers the potential to handle the efficient calculations of large-scale woven structure models.

High-Efficiency Simulation of Dynamic Stability Derivatives Based on a Particle Swarm Optimization and Long Short-Term Memory Network (PSO-LSTM) Coupling Aerodynamic Model

A new high-efficiency method based on a particle swarm optimization and long short-term memory network is proposed in this study to predict the aerodynamic forces in an unsteady state. Based on the predicted aerodynamic forces, the dynamic derivative is further calculated. Using particle swarm optimization to optimize the hyper-parameters of a neural network, the long short-term memory network prediction model can be constructed according to the known simulating aerodynamic data to predict the aerodynamic performance of aircraft in unknown states. By coupling the least-squares method in an aerodynamic derivative model, the dynamic derivative can be quickly obtained. Unsteady motion of NACA 0012 airfoil was taken as the research example to verify this method, and its longitudinal combined dynamic derivatives were predicted and compared with CFD simulation results. The results show that the dynamic derivatives predicted by the PSO-LSTM method have high accuracy, with an error of no more than 1% compared to CFD, and a 70% improvement in efficiency. The method proposed in this study has good generalization ability and can realize fast and accurate prediction of dynamic derivatives with a small number of samples.

A Heterogeneous Parallel Algorithm for Euler-Lagrange Simulations of Liquid in Supersonic Flow

In spite of its prevalent usage for simulating the full-field process of the two-phase flow, the Euler–Lagrange method suffers from a heavy computing burden. Graphics processing units (GPUs), with their massively parallel architecture and high floating-point performance, provide new possibilities for high-efficiency simulation of liquid-jet-related systems. In this paper, a central processing unit/graphics processing unit (CPU/GPU) parallel algorithm based on the Euler–Lagrange scheme is established, in which both the gas and liquid phase are executed on the GPUs. To realize parallel tracking of the Lagrange droplets, a droplet dynamic management method is proposed, and a droplet-locating method is developed to address the cell. Liquid-jet-related simulations are performed on one core of the CPU with a GPU. The numerical results are consistent with the experiment. Compared with a setup using 32 cores of CPUs, considerable speedup is obtained, which is as high as 32.7 though it decreases to 20.2 with increasing droplets.

Partially coherent light propagation through a kinoform lens.

Combining wave optics propagation and geometric ray tracing, the mutual optical intensity (MOI) model is extended to quantitatively simulate the propagation of partially coherent light through a kinoform lens at high speed. The MOI model can provide both a high accuracy and a high efficiency simulation. The intensity and coherence degree distributions at the focal plane are calculated using the MOI model. It is beneficial to improve the focusing capability of the kinoform lens by reducing the coherence or increasing the number of lens steps. In addition, increasing the number of steps is also beneficial to increase the photon flux and reduce the depth of focus.

Beam element method for mechanical analysis of 2.5D woven composite: Modeling strategy and finite element method simulation

This work presents a beam element approach for the modeling and high-efficiency simulation of mechanical properties of 2.5D woven composite. For the beam element model, a technical scheme for the parametric modeling of 2.5D woven fabrics was produced. Considering the constraint relationship between the matrix and the fibers, we proposed a method for creating matrix beam elements. Then, a beam element solver was compiled to simulate the mechanical properties of the 2.5D woven composite. Meso-scale analysis of curved shallow-crossing linking 2.5D woven composite using the proposed model obtained the accurate tensile modulus. Full-scale analysis was implemented to simulate bending behavior of straight shallow-crossing linking 2.5D woven composite, and the simulation results agreed well with the experimental results. The above analysis could automatically complete modeling, analysis and post-processing in a relatively short time, reflecting the efficiency advantages of the method in this paper.

High-efficiency simulation of nonstationary wind velocity using diagonal POD of decomposed time-frequency interpolation node spectrum matrices

The classical spectral representation method (SRM) used extensively to simulate nonstationary wind fields suffers from lower efficiency. Although some tries can already accelerate SRM, the efficiency improvement is restricted when the number of simulation points is large. For this reason, this paper proposed a high-efficiency interpolation scheme to boost the efficiency of SRM. Firstly, the decomposed time-frequency interpolation node spectrum matrices can be approximately decouple into the products of time and frequency functions using diagonal proper orthogonal decomposition (POD). Specifically, the POD operation is just for the diagonal elements, which are low-dimensional matrices. Since Cholesky decomposition is merely needed in the time-frequency interpolation point, the time consumed by spectral decomposition will be significantly reduced. Then, one-dimensional (1D) interpolation is implemented for these decoupling terms in the time and frequency directions, respectively. The decoupling results only contains a few time terms, so the number of 1D interpolation operations can be considerably decreased. Moreover, by exchanging the summation order, very few fast Fourier transform operations are required to accelerate harmonic superposition. Therefore, the proposed method may further enhance the simulation efficiency. Finally, through numerical examples, the accuracy and superiority of the proposed method are demonstrated.

MDD: A Unified Model-Driven Design Framework for Embedded Control Software

Model-driven methods are widely used in embedded control software development. Current design tools, such as Ptolemy-II and Simulink, have strong modeling capability but their simulation and code generation functionalities are challenged by the increasing complexity of control requirements. For simulation, emulating the triggering of the actor leads to additional time overhead and speed degradation. For code generation, generating redundant content degrades the code quality. Besides, current tools do not have a unified interface, which makes it difficult to cooperation. In this article, we propose a unified model-driven design framework MDD to facilitate embedded control software development. MDD can support the unification of models built by different modeling tools for high-efficiency simulation and high-quality code generation. The MDD framework supports the expansion of more modeling tools, and also supports the expansion of more uses, such as unified testing and verification. First, it offers a model intermediate representation (MIR) and several corresponding parsers, which facilitate a unified representation and cooperation for different design tools. Then, based on data flow schedule analysis of the original MIR, intermediate code representation will be generated for optimized code synthesis. Finally, a variety of code translators will synthesize the intermediate code representation into the code of actual use, such as code for simulation and code for deployment. For evaluation, we enhance two widely used design tools in industry, Ptolemy-II and Simulink, and apply them on the implementation of several benchmark models and a real-world self-driving control software of our industrial collaborator. Using MDD can help reduce their simulation time by 98.9% and 92.6%, the generated code by 99.7% and 69.9% in the number of lines, and 94.3% and 34.3% in code execution time, respectively.

Simulation Research on Flow Boiling and Heat Transfer of Micro-channel for Electronic Cooling

Micro-channel heat exchanger is a popular device for the electronic cooling. Heat transfer of flow boiling in micro-channel is a research hotspot. For the convenience of the theoretical research on micro-channel, a high efficiency simulation model on flow boiling and heat transfer of micro-channel was established. In the simulation research, the influence rules of operating conditions and thermal properties of refrigerants (working fluids) on the flow boiling were studied; the distribution rules along flow direction of characteristic parameters such as vapor quality, Heat Transfer Coefficient (HTC), pressure drop and bottom wall temperature of micro-channel T w were analyzed; the key factors on the distribution of characteristic parameters were proposed. The characteristic parameters based on the refrigerants R134a and R1234ze(E) in micro-channel were compared and researched. According to the simulation results, HTC and pressure drop of R134a are larger and smaller than those of R1234ze(E) respectively, the uniformities of HTC and T w of R134a are all better than those of R1234ze(E) respectively.

Culture of patient-derived multicellular clusters in suspended hydrogel capsules for pre-clinical personalized drug screening.

A personalized medication regimen provides precise treatment for an individual and can be guided by pre-clinical drug screening. The economical and high-efficiency simulation of the liver tumor microenvironment (TME) in a drug-screening model has high value yet challenging to accomplish. Herein, we propose a simulation of the liver TME with suspended alginate-gelatin hydrogel capsules encapsulating patient-derived liver tumor multicellular clusters, and the culture of patient-derived tumor organoids(PDTOs) for personalized pre-clinical drug screening. The hydrogel capsule offers a 3D matrix environment with mechanical and biological properties similar to those of the liver in vivo. As a result, 18 of the 28 patient-derived multicellular clusters were successfully cultured as PDTOs. These PDTOs, along with hepatocyte growth factor (HGF) of non-cellular components, preserve stromal cells, including cancer-associated fibroblasts (CAFs) and vascular endothelial cells (VECs). They also maintain stable expression of molecular markers and tumor heterogeneity similar to those of the original liver tumors. Drugs, including cabazitaxel, oxaliplatin, and sorafenib, were tested in PDTOs. The sensitivity of PDTOs to these drugs differs between individuals. The sensitivity of one PDTO to oxaliplatin was validated using magnetic resonance imaging (MRI) and biochemical tests after oxaliplatin clinical treatment of the corresponding patient. Therefore, this approach is promising for economical, accurate, and high-throughput drug screening for personalized treatment.

An online parameter identification and real-time optimization platform for thermal systems and its application

Real-time performance optimization of thermal systems is crucial for energy conservation but also challenging because of the high system complexity and time sensitivity. Herein, an online parameter identification and real-time optimization platform for thermal systems is developed, and a gas-steam combined cycle cogeneration system is used to demonstrate its capability. The platform integrates data collection, parameter identification, system simulation, and real-time optimization modules. The data preprocessing and parameter identification modules collects real-time operation parameters for optimization. The system simulation module applies the heat current method to model the cogeneration system precisely, and a high-efficiency simulation procedure is proposed using the hierarchical and categorized (H&C) algorithm. The system optimization module introduces the artificial neural network technology to ensure the response time of real-time optimization. Meanwhile, the H&C algorithm and genetic algorithm are combined to update the database to improve the optimization performance gradually. The platform is first validated on three typical conditions. It is further deployed at a power plant, where a field test is conducted for the practical verification. Field test results show that the standard coal consumption of the cogeneration system could be reduced by 0.415 g/kWh by using the platform, which proves its practicability.

A high-efficiency simulation method of wind field and its application on transmission line

Generally, the fluctuating wind is simplified as several independent one-dimensional multivariate stationary Gaussian processes in simulating a natural wind field. The correlation in the lateral, longitudinal and vertical directions should all be considered in the simulation of longitudinal wind field for the large-span spatial structures. In fact, this type of structure has lots of simulation points. The calculation amount of wind field simulation by the harmonic superposition method depends on the scale of cross-spectral density matrix, which is directly related to the number of simulated points, leading to a low efficiency when generating the time-varying wind speed. This paper innovatively proposes a high-efficiency simulation method for the longitudinal wind field based on Taylor's hypothesis. Subsequently, the effectiveness of the proposed wind field method was verified by the numerical simulation. Finally, the dynamic responses of a transmission tower-line system under the wind loadings generated with the new method and traditional method are calculated and compared. The percentages difference of the mean and maximum axial force at the main tower members are less than 0.02% and 1%, respectively, indicating the effectiveness of the proposed time delay method. The results also show that the proposed simulation method of wind field can not only ensure the simulation accuracy, but also significantly improve the efficiency of wind speed generation, which is suitable for the wind load simulation of large-span spatial structures.

High-efficiency simulation of VENUS-3 neutron-shielding problem with an automatic and enhanced hybrid Monte-Carlo-Deterministic method

To solve the deep-penetration problem in the Monte-Carlo simulation, the classic consistent adjoint driven importance sampling (CADIS) and forward-weighted CADIS (FW-CADIS) hybrid MC-deterministic method is adopted and enhanced in this paper. An automatic hybrid MC-deterministic code, NECP-MCX, is newly developed. NECP-MCX embeds the discrete-ordinate code NECP-Hydra to automatically perform the forward and adjoint neutron-transport calculations and set up the importance parameters for the MC simulation. In massive parallel calculation for large shielding problems, huge amounts of memory are required to save detailed weight-window information. To mitigate the memory limitation, a mesh-coarsening algorithm is developed based on the contributon theory. It can be applied in the traditional Cartesian-mesh and the nested-mesh structure. NECP-MCX was applied to the VENUS-3 benchmark. The results show that NECP-MCX with the enhanced hybrid method is effective in variance reduction and memory saving for the simulation of large and complicated shielding problems on parallel computer resources.

Near real-time prediction of wind-induced tree damage at a city scale: Simulation framework and case study for Tsinghua University campus

During typhoon events, wind damage to trees in urban areas may have various adverse impacts on urban functions and cause direct and indirect economic losses. To realize the near real-time prediction of wind damage to urban trees, this study proposes a high-efficiency simulation framework by coupling computational fluid dynamics and mechanistic tree damage modeling. The proposed framework involves four key steps: modeling effects of trees on urban airflow, constructing a scenario bank, near real-time predicting urban airflow, and simulating wind-induced tree damage. The accuracy and efficiency of the methods used in each step are validated. A real-world, complex urban area in Beijing, China, namely the Tsinghua University campus, is used as a case study to showcase the workflow. A user-friendly program, THU-NEWDRT, is developed to help managers efficiently evaluate the wind-induced damage risk of campus trees. Finally, a set of hypothetical strong wind events are used to exemplify the practicality of the proposed framework.

A high-efficiency simulation method for analyzing the impact of exhausted air from temporary hospitals built for the treatment of novel coronavirus pneumonia

A high-efficiency simulation method for analyzing the impact of exhausted air from temporary hospitals built for the treatment of novel coronavirus pneumonia

Application of the MST turbulence model to predict the tip leakage vortex flows

PurposeTip leakage vortex flow (TLV) is a common flow phenomenon in the axial-flow hydraulic machinery. High-efficiency simulation of TLV is still not an easy task because of the complex turbulent vortex-cavitation interactions. As an important basis of CFD, turbulence model directly affects the efficient computation of TLV. The purpose of this paper is to evaluate the newly developed MST turbulence model in predicting the TLV flows.Design/methodology/approachBy using the MST turbulence model and the ZGB cavitation model, numerical simulations of the TLV generated by a NACA0009 hydrofoil were performed under the cavitation-free and cavitation conditions, and the results were compared with the available experimental data.FindingsThe important features of TLV are well captured by the MST-based simulation scheme, and the problem of under-predicting the cavitating TLV tube is well solved. Turbulent viscosity is reasonably adjusted in the TLV core regions, and the LES-like mode is activated, which is beneficial to obtain more turbulent information on the same URANS grids. The requirements of grid size and time step of the MST model are much lower than that of the LES method, thereby weighing a good balance between the simulation accuracy and computation cost.Originality/valueThe MST turbulence model is suitable for the high-efficiency simulation of the TLV flows, which can lay a good foundation for efficient engineering computations of the cavitating TLV in the axial-flow hydraulic machinery.