High-precision Simulation Research Articles

A numerical simulation research on fish adaption behavior based on deep reinforcement learning and fluid–structure coupling: The refuge–predation behaviors of intelligent fish under varying environmental pressure

The study of fish swimming behavior and locomotion mechanisms holds substantial scientific and engineering significance. With the rapid progression of artificial intelligence, the integration of artificial intelligence with high-precision numerical simulation methods presents a novel and highly efficient tool for investigating fish behavior. In this paper, we proposed a fish perception model that more closely reflects natural logic. By introducing the individual vision and partially visibility model, a physics-based visual system that mirrored the sensory capabilities of live fish was developed. Furthermore, through the construction of a flow vision using conventional neural networks, we enhanced the intelligent fish's ability to detect unsteady hydrodynamic parameters via numerical lateral line. The validity of the new model was demonstrated through experiments, which the intelligent fish hunts complex moving targets in unsteady flow. Finally, we applied the model to study the refuge/predation behaviors of coral reef fish under varying unsteady flow pressures. The results indicated that swimming capabilities significantly impact fish survival strategies in high flow velocity, highly unsteady hydrodynamic environments, shaping distinct evolutionary decision-making traits. These insights may help to understand the niche competition mechanisms of fish in different flow conditions.

Multiscale formation mechanism and instability characteristic of the submerged vortices caused by a closed pump intake

The intake system serves as a crucial inlet structure for tidal pumping stations along the coastal regions. However, the various types of submerged vortices caused by the closed intake disrupt the energy-conversion stability, limiting the efficient and safe operation of the units. Especially when the multiple vortices are mixed enter the pump, the pump's energy consumption increases, and the hydraulic stability of the intake further decreases. This study used the high-precision simulation method to elucidate that the anisotropic turbulent structure around the roof-attached vortex (RAV) and the Reynolds shear stress are the critical factors for initiating small-scale RAV. The vertical and its enstrophy transport equation were used to explain that the vortex stretching term is the primary source of inducing the vertical vorticity evolution of RAV and floor-attached vortex (FAV). The tilting term provides a power source for vortex wandering. Based on the high-speed visualization experiment, the instability characteristics analysis of the vortices showed that the root of RAV dissipation was the existence of a critical stagnation point, SRAV, and the dissipation form exhibited “bubble-like fragmentation.” The unstable dissipation of the FAV does not have a vital stagnation point, and the dissipation form manifests as “vortex filament dissipation.” The results have important academic value and theoretical guidance significance for ensuring the safe and efficient operation of the tidal units.

Effect of injection strategy on spray and combustion processes in 2-stroke rod-less opposed piston engine (2S-ROPE)

The 2-stroke Rod-less Opposed Piston Engine (2S-ROPE) is a novel engine design that has garnered attention owing to its high power and low fuel consumption. This study investigated the effects of different fuel injection strategies on the in-cylinder working process of a 2S-ROPE engine, which features a smaller combustion space and lateral injection than conventional diesel engines. A high-precision three-dimensional simulation model was developed to examine the fuel atomization and in-cylinder combustion processes under four distinct injection strategies (S1, S2, S3, and S4). The results demonstrated that the injection strategy significantly influenced the number of oil droplets, particularly for small particles. The number of small droplets in S4 was approximately 6 times that in S1. The double-layer injection strategies (S3 and S4) exhibited a better atomization breakup and oil-air mixing, leading to a faster combustion rate and higher lift power than the single-layer injection strategies (S1 and S2). These findings suggest that the double-layer injection strategy is more suitable for a 2S-ROPE engine, increasing the lift power by up to 23 %. The results can guide the improvement of combustion parameters in most opposed piston engines.

Monitoring, simulation and early warning of cyanobacterial harmful algal blooms: An upgraded framework for eutrophic lakes

Cyanobacterial Harmful Algal Bloom (CyanoHAB) is a global aquatic environmental issue, posing considerable eco-environmental challenges in freshwater lakes. Comprehensive monitoring and accurate prediction of CyanoHABs are essential for their scientific management. Nevertheless, traditional satellite-based monitoring and process-oriented prediction methods of CyanoHABs failed to satisfy this demand due to the limited spatiotemporal resolutions of both monitoring data and prediction results. To address this issue, this paper proposes an upgraded framework for comprehensive monitoring and accurate prediction of CyanoHABs. A collaborative CyanoHAB monitoring network was firstly constructed by integrating space, aerial, and ground-based monitoring means. As a result, CyanoHAB conditions were assessed frequently covering the entire lake, its key areas, and core positions. Furthermore, by overcoming technical limitations associated with high-precision simulation of the growth-drift-accumulation process of CyanoHABs, such as the unclear drifting process of CyanoHABs and the mechanism of its coastal accumulation, the multi-scale CyanoHAB prediction was realized interconnecting the entire lake and its nearshore areas. The implemented framework has been applied in Lake Chaohu for over three years. It provided high-frequency and high-spatial-resolution CyanoHAB monitoring, as well as its multi-scale and accurate simulation. The application of this framework in Lake Chaohu had significantly improved the accuracies of CyanoHAB monitoring, simulation, and early warning. This advancement holds significant scientific value and offers potential for CyanoHAB prevention and control in eutrophic lakes.

Research on background heat flux of the thermal balance test system based on solar simulator

Abstract In the thermal balance test system based on the solar simulator, the background heat flux of the test system can cause additional heating to the spacecraft, reducing the effectiveness of the thermal test. Hence, it is necessary to conduct in-depth research on the impact of background heat flux through experimental and numerical methods. This paper first measures the background heat flux of the thermal test system based on the KM6 large-scale solar simulator experimentally, which is 35W/m2. Then, a simulation model of the thermal balance test system is established to clarify that the background heat flux originates from the cone chamber and collimating reflector of the solar simulator system. The result provides technical support for achieving a high-precision simulation of the space external heat flux based on the solar simulator.

Underground rescue path planning based on a comprehensive risk assessment approach

Fire incidents in underground environments, such as subway stations and shopping malls, pose significant hazards due to restricted ventilation and confined spaces. These conditions complicate rescue operations, particularly given the unpredictable nature of fires. Effective integration of fire risk assessment into rescue path planning is essential for ensuring both safety and operational efficiency. However, fire risk is inherently complex, varying across both temporal and spatial dimensions, and accurate assessment depends on precise fire situation inference. Despite advancements in fire simulation technologies, inconsistencies in geometric structures between computational units limit seamless integration with path planning models. Consequently, many existing studies rely on simplistic and less reliable linear fire inference models, compromising the safety of rescue operations. This paper addresses these challenges by proposing an underground rescue path planning method based on a comprehensive fire risk assessment, aimed at enhancing both safety and operational efficiency. A fire risk assessment approach, driven by fire situation inference, is introduced, employing a novel grid-matching transformation to capture the spatio-temporal dynamics of fire conditions using high-precision simulation software. Additionally, an improved A* algorithm is developed for real-time rescue path optimization, minimizing path risk based on the results of the risk assessment. The proposed method is validated through a detailed case study, demonstrating its effectiveness and reliability.

Seismic nonlinear interaction and uplifting effects between the nuclear island building and soil

Since the Fukushima nuclear accident, seismic design requirements have increased, necessitating a more refined evaluation of base uplift for weakly anchored nuclear island buildings. The elevated cooling water over 3000 t is a distinguishing feature of third-generation reactor buildings (RBs). To assess potential safety-adverse coupling effects, seismic wave propagation process through viscoelastic soils, discontinuous interfaces, and sloshing water was analysed. To facilitate nonlinear systematic simulation and parametric study, the traditional soil-structure interaction direct methods are improved and programmed on: thickness-independent viscous-spring elements for stable static-dynamic boundary transitions; seismic forces separated from the artificial boundary for flexible mesh planning; elevated water simulated with gravity stacking and hydrodynamic action. A nuclear island region encompassing water-cooled RBs and underlying soil cushion layer was investigated as a typical scenario to reveal rules using the proposed high-precision simulation platform. Non-negligible structural risks and correlations between multiple factors were quantitatively elucidated according to simulation findings. A time-lagged increase in the base overturning moment may occur because of water oscillations. As the water level increases to 85 %, the uplift height increases, adversely affecting the in-structure response spectra. Earthquake-induced intense uplift may lead to an increase in hydrodynamic pressure along the inner wall. The research results support the practical assessment of buildings with water cooling facilities located in soft composite sites with high seismic intensities.

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.

Physics-informed neural network for simulating magnetic field of permanent magnet

Abstract With the rapid development of deep learning, its application in physical field simulation has been widely concerned, and it has begun to lead a new model of meshless simulation. In this paper, research based on physics-informed neural networks is carried out to solve partial differential equations related to the physical laws of electromagnetism. Then the magnetic field simulation is realized. In this method, the governing equation and the boundary conditions containing physical information are embedded into the neural network loss function as constraints, and the backpropagation of neural networks is realized based on automatic differentiation to solve partial differential equations. The high-precision simulation of tile-shaped and rectangular permanent magnet magnetic fields of permanent magnet motors based on physical information neural network is studied, and the error is within 5%. We consider the simulation of magnetic field in two coordinate systems, and realize the joint training of multiple neural networks in multiple sub-domains and different media.

Rigid-flexible coupling dynamic-assisted imbalanced fault diagnosis for helicopter tail transmission system

Helicopters operate in extreme environments, complicating the balanced and accurate acquisition of operational data. Predicting high-precision failures in helicopter tail-drive systems is particularly challenging due to severe data imbalances. To address this, a fault diagnosis method based on rigid-flexible coupling dynamics is proposed. A high-precision simulation model generates source domain data samples, validated by comparing the frequency domain components and RMS values of simulated and tested vibration responses under healthy conditions. An adaptive Local Maximum Mean Discrepancy (LMMD) mechanism aligns features between simulated and tested data. Additionally, the Coordinate-Separable Convolutional ResNet (CSC-ResNet) network is proposed to efficiently learn high-dimensional feature knowledge. Results show the proposed method outperforms others in fault diagnosis accuracy and smoothness, offering a new perspective for fault diagnosis of helicopter tail transmission systems.

Research on Landing Dynamics of Foot-High Projectile Body for High-Precision Microgravity Simulation System

Research on Landing Dynamics of Foot-High Projectile Body for High-Precision Microgravity Simulation System

A Synthetic Aperture Radar Imaging Simulation Method for Sea Surface Scenes Combined with Electromagnetic Scattering Characteristics

Synthetic aperture radar (SAR) simulation is a vital tool for planning SAR missions, interpreting SAR images, and extracting valuable information. SAR imaging is essential for analyzing sea scenes, and the accuracy of sea surface and scattering models is crucial for effective SAR simulations. Traditional methods typically employ empirical formulas to fit sea surface scattering, which are not closely aligned with the principles of electromagnetic scattering. This paper introduces a novel approach by constructing multiple sea surface models based on the Pierson–Moskowitz (P-M) sea spectrum, integrated with the stereo wave observation projection (SWOP) expansion function to thoroughly account for the influence of wave fluctuation characteristics on radar scattering. Utilizing the shooting and bouncing ray-physical optics (SBR-PO) method, which adheres to the principles of electromagnetic scattering, this study not only analyzes sea surface scattering characteristics under various sea conditions but also facilitates the computation of scattering coupling between multiple targets. By constructing detailed scattering distribution data, the method achieves high-precision SAR simulation results. The scattering model developed using the SBR-PO method provides a more nuanced description of sea surface scenes compared to traditional methods, achieving an optimal balance between efficiency and accuracy, thus significantly enhancing sea surface SAR imaging simulations.

Void fraction measurement of slug flow using electromagnetic wave phase sensor based on optimized hybrid dielectric constant

The void fraction is one of the basic parameters to study the gas-liquid two-phase flow, which has great significance to the transportation of oil pipelines and the design of nuclear reactor cooling towers. However, due to the complex and variable nature of gas-liquid two-phase flow, accurately measurement of the void fraction has remained a challenging task in both scientific research and industrial applications. According to the principle of electromagnetic wave propagation, a coaxial line phase sensor was designed, a hybrid dielectric constant model based on the homogeneous flow was established and a void fraction based on hybrid dielectric constant model was proposed. The experiments were carried out on the high-precision gas-liquid two-phase flow simulation experimental setup at Hebei University, China (70 data points), and the void fraction model was inspected and verified. Five typical hybrid dielectric constant correlations were compared. Introducing the frequency weight, optimizing the hybrid dielectric constant model based on the Series – Parallel correlation, a new void fraction prediction correlation of slug flow was proposed and evaluated. The results indicated that the mean absolute percentage error (MAPE) of the new void fraction correlation is 1.02 % and the all of the relative errors are within ±5 % error band.

A semi-analytical method for determining the mode-I delamination R-curve and fiber bridging traction-separation law of Double-double laminates

Delamination, as one of the most prevalent failure modes of composites, was significantly influenced by the interface angles. In contrast to the limited combinations of interface angles found in traditional laminates, DD laminates, with unique sequence [±Φ/±Ψ]rT and diverse interface angles , urgently required extensive experiments and high-precision simulation analyses to delve into the complexities and unique properties of their interlayer performance. However, the calculation process of current method for determining the R-curve and the bridging traction-separation law was time-consuming. This study proposed a simplified semi-analytical method based on the Euler–Bernoulli beam theory that only required recording initial crack length, final crack length, initial compliance and final compliance. The method validation showed that the deviation between the results obtained from the semi-analytical method and the MBT method averaged no more than 2%. In addition, a tri-linear cohesive zone model based on the delamination fracture micro-mechanism was developed combining semi-analytical method. Both the initial load and ultimate load errors between the simulation and experimental results were within 5 N, showing the accuracy of the model and the semi-analytical method. This method provided a simple and effective way to study the delamination propagation behaviors of DD laminates.

N-level complex helical structure modeling method

This paper primarily explores the modeling method of n-level complex helical structures with coal mining machine cables as the research object. The paper first elaborately introduces the modeling method of n-level helix curves based on parametric equations and coordinate transformations, and compensates for the n-level helix curves with corrected pitch, which can obtain more accurate n-level helix curves and improve the accuracy of n-level helix curves modeling. Subsequently, based on this high-precision n-level helix curves modeling method, the paper elaborates on the method of solving pitch and twisting radius of multi-layer helical structure. Calculation scripts were written based on the above methods, which can be used to batch calculate the twisting radius and pitch of each layer structure in multi-layer structures when satisfying the conditions of in-layer tangency, inter-layer tangency, and extrusion deformation, and retain the actual results through logical judgment. Then, based on the above two methods, the paper developed a modeling method for braided structures based on piecewise functions containing fifth-order polynomials, which can effectively avoid the problem of insufficiently dense arrangement of braided lines and easy interference in traditional methods. Finally, a set of modeling tools was developed using C# and Python in Grasshopper to implement the modeling algorithm. Taking the MCPT-1.9/3.3 3120 + 170 + 4 * 10 coal mining machine cable as an example. The cable was modeled using both the method proposed in this paper and the traditional method. Comparative data shows that the method proposed in this paper can reduce errors by 3.31E6 times in the second-level and above helical structures. In addition this paper compares the standard line length, measured line length, and the line length established by the proposed model, showing that the relative errors are both less than 0.1941%. This paper provides a new, systematic, high-precision, and full-process cable modeling method, in which all parameters except the process parameters are accurately solved by equations. It lays a theoretical foundation for the high-precision simulation and intelligent sensing cables, which is of great significance for improving the safety, stability, and efficient development of the coal mining industry. The research results of the paper can not only be applied to the modeling of coal mining machine cables but also can be extended to the modeling of other complex multi-layer helical structures.

Programmable silicon-photonic quantum simulator based on a linear combination of unitaries

Simulating the dynamic evolution of physical and molecular systems in a quantum computer is of fundamental interest in many applications. The implementation of dynamics simulation requires efficient quantum algorithms. The Lie-Trotter-Suzuki approximation algorithm, also known as the Trotterization, is basic in Hamiltonian dynamics simulation. A multi-product algorithm that is a linear combination of multiple Trotterizations has been proposed to improve the approximation accuracy. However, implementing such multi-product Trotterization in quantum computers remains challenging due to the requirements of highly controllable and precise quantum entangling operations with high success probability. Here, we report a programmable integrated-photonic quantum simulator based on a linear combination of unitaries, which can be tailored for implementing the linearly combined multiple Trotterizations, and on the simulator we benchmark quantum simulation of Hamiltonian dynamics. We modify the multi-product algorithm by integrating it with oblivious amplitude amplification to simultaneously reach high simulation precision and high success probability. The quantum simulator is devised and fabricated on a large-scale silicon-photonic quantum chip, which allows the initialization, manipulation, and measurement of arbitrary four-qubit states and linearly combined unitary gates. As an example, the quantum simulator is reprogrammed to emulate the dynamics of an electron spin and nuclear spin coupled system. This work promises the practical dynamics simulations of real-world physical and molecular systems in future large-scale quantum computers.

High-Precision Numerical Simulation Study of the Aging Precipitation Behavior in Al-Li Alloys Based on Improved Kampmann-Wagner Numerical (KWN) Model

High-Precision Numerical Simulation Study of the Aging Precipitation Behavior in Al-Li Alloys Based on Improved Kampmann-Wagner Numerical (KWN) Model

Machine learning for high-precision simulation of dissolved organic matter in sewer: Overcoming data restrictions with generative adversarial networks

Understanding the transformation process of dissolved organic matter (DOM) in the sewer is imperative for comprehending material circulation and energy flow within the sewer. The machine learning (ML) model provides a feasible way to comprehend and simulate the DOM transformation process in the sewer. In contrast, the model accuracy is limited by data restriction. In this study, a novel framework by integrating generative adversarial network algorithm-machine learning models (GAN-ML) was established to overcome the drawbacks caused by the data restriction in the simulation of the DOM transformation process, and humification index (HIX) was selected as the output variable to evaluate the model performance. Results indicate that the GAN algorithm's virtual dataset could generally enhance the simulation performance of regression models, deep learning models, and ensemble models for the DOM transformation process. The highest prediction accuracy on HIX (R2 of 0.5389 and RMSE of 0.0273) was achieved by the adaptive boosting model which belongs to ensemble models trained by the virtual dataset of 1000 samples. Interpretability analysis revealed that dissolved oxygen (DO) and pH emerge as critical factors warranting attention for the future development of management strategies to regulate the DOM transformation process in sewers. The integrated framework proposed a potential approach for the comprehensive understanding and high-precision simulation of the DOM transformation process, paving the way for advancing sewer management strategy under data restriction.

Моделирование нестационарного тепломассопереноса в длинном очистном забое с учетом особенностей нагрева и охлаждения горного оборудования

Adverse microclimatic conditions in mines and shafts negatively affect both health of employees and the safety of workflows as a whole. The existing models to calculate microclimatic parameters can consider technogenic heat emission sources (mining machinery and equipment) only in «operation» and «shutdown» modes. For the first mode, heat emissions are adopted as constant; for the second mode, they are identically zero. In reality, however, thermal inertia is specific to the equipment. It is crucial to consider it for the correct simulation of aerological processes in mine ventilation networks. A dynamic model enabling the calculation of changes in microclimatic parameters (temperature and relative air humidity) for the preset time interval and equipment operation mode in the space of longwall mining and the adjacent fitting forklifts has been suggested in the article to increase the safety of mining operations. The key feature of the model is the registration of non-stationary heat transfer between the air and the power train (the source of heat emissions). The airflow of the motor by ventilation is provided in order to protect the source motor against overheating. Upon the shutdown of the source, the cooling system is switched off, and the source is cooled due to the natural heat exchange with the air. The simulation results are provided as a space-and-time air temperature field. The high-precision simulation is confirmed by insignificant differences between calculated and experimental values. Based on the developed model, an approach to forecasting heat load levels for an employee during a work shift is proposed. The approach is based on the simulation data and the data on the employee’s location during the work shift (planogram-based). The results of the simulation show insignificant differences compared with the data of continuous measurements, which can be explained by the deviation of a real operational process from a modeled planogram. Based on the above-mentioned, it can be concluded that the model is applicable for the assessment of the thermal stress level to which employees are exposed when attending operating working areas.

Investigation of the bubble deflection using graphics processing unit accelerated multiple relaxation time lattice Boltzmann method: The effect of bubble size and liquid viscosity

Bubble deflection is important for bubble motion and bubble mass transfer in multiphase reactors. However, the mechanism triggering the instability is controversial. In this study, we first perform a graphics processing unit-accelerated multiple relaxation time lattice Boltzmann method (MRT-LBM) to simulate the motion process of single bubbles (1.8–8.0 mm) freely rising in stationary liquids with different viscosities. Then, we further analyze the influence of the bubble size and liquid viscosity on the characteristics of the time-dependent bubble motion, including the bubble shape, velocity, and deflection, based on the high-precision numerical simulation results. The results show that the formation and shedding of bubble wake vortices are responsible for the oscillation of the bubble shape. The interaction of bubble wake vortices and bubble shape is the primary cause of bubble deflection. Finally, an empirical model, taking into account the bubble acceleration and deflection angle, is developed to characterize the effect of bubble size and liquid viscosity on the drag coefficient of a rising bubble. This study provides insight into the bubble deflection and the bubble dynamics.