Interaction Force Model Research Articles

Effect of the volume fraction gradient on the phase interaction force model for disperse two-phase flows

Effect of the volume fraction gradient on the phase interaction force model for disperse two-phase flows

Dependent Hidden Markov Model for pedestrian intention prediction: considering Multivariate Interaction Force

Accurately recognizing and predicting pedestrian intentions is crucial for autonomous vehicle safety. However, existing prediction models often fail to comprehensively consider interactions between various traffic elements, resulting in suboptimal accuracy and robustness, especially in complex environments. To address this, we propose a pedestrian intention prediction model combining the Multivariate Interaction Force (MIF) model and a Dependent Hidden Markov Model (DE-HMM) for unsignalized midblock crossings. The MIF model captures dynamic interactions among pedestrians, vehicles, and the environment, while DE-HMM uses MIF data and pedestrian head orientation for predictions. Our model achieves 91.5% accuracy in recognizing crossing intentions, and 88.7% and 85.1% accuracy for predictions 0.5s and 1s ahead, respectively, outperforming current mainstream models and demonstrating strong robustness in special scenarios.

Nonlinear modeling of nanoscale interaction forces between atomic force microscope and carbon nanotubes

This paper introduces a non-linear non-classical model of nanoscale interaction forces between atomic force microscope and carbon nanotubes in a manipulation process. To accurately model the 3D manipulation process, Prandtl-Tomlinson friction model and the Hertz, JKR, and Lundberg contact mechanics theories were employed, taking into account the CNT geometry and manipulation conditions. The applied forces exerted by both the substrate and the probe on the CNT were extracted. The dynamic characteristics of the nanorods and nanotubes were investigated by employing the non-linear modified couple stress Timoshenko beam. Additionally, the cantilever was modeled using the Mindlin plate theory. The findings showed a good agreement between the experimental data of multi-walled carbon nanotube with a diameter of 100 nm, and the theoretical simulations. In addition to critical force and time, CNT bending results were presented using various Timoshenko theories. In order to validate the results of the maximum bending, the outcomes derived from the computational modeling of a polystyrene nanorod using the Euler-Bernoulli and Timoshenko theories were juxtaposed with the existing classical bending outcomes. Finally, the effects of the size parameter were investigated in non-classical polystyrene models. The findings indicated that considering the size effects is important; For instance, the variance between classical and non-classical models can exceed 57% for l/D = 0.5.

Assessment of Agent Avoidance Behavior in the Face of Fire Hazards

ABSTRACT An assessment approach is proposed to assess the injury consequences of evacuation in the face of fire hazards, taking into account the spatial-temporal distribution of fire hazards and the time-varying location of agents. In this study, the diffusion process of fire hazards is simulated first using the fire dynamics simulator (FDS version 6.7.7) software, and an assessment approach is proposed, when fire hazards including toxic gases, thermal radiation, high temperature, and extinction coefficient are considered. Then, a novel fire avoidance model based on the modified social force model is proposed, and the impacts of heat release rate and soot yield on the injury consequences are discussed. The results demonstrate that an increase in heat release rate leads to an increase in the temperature and radiation values near the fire source, which directly raises the injury consequences. Soot yield primarily affects environmental visibility and thus the agent’s evacuation speed, which in turn affects the exposure time in fire hazards and injury consequences. Finally, the proposed fire avoidance model is compared with the existing radiation repulsive force model and the interaction force model between agents and fire. It is concluded that the proposed fire avoidance model can present a more reasonable fire avoidance behavior with significantly less cumulative injuries than the existing fire avoidance models.

Dynamic Modeling and Combination Analysis of Plunger Valve Considering Both Flow and Actuator

The plunger valve has an important role in a large compressor system as its operating characteristics directly affect the aerodynamic boundary condition of the compressor equipment. In this study, dynamic modeling and analysis method of the plunger valve are proposed for an accurate control of the system. By considering the interaction between the dynamic flow in the valve and actuator action, a lumped parameter model for the fluid–structure interaction force and multibody dynamic model of the actuator are developed based on intrinsic correlation parameters. A combination analysis to simultaneously predict valve flow and actuator dynamic characteristics is proposed. The predicted results are in a good agreement with experimental data, which validates the proposed model and analysis method. The analysis results show that the coupling effect between the valve flow and actuator is significant and has an important role in valve control, particularly when the valve opening is smaller. Compared to the experimental data and computational fluid dynamics results, the presented methods are accurate for valve control and effective for prediction of flow rate.

Influence of the abrasive shape-position characteristic on the grinding thermo-mechanical coupling

Grinding is a generally utilized method, removing excess materials through effective abrasives. The grinding abrasives with multiple shape-position characteristics play a dominant role in determining the thermo-mechanical coupling, which may influence the surface quality directly. To investigate this correlated influence mechanism, this paper focuses on the abrasive shape and position characteristic on the grinding thermo-mechanical process with the analytic single abrasive interaction force model by considering the abrasive shape and its distribution information. It can be found that the mapped dynamic grinding temperature is actually discretized on the workpiece surface, which is on account of the diversity of the abrasive shape and its distribution. Moreover, higher spherical and conical abrasive particles, as well as lower pyramid shaped abrasive particle ratios, can generate greater specific grinding energy with a discretized temperature distribution, when compared with a higher proportion of pyramid shaped abrasive. The study can be utilized to provide valuable theoretical foundation for engineering practice by preparing structural wheel and its grinding property.

Unmanned Underwater Vehicle Autonomy and Control near Submarines Using Actively Sampled Surrogates

Many tools have been developed to simulate unmanned underwater vehicle (UUV) motion and autonomous behaviors to evaluate UUV capabilities. However, there is no simulator that performs real-time modeling of the complex hydrodynamic interaction forces that a UUV experiences when operating near a moving submarine. These hydrodynamic interactions must be determined in real time to simulate the launch and recovery of UUVs from submarines. Potential flow models may be fast enough to solve the hydrodynamic interactions in real time, but by oversimplifying the physics and neglecting viscosity, they introduce inaccuracies into the simulations. Computational fluid dynamics (CFD) is capable of accurately modeling these hydrodynamic interactions, but simulations take hours or days to solve. To overcome this obstacle, a machine learning method known as Gaussian process (GP) regression is used to create a surrogate reduced-order-model that predicts the hydrodynamic interactions in real time. The GP regression model is trained by actively sampling CFD simulations in order to accurately model complex hydrodynamic interactions. This new approach allows the GP regression model to be incorporated into a UUV motion simulator and evaluate how the UUV is affected by the hydrodynamic interactions. Operating envelopes are developed that outline regions where the UUV safely overcomes the hydrodynamic interactions and where the UUV is overpowered and collides with the submarine. By incorporating this surrogate model into the autonomy architecture, new autonomous behaviors are created that compensate for the hydrodynamic interactions by adjusting the desired UUV heading and speed which allows it to better stay on course.

Euler-Euler CFD simulation of high velocity gas injection at pool scrubbing conditions

Pressure relief by blowdown is one of the most important measures to prevent excessive pressures in the primary circuit or containment in severe nuclear accidents. Pool scrubbing can significantly reduce the release of radioactive materials, e.g., aerosols, to the environment during the pressure relief. The decontamination factor indicating the particle retention efficiency depends, among other factors, on the hydrodynamic conditions of the gas-liquid two-phase flow inside the pool. In the present work, the hydrodynamics in two typical pool scrubbing experiments is investigated with the two-fluid model, and the influence of some key factors including bubble diameter, nozzle submergence as well as interaction models are analysed. One case is a rectangular pool and the other is a cylindrical column, and their injection Weber number is around 2×103 and 4×105, respectively. The numerical results show that as the distance from the nozzle exit increases, the void fraction and velocity field expand from the central region, where the nozzle is located, to the whole cross section. The profile and its development depends largely on the bubble size and the interaction force model. It reveals that in the monodisperse simulation, the tuning of bubble diameter is necessary for achieving good agreement, although it is difficult for high velocity gas injection. More information is required to properly describe the bubble size distribution as well as its evolution in pool scrubbing conditions. Furthermore, the experimental data show clear drag reduction in the bubble swarm generated by the gas jet, and the mechanism and model improvement possibilities need to be investigated.

Development of Wearable Tactile Device with Pressure Presentation and Interaction Force Model for Realization of Remote Handshake

Development of Wearable Tactile Device with Pressure Presentation and Interaction Force Model for Realization of Remote Handshake

Insight on bulk shear strength parameters of clay using discrete element approach incorporating physics-based interparticle force model

This paper aims to provide insight on factors affecting the bulk shear strength parameters of clay, i.e., the cohesion and internal friction as well as the effects of memory of preconsolidation pressure. A unique Discrete Element Method (DEM) model is built on platy particles with customized particle interaction force model. The particle interaction force model considers non-contact forces (such as the long-range electrostatic repulsion, short-range van der Waals attraction) as well as the direct contact force. The long-range electrostatic forces are calibrated by measurement with Atomic Force Microscope (AFM). Parameters for direct particle contacts of the regular DEM contact model, such as the contact stiffness and the friction coefficient, are calibrated by use of experimental consolidation and direct shear testing data. Computational simulations are conducted on digital clay specimen subjected to virtual direct shear tests. The predicted experimental responses of the digital specimens are consistent with typically observed in experiments including the shear stress-shear strain relationship, volumetric contraction and dilation, shear band formation, etc. From the stress–strain curves, the soil strength parameters are obtained with common experimental criteria. The DEM simulation results show that higher preconsolidation pressure drives more particles to overcome non-contact force into direct contacts and consequently bonding by van der Waals force. Consequently, the bulk cohesion of clay increases with increasing preconsolidation pressure. The results show that bulk cohesion strength is mainly attributed to the attractive interparticle force as well as the interlocking of platy particle, while the bulk internal friction angle is affected by the particle friction coefficient and particle fabric. Overall, the simulation results indicate the experimentally observed macroscopic shear strength parameters c and φ are linked to the microscope characteristics of soil particles and their mutual interactions. The results offer insight on the microscopic properties of particles on the bulk macroscopic strength behaviors. Besides, this work demonstrates a new strategy for simulation-based prediction of bulk soil strength parameters, by incorporating microscale characterization of the interparticle interactions and particle fabric into the particle-based DEM model.

Short-range repulsive force model for near-contact interactions of bubbles.

We introduce a short-range repulsive force model to tackle near-contact interactions when the collision occurs between bubbles. In contrast to the previous numerical method adopting the adaptive mesh refinement technique, such a mesoscale model can be applied to a relatively coarse mesh, which can prevent the nonphysical coalescence between bubbles without excessive mesh refinement. We assume that the repulsive force is inversely proportional to the third power of distance, as a reasonable approximation to the short-range phase interactions. The model is validated against two different experiments. In both experiments, two identical bubbles rising side by side were considered. First, the experiment performed in a water-glycerol mixture helps determine the model parameter K. Second, three typical combinations of bubble size and initial separation distance are simulated, presenting different types of interactions, i.e., coalescence, bouncing coalescence, and bouncing separation, agreeing well with the second experiment, which was performed in pure water. Owing to its simplicity, this model can be easily implemented into existing codes, and it can be extended to the case with multiple bubbles or droplets.

Identification of a Practical Digital Twin for Simulation of Machine Tools

A practical digital twin for machine tools is proposed in this study. The proposed digital twin is capable of time-domain simulation of machine tools and consists of a controller model, machining process model, and machine dynamic model. To predict the quality of the machined surface after the finishing processes, a precise dynamic model is required. The developed dynamic model consists of an interaction force model, vibration model, and friction force model. A linear auto regressive with exogenous inputs (ARX) model is adopted for the interaction and vibration models. Based on a systematic analysis of the disturbance forces of the machine tool, the friction characteristics are extracted to a displacement-dependent friction model and velocity-dependent friction model. A nonlinear Hammerstein model is adopted to identify the friction. Online identification systems based on the recursive least-squares (RLS) method are developed and tested for each model.

Research on accurate modeling of hydrodynamic interaction forces on AUVs operating in tandem

The hydrodynamic interaction force between autonomous underwater vehicles (AUVs) operating in tandem can adversely affect the hydrodynamic prediction of individual AUVs and the formation control of the tandem fleet. Accurate modeling of hydrodynamic interaction forces is crucial to the model-based controller design of AUVs. In this paper, we innovatively propose a modeling method that can describe the hydrodynamic interaction relationship accurately and continuously (when the spacing between adjacent AUVs changes). First, an accurate hydrodynamic model for individual AUVs in tandem fleets is established by modifying the typical model through the consideration of memory effects. Second, a model of hydrodynamic interaction forces is derived by subtracting hydrodynamic forces acting on a single AUV operating independently from those acting on an AUV operating in tandem. To enable this model to continuously describe the hydrodynamic interaction relationship when the spacing changes, this model is further derived by taking the spacing as an independent variable based on the parameter conversion method. Finally, planar motion mechanism (PMM) tests are carried out using the computational fluid dynamics (CFD) method to verify the accuracy and continuity of the proposed modeling method. The results show that compared with the typical model, the average error of hydrodynamic forces predicted by the proposed model is reduced by 5.36%, which verifies the feasibility and effectiveness of the proposed modeling method.

Mechanism study on spreading dynamics of nanofluids droplet coupled with thermal evaporation

Droplet-wall interactions occur in many advanced engineering technologies, such as 3D printing, spray coating, and even quantum light-emitting diode(QLED). Nanofluids (colloids of nanoparticles) are becoming increasingly important working fluids for more excellent performances. Computer modeling of fluid flows with the large deformation of free surface usually presents great challenges for conventional grid-based numerical methods. The smoothed particle hydrodynamics (SPH) method has been widely used in such droplet dynamics because of its meshless Lagrange methods, as well as the applicability to macro-scale simulation. In the paper, the numerical model based on the SPH method is presented to predict the detailed outcome of sessile and transient nanofluid droplets. The surface tension of droplets is taken into consideration by the inter-particle interaction force (IIF) model for its advantages in modeling the contact angle during wetting. The properties of nanofluids are obtained by averaging the properties of base fluids and nanoparticles, based on the assumption that nanofluids of low concentration are a homogeneous mixture and Newtonian fluid. The assumption is proposed based on the rheological measurement of nanofluids. Heat conduction is added into the SPH model when the impacted surfaces are heated, and the evaporation is modeled by “extinguishing” the SPH particles. The SPH model predicts the evolution of the droplet surface from spreading to receding, even rebounding on the wall. Moreover, the normalized droplet diameters predicted by the SPH model agree well with the experimental data from the high-speed camera. The proposed SPH models have been used to study the effects of heating temperatures and nanofluids concentration on droplet-wall interactions. The modified SPH models can handle the nanofluids droplet dynamics, along with large deformation, thermal transfer, and evaporation. The results demonstrate that the SPH model is a powerful tool to study the complex droplet dynamics and to predict the patterns of droplet deformation as well as the thermal distribution.

A machine learning-based interaction force model for non-spherical and irregular particles in low Reynolds number incompressible flows

In this study, interaction force of non-spherical particles in low Reynolds number gas-solid flow is investigated by neural network approaches. An artificial neural network (ANN) model is developed to correlate the non-spherical particle shape and the flow conditions with the interaction force. To define the particle shape, spherical harmonic expansion is applied. Furthermore, variational autoencoder model is then used to extract latent geometric features. The latent vector is utilized as an input with the Reynolds number for the ANN. The interaction force data, which is used as output data of the ANN, is obtained by particle resolved direct numerical simulation for 5200 non-spherical particles. The proposed model enables unsupervised extraction for non-spherical particle shapes and accurate predictions on the interaction force without heavy computation. This study provides the model that can explain complicated shapes of particles and be applied to a large scale, computational fluid dynamics simulation.

Semi-Autogenous Wet Grinding Modeling with CFD-DEM

The paper highlights the features of constructing a model of a wet semi-autogenous grinding mill based on the discrete element method and computational fluid dynamics. The model was built using Rocky DEM (v. 4.4.2, ESSS, Brazil) and Ansys Fluent (v. 2020 R2, Ansys, Inc., United States) software. A list of assumptions and boundary conditions necessary for modeling the process of wet semi-autogenous grinding by the finite element method is presented. The created model makes it possible to determine the energy-coarseness ratios of the semi-autogenous grinding (SAG) process under given conditions. To create the model in Rocky DEM the following models were used: The Linear Spring Rolling Limit rolling model, the Hysteretic Linear Spring model of the normal interaction forces and the Linear Spring Coulomb Limit for tangential forces. When constructing multiphase in Ansys Fluent, the Euler model was used with the primary phase in the form of a pulp with a given viscosity and density, and secondary phases in the form of air, crushing bodies and ore particles. The resistance of the solid phase to air and water was described by the Schiller–Naumann model, and viscosity by the realizable k-epsilon model with a dispersed multiphase turbulence model. The results of the work methods for material interaction coefficients determination were developed. A method for calculating the efficiency of the semi-autogenous grinding process based on the results of numerical simulation by the discrete element method is proposed.

Human-centred adaptive control of lower limb rehabilitation robot based on human–robot interaction dynamic model

A rehabilitation robot can effectively alleviate the shortcomings and deficiencies of traditional treatments. The early stages of rehabilitation training use passive control based on a predefined trajectory. The goal of passive control is to control the motion of the robot, rather than the real motion of the human. However, the human and robot are connected by bands; thus, errors exist between them, and these errors affect the outcome of the rehabilitation training. This study proposes human-centred adaptive control of a lower limb rehabilitation robot based on a dynamic model of human–robot interactions. An equivalent spring model in three-dimensional space is proposed for expressing the interaction torque between the human and robot, reflecting the torque exerted by the robot on the human. A dynamic model for the human–robot system is established based on the human–robot interaction model. To overcome the uncertainty regarding the parameters of the human limbs and robots and that of the stiffness coefficient in the interaction force model, an adaptive controller is designed, and the stability of the system is analysed. The simulation results indicate the effectiveness of the controller.

Control of Teleoperation Systems in the Presence of Varying Transmission Delay, Non-passive Interaction Forces, and Model Uncertainty

SUMMARYThis paper addresses robust stability and position tracking problems in teleoperation systems subject to varying delay in the communication medium, uncertainties in the models of manipulators, and non-passive interaction forces in the terminations. Fixed-structure nonlinear control law is developed based on the notion of Interconnection and Damping Assignment Passivity-Based Control (IDA-PBC) scheme. Then, utilizing the Lyapunov–Krasovskii theorem, sufficient conditions are derived in terms of Linear Matrix Inequalities (LMIs) to tune the controller parameters. Differently from literature, the objectives are achieved without requirement for any passive parts in the model of interaction forces. Comparative simulations and experimental results demonstrate the applicability and superiority of the proposed method.

A New Interaction Force Model of Gold Nanorods Derived by Molecular Dynamics Simulation.

Interactions between nanoparticles is one of the key factors governing their assembly for ordered structures. Understanding such interactions between non-spherical nanoparticles and developing a quantitative force model are critical to achieving the ordered structures for various applications. In the present study, the non-contact interactions of two identical gold nanorods (AuNRs) with different aspect ratios have been studied by molecular dynamics simulation. A new interaction potential and force model for two nanorods approaching side-by-side has been proposed as a function of particle surface separation and their relative orientation. In addition, the interaction potentials of two nanorods approaching in other typical orientation configurations (i.e., crossed, head-to-head and head-to-side) have also been investigated.

Passivity-based control of nonlinear teleoperation systems with non-passive interaction forces

This paper addresses the problem of asymptotic stability and position tracking in nonlinear teleoperation systems interacting with non-passive operator and environment. A nonlinear control law which is designed based on Interconnection and Damping Assignment Passivity-Based Control (IDA-PBC) scheme, uses the positions and velocities of the joints of manipulators to provide asymptotic stability of tracking errors. Using the Lyapunov–Krasovskii theorem, sufficient conditions are derived in terms of computationally amenable Linear Matrix Inequalities (LMIs), to tune the controller parameters in the presence of asymmetrical varying time delay in the communication channel. The proposed controller synthesis methodology requires no known passive part in the dynamical model of interaction forces. Moreover, using the integral control notion, the asymptotic stability of the synchronization errors is assured. Comparative simulation results are presented to demonstrate the superiority of the proposed method compared to some rival ones. Finally, experimental results from a laboratory teleoperator are reported to confirm the applicability of the introduced scheme.