Artificial Force Research Articles

Quantum Chemical Model Calculations of Adhesion and Dissociation between Epoxy Resin and Si-Containing Molecules

There is no doubt that when solid surfaces are modified, the functional groups and atoms directly bonded to solid atoms play a major role in adsorption interactions with molecules or resins. In this study, the adhesion and dissociation between epoxy resin and molecules containing Si atoms were analyzed. The analysis, conducted in contact with the solid surface of silicon, utilized quantum chemical calculations based on a molecular model. We compared some Si-containing molecular models to test quantum chemical calculations that contribute to the study of adhesion and dissociation between epoxy resins and solid surfaces somehow other than simple potential energy curve calculations. The AFIR (artificial force induced reaction) method, implemented in the GRRM (global reaction route mapping) program, was employed to separate an epoxy resin model molecule and three types of silicon compounds (Si(CH3)2(OH)2, Si(CH3)4, and (CH3)2SiF2) in three directions, determining their minimum dissociation energy when changing the applied energy by 2.5 kJ/mol. In systems with weak hydrogen bonds, such as Si(CH3)4 or (CH3)2SiF2, the energy required for dissociation was not large; however, in systems with strong hydrogen bonds, such as Si(CH3)2(OH)2, dissociation was more difficult in the vertical direction. Although anisotropy due to hydroxyl groups was calculated in the horizontal direction, dissociation remained relatively easy.

Topology optimization of regenerative cooling structures under high Reynolds number flow with variable thermo-physical properties

In the design of thermal protection system for hypersonic vehicles, the efficient convective heat transfer within regenerative cooling channels plays a critical role in maintaining their thermal performance. This study focuses on the topology optimization (TO) of the cooling channels that operate at high Reynolds number and have variable thermo-physical properties. A novel approach is introduced to enhance the density-based method by incorporating an effective artificial force correction and tabulating the temperature-dependent thermal properties. Several topology-optimized cooling layouts were generated to minimize the maximum temperature within the design domain while considering different power dissipation constraints. This confirms the validity of the proposed lumped correction term in momentum equation accounting both viscous and convective body forces. Regarding the thermal performance of the optimized layouts, the staggered arrangement of cellular ribs in the TO channel was found to induce multiple flow separations and promote turbulent mixing, thereby improving heat transfer efficiency and mitigating the thermal acceleration effect. Conjugate heat transfer calculations revealed that the optimal topology-optimized channel achieved a 24.3% improvement in overall thermal performance while being 15.3% lighter than the straight channel design. Furthermore, the optimal topology optimized layout consistently outperformed the straight channel design by 6.6% to 24.3% in terms of the overall thermal performance across a wide range of heat flux distribution and mass flow rate conditions. This investigation highlights the effectiveness of topology optimization in designing regenerative cooling structures featuring high Reynolds number hydrocarbon thermal fluid flow.

Adjoint-based shape optimization for compressible flow based on volume penalization method

AbstractReducing the resistance of compressible flow around a blunt body is of great interest in engineering applications, while an efficient shape optimization method for compressible flows remains far from well established, especially for high Mach numbers. To this end, a volume penalization method for simulating compressible flows past a no-slip and isothermal solid is established by introducing an artificial body force and a heat sink into the governing equations. The level-set functions are introduced as design variables, and the cost functional is defined as the total drag acting on the solid. Then, a continuous adjoint-based shape optimization algorithm for drag reduction is developed by deriving the adjoint equations, the adjoint boundary conditions, and the shape update formula. Both the forward and adjoint simulations are verified by existing studies. The results show that the relative deviations of the drag coefficients obtained in the present study from those reported in the reference studies are around 5% at most, and also a comparable drag reduction rate and also optimal shapes can be reproduced by the present optimization scheme for benchmark problems at relatively low Mach numbers considered in previous studies. Finally, the present method is applied to shape optimization of an initially two-dimensional cylinder and also a three-dimensional sphere in the transonic regime of Ma∞ = 1.2. The drag reduction of over 20% is achieved for both two-dimensional and three-dimensional cases.

Pizza3: A general simulation framework to simulate food-mechanical and food-deconstruction problems

Current mesh-based simulation approaches face significant challenges in continuously modeling the mechanical behaviors of foods through processing, storage, deconstruction, and digestion. This is primarily due to the limitations of continuum mechanics in dealing with systems characterized by free boundaries, substantial deformations, mechanical failures, and non–homogenized mechanical properties. The dynamic nature of food microstructure and the transformation of the food bolus, in relation to its composition, present formidable obstacles in computer-aided food design. In response, the Pizza3 project adopts an innovative methodology, utilizing an explicit microstructural representation to construct and subsequently deconstruct food products in a modular, Lego-like fashion. Central to this simulation approach are “food atoms”, conceptualized from the principles of smoothed particle hydrodynamics. These units are significantly larger than actual atoms but are finely scaled to represent both solid and liquid states of food faithfully. In solid phases, food atoms interact via pairwise forces akin to bond-peridynamic methods, thus extending the capabilities of continuum mechanics to encompass large deformations and fracturing phenomena. For liquids, the model employs artificial conservative and dissipative forces, enabling the simulation of a variety of phenomena within the framework of partial compressibility. The interaction dynamics between rigid and soft objects and fluids are accurately captured through Hertzian contact mechanics, offering a versatile parameterization applicable to impermeable (but possibly penetrable) surfaces and enforcing no-slip conditions. The efficacy of this framework is showcased through the successful modeling of three time-dependent 3D scenarios, each rigorously validated against established analytical and experimental models. Advancing beyond these initial applications, the framework is further extended to more intricate cases inadequately addressed in current literature. This extension sheds light on the underlying mechanisms of in-mouth texture perception, offering new insights and tools for food engineering and design.

Chemography-guided analysis of a reaction path network for ethylene hydrogenation with a model Wilkinson's catalyst.

Visualization and analysis of large chemical reaction networks become rather challenging when conventional graph-based approaches are used. As an alternative, we propose to use the chemical cartography ("chemography") approach, describing the data distribution on a 2-dimensional map. Here, the Generative Topographic Mapping (GTM) algorithm - an advanced chemography approach - has been applied to visualize the reaction path network of a simplified Wilkinson's catalyst-catalyzed hydrogenation containing some 105 structures generated with the help of the Artificial Force Induced Reaction (AFIR) method using either Density Functional Theory or Neural Network Potential (NNP) for potential energy surface calculations. Using new atoms permutation invariant 3D descriptors for structure encoding, we've demonstrated that GTM possesses the abilities to cluster structures that share the same 2D representation, to visualize potential energy surface, to provide an insight on the reaction path exploration as a function of time and to compare reaction path networks obtained with different methods of energy assessment.

Peridynamics contact model: Application to healing using phase field theory

This paper presents a contact algorithm in non-ordinary state-based peridynamics (NOSB-PD) framework and its application in healing phase field (HPF) theory. The idea here is to exploit the nonlocality in PD to model the contact between two deformable bodies. The proposed method does not require artificial short-range force or additional degrees of freedom, e.g., Lagrange multiplier, which are often used in the conventional classical and PD contact models. In the regions where contact is likely to take place, neighbor search is performed at every time step and extra particles entering the horizon are identified. These extra particles form artificial bonds which transfer forces only in compression. This feature is essential for rebound simulation. Envisioning surface-to-surface bonding as the opposite process of cracking, we propose an HPF theory to model high velocity impact induced bonding between two material bodies. Here an HPF based bonding criterion is postulated and integrated with the proposed contact algorithm. The solution of the governing equations is obtained using the fourth order Runge-Kutta method. The efficacy of the proposed contact algorithm is demonstrated by simulations of impact and rebound of two plates, two cylinders, and cylinder with rectangular prism and comparing the energy time histories with finite element solutions obtained using ANSYS®. The potential of the proposed HPF theory is demonstrated through simulation of impact of two plates where the plates rebound when the impact velocity is below a critical value, and above that velocity, the plates join with each other.

Synergy and medial effects of multimodal cueing with auditory and electrostatic force stimuli on visual field guidance in 360° VR

This study investigates the effects of multimodal cues on visual field guidance in 360° virtual reality (VR). Although this technology provides highly immersive visual experiences through spontaneous viewing, this capability can disrupt the quality of experience and cause users to miss important objects or scenes. Multimodal cueing using non-visual stimuli to guide the users’ heading, or their visual field, has the potential to preserve the spontaneous viewing experience without interfering with the original content. In this study, we present a visual field guidance method that imparts auditory and haptic stimulations using an artificial electrostatic force that can induce a subtle “fluffy” sensation on the skin. We conducted a visual search experiment in VR, wherein the participants attempted to find visual target stimuli both with and without multimodal cues, to investigate the behavioral characteristics produced by the guidance method. The results showed that the cues aided the participants in locating the target stimuli. However, the performance with simultaneous auditory and electrostatic cues was situated between those obtained when each cue was presented individually (medial effect), and no improvement was observed even when multiple cue stimuli pointed to the same target. In addition, a simulation analysis showed that this intermediate performance can be explained by the integrated perception model; that is, it is caused by an imbalanced perceptual uncertainty in each sensory cue for orienting to the correct view direction. The simulation analysis also showed that an improved performance (synergy effect) can be observed depending on the balance of the uncertainty, suggesting that a relative amount of uncertainty for each cue determines the performance. These results suggest that electrostatic force can be used to guide 360° viewing in VR, and that the performance of visual field guidance can be improved by introducing multimodal cues, the uncertainty of which is modulated to be less than or comparable to that of other cues. Our findings on the conditions that modulate multimodal cueing effects contribute to maximizing the quality of spontaneous 360° viewing experiences with multimodal guidance.

A STUDY ON ROLE OF AUTOMOBILE INDUSTRY IN INDIA AND ITS CUSTOMERS SATISFACTION

Client satisfaction is defined by ISO 9000 as the opinion of druggies regarding how well a product satisfies its requirements. A veritably particular evaluation is that of client satisfaction. The main factor propelling the expansion of the Indian machine assiduity is the rise in demand for buses and other vehicles, which is fueled by rising inflows. The development of accessible prepayment plans and customized backing options has also backed in the expansion of the bus assiduity. Encyclopedically, the automotive sector is a significant artificial and profitable force. It produces 60 million motorcars and exchanges annually, which regard for about half of the oil painting consumed worldwide. There are 4 million direct jobs in this assiduity, and numerous further circular jobs are created. Indeed if a lot of big businesses struggle with overcapacity

Enhancing heat transfer in power transformer radiators via thermo-fluid dynamic analysis with periodic thermal boundary conditions

The efficient dissipation of energy losses in electrical power transformers is crucial to prevent overheating of their windings and ensure proper functioning. In this study, we investigate the thermal design of a 30 [MVA], 132/34.5/13.8 [kV] power transformer radiator operating in Oil Natural-Air Natural mode by using Computational Fluid Dynamics (CFD) simulations. We introduce artificial body forces in the momentum Navier-Stokes equation to analyze the thermo-fluid dynamic performance of secondary transverse flows. Additionally, we propose a numerical scheme to solve the thermal equation with periodic boundary conditions using a reduced length of the oil channel, allowing for the decoupling of the thermal and fluid dynamic problems. To enhance the heat transfer, we propose the use of turbulators and wall indentation arrangements. Through our simulations, we analyze the effects of these enhancements on the cooling capacity of the transformer radiator. Our results demonstrate that these modifications increase the heat transfer coefficient and improve the cooling capacity of the radiator. Furthermore, we propose manufacturing considerations for the turbulators and wall indentation arrangements to ensure their practicality. Our findings provide valuable insights into the thermal design of power transformer radiators and demonstrate the effectiveness of turbulators and wall indentation arrangements in enhancing their cooling capacity.

ПРОБЛЕМА СООТНОШЕНИЯ МАТЕРИИ И СОЗНАНИЯ С ТОЧКИ ЗРЕНИЯ СОВРЕМЕННОЙ ТЕОРИИ ИНФОРМАЦИИ

In the article, the authors propose to consider the problem of the relationship between matter and consciousness from a slightly different angle. Known. that the results obtained to date in the field of studying neural networks and artificial intelligence force us to largely reconsider the content of the concept of “consciousness”.The emergence of modern information processing systems, including the most highly developed ones, essentially represent certain fundamental properties inherent in matter as such. This conclusion is based on experimental data proving that a complex system of any nature becomes such provided that it is converted into a neural network or its analogue. In this context, “consciousness” corresponds to only one of the levels of the complex hierarchy of systems of perception and information processing that permeate the universe from the physical and chemical level to the level of the Universe.It has been suggested that, in accordance with existing well-known theories about the world spirit, it is permissible to interpret the so-called World Spirit (according to Hegel) by considering the Universe as a kind of neural network that forms a certain system of perception and processing of information.

Organ registration from partial surface data in augmented surgery from an optimal control perspective

We address the problem of organ registration in augmented surgery, where the deformation of the patient’s organ is reconstructed in real-time from a partial observation of its surface. Physics-based registration methods rely on adding artificial forces to drive the registration, which may result in implausible displacement fields. In this paper, we look at this inverse problem through the lens of optimal control, in an attempt to reconstruct a physically consistent surface load. The resulting optimization problem features an elastic model, a least-squares data attachment term based on orthogonal projections, and an admissible set of surface loads defined prior to reconstruction in the mechanical model. After a discussion about the existence of solutions, we analyse the necessary optimality conditions and use them to derive a suitable optimization algorithm. We implement an adjoint method and we test our approach on multiple examples, including the so-called Sparse Data Challenge . We obtain very promising results, that illustrate the feasibility of our approach with linear and nonlinear models.

Energy-optimal adaptive artificial potential field method for path planning of free-flying space robots

Aiming at planning a collision-free path for a free-flying space robot (FFSR), an energy-optimal collision avoidance strategy is proposed using the adaptive artificial potential field (AAPF) approach. To address the goals non-reachable with obstacles nearby (GNRON) issues of artificial potential field (APF), an adaptive and secure path planning method is proposed by incorporating a smooth decay function into the repulsive potential field. Meanwhile, a time-varying shaping parameter of attractive potential field is optimized combined with the state-dependent Riccati equation technique to reduce the energy cost of the FFSR. In case the system gets trapped in local minimum, an escape force is elaborately designed to replace artificial potential force based on optimal theory, whose direction vector guides the FFSR to jump out of the local minimum with minimal energy. Finally, simulation results on a planar FFSR demonstrate the effectiveness of the proposed methodology and show improved performance compared with the existing artificial potential field (APF) in terms of escaping local minimum and reducing energy consumption.

Updated Lagrangian nonlocal general particle dynamics for large deformation problems

The traditional general particle dynamics (GPD) has been successfully applied in modeling fracture propagation, frictional contact and stick–slip problems in rocks. In this study, the updated Lagrangian nonlocal general particle dynamics (UL-NGPD) method is proposed to solve large deformation problems. In the UL-NGPD, the continuity equation and momentum equation are reformulated in the integro-differential formulation by introducing nonlocal theories in the updated Lagrangian framework. The artificial viscosity and artificial force state are utilized to enhance the numerical stability and accuracy in modeling large deformation. The nonlocal velocity gradient in the deformed configuration is used to update the Cauchy stress rate from the Drucker-Prager elasto-plastic constitutive model with strain-softening behaviour for solids. The UL-NGPD paradigm is numerically implemented through an explicit Predictor-Corrector scheme for high-performance computing. The stability and accuracy of the UL-NGPD are verified by numerical tests on compression test, slope stability analysis and aluminum bar collapse experiment. Thereafter, simulations of granular soil collapse and retrogressive landslide in sensitive clays are presented to demonstrate its efficacy and robustness in modeling challenging geotechnical problems involving large deformation. The numerical results show that the proposed UL-NGPD is powerful and suitable for analyzing large deformation problems in geotechnical engineering.

Artificial neural network-based ground reaction force estimation and learning for dynamic-legged robot systems.

Legged robots have become popular in recent years due to their ability to locomote on rough terrains; these robots are able to walk on narrow stepping-stones, go upstairs, and explore soft ground such as sand. Ground reaction force (GRF) is the force exerted on the body by the ground when they are in contact. This is a key element and is widely used for programming the locomotion of the legged robots. Being capable of estimating the GRF is advantageous over measuring it with the actual sensor system. Estimating allows one to simplify the system, and it is meant to be capable of prediction, and so on. In this article, we present a neural network approach for GRF estimation for the legged robot system. In order to fundamentally study the GRF estimation of the robot leg, we demonstrate our approach for a single-legged robot with a degree of freedom (DoF) of two with hip and knee joints on a flat-surface. The first joint is directly driven from the actuator, and another joint is belt-pulley driven from the second actuator to take advantage of the long range of motion. The neural network is designed to estimate GRF without attaching force sensors such as load cells, and the encoder is the only sensor used for the estimation. We propose a two-staged multi-layer perceptron (MLP) solution based on supervised learning to estimate GRF in the physical-world. The first stage of the MLP model is trained using datasets from the simulation, enabling it to estimate the simulation-staged GRF. The second stage of the MLP model is trained in the physical world using the simulation-staged GRF obtained from the first stage MLP as the input. This approach enables the second stage MLP to bridge the simulation to the physical world. The root mean squared error (RMSE) is 0.9949 N on the validation datasets in the best case. The performance of the trained network is evaluated when the robot follows trajectories that are not used in training the two-stage GRF estimation network.

COOPERATIVE SOURCE DETECTION USING AN OPTIMIZED DISTRIBUTED LEVY FLIGHT ALGORITHM

Source signal detection plays important roles in many real-world target searching problems. Source detection is necessary before a full search process utilizing the detected signal can be performed where minimizing the detection time and maximizing the search space exploration or coverage are the main problems. In this paper, an optimized Levy Flight algorithm known as a Distributed Levy Flight (DLF) for swarm agents is proposed. The DLF algorithm is optimized by means of repulsive artificial potential force to disperse the agents in order to optimize the search space coverage and detection time. Additionally, to integrate cooperative behavior, an artificial attractive force is used to maintain communication among the agents. The results showed that the proposed DLF algorithm successfully improve detection time (113.1s) and area coverage (78.3%) compared to the existing algorithms: Brownian Walk (325.5s, 31.7%), Correlated Random Walk (356.2s, 35.1%), Levy Flight (201.3s, 56.6%), Levy Flight with Artificial Potential Fields (151.9s, 70.2%).

Topological Design Optimization Approach for Winding Oil Flow Paths in Oil-Natural Air-Natural Transformers Based on a Fluidic-Thermal Coupled Model

Power transformers are a critical component in transmission and distribution systems. To limit the temperature rise to extend the life-cycle while operating with enough reliability and controllability of a transformer, the design of the cooling system has attracted extensive research attention. In this paper, a topology optimization (TO) methodology is presented for designing the coolant flow paths in a prototype oil-natural air-natural (ONAN) power transformer to maximize the winding heat dissipation capacity without any compromise on the flow resistance. First, the thermal and fluid flow characteristics in both the winding and the radiator of the prototype transformer are numerically investigated through a fluidic-thermal coupled field approach. The preliminary cooling effectiveness of the oil circulation system is initialized. Second, a material-density-based TO scheme is employed to realize the optimal design of the oil baffle structures. In the TO optimization, artificial Darcy frictional forces are applied to the solidified cells to block their internal flows in the fluidic calculations, while the thermal conduction coefficients in those cells are enhanced to separate the baffles from the flowing oil in thermal analyses. Finally, the fluidic and thermal coupled fields of the prototype transformer winding region with structurally optimized oil baffles are numerically investigated to validate the TO effectiveness.

Application of Cross model for granular flow and impact analysis using three-dimensional B-spline material point method

Granular flow and impact, such as landslides and debris flows, are typical problems involving large deformations of non-Newtonian free surfaces, which are of great interest in geological engineering and also pose challenges for traditional mesh-based numerical methods. As an enhancement of the traditional Material Point Method (MPM), the B-Spline Material Point Method (BSMPM) can not only effectively reduce mesh-crossing and quadrature errors, but also facilitate the tracking and capturing of free surfaces and contact interfaces. In this paper, the non-Newtonian general Cross model, the rheological parameters of which are determined by the Bingham model and the Mohr-Coulomb yield criterion, is introduced into the three-dimensional BSMPM (3D BSMPM) for simulating granular flow and impact problems. Interparticle effects of granular materials are represented by artificial damping forces. Dynamic simulations are carried out on the collapse of sand column and glass beads, the flow of bentonite suspensions, and the impact between granular mass and elastic obstacles. The overall evolution of granular flow and impact behavior are presented and compared with existing experimental and/or original MPM results. It is found that the proposed method well reproduces the overall process of granular flow and impact behavior, including its various stages of formation, acceleration, deceleration, and deposition, as well as the impact pressure. The results show that the granular flow and impact behavior can be well represented by the proposed 3D BSMPM with the Cross rheological model, demonstrating the effectiveness of the proposed method in simulating complicated environmental fluid dynamics.

A Combined Reaction Path Search and Hybrid Solvation Method for the Systematic Exploration of Elementary Reactions at the Solid-Liquid Interface.

We present a combined simulation method of single-component artificial force induced reaction (SC-AFIR) and effective screening medium combined with the reference interaction site model (ESM-RISM), termed SC-AFIR+ESM-RISM. SC-AFIR automatically and systematically explores the chemical reaction pathway, and ESM-RISM directly simulates the precise electronic structure at the solid-liquid interface. Hence, SC-AFIR+ESM-RISM enables us to explore reliable reaction pathways at the solid-liquid interface. We applied it to explore the dissociation pathway of an H2O molecule at the Cu(111)/water interface. The reaction path networks of the whole reaction and the minimum energy paths from H2O to H2 + O depend on the interfacial environment. The qualitative difference in the energy diagrams and the resulting change in the kinematically favored dissociation pathway upon changing the solvation environments are discussed. We believe that SC-AFIR+ESM-RISM will be a powerful tool to reveal the details of chemical reactions in surface catalysis and electrochemistry.

Systematic Search for Thermal Decomposition Pathways of Formic Acid on Anatase TiO2 (101) Surface**

AbstractIn this study, the reaction pathways for the thermal decomposition of formic acid on the anatase TiO2 (101) surface were systematically investigated. The investigation was carried out using a single‐component artificial force induced reaction method that combines density functional theory calculations. In order to uncover the overall mechanism at low surface coverage, we explored reaction path networks for three different conditions of the anatase TiO2 (101) surfaces: clean, protonated, and oxygen‐deficient surfaces. Previous temperature‐programmed desorption (TPD) experiments had shown that H2O desorption starts at a low temperature of about 300 K, while CO and formaldehyde desorption starts at high temperatures of about 500 K. The present reaction path networks are consistent with the overall trend observed in the TPD experiments. Using the reaction pathways extracted from these networks, the overall dissociation mechanism has been discussed.

Development of Advective Dynamic Stabilization scheme for ISPH simulations of free-surface fluid flows

This study presents an enhanced version of a numerical stabilizing scheme, namely, the Dynamic Stabilization scheme (DS) by Tsuruta et al. (2013), referred to as the Advective DS scheme (ADS) for further enhancement of the numerical stability and accuracy in ISPH simulations of free-surface fluid flows. To ensure general stability of calculations, particle methods may benefit from particle regularization schemes including artificial repulsive force schemes to keep particles equally distanced. DS explicitly provides a stabilizing force based on the overlapped state of a target particle and its neighboring particle, resulting in a momentum-conservative repulsive force and stable simulations. However, DS may also result in numerical noises and numerical dissipation. Such numerical noises stem from the excess stabilizing forces because of consideration of the particle positions only. The approaching velocities of particles, corresponding to the divergence-free condition, are ignored. To precisely consider the dynamic states of particles in derivation of stabilizing forces, in ADS, the approaching velocities are additionally considered and the stabilizing forces are derived in a variationally consistent form based on time rate of particle overlapping state, to precisely recover the exact deteriorated particle regularity state. The enhanced performance of the proposed ADS scheme is shown through some benchmark tests including a Taylor-Green vortex, a dam break as a violent free-surface flow, an oscillating drop and a rotating square patch. The enhanced performance of ADS in terms of reproduced pressure and velocity fields, energy conservation and convergence are well demonstrated.