Gravitational Potential Field Research Articles

Study of hydrogen fuel cell unmanned surface vehicle crane collision avoidance control by using an improved artificial potential field

ABSTRACT In this paper, a collision avoidance control strategy based on an enhanced Artificial Potential Field (APF) is proposed to overcome stationary and dynamic surface obstacles for Unmanned Surface Vehicle Crane (USVC) powered by hydrogen fuel cells. The proposed collision avoidance control relies on the gravitational and repulsive potential field functions. An angle limitation and speed optimisation design strategies are derived to enhance the path planning performance and guarantee the safety of the system. Finally, the simulation and experiment of USVC platform equipped with hydrogen fuel cells are developed to confirmed the effectiveness and reliability of the collision avoidance control strategy based on a novel APF under several obstacles.

Modeling risk potential fields for mandatory lane changes in intelligent connected vehicle environment

In the environment of Intelligent Connected Vehicles (ICVs), the ICV system is capable of gathering, processing, and transmitting the majority of traffic information to each vehicle, thereby empowering drivers to make more informed and secure decisions. Nevertheless, ICVs are still incapable of completely avoiding traffic conflicts and accidents. Consequently, developing a risk assessment model for ICVs is crucial for their deployment. To investigate the dynamic patterns of lane-changing vehicle risks within ICV environments, this study developed a quantitative relationship model based on the Artificial Potential Field (APF) theory. The model correlates the Total Potential Field (TPF) of mandatory lane-changing (MLC) vehicle with the longitudinal/transverse gravitational potential field (LGPF/TGPF) and the longitudinal/transverse repulsion potential field (LRPF/TRPF). Subsequently, three sets of Human Machine Interface (HMI) systems were developed to delineate distinct ICV environments: baseline, warning group, and guidance group. The baseline furnishes fundamental data, the warning group supplements preceding vehicle icons and real-time headway information, whereas the guidance group additionally augments speed and voice guidance functionalities. Following this, a simulated driving experiment involving 43 participants was carried out to simulate MLC scenarios in highway merging sections. Using enumeration and gradient descent methods, the quantitative relationship between different types of risk fields was determined. The findings indicated that the ICV environment significantly impacts the mean values of LGPF, TGPF, LRPF (Leading Vehicle, LV), and TRPF, while insignificantly affecting the mean value of LRPF (Following Vehicle, FV). Nevertheless, a notable discrepancy in the mean value of LRPF (FV) was observed between the warning and guidance groups. Comparative results with lane positions demonstrate that the proposed TPF accurately depicts vehicle lane-changing behaviors. Comparative results with classical risk indicators indicate that TPF more accurately depicts the actual driving risks and variation trends faced by vehicles in different MLC processes. The research findings will be pivotal in improving real-time control and guidance strategies for vehicles in highway merging sections under ICV environments.

The Dynamic Path Planning of Autonomous Vehicles on Icy and Snowy Roads Based on an Improved Artificial Potential Field

The crucial dynamic path planning of autonomous vehicles is achieved via obstacle avoidance path planning technology. The reduction of the tire adhesion coefficient on icy and snowy roads (ISRs) increases the difficulty of autonomous vehicles’ control. In this paper, the driving characteristics of vehicles on ISRs are established, and the artificial potential field function is introduced to avoid collision risk when planning a path. A dynamic path planning algorithm for autonomous vehicles based on the artificial potential field (APF) is established. The adjustment factor is added to the gravitational potential field, and a judgment coefficient is added to the repulsive potential field to improve the artificial potential field function, based on the low adhesion of vehicles on ISRs. Moreover, a path with a continuous curvature is generated to achieve the driving comfort and driving safety of the planned path via trajectory smoothing. By establishing the Carsim/Simulink co-simulation platform, the effectiveness of dynamic path planning for autonomous vehicles under different algorithms and different obstacle models is compared. The results show that the improved APF algorithm has an obvious effect on the smoothness of the path and the reduction of the curvature mutation and can generate a safe and efficient path on icy and snowy roads. The dynamic obstacle avoidance of the improved APF algorithm improves the pre-judgment accuracy of the collision risk assessment of autonomous vehicles and shows the superiority of the improved algorithm.

Potential field-based cooperative adaptive cruising control for longitudinal following and lane changing of vehicle platooning

Vehicle platooning often needs to execute lateral lane changing on highways while maintaining longitudinal following. This simultaneous lateral and longitudinal movement presents a significant challenge to maintaining the stability of vehicle platooning. To address the issue of stability during longitudinal following and lane changing, a control method based on the artificial potential field (APF) is proposed. The controller combines the obstacle potential field with the target gravitational potential field to guide the follower vehicle. The virtual trailing vehicle is added to enhance the convergence of the following error in the platooning. In the two-dimensional plane, the lateral error is redefined through the implementation of a look-ahead control concept. The proposed controller was tested under New European Driving Cycle (NEDC) working conditions, a traffic flow oscillation experiment, and a double lane changing test. The results demonstrate that the controller is capable of ensuring string stability and achieving an exceptional following effect.

A Nonuniform Clustering Routing Algorithm Based on a Virtual Gravitational Potential Field in Underwater Acoustic Sensor Network

Abstract-Due to the harsh deployment environment of the underwater coustic sensor networks (UASNs), a reliable and energy-saving routing algorithm has always been an important challenge and a hot topic. A Non-uniform Clustering (NC) algorithm is designed first in which clusters are genetated according to different node densities. Based on NC, the backbone of the underwater acoustic sensor network is formed in UASNs. To guarantee the reliability of data transmission of the backbone network, a Non-uniform Clustering Routing algorithm based on Virtual Gravitational Potential Field (NC_RVGPF) is proposed. This algorithm (1) establishes a virtual gravitational potential field model to allow data transmission by three-dimensional underwater nodes, (2) designs the virtual gravitational potential energy by combining the transmission distance between the nodes, the residual energy of the nodes, and other parameters, and (3) selects the path of the highest average potential energy as being the optimal path of data transmission. The simulation results show that compared with the classical routing algorithm, NC_RVGPF algorithm has higher transmission efficiency, less energy consumption, and can more effectively extend the network’s lifetime.

Optimal path planning of spacecraft fleet to asteroid detumbling utilizing deep neural networks and genetic algorithm

Following space discoveries, asteroids were found as rich sources of minerals and organic matter that can be exploited. In this paper, we present a precise, fast, and robust energy-optimal soft landing with a combined GA-Collocation method for a spacecraft fleet aimed at an irregular asteroid detumbling mission. It is assumed that the spacecraft fleet carried to the asteroid's equilibrium points introduced as the start locations of the mission. Here, the 433 Eros asteroid has been considered as the stony target known for its irregular elongated shape and nearly large dimension. We modeled the gravitational potential field by polyhedron as the most accurate one for such asymmetric objects. Hence, to decline the high burden computational of related equations in gravitational acceleration calculation, a Deep Neural Network with seven hidden layers and a relatively large dataset covering 6000 pairs has been developed. We utilized a Genetic Algorithm to guess systematically more optimal and reliable initial costates of some key parameters to raise the speed and accuracy of estimation. The acceptable efficiency and accuracy in optimal path prediction of the presented approach for a fleet of spacecraft approved throughout precise simulations. Eventually, the feasibility of the proposed approach is demonstrated through the corresponding results.

Tilt angle filter effect on noise cancelation and structural edges detection in hydrocarbon sources in a gravitational potential field

Noise cancelation is the process done to remove out-of-range anomalies and make better edge boundaries interpretation. One of the most challenging issues in describing gravitational maps is separating the anomalies related to shallow sources from the deep ones. Furthermore, Existing noise can make it arduous to separate shallow blurred boundaries. In this study in SE Iran, gravitational surveying was carried out in shallow areas from the west of Qeshm to the Hormuz islands in a regular network with a distance of one kilometer. The range of gravitational Bouguer was -297 to -330 mGal. Modeling and determining geometrical parameters revealed five negative anomalies from salt penetration. The residual gravity was computed by deducting gravitational effects related to deep sources from measured gravitational data. Correspondingly, estimating the boundary and edge of the subsurface masses will be better than local filters, and anomalies will be highlighted with more intensity. Furthermore, three major fault systems in the Zagros basin were determined as the primary origin of activity and expansion of Hormuz salt. Sensitivity analysis was employed utilizing analytical signals and maps of tilt angle filtering, which both revealed the same satisfying results of -297 to -330 mGal. In this article, the effect of the tilt angle local phase filter on a synthetic model was accomplished through numerical coding. As a result, Total Horizontal Derivative (THDR) provides location of salt intrusion in Qeshm area; whereas the best image of salt intrusion, in terms of feature edge illumination, presented by Analytical signal of residual gravity map.

Analysis of the Conditions of Mechanical Equilibrium on the Curved Surface of a Vapor–Liquid System in a Gravitational Field

A thermodynamic analysis of mechanical equilibrium conditions is performed for the curved interface of a vapor–liquid system in the gravitational field potential with regard to ratios of experimental times of relaxation of thermodynamic parameters (momentum, energy, and mass). In a kinetic analysis of the relaxation stage of reaching the equilibrium state, it is revealed that it is important to consider the physical nature of the boundary of separating phases. The mechanical model of the boundary is one with an intermediate foreign film preventing the attainment of chemical equilibrium between the neighboring phases. The real boundary of coexisting phases has a variable density profile corresponding to the condition of the constant chemical potential throughout the region of transition and in the neighboring coexisting phases. The absence of an intermediate film excludes the priority of the mechanical equilibrium over the chemical equilibrium and results in pressure being the function of local temperature and chemical potential values (excluding the application of the Laplace equation). Considering times of relaxation is found to change the familiar Gibbs expression for the pressure jump between coexisting vapor and fluid as functions of the boundary in the gravitational field potential. A consequence of considering the correct ratio of momentum and mass times of relaxation is discussed: the phase equilibrium conditions of a separating vapor–liquid system in combined gravitational and surface force fields must be analyzed in order to solve problems of the capillary theory.

Tilt Angle Filter Effect on Noise Cancelation and Structural Edges Detection in Hydrocarbon Sources in a Gravitational Potential Field

Tilt Angle Filter Effect on Noise Cancelation and Structural Edges Detection in Hydrocarbon Sources in a Gravitational Potential Field

On the question of the radius of elementary particles

This article belongs to the field of theoretical physics, specifically the study of elementary particles. We discuss the parameters of elementary particles, their interactions with gravitational potential and magnetic fields, stability with respect to their lifetimes, as well as interactions between particles with different parameters, including different masses. We clarify the concept of electric charge for particles. We use methods and formulas from classical physics that are accessible to a wide range of interested individuals.

Deep Potential: Recovering the Gravitational Potential from a Snapshot of Phase Space

One of the major goals of the field of Milky Way dynamics is to recover the gravitational potential field. Mapping the potential would allow us to determine the spatial distribution of matter—both baryonic and dark—throughout the galaxy. We present a novel method for determining the gravitational field from a snapshot of the phase-space positions of stars, based only on minimal physical assumptions, which makes use of recently developed tools from the field of deep learning. We first train a normalizing flow on a sample of observed six-dimensional phase-space coordinates of stars, obtaining a smooth, differentiable approximation of the distribution function. Using the collisionless Boltzmann equation, we then find the gravitational potential—represented by a feed-forward neural network—that renders this distribution function stationary. This method, which we term “Deep Potential,” is more flexible than previous parametric methods, which fit restricted classes of analytic models of the distribution function and potential to the data. We demonstrate Deep Potential on mock data sets and demonstrate its robustness under various nonideal conditions. Deep Potential is a promising approach to mapping the density of the Milky Way and other stellar systems, using rich data sets of stellar positions and kinematics now being provided by Gaia and ground-based spectroscopic surveys.

Multiphysics Modeling of Volcanic Unrest at Mt. Ruapehu (New Zealand)

AbstractPre‐eruptive signals at the crater lake‐bearing Mt. Ruapehu (New Zealand) are either absent or hard to identify. Here, we report on geophysical anomalies arising from hydrothermal unrest (HTU) and magmatic unrest (MU) using multiphysics numerical modeling. Distinct spatio‐temporal anomalies are revealed when jointly solving for ground displacements and changes in gravitational and electrical potential fields for a set of subsurface disturbances including magma recharge and anomalous hydrothermal flow. Protracted hydrothermal injections induce measurable surface displacements (>0.5 cm) at Ruapehu's summit plateau, while magmatic pressurization (5–20 MPa) results in ground displacements below detection limits. Source density changes of 10 kg/m3 (MU simulations) and CO2 fluxes between 2,150 and 3,600 t/d (HTU simulations) induce resolvable residual gravity changes between +8 and −8 μGal at the plateau. Absolute self‐potential (SP) anomalies are predicted to vary between 0.3 and 2.5 mV for all unrest simulations and exceed the detection limit of conventional electric surveying. Parameter space exploration indicates that variations of up to 400% in the Biot‐Willis coefficient produce negligible differences in surface displacement in MU simulations, but strongly impact surface displacement in HTU simulations. Our interpretation of the findings is that monitoring of changes in SP and gravity should permit insights into MU at Ruapehu, while HTU is best characterized using ground displacements, residual gravity changes and SP anomalies. Our findings are useful to inform multiparameter monitoring strategies at Ruapehu and other volcanoes hosting crater lakes.

Asteroids and Their Mathematical Methods

In this paper, the basic classification of asteroids and the history and current situation of asteroid exploration are introduced. Furthermore, some recent research progress on the orbital dynamics of asteroids, including models of the gravitational potential field, the dynamics near asteroids, hopping motion on the surface, and bifurcations under varying external parameters, is reviewed. In the meanwhile, the future research development such as the configuration and evolution of binary or triple asteroid systems and near-Earth asteroid defense is briefly discussed.

Relativistic Hypercomputing: Problems and Prospects from the Physicist’s Point of View

The paper presents the main results on hypercomputing based on the use of relativistic effects. Two approaches to the problem are compared – formal-logical and physical. The basis of the physical approach is the study of the metric of curved space-time manifolds on which hypercomputing are realized, obtained either by applying the equivalence principle or by solving Einstein's equations. The properties of Malament-Hogarth spaces arising in these manifolds are discussed. The advantages of the physical approach are shown, which make it possible to verify the possibility of hypercomputing by the example of the problem of calculating the sum of the divergent Dirichlet series for the Riemann zeta function, which requires overcoming the so-called Turing barrier. It is stressed the possibility of using numerical algebras that differ from the field of real numbers, which promises significant progress in the development of modern physical theories first of all in cosmology. The issues of relativistic theory are considered separately. The relativistic solution of the problem of motion with constant acceleration by finding the gravitational potential field of an infinite homogeneous plane is discussed. The solution of this problem by applying the equivalence principle is also discussed. The results are compared with the well-known solutions of V. Fock and R. Tolman.

Benchmark forward gravity schemes: the gravity field of a realistic lithosphere model WINTERC-G

Abstract. Several alternative gravity forward modelling methodologies and associated numerical codes with their own advantages and limitations are available for the solid Earth community. With upcoming state-of-the-art lithosphere density models and accurate global gravity field data sets, it is vital to understand the opportunities and limitations of the various approaches. In this paper, we discuss the four widely used techniques: global spherical harmonics (GSH), tesseroid integration (TESS), triangle integration (TRI), and hexahedral integration (HEX). A constant density shell benchmark shows that all four codes can produce similar precise gravitational potential fields. Two additional shell tests were conducted with more complicated density structures: laterally varying density structures and a crust–mantle interface density. The differences between the four codes were all below 1.5 % of the modelled gravity signal suitable for reproducing satellite-acquired gravity data. TESS and GSH produced the most similar potential fields (<0.3 %). To examine the usability of the forward modelling codes for realistic geological structures, we use the global lithosphere model WINTERC-G that was constrained, among other data, by satellite gravity field data computed using a spectral forward modelling approach. This spectral code was benchmarked against the GSH, and it was confirmed that both approaches produce a similar gravity solution with negligible differences between them. In the comparison of the different WINTERC-G-based gravity solutions, again GSH and TESS performed best. Only short-wavelength noise is present between the spectral and tesseroid forward modelling approaches, likely related to the different way in which the spherical harmonic analysis of the varying boundaries of the mass layer is performed. The spherical harmonic basis functions produce small differences compared to the tesseroid elements, especially at sharp interfaces, which introduces mostly short-wavelength differences. Nevertheless, both approaches (GSH and TESS) result in accurate solutions of the potential field with reasonable computational resources. Differences below 0.5 % are obtained, resulting in residuals of 0.076 mGal standard deviation at 250 km height. The biggest issue for TRI is the characteristic pattern in the residuals that is related to the grid layout. Increasing the resolution and filtering allow for the removal of most of this erroneous pattern, but at the expense of higher computational loads with respect to the other codes. The other spatial forward modelling scheme, HEX, has more difficulty in reproducing similar gravity field solutions compared to GSH and TESS. These particular approaches need to go to higher resolutions, resulting in enormous computation efforts. The hexahedron-based code performs less than optimal in the forward modelling of the gravity signature, especially with a laterally varying density interface. Care must be taken with any forward modelling software as the approximation of the geometry of the WINTERC-G model may deteriorate the gravity field solution.

Multi-stage puncture path planning algorithm of ablation needles for percutaneous radiofrequency ablation of liver tumors

This paper designs a multi-stage puncture path planning algorithm of ablation needles for percutaneous radiofrequency ablation of liver tumors, in order to guide or assist clinicians automatically plan the puncture path of ablation needle, and improve the safety and effectiveness of percutaneous radiofrequency ablation for liver cancer. Firstly, the initial feasible puncture paths satisfying the hard constraints are obtained by quantifying different clinical multi-constraint conditions. Then, according to the soft constraints, the risk index of puncture path is designed to realize the first-stage path planning. Secondly, considering the zero potential energy point and multi-tumor puncture, we embed the gravitational additional potential field to improve the traditional artificial potential field, and the second-stage path planning of candidate puncture paths is carried out by calculating the comprehensive potential energy of the paths. Finally, the reliability of the ablation needle trajectory is evaluated based on the relationship between the candidate puncture paths and liver segments, and the third-stage path planning is realized to determine the optimal puncture path. Through the quantitative and qualitative evaluation of the results, it is proved that our algorithm can obtain an optimal puncture path that meets the clinical conditions, which is expected to guide clinicians in the puncture path planning of percutaneous radiofrequency ablation for liver cancer.

Improved reinforcement learning algorithm for mobile robot path planning

In order to solve the problem that traditional Q-learning algorithm has a large number of invalid iterations in the early convergence stage of robot path planning, an improved reinforcement learning algorithm is proposed. Firstly, the gravitational potential field in the improved artificial potential field algorithm is introduced when the Q table is initialized to accelerate the convergence. Secondly, the Tent Chaotic Mapping algorithm is added to the initial state determination process of the algorithm, which allows the algorithm to explore the environment more fully. In addition, an ε-greed strategy with the number of iterations changing the ε value becomes the action selection strategy of the algorithm, which improves the performance of the algorithm. Finally, the grid map simulation results based on MATLAB show that the improved Q-learning algorithm has greatly reduced the path planning time and the number of non-convergence iterations compared with the traditional algorithm.

Accounting for GIA signal in GRACE products

SUMMARY The Gravity Recovery and Climate Experiment (GRACE) observes gravitational potential anomalies that include the effects of present-day surface mass change (PDSMC)- and glacial isostatic adjustment (GIA)-driven solid Earth mass redistribution. Therefore, GIA estimates from a forward model are commonly removed from GRACE to estimate PDSMC. There are several GIA models and to facilitate users in using a GIA model of their choice, both GRACE and GIA products are made available in terms of global gridded fields representing mass anomaly. GRACE-observed gravitational potential anomalies are represented in terms of equivalent water height (EWH) with a relation that accounts for an elastic solid Earth deformation due to PDSMC. However, for obtaining GIA EWH fields from GIA gravitational potential fields, two relations are being used: one that is similar to that being used for GRACE EWH and the other that does not include an elastic deformation effect. This leaves users with the possibility of obtaining different values for PDSMC with a given GRACE and GIA field. In this paper, we discuss the impact of this problem on regional mass change estimates and highlight the need for consistent treatment of GIA signals in GRACE observations.

Minimum Detectable Mass and Volume Fluxes During Magmatic Recharge at High Prominence Volcanoes: An Application to Erciyes Dağ Volcano (Turkey)

Magma reservoir recharge is widely recognised as a precursor of eruptive activity. However, the causative relationships between reservoir rejuvenation and surface observables such as gravitational potential field changes and ground deformation are still poorly understood. At intermediate and silicic intra-plate volcanoes where crustal mechanical heterogeneity combined with high-prominence are expected to fundamentally affect the crustal stress and strain relationship, protracted period of repose and absence of monitoring data raise questions about the detectability of magma recharge. Here we report results from integrated geodetic forward modelling of ground displacements and gravity changes from reservoir recharge at Erciyes Dağ, a large prominence (∼2,800 m), yet poorly studied, stratovolcano of the Central Anatolian Volcanic Province in Turkey. The most recent eruption at ∼7000 BC, close proximity to the Kayseri Metropolitan Area and absence of dedicated volcano monitoring set a precedent to explore stealth magmatic processes at the volcano. Using finite element analysis we systematically explore the influence of subsurface mechanical heterogeneities and topography on surface deformation and gravity changes from magmatic recharge of Erciyes Dağ’s reservoir. We show that whilst crustal heterogeneity amplifies ground displacements and gravity variations, the volcano’s substantial prominence has the opposite effect. For generic reservoir pressure and density changes of 10 MPa and 10 kg m−3 predicted vertical displacements vary by a factor of 5 while residual gravity changes vary by a factor of 12 between models ignoring topography or mechanical heterogeneity and those that do not. We deduce reservoir volume and mass changes of order 10–3 km3 and 1010 kg, respectively, at the detectability limit of conventional surveying techniques at the volcano. Though dependent on model assumptions, all results indicate that magma recharge at Erciyes Dağ may go undetected at fluxes 1) sufficient to maintain an active reservoir containing eruptable magma and 2) similar to those reported for intermediate/silicic volcanoes with repose times of 100–1,000s of years (e.g., Parinacota) and persistently active mafic volcanoes such as Mt. Etna and Stromboli. Our findings may be utilised to inform integrated geodetic and gravimetric monitoring at Erciyes Dağ and other large prominence silicic volcanoes and could provide early insights into reservoir rejuvenation with implications for the development of disaster risk reduction initiatives.

Self-gravitating vector dark matter

We derive the non-relativistic limit of a massive vector field. We show that the Cartesian spatial components of the vector behave as three identical, non-interacting scalar fields. We find classes of spherical, cylindrical, and planar self-gravitating vector solitons in the Newtonian limit. The gravitational properties of the lowest-energy vector solitons$\mathrm{-}$the gravitational potential and density field$\mathrm{-}$depend only on the net mass of the soliton and the vector particle mass. In particular, these self-gravitating, ground-state vector solitons are independent of the distribution of energy across the vector field components, and are indistinguishable from their scalar-field counterparts. Fuzzy Vector Dark Matter models can therefore give rise to halo cores with identical observational properties to the ones in scalar Fuzzy Dark Matter models. We also provide novel hedgehog vector soliton solutions, which cannot be observed in scalar-field theories. The gravitational binding of the lowest-energy hedgehog halo is about three times weaker than the ground-state vector soliton. Finally, we show that no spherically symmetric solitons exist with a divergence-free vector field.