Obstacle Size Research Articles

Intelligent Vector Field Histogram based collision avoidance method for AUV

Intelligent Vector Field Histogram (IVFH) is proposed to accomplish the collision avoidance of Autonomous Underwater Vehicle (AUV) in underwater three-dimensional dynamic space. The directed cuboid static obstacle environment model is introduced to improve the efficiency of collision avoidance decision-making. The candidate direction set is composed of relative heading and relative pitch. According to the obstacle distribution of local environment, the traveling fitness of each candidate direction is calculated from the perspectives of safety and rapidity, so as to realize the collision avoidance of AUV in three-dimensional dynamic environment. IVFH method can adaptively adjust the parameters that affect the collision avoidance action amplitude according to the obstacle distance and size. The collision avoidance velocity is adjusted by fuzzy logic according to the environment conditions, so as to ensure that AUV can fully perceive the environment and then complete the collision avoidance decision-making. The simulation results show that IVFH method can overcome the threshold sensitivity of traditional VFH method, escape from the trap area, and realize collision avoidance in three-dimensional dynamic complex obstacle environment. The proposed IVFH collision avoidance method has been verified by simulations, as well as lake and sea experiments, demonstrating its effectiveness and practicability.

GHOSTly flute music: drumlins, moats and the bed of Thwaites Glacier

AbstractGlacier-bed characteristics that are poorly known and modeled are important in projected sea-level rise from ice-sheet changes under strong warming, especially in the Thwaites Glacier drainage of West Antarctica. Ocean warming may induce ice-shelf thinning or loss, or thinning of ice in estuarine zones, reducing backstress on grounded ice. Models indicate that, in response, more-nearly-plastic beds favor faster ice loss by causing larger flow acceleration, but more-nearly-viscous beds favor localized near-coastal thinning that could speed grounding-zone retreat into interior basins where marine-ice-sheet instability or cliff instability could develop and cause very rapid ice loss. Interpretation of available data indicates that the bed is spatially mosaicked, with both viscous and plastic regions. Flow against bedrock topography removes plastic lubricating tills, exposing bedrock that is eroded on up-glacier sides of obstacles to form moats with exposed bedrock tails extending downglacier adjacent to lee-side soft-till bedforms. Flow against topography also generates high-ice-pressure zones that prevent inflow of lubricating water over distances that scale with the obstacle size. Extending existing observations to sufficiently large regions, and developing models assimilating such data at the appropriate scale, present large, important research challenges that must be met to reliably project future forced sea-level rise.

Caring for Rural Patients at End of Life: Perceptions of Critical Access Hospital Nurses.

Critical access hospitals were created to bring health care to rural populations. These hospitals lack equipment and resources, but the nurses who work there still provide end-of-life care to critically ill and dying patients. To determine how nurses in critical access hospitals perceive the size of obstacles and helpful behaviors for the provision of end-of-life care. Questionnaires were sent to a cross-sectional, nationally representative sample of nurses working in 39 critical access hospitals. The nurses were asked to score obstacle and helpful behavior items on a scale of from 0 (not an obstacle or not a help, respectively) to 5 (extremely large obstacle or extremely large help, respectively). The items were then ranked from highest to lowest according to their mean scores. Seven of the top 10 obstacles were directly related to family behaviors and attitudes, such as families not understanding what lifesaving measures entail and internal family disagreements about life support. Helpful behaviors ranked in the top 10 included interventions that were controlled by nurses and items that affected the nurses' having adequate time to deliver end-of-life care. Obstacles and helpful behavior items unique to critical access hospitals, such as a lack of resources and the nurse knowing the patient or the patient's family, ranked below the top 10 items. Obstacles and helpful behaviors for providing end-of-life care remain consistent. Nurses in critical access hospitals are accustomed to working without the typical resources found in urban hospitals and thus did not perceive resource deficits to be among the greatest obstacles to providing end-of-life care. Family behaviors and attitudes remain the most dominant obstacle noted by nurses.

Vortex shedding frequency of a moving obstacle in a Bose–Einstein condensate

We experimentally investigate the periodic vortex shedding dynamics in a highly oblate Bose–Einstein condensate using a moving penetrable Gaussian obstacle. The shedding frequency f v is measured as a function of the obstacle velocity v and characterized by a linear relationship of f v = a(v − v c) with v c being the critical velocity. The proportionality constant a is linearly decreased with a decrease in the obstacle strength, whereas v c approaches the speed of sound. When the obstacle size increases, both a and v c are decreased. We discuss a possible association of a with the Strouhal number in the context of universal shedding dynamics of a superfluid. The critical vortex shedding is further investigated for an oscillating obstacle and found to be consistent with the measured f v. When the obstacle’s maximum velocity exceeds v c but its oscillation amplitude is not large enough to create a vortex dipole, we observe that vortices are generated in the low-density boundary region of the trapped condensate, which is attributed to the phonon emission from the oscillating obstacle.

CFD-based approach to design the heart-shaped micromixer with obstacles

Abstract Microfluidic devices/systems, including Micro-Total-Analysis-System (µTAS), Point of Care Testing (POCT) and Lab-On-a-Chip (LOC) are used in many chemical and biological assays applications. Among the vital tasks that these microfluidic devices must achieve essentially include a high degree of mixing and accordingly, micromixers are being used for the same purpose. The design depends on the yield required in particular application. In the proposed study, the four kinds of heart-shaped micromixers with different obstacles have been studied through simulations. The influence of the shape and size of different obstacles viz., circular shape, diamond shape, teardrop shape, and heart shape obstacles on the performance characteristics has been studied. The performance characteristics namely, the mixing index and pressure drop have been used. In accordance with the study, a heart-shaped micromixer with heart shape obstacles (HSM-HSO) has come out to be the most efficient micromixer due to the significant chaotic convection effect. The heart-shaped micromixer with heart shape obstacles (HSM-HSO) of size 0.350 µm × 0.350 µm has shown better performance for a wider range of Reynolds number (Re), i.e., mixing index of Re > 0.99, for Re of 0.1 and Re in the range of 15–45.

The atomic obstacle size influence on the Hydrogen flow inside a nanochannel: A molecular dynamics approach to predict the fluid atomic arrangements

In the current computational work, the atomic behaviour of Hydrogen (H) atoms (as fluid) inside 2D Platinum (Pt) nanochannel (NC) in the presence of obstacles is described using molecular dynamics simulation (MDS) for clinical applications. This simulation method is reported by temperature (T), total energy, profiles of density/velocity/T and interaction energy of simulated compounds. Computationally, a fluid-NC system modelled with Universal Force Field (UFF) and Embedded Atom Model (EAM) potentials (force-fields). MD outputs indicated the potential energy of samples converged to a negative amount after 5 ns. This physical behaviour shows the stability of the defined system at T=300 K. Furthermore, the simulation results show the atomic behaviour of H fluid optimized by atomic obstacle radius optimizing. By using NC with an obstacle, the interaction energy between fluid atoms and NC walls reach -40.44 eV and by this process occur, mass transfer phenomenon optimized for clinical aims.

A neutrally buoyant particle captured by vortex in a lid-driven cavity with an internal obstacle

The flow in the square cavity with internal obstacles exists widely; thus, investigating the effect of the existence of the obstacles on the flow and the motion of the solid particles is important. To understand, predict, and control the motion of the solid particles, the motion of a neutrally buoyant circular particle in a lid-driven square cavity with an internal circular obstacle is studied with the lattice Boltzmann method, where the effects of the obstacle size, obstacle location, initial position of the circular particle, and Reynolds number are investigated. Under the effect of the obstacle, the flow and the motion of the particle are quite different. Especially, under some cases, no limit cycle is observed, and the particle is captured by the secondary vortex at the lower layer of the square cavity, which is insensitive to the initial position of the circular particle. The effect of the Reynolds number on the motion of the particle is significant, with the increase in the Reynolds number, and the motion of the particle is different obviously. At low Reynolds numbers, the motion of the particle is confined by the primary vortex, which moves along the limit cycle at the upper layer of the square cavity. With the increase in the Reynolds number, the effect of the inertia of the particle becomes stronger, and the particle moves from the primary vortex to the secondary vortex until it is captured by the secondary vortex. At relatively high Reynolds numbers, the primary vortex develops, and the particle is confined by the primary vortex again, forming another limit cycle.

Finite-size effects on heat and mass transfer in porous electrodes

In thin electrode applications, as the ratio of the obstacle size with respect to the system size increases, issues such as finite-size effects become more influential in the transport of heat and mass within a porous structure. This study presents a numerical approach to evaluate the finite-size effects on the heat and mass transfer in porous electrodes. In particular, numerical simulations based on the lattice Boltzmann method (LBM) are employed to analyze the pore-scale transport phenomena. Analyzing the results at both the electrode level and the pore level shows that the mass transfer performance is more influenced by the finite-size effects compared to the transfer of heat. The numerical simulations show that as the parameter m being the ratio of the electrode thickness to the particle diameter is halved, the effective diffusivity increases by 20% while the effective conductivity remains unchanged. We propose a novel analytical tortuosity–porosity (τ−ϕ) correlation as τ=[1−(1−ϕ)m+1]/ϕ where the finite-size effects are taken into account via the parameter m. Besides, particles of small size provide more uniform distributions of temperature and concentration within the porous structure with standard deviations of approximately half of the values obtained from the case made up of large particles. Our findings at the electrode level are compared with the commonly used macroscopic porosity-dependent correlations found in the literature. At the end, by performing a systematic assessment, we provide guidelines for efficient design of porous electrodes.

EVs on Road Ground-Impact Energy Evaluation Methodology: Dynamic of a Finite Element (FE)-Based Battery Pack Integrated into Full Vehicle Multi-Body Model on Abaqus

<div class="section abstract"><div class="htmlview paragraph">The present paper documents a comprehensive study on the ground-impact of battery packs in Electric Vehicles (EVs), a paramount concern for vehicle manufacturers. During an accidental crash, battery packs are usually exposed dangerously to possible intrusion of foreign objects (e.g., road debris). With the purpose of developing a generic methodology to evaluate the released energy content and due to high nonlinearities involved during the ground-impact maneuvers, a hybrid full vehicle model is needed. Hence, both FE-based battery case and virtual energy sensors have been integrated into the current Abaqus multi-body (MB) full vehicle model (suspensions, steering system, engine and a trimmed body). Energy peaks are estimated simulating a vehicle going over obstacles that a typical customer can encounter in daily-life (no off-normal situations) performed at different approaching speeds and obstacle sizes.</div><div class="htmlview paragraph">To evaluate the energy, the battery plate is divided as if it were a spaced grid of identical square-sized modules. Plate surface modularization is useful to install properly a certain amount of virtual sensors that store and measure the energy released during the impact. In addition, this strategic layout promotes the accuracy of the contact conditions between obstacles and the battery case.</div><div class="htmlview paragraph">The concept underlying the proposed multidisciplinary sequential procedure, based on three different phases (on road-impact energy evaluation, load cases definition and battery case/mechanical structure strength), ensures both to define specification for subsequent analyses (making iterations on the structure faster) and to possibly complete an effective design validation of the specific vehicle project under test. This methodology has been successfully applied transversally to several vehicle architectures (e.g., light commercial vehicles, sport/compact utility vehicles, supercars) and it shows the benefits of choosing the integration strategy over a typical co-simulation approach.</div></div>

Contained-Reflected Megaturbidites of the Marnoso-arenacea Formation (Contessa Key Bed) and Helminthoid Flysches (Northern Apennines, Italy) and Hecho Group (South-Western Pyrenees)

Contained-reflected beds deposited by fully-ponded or partially-reflected turbidity currents are important because their correct evaluation can give important indications on the degree of basin confinement and on the type, size and orientation of the morphological obstacle. Through a detailed facies analysis of various significant megabeds in the Marnoso-arenacea Formation, including the Contessa key bed, in the helminthoid flysches in the northern Apennines (Italy) and in the Pyrenees (megaturbidite MT5), this work proposes a depositional model that is well consistent with the recent experimental data available in the literature, discussing their strengths and limits. The Contessa and flysch megabeds fit very well with the experimental conditions because they are deposited in narrow and elongated confined basins characterized by axial flows. Indeed, in the proposed model, it is possible to recognize facies deposited by: 1) a basal underflow directed towards the bounding slope (Facies A), 2) an intermediate part of the flow characterized by lateral deflections (facies B1), 3) an upper well-developed reversing flow (facies B2) and 4) an uppermost residual reversing flow recording the final collapse of the fine-grained suspended load forming a poorly-sorted slurry facies C and a very thick mudstone unit D. Facies A, B1 and B2 are usually separated by very thin fine-grained muddy drapes rich in carbonaceous matter, which can be traced throughout the basin. These drapes - very common in contained and confined beds in these settings - can be related to internal density surfaces, along which decoupling processes, separating underflows from reversing overflows, can easily occur. Conversely, as the MT5 is characterized by a source transversal to an elongated narrow basin, the large flow volume versus basin capacity hinders the generation of reversing flows and rebound layers favoring the formation of fully-ponded pulsating overflows able to deposit alternations of laminated and massive units. This facies type can be observed in the basins that are characterized by axial flows only near the basin margins where the pulsating collapse of the reversing flow can dominate. This study shows that the integration of detailed field studies are essential to validate experimental data from an applicative point of view.

An experimental study of oil slick contraction by chemical herders and fragmentation by obstacles

Chemical herders are a promising technique for treatment of oil spills in icy waters at high latitudes. However, obstacles on the water surface such as floating ice affects or interferes with all spill response countermeasures including chemical herder operations by fracturing the contracting oil slick and trapping small oil patches. Here we experimentally investigate the fluid dynamics of oil slick contraction and the interaction of the contracting oil slick with single obstacles of different shapes and sizes in a laboratory scale basin using Alaska North Slope crude oil and OP-40 herding agent. Oil slick area and thickness, oil-herder interface contraction speed, and the spatial distribution of the slick were optically measured over time, and particle image velocimetry (PIV) was used to measure the flow of the oil slick around the obstacles. For all obstacle sizes and shapes, an oil tail in the obstacle wake was generated as the oil-herder interface passed, which subsequently fractured by a capillary-type instability. Larger and less streamlined obstacles retained greater amounts of oil in these tails. In addition, a widely used theoretical thin film spreading model was successfully used to describe the spreading of the chemical herder against the oil slick at equilibrium. These results provide a foundation for future investigation of synergistic trapping of oil by multiple obstacles as would be seen in the field.

Sharp convergence rates for Darcy’s law

This article is concerned with Darcy’s law for an incompressible viscous fluid flowing in a porous medium. We establish the sharp convergence rate in a periodically perforated and bounded domain in for where ε represents the size of solid obstacles. This is achieved by constructing two boundary layer correctors to control the boundary layers created by the incompressibility condition and the discrepancy of boundary values between the solution and the leading term in its asymptotic expansion. One of the correctors deals with the tangential boundary data, while the other handles the normal boundary data.

A 3D Point-of-Intention Estimation Method Using Multimodal Fusion of Hand Pointing, Eye Gaze and Depth Sensing for Collaborative Robots

Hand pointing psychologically expressing intention has been fused with eye gaze to assist in detecting the point of intention (POI). Ideally, a POI detection approach using a pair of hand-pointing and eye-gaze rays may achieve precise POI positioning in 3-dimensional (3D) space; however, an object sometimes occludes the detection process in real applications. This paper proposes a method of 3D POI estimation using multimodal fusion of hand pointing, eye gaze and depth sensing for collaborative robots. In this method, depth sensors are used to assist in the fusion of the original hand-pointing and eye-gaze rays to determine the POI based on a volume of interest (VOI) to find 3D POI. At real production sites where humans work with collaborative robots, workpieces may sometimes occlude the depth sensors, resulting in blind views. This problem is solved by increasing the number of depth sensors and arranging them with overlapping view ranges to cover otherwise blind views due to occlusion. The number of depth sensors is determined based on the largest possible obstacle size determined by users in advance. Experiments performed by 10 participants confirm the effectiveness of POI estimation in the presence of obstacles; specifically, with our proposed method, we measured 3D POIs at 50 cm, 70 cm, 75 cm, 80 cm, 85 cm, 90 cm, and 95 cm with average distance errors of 0.82%, 0.68%, 0.68%, 0.72%, 0.76%, 0.87%, and 0.81%, respectively, compared with the conventional POI estimation method based on the fusion of hand pointing and eye gaze.

Multiple bottle beams based on metasurface optical field modulation and their capture of multiple atoms

Compared to conventional devices, metasurfaces offer the advantages of being lightweight, with planarization and tuning flexibility. This provides a new way to integrate and miniaturize optical systems. In this paper, a metasurface capable of generating multiple bottle beams was designed. Based on the Pancharatnam–Berry (P–B) phase principle, the metasurface lens can accurately control the wavefront by adjusting the aspect ratio of the titanium dioxide nanopillars and the rotation angle. When irradiated by left-handed circularly polarized light with a wavelength of 632.8 nm, the optical system can produce multiple micron bottle beams. Taking two bottle beams as examples, the longitudinal full widths at half-maximum of the optical tweezers can reach 0.85 μm and 1.12 μm, respectively, and the transverse full widths at half-maximum can reach 0.46 μm and 0.6 μm. Also, the number of generated bottle beams can be varied by controlling the size of the annular obstacle. By changing the x-component of the unit rotation angle, the metasurface can also change the shape of the bottle beam — the beam cross-section can be changed from circular to elliptical. This paper also analyzes the trapping of ytterbium atoms by the multi bottle beam acting as optical tweezers. It is found that the multi bottle beam can cool and trap multiple ytterbium atoms.

Physics-based estimates of drag coefficients for the impact pressure calculation of dense snow avalanches

In avalanche engineering and hazard mapping, computing impact pressures exerted by avalanches on rigid structures has long been a difficult task that requires combining empirical equations, rules of thumb, engineering judgment and experience. Until the 1990s, well-documented avalanches were seldom, and the main source of information included back-analysis of damage to structures and scarce field measurements. By the 1990s, several field sites were equipped across Europe, and since then they have provided new insights into the physics of impact. The main problem has been the difficulty in interpreting and generalizing the results to propose sound methods for estimating impact pressure. Testing a wide range of flow conditions has also been difficult in the field. To go a step forward in the elaboration of new guidelines for computing avalanche forces, we developed a numerical code based on the Discrete Element Method (DEM), which made it possible to simulate how an avalanche interacts with a rigid obstacle and to study how impact pressure depends on obstacle shape and size, as well as the avalanche flow regime. We extracted pressure and velocity data from the Vallée de la Sionne database to validate the DEM code, calibrate the model parameters, and elaborate avalanche scenarios. We studied four avalanches scenarios related to distinct flow regimes of the avalanche’s dense core. In these scenarios, snow cohesion and velocity were imposed at the upstream boundary of the computational domain. Building on earlier work, we generalized an empirical equation for computing impact pressure as a function of snow cohesion, velocity, flow regime, and structure shape and size. Various coefficients were defined and calibrated from our DEM data. Within the range of tested values, we found good agreement between estimated pressure and field data.

Jetting onset on a liquid surface accelerated past a submerged cylinder

A novel experiment is presented to study the initial disturbances on a free surface due to the constant acceleration of liquid around a submerged obstacle. The surface response to different obstacle sizes, initial surface heights and fluid velocities is measured using high-speed videography. Perturbations observed on the surface are classified into either jetting or gravity waves by measuring the steepness of growing liquid columns. A classification phase map between these two regimes is obtained and compared with analytical results by Martín Pardo and Nedić (2021). The agreement between decision boundaries is good for high Froude numbers (high fluid velocities) but deteriorates at lower velocities, where viscosity and surface tension effects (not considered in the analytical model) have a greater predominance. The surface profile and perturbation amplitude measured in experiments are also compared against this analytical model. In all cases, the model accurately predicts the corresponding experimental results at the beginning of the motion, but the prediction error increases with time. It is also observed that faster moving surfaces that lead to the onset of jetting have greater prediction accuracies and longer validity times of the predictions.

Small obstacle size prediction based on a GA-BP neural network.

Accurate and effective acquisition of obstacle size parameters is the basis for environment perception, path planning, and autonomous navigation of mobile robots, and is the key to improve the walking performance of mobile robots. In this paper, a generic algorithm-back propagation (GA-BP) neural network-based method for small obstacle size prediction is proposed for mobile robots to perceive the environment quantitatively. A machine vision-based small obstacle size measurement experiment was designed, and 228 sets of sample data were obtained. A genetic algorithm optimized back propagation neural network was used to build a small obstacle size prediction model with obstacle pixel width, pixel height, pixel area, and obstacle-to-camera distance as input parameters and actual obstacle width, actual height, and actual area as output parameters. The results show that the correlation coefficient (R2) between the predicted and expected values of the test data is higher than 0.999, the root mean square error is lower than 5.573, and the mean absolute percentage error is lower than 2.84%. The good agreement between its predicted and expected values indicates that the model can accurately predict the size of small obstacles. The GA-BP neural network-based small obstacle size prediction method proposed in this paper is simple to execute, has good real-time performance, and provides a new, to the best of our knowledge, way of thinking for mobile robots to acquire environmental data.

Dynamical Mechanisms of Vortex Pinning in Superfluid Thin Films.

We characterize the mechanisms of vortex pinning in a superfluid thin film described by the two-dimensional Gross-Pitaevskii equation. We consider a vortex "scattering experiment" whereby a single vortex in a superfluid flow interacts with a circular, uniform pinning potential. By an analogy with linear dielectrics, we develop an analytical hydrodynamic approximation that predicts vortex trajectories, the vortex fixed point and the unpinning velocity. We then solve the Gross-Pitaevskii equation to validate this model, and build a phase portrait of vortex pinning. We identify two different dynamical pinning mechanisms marked by distinctive phonon emission signatures: one enabled by acoustic radiation and another mediated by vortex dipoles nucleated within the pin. Relative to obstacle size, we find that pinning potentials on the order of the healing length are more effective for vortex capture. Our results could be useful in mitigating the negative effects of drag due to vortices in superfluid channels, in analogy to maximizing supercurrents in type-II superconductors.

A homogenised model for flow, transport and sorption in a heterogeneous porous medium

A major challenge in flow through porous media is to better understand the link between microstructure and macroscale flow and transport. For idealised microstructures, the mathematical framework of homogenisation theory can be used for this purpose. Here, we consider a two-dimensional microstructure comprising an array of obstacles of smooth but arbitrary shape, the size and spacing of which can vary along the length of the porous medium. We use homogenisation via the method of multiple scales to systematically upscale a novel problem involving cells of varying area to obtain effective continuum equations for macroscale flow and transport. The equations are characterised by the local porosity, a local anisotropic flow permeability, an effective local anisotropic solute diffusivity and an effective local adsorption rate. These macroscale properties depend non-trivially on the two degrees of microstructural geometric freedom in our problem: obstacle size and obstacle spacing. We exploit this dependence to construct and compare scenarios where the same porosity profile results from different combinations of obstacle size and spacing. We focus on a simple example geometry comprising circular obstacles on a rectangular lattice, for which we numerically determine the macroscale permeability and effective diffusivity. We investigate scenarios where the porosity is spatially uniform but the permeability and diffusivity are not. Our results may be useful in the design of filters or for studying the impact of deformation on transport in soft porous media.

UAV low-altitude obstacle detection based on the fusion of LiDAR and camera

In this paper, aiming at the flying scene of the small unmanned aerial vehicle (UAV) in the low-altitude suburban environment, we choose the sensor configuration scheme of LiDAR and visible light camera, and design the static and dynamic obstacle detection algorithms based on sensor fusion. For static obstacles such as power lines and buildings in the low-altitude environment, the way that image-assisted verification of point clouds is used to fuse the contour information of the images and the depth information of the point clouds to obtain the location and size of static obstacles. For unknown dynamic obstacles such as rotary-wing UAVs, the IMM-UKF algorithm is designed to fuse the distance measurement information of point clouds and the high precision angle measurement information of image to achieve accurate estimation of the location and velocity of the dynamic obstacles. We build an experimental platform to verify the effectiveness of the obstacle detection algorithm in actual scenes and evaluate the relevant performance indexes.