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At least 181 records · Page 10

The Plasma Wake Downstream of Lunar Topographic Obstacles: Preliminary Results from 2D Particle Simulations

Anticipating the plasma and electrical environments in permanently shadowed regions (PSRs) of the moon is critical in understanding local processes of space weathering, surface charging, surface chemistry, volatile production and trapping, exo-ion sputtering, and charged dust transport. In the present study, we have employed the open-source XOOPIC code [I] to investigate the effects of solar wind conditions and plasma-surface interactions on the electrical environment in PSRs through fully two-dimensional pattic1e-in-cell simulations. By direct analogy with current understanding of the global lunar wake (e.g., references) deep, near-terminator, shadowed craters are expected to produce plasma "mini-wakes" just leeward of the crater wall. The present results (e.g., Figure I) are in agreement with previous claims that hot electrons rush into the crater void ahead of the heavier ions, fanning a negative cloud of charge. Charge separation along the initial plasma-vacuum interface gives rise to an ambipolar electric field that subsequently accelerates ions into the void. However, the situation is complicated by the presence of the dynamic lunar surface, which develops an electric potential in response to local plasma currents (e.g., Figure Ia). In some regimes, wake structure is clearly affected by the presence of the charged crater floor as it seeks to achieve current balance (i.e. zero net current to the surface).

Zimmerman, Michael I.↗

Numerical approach of collision avoidance and optimal control on robotic manipulators

Collision-free optimal motion and trajectory planning for robotic manipulators are solved by a method of sequential gradient restoration algorithm. Numerical examples of a two degree-of-freedom (DOF) robotic manipulator are demonstrated to show the excellence of the optimization technique and obstacle avoidance scheme. The obstacle is put on the midway, or even further inward on purpose, of the previous no-obstacle optimal trajectory. For the minimum-time purpose, the trajectory grazes by the obstacle and the minimum-time motion successfully avoids the obstacle. The minimum-time is longer for the obstacle avoidance cases than the one without obstacle. The obstacle avoidance scheme can deal with multiple obstacles in any ellipsoid forms by using artificial potential fields as penalty functions via distance functions. The method is promising in solving collision-free optimal control problems for robotics and can be applied to any DOF robotic manipulators with any performance indices and mobile robots as well. Since this method generates optimum solution based on Pontryagin Extremum Principle, rather than based on assumptions, the results provide a benchmark against which any optimization techniques can be measured.

Wang, Jyhshing Jack↗

Computer vision techniques for rotorcraft low altitude flight

Rotorcraft operating in high-threat environments fly close to the earth's surface to utilize surrounding terrain, vegetation, or manmade objects to minimize the risk of being detected by an enemy. Increasing levels of concealment are achieved by adopting different tactics during low-altitude flight. Rotorcraft employ three tactics during low-altitude flight: low-level, contour, and nap-of-the-earth (NOE). The key feature distinguishing the NOE mode from the other two modes is that the whole rotorcraft, including the main rotor, is below tree-top whenever possible. This leads to the use of lateral maneuvers for avoiding obstacles, which in fact constitutes the means for concealment. The piloting of the rotorcraft is at best a very demanding task and the pilot will need help from onboard automation tools in order to devote more time to mission-related activities. The development of an automation tool which has the potential to detect obstacles in the rotorcraft flight path, warn the crew, and interact with the guidance system to avoid detected obstacles, presents challenging problems. Research is described which applies techniques from computer vision to automation of rotorcraft navigtion. The effort emphasizes the development of a methodology for detecting the ranges to obstacles in the region of interest based on the maximum utilization of passive sensors. The range map derived from the obstacle-detection approach can be used as obstacle data for the obstacle avoidance in an automatic guidance system and as advisory display to the pilot. The lack of suitable flight imagery data presents a problem in the verification of concepts for obstacle detection. This problem is being addressed by the development of an adequate flight database and by preprocessing of currently available flight imagery. The presentation concludes with some comments on future work and how research in this area relates to the guidance of other autonomous vehicles.

Sridhar, Banavar↗

Stereo Vision Based Terrain Mapping for Off-Road Autonomous Navigation

Successful off-road autonomous navigation by an unmanned ground vehicle (UGV) requires reliable perception and representation of natural terrain. While perception algorithms are used to detect driving hazards, terrain mapping algorithms are used to represent the detected hazards in a world model a UGV can use to plan safe paths. There are two primary ways to detect driving hazards with perception sensors mounted to a UGV: binary obstacle detection and traversability cost analysis. Binary obstacle detectors label terrain as either traversable or non-traversable, whereas, traversability cost analysis assigns a cost to driving over a discrete patch of terrain. In uncluttered environments where the non-obstacle terrain is equally traversable, binary obstacle detection is sufficient. However, in cluttered environments, some form of traversability cost analysis is necessary. The Jet Propulsion Laboratory (JPL) has explored both approaches using stereo vision systems. A set of binary detectors has been implemented that detect positive obstacles, negative obstacles, tree trunks, tree lines, excessive slope, low overhangs, and water bodies. A compact terrain map is built from each frame of stereo images. The mapping algorithm labels cells that contain obstacles as no-go regions, and encodes terrain elevation, terrain classification, terrain roughness, traversability cost, and a confidence value. The single frame maps are merged into a world map where temporal filtering is applied. In previous papers, we have described our perception algorithms that perform binary obstacle detection. In this paper, we summarize the terrain mapping capabilities that JPL has implemented during several UGV programs over the last decade and discuss some challenges to building terrain maps with stereo range data.

passive perception↗

Resource Assessment for Distributed Wind Energy: An Evaluation of Best-Practice Methods in the Continental US

Current wind resources within the United States (US) indicate a potential to profitably install nearly 1,400 gigawatts of distributed wind (DW) capacity. This amount is equivalent to over half of the United States’ current energy demand from electricity, making it enough to power millions of homes and businesses and replace countless fossil fuel-based generating plants. Despite the potential growth of DW in the US, deployments are presently hindered by a lack of confidence in resource estimation methods. One potential challenge is that smaller-scale turbines, with hub heights of 40 meters or less, are disproportionately impacted by obstacles such as buildings and vegetation. These obstacles may produce complex wake effects, best modeled with high-fidelity complex fluid dynamics (CFD) models that are too computationally expensive to use for routine siting and resource assessment. Thus, installers today make use of heuristics and simple equations to approximate the impact of obstacles while also leveraging long-term resource data from commercial or publicly available atmospheric models. This study evaluates these historical and commonly used methods alongside new lower-order obstacle models produced from CFD simulations and measurement-based bias correction. The preliminary results from this study show the importance of taking care in the choice and application of mesoscale atmospheric models and the significant value of bias correction using measurements from nearby meteorological towers. Detailed obstacle modeling provides only modest additional gains in performance and, in some cases, can add error, especially at sites where turbines have already been located to avoid obvious impact from upwind obstacles. These findings reinforce the importance of collecting in situ measurements and suggest that obstacle models may be better applied in practice to automated or computer-aided siting, rather than in economic wind resource assessments.

17 WIND ENERGY↗

TEM Approaches for Microstructure-Informed Prediction of Mechanical Properties in Structural Alloys

Predicting the mechanical performance of structural alloys from their evolving microstructure remains a major challenge in materials science, particularly for nuclear structural materials, where irradiation-induced defects span multiple types and length scales and interact through complex mechanisms. The dispersed barrier hardening (DBH) [1] and Friedel–Kroupa–Hirsch (FKH) [2,3] models have been widely used to evaluate the hardening contributions of individual obstacles and to estimate tensile strength from quantified microstructures; however, when multiple size-dependent obstacles coexist and evolve, predicting temperature-dependent tensile strength becomes significantly more complex, and a fully consistent hardening model is still lacking. Transmission electron microscopy (TEM) plays a central role in refining hardening models and enabling predictive assessments of tensile strength evolution by providing quantitative characterization of dislocations, irradiation-induced defects (e.g., dislocation loops and cavities), precipitates, and grain structure (Fig. 1.). These experimentally measured defect densities are incorporated into physically based hardening models with size- and shape- dependent obstacle strengths [4], using root-sum-square superposition for obstacles of comparable strength and linear superposition for dissimilar ones [5]. In addition, recent advances in TEM [6-8], including high-resolution imaging, 4D-STEM strain mapping, EDS/EELS elemental analysis, and flash-polishing-based TEM specimen preparation and extraction-replica methods (Fig. 2), further improve the accuracy of microstructural quantification. By comparison with prior studies as well as our own results, we show that when TEM-derived microstructural information is carefully integrated with physically grounded hardening models, yield strength (or irradiation-induced hardening) measured at room temperature can be predicted with good quantitative agreement across multiple alloy classes. In-situ TEM combined with high-temperature mechanical testing represents an important next step for refining hardening models by directly probing dislocation–obstacle interactions across varying irradiation doses and temperatures [9]. Because the barrier strength factor (α) depends on both temperature and obstacle size, it should not be treated as a constant fitting parameter; rather, it must be explicitly evaluated to achieve physically meaningful predictions of mechanical behaviour at operating temperatures. This presentation therefore discusses why all strengthening contributions (e.g., Peierls stress, solid-solution strengthening, voids, bubbles, dislocation loops, dislocation lines, and grain boundaries) must be considered collectively, why appropriate superposition methods are essential when obstacles possess different barrier strength factors, how hardness measurements can be meaningfully related to tensile properties, and how TEM-derived microstructural information can be systematically incorporated into hardening models. More broadly, it outlines a pathway toward microstructure-informed prediction of mechanical properties and supports the goal of establishing science-based tools for evaluating structural materials in extreme environments [10].

Lin, Yan-Ru [ORNL] (ORCID:0000000339991473)↗

The solar wind interaction with Venus

The Pioneer Venus Orbiter (PVO) mission has played a key role in establishing the nature of the solar wind interaction with Venus. Although earlier probes had determined that Venus presented an obstacle much smaller than the size of earth's magnetosphere to the solar wind, they did not carry out in situ measurements pertaining to solar wind interaction studies at low enough altitudes to determine why. They also did not provide datasets of sufficient duration to study the variability of the interaction of both short (one day) and long (solar cycle) timescales. The first 600 of the nearly 5000 orbits of PVO magnetometer data have been used to determine a very low upper limit on the intrinsic dipolar magnetic moment of Venus. The consequence of that low magnetic moment is that the solar wind interacts directly with the upper atmosphere and ionosphere. Relative to a dipolar field obstacle, the ionospheric obstacle is rather incompressible. A bow shock is observed to stand in front of the nearly Venus-sized ionospheric obstacle at a comparatively steady subsolar altitude of approximately 1.5 R(v) (Venus radii). This shock decelerates the supersonic solar wind plasma so that it can flow around the obstacle. It was found to change its average position in the terminator plane from about 2.4 R(v) to 2.1 R(v) as the solar cycle progressed from the 1978 orbit insertion near solar maximum through the 1986-87 solar minimum, and back again during the latest solar activity increase. Between the bow shock and the ionosphere proper, the slowed solar wind plasma flow diverges near the subsolar point and makes its way across the terminator where it reaccelerates and continues anti-Sunward. The solar wind magnetic field, which is in effect frozen into the flowing plasma, is distorted in this 'magnetosheath' region so that it appears to hang up or drape over the dayside ionosphere before it slips around with the flow. These features of the solar wind interaction are also seen when the obstacle is a dipole magnetic field, but there are two important distinctions. In the wake of the Venus obstacle one finds an induced magnetic tail composed of varying interplanetary fields rather than the constant fields of intrinsic origin. This magnetotail is further seen to be populated by Heavy (0+) ions that are evidently escaping from the planet at significant (approximately 10(exp -25) s(exp -1)) rates. These heavy ions are also observed in the dayside magnetosheath. The interpretation is that ions are produced by both photoionization and solar wind electron impact ionization of the upper neutral atmosphere that extends into the magnetosheath.

Luthmann, J. G.↗

Sheaths: A Comparison of Magnetospheric, ICME, and Heliospheric Sheaths

When a supersonic flow encounters an obstacles, shocks form to divert the flow around the obstacle. The region between the shock and the obstacle is the sheath, where the supersonic flow is compressed, heated, decelerated, and deflected. Supersonic flows, obstacles, and thus sheaths are observed on many scales throughout the Universe. We compare three examples seen in the heliosphere, illustrating the interaction of the solar wind with obstacles of three very different scales lengths. Magnetosheaths form behind planetary bow shocks on scales ranging from tens to 100 planetary radii. ICME sheath form behind shocks driven by solar disturbances on scale lengths of a few to tens of AU. The heliosheath forms behind the termination shock due to the obstacle presented by the interstellar medium on scale lengths of tens to a hundred AU. Despite this range in scales some common features have been observed. Magnetic holes, possibly due to mirror mode waves, have been observed in all three of these sheaths. Plasma depletion layers are observed in planetary and ICME sheaths. Other features observed in some sheaths are wave activity (ion cyclotron, plasma), energetic particles, transmission of Alfven waves/shocks, tangential discontinuities turbulence behind quasi-parallel shocks, standing slow mode waves, and reconnection on the obstacle boundary. We compare these sheath regions, discussing similarities and differences and how these may relate to the scale lengths of these regions.

Sibeck, D. G.↗

Building wakes in disturbed layers

The wind profiles in the wakes of buildings in a disturbed shear layer are investigated for conditions experienced during aircraft take-off and landing. Experiments were conducted in a pipe flow apparatus in which an equilibrium flow is disturbed by pipe roughness, simulating obstacles upwind of a building, with the disturbed flow made to flow past a second obstacle, simulating a building. Velocity and turbulence profiles of disturbed and equilibrium flows upstream and downstream of the obstacles are presented. It is concluded that the integrated momentum flow of a boundary layer behind an obstacle can be greater than the upstream momentum flow, if the exponent of the upstream velocity profile is sufficiently high and the boundary layer has been disturbed by upstream obstacles. The rise of the turbulence level behind the obstacle is also dependent on the profile exponent in a disturbed layer.

Logan, E.↗

Spacecraft-environment interaction: The environmental plasma aspect

The effects involved in the interaction between an obstacle and a space plasma can be divided into: (1) effects on the obstacle itselt (i.e., its charging); and (2) effects on the environmental plasma due to the motion of the obstacle (i.e., the creation of shocks ahead of the obstacle and complicated wakes behind the obstacle). In the wake (or antisolar direction), plasma oscillations are excited and instabilities, wave-particle interactions, turbulence, etc., are believed to take place. The effects on the obstacle and on the environmental space plasma are coupled. Hence, simultaneous solutions to the Vlasov (or Boltzmann) and Poisson equations are sought. To obtain realistic solutions of practical use, three-dimensional and time-dependent models of the interaction are needed. Achieving the latter is indeed not simple.

Samir, U.↗

Mixing and Noise Benefit Versus Thrust Penalty in Supersonic Jets Using Impingement Tones

This paper reports the results of an experimental investigation on the effect of impingement tones generated by obstacles of various geometries on the spreading of a supersonic jet flow. A rectangular supersonic jet was produced using a convergent-divergent nozzle that was operated near its design point (with shocks minimized). The immersion of obstacles in the flow produced an intense impingement tone which then propagated upstream (as feedback) to the jet lip and excited the antisymmetric hydrodynamic mode in the jet, thus setting up a resonant self-sustaining loop. The violent flapping motion of the jet due to excitation of the antisymmetric mode, combined with the unsteady wakes of the obstacles, produced large changes in jet mixing. It was possible to control the frequency and amplitude of the impingement tone excitation by varying the nozzle-to-obstacle distance and the obstacle immersion. By proper shaping of the obstacles it was possible to reduce the thrust penalty significantly.

Raman, Ganesh↗

Small UAV Flight Planning in Urban Environments

This work proposes a fast algorithm for generating obstacle-free and wind-efficient flight paths at a constant above-ground-level altitude in urban environments because a fast flight path planning algorithm is an essential function or service needed for enabling small unmanned aerial vehicle (sUAV) to operate in urban environments within Class G airspace. The proposed method first converts the 3D path planning problem to a 2D problem by constructing an obstacle map at a given above-ground-level altitude. A quad-tree decomposition is then used to build a search space in terms of obstacle occupancy and wind difference. The wind cost of traveling through each cell is defined based on energy consumption under various wind conditions. A repulsive potential is also adopted to make sure that the flight plans stay away from obstacles. The Theta* search algorithm, a variant of A* algorithm, is applied to mitigate the path angle change constraints introduced by grid-based graphs. With the Theta* and postsmoothing techniques, an obstacle-free, wind efficient, and constant above-ground-level flight plan can be quickly generated for sUAV operations in urban environments while meeting the lateral path angle constraints. The results showed that the path planning algorithm is efficient and can be finished within several seconds. With a proper choice of wind coefficient, the proposed path planning algorithm outperforms the multiple-shooting trajectory optimization method even in an obstacle-free environment. With the flexibility of incorporating other geo-related costs and computation efficiency, the proposed algorithm shows the potential for real-time flight path planning in complex urban environments.

Path planning↗

Computer vision techniques for rotorcraft low-altitude flight

A description is given of research that applies techniques from computer vision to automation of rotorcraft navigation. The effort emphasizes the development of a methodology for detecting the ranges to obstacles in the region of interest based on the maximum utilization of passive sensors. The range map derived from the obstacle detection approach can be used as obstacle data for the obstacle avoidance in an automataic guidance system and as advisory display to the pilot. The lack of suitable flight imagery data, however, presents a problem in the verification of concepts for obstacle detection. This problem is being addressed by the development of an adequate flight database and by preprocessing of currently available flight imagery. Some comments are made on future work and how research in this area relates to the guidance of other autonomous vehicles.

Sridhar, Banavar↗

Teleautonomous guidance for mobile robots

Teleautonomous guidance (TG), a technique for the remote guidance of fast mobile robots, has been developed and implemented. With TG, the mobile robot follows the general direction prescribed by an operator. However, if the robot encounters an obstacle, it autonomously avoids collision with that obstacle while trying to match the prescribed direction as closely as possible. This type of shared control is completely transparent and transfers control between teleoperation and autonomous obstacle avoidance gradually. TG allows the operator to steer vehicles and robots at high speeds and in cluttered environments, even without visual contact. TG is based on the virtual force field (VFF) method, which was developed earlier for autonomous obstacle avoidance. The VFF method is especially suited to the accommodation of inaccurate sensor data (such as that produced by ultrasonic sensors) and sensor fusion, and allows the mobile robot to travel quickly without stopping for obstacles.

Borenstein, J.↗

Technologies for automating rotorcraft nap-of-the-earth flight

This paper discusses the technologies required for automating rotorcraft nap-of-the-earth flight, where the use of natural obstacles for masking from the enemy is intentional and the danger of undesirable obstacles such as enemy traps is real. Specifically, the automatic guidance structure is modeled by three decision-making levels: the far-field mission planning and the mid-field terrain-masking trajectory shaping are both driven by prestored terrain data, whereas the nearfield obstacle detection/avoidance is driven by real-time on-board sensor data. This paper summarizes the far-field and mid-field accomplishments, and reports on the status of the more-recent efforts in obstacle detection and avoidance development. Obstacle detection is based primarily on passive imaging sensors for the desirable properties of covertness and wide field of view, although active sensors are included in the structure to provide the much needed high resolution for thin-wire detection.

Cheng, Victor H. L.↗

Neural network structure for navigation using potential fields

A hybrid-network method for obstacle avoidance in the truck-backing system of D. Nguyen and B. Widrow (1989) is presented. A neural network technique for vehicle navigation and control in the presence of obstacles has been developed. A potential function which peaks at the surface of obstacles and has its minimum at the proper vehicle destination is computed using a network structure. The field is guaranteed not to have spurious local minima and does not have the property of flattening-out far from the goal. A feedforward neural network is used to control the steering of the vehicle using local field information. The network is trained in an obstacle-free space to follow the negative gradient of the field, after which the network is able to control and navigate the truck to its target destination in a space of obstacles which may be stationary or movable.

Plumer, Edward S.↗