Browse Topic: Cartography
Axles are a prominent part of automotive design. Along with a power transmission and differential system, axles support a vehicle’s weight and road-load reactions. Axles carry different attachments such as brakes and suspensions using brackets. Welds play an important role in design and longevity of bracket assemblies. Welds can be susceptible to fractures caused by intrusions akin to cracks and/or discontinuities, compounded by stress concentration due to weld profile and welding processes. Additionally, the simultaneous optimization of both brackets and welds remains a challenge with limited available methods. While topography or shape optimization techniques can enhance bracket robustness by minimizing compliance as the objective, this approach might inadvertently elevate the likelihood of weld fracture if weld dimensions are not concurrently updated. In this endeavor, compliance is used to improve weld life without affecting bracket robustness by using the Vertex Morphing optimization technique. Existing weld dimensions are kept intact. Structural Stress Method is one of the widely accepted method available to calculate weld fatigue life using nodal forces. These nodal forces are optimized to achieve a desired improvement. Optimized design demonstrates significant improvement in weld fatigue life without affecting bracket robustness. This method can be used in conjunction with other optimization techniques and can be leveraged in concept design as well.
When measuring with light, the lateral extent of the structures that can be resolved by an optical imaging system is fundamentally diffraction limited. Overcoming this limitation is a topic of great interest in recent research, and several approaches have been published in this area. In a recent study published in the Journal of Optical Microsystems, a team of researchers from the University of Kassel in Germany presented an approach that uses microspheres placed directly on the surface of the object to extend the limits of interferometric topography measurements for optical resolution of small structures.
In an increasingly solar world, the need is growing for economical, large-scale backup systems to provide power when the sun is down and the air is calm. Lithium-ion (Li-ion) batteries are too expensive, and other options — such as pumped hydro — require specific topography that’s not always available.
An object hidden below ground has been located using quantum technology — a long-awaited milestone with profound implications for industry, human knowledge, and national security.
This paper introduces recent developments in the computation of rotorcraft noise footprint, implemented in an Airbus Helicopters' internal software. The paper presents the main ingredients that have led to enhance the efficiency and accuracy of such noise footprint computation. This includes taking into account both the particularities of turns in noise emission and the influence of the wind on noise propagation. Furthermore, the software is able to assess a real traffic environmental impact, since computations are done within a realistic 3D simulation environment, taking into account both the curvature of the Earth and the topography of the ground. A variety of noise annoyance indicators can be computed thanks to the coupling with demographic and background noise data. Such realistic noise footprint computation is embedded in a tailored algorithmic scheme aiming at optimizing rotorcraft trajectories in such a way that their associated noise footprint is minimized. The proposed optimization approach has been tested on multiple real-world case studies, showing significant prospective noise reduction compared to reference trajectories.
An analysis of shoreline change, dune volume, beach volume, beach slope, and cumulative elevation change along the northern Outer Banks of North Carolina near the CHL Field Research Facility over a 6-year study period. Army Engineer Research and Development Center, Vicksburg, Mississippi The dynamic nature of the nation's coastlines necessitates frequent shoreline monitoring and mapping. The U.S. Army Engineer Research and Development Center, Coastal and Hydraulics Laboratory (CHL), Field Research Facility (FRF), has collected datasets on the nearshore zone's changing conditions for over 40 years. During the course of these efforts, CHL has continued to develop different technologies to refine shoreline monitoring techniques, with a particular focus on the application of remote sensing technology to coastal monitoring. Light detection and ranging (lidar) scanners have proven useful for the CHL coastal measurement efforts, providing highly detailed data of coastal change and hydrodynamic processes. Lidar is frequently collected from stationary ground-based platforms, which provide fine detail (100s to 1000s of points per meter) in one location or mobile airborne sampling approaches that provide coverage over large areas but at lower resolution (1 to 10s of points per meter). The U.S. Army Corps of Engineers (USACE), U.S. Naval Oceanographic Office, and National Oceanic and Atmospheric Administration (NOAA) formed the Joint Airborne Lidar Bathymetry Technical Center of eXpertise in 1998 to support coastal mapping requirements and committed to surveying the U.S. coastline every 5 years with airborne lidar. As a result of these and other efforts, coastal monitoring with airborne lidar data has provided a range of insights into coastal change since the late 1990s.
The dynamic nature of the nation’s coastlines necessitates frequent shoreline monitoring and mapping. The U.S. Army Engineer Research and Development Center, Coastal and Hydraulics Laboratory (CHL), Field Research Facility (FRF), has collected datasets on the nearshore zone’s changing conditions for over 40 years. During the course of these efforts, CHL has continued to develop different technologies to refine shoreline monitoring techniques, with a particular focus on the application of remote sensing technology to coastal monitoring. Light detection and ranging (lidar) scanners have proven useful for the CHL coastal measurement efforts, providing highly detailed data of coastal change and hydro-dynamic processes.
ABSTRACT Future autonomous combat vehicles will need to travel off-road through poorly mapped environments. Three-dimensional topography may be known only to a limited extent (e.g. coarse height), but this will likely be noisy and of limited resolution. For ground vehicles, 3D topography will impact how far ahead the vehicle can “see”. Higher vantage points and clear views provide much more useful path planning data than lower vantage points and occluded views from trees and structures. The challenge is incorporating this knowledge into a path planning solution. When should the robot climb higher to get a better view or else continue moving along the shortest path predicted by current information? We investigated the use of Deep Q-Networks (DQN) to reason over this decision space, comparing performance to conventional methods. In the presence of significant sensor noise, the DQN was more successful in finding a path to the target than A* for all but one type of terrain. Citation: E. Martinson, B. Purman, A. Dallas, “Topography Dependent Path Planning”, In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI, Aug. 10-12, 2021.
Highly autonomous vehicles have drawn the interests of many researchers in recent years. For highly autonomous vehicles, a high-definition (HD) map is crucial since it provides accurate information for autonomous driving. However, due to the possible fast-changing environment, the performance of HD maps will deteriorate over time if timely updates are not ensured. Therefore, this paper studies the updating of lightweight HD maps in closed areas. Firstly, a novel two-layer map model called a lightweight HD map is introduced to support autonomous driving in a flexible and efficient way. Secondly, typical updating of scenarios in closed areas with non-paved roads is abstracted into operations including area border expansion, road addition, and road deletion. Meanwhile, a map updating framework is proposed to address the issue of map updating in closed areas. Finally, an experiment is conducted to demonstrate the feasibility and effectiveness of the proposed map updating approach.
A wet clutch model is required in automotive propulsion system simulations for enabling robust design and control development. It commonly assumes Coulomb friction for simplicity, even though it does not represent the physics of hydrodynamic torque transfer. In practice, the Coulomb friction coefficient is treated as a tuning parameter in simulations to match vehicle data for targeted conditions. The simulations tend to deviate from actual behaviors for different drive conditions unless the friction coefficient is adjusted repeatedly. Alternatively, a complex hydrodynamic model, coupled with a surface contact model, is utilized to enhance the fidelity of system simulations for broader conditions. The theory of elastic asperity deformation is conventionally employed to model clutch surface contact. However, recent examination of friction material shows that the elastic modulus of surface fibers significantly exceeds the contact load, implying no deformation of fibers. This article investigates the friction material contact mechanics through numerical simulations. A surface model is constructed based on microscopic examination of material topography and properties. An FEM simulation is conducted to examine the interactions between surface fibers and the surrounding medium under loaded conditions. The change in real contact area with respect to nominal surface pressure correlates qualitatively the simulations and experiments. The numerical study provides insight into frictional material contact mechanics that is not directly observable. It also supports the assumptions behind an empirical fiber contact model that was recently introduced to enhance hydrodynamic clutch models.
A Montreal-based company leverages artificial intelligence to take on the task of developing high-definition maps of Canada. Fully-automated vehicles will only be as smart as the datasets they use to determine their driving pathways. Jakarto Cartographie 3D, a young company based in Montreal, Canada, is working on artificial-intelligence (AI)-powered, high-definition (HD) maps that it claims offer 2-3 cm (.787- to 1.2-inch) absolute precision and relative precision measured in millimeters. In other words, better maps that will allow for better automated vehicles (AVs). Started two years ago, Jakarto currently has three Nissan NV200 mapping vans equipped with a data collection unit that contains five cameras, a GPS unit and two ZF-supplied lidar sensors that each generate one million points per second. Jakarto calls the resulting maps RoadSkeleton, claiming they'll be beneficial for smart cities and AVs.
ABSTRACT To address the need for rapid capture of terrain profiles, and changes in terrain, researchers from Michigan Tech demonstrated a UAS collection system, during a live exercise, supported by the North Atlantic Treaty Organization’s (NATO) Science and Technology Organization (STO). The UAS collection system was deployed to provide high resolution topography (resolution less than 1 cm) with a terrain collection rate greater than 1 meter per second and results were processed within minutes. The resulting topography is of sufficient quality to demonstrate that the technique can be applied to update mobility models, as well as the detection of traverse by ground vehicles.
Sector mesh modeling is the dominant computational approach for combustion system design optimization. The aim of this work is to quantify the errors descending from the sector mesh approach through three geometric modeling approaches to an optical diesel engine. A full engine geometry mesh is created, including valves and intake and exhaust ports and runners, and a full-cycle flow simulation is performed until fired TDC. Next, an axisymmetric sector cylinder mesh is initialized with homogeneous bulk in-cylinder initial conditions initialized from the full-cycle simulation. Finally, a 360-degree azimuthal mesh of the cylinder is initialized with flow and thermodynamics fields at IVC mapped from the full engine geometry using a conservative interpolation approach. A study of the in-cylinder flow features until TDC showed that the geometric features on the cylinder head (valve tilt and protrusion into the combustion chamber, valve recesses) have a large impact on flow complexity. As a result, errors in near-TDC swirl ratio, vortex structure and turbulence availability were seen when employing sector meshing, even if a 360-degree sector, with direct IVC flow mapping, was used. During injection, lack of geometric details on the head led to the inability to predict the formation of an upper recirculation region on the tumbling plane, above the piston step, which has been associated with thermal efficiency benefits with the stepped-lip bowl. Initialization of the flow anisotropies in the cylinder resulting from the intake process at IVC were instead seen to have a smaller effect. The results also showed that tuning IVC quantities in a sector mesh cannot effectively compensate for its missing geometric and flow details.
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