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This paper describes an approach to integrating high-fidelity vehicle dynamics with a high-fidelity gaming engine, specifically with respect to terrain. The work is motivated by the experimental need to have both high-fidelity visual content with high-fidelity vehicle dynamics to drive a motion base simulator. To utilize a single source of terrain information, the problem requires the just-in-time sharing of terrain content between the gaming engine and the dynamics model. The solution is implemented as a client-server with the gaming engine acting as a stateless server and the dynamics acting as the client. The client is designed to actively maintain a locally cashed terrain grid around the vehicle and actively refresh it by polling the server in an on-demand mode of operation. The paper discusses the overall architecture, the protocol, the server, and the client designs. A practical implementation is described and shown to effectively function in real-time.

Materials play a key role in our day to day life and have shaped the industrial revolution to a great extent. Right selection of material for meeting a particular objective is the key to success in today’s world where the cost as well as sustainability of any equipment or a system have assumed greater significance than ever before. In automotive industry, materials have a definitive role as far as the mobility and safety is concerned. Materials that can absorb the required energy or impact can be manufactured through different manufacturing as well as metallurgical processes which involves appropriate heat treatment and bringing correct chemical compositions etc. However, they can also be formed by simpler methods such as combining certain materials together in the form of layered combinations to form light weight composites.

Abstract An accurate Unmanned Aerial System (UAS) Flight Dynamics Model (FDM) allows us to design its efficient controller in early development phases and to increase safety while reducing costs. Flight tests are normally conducted for a pre-established number of flight conditions, and then mathematical methods are used to obtain the FDM for the entire flight envelope. For our UAS-S4 Ehecatl, 216 local FDMs corresponding to different flight conditions were utilized to create its Local Linear Scheduled Flight Dynamics Model (LLS-FDM). The initial flight envelope data containing 216 local FDMs was further augmented using interpolation and extrapolation methodologies, thus increasing the number of trimmed local FDMs of up to 3,642. Relying on this augmented dataset, the Support Vector Machine (SVM) methodology was used as a benchmarking regression algorithm due to its excellent performance when training samples could not be separated linearly.

Abstract Letter from the Guest Editors

Abstract Fighter pilots must study models of aircraft dynamics before learning complex maneuvers and tactics. Similarly, autonomous fighter aircraft applications may benefit from a model-based learning approach. Instead of using a preexisting physics model of a given aircraft, a machine learning system can learn a predictive model of the aircraft physics from training data. Furthermore, it can model interactions between multiple friendly aircraft, enemy aircraft, and the environment. Such a system can also learn to represent state variables that are not directly observable, as well as dynamics that are not hard coded. Existing model-based methods use a deep neural network that takes observable state information and agent actions as input and provides predictions of future observations as output. The proposed method builds upon this approach by adding a residual feedforward skip connection from some of the inputs to all of the outputs of the deep neural network.

Almost 75% of all elements are metals. Metals can be classified as either ferrous or non-ferrous and generally conduct electricity and heat well. Most metals are malleable and ductile and are, in general, heavier than other elemental substances. The following six eLearning courses are included in the Materials bundle. Each course is approximately one-hour in duration. See topics/outline for additional details. Introduction to Metals, Ferrous Metals, Nonferrous Metals, Classification of Steel, Essentials of Heat Treatment of Steel Exotic Alloys

Ferrous metals contain iron and are prized for their tensile strength and durability. Most are magnetic and contain a high carbon content which generally makes them, with the exception of wrought iron and stainless steel, vulnerable to rust. The following seven eLearning courses are included in the Ferrous Materials Bundle: Steel and Cast Iron. Each course is approximately one-hour in duration. Modules include: Introduction to Physical Properties, Introduction to Mechanical Properties, Introduction to Metals, Hardness Testing, Ferrous Metals, Classification of Steel, Essentials of Heat Treatment of Steel.

While traveling on any type of ground, the damper of a vehicle has the critical task of attenuating the vibrations generated by its irregularities, to promote safety, stability, and comfort to the occupants. To reach that goal, several passive dampers projects are optimized to embrace a bigger frequency range, but, by its limitations, many studies in semiactive and active dampers stands out by promoting better control of the vehicle dynamics behavior. In the case of military vehicles, which usually have more significant dimensions than the common ones and can run on rough or unpaved lands, the use of semi-active or active dampers reveals itself as a promising alternative. Motivated by that, the present study performs an analysis of the vertical dynamics of a wheeled military vehicle with four axles, using magnetorheological dampers. This study is made using a configuration of the distances between the axles of the vehicle, which is chosen from five available options.

We present an approach in which we use simulation to capture the two-way coupling between the dynamics of a vehicle and that of a fluid that sloshes in a tank attached to the vehicle. The simulation is carried out in and builds on support provided by two modules: Chrono::FSI (Fluid-Solid Interaction) and Chrono::Vehicle. The dynamics of the fluid phase is governed by the mass and momentum (Navier-Stokes) equations, which are discretized in space via a Lagrangian approach called Smoothed Particle Hydrodynamics. The vehicle dynamics is the solution of a set of differential algebraic equations of motion. All equations are discretized in time via a half-implicit symplectic Euler method. This solution approach is general - it allows for fully three dimensional (3D) motion and nonlinear transients. We demonstrate the solution in conjunction with the simulation of a vehicle model that performs a constant radius turn and double lane change maneuver.

This Aerospace Standard (AS) is to be used as a supplement to SAE AS7109. In addition to the requirements contained in AS7109, the requirements contained herein shall apply to suppliers seeking NADCAP Coatings accreditation who are engaged in thermal spray.

This Aerospace Standard (AS) is to be used as a supplement to SAE AS7109. In addition to the requirements contained in AS7109, the requirements contained herein shall apply to suppliers seeking NADCAP Coatings accreditation who are engaged in stripping of coated material.