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Abstract The demand for contactless, rapid manufacturing has increased over the years, especially during the COVID-19 pandemic. Additive manufacturing (AM), a type of rapid manufacturing, is a computer-based system that precisely manufactures products. It proves to be a faster, cheaper, and more efficient production system when integrated with cloud-based manufacturing (CBM). Similarly, the need for semiconductors has grown exponentially over the last five years. Several companies could not keep up with the increasing demand for many reasons. One of the main reasons is the lack of a workforce due to the COVID-19 protocols. This article proposes a novel technique to manufacture semiconductor chips in a fast-paced manner. An algorithm is integrated with cloud, machine vision, sensors, and email access to monitor with live feedback and correct the manufacturing in case of an anomaly.

This document defines the characteristics necessary to standardize the airborne recorder download file format in order to facilitate data import, transcription, and exchange. A standardized data format will reduce the variety of readout equipment required for airborne recorder data transcription. This document defines the detailed architecture of the Recorder Standard Output (RSO) file. The architecture is a tagged file structure within which many different files and their formats can be supported. The structure is necessary to support newer recording requirements for flight data, data link, audio, and image recording. This structure is intended for use with all civil recorders and should support use with military recorders.

Traditional ground vehicle architectures comprise of a chassis connected via passive, semi-active, or active suspension systems to multiple ground wheels. Current design-optimizations of vehicle architectures for on-road applications have diminished their mobility and maneuverability in off-road settings. Autonomous Ground Vehicles (AGV) traversing off-road environments face numerous challenges concerning terrain roughness, soil hardness, uneven obstacle-filled terrain, and varying traction conditions. Numerous Active Articulated-Wheeled (AAW) vehicle architectures have emerged to permit AGVs to adapt to variable terrain conditions in various off-road application arenas (off-road, construction, mining, and space robotics). However, a comprehensive framework of AAW platforms for exploring various facets of system architecture/design, analysis (kinematics/dynamics), and control (motions/forces) remains challenging.

The aerospace industry is facing immense challenges due to increased design complexity and higher levels of integration, particularly in the electrification of aircraft. These challenges can easily impact program cost and product time to market. System electrification and electromagnetic compatibility (EMC) have become critical issues today. In the context of 3D electromagnetics, EMC electromagnetic compatibility ensures the original equipment manufacturer (OEM) that radiated emissions from various electronic devices, such as avionics or the entire aircraft for that matter, do not interfere with other electronic products onboard the aircraft.

Thermal Management Techniques in Avionics Cooling Curing the Porosity Problem in Additive Manufacturing Space-Qualified Crystal Oscillators Reimagining Automated Test During a Pandemic EW: New Challenges, Technologies, and Requirements Software Enables New-Age, Flexible Test Solution for Analog and Digital Radios Formal Process Modeling to Improve Human-Decision-Making During Test and Evaluation Range Control Using the Innoslate software tool to formally model the process of conducting test range events can expose previously overlooked ambiguities and identify high-value decision points? Test and Evaluation of Autonomy for Air Platforms Tools, approaches, and insights to confidently approach the safe, secure, effective, and efficient testing of autonomy on air platforms.

Abstract The advancement in vision sensors and embedded technology created the opportunity in autonomous vehicles to look ahead in the future to avoid potential obstacles and steep regions to reach the target location as soon as possible and yet maintain vehicle safety from rollover. The present work focuses on developing a nonlinear model predictive controller (NMPC) for a high-speed off-road autonomous vehicle, which avoids undesirable conditions including stationary obstacles, moving obstacles, and steep regions while maintaining the vehicle safety from rollover. The NMPC controller is developed using CasADi tools in the MATLAB environment. The CasADi tool provides a platform to formulate the NMPC problem using symbolic expressions, which is an easy and efficient way of solving the optimization problem. In the present work, the vehicle lateral dynamics are modeled using the Pacejka nonlinear tire model.

Alternative fuels and propulsion poised for growth in US fleets

As powertrain hybridization technologies are becoming popular, their application for heavy-duty military vehicles is drawing attention. An intelligent design and operation of the energy management system (EMS) is important to ensure that hybrid military vehicles can operate efficiently, simultaneously maximize fuel economy and minimize monetary cost, while successfully completing mission tasks. Furthermore, an integrated EMS framework is vital to ensure a functional vehicle power system (VPS) to survive through critical missions in a highly stochastic environment, when needed. This calls for situational awareness and dynamic system reconfiguration capabilities on-board of the military vehicle. This paper presents a new energy management and control (EMC) framework based on holistic situational awareness (SA) and dynamic reconfiguration of the VPS.

This third edition of Automatic Target Recognition provides a roadmap for breakthrough ATR designs―with increased intelligence, performance, and autonomy. Clear distinctions are made between military problems and comparable commercial deep-learning problems. These considerations need to be understood by ATR engineers working in the defense industry as well as by their government customers. A reference design is provided for a next-generation ATR that can continuously learn from and adapt to its environment. The convergence of diverse forms of data on a single platform supports new capabilities and improved performance. This third edition broadens the notion of ATR to multisensor fusion. Radical continuous-learning ATR architectures, better integration of data sources, well-packaged sensors, and low-power teraflop chips will enable transformative military designs.

This work covers the historical development of Built-In-Test (BIT) for fiber optic interconnect links for aerospace applications using Optical Time Domain Reflectometry (OTDR) equipped transceivers. The original failure modes found that installed fiber optic links must be disconnected before diagnosis could begin, often resulting in “no fault found” (NFF) designation. In fact, the observed root cause was that most (85%) of the fiber optic link defects were produced by contamination of the connector end faces. In March of 2006, a fiber optics workshop was held with roughly sixty experts from system and component manufacturers to discuss the difficulties of fiber optic test in aerospace platforms. During this meeting it was hypothesized that Optical Time Domain Reflectometry (OTDR) was feasible using an optical transceiver transmit pulse as a stimulus. The time delay and amplitude of received reflections would correlate with the position and severity of link defects, respectively.