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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.

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.

Abstract This article investigates the fuel savings potential of a series hybrid military truck using a simultaneous battery pack design and powertrain supervisory control optimization algorithm. The design optimization refers to the sizing of the lithium-ion battery pack in the hybrid configuration. The powertrain supervisory control optimization determines the most efficient way to split the power demand between the battery pack and the engine. Despite the available design and control optimization techniques, a generalized mathematical formulation and solution approach for combined design and control optimization is still missing in the literature. This article intends to fill that void by proposing a unified framework to simultaneously optimize both the battery pack size and power split control sequence. This is achieved through a combination of genetic algorithm (GA) and Pontryagin’s minimum principle (PMP) where the design parameters are integrated into the Hamiltonian function.

Abstract In the last decades we have witnessed an increasing number of military operations in urban environments. Complex urban operations require high standards of training, equipment, and personnel. Emergency forces on the ground will need specialized vehicles to support them in all parts and levels of this extremely demanding environment including the subterranean and interior of infrastructure. The development of vehicles for this environment has lagged but offers a high payoff. This article describes the method for developing a concept for an urban operations vehicle by characterization of the urban environment, deduction of key issues, evaluation of related prototyping, science fiction story-typing of the requirements for such a vehicle, and comparison with field-proven and scalable solutions. Embedding these thoughts into a comprehensive research and development program provides lines of development, setting the stage for further research.

Abstract Presently, 270 V direct current (DC) systems replace older 28 V DC voltage systems in both the civil and military aviation industry due to the requirement for more electrical power needs on board. Therefore, the existing avionics require retrofitting. The conversion from 270 V to 28 V appears to be quite promising for both old and new systems. This study aims to design an interleaved synchronous modular buck converter topology as a candidate for these requirements. Calculations for the converter design are conducted considering aviation standards. Switching with pulse-width modulation (PWM) is used to control the power converter. A double-loop feedback control system based on voltage and current feedback is designed. Therefore, the buck converter circuit with 1145 W power output is proposed, which supplies a 28 V and 41 A DC output from a 270 V DC input. The concept is verified using simulations and hardware-in-the-loop (HIL) experimental results.

Abstract To assist in initializing the conceptual design of hypersonic aircraft, we outline a new, systematic framework based on historical aircraft data and primarily composed of design data and regression models. It is a rapid, low-fidelity analysis to provide a starting point for the conceptual design process by (1) assessing the performance capabilities of four types of high-speed aircraft, (2) providing initial estimates for weights and geometry with uncertainty, and (3) exploring how changes in these affect performance within design spaces. Using this framework, an initial set of reasonable aircraft configurations is obtained based on speed, altitude, and payload requirements, which can serve to accelerate the design process and avoid unforeseen problems later in the design cycle. An example is provided to demonstrate the application of the framework to launch the conceptual design of a new hypersonic aircraft with a given set of mission requirements.

Abstract Autonomy has the potential to make the most radical impact by significantly reducing the number of soldiers in harm’s way and changing the military paradigm. Benefits of autonomy to improve the Army’s mission capabilities and the rapid evolution of military systems exerts pressure to develop these systems quickly. Since the associated technological development is highly fast paced and stochastic, approaches that develop systems for stochastic future scenarios are required. In this article we present a vision for the autonomous high-mobility military systems for that future. We discuss the ramifications of autonomy in five areas: (1) fleet organization, (2) physical attributes of high-mobility military systems, (3) individual behaviors of autonomous assets, (4) interactions between humans and autonomous systems, and (5) operation and teaming strategies. We present the future vision, implications, requirements, and technological challenges for each of the five areas.

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.

Abstract TOC

Abstract Threat identification and security analysis have become mandatory steps in the engineering design process of high-assurance systems, where successful cyberattacks can lead to hazardous property damage or loss of lives. This article describes a novel approach to perform security analysis on embedded systems modeled at the architectural level. The tool, called Security Threat Evaluation and Mitigation (STEM), associates threats from the Common Attack Pattern Enumeration and Classification (CAPEC) library with components and connections and suggests potential defense patterns from the National Institute of Standards and Technology (NIST) Special Publication (SP) 800-53 security standard. This article also provides an illustrative example based on a drone package delivery system modeled in AADL.