Advancements in the field of artificial intelligence (AI) are accelerating as the technology matures from being research-orientated to being deployed in a wide range of products and services, such as autonomous vehicles. While Convolutional Neural Networks (CNNs) were first described in the 1950s, the technology remained an academic concept until the availability of large training data sets and powerful Graphics Processor Units (GPUs), a processor architecture ideal for the heavy math computational demands associated with neural network processing. Once scientists had low-cost and high-performance platforms, the technology exploded for many commercial uses. Military use is more challenging due to the lack of large data sets, but that is changing too as areas including thermal imagery are starting to be used.

When firing artillery, there is typically a maximum angle that the platform cannot exceed relative to the Earth plane. This is due to the large recoil forces involved and the risk of destabilizing the platform the weapon is mounted to. Mobile systems are particularly sensitive to this as the attitude of the platform relative to Earth is constantly changing. A simple solution is to add pitch and roll sensors directly to the platform. However, many mobile systems already have an assortment of sensors that can be used to calculate the platform attitude.

Motivated by the demand for an even larger storage capacity in the information era, research efforts have been devoted to the development of more efficient and cost-effective memory elements.

Content addressable memory (CAM) is one of the most promising hardware solutions for high-speed data searching and has many practical applications such as anti-virus scanners, internet protocol (IP) filters, and network switches. Since CAM stores the data in its internal memory elements and compares them with the search data in parallel, it can achieve much faster speed compared to the software lookup.

Rugged Servers with Skylake Architecture

Themis Computer^® (Fremont, CA) announced the launch of its next generation XR6 Rugged Enterprise Servers (RES) featuring the newest Intel^® Xeon^® Scalable (Skylake) Processors.

Plain bearings are used across a wide range of aerospace applications to help achieve better fuel efficiency, extend maintenance intervals, and lower carbon emissions. These applications include installation in aircraft wing systems (flaps, spoilers, and slats), flight controls, cockpit controls, auxiliary power units, landing gear, door systems, and aircraft interiors (seats, bins, latches, and hinge points). “Our plain bearings even have a footprint on Mars,” said Brett Ricci, GGB Aerospace Strategic Account Manager for North America. “Operating in temperatures between -200°C to +280°C, our plain bearings have served as the primary suspension components in the robotic drilling arm of NASA’s Curiosity Mars Rover since 2012.”

Additive Manufacturing (AM) is growing in importance as a fabrication process for the space industry, enabling weight and cost savings through optimized designs for components. The use of AM gives aerospace engineers an alternative to more traditional manufacturing processes, but also retains the challenge of producing parts without defects. These problems can be approached using nondestructive methods such as X-ray Computed Tomography (CT) and Finite Element Modelling (FEM) to inspect geometries and quantify the impact of defects on the mechanical properties of a part, taking into account factors such as internal stress from metal cooling during fabrication.

Structural analysis of solid rocket motors is challenging for several reasons, but the most important of these is the complex behavior of the propellant. The mechanical response of a solid propellant is time and temperature dependent. The complexity of the mathematical analysis of the propellant depends on the loading conditions, but for some loading situations, the linear viscoelasticity assumption is reasonable. In particular, linear viscoelasticity is perhaps the most appropriate material behavior description for use in the simulations of stresses related to storage conditions. Typically, simulations use a viscoelastic model in the form of a Prony series and a Williams–Landel–Ferry (WLF) equation. The parameters in these models are derived from stress relaxation experiments, making the stress relaxation experiment a key viscoelastic test, analogous to the tensile test for linear elastic materials.

Kinematically ground polygonal shapes have been used as drive connections for more than 45 years. What is now referred to as Polygon Systems was developed by Fortunawerke, Stuttgart, West Germany, who patented a grinding machine capable of producing matched polygonal shaft and bore diameters.

Microelectromechanical systems (MEMS) three-axis acceleration threshold sensors have been developed to measure acceleration threshold levels using voltage switching when the threshold is reached. Switches with different damping coefficients result in different mechanical impedances and response times. Analytical and numerical methods to model damping coefficient values based on empirical data are needed to characterize three-axis acceleration sensors; traditional methods use the displacement of an underdamped system to calculate the damping ratio.