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Lattice-based mechanical metamaterials can be tailored for a wide variety of applications by modifying the underlying mesostructure. However, most existing lattice patterns take symmetry as a starting point. We show that asymmetric lattice patterns can be more likely to have certain mechanical properties than symmetric lattice patterns. To directly compare the effects of asymmetric versus symmetric lattice arrangements, a constrained design space is defined. A generative design process is used to generate both symmetric and asymmetric lattice patterns within the design space. Asymmetric lattice patterns are shown to have distinct metamaterial property spaces from symmetric lattice patterns. Key design features are identified that are present predominantly in asymmetric lattice patterns. We show that asymmetric lattice patterns with two of these features (arrows and spider nodes) are more likely to induce a broader range of Poisson's ratios and larger shear stiffness values, respectively, compared to lattice patterns without these features. In addition, we show that symmetry can play a role in hampering the impact of multiple features when present. This work provides insights into the benefits of using asymmetric lattice patterns in select metamaterial design applications.

The past decade has witnessed a growing interest in lunar exploration missions. The autonomy of lunar surface and in-orbit missions is, however, dependent on accurate and instantaneous navigation services. These services can not be provided by current Global Navigation Satellite Systems (GNSS) whose signals suffer from poor geometry and coverage in the vicinity of the Moon. Preliminary results of a systems architecture study on a new satellite navigation system orbiting the moon are presented. Lunar frozen orbit conditions under J2, C22 and third-body perturbations are assumed. The formulation includes the following design decisions: (1) Orbit semi-major axis, (2) Number of satellites, (3) Number of orbital planes, (4) Satellite phasing in adjacent planes, (5) Orbit eccentricity and (6) Argument of periapsis.The Borg Multi-Objective Evolutionary Algorithm (MOEA) framework is used to optimize the satellite constellation design problem, with a fitness function that takes into account performance, cost, availability and station-keeping deltaV. The performance metric is based on the Geometric Dilution of Precision (GDOP), which is computed over a grid of 500 equidistant points on the lunar surface. Additionally, the input satellite orbits used in the GDOP computation are obtained from high-fidelity orbit propagation using NASA General Mission Analysis Toolbox. Finally, satellite costs are based on satellite dry mass estimates derived from the power budget analysis assuming a satellite lifetime of 10 years. Results show that Lunar GNSS constellation with 20 satellites at frozen orbits can achieve satisfactory performance at mid-latitudes but not at the poles., Comment: 8 pages, 6 figures

Global Navigation Satellite Systems (GNSS) provide ubiquitous, continuous and reliable positioning, navigation and timing information around the world. However, GNSS space segment design decisions have been based on the precursor Global Positioning System (GPS), which was designed in the 70s. This paper revisits those early design decisions in view of major technological advancements and new GNSS environmental threats. The rich tradespace between User Navigation Error (UNE) performance and constellation deployment costs is explored and conclusions are complemented by sensitivity analysis and association rule mining. This study finds that constellations at an orbit altitude of ~2 Earth radii can outperform existing GNSS in terms of cost, robustness and UNE. These insights should be taken into account when designing future generations of GNSS., Comment: 22 pages, submitted to IEEE Transactions on Aerospace and Electronic Systems, second round of review Corrected figure 10

This paper describes the objectives and current status of the 3D-CHESS project which aims to demonstrate a new Earth observing strategy based on a context-aware Earth observing sensor web. This sensor web consists of a set of nodes with a knowledge base, heterogeneous sensors, edge computing, and autonomous decision-making capabilities. Context awareness is defined as the ability for the nodes to gather, exchange, and leverage contextual information (e.g., state of the Earth system, state and capabilities of itself and of other nodes in the network, and how those states relate to the dy- namic mission objectives) to improve decision making and planning. The current goal of the project is to demonstrate proof of concept by comparing the performance of a 3D- CHESS sensor web with that of status quo architectures in the context of a multi-sensor inland hydrologic and ecologic monitoring system.