11115 research outputs found
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Development of a standard maritime \u3ci\u3eC\u3csup\u3e2\u3c/sup\u3e\u3csub\u3en\u3c/sub\u3e\u3ci\u3e model using satellite measurements
No full textQuantifying ambient aerosol absorption and scatter from nano- and micro-particle number concentrations
No full textInfrastructure Planning for Multi-Vehicle Routing with Cooperative Localization
No full textExcerpt: The scope of this paper pertains to the problem of multi-vehicle cooperative navigation in a known environment, where known features are identified for localization
Uncertainty Quantification by Probabilistic Analysis of Stirling Engine Performance
No full textA Stirling engine thermodynamic cycle was computationally simulated and probabilistically evaluated in view of the several uncertainties in the performance parameters. Cumulative distribution functions and sensitivity factors were computed for the overall thermal efficiency and net specific power output due to the thermodynamic random variables. These results can be used to quickly identify the most critical design variables in order to optimize the design, enhance performance, increase system availability and make it cost effective. The analysis leads to the selection of the appropriate measurements to be used in the Stirling engine health determination and to the identification of both the most critical measurements and parameters. Probabilistic analysis aims at unifying and improving the control and health monitoring of Stirling engine by increasing the quality and quantity of information available about the engine’s health and performance
Mechanical Response of Cylindrically Mapped Triply Periodic Minimal Surface Structures Under Combined Loading
No full textThis work explored combined tensile and torsional loads applied to additively manufactured Inconel 718 specimens employing Triply Periodic Minimal Surface (TPMS) structures. The gyroid TPMS unit cell was selected with two variations of cylindrical cell maps by varying arc count. The 4-arc and 8-arc structures were tested in an axial-torsion test frame at room temperature using equal parts of vertical and angular displacement control until failure. The data from the tests were compared to finite element analysis models to visualize when yielding was predicted. Finally, the fracture surfaces were investigated with a scanning electron microscope to characterize the primarily ductile fracture
Magnetic Field Variability as a Consistent Predictor of Solar Flares
No full textSolar flares are intense bursts of electromagnetic radiation that occur due to a rapid destabilization and reconnection of the magnetic field. While preflare signatures and trends have been investigated from magnetic observations prior to flares for decades, analysis that characterizes the variability of the magnetic field in the hours prior to flare onset has not been included in the literature. Here, the 3D magnetic field is modeled using a nonlinear force-free field extrapolation for 6 hr before and 1 hr after 18 on-disk solar flares and flare quiet windows for each active region. Parameters are calculated directly from the magnetic field from two field isolation methods: the “active region field,” which isolates field lines where the photospheric field magnitude is ≥200 Gauss, and the “high current region,” which isolates field lines in the 3D field where the current, nonpotential field, twist, and shear exceed predefined thresholds. For this small pool of clean events, there is a significant increase in variation starting 2–4 hr before flare onset for the current, twist, shear, and free energy, and the variation continues to increase through the flare start time. The current, twist, shear, and free energy are also significantly stronger through the lower corona and their separation from flare quiet height curves scales with flare strength. Methods are proposed to combine variation of the magnetic fields with variation of other data products prior to flare onset, suggesting a new potential flare prediction capability
Quantifying capability gaps via information relaxation and deep reinforcement learning in infinite-horizon Markov decision processes: A military air battle management application
No full textExcerpt: This paper presents a novel application of information relaxation techniques to quantify upper bounds on solution quality in a complex, stochastic, and dynamic assignment problem in military air battle management. Information relaxation refers to relaxing the non-anticipativity constraints in a sequential decision-making problem that require a decision-maker to act only on currently available information. We introduce a temporal event horizon—–an adjustable window into future stochastic outcomes—–to explore the marginal value of information in shaping decision policies
Analysis of the Circular Restricted N-Body Problem (CRNBP) in the Sun-Venus System
No full textThird-body dynamical approximations such as the Circular Restricted 3-Body Problem (CR3BP) have become ubiquitous in orbital mechanics in determining useful trajectories in systems with two massive bodies and a spacecraft. These models provide a better estimation of real-world trajectories than the simple 2-Body Problem (2BP), but the addition of a greater number of massive celestial bodies to gain insights into the effect of additional gravitational perturbations would enable the design of more accurate trajectories without reliance on a higher-fidelity ephemerides n-body model. As this extension to the CR3BP, the Circular Restricted N-body Problem (CRNBP) was first presented in 2022 by Negri and Prado [1]. Using that CRNBP model, initial conditions from the Sun-Venus CR3BP are propagated numerically in CRNBP for multiple orbit types to include the gravitational effects of Mercury and Earth. The resulting trajectories are compared between the two models, demonstrating that significant perturbing effects and a reliance on the initial phase angles of the tertiary and quaternary bodies exist. Some trajectories and initial phase angle cases are identified to be less perturbed over the time period of propagation, which may aid in the selection of more stable trajectories or the selection of an initial epoch at which to enter certain orbits. This analysis demonstrates the main benefit of the CRNBP model. Additionally, the application of Poincaré mapping to this problem and the challenges with this approach are examined