11115 research outputs found
Sort by
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
Varying Fidelity Comparative Analysis of Space Shuttle (STS-1) Reentry Dynamics
No full textThis paper describes concepts, modeling decisions, and engineering approximations that can be used to develop reentry simulations at various degree(s)-of-freedom (DOF). Included in this paper is a methodology for simulating the inaugural flight of the Space Shuttle (STS-1) from 3DOF to 6DOF. This paper uniquely quantifies trajectory state error to consolidate information that quantifies simulation error due to various design choices. Utilizing this methodology, it is demonstrated that the maximum error incurred by a Newtonian panel-method is O(10−3). Additionally, in 6DOF, various tracking control solutions including first and second-order attitude controllers are implemented to compare various estimation methods for tracking a specified control solution. Error analysis for each DOF simulation show that 4DOF modeling accurately captures the desired translational state trajectory; however, 6DOF modeling is necessary to properly consider the control torque. This paper demonstrates how various challenges to 6DOF modeling can be overcome to produce accurate reconstructions of a complex reentry scenario
The Relative Effects of Internal Reynolds Number and Advective Capacity Ratio on the Coolant Warming Factor
No full textConjugate heat transfer experiments to predict turbine component temperatures involve matching the Biot number of the experimental condition to that of the engine condition. Done properly, such an experiment could yield an overall effectiveness distribution that is relevant to the engine condition. However, the underlying theory suggests that the coolant warming factor, χ, must also be matched to achieve the desired effect, and the requirements to do so have been neglected in the literature. Additionally, little success has been achieved in determining the theoretical requirements to match χ. In this work, we develop these requirements, apply them for when coolant flow is scaled by the Reynolds number ratio and advective capacity ratio, and test them by comparing computational results against experimental data. The findings from this study indicate a strong influence of the thermal conductivity of the coolant. Interestingly, a thermal conductivity inappropriately large will have opposite effects on the coolant warming factor depending on which coolant flow rate parameter is used to characterize the coolant flow. Knowledge of the subtle requirements to properly replicate the coolant warming factor in an experiment will allow turbine designers to achieve more accurate surface temperature predictions through properly designed experiments
The Effects of proton irradiation on the current–voltage and capacitance–voltage characteristics of GeSn/Si photodiodes
No full text
Global Ionospheric F Region Parameters From GNSS-POD Limb Measurements: Evaluations and Comparisons With Two Empirical Models - IRI-2020 and NeQuick-2
No full textAn optimal estimation (OE) technique has recently been developed for F region electron density (Ne) using Global Navigation Satellite System (GNSS) limb sounding on low Earth orbit (LEO) satellites (COSMIC-2, Spire, and FengYun-3). This method provides unprecedented spatiotemporal sampling for global monthly Ne climatology within 100–500 km in 2 hr intervals. The global dataset, collected during mid to moderately high solar activity, is compared with leading models: IRI-2020 and NeQuick-2. Diurnal variations in summer, winter, and equinoctial months are examined for the F2-layer peak, as well as the topside and bottomside of the F region. The observed and modeled NmF2 and hmF2 show good agreement during the daytime, but discrepancies appear with NeQuick-2 at night. The OE-retrieved dataset reveals distinct interhemispheric differences in topside scale height between the summer and winter hemispheres, which are not adequately captured by models. The estimated topside scale heights in IRI-2020 are ~20–30 km higher than observations on regional scale, but this difference decreases to ~12–20 km on global scale. In the bottomside, the agreement between observations and models varies significantly between daytime and nighttime conditions. During the daytime, the global bottomside thicknesses derived from OE-retrieved profiles agree within 10 km with the IRI-2020, but they are ~10–15 km higher than NeQuick-2. The nighttime thicknesses differ substantially, with deviations reaching up to ~30 km compared to IRI-2020 and ~45 km compared to NeQuick-2. As models face challenges due to lack of reliable measurements, especially in the topside and bottomside, improvements in GNSS-LEO observing techniques can provide more accurate and comprehensive data to characterize the global ionosphere