Getting Experimental Data to End Users via a Research to Operations Paradigm
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The deterministic radiation transport code HZETRN (High charge (Z) and Energy TRaNsport) was developed by NASA to study the effects of cosmic radiation on astronauts and instrumentation shielded by various materials. This work presents an analysis of computed differential flux from HZETRN compared with measurement data from three balloon-based experiments over a range of atmospheric depths, particle types, and energies. Model uncertainties were quantified using an interval-based validation metric that takes into account measurement uncertainty both in the flux and the energy at which it was measured. Average uncertainty metrics were computed for the entire dataset as well as subsets of the measurements (by experiment, particle type, energy, etc.) to reveal any specific trends of systematic over- or under-prediction by HZETRN. The distribution of individual model uncertainties was also investigated to study the range and dispersion of errors beyond just single scalar and interval metrics. The differential fluxes from HZETRN were generally well-correlated with balloon-based measurements; the median relative model difference across the entire dataset was determined to be 30%. The distribution of model uncertainties, however, revealed that the range of errors was relatively broad, with approximately 30% of the uncertainties exceeding ± 40%. The distribution also indicated that HZETRN systematically under-predicts the measurement dataset as a whole, with approximately 80% of the relative uncertainties having negative values. Instances of systematic bias for subsets of the data were also observed, including a significant underestimation of alpha particles and protons for energies below 2.5 GeV/u. Muons were found to be systematically over-predicted at atmospheric depths deeper than 50 g/cm(sup 2) but under-predicted for shallower depths. Furthermore, a systematic under-prediction of alpha particles and protons was observed below the geomagnetic cutoff, suggesting that improvements to the light ion production cross sections in HZETRN should be investigated.
Transition models based on auxiliary transport equations augmenting the Reynolds-averaged Navier-Stokes (RANS) framework often rely upon the correlations that were derived from a limited number of low-speed experiments and do not account for all of the transition mechanisms and/or their variation with the significant flow parameters. Available data from a recent experiment in the National Transonic Facility at the NASA Langley Research Center are used to assess the current transition modeling capability in NASA's OVERFLOW 2.2o code for a swept wing configuration at transonic cruise conditions. Specifically, the OVERFLOW solutions are used together with detailed stability analysis of the boundary layer flow over the new Common Research Model with Natural Laminar Flow (CRM-NLF) to evaluate the accuracy and the robustness of the transport-equation-based transition models, with the goal of proposing improvements that would help to strengthen the physical basis of these models for the important class of flows involving the combined effects of crossflow and flow compressibility. Results highlight the significant underprediction of the laminar flow extent within the inboard region of the wing, wherein the onset of transition may be attributed to a gradual amplification of Tollmien-Schlichting instabilities.
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Transition models based on auxiliary transport equations augmenting the Reynolds-averaged Navier-Stokes (RANS) framework often rely upon transition correlations that were derived from a limited number of low-speed experiments and these models often fail to account for all of the relevant transition mechanisms and/or the variation in those mechanisms with respect to changes in the significant flow parameters. Available data from a recent experiment on the Common Research Model with Natural Laminar Flow (CRM-NLF) in the National Transonic Facility at the NASA Langley Research Center are used to assess the current transition modeling capability in NASA's OVERFLOW 2.3b solver for a swept wing configuration with nonzero taper and transonic cruise conditions. Specifically, the OVERFLOW solutions are used to evaluate the accuracy and robustness of the transport-equation-based transition models. Results highlight that the Spalart-Allmaras-based amplification factor transport (AFT-2017b) equation model and Menter’s shear-stress transport equation (SST2003)-based Langtry-Menter transition models (either with or without the modeling of crossflow transition) significantly underpredict the reported extent of laminar flow region over the entire span of the wing, irrespective of which instability mechanism(s) is expected to dominate the onset of the transition process. We show that the transition correlations underlying these models fail to account for the stabilizing effect of compressibility on the Tollmien-Schlichting transition, which is likely to be a major contributor to the underprediction of the laminar flow region on the CRM-NLF. The SST-2003-based Langtry-Menter model also appears to inaccurately predict the chordwise pressure variation along the majority of the wing span at all the flow conditions studied herein, due to how the turbulence intensity levels were enforced in the computations and how that was interfering with the functioning of the underlying turbulence model within the boundary layer. The AFT and Langtry-Menter models appear to be sensitive to the level of the freestream turbulence intensity, but the degree of sensitivity varies across the models.
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Small unmanned aircraft and electric vertical takeoff and landing (eVTOL) aircraft have recently emerged as vehicles able to perform new missions and stimulate future air transportation methods. This dissertation presents several system identification research advancements for these modern aircraft configurations enabling accurate mathematical model development for flight dynamics simulations based on wind-tunnel and flight-test data. The first part of the dissertation focuses on advances in flight-test system identification methods using small, fixed-wing, remotely-piloted, electric, propeller-driven aircraft. A generalized approach for flight dynamics model development for small fixed-wing aircraft from flight data is described and is followed by presentation of novel flight-test system identification applications, including: aero-propulsive model development for propeller aircraft and nonlinear dynamic model identification without mass properties. The second part of the dissertation builds on established fixed-wing and rotary-wing aircraft system identification methods to develop modeling strategies for transitioning, distributed propulsion, eVTOL aircraft. Novel wind-tunnel experiment designs and aero-propulsive modeling approaches are developed using a subscale, tandem tilt-wing, eVTOL aircraft, leveraging design of experiments and response surface methodology techniques. Additionally, a method applying orthogonal phase-optimized multisine input excitations to aircraft control effectors in wind-tunnel testing is developed to improve test efficiency and identified model utility. Finally, the culmination of this dissertation is synthesis of the techniques described throughout the document to form a flight-test system identification approach for eVTOL aircraft that is demonstrated using a high-fidelity flight dynamics simulation. The research findings highlighted throughout the dissertation constitute substantial progress in efficient empirical aircraft modeling strategies that are applicable to many current and future aeronautical vehicles enabling accurate flight simulation development, which can subsequently be used to foster advancement in many other pertinent technology areas.
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In this article, we present the datasets collected from nine different Li-ion batteries. These datasets contain voltage, current and time measurements during a full charge-discharge cycle of a battery at very low current (that is nearly at �/30 rate). Such low current rate data is suitable for open circuit voltage characterization. The collection of this data was done through the use of an Arbin battery cycler and a thermal chamber was used to control the test temperature. Data were collected over a wide range of temperatures from −25∘C to 50∘C.
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