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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Quantifying Pilot Contribution to Flight Safety During Dual Generator Failure

Accident statistics cite flight crew error in over 60% of accidents involving transport category aircraft. Yet, a well-trained and well-qualified pilot is acknowledged as the critical center point of aircraft systems safety and an integral safety component of the entire commercial aviation system. No data currently exists that quantifies the contribution of the flight crew in this role. Neither does data exist for how often the flight crew handles non-normal procedures or system failures on a daily basis in the National Airspace System. A pilot-in-the-loop high fidelity motion simulation study was conducted by the NASA Langley Research Center in partnership with the Federal Aviation Administration (FAA) to evaluate the pilot's contribution to flight safety during normal flight and in response to aircraft system failures. Eighteen crews flew various normal and non-normal procedures over a two-day period and their actions were recorded in response to failures. To quantify the human's contribution, crew complement was used as the experiment independent variable in a between-subjects design. Pilot actions and performance when one of the flight crew was unavailable were also recorded for comparison against the nominal two-crew operations. This paper details diversion decisions, perceived safety of flight, workload, time to complete pertinent checklists, and approach and landing results while dealing with a complete loss of electrical generators. Loss of electrical power requires pilots to complete the flight without automation support of autopilots, flight directors, or auto throttles. For reduced crew complements, the additional workload and perceived safety of flight was considered unacceptable.

Etherington, Timothy J.↗
DOE OSTI2023

Investigation of process history and underlying phenomena associated with the synthesis of plutonium oxides using Vector Quantizing Variational Autoencoder

Accurate, high throughput, and unbiased analysis of plutonium oxide particles is needed for analysis of the phenomenology associated with process parameters in their synthesis. Compared to qualitative and taxonomic descriptors, quantitative descriptors of particle morphology through scanning electron microscopy (SEM) have shown success in analyzing process parameters of uranium oxides. Among other candidates, a neural network called a Vector Quantizing Variational Autoencoder (VQ-VAE) has shown the ability to quantitatively describe particle morphology to attain >85% accuracy in identifying uranium oxide processing routes. We utilize a VQ-VAE to quantitatively describe plutonium dioxide (PuO 2 ) particles created in a designed experiment and investigate their phenomenology and prediction of their process parameters. PuO 2 was calcined from Pu(III) oxalates that were precipitated under varying synthetic conditions that related to concentrations, temperature, addition and digestion times, precipitant feed, and strike order; the surface morphology of the resulting PuO 2 powders were analyzed by SEM. A pipeline was developed to extract and quantify useful image representations for individual particles with the VQ-VAE, then further reduce the dimensionality of the feature space using a bottlenecking neural network fit to perform multiple classification tasks simultaneously. The reduced feature space could predict process parameters with greater than 80% accuracies for some parameters with a single particle. They also showed utility for grouping particles with similar surface morphology characteristics together. Both the clustering and classification results reveal valuable information regarding which chemical process parameters chiefly influence the PuO 2 particle morphologies: strike order and oxalic acid feedstock. Doing the same analysis with multiple particles was shown to improve the classification accuracy on each process parameter over the use of a single particle, with statistically significant results generally seen with as few as four particles in a sample.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Nanostructures for Electrical Energy Storage (NEES) (2020 Final Technical Report)

Nanostructures for Electrical Energy Storage (NEES, www.efrc.umd.edu) was an Energy Frontier Research Center supported by the DOE Office of Science, Basic Energy Sciences, from 8/1/2009 to 7/31/2020. Led by the University of Maryland, NEES enjoyed extensive collaborations with its funded partners, including two DOE Laboratories and six universities. The NEES vision has been to reveal a set of scientific insights and design principles that can underpin a next-generation electrical energy storage approach, building on advances in nanoscale science and technology to achieve simultaneous high power and high energy over extended charge/discharge cycling. The vision is motivated by the recognition that scaling into the nano regime opens the door to new physical phenomena and that the tools enlisted in nanoscale research provide major new opportunities for the synthesis not only of materials at molecular scale but for structures at nano scale and above. NEES has translated this vision into its research program based on two observations. First, while the behavior of ions and electrons in electrolytes and in electrode materials is crucial to electrical energy storage (or more appropriately electrochemical energy storage), it is the transport of ion and electron charge between different structural components of a storage device that ultimately determine its performance. With it well recognized that the choice of electrode materials typically constrain ion transport kinetics as well as maximum ion concentration, the search for better electrode materials has been a primary driver of battery research. At the same time the synthesis of electrodes is typically based on aggregation of particles with varying size, shape, and orientation in the electrode. Together with the presence of additional materials to impart electrical conductivity and cohesion to the composite electrode, change in electrode materials is necessarily accompanied by structural changes at the nano/micro scale that are difficult to categorize and manage. From the beginning, NEES’ vision has been to create and study simpler, highly controlled spatial arrangements of known materials as battery components (electrodes, current collectors, and electrolyte) and to understand how design and structure above the molecular scale determines the energy storage performance available from known materials. Second, advances in nanoscience dramatically expanded the portfolio of synthesis methods, structural motifs, and new phenomena available for research. Some of these gave rapid access to new building blocks at the deep nanoscale (e.g., carbon nanotubes grown by self-assembly, nanoscale arrays formed by electrochemical self-alignment, monolayer films controlled by self-limiting reaction). Such advances served as the enabler for the NEES vision to be pursued experimentally through study of 3D structures created and controlled at the nano, micro, and meso scales. Here, we use meso as in the BES MESO Report, implying not only intermediate or varying length scales, but very much the way behavior is influenced by other factors including aggregation of nanocomponents at different densities and spatial configurations, statistical variations in the aggregates, hierarchical architectures in which they can be assembled, or local 3D configurations that result from the architectures. Over its life cycle, NEES has pursued two overarching goals: (1) to understand the scientific fundamentals of electrochemical storage from the nanoscale to the mesoscale; and (2) to create and learn from innovative, controlled, heterogeneous nanostructures, where such nanostructures can enable the first goal and serve as models for future paradigms in energy storage. Specific goals have included: Synthesize heterogeneous nanostructures comprised of multiple materials arranged in controlled fashion and characterize their behavior; Demonstrate and elucidate design principles for achieving simultaneous high power and high energy; Develop materials processes which enable precision control of thin layers and 3D structures; Investigate the impact of artificial interphases on electrode stability during ion insertion/deinsertion; Create dense arrays of nanostructures to understand how the architecture of these assemblies, along with nanostructure design, influences energy storage behavior at the mesoscale; Identify and understand the consequences of nanoconfinement and local inhomogeneities in 3D mesoscale arrays; Develop and apply computational models to stimulate, guide and interpret experiments.

25 ENERGY STORAGE↗
DOE OSTI2025

PROTOCALC, a W -band Polarized Calibrator for Cosmic Microwave Background Telescopes: Application to Simons Observatory and CLASS

Current- and next-generation cosmic microwave background (CMB) experiments will measure polarization anisotropies with unprecedented sensitivities. The need for high precision in these measurements underscores the importance of gaining a comprehensive understanding of instrument properties, with a particular emphasis on the study of the beam properties, and especially their polarization characteristics and the measurement of the polarization angle. In this context, a major challenge lies in the scarcity of millimeter polarized astrophysical sources with sufficient brightness and calibration knowledge to meet the stringent accuracy requirements of future CMB missions. This led to the development of a drone-borne calibration source designed for the frequency band centered on approximately 90 GHz, matching a commonly used channel in ground-based CMB measurements. The Prototype Calibrator for Cosmology, PROTOCALC, has undergone thorough in-lab testing, and its properties have been subsequently modeled through simulation software integrated into the standard Simons Observatory analysis pipeline. Moreover, the PROTOCALC system has been tested in the field, having been deployed twice on calibration campaigns with CMB telescopes in the Atacama Desert. The data collected constrain the roll angle of the source with a statistical accuracy of 0$^°_•$045.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

A multi-year short-range hindcast experiment with CESM1 for evaluating climate model moist processes from diurnal to interannual timescales

Abstract. We present a multi-year short-range hindcast experiment and its experimental design for better evaluation of both the mean state and variability of atmospheric moist processes in climate models from diurnal to interannual timescales and facilitate model development. We used the Community Earth System Model version 1 as the base model and performed a suite of 3 d hindcasts initialized every day starting at 00:00 Z from 1997 to 2012. Three processes – the diurnal cycle of clouds during different cloud regimes over the central US, precipitation and diabatic heating associated with the Madden–Julian Oscillation (MJO), and the response of precipitation, surface radiative and heat fluxes, as well as zonal wind stress to sea surface temperature anomalies associated with the El Niño–Southern Oscillation – are evaluated as examples to demonstrate how one can better utilize simulations from this experiment to gain insights into model errors and their connection to physical parameterizations or large-scale state. This is achieved by comparing the hindcasts with corresponding long-term observations for periods based on different phenomena. These analyses can only be done through this multi-year hindcast approach to establish robust statistics of the processes under well-controlled large-scale environment because these phenomena are either a result of interannual climate variability or only happen a few times in a given year (e.g., MJO, or cloud regime types). Furthermore, comparison of hindcasts to the typical simulations in climate mode with the same model allows one to infer what portion of a model's climate error directly comes from fast errors in the parameterizations of moist processes. As demonstrated here, model biases in the mean state and variability associated with parameterized moist processes usually develop within a few days and manifest within weeks to affect the simulations of large-scale circulation and ultimately the climate mean state and variability. Therefore, model developers can achieve additional useful understanding of the underlying problems in model physics by conducting a multi-year hindcast experiment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Leveraging design of experiments to build chemometric models for the quantification of uranium (VI) and HNO3 by Raman spectroscopy

Partial least squares regression (PLSR) and support vector regression (SVR) models were optimized for the quantification of U(VI) (10–320 g L −1 ) and HNO 3 (0.6–6 M) by Raman spectroscopy with optimized calibration sets chosen by optimal design of experiments. The designed approach effectively minimized the number of samples in the calibration set for PLSR and SVR by selecting sample concentrations with a quadratic process model, despite complex confounding and covarying spectral features in the spectra. The top PLS2 model resulted in percent root mean square errors of prediction for U(VI), HNO 3 , and NO 3 − of 3.7%, 3.6%, and 2.9%, respectively. PLS1 models performed similarly despite modeling an analyte with a majority linear response (i.e., uranyl symmetric stretch) and another with more covarying vibrational modes (i.e., HNO 3 ). Partial least squares (PLS) model loadings and regression coefficients were evaluated to better understand the relationship between weaker Raman bands and covarying spectral features. Support vector machine models outperformed PLS1 models, resulting in percent root mean square error of prediction values for U(VI) and HNO 3 of 1.5% and 3.1%, respectively. The optimal nonlinear SVR model was trained using a similar number of samples (11) compared with the PLSR model, even though PLS is a linear modeling approach. The generic D-optimal design presented in this work provides a robust statistical framework for selecting training set samples in disparate two-factor systems. This approach reinforces Raman spectroscopy for the quantification of species relevant to the nuclear fuel cycle and provides a robust chemometric modeling approach to bolster online monitoring in challenging process environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A sensitivity analysis to predict the neutronics behavior of samples irradiated in the VTR rabbit system

We report a low-order neutronics model is developed to carry out hundreds of simulations efficiently and investigate the neutronics behavior of samples being irradiated in a test reactor setting under different geometrical constraints. The low-order model allowed for simulations that yield the expected neutronics behavior of any irradiated sample in any environment and allows for the calculation of highly accurate spatially averaged statistics and idealized spatial distributions in the neutron flux. Several benchmarks are performed to evaluate the performance and limitations of the low-order model revealing many important findings. The low-order model predicted the LHGR in the EBR-II driver fuel to within 2.34% by only simulating the fuel rod by itself, which served as a validation for the model. Sensitivity studies investigated 3% enriched UO 2 and U-10Zr being irradiated in the Versatile Test Reactor rabbit system. The analyses investigated a range of combinations of 15 radii and 5 heights for each sample in the rabbit system. Similar data sets are also provided for irradiations in the Advanced Test Reactor’s B-10 irradiation position, which is a thermal neutron spectrum environment. Generalized fits and fit coefficients are obtained for sample heating, reaction rate densities, and local multiplication rate characteristics, allowing the predictions of the neutronics behavior of the samples based on their geometrical constraints. The analyses and fits laid the groundwork for developing a user-end Multiphysics analysis framework to assist and accelerate irradiation experiment design and optimization.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Out-of-Distribution Detection and Radiological Data Monitoring Using Statistical Process Control

Abstract Machine learning (ML) models often fail with data that deviates from their training distribution. This is a significant concern for ML-enabled devices as data drift may lead to unexpected performance. This work introduces a new framework for out of distribution (OOD) detection and data drift monitoring that combines ML and geometric methods with statistical process control (SPC). We investigated different design choices, including methods for extracting feature representations and drift quantification for OOD detection in individual images and as an approach for input data monitoring. We evaluated the framework for both identifying OOD images and demonstrating the ability to detect shifts in data streams over time. We demonstrated a proof-of-concept via the following tasks: 1) differentiating axial vs. non-axial CT images, 2) differentiating CXR vs. other radiographic imaging modalities, and 3) differentiating adult CXR vs. pediatric CXR. For the identification of individual OOD images, our framework achieved high sensitivity in detecting OOD inputs: 0.980 in CT, 0.984 in CXR, and 0.854 in pediatric CXR. Our framework is also adept at monitoring data streams and identifying the time a drift occurred. In our simulations tracking drift over time, it effectively detected a shift from CXR to non-CXR instantly, a transition from axial to non-axial CT within few days, and a drift from adult to pediatric CXRs within a day—all while maintaining a low false positive rate. Through additional experiments, we demonstrate the framework is modality-agnostic and independent from the underlying model structure, making it highly customizable for specific applications and broadly applicable across different imaging modalities and deployed ML models.

Zamzmi, Ghada↗
NASA NTRS1988

Initial blood storage experiment

The design of the Initial Blood Storage Experiment (IBSE) was based upon a carefully controlled comparison between identical sets of human blood cell suspensions - red cells, white cell, and platelets - one set of which was transported aboard the Columbia on a 6 day 11 hour mission, and the other held on the ground. Both sets were carried inside stainless steel dewars within specially fabricated flight hardware. Individual bags of cell suspensions were randomly assigned with respect to ground vs orbit status, dewar chamber, and specific location within the dewar. To foster optimal preservation, each cell type was held under specific optimal conditions of pH, ionic strength, solute concentration, gas tension, and temperature. An added variable in this initial experiment was provided by the use of three different polymer/plasticizer formulations for the sealed bags which held the blood cells. At termination of the experiment, aliquots of the suspensions, identified only by code, were distributed to be assayed. Assays were selected to constitute a broad survey of cellular properties and thereby maximize the chances of detection of gravitational effects. A total of 74 different outcome measurements were reported for statistical analysis. When the measurements were completed, the results were entered into the IBSE data base, at which time the data were matched with the original blood bag numbers to determine their status with respect to polymer/plasticizer type, orbit status (orbit or ground), and storage position within the experimental hardware. The data were studied by analysis of variance. Initially, type of bag and orbital status were main factors; later more detailed analyses were made on specific issues such as position in the hardware and specific plastic. If the analysis of variance indicated a statistical significance at the 5 percent level the corresponding p-value was reported.

Surgenor, Douglas MACN.↗
NASA NTRS2005

Saturn radiation (SATRAD) model

The Saturnian radiation belts have not received as much attention as the Jovian radiation belts because they are not nearly as intense—the famous Saturnian particle rings tend to deplete he belts near where their peak would occur. As a result, there has not been a systematic development of engineering models of the Saturnian radiation environment for mission design. A primary exception is that of Divine (1990). That study used published data from several charged particle experiments aboard the Pioneer 11, Voyager 1, and Voyager 2 spacecraft during their flybys at Saturn to generate numerical models for the electron and proton radiation belts between 2.3 and 13 Saturn radii. The Divine Saturn radiation model described the electron distributions at energies between 0.04 and 10 MeV and the proton distributions at energies between 0.14 and 80 MeV. The model was intended to predict particle intensity, flux, and fluence for the Cassini orbiter. Divine carried out hand calculations using the model but never formally developed a computer program that could be used for general mission analyses. This report seeks to fill that void by formally developing a FORTRAN version of the model that can be used as a computer design tool for missions to Saturn that require estimates of the radiation environment around the planet. The results of that effort and the program listings are presented here along with comparisons with the original estimates carried out by Divine. In addition, Pioneer and Voyager data were scanned in from the original references and compared with the FORTRAN model’s predictions. The results were statistically analyzed in a manner consistent with Divine’s approach to provide estimates of the ability of the model to reproduce the original data. Results of a formal review of the model by a panel of experts are also presented. Their recommendations for further tests, analyses, and extensions to the model are discussed.

Evans, R. W.↗
DOE OSTI2023

Model-based quantification of margins and uncertainties in metal additive manufacturing for process design and qualification

Laser powder bed fusion (LPBF) Additive Manufacturing (AM) has the potential to enable the production of components with novel designs and material properties unachievable otherwise. However, process repeatability is a challenge, making qualification ill-defined and greatly reducing the utility of what could be an important manufacturing technology. In this work, a combination of modeling, uncertainty quantification (UQ), and experimentation are used in an effort to predict and bound the range of possible outcomes of the LPBF process. Quantities of interest predicted are melt pool dimensions, microstructure features, and mechanical distortions. A combination of high fidelity thermal-fluid models, microstructure growth models, and reduced fidelity, rapid thermal and mechanical models are used. Uncertainty propagation techniques are used to predict probability distributions of quantities of interest from estimates of process uncertainties. Repeated experiments are done to quantify observed probability distributions and compared to predicted distributions to determine if predictions are precise and accurate. Novel modeling methods are microstrucutre characterization techniques are also discussed. It is found that high fidelity models do a generally good job bounding experimentally observed melt pool morphologies for both bead-on-plate and powder bed cases. Microstructure models are able to bound a number of experimentally observed microstructure statistics, but with low precision due to challenges with calibrating the microstructure growth model parameters. A developed modified inherent strain distortion model does not accurately predict observed distortions. A lumped laser distortion model shows promise in being both accurately and precisely bounding observed outcomes from the deflection comb build, but requires further evaluation on more builds and geometries.

36 MATERIALS SCIENCE↗
NASA NTRS1980

Backward deletion to minimize prediction errors in models from factorial experiments with zero to six center points

Population model coefficients were chosen to simulate a saturated 2 to the 4th fixed-effects experiment having an unfavorable distribution of relative values. Using random number studies, deletion strategies were compared that were based on the F-distribution, on an order statistics distribution of Cochran's, and on a combination of the two. The strategies were compared under the criterion of minimizing the maximum prediction error, wherever it occurred, among the two-level factorial points. The strategies were evaluated for each of the conditions of 0, 1, 2, 3, 4, 5, or 6 center points. Three classes of strategies were identified as being appropriate, depending on the extent of the experimenter's prior knowledge. In almost every case the best strategy was found to be unique according to the number of center points. Among the three classes of strategies, a security regret class of strategy was demonstrated as being widely useful in that over a range of coefficients of variation from 4 to 65%, the maximum predictive error was never increased by more than 12% over what it would have been if the best strategy had been used for the particular coefficient of variation. The relative efficiency of the experiment, when using the security regret strategy, was examined as a function of the number of center points, and was found to be best when the design used one center point.

Holms, A. G.↗
NASA NTRS2005

Saturn Radiation (SATRAD) Model

The Saturnian radiation belts have not received as much attention as the Jovian radiation belts because they are not nearly as intense-the famous Saturnian particle rings tend to deplete the belts near where their peak would occur. As a result, there has not been a systematic development of engineering models of the Saturnian radiation environment for mission design. A primary exception is that of Divine (1990). That study used published data from several charged particle experiments aboard the Pioneer 1 1, Voyager 1, and Voyager 2 spacecraft during their flybys at Saturn to generate numerical models for the electron and proton radiation belts between 2.3 and 13 Saturn radii. The Divine Saturn radiation model described the electron distributions at energies between 0.04 and 10 MeV and the proton distributions at energies between 0.14 and 80 MeV. The model was intended to predict particle intensity, flux, and fluence for the Cassini orbiter. Divine carried out hand calculations using the model but never formally developed a computer program that could be used for general mission analyses. This report seeks to fill that void by formally developing a FORTRAN version of the model that can be used as a computer design tool for missions to Saturn that require estimates of the radiation environment around the planet. The results of that effort and the program listings are presented here along with comparisons with the original estimates carried out by Divine. In addition, Pioneer and Voyager data were scanned in from the original references and compared with the FORTRAN model s predictions. The results were statistically analyzed in a manner consistent with Divine s approach to provide estimates of the ability of the model to reproduce the original data. Results of a formal review of the model by a panel of experts are also presented. Their recommendations for further tests, analyses, and extensions to the model are discussed.

Garrett, H. B.↗
DOE OSTI2018

A novel variant of torque teno virus 7 identified in patients with Kawasaki disease

Kawasaki disease (KD), first identified in 1967, is a pediatric vasculitis of unknown etiology that has an increasing incidence in Japan and many other countries. KD can cause coronary artery aneurysms. Its epidemiological characteristics, such as seasonality and clinical picture of acute systemic inflammation with prodromal intestinal/respiratory symptoms, suggest an infectious etiology for KD. Interestingly, multiple host genotypes have been identified as predisposing factors for KD. To explore experimental methodology for identifying etiological agent(s) for KD and to optimize epidemiological study design (particularly the sample size) for future studies, we conducted a pilot study. For a 1-year period, we prospectively enrolled 11 patients with KD. To each KD patient, we assigned two control individuals (one with diarrhea and the other with respiratory infections), matched for age, sex, and season of diagnosis. During the acute phase of disease, we collected peripheral blood, nasopharyngeal aspirate, and feces. We also determined genotypes, to identify those that confer susceptibility to KD. There was no statistically significant difference in the frequency of the risk genotypes between KD patients and control subjects. We also used unbiased metagenomic sequencing to analyze these samples. Metagenomic sequencing and PCR detected torque teno virus 7 (TTV7) in two patients with KD (18%), but not in control subjects (P = 0.111). Sanger sequencing revealed that the TTV7 found in the two KD patients contained almost identical variants in nucleotide and identical changes in resulting amino acid, relative to the reference sequence. Additionally, we estimated the sample size that would be required to demonstrate a statistical correlation between TTV7 and KD. Future larger scale studies with carefully optimized metagenomic sequencing experiments and adequate sample size are warranted to further examine the association between KD and potential pathogens, including TTV7.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Multimodality in the Search for New Physics in Pulsar Timing Data and the Case of Kination-amplified Gravitational-wave Background from Inflation

We investigate the kination-amplified inflationary gravitational-wave background (GWB) interpretation of the signal recently reported by various pulsar timing array (PTA) experiments. Kination is a post-inflationary phase in the expansion history dominated by the kinetic energy of some scalar field, characterized by a stiff equation of state w = 1. Within the inflationary GWB model, we identify two modes that can fit the current data sets (NANOGrav and EPTA) with equal likelihood: the kination-amplification (KA) mode and the ordinary, no-kination-amplification (no-KA) mode. The multimodality of the likelihood motivates a Bayesian analysis with nested sampling. We analyze the free spectra of current PTA data and mock free spectra constructed with higher signal-to-noise ratios using nested sampling. The analysis of the mock spectrum designed to be consistent with the best fit to the NANOGrav 15 yr (NG15) data successfully reveals the expected bimodal posterior for the first time while excluding the reheating mode that appears in the fit to the current NG15 data, making a case for our correct and comprehensive treatment of potential multimodal posteriors arising from future PTA data sets. The resultant Bayes factor is $\mathcal{B}$ $\equiv$ Z no–KA /Z KA = 2.9 ± 1.9, indicating comparable statistical significance between the two modes. Given the theoretical model-building challenges of producing highly blue-tilted primordial tensor spectra, the KA mode has the advantage of requiring less blue primordial spectra, compared with the no-KA mode. The synergy between future cosmic microwave background polarization, pulsar timing, and laser interferometer measurements of gravitational waves will help resolve the ambiguity implied by the multimodal posterior in PTA-only searches.

Cosmology↗
NASA NTRS2001

First Flight of the Advanced Thin Ionization Calorimeter (ATIC) Balloon Experiment

The ATILT instrument is designed to measure the composition and energy spectra of Z = 1 to 28 cosmic rays over the energy range -10 GeV - 100 TeV. ATIC was launched as a long duration test balloon flight on 12/28/00 local time from McMurdo, Antarctica. The operations preceding and during launch went very smoothly. During the first -20 hr while the instrument remained within line of sight (LOS), a full system check out was conducted, the experiment was operated in several test configurations, and all major tuning was completed. Preliminary analysis of the science data indicates that the overall detector system is functioning as expected. With our fully functioning analysis software we were able to monitor the data in nearly real time. Each event was reconstructed event-by-event to confirm the detector performance. The shower profiles indicate that the shower maximum location is deeper in the calorimeter for higher energy events, as expected. The energy spectra of protons, Helium nuclei, and "all particles" appear to follow power laws. Both the Si matrix and top scintillator layer of the charge module show clear charge separation for p and He. As the statistics increase, heavy nuclei charge separation will be evaluated. We will present preliminary results of the LOS data, as well as other data that will be available from the flight-data hard disk,

Case, G.↗
NASA NTRS2017

Quantifying Pilot Contribution to Flight Safety during Hydraulic Systems Failure

Accident statistics cite the flight crew as a causal factor in over 60% of large transport aircraft fatal accidents. Yet, a well-trained and well-qualified pilot is acknowledged as the critical center point of aircraft systems safety and an integral safety component of the entire commercial aviation system. The latter statement, while generally accepted, cannot be verified because little or no quantitative data exists on how and how many accidents/incidents are averted by crew actions. A joint NASA/FAA high-fidelity motion-base human-in-the-loop test was conducted using a Level D certified Boeing 737-800 simulator to evaluate the pilot's contribution to safety-of-flight during routine air carrier flight operations and in response to aircraft system failures. To quantify the human's contribution, crew complement (two-crew, reduced crew, single pilot) was used as the independent variable in a between-subjects design. This paper details the crew's actions, including decision-making, and responses while dealing with a hydraulic systems leak - one of 6 total non-normal events that were simulated in this experiment.

Kramer, Lynda J.↗
DOE OSTI2023

High-fidelity Experiments of Turbulent Buoyant Jets from Simultaneous Particle Image Velocimetry and Laser Induced Fluorescence

Accurate models of turbulent buoyant flows are essential for the design of nuclear reactors thermal hydraulics and passive safety systems. However, available models fail to fully capture the physics of turbulent mixing when buoyancy becomes predominant with respect to momentum. Therefore, high-fidelity experiments of well-controlled fundamental flows are needed to develop and validate more accurate models. We performed experiments of positive and negative turbulent buoyant jets, both in uniform and stratified environments, with the aim of understanding the thermal hydraulics of turbulent mixing with variable density and providing high-fidelity data for the development and validation of turbulence models. Non-intrusive, simultaneous Particle Image Velocimetry and Laser Induced Fluorescence measurements were carried out to acquire instantaneous velocity and concentration fields on a vertical section parallel to the axis of a jet in the self-similar region. The Refractive Index Matching method was applied to measure high-resolution buoyant jets with up to 8.6% density difference. These data are free of the typical errors that characterize optical measurements of buoyancy driven flows (e.g., natural and mixed convection) where the refractive index of the fluid is inhomogeneous throughout the measurement domain. Turbulent statistics and entrainment of buoyant jets in uniform and stratified environments are presented. These data are compared with non-buoyant jets in uniform environment, as a reference to investigate the effects of buoyancy and stratification on turbulent mixing. The results will be used for the assessment of current turbulence models and as basis for the development of a new one that captures turbulent mixing.

42 ENGINEERING↗