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Results for “Closure correlations”

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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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Studies of planning behavior of aircraft pilots in normal, abnormal, and emergency situations

A methodology for the study of human planning behavior in complex dynamic systems is presented and applied to the study of aircraft pilot behavior in normal, abnormal and emergency situations. The method measures the depth of planning, that is the level of detail employed with respect to a specific task, according to responses to a verbal questionnaire, and compares planning depth with variables relating to time, task criticality and the probability of increased task difficulty. In two series of experiments, depth of planning was measured on a five- or ten-point scale during various phases of flight in a HFB-320 simulator under normal flight conditions, abnormal scenarios involving temporary runway closure due to snow removal or temporary CAT-III conditions due to a dense fog, and emergency scenarios involving engine shut-down or hydraulic pressure loss. Results reveal a dichotomy between event-driven and time-driven planning, different effects of automation in abnormal and emergency scenarios and a low correlation between depth of planning and workload or flight performance.

Johannsen, G.↗
NASA NTRS1975

Crack-closure and crack-growth measurements in surface-flawed titanium alloy Ti6Al-4V

The crack-closure and crack-growth characteristics of the titanium alloy Ti-6Al-4V were determined experimentally on surface-flawed plate specimens. Under cyclic loading from zero to tension, cracks deeper than 1 mm opened at approximately 50 percent of the maximum load. Cracks shallower than 1 mm opened at higher loads. The correlation between crack-growth rate and the total stress-intensity range showed a lower threshold behavior. This behavior was attributed to the high crack-opening loads at short cracks because the lower threshold was much less evident in correlations between the crack-growth rates and the effective stress-intensity range.

Elber, W.↗
DOE OSTI2019

Uncertainty Quantification on SAM Simulations of EBR-II Loss-of-Flow Tests

The System Analysis Module (SAM) is a modern system analysis tool being developed at Argonne National Laboratory for advanced non-LWR safety analysis. It aims to provide fast-running, whole-plant transient analyses capability with improved-fidelity for SFR, LFR, and MSR/FHR. In prior work, SAM has performed well in modeling the EBR-II benchmark based on the SHRT-17 and SHRT-45R protected and unprotected loss-of-flow experiments. However, underlying uncertainties in the modeling parameters need to be quantified to gain confidence in any best-estimate simulations. In this work, a Python coupling framework between Dakota and SAM has been developed to investigate these uncertainties, alongside code enhancements in SAM for user-flexibility in perturbing physical closure models and fluid equations of state. 25 significant input parameters covering boundary conditions, geometry, physical closure models, and equations of state were identified with their uncertainties defined from literature. Two SAM transient models for SHRT-17 and SHRT-45R were perturbed on these input parameters using Latin Hypercube Sampling and the uncertainties in predicted maximum fuel, cladding, and coolant temperatures were quantified as the output responses. Spearman rank correlation of input parameters to the predicted temperatures indicated that the most sensitive parameters include the initial core power, pipe wall drag, fuel & coolant conductivity, and peak channel flow area. Sensitivity of input parameters was found to differ between the two transients and core channel modeling strategies. The overall perturbations did not result in large uncertainties in the predicted temperatures, despite the efforts made to obtain accurate yet conservative input uncertainties.

Mui, Travis↗
NASA NTRS2026

Thermochemically-Closed Sonic-Flow Inversion for Enthalpy and Temperature in Multispecies Arc-Jet Flows

A thermochemically-closed sonic-flow inversion framework (TSIF) is developed to infer bulk enthalpy and total temperature upstream of a choked nozzle in arc-jet flows. The formulation recasts a pressure-rise total enthalpy quantification technique as an inverse problem in characteristic-velocity c * space using measured mass flow rate, upstream total pressure, gas composition, and nozzle throat geometry as inputs. Unlike calorimetric energy-balance approaches or optical diagnostics, the method relies primarily on routinely measured facility quantities combined with explicit thermochemical closure. Thermochemical states are obtained using NASA’s open-source Chemical Equilibrium with Applications (CEA) code, enabling construction of a chemistry-consistent relation between characteristic velocity, total enthalpy, and total temperature under equilibrium or frozen assumptions. A discharge coefficient is self-calibrated using cold-flow (arc-off) operation data and applied to hot-flow (arc-on) measurements, enabling upstream losses to be accounted for without empirical correlations. The framework is applied to air, N 2 , and CO 2 –N 2 arc-jet flows and demonstrates expected trends for the inferred thermochemical states as function of arc power, specific energy input, mass-flow, heater configuration, and test gas. In the air limit, under equilibrium assumptions, the method recovers the classical high-enthalpy asymptotic correlation of Winovich with a mean residual of 4.4%, demonstrating compatibility with established sonic-flow scaling, while extending applicability to arbitrary multi-species mixtures and non-equilibrium chemistry. The framework provides a mixture-flexible methodology for determining bulk thermochemical states in modern arc-jet environments using routine facility pressure, mass-flow, gas-composition, and nozzle-geometry information together with a cold-flow calibration.

stagnation heat flux↗
NASA NTRS1987

Investigation of third-order closure model of turbulence for the computation of incompressible flows in a channel with a backward-facing step

To predict the diffusion process of the Reynolds stresses in reattaching shear flows, the transport model for the triple-velocity products has been developed and tested for the computation of the flow in a channel with a backward-facing step. Upon comparison of the results of uuv, uvv, and vvv with those obtained by using existing algebraic correlations, it was shown that the present model improved the prediction of the triple-velocity products.

Amano, R. S.↗
DOE OSTI2018

Saturation scalings of toroidal ion temperature gradient turbulence

The emerging understanding of instability-driven plasma-turbulence saturation in terms of energy transfer to stable modes in the same scale range as the instability is employed to derive a saturation theory for the toroidal branch of ion temperature gradient turbulence that provides the scaling of turbulence and zonal flow levels for all physical parameters. The theory is based on the eigenmode decomposition of a nonlinear fluid model, which is subjected to a statistical closure and simplified via an ordering expansion consistent with zonal-flow catalyzed energy transfer from the unstable mode to the stable mode at large scale. Solution of the closed energy balance equations yields a turbulence level that is proportional to the ratio of the zonal flow damping rate and the inverse of the triplet correlation time of the zonal-flow catalyzed wavenumber triplet interaction. The zonal flow energy is proportional to the ratio of the growth rate and the inverse triplet correlation time. The saturation scalings are applied to the ion heat flux, showing that it has a factor proportional to the quasilinear heat flux and a correction factor that includes the inverse of the triplet correlation time and a reduction due to the stable mode.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1998

Cardiogenic oscillation phase relationships during single-breath tests performed in microgravity

We studied the phase relationships of the cardiogenic oscillations in the phase III portion of single-breath washouts (SBW) in normal gravity (1 G) and in sustained microgravity (microG). The SBW consisted of a vital capacity inspiration of 5% He-1.25% sulfurhexafluoride-balance O2, preceded at residual volume by a 150-ml Ar bolus. Pairs of gas signals, all of which still showed cardiogenic oscillations, were cross-correlated, and their phase difference was expressed as an angle. Phase relationships between inspired gases (e.g., He) and resident gas (n2) showed no change from 1 G (211 +/- 9 degrees) to microG (163 +/- 7 degrees). Ar bolus and He were unaltered between 1 G (173 +/- 15 degrees) and microG (211 +/- 25 degrees), showing that airway closure in microG remains in regions of high specific ventilation and suggesting that airway closure results from lung regions reaching low regional volume near residual volume. In contrast, CO2 reversed phase with He between 1 G (332 +/- 6 degrees) and microG (263 +/- 27 degrees), strongly suggesting that, in microG, areas of high ventilation are associated with high ventilation-perfusion ratio (VA/Q). This widening of the range of VA/Q in microG may explain previous measurements (G.K. Prisk, A.R. Elliott, H.J.B. Guy, J.M. Kosonen, and J.B. West J. Appl. Physiol. 79: 1290-1298, 1995) of an overall unaltered range of VA/Q in microG, despite more homogeneous distributions of both ventilation and perfusion.

Non-NASA Center↗
NASA NTRSDate not supplied

Communication Demand in the National Airspace - A Federated Learning Approach

Within the national airspace system (NAS), efficient use of spectrum remains a challenge; as UAS and UAM missions evolve, the amount of mission-critical aircraft communications are expected to significantly grow. To accommodate the increased demand, NASA Glenn Research Center is investigating artificial intelligence approaches that could dynamically allocate spectrum; however, these solutions are driven by communication and aviation data items, many of which are not directly available. One such cornerstone data item is communication demand, parameterizing the needs within a sector in terms that may directly inform spectrum allocation, such as channel access duration, bandwidth, and modulation type. This paper considers the complexity of predicting communication demand as a function of NAS behaviors. Unlike prior prediction work in communications, this research must consider how the NAS may be impacted by external factors - such as convective weather and closures - rather than estimating demand from time-series forecasting alone. Much of this research considers a federated learning design to predict communication events in terms of the type of event occurring (sector coordination, conflict resolution, etc.). To do so, an investigation of products from Sherlock Data Warehouse is conducted, identifying the trends, sufficiency, and correlations of each product to identified events. Additionally, a preliminary discussion for inferring associations between these event types and their communication parameters (duration, bandwidth, modulation) is presented. By utilizing federated learning, imbalances in the types of events and data present throughout the NAS can inform local models without impairing global training. Furthermore, the two-stage approach proposed allows for robust and speculative communication modelling, as communication techniques continue to evolve. As a result, this model enables a generalized approach to understanding NAS communications which is able to inform long-term changes to aviation spectrum management.

Nathan Schimpf↗
NASA NTRSDate not supplied

A Federated Learning Approach to Predicting Communication Demand in the National Airspace

Within the national airspace system (NAS), efficient use of spectrum remains a challenge; as UAS and UAM missions evolve, the amount of mission-critical aircraft communications are expected to significantly grow. To accommodate the increased demand, NASA Glenn Research Center is investigating artificial intelligence approaches that could dynamically allocate spectrum; however, these solutions are driven by communication and aviation data items, many of which are not directly available. One such cornerstone data item is communication demand, parameterizing the needs within a sector in terms that may directly inform spectrum allocation, such as channel access duration, bandwidth, and modulation type. This paper considers the complexity of predicting communication demand as a function of NAS behaviors. Unlike prior prediction work in communications, this research must consider how the NAS may be impacted by external factors - such as convective weather and closures - rather than estimating demand from time-series forecasting alone. Much of this research considers a federated learning design to predict communication events in terms of the type of event occurring (sector coordination, conflict resolution, etc). To do so, an investigation of products from Sherlock Data Warehouse is conducted, identifying the trends, sufficiency, and correlations of each product to identified events. Additionally, a preliminary discussion for inferring associations between these event types and their communication parameters (duration, bandwidth, modulation) is presented. By utilizing federated learning, imbalances in the types of events and data present throughout the NAS can inform local models without impairing global training. Furthermore, the two-stage approach proposed allows for robust and speculative communication modelling, as communication techniques continue to evolve. As a result, this model enables a generalized approach to understanding NAS communications which is able to inform long-term changes to aviation spectrum management.

Nathan Schimpf↗
DOE OSTI2020

Mesh-Sequenced Realizations for Evaluation of Subgrid-Scale Models for Turbulent Combustion

This paper develops a new approach for analysis of subgrid closures for turbulent combustion as modeled using direct quadrature (finite-rate chemistry) techniques. The approach, termed multiresolution analysis through mesh-sequenced realizations (MRA-MSR), conducts simultaneous, constrained large-eddy simulations on a set of hierarchically coarsened meshes. Furthermore, the availability of underlying fine-mesh (subgrid) data corresponding to coarse-mesh locations allows a clearer assessment of the effects of unresolved fluctuations on apparent reactivity. A key to MRA-MSR is the correlation of eddy structures at coarser mesh levels, which is facilitated by the transfer of filtered fine-mesh velocity information. A seven-mesh MRA-MSR hierarchy using three resolution levels is applied to one of the Sydney bluff-body stabilized methane–hydrogen flames. Analysis of the simultaneously evolved data at different resolution levels reveals several interesting trends. First, at high Damköhler numbers, there is clear evidence of attenuation of apparent reactivity due to the effects of unresolved fluctuations. Secondly, single-point, single-time filtered density functions of a normalized subgrid Damköhler number show a characteristic beta probability density function (PDF) form and display evidence of scale similarity. Interrogation of the MRA-MSR database also shows that the recently-proposed least-squares minimization (LSM) turbulence–chemistry interaction model can account for the observed diminishment in reactivity at high Damköhler numbers but cannot reduce scatter significantly. A new form of the LSM model, which makes use of the normalized subgrid Damköhler number beta PDF distribution, performs slightly better than the original model, illustrating the potential of MRA-MSR both in assessing existing closure concepts and in developing new ones.

42 ENGINEERING↗
NASA NTRS1992

Fracture mechanics parameters for small fatigue cracks

This paper presents a review of some common small-crack test specimens, the underlying causes of the small-crack effect, and the fracture-mechanics parameters that have been used to correlate or predict their growth behavior. This review concentrates on continuum mechanics concepts and on the nonlinear behavior of small cracks. The paper reviews some stress-intensity factor solutions for small-crack test specimens and develops some simple elastic-plastic J integral and cyclic J integral expressions that include the influence of crack-closure. These parameters were applied to small-crack growth data on two aluminum alloys, and a fatigue life prediction methodology is demonstrated. For these materials, the crack-closure transient from the plastic wake was found to be the major factor in causing the small-crack effect.

Newman, J. C., Jr.↗
DOE OSTI2017

Internal Nozzle Flow Simulations of Gasoline-Like Fuels under Diesel Operating Conditions

Spray formation in internal combustion engines with direct injection is strictly correlated with internal nozzle flow characteristics, which are in turn influenced by fuel physical properties and injector needle motion. This paper pre-sents a series of 3D simulations that model the in-nozzle flow in a 5-hole mini-sac diesel injector. Two gasoline-like naphtha fuels, namely full-range and light naphtha, were tested under operating conditions typical of diesel applica-tions and were compared with n-dodecane, selected from a palette used as diesel surrogates. Validated methodolo-gies from our previous work were employed to account for realistic needle motion. The multi-phase nature of the problem was described by the mixture model assumption with the Volume of Fluid method. Cavitation effects were included by means of the Homogeneous Relaxation Model and turbulence closure was achieved with the Standard k-ε model in an Unsteady Reynolds-Averaged Navier-Stokes formulation. The results revealed that injector perfor-mance and propensity to cavitation are influenced by the fuel properties. Analyses of several physical quantities were carried out to highlight the fuel-to-fuel differences in terms of mass flow rate, discharge coefficients, and fuel vapor volume fraction inside the orifices. A series of parametric investigations was also performed to assess the fuel response to varied fuel injection temperature, injection pressure, and cross-sectional orifice area. For all cases, the strict correlation between cavitation magnitude and saturation pressure was confirmed. Owing to their higher volatil-ity, the two gasoline-like fuels were characterized by higher cavitation across all the simulated conditions. Occur-rence of cavitation was mostly found at the needle seat and at the orifice inlets during the injection event’s transient, when very small gaps exist between the needle and its seat. This behavior tended to disappear at maximum needle lift, where cavitation was absent for all fuels. Differences in mass flow rate between the naphtha fuels and n-dodecane were measured and ascribed to the different densities of the three fuels. Nevertheless, they were found to be smaller than expected, owing to the lower viscosity of the gasoline-like fuels. This beneficial influence of the lower viscosity was shown to be less effective at higher temperature, where the relative viscosity differences de-creased.

Torelli, R.↗
NASA NTRS2003

Oxidation Kinetics and Strength Degradation of Carbon Fibers in a Cracked Ceramic Matrix Composite

Experimental results and oxidation modeling will be presented to discuss carbon fiber susceptibility to oxidation, the oxidation kinetics regimes and composite strength degradation and failure due to oxidation. Thermogravimetric Analysis (TGA) was used to study the oxidation rates of carbon fiber and of a pyro-carbon interphase. The analysis was used to separately obtain activation energies for the carbon constituents within a C/SiC composite. TGA was also conducted on C/SiC composite material to study carbon oxidation and crack closure as a function of temperature. In order to more closely match applications conditions C/SiC tensile coupons were also tested under stressed oxidation conditions. The stressed oxidation tests show that C/SiC is much more susceptible to oxidation when the material is under an applied load where the cracks are open and allow for oxygen ingress. The results help correlate carbon oxidation with composite strength reduction and failure.

Halbig, Michael C.↗
NASA NTRS2007

A Side by Side Comparison of Filter-Based PM(sub 2.5) Measurements at a Suburban Site: A Closure Study

Reliable determination of the effects of air quality on public health and the environment requires accurate measurement of PM(sub 2.5) mass and the individual chemical components of fine aerosols. This study seeks to evaluate PM(sub 2.5) measurements that are part of a newly established national network by comparing them with a more conventional sampling system. Experiments were carried out during 2002 at a suburban site in Maryland, United States, where two samplers from the U.S. Environmental Protection Agency (USEPA) Speciation Trends Network: Met One Speciation Air Sampling System STNS and Thermo Scientific Reference Ambient Air Sampler STNR, two Desert Research Institute Sequential Filter Samplers DRIF, and a continuous TEOM monitor (Thermo Scientific Tapered Element Oscillating Microbalance) were sampling air in parallel. These monitors differ not only in sampling configuration but also in protocol-specific sample analysis procedures. Measurements of PM(sub 2.5) mass and major contributing species were well correlated among the different methods with r-values > 0.8. Despite the good correlations, daily concentrations of PM(sub 2.5) mass and major contributing species were significantly different at the 95% confidence level from 5 to 100% of the time. Larger values of PM(sub 2.5) mass and individual species were generally reported from STNR and STNS. The January STNR average PM(sub 2.5) mass (8.8 (micro)g/per cubic meter) was 1.5 (micro)g/per cubic meter larger than the DRIF average mass. The July STNS average PM(sub 2.5) mass (27.8 (micro)g/per cubic meter) was 3.8 (micro)g/per cubic meter larger than the DRIF average mass. These differences can only be partially accounted for by known random errors. Variations in flow control, face velocity, and sampling artifacts likely influence the measurement of PM(sub 2.5) speciation and mass closure. Simple statistical tests indicate that the current uncertainty estimates used in the STN network may underestimate the actual uncertainty.

Haines, Jennifer C.↗
DOE OSTI2014

Molecular insights into RNA and DNA helicase evolution from the determinants of specificity for a DEAD-box RNA helicase

How different helicase families with a conserved catalytic ‘helicase core’ evolved to function on varied RNA and DNA substrates by diverse mechanisms remains unclear. In this study, we used Mss116, a yeast DEAD-box protein that utilizes ATP to locally unwind dsRNA, to investigate helicase specificity and mechanism. Our results define the molecular basis for the substrate specificity of a DEAD-box protein. Additionally, they show that Mss116 has ambiguous substrate-binding properties and interacts with all four NTPs and both RNA and DNA. The efficiency of unwinding correlates with the stability of the ‘closed-state’ helicase core, a complex with nucleotide and nucleic acid that forms as duplexes are unwound. Crystal structures reveal that core stability is modulated by family-specific interactions that favor certain substrates. This suggests how present-day helicases diversified from an ancestral core with broad specificity by retaining core closure as a common catalytic mechanism while optimizing substrate-binding interactions for different cellular functions.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1989

Prediction of fatigue-crack growth in a high-strength aluminum alloy under variable-amplitude loading

The present paper is concerned with the application of an analytical crack-closure model to study crack growth under various load histories. The model was based on a concept like the Dugdale model, but modified to leave plastically deformed material in the wake of the advancing crack tip. The thickness effect was accounted for by using a 'constraint' factor on tensile yielding at the crack tip. The model was used to correlate crack-growth rates under constant-amplitude loading, and to predict crack growth under variable-amplitude loading on a high-strength aluminum alloy (7475-T7351) sheet material. The experimental data was obtained from Zhang et al. Predicted crack-growth lives agreed well with experimental data. For ten crack-growth tests subjected to various variable-amplitude load histories, the ratio of predicted-to-experimental lives ranged from 0.54 to 1.19. The mean value of predicted-to-experimental lives was 0.95 with a standard error of 0.2 for a constraint factor of 1.9.

Newman, J. C., Jr.↗
DOE OSTI2017

Rational design of super-alkalis and their role in CO 2 activation

Super-alkalis are clusters of atoms. With ionization potentials smaller than those of the alkali atoms, they are playing an increasing role in chemistry as highlighted by recent applications in solar cells as well as in Li-ion batteries. For the past 40 years superalkalis were designed using inorganic elements with the sp orbital character. Here, we show that a large class of superalkalis composed of only simple metal atoms, transition metal complexes as well as organic molecules can be designed by making use of electron counting rules beyond the octet rule. Examples include Al3+, Mn(B3N3H6)2+, B9C3H12+, and C5NH6+ which obey the jellium shell closure rule, the 18-electron rule, the Wade–Mingos rule, and Hückel's aromatic rule, respectively. We further show that the ability of superalkalis to transfer an electron easily can be used to activate a CO2 molecule by transforming it from a linear to a bent structure. These results, based on density functional theory with generalized gradient approximation for exchange–correlation potential, open the door to a new class of catalysts for CO2 activation.

Zhao, Tianshan↗
DOE OSTI2020

Multimodel simulation of vertical gas transfer in a temperate lake

In recent decades, several lake models of varying complexity have been developed and incorporated in numerical weather prediction systems and climate models. To foster enhanced forecasting ability and verification, improvement of these lake models remains essential. This especially applies to the limited simulation capabilities of biogeochemical processes in lakes and greenhouse gas exchanges with the atmosphere. Here we present multi-model simulations of physical variables and dissolved gas dynamics in a temperate lake (Harp Lake, Canada). The five models (ALBM, FLake, LAKE, LAKEoneD, MTCR-1) considered within this most recent round of the Lake Model Intercomparison Project (LakeMIP) all captured the seasonal temperature variability well. In contrast, none of the models is able to reproduce the exact dates of ice-cover and ice-off, leading to considerable errors in the simulation of eddy diffusivity around those dates.We then conducted an additional modeling experiment with a diffusing passive tracer to isolate the effect of the eddy diffusivity on gas concentration. Remarkably, sophisticated k -" models do not demonstrate a significant difference in the vertical diffusion of a passive tracer compared to models with much simpler turbulence closures. All models simulate less intensive spring overturn compared to autumn. Reduced mixing in the models consequently leads to the accumulation of the passive tracer distribution in the water column. The lake models with a comprehensive biogeochemical module, such as ALBM and LAKE, predict dissolved oxygen dynamics adequate to the observed data. However, for the surface carbon dioxide concentration the correlation between modeled (ALBM, LAKE) and observed data is weak (~0.3). Overall our results indicate the need to improve the representation of physical and biogeochemical processes in lake models, thereby contributing to enhanced weather prediction and climate projection capabilities.

Guseva, Sofya↗