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At least 379 records · Page 21

A parametric numerical study of mixing in a cylindrical duct

The interaction is described of some of the important parameters affecting the mixing process in a quick mixing region of a rich burn/quick mix/lean burn (RQL) combustor. The performance of the quick mixing region is significantly affected by the geometric designs of both the mixing domain and the jet inlet orifices. Several of the important geometric parameters and operating conditions affecting the mixing process were analytically studied. Parameters such as jet-to-mainstream momentum flux ratio (J), mass flow ratio (MR), orifice geometry, orifice orientation, and number of orifices/row (equally spaced around the circumferential direction were analyzed. Three different sets of orifice shapes were studied: (1) square, (2) elongated slots, and (3) equilateral triangles. Based on the analytical results, the best mixing configuration depends significantly on the penetration depth of the jet to prevent the hot mainstream flow from being entrained behind the orifice. The structure in a circular mixing section is highly weighted toward the outer wall and any mixing structure affecting this area significantly affects the overall results. The increase in the number of orifices per row increases the mixing at higher J conditions. Higher slot slant angles and aspect ratios are generally the best mixing configurations at higher momentum flux ratio (J) conditions. However, the square and triangular shaped orifices were more effective mixing configurations at lower J conditions.

Oechsle, V. L.↗

Continuously Improving Parametric Modeling with Historical Data on the ICESat-2 Mission

This paper delves into the details of the Joint Confidence Level (JCL) process performed for the Ice, Cloud, and Land Elevation Satellite (ICESat)-2 mission and how past performance was incorporated into subsequent JCL models to enable the project to continuously analyze potential slips to their launch readiness date (LRD). One year prior to the mission Preliminary Review (mPDR), the JCL model development process began. The first model was well received at the mPDR, held on October 10, 2012, and the input received by the Standing Review Board was incorporated into the model for the official data drop for key decision point (KDP)-C. The 70% JCL results of the October 2012 mPDR model forecast an LRD of February 2017 and associated cost of $830M. This result in 2012 immediately highlighted potential challenges with the project-planned LRD of July 2016. The year following the mPDR, the project had sustained a oneyear slip in the LRD due to problematic systems engineering requirement issues which impacted all project subsystems. This slip moved the project planned LRD from July 2016 to July 2017, an additional 5 months beyond the 2012 model’s 70% JCL result for the LRD of February 2017. As the project was quickly approaching the mission Critical Design Review (mCDR), the need for reliable JCL results increased significantly. The project held discussions on the JCL modeling process and focused on the input uncertainty distributions. Specifically, to identify the uncertainty distributions that the 2012 mPDR model would have needed to produce a 70% LRD result of July 2017. This led the project to compare multiple uncertainty distributions, and ultimately spurred the project to utilize uncertainty distributions that incorporated project past performance and historical data to forecast potential LRD slips. The revised results, created in 2014 and utilizing the new uncertainty distributions, showed that with 70% confidence, the ICESat-2 mission would launch in August 2018 with a cost of $1,044M. Today, ICESat-2 is scheduled to launch on September 15, 2018 with a project management (PM) agreement value of $1,056M. This illustrates how a JCL model can be continuously improved to produce valuable results for a project, even in cases of LRD delays. The primary reason for the ICESat-2 LRD delay is due to a laser failure on the primary instrument. Laser failure was one of the highest risk and uncertainty drivers within the JCL model. The project placed the most risk in this area of the model, and the model further identified the laser as the top risk driver and contributor to the LRD result. This further illustrates how a JCL can be used to predict and quantify possible issues on new technology missions.

Krygiel, Joseph↗

Bulk viscosity from Urca processes: npeμ matter in the neutrino-trapped regime

In this work, we extend our previous study of the bulk viscosity of hot and dense npe matter induced by the Urca process in the neutrino trapped regime to npeμ matter by adding the muonic Urca processes as well as the purely leptonic electroweak processes involving electron-muon transition. Here, the nuclear matter is modeled in a relativistic density functional approach with two different parametrizations which predict neutrino dominated matter (DDME2 model) and anti-neutrino dominated matter (NL3 model) at temperatures for which neutrinos/anti-neutrinos are trapped. In the case of neutrino-dominated matter, the main equilibration mechanism is lepton capture, whereas in the case of antineutrino-dominated matter this is due to neutron decay. We find that the equilibration rates of Urca processes are higher than that of the pure leptonic processes, which implies that the Urca bulk viscosity can be computed with the leptonic reactions assumed to be frozen. We find that the bulk viscosity decreases with temperature as ζ~T –2 at moderate temperatures. At high temperatures this scaling breaks down by sharp drops of the bulk viscosity close to the temperature where the proton fraction is density-independent and the matter becomes scale-invariant. This occurs also when the matter undergoes a transition from the antineutrino-dominated regime to the neutrino-dominated regime where the bulk viscosity attains a local maximum. We also estimate the bulk viscous dissipation timescales and find that these are in the range ≳ 1 s for temperatures above the neutrino trapping temperature. These timescales would be relevant only for long-lived objects formed in binary neutron star mergers and hot proto-neutron stars formed in core-collapse supernovas.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Region and cloud regime dependence of parametric sensitivity in E3SM atmosphere model

Abstract The Department of Energy (DOE)’s Energy Exascale Earth System Model (E3SM), including its atmosphere model (EAM), has many relatively new features. In a previous study we conducted a systematic parametric sensitivity analysis for EAM based on short, perturbed parameter ensemble (PPE) simulations, mainly focusing on global mean climate features and metrics. While parameter values in global climate models are generally invariant in space and time, model response to parameters perturbation may vary by regions and climate regimes, which motivates the need to better understand the EAM model behaviors and physics at regional scale and process level. In this study, using the same set of PPE simulations and a similar sensitivity analysis framework, we identify parameters that cause largest sensitivities over different regions and compare model responses in fast atmospheric processes to the parameters across different cloud regimes for several important cloud-related fidelity metrics. We find that cloud forcing has opposite response to some parameters over mid-latitude vs. tropical land. We also analyze how the parametric sensitivity varies as stratocumulus transitions to shallow convection and to deep convection over ocean. Low cloud forcing and shortwave cloud forcing in the subtropical eastern Pacific are most sensitive to the parameters controlling the width of the probability density function (PDF) of the subgrid vertical velocity ( w’ ) ( gamma ) and the damping of the w’ skewness ( c8 ) near the coast but become more sensitive to the parameter affecting the damping of the w’ variance ( c1 ) further offshore. Detailed interpretation of the spatial dependence of parametric sensitivity is provided. We also investigate how the parametric sensitivity evolves with prediction duration. This study improves our process-level understanding of cloud physics and parameterization and provides insights for developing more advanced regime-aware parameterization schemes in global climate model.

54 ENVIRONMENTAL SCIENCES↗

An additively-manufactured molten salt-to-supercritical carbon di-oxide primary heat exchanger for solar thermal power generation – Design and techno-economic performance

The design and techno-economic performance of a compact additively manufactured (AM) molten salt (MS)-to-supercritical carbon di-oxide (sCO2) primary heat exchanger (PHE) for solar thermal application is described. The PHE design consists of sCO2 flow through an array of microscale pin fins while the MS flows through mm-scale rectangular channels. Constraints imposed by AM using laser powder bed fusion method are considered in the design. Structural and fluid flow simulations are performed to arrive at a viable design of the core and headers. A simplified one-dimensional steady state model for the PHE is developed including the impact of surface roughness from the AM process. A process-based cost model is used to determine the tradeoff between thermofluidic design and manufacturing cost. A parametric study is performed using the thermo-fluidic and cost models to determine the set of geometrical and flow variables that result in high power density and low cost, while restricting the pressure drop on the sCO2 side to less than 2% of line pressure. Flow rates of MS and sCO2 were varied over heat capacity rate ratios ranging from 0.2 to 1. Results indicate that it is possible to design a low-pressure drop AM PHE with an effectiveness of 90% and a power density in excess of 10 MW/m3 (including headers). Fabrication of representative nickel superalloy specimens are shown to demonstrate that low-porosity parts with the requisite dimensional tolerance of PHE core can be generated.

14 SOLAR ENERGY↗

An urnful of blinding functions

There is a fundamental connection between the mathematical theory of discrete probability distributions and the parametric curves and surfaces of computer-aided geometric design. It is no accident that the blending functions of Bezier curves and surfaces have an obvious probabilistic interpretation, nor is it a coincidence that the normalized uniform B-spline basis functions also model a simple stochastic process. The link between probability and geometry, and how to exploit simple probabilistic arguments to derive many of the classical geometric properties of the parametric curves and surfaces currently in vogue in computer-aided geometric design is discussed. This probabilistic approach is also used to introduce many new types of curves and surfaces, and it is demonstrated how probability theory can be used to simplify, unify, and generalize many well-known results.

Goldman, R. N.↗

Directly probing the Higgs-top coupling at high scales

We explore the sensitivity to new physics for the coupling of the Higgs boson (h) and top quark (t) at high energy scales with the process ${pp}$→ $t\bar{t}h$ at the high-luminosity LHC. This process probes the coupling in both the space-like and time-like domains at a high scale, complementary to the off-shell Higgs processes in the time-like domain. The effects from physics beyond the Standard Model are parametrized in terms of the effective field theory framework and a non-local Higgs-top form factor. Focusing on the boosted Higgs regime in association with jet substructure techniques, we show that the present search can directly probe the Higgs-top coupling to good precision, providing a strong sensitivity to the new physics scale

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

An optimized cubic interpolator for image resampling

It is noted that the cubic resampling function is only one member of a family of functions, defined by the single parameter of the slope of the cubic function at its first zero crossing, whose other members are in some cases superior to the standard cubic. This superiority is especially noteworthy with respect to the extent of gray level overshoot induced by the resampling process at high contrast edges. It is shown that there is an optimum member of this 'parametric cubic convolution' family which minimizes the mean-squared radiometric error arising from interpolation. This interpolator requires no additional computation time over the conventional cubic one. These conclusions are supported and illustrated by resampling simulations with both a high resolution digitized aerial image and a Landsat Multispectral Scanner image.

Schowengerdt, R. A.↗

Cost estimating methods for advanced space systems

The development of parametric cost estimating methods for advanced space systems in the conceptual design phase is discussed. The process of identifying variables which drive cost and the relationship between weight and cost are discussed. A theoretical model of cost is developed and tested using a historical data base of research and development projects.

Cyr, Kelley↗

Magnetic beneficiation of highland and hi-Ti mare soils - Magnet requirements

Magnetic beneficiation of immature highland soil 67511 recovered 22 wt pct of the sample with an iron oxide content of 0.6 pct. Magnetic isolates of immature highland soils are candidates for the manufacture of silicon, aluminum, and other metals. Fifty-seven percent of the ilmenite in immature mare soil 71061 was recovered in magnetic processing. Ilmenite can be recovered by magnetic separation but may be difficult to 'high'grade'. A parametric description is given of magnetic separators suitable for supplying ilmenite for the production of 22.7 metric tons per year oxygen.

Oder, R. R.↗

RS-84 Engine

The RS-84 is the first reusable hydrocarbon staged combustion liquid rocket engine. This engine is being developed to meet NASA s crew safety goals with a highly reliable and low cost main engine as a part of the NASA Space Launch Initiative program for the next generation reusable launch system. The NASA-MSFC and Rocketdyne team brings over 50 years of successful rocket engine development experience to meet the challenges of this new program. This team s extensive design database has been anchored with almost five decades of hydrocarbon rocket engine development and flight operations experience including Delta, Atlas, and Saturn vehicles and nearly three decades of successfully operating the world s only reusable pump-fed rocket engine, the Space Shuttle Main Engine. The team also fully benefits from the proven and experienced engineering staffs that recently completed the successful MC-1 FASTRAC , XRS-2200, and RS-68 engine development programs and the ongoing IPD and RS-76 technology development. Advances in integrated parametric design and analysis tools, advanced materials knowledge base, and state-of-the-art fabrication processes anchored and refined during the recent engine development programs are already being used by the team to design this engine.

Stegman, E.↗

The Effect of Fiber-Angle Fidelity on the Linear Response of Tow-steered Composite Plates

Composite laminate tailoring is traditionally performed by uniformly changing the in-plane ply orientation to obtain the desired mechanical performance. The emergence of tow-steered plies, where the fibers follow a prescribed curvilinear path, have increased the tailorability of composite laminates. However, characterizing the behavior of tow-steered laminates using finite element analysis is challenging because additional, and often numerous, orientation definitions may be required. The additional orientation definitions detrimentally increase the computational cost and hinder the use of advanced analysis techniques, such as Monte Carlo or uncertainty quantification, in the design process. To reduce computational cost without adversely affecting mechanics-based performance, the results of a parametric study that was used to investigate the effects of fiber-angle fidelity, element size, and tow-steered radius-of-curvature on various loading scenarios for tow-steered composite plates are presented. The three loading scenarios that were analyzed using finite element analysis included an axial tension load, an applied constant through-thickness-direction pressure load, and an axial compression load. Results for mechanics-based metrics of interest are presented and discussed for each loading scenario. Little sensitivity (less than one percent difference) to the effect of fiber-angle fidelity is observed in the mechanics-based metrics until the coarse-end of the considered range. Sensitivity to element size generally dominates the observed results for the mechanics-based metrics. Notable reductions in the preprocessing time are observed for increasingly coarse element size and fiber-rounding parameters. The preprocessing times decreased up to three orders of magnitude from a few thousand seconds to a few seconds without loss of accuracy in the mechanics-based metrics. Such increased computational performance is of particular interest to the structural design and analysis communities that may be conducting large counts of finite-element analyses, such as in other parametric studies, Monte-Carlo analyses, uncertainty quantification, or tow-steered optimization.

tow-steered composites↗

Thermodynamic modeling of MDEA(aq)-NH 3 (aq)-K 2 CO 3 (aq)-CO 2 (aq) using the Extended UNIQUAC model

Here, the development of advanced processes for carbon dioxide capture requires reliable thermodynamic models to ensure accurate process design. This work presents an optimized parameter set of the Extended UNIQUAC model for advanced mixed solvent solutions containing CO 2 -MDEA-NH 3 -K 2 CO 3 in water. The model was parameterized using vapor–liquid equilibrium, pure component saturation pressure, excess enthalpy, heat of absorption, molar heat capacity, apparent molar heat capacity, and solid–liquid equilibrium. These thermal and equilibrium properties cover temperatures between 253.6 K to 600 K and pressures up to 75.6 bar. The current model represents an extension of previous versions that were suitable for modeling aqueous NH 3 and K 2 CO 3 solutions. This parametrization accounts for molecular interactions between MDEA and these two components, which allows for the design of advanced capture processes. This paper demonstrates that the new model parameters are valid within the range of operational conditions typically found in CO 2 capture processes.

42 ENGINEERING↗

Improving deep learning model performance under parametric constraints for materials informatics applications

Abstract Modern machine learning (ML) and deep learning (DL) techniques using high-dimensional data representations have helped accelerate the materials discovery process by efficiently detecting hidden patterns in existing datasets and linking input representations to output properties for a better understanding of the scientific phenomenon. While a deep neural network comprised of fully connected layers has been widely used for materials property prediction, simply creating a deeper model with a large number of layers often faces with vanishing gradient problem, causing a degradation in the performance, thereby limiting usage. In this paper, we study and propose architectural principles to address the question of improving the performance of model training and inference under fixed parametric constraints. Here, we present a general deep-learning framework based on branched residual learning (BRNet) with fully connected layers that can work with any numerical vector-based representation as input to build accurate models to predict materials properties. We perform model training for materials properties using numerical vectors representing different composition-based attributes of the respective materials and compare the performance of the proposed models against traditional ML and existing DL architectures. We find that the proposed models are significantly more accurate than the ML/DL models for all data sizes by using different composition-based attributes as input. Further, branched learning requires fewer parameters and results in faster model training due to better convergence during the training phase than existing neural networks, thereby efficiently building accurate models for predicting materials properties.

36 MATERIALS SCIENCE↗

Bubble Combustion

A method of energy production that is capable of low pollutant emissions is fundamental to one of the four pillars of NASA s Aeronautics Blueprint: Revolutionary Vehicles. Bubble combustion, a new engine technology currently being developed at Glenn Research Center promises to provide low emissions combustion in support of NASA s vision under the Emissions Element because it generates power, while minimizing the production of carbon dioxide (CO2) and nitrous oxides (NOx), both known to be Greenhouse gases. and allows the use of alternative fuels such as corn oil, low-grade fuels, and even used motor oil. Bubble combustion is analogous to the inverse of spray combustion: the difference between bubble and spray combustion is that spray combustion is spraying a liquid in to a gas to form droplets, whereas bubble combustion involves injecting a gas into a liquid to form gaseous bubbles. In bubble combustion, the process for the ignition of the bubbles takes place on a time scale of less than a nanosecond and begins with acoustic waves perturbing each bubble. This perturbation causes the local pressure to drop below the vapor pressure of the liquid thus producing cavitation in which the bubble diameter grows, and upon reversal of the oscillating pressure field, the bubble then collapses rapidly with the aid of the high surface tension forces acting on the wall of the bubble. The rapid and violent collapse causes the temperatures inside the bubbles to soar as a result of adiabatic heating. As the temperatures rise, the gaseous contents of the bubble ignite with the bubble itself serving as its own combustion chamber. After ignition, this is the time in the bubble s life cycle where power is generated, and CO2, and NOx among other species, are produced. However, the pollutants CO2 and NOx are absorbed into the surrounding liquid. The importance of bubble combustion is that it generates power using a simple and compact device. We conducted a parametric study using CAVCHEM, a computational model developed at Glenn, that simulates the cavitational collapse of a single bubble in a liquid (water) and the subsequent combustion of the gaseous contents inside the bubble. The model solves the time-dependent, compressible Navier-Stokes equations in one-dimension with finite-rate chemical kinetics using the CHEMKIN package. Specifically, parameters such as frequency, pressure, bubble radius, and the equivalence ratio were varied while examining their effect on the maximum temperature, radius, and chemical species. These studies indicate that the radius of the bubble is perhaps the most critical parameter governing bubble combustion dynamics and its efficiency. Based on the results of the parametric studies, we plan on conducting experiments to study the effect of ultrasonic perturbations on the bubble generation process with respect to the bubble radius and size distribution.

Corrigan, Jackie↗

Parametric Study of Reactive Melt Infiltration

Reactive melt infiltration is viewed as a promising means of achieving near-net shape manufacturing with quick processing time and at low cost. Since the reactants and products are, in general, of varying density, overall conservation of mass dictates that there is a force related to chemical conversion which can directly influence infiltration behavior. In effect, the driving pressure forces may compete with the forces from chemical conversion, affecting the advancement of the front. We have developed a two-dimensional numerical code to examine these effects, using reaction-formed silicon carbide as a model system for this process. We have examined a range of initial porosities, pore radii, and reaction rates in order to investigate their effects on infiltration dynamics.

Nelson, Emily S.↗

Parametric study in weld mismatch of longitudinally welded SSME HPFTP inlet

Welded joints are an essential part of pressure vessels such as the Space Shuttle Main Engine (SSME) Turbopumps. Defects produced in the welding process can be detrimental to weld performance. Recently, review of the SSME high pressure fuel turbopump (HPFTP) titanium inlet x rays revealed several weld discrepancies such as penetrameter density issues, film processing discrepancies, weld width discrepancies, porosity, lack of fusion, and weld offsets. Currently, the sensitivity of welded structures to defects is of concern. From a fatigue standpoint, weld offset may have a serious effect since local yielding, in general, aggravates cyclic stress effects. Therefore, the weld offset issue is considered. Using the finite element method and mathematical formulations, parametric studies were conducted to determine the influence of weld offsets and a variation of weld widths in longitudinally welded cylindrical structures with equal wall thickness on both sides of the joint. From the study, the finite element results and theoretical solutions are presented.

Min, J. B.↗

Multiple frequency radar observations of high-latitude E region irregularities in the HF modified ionosphere

This paper discusses the results of the September 1983 observations of artificial field-aligned irregularities (AFAIs) in the Tromso, Norway region, made by backscatter radars operating at 46.9, 143.8, 21.4, and 140.0 MHz. Four classes of resonant instability processes at work in the E and F regions are examined in detail: (1) the coupling of parametric decay instability waves across geomagnetic field lines, (2) thermal parametric instability, (3) four-wave interaction thermal parametric instability, and (4) the resonance instability. The characteristics of the AFAI scatter are described, with special attention given to the growth and decay time constants, functional dependence on the heater power and polarization, and the scattering cross sections of the irregularities.

Noble, S. T.↗