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DOE OSTI2019

Power-Law Scaling in the Internal Variability of Cumulus Cloud Size Distributions due to Subsampling and Spatial Organization

In this study, the spatial structure of cumulus cloud populations is investigated using three-dimensional snapshots from large-domain LES experiments. The aim is to understand and quantify the internal variability in cloud size distributions due to subsampling effects and spatial organization. A set of idealized shallow cumulus cases is selected with varying degrees of spatial organization, including a slowly organizing marine precipitating case and five more quickly organizing diurnal cases over land. A subdomain analysis is applied, yielding cloud number distributions at sample sizes ranging from severely undersampled to nearly complete. A strong power-law scaling is found in the relation between cloud number variability and subdomain size, reflecting an inverse linear relation. Scaling subdomain size by cloud size yields a data collapse across time points and cases, highlighting the role played by cloud spacing in controlling the stochastic variability. Spatial organization acts on top of this baseline model by increasing the maximum cloud size and by enhancing the variability in the number of smallest clouds. This reflects that the smaller clouds start to live on top of larger-scale thermodynamic structures, such as cold pools, which favor or inhibit their formation. Compositing all continental cumulus cases suggests the existence of a prototype diurnal time dependence in the spatial organization. A simple stochastic expression for cloud number variability is proposed that is formulated in terms of two dimensionless groups, which allows objective estimation of the degree of spatial organization in simulated and observed cumulus cloud populations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2007

Effective Inflow Conditions for Turbulence Models in Aerodynamic Calculations

The selection of inflow values at boundaries far upstream of an aircraft is considered, for one- and two-equation turbulence models. Inflow values are distinguished from the ambient values near the aircraft, which may be much smaller. Ambient values should be selected first, and inflow values that will lead to them after the decay second; this is not always possible, especially for the time scale. The two-equation decay during the approach to the aircraft is shown; often, the time scale has been set too short for this decay to be calculated accurately on typical grids. A simple remedy for both issues is to impose floor values for the turbulence variables, outside the viscous sublayer, and it is argued that overriding the equations in this manner is physically justified. Selecting laminar ambient values is easy, if the boundary layers are to be tripped, but a more common practice is to seek ambient values that will cause immediate transition in boundary layers. This opens up a wide range of values, and selection criteria are discussed. The turbulent Reynolds number, or ratio of eddy viscosity to laminar viscosity has a huge dynamic range that makes it unwieldy; it has been widely mis-used, particularly by codes that set upper limits on it. The value of turbulent kinetic energy in a wind tunnel or the atmosphere is also of dubious value as an input to the model. Concretely, the ambient eddy viscosity must be small enough to preserve potential cores in small geometry features, such as flap gaps. The ambient frequency scale should also be small enough, compared with shear rates in the boundary layer. Specific values are recommended and demonstrated for airfoil flows

Spalart, Philippe R.↗

DOE OSTI2020

Machine learning to predict biomass sorghum yields under future climate scenarios

Crop yield modeling is critical in the design of national strategies for agricultural production, particularly in the context of a changing climate. Forecasting yields of bioenergy crops at fine spatial resolutions can help to evaluate near-term and long-term pathways for scaling up bio-based fuel and chemical production, and for understanding the impacts of abiotic stressors such as severe droughts and temperature extremes on potential biomass supply. In this work we used a large dataset of 28,364 Sorghum bicolor yield samples (uniquely identified by county and year of observation), environmental variables, and multiple approaches to analyze historical trends in sorghum productivity across the USA. We selected the most accurate machine learning approach (a variation of the random forest approach) to predict future trends in sorghum yields under four greenhouse gas (GHG) emission scenarios and two irrigation regimes. We identified irrigation practices, vapor pressure deficit, and time (a proxy for technological improvement) as the most important predictors of sorghum productivity. Our results showed a decreasing trend of sorghum yields over future years (on average 2.7% from 2018 to 2099), with greater decline under a high GHG emissions scenario (3.8%) and in the absence of irrigation (4.6%). Geographically, we observed the steepest predicted declines in the Great Lakes (8.2%), Upper Midwest (7.5%), and Heartland (6.7%) regions. Our study demonstrates the use of machine learning to identify environmental controllers of sorghum biomass yield and predict yields with reasonable accuracy. These results can inform the development of more realistic biomass supply projections for bioenergy if sorghum production is scaled up. (c) 2020 Society of Chemical Industry and John Wiley & Sons, Ltd

09 BIOMASS FUELS↗

DOE OSTI2022

An analytical method for identifying synergies between behind-the-meter battery and thermal energy storage

Electric utilities build generation capacity to meet the highest demand period, and they often pass on the costs associated with these peaking generators to building owners through demand charges. Building owners can minimize these demand charges by shifting energy use away from peak periods with behind-the-meter storage. This storage can include batteries, which can directly shift the metered load, or thermal energy storage, which can shift thermal-driven electric loads like air conditioning. However, there is a lack of research on how best to combine battery and thermal energy storage. In this study, we develop an analytical sizing method to calculate the potential demand reduction and annualized cost savings for different combinations of thermal and battery energy storage sizes. We show that adding batteries to a thermal energy storage system can increase the total system's load shaving potential. This is particularly true when the building has onsite photovoltaic generation or electric vehicle charging, which add significant variability to the load shape. We also show that for a given total storage size, selecting a higher fraction of thermal energy storage can significantly lower the cycling of the battery, and therefore extend the battery life. This, combined with the expected lower first cost of thermal energy storage materials compared to batteries, shows that hybrid energy storage systems can outperform a standalone battery or standalone thermal storage system. Assuming the thermal storage has a capital cost 6x lower than the battery, our analysis shows that the optimal system is 71% thermal energy storage and 29% battery energy storage for a scenario with electric vehicle charging. The annualized cost savings for this system are $48.6 k/yr, whereas an equivalently sized standalone thermal energy storage system would provide annualized cost savings of $28.5 k/yr and a standalone battery would lead to savings of $8.72 k/yr. The hybrid system also reduces battery cycling by 52% compared to a standalone battery, extending battery lifetime.

25 ENERGY STORAGE↗

DOE OSTI2025

Metal additive manufacturing simulation across length, time, and computing scales

Metal additive manufacturing (AM) offers a unique opportunity for production of advanced materials and complex geometries. However, variability in microstructure and properties challenges conventional approaches to design, process optimization, qualification, and materials selection. Modeling and simulation can improve understanding of AM processing and materials, but also poses major challenges for existing computational methods. Simultaneously, modern scientific computing hardware has become increasingly complex, most notably with the adoption of hybrid architectures such as Graphical Processing Units (GPUs). If appropriately utilized, emerging computational capabilities provide an opportunity to reveal new insight into AM processing and the resulting material structure and properties. In this review we describe the computational AM landscape, identify critical gaps, and highlight opportunities to impact the development and application of AM. First, the requirements and challenges of representative AM problem statements will be defined. Here, these problems range from scientific studies to industrial applications and are designed to capture the breadth of challenges facing the AM community. Next, the current state of AM modeling and simulation is evaluated, broken down by enabling hardware and software, process simulation, microstructure simulation, and property simulation. Each section describes the diversity of simulation approaches and associated trade-offs in physical fidelity and computational expense. Each area is then assessed based on their suitability and readiness for current and developing computational architectures. Lastly, the greatest opportunities for future research and application are highlighted, including gaps in modeling capabilities, opportunities for near-term application, and key scientific challenges.

additive manufacturing↗

DOE OSTI2019

SEPATH: benchmarking the search for pathogens in human tissue whole genome sequence data leads to template pipelines

Background: Human tissue is increasingly being whole genome sequenced as we transition into an era of genomic medicine. With this arises the potential to detect sequences originating from microorganisms, including pathogens amid the plethora of human sequencing reads. In cancer research, the tumorigenic ability of pathogens is being recognized, for example, Helicobacter pylori and human papillomavirus in the cases of gastric non-cardia and cervical carcinomas, respectively. As of yet, no benchmark has been carried out on the performance of computational approaches for bacterial and viral detection within host-dominated sequence data. Results: We present the results of benchmarking over 70 distinct combinations of tools and parameters on 100 simulated cancer datasets spiked with realistic proportions of bacteria. mOTUs2 and Kraken are the highest performing individual tools achieving median genus-level F1 scores of 0.90 and 0.91, respectively. mOTUs2 demonstrates a high performance in estimating bacterial proportions. Employing Kraken on unassembled sequencing reads produces a good but variable performance depending on post-classification filtering parameters. These approaches are investigated on a selection of cervical and gastric cancer whole genome sequences where Alphapapillomavirus and Helicobacter are detected in addition to a variety of other interesting genera. Conclusions: We provide the top-performing pipelines from this benchmark in a unifying tool called SEPATH, which is amenable to high throughput sequencing studies across a range of high-performance computing clusters. SEPATH provides a benchmarked and convenient approach to detect pathogens in tissue sequence data helping to determine the relationship between metagenomics and disease.

Viral↗

DOE OSTI2024

Long-Term Infrasound Sensor Calibration and Characterization

Previous testing has shown that infrasound sensors deployed in the field can exhibit notable deviations from their nominal, lab-based calibrations. These variations may be due to changes in environmental conditions, long-term sensor drift, or other unresolved features. In early 2018, we installed two identical infrasound elements with five infrasound sensors at each element (Chaparral M50A, Chaparral M64LN, CEA/Martec MB2005, CEA/Seismowave MB3a, and Hyperion IFS-5113A). These sensors were accepted or under consideration for use in the International Monitoring System network of the Comprehensive Nuclear-Test-Ban Treaty. Each element had all sensors connected to a single digitizer and port to the atmosphere. We also recorded instrument enclosure air temperature and humidity and external air temperature. Using the MB2005 as the reference, we examine the relative sensor response (both magnitude and phase) as a function of time and frequency and compare it with quarterly laboratory calibrations and environmental conditions. Here, we find that the magnitude response for all sensors exhibits some variability in both the lab and field, with the amplitude variations often >5%. The field-based variations are more severe and occur on both long-term (months) and short-term (hours) timescales. Short-term variability correlates with changes in environmental conditions and is considerable (up to 25%) for the Chaparral M50A and noticeable (∼5%) for the French Alternative Energies and Atomic Energy Commission (CEA) MB3a. Long-term magnitude variability for the Chaparral M50A was up to 50% and does not clearly correlate with environmental conditions. The other sensors show some long-term magnitude offsets, but they have relatively stable responses in the conditions we examined. The MB3a also displays some frequency-dependent magnitude variability and shows a minor dependence on temperature. Phase estimates are stable and near zero for all sensors tested. These results strongly suggest sensor response and variability due to environmental conditions should be considered in future infrasound data interpretation and sensor selection and development.

Fee, David↗

NASA NTRS1973

A parametric study of planform and aeroelastic effects on aerodynamic center, alpha- and q-stability derivatives

Summarized are the aerodynamic center, alpha and q- aeroelastic effects on fighter-type aircraft in the 18,700 N gross range. The results indicate that with proper tailoring of planform (fixed or variable sweep), stiffner and elastic axis location it is possible to minimize trim requirements between selected extreme conditions. The inertial effects were found to be small for this class of aircraft.

Roskam, J.↗

NASA NTRS1976

Performance, emissions, and physical characteristics of a rotating combustion aircraft engine

The RC2-75, a liquid cooled two chamber rotary combustion engine (Wankel type), designed for aircraft use, was tested and representative baseline (212 KW, 285 BHP) performance and emissions characteristics established. The testing included running fuel/air mixture control curves and varied ignition timing to permit selection of desirable and practical settings for running wide open throttle curves, propeller load curves, variable manifold pressure curves covering cruise conditions, and EPA cycle operating points. Performance and emissions data were recorded for all of the points run. In addition to the test data, information required to characterize the engine and evaluate its performance in aircraft use is provided over a range from one half to twice its present power. The exhaust emissions results are compared to the 1980 EPA requirements. Standard day take-off brake specific fuel consumption is 356 g/KW-HR (.585 lb/BHP-HR) for the configuration tested.

Berkowitz, M.↗

NASA NTRS1979

Decoupling control of a long flexible beam in orbit

The paper presents a method of control for large flexible systems using state variable feedback, with a long flexible beam given as an example. These feedback gains are selected: (1) based on the decoupling of the original coordinates and to obtain proper damping and (2) by applying the linear regulator problem to the individual modal coordinates separately. It is shown that the linear control law thus obtained are then evaluated by numerical integration of the non-linear system equations. Also included are results showing the effects (control spillover) on the uncontrolled modes when the number of controllers is less than the number of modes, and the effects of inaccurate knowledge of the control influence coefficients which lead to errors in the calculated feedback gains.

Reddy, A. S. S. R.↗

NASA NTRS1981

VTOL as it applies to resource development in the Canadian north

It is pointed out that, for many of the natural resource development projects planned in Canada between now and the end of the century, it may be necessary for the work force to commute to the site by air. Examples of successful operations, including those involving VTOL, are given. A computer program developed for determining the least expensive type of aircraft for commuting to remote projects is described. It is noted that the program can select both fixed-wing and helicopter aircraft types for a specific project, employing such variables as the size and shift schedules of the work force and the commuting distance. Capital and operating costs of existing and proposed aircraft types, as well as groundside infrastructure operations and maintenance costs, are compared for competing aircraft.

Lightfoot, R. N.↗

NASA NTRS1984

A simulation of remote sensor systems and data processing algorithms for spectral feature classification

A computational model of the deterministic and stochastic processes involved in multispectral remote sensing was designed to evaluate the performance of sensor systems and data processing algorithms for spectral feature classification. Accuracy in distinguishing between categories of surfaces or between specific types is developed as a means to compare sensor systems and data processing algorithms. The model allows studies to be made of the effects of variability of the atmosphere and of surface reflectance, as well as the effects of channel selection and sensor noise. Examples of these effects are shown.

Arduini, R. F.↗

NASA NTRS1985

Extraction of information from major element chemical analyses of lunar basalts

Major element chemical analyses often form the framework within which similarities and differences of analyzed specimens are noted and used to propose or devise models. When percentages are formed the ratios of pairs of components are preserved whereas many familiar statistical and geometrical descriptors are likely to exhibit major changes. This ratio preserving aspect forms the basis for a proposed framework. An analysis of compositional variability within the data set of 42 major element analyses of lunar reference samples was selected to investigate this proposal.

Butler, J. C.↗

NASA NTRS1986

Sensitivity analysis and approximation methods for general eigenvalue problems

Optimization of dynamic systems involving complex non-hermitian matrices is often computationally expensive. Major contributors to the computational expense are the sensitivity analysis and reanalysis of a modified design. The present work seeks to alleviate this computational burden by identifying efficient sensitivity analysis and approximate reanalysis methods. For the algebraic eigenvalue problem involving non-hermitian matrices, algorithms for sensitivity analysis and approximate reanalysis are classified, compared and evaluated for efficiency and accuracy. Proper eigenvector normalization is discussed. An improved method for calculating derivatives of eigenvectors is proposed based on a more rational normalization condition and taking advantage of matrix sparsity. Important numerical aspects of this method are also discussed. To alleviate the problem of reanalysis, various approximation methods for eigenvalues are proposed and evaluated. Linear and quadratic approximations are based directly on the Taylor series. Several approximation methods are developed based on the generalized Rayleigh quotient for the eigenvalue problem. Approximation methods based on trace theorem give high accuracy without needing any derivatives. Operation counts for the computation of the approximations are given. General recommendations are made for the selection of appropriate approximation technique as a function of the matrix size, number of design variables, number of eigenvalues of interest and the number of design points at which approximation is sought.

Murthy, D. V.↗

NASA NTRS1988

Liquid rocket boosters for the Space Shuttle - An outline of trade issues and analysis techniques

Numerous liquid rocket booster configurations were studied to replace the Solid Rocket Boosters on the current Space Shuttle. While improved safety, reliability, performance and economy of operation were sought, the designs also sought to minimize volumetric growth to reduce aerodynamic loads and structural modifications. Aero loads could be significant as a function of booster diameter if extrapolated directly from solid rocket characteristics. Procedures to meet these goals with analytical booster sizing and simple dynamic simulations are shown. Engine chamber pressure proved to be a good independent variable for implications of pressure-fed and pump-fed engines, fuel and material selection. For some configurations, ascent trajectory modifications were suggested: longer vertical rise, lofting, heads-up orientation, and higher first and second stage target altitudes. Since engine manufacture would dominate booster costs, booster simplification of reuse are discussed based on cost estimates.

Kelly, W. D.↗

NASA NTRS1990

High galactic latitude cataclysmic variables

A sample of stars which are either known or are good candidates for being halo cataclysmic variables has been isolated. This sample consists of 84 stars of which 57 are dwarf novae (two of these are probable DQ Her systems), 12 are novalike stars, seven are AM Her objects, and eight are classical novae. Periodicities are known for 27 of the systems. If these stars are indeed halo members, then their distances range from 350 pc to 8 kpc and they represent objects that should be significantly older than their disk counterparts. If they do not represent true halo members, then they are intrinsically very faint systems (Mv greater than +10). Comparing the gross properties of this sample to those for the disk cataclysmic variables, it is found that below the period gap, the mean outburst amplitude for the halo dwarf novae is 3 mag greater than for the disk dwarf novae. For systems with periods less than 4 h, the halo cataclysmic variables have a higher percentage of systems below the period gap than the disk cataclysmic variables. The implications of these findings are discussed, as well as possible sample biases and selection effects.

Howell, Steve B.↗

NASA NTRS1991

Quasi-perpendicular/quasi-parallel divisions of earth's bow shock

Computer-drawn diagrams of the boundaries between quasi-perpendicular and quasi-parallel areas of earth's bow shock are displayed for a few selected cone angles of static interplanetary magnetic field (IMF). The effect on the boundary of variable IMF in the foreshock is also discussed and shown for one nominal case. The boundaries demand caution in applying them to the realistic, dynamic conditions of the solar wind and in interpreting the effects of small cone angles on the distributions of structures at the shock. However, the calculated, first-order boundaries are helpful in defining areas of the shock where contributions from active structures inherent in quasi-parallel geometry may be distinguishable from those derived secondarily from upstream reflected ion dynamics. The boundaries are also compatible with known behavior of daytime ULF geomagnetic waves and pulsations according to models postulating that cone angle-controlled, time-dependent ULF activity around the subsolar point of the bow shock provides the source of geomagnetic excitation.

Greenstadt, E. W.↗

NASA NTRS1994

Optimization of Orifice Geometry for Cross-Flow Mixing in a Cylindrical Duct

Mixing of gaseous jets in a cross-flow has significant applications in engineering, one example of which is the dilution zone of a gas turbine combustor. Despite years of study, the design of jet injection in combustors is largely based on practical experience. A series of experiments was undertaken to delineate the optimal mixer orifice geometry. A cross-flow to core-flow momentum-flux ratio of 40 and a mass flow ratio of 2.5 were selected as representative of an advanced design. An experimental test matrix was designed around three variables: the number of orifices, the orifice aspect ratio (long-to-short dimension), and the orifice angle. A regression analysis was performed on the data to arrive at an interpolating equation that predicted the mixing performance of orifice geometry combinations within the range of the test matrix parameters. Results indicate that mixture uniformity is a non-linear function of the number of orifices, the orifice aspect ratio, and the orifice angle. Optimum mixing occurs when the asymptotic mean jet trajectories are in the range of 0.35 less than r/R less than 0.5 (where r = 0 is at the mixer wall) at z/R = 1.0. At the optimum number of orifices, the difference between shallow-angled slots with large aspect ratios and round holes is minimal and either approach will lead to good mixing performance. At the optimum number of orifices, it appears possible to have two local optimums where one corresponds to an aspect ratio of 1.0 and the other to a high aspect ratio.

Sowa, W. A.↗