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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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At least 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

SU-F-E-20: A Mathematical Model of Linac Jaw Calibration Integrated with Collimator Walkout

Purpose: Accurate jaw calibration is possible, but it does not necessarily achieve good junctions because of collimator rotation walkout. We developed a mathematical model seeking to pick an origin for calibration that minimizes the collimator walkout effect. Methods: We use radioopaque markers aligned with crosshair on the EPID to determine the collimator walkout at collimator angles 0°, 90° and 270°. We can accurately calibrate jaws to any arbitrary origin near the radiation field centre. While the absolute position of an origin moves with the collimator walkout, its relative location to the crosshair is an invariant. We studied two approaches to select an optimal origin. One approach seeks to bring all three origin locations (0°–90°–270°) as close as possible by minimizing the perimeter of the triangle formed by these points. The other approach focuses on the gap for 0°–90° junctions. Results: Our perimeter cost function has two variables and non-linear behaviour. Generally, it does not have zero-perimeter-length solution which leads to perfect jaw matches. The zero solution can only be achieved, if the collimator rotates about a single fixed axis. In the second approach, we can always get perfect 0°–0° and 0°–90° junctions, because we ignore the 0°–270° situation. For our TrueBeams, both techniques for selecting an origin improved junction dose inhomogeneities to less than ±6%. Conclusion: Our model considers the general jaw matching with collimator rotations and proposes two potential solutions. One solution optimizes the junction gaps by considering all three collimator angles while the other only considers 0°–90°. The first solution will not give perfect matching, but can be clinically acceptable with minimized collimator walkout effect, while the second can have perfect junctions at the expense of the 0°–270° junctions. Different clinics might choose between these two methods basing on their clinical practices.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Improving thermodynamic nudging in the E3SM Atmosphere Model version 2 (EAMv2): strategy and hindcast skills on weather systems

Nudging techniques are commonly employed to constrain atmospheric simulations toward observed states, facilitating model evaluation and sensitivity studies. However, if applied improperly – particularly to thermodynamic variables such as temperature and humidity – nudging can distort physical processes and introduce spurious biases, undermining the credibility of the simulations. This study presents an improved nudging implementation that applies vertically modulated tendencies to reduce adverse impacts on model physics. The framework is tested in version 2 of the Energy Exascale Earth System Model (EAMv2) using a suite of hindcast simulations nudged toward ERA5 reanalysis. We systematically evaluate the individual and combined effects of nudging wind, temperature, and humidity fields on the model's ability to represent large-scale atmospheric states and high-impact weather systems. Results show that the revised strategy – particularly when nudging temperature and humidity at selected levels – enhances hindcast skill by improving agreement with ERA5 without degrading the hydrological cycle or precipitation processes. Additional improvements in surface temperature, outgoing longwave radiation, and precipitation biases are achieved through targeted nudging of land-surface variables. The proposed approach strengthens the representation of large-scale conditions relevant to tropical cyclones, atmospheric rivers, and extratropical cyclones in the low-resolution EAMv2. These findings demonstrate that carefully designed thermodynamic nudging, especially of temperature and humidity, improves the realism of constrained simulations and broadens the utility of nudged EAMv2 for atmospheric modeling, machine learning, and high-impact weather research.

Atmospheric river↗
DOE OSTI2016

Electrical capacitance as a predictor of root dry weight in shrub willow ( Salix ; Salicaceae) parents and progeny

Premise of the study: Root biomass is an important trait often disregarded in woody perennial selection due to the challenge and expense of accurately and efficiently measuring large populations. In this study, we aim to develop a simple method that can predict root dry weight within a diverse shrub willow ( Salix ) breeding population representing species hybrids and their parents using root electrical capacitance (REC). Methods: The REC method was tested on plants started from cuttings and grown in pots with potting mix in the greenhouse for 11 wk to assess the relationship of REC with 24 biomass traits and its usefulness in allometric models for root and stem dry biomass. Results: Strong linear and positive correlations were found between REC and root dry biomass ( r = 0.88). The total proportion of variance of root and stem dry biomass explained by predictors in multiple regression was 85% and 69%, respectively. The relative importance of predictor variables in allometric models was dominated by the contribution of REC. Discussion: This work provides an efficient and nondestructive technique to indirectly quantify root biomass of genetically diverse shrub willow progeny, which has great promise for selection of genotypes with varying root biomass and for the accurate estimation of belowground carbon sequestration.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1984

Inversion of vegetation canopy reflectance models for estimating agronomic variables. II - Use of angle transforms and error analysis as illustrated by Suits' model

The technique for inverting a vegetation canopy reflectance model described earlier (Goel and Strebel, 1983) is investigated further. The novel concept of an 'angle transform' is introduced. This concept allows the formation of functions of reflectances at different view zenith and azimuth angles, which are either sensitive or insensitive to a certain agronomic parameter. A proper combination of these functions can allow determination of all the important agronomic and spectral parameters from measured canopy reflectance data. The technique is demonstrated using Suits' (1972) model for homogeneous canopies. It is shown that leaf area index, leaf reflectance and transmittance, and average leaf angle all can be determined from the canopy reflectance at a set of selected view zenith and azimuth angles. A sensitivity analysis of the calculated values to the errors in the data is also carried out. Guidelines are formulated for the number and types of observations required to obtain the values of a particular canopy variable to within a given degree of accuracy for a given level of error in the measurement of canopy reflectance.

Goel, N. S.↗
DOE OSTI2015

Collaborative project. Ocean-atmosphere interaction from meso-to planetary-scale. Mechanisms, parameterization, and variability

This project aims to improve long term global climate simulations by resolving ocean mesoscale activity and the corresponding response in the atmosphere. The main computational objectives are; i) to perform and assess Community Earth System Model (CESM) simulations with the new Community Atmospheric Model (CAM) spectral element dynamical core; ii) use static mesh refinement to focus on oceanic fronts; iii) develop a new Earth System Modeling tool to investigate the atmospheric response to fronts by selectively filtering surface flux fields in the CESM coupler. The climate research objectives are 1) to improve the coupling of ocean fronts and the atmospheric boundary layer via investigations of dependency on model resolution and stability functions: 2) to understand and simulate the ensuing tropospheric response that has recently been documented in observations: and 3) to investigate the relationship of ocean frontal variability to low frequency climate variability and the accompanying storm tracks and extremes in high resolution simulations. This is a collaborative multi-institution project consisting of computational scientists, climate scientists and climate model developers. It specifically aims at DOE objectives of advancing simulation and predictive capability of climate models through improvements in resolution and physical process representation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Intraseasonal to interannual variability of Kelvin wave momentum fluxes as derived from high-resolution radiosonde data

Abstract. Observational estimates of Kelvin wave momentum fluxes in the tropical lower stratosphere remain challenging. Here we extend a method based on linear wave theory to estimate daily time series of these momentum fluxes from high-resolution radiosonde data. Daily time series are produced for sounding sites operated by the US Department of Energy (DOE) and from the recent Dynamics of the Madden–Julian Oscillation (DYNAMO) field campaign. Our momentum flux estimates are found to be robust to different data sources and processing and in quantitative agreement with estimates from prior studies. Testing the sensitivity to vertical resolution, our estimated momentum fluxes are found to be most sensitive to vertical resolution greater than 1 km, largely due to overestimation of the vertical wavelength. Climatological analysis is performed over a selected 11-year span of data from DOE Atmospheric Radiation Measurement (ARM) radiosonde sites. Analyses of this 11-year span of data reveal the expected seasonal cycle of momentum flux maxima in boreal winter and minima in boreal summer, and variability associated with the quasi-biennial oscillation of maxima during easterly phase and minima during westerly phase. Comparison between periods with active convection that is either strongly or weakly associated with the Madden–Julian Oscillation (MJO) suggests that the MJO provides a nontrivial increase in the lowermost stratospheric momentum fluxes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Modelling individual variability in growth of bull trout in the Walla Walla River Basin using a hierarchical von Bertalanffy growth model

Abstract We examined growth in length of fluvial bull trout ( Salvelinus confluentus ) in the Walla Walla River Basin, Washington and Oregon. Our objectives were to quantify individual variability in growth; examine growth within and among years, life history forms, life stages and sexes; and estimate von Bertalanffy growth parameters. Individual variability was evaluated by modelling asymptotic length ( L ∞ ) and the growth coefficient ( k ) as random variables. All models were fit with Bayesian methods and were evaluated for fit by the deviance information criterion. By incorporating individual variability, population‐level estimates of L ∞ and k appeared appropriate and estimated growth trajectories for specific bull trout fit individual observed patterns in growth. Growth trajectories and positive correlation between individual estimates of L ∞ and k suggest that some individuals grow at a faster rate and reach a larger maximum size than other individuals and those differences are maintained throughout life. Selected models suggest that fluvial migrants have higher estimates of L ∞ and k than residents, but there were only slight differences in parameter estimates among migrants from two adjacent spawning populations in the Walla Walla River Basin, as well as between males and females. Growth rates increased for fluvial migrants after subadult emigration. Individual variability in growth is consistent with the life history diversity assumed essential for bull trout population persistence. Quantifying this variability is important for modelling population dynamics and viability to conserve this threatened species.

Harris, Julianne E.↗
DOE OSTI2024

gcm_eval (Global Climate Model Evaluation) [SWR-24-37]

The interplay between energy, climate, and weather is becoming more complex as our changing climate continues to affect the weather we experience which in turn drives changes in the ever increasing share of renewable energy generation and energy demand. Energy system analyses commonly rely on meteorological inputs to estimate renewable energy generation and energy demand; however, these inputs rarely represent the estimated impacts of future climate change. Climate models and publicly available climate change datasets can be used for this purpose, but the selection of inputs from the myriad of available models and datasets is a nuanced and often subjective process. There is no single perfect climate model or dataset for all applications. In this repository, we include software and the corresponding assessments of various global climate models (GCMs) from the Coupled Model Intercomparison Project (CMIP6), evaluating their skills with respect to the historical climate and comparing of their future projections of climate change. We focus on variables that directly affect the energy system including the representation of extreme values that can drive grid resilience events. The objective of this repository is not to recommend the best climate model and dataset for a given analysis, but instead to provide a reference to facilitate the selection of climate models and datasets in subsequent work.

Buster, Grant↗
DOE OSTI2022

Effective properties of semitransparent radiative cooling materials with spectrally variable properties

Radiative cooling is a promising solid-state, non-vapor-compression technology for passive refrigeration and air conditioning. Although this phenomenon occurs naturally, achieving a significant amount of cooling to make it a technically and economically viable technology requires highly engineered, spectrally selective radiative surfaces. These characteristics make radiative cooling difficult to estimate, particularly when it is integrated with other systems such as photovoltaic panels or building envelopes. The complexity further increases when the substrate also participates in the radiative cooling (along with the radiative coating). Energy estimation is becoming increasingly critical because of the recent focus on the semitransparent radiative coatings that transmit a variety of colors to enhance the aesthetic appeal of the system. In this work, we propose an iterative method to calculate the effective radiative properties, which provides the same net radiative cooling that would be observed using the spectral properties at both the coating and substrate surfaces. Compared to traditional methods that rely on either computationally expensive full spectral analysis or methods for averaging each radiative surface parameter locally, our proposed method focuses on calculating effective properties that provide the same the net cooling effect as a full spectral analysis by accounting the emissivity, absorptivity, and transmissivity collectively, thereby providing an overall estimation error of less than 0.2%. We believe that this study will be beneficial to the engineering communities that employ complex simulation codes and require lumped solar and thermal radiation related parameters.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1994

Multidisciplinary design optimization using genetic algorithms

Multidisciplinary design optimization (MDO) is an important step in the conceptual design and evaluation of launch vehicles since it can have a significant impact on performance and life cycle cost. The objective is to search the system design space to determine values of design variables that optimize the performance characteristic subject to system constraints. Gradient-based optimization routines have been used extensively for aerospace design optimization. However, one limitation of gradient based optimizers is their need for gradient information. Therefore, design problems which include discrete variables can not be studied. Such problems are common in launch vehicle design. For example, the number of engines and material choices must be integer values or assume only a few discrete values. In this study, genetic algorithms are investigated as an approach to MDO problems involving discrete variables and discontinuous domains. Optimization by genetic algorithms (GA) uses a search procedure which is fundamentally different from those gradient based methods. Genetic algorithms seek to find good solutions in an efficient and timely manner rather than finding the best solution. GA are designed to mimic evolutionary selection. A population of candidate designs is evaluated at each iteration, and each individual's probability of reproduction (existence in the next generation) depends on its fitness value (related to the value of the objective function). Progress toward the optimum is achieved by the crossover and mutation operations. GA is attractive since it uses only objective function values in the search process, so gradient calculations are avoided. Hence, GA are able to deal with discrete variables. Studies report success in the use of GA for aircraft design optimization studies, trajectory analysis, space structure design and control systems design. In these studies reliable convergence was achieved, but the number of function evaluations was large compared with efficient gradient methods. Applicaiton of GA is underway for a cost optimization study for a launch-vehicle fuel-tank and structural design of a wing. The strengths and limitations of GA for launch vehicle design optimization is studied.

Unal, Resit↗
DOE OSTI2021

Effects of different vegetation drag parameterizations on the tidal propagation in coastal marshlands

Vegetation drag is a fundamental quantity directly affecting results for both long- and short-term coastal marsh and geomorphological studies. The vegetation drag in coastal marshland has been modeled by various two-dimensional (2D) and threedimensional (3D) numerical parameterizations. 2D parameterizations treat coastal marshes as bottom roughness elements, while 3D parameterizations resolve the vertically-variable vegetation drag through the water column. However, differences in tidal propagation arising from different drag parameterizations within a single model are largely unknown, and clear guidance on parameterization selection is still missing. In this study, we implemented four vegetation drag parameterizations into the Model for Prediction Across Scales-Ocean (MPAS-O), which include 1) a 2D parameterization using land-cover type-determined Manning’s n (2DLM); 2) a 2D parameterization using vegetation-determined Manning’s n (2DVM); 3) a 3D parameterization for stiff vegetation (3DSV); and 4) a 3D parameterization for flexible vegetation (3DFV). Estimates of the flow resistance effects from these parameterizations were compared using a series of idealized tidal propagation simulations. Given the same tidal condition, flooding depth and flooding distance are the largest in the 2DLM simulations and the smallest in the 3DSV simulations. 2DVM results are the closest to the 2DLM results. 3DFV results are the closest to the average of 2DVM, 3DSV, and 3DFV results. 2DVM and 3DSV results are the least and most sensitive to the vegetation aboveground biomass, respectively. Based on the input data requirement and computational efficiency of each parameterization, a comparison summary is provided to help inform parameterization selection for specific applications. Here, the effects of these parameterizations on coastal geomorphology are further discussed, and the results demonstrate that estimates of the long-term evolution of coastal marshes and coastal morphology depend upon the selection of the vegetation drag parameterization

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Metal–Ligand Cooperativity via Exchange Coupling Promotes Iron- Catalyzed Electrochemical CO 2 Reduction at Low Overpotentials

Biological and heterogeneous catalysts for the electrochemical CO 2 reduction reaction (CO 2 RR) often exhibit a high degree of electronic delocalization that serves to minimize overpotential and maximize selectivity over the hydrogen evolution reaction (HER). Here, we report a molecular iron(II) system that captures this design concept in a homogeneous setting through the use of a redox non-innocent terpyridine-based pentapyridine ligand (tpyPY2Me). As a result of strong metal-ligand exchange coupling between the Fe(II) center and ligand, [Fe(tpyPY2Me)] 2+ exhibits redox behavior at potentials 640 mV more positive than the isostructural [Zn(tpyPY2Me)] 2+ analog containing the redox-inactive Zn(II) ion. This shift in redox potential is attributed to the requirement for both an open-shell metal ion and a redox non-innocent ligand. The metal-ligand cooperativity in [Fe(tpyPY2Me)] 2+ drives the electrochemical reduction of CO 2 to CO at low overpotentials with high selectivity for CO 2 RR (>90%) and turnover frequencies of 100,000 s -1 with no degradation over 20 h. The decrease in the thermodynamic barrier engendered by this coupling also enables homogeneous CO 2 reduction catalysis in water without compromising selectivity or rates. Synthesis of the two-electron reduction product, [Fe(tpyPY2Me)] o , and characterization by X-ray crystallography, Mössbauer spectroscopy, X-ray absorption spectroscopy (XAS), variable temperature NMR, and density functional theory (DFT) calculations, support assignment of an open-shell singlet electronic structure that maintains a formal Fe(II) oxidation state with a doubly reduced ligand system. Furthermore, this work provides a starting point for the design of systems that exploit metal-ligand cooperativity for electrocatalysis where the electrochemical potential of redox non-innocent ligands can be tuned through secondary metal-dependent interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Assessing methods in fusion and fitting for time series construction in remote sensing-based earth observations

This study evaluates the comparative performance of spatiotemporal fusion and time-series fitting methods for constructing high-spatiotemporal-resolution remote sensing time-series data. Due to in-class similarity of fusion methods and fitting methods, we employ the Fit-FC (Fitting, spatial Filtering, and residual Compensation) model as a representative fusion method and the linear harmonic fitting model as a representative fitting method. Both Fit-FC and the linear harmonic fitting are widely used for high-spatiotemporal-resolution time-series data construction, and we modify the original Fit-FC model to enable automatic time-series fusion. To ensure data representativeness, we use 3 years (2019–2021) of Harmonized Landsat and Sentinel-2 surface reflectance datasets and Terra MCD43A4 products. Eight experimental regions are selected worldwide to guarantee generalization of the comparative performance between fusion and fitting methods, covering diverse land-use types (cropland, developed land, forest, and grassland) and varying climatological conditions. Time-series of NDVI and surface reflectance are analyzed under both actual observations and simulated data-missing scenarios. The constructed time-series data reveals that (1) the modified Fit-FC and linear harmonic fitting model achieve excellent performance in constructing high-resolution time-series images; (2) the fusion method outperforms the fitting method in constructing time-series of NDVI and surface reflectance images in cropland-, forest-, and grassland-dominated regions; (3) both methods achieve comparable performance in developed-dominated regions; (4) the fusion method is more robust to missing data, and better captures abrupt phenological transitions under conditions of continuous missing data; (5) the fitting method is computationally more efficient, making it suitable for large-scale time-series image reconstruction. This study provides valuable insights for selecting optimal strategies to generate high-resolution time-series images across diverse application scenarios and lays a foundation for extensions to other vegetation indices or land surface variables.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

SU-F-BRD-12: When Does Pencil Beam Scanning Become Superior to Passive Scattered Proton Therapy for Pediatric Head and Neck Cancers?

Purpose: To investigate the dosimetric benefits of pencil beam scanning (PBS) compared with passive scattered (PS) proton therapy for treatment of pediatric head&neck patients as a function of the PBS spot size and explore the advantages of using apertures in PBS. Methods: Ten pediatric patients with head&neck cancers treated by PS proton therapy at our institution were retrospectively selected. The histologies included rhabdomyosarcoma, ependymoma, astrocytoma, craniopharyngioma and germinoma. The prescribed dose ranged from 36 to 54 Gy(RBE). Five PBS plans were created for each patient using variable spot size (average sigma at isocenter) and choice of beam specific apertures: (1) 10mm spots, (2) 10mm spots with apertures, (3) 6mm spots, (4) 6mm spots with apertures, and (5) 3mm spots. The plans were optimized for intensity modulated proton therapy (IMPT) with no single beam uniformity constraints. Dose volume indices as well as equivalent uniform dose (EUD) were compared between PS and PBS plans. Results: Although target coverage was clinically adequate for all cases, the plans with largest (10mm) spots provide inferior quality compared with PS in terms of dose to organs-at-risk (OAR). However, adding apertures to these plans ensured lower OAR dose than PS. The average EUD difference between PBS and PS plans over all patients and organs at risk were (1) 2.5%, (2) −5.1%, (3) -5%, (4) −7.8%, and (5) −9.5%. As the spot size decreased, more conformal plans were achieved that offered similar target coverage but lower dose to the neighboring healthy organs, while alleviating the need for using apertures. Conclusion: The application of PBS does not always translate to better plan qualities compared to PS depending on the available beam spot size. We recommend that institutions with spot size larger than ∼6mm at isocenter consider using apertures to guarantee clinically comparable or superior dosimetric efficacy to PS treatments.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Building a Business Case for Compressed Natural Gas in Fleet Applications

VICE 2.0 is the second generation of the VICE financial model developed by the National Renewable Energy Laboratory for fleet managers to assess the financial soundness of converting their fleets to run on CNG. VICE 2.0 uses a number of variables for infrastructure and vehicles to estimate the business case for decision-makers when considering CNG as a vehicle fuel. Enhancements in version 2.0 include the ability to select the project type (vehicles and infrastructure or vehicle acquisitions only), and to decouple vehicle acquisition from the infrastructure investment, so the two investments may be made independently. Outputs now include graphical presentations of investment cash flow, payback period (simple and discounted), petroleum displacement (annual and cumulative), and annual greenhouse gas reductions. Also, the Vehicle Data are now built around several common conventionally fueled (gasoline and diesel) fleet vehicles. Descriptions of the various model sections and available inputs follow. Each description includes default values for the base-case business model, which was created so economic sensitivities can be investigated by altering various project parameters one at a time.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1974

Operations planning simulation: Model study

The use of simulation modeling for the identification of system sensitivities to internal and external forces and variables is discussed. The technique provides a means of exploring alternate system procedures and processes, so that these alternatives may be considered on a mutually comparative basis permitting the selection of a mode or modes of operation which have potential advantages to the system user and the operator. These advantages are measurements is system efficiency are: (1) the ability to meet specific schedules for operations, mission or mission readiness requirements or performance standards and (2) to accomplish the objectives within cost effective limits.

Source record↗
NASA NTRS1978

The role of drop velocity in statistical spray description

The justification for describing a spray by treating drop velocity as a random variable on an equal statistical basis with drop size was studied experimentally. A double exposure technique using fluorescent drop photography was used to make size and velocity measurements at selected locations in a steady ethanol spray formed by a swirl atomizer. The size velocity data were categorized to construct bivariate spray density functions to describe the spray immediately after formation and during downstream propagation. Bimodal density functions were formed by environmental interaction during downstream propagation. Large differences were also found between spatial mass density and mass flux size distribution at the same location.

Groeneweg, J. F.↗
NASA NTRS1980

Manned maneuvering unit latching mechanism

The astronaut/Manned Maneuvering Unit interface, which presented a challenging set of requirements for a latching mechanism, is described. A spring loaded cam segment with variable ratio pulley release actuator was developed to meet the requirements. To preclude jamming of the mechanism, special precautions were taken such as spring loaded bearing points and careful selection of materials to resist cold welding. The mechanism successfully passed a number of tests which partially simulated orbital conditions.

Allton, C. S.↗