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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

SU-F-T-158: Experimental Characterization of Field Size Dependence of Dose and Lateral Beam Profiles of Scanning Proton and Carbon Ion Beams for Empirical Model in Air

Purpose: The Gaussian model for the lateral profiles in air is crucial for an accurate treatment planning system. The field size dependence of dose and the lateral beam profiles of scanning proton and carbon ion beams are due mainly to particles undergoing multiple Coulomb scattering in the beam line components and secondary particles produced by nuclear interactions in the target, both of which depend upon the energy and species of the beam. In this work, lateral profile shape parameters were fitted to measurements of field size dependence dose at the center of field size in air. Methods: Previous studies have employed empirical fits to measured profile data to significantly reduce the QA time required for measurements. From this approach to derive the weight and sigma of lateral profiles in air, empirical model formulations were simulated for three selected energies for both proton and carbon beams. Results: The 20%–80% lateral penumbras predicted by the double model for proton and single model for carbon with the error functions agreed with the measurements within 1 mm. The standard deviation between measured and fitted field size dependence of dose for empirical model in air has a maximum accuracy of 0.74% for proton with double Gaussian, and of 0.57% for carbon with single Gaussian. Conclusion: We have demonstrated that the double Gaussian model of lateral beam profiles is significantly better than the single Gaussian model for proton while a single Gaussian model is sufficient for carbon. The empirical equation may be used to double check the separately obtained model that is currently used by the planning system. The empirical model in air for dose of spot scanning proton and carbon ion beams cannot be directly used for irregular shaped patient fields, but can be to provide reference values for clinical use and quality assurance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Oral delivery of a functional algal-expressed TGF-β mimic halts colitis in a murine DSS model

Inflammatory bowel disease (IBD) is a set of immunological disorders which can generate chronic pain and fatigue associated with the inflammatory symptoms. The treatment of IBD remains a significant hurdle with current therapies being only partially effective or having significant side effects, suggesting that new therapies that elicit different modes of action and delivery strategies are required. TGM1 is a TGF-β mimic that was discovered from the intestinal helminth parasite Heligmosomoides polygyrus and is thought to be produced by the parasite to suppress the intestinal inflammation response to help evade host immunity, making it an ideal candidate to be developed as a novel anti-inflammatory bio-therapeutic. Here we utilized the expression system of the edible green algae Chlamydomonas reinhardtii in order to recombinantly produce active TGM1 in a form that could be ingested. C. reinhardtii robustly expressed TGM1, and the resultant recombinant protein is biologically active as measured by regulatory T cell induction. When delivered orally to mice, the algal expressed TGM1 is able to ameliorate weight loss, lymphadenopathy, and disease symptoms in a mouse model of DSS-induced colitis, demonstrating the potential of this biologic as a novel treatment of IBD.

09 BIOMASS FUELS↗
NASA NTRS2012

Survey of Applications of Active Control Technology for Gust Alleviation and New Challenges for Lighter-weight Aircraft

This report provides a historical survey and assessment of the state of the art in the modeling and application of active control to aircraft encountering atmospheric disturbances in flight. Particular emphasis is placed on applications of active control technologies that enable weight reduction in aircraft by mitigating the effects of atmospheric disturbances. Based on what has been learned to date, recommendations are made for addressing gust alleviation on as the trend for more structurally efficient aircraft yields both lighter and more flexible aircraft. These lighter more flexible aircraft face two significant challenges reduced separation between rigid body and flexible modes, and increased sensitivity to gust encounters due to increased wing loading and improved lift to drag ratios. The primary audience of this paper is engineering professionals new to the area of gust load alleviation and interested in tackling the multifaceted challenges that lie ahead for lighter-weight aircraft.

Regan, Christopher D.↗
DOE OSTI2017

Optimal Energy Control of a Dual Fuel Vehicle Fuelled by Natural Gas and E10

Due to the increasing availability of natural gas, there is growing interest in using this fuel for transportation. Utilizing natural gas along with gasoline can provide a way to leverage the high knock resistance of natural gas while avoiding some of the ignitability challenges of this fuel. This paper leverages experimental data for a single cylinder engine to model power production on a mid-size sedan. Using this model, an optimal energy management strategy is explored. Several weighting strategies are considered including techniques which consider fuel availability, fuel cost, and carbon emissions. The effectiveness of these methods are considered over the UDDS, HWY, and US06 cycles. While there is little benefit to such a fuel blending algorithm at low loads, at high loads (such as those encountered in the US06 cycle) blending can provide up to a 7% improvement in efficiency.

Control and diagnosis of automotive systems↗
DOE OSTI2022

A fully Lagrangian, non-parametric bias model for dark matter halos

Here, we present a non-parametric Lagrangian biasing model and fit the ratio of the halo and mass densities at the field level using the mass-weighted halo field in the AbacusSummit simulations at z=0.5. Unlike the perturbative halo bias model that has been widely used in interpreting the observed large-scale structure traced by galaxies, we find a non-negative halo-to-mass ratio that increases monotonically with the linear overdensity δ 1 in the initial Lagrangian space. The bias expansion, however, does not guarantee non-negativity of the halo counts, and may lead to rising halo number counts at negative overdensities. The shape of the halo-to-mass ratio is unlikely to be described by a polynomial function of δ 1 and other quantities. Especially for massive halos with 6×10 12 h -1 M ⊙ , the halo-to-mass ratio starts soaring up at δ 1 >0, substantially different from the predictions of the bias expansion. We show that for the halo masses we consider (M>3×10 11 h -1 M ⊙ ) a non-parametric halo-to-mass ratio as a function of δ 1 and its local derivative ∇^2δ 1 can recover the halo power spectra to sub-percent level accuracy for wavenumbers k=0.01-0.1 h Mpc -1 given a proper smoothing scale to filter the initial density field, even though we do not fit the power spectrum directly. However, there is mild dependence of the recovery of the halo power spectrum on the smoothing scale and other input parameters. At k<0.01 h Mpc -1 and for massive halos with M>6x10 12 h -1 M ⊙ , our non-parametric model leads to a few percent overestimation of the halo power spectrum, indicating the need for larger or multiple smoothing scales. The halo-to-mass ratios obtained qualitatively agree with intuitions from extended Press-Schechter theory. We compare our framework to the bias expansion and discuss possible extensions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

County Level Annual Population Projections for SSP3 and SSP5

This dataset consist of annual (2020-2100) county-level population projections for the United States (U.S.) for Shared Socioeconomic Pathways (SSPs) 3 and 5. The original decadal state-level data is used as an input to the gridded population data model to downscale the state-level projections for each SSP to a 1 km grid. The 1 km data is then aggregated to the county-level using the 2020 TIGER/Line county shapefiles from the U.S. Census Bureau. The two data files are shared as .csv files with the following structure: Rows = Data for individual counties which are identified using their Federal Information Processing Standard (FIPS) code. The FIPS code is stored in the first column. Columns = Each year from 2020-2100 is an individual column. For easier reference, the state name associated with each row is stored in the last column. Values in each cell are the downscaled estimated population for that county-year combination. Values are fractional due to the weighting scheme used in the downscaling. The paper and model source code cited in the "Related Works" section describes the initial source of the population projections.

FIPS↗
DOE OSTI2021

Dietary Methionine Supplementation Exacerbates Gastrointestinal Toxicity in a Mouse Model of Abdominal Irradiation

Identification of appropriate dietary strategies for prevention of weight and muscle loss in cancer patients is crucial for successful treatment and prolonged patient survival. High-protein oral nutritional supplements decrease mortality and improve indices of nutritional status in cancer patients; however, high-protein diets are often rich in methionine, and experimental evidence indicates that a methionine-supplemented diet (MSD) exacerbates gastrointestinal toxicity after total body irradiation. Here, we sought to investigate whether MSD can exacerbate gastrointestinal toxicity after local abdominal irradiation, an exposure regimen more relevant to clinical settings.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

A Conceptual Model for the Response of Tropical Rainfall to Orbital Variations

Tropical rainfall to first order responds to variations in Earth’s orbit through shifts of the intertropical convergence zone (ITCZ) and changes in zonally averaged rainfall intensity. Here, a conceptual model is developed that represents both processes and their response to orbital insolation variations. The model predicts the seasonal evolution of tropical rainfall between 30°S and 30°N. Insolation variations impact seasonal rainfall in two different ways: thermodynamically, leading to variations in rainfall intensity through modulation of the water vapor content of the atmosphere; and dynamically, leading to shifts of the ITCZ through modulation of the global atmospheric energy budget. Thermodynamic and dynamic effects act together to shape the annual-mean response of tropical rainfall to changes in Earth’s orbit. The model successfully reproduces changes in annual-mean rainfall inferred from paleo-proxies across several glacial–interglacial cycles. It illuminates how orbital precession and variations of Earth’s obliquity affect tropical rainfall in distinct ways near the equator and farther away from it, with spectral signatures of precession and obliquity variations that shift with latitude. It also provides explanations for the observed different phasings of rainfall minima and maxima near the equator and away from it. For example, the model reproduces a phase shift of ~10 ka between rainfall records from caves in northern Borneo (4°N) and from China (approximately 30°N). Finally, the model suggests that such phase shifts arise through a different weighting of ITCZ shifts and variations in rainfall intensity, thus providing insight into the mechanisms that drive tropical rainfall changes on orbital time scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Radiation Modeling of Z1: Validation of a Novel Radioisotope System

This paper presents the development of a radiation model for a novel strontium-90 (Sr-90) radioisotope heat source developed by Zeno Power Systems (Zeno), which demonstrates a groundbreaking fuel and shielding design that significantly reduces weight compared to traditional concepts. A Monte Carlo N-Particle (MCNP) model has been created to assess the effectiveness of this fuel and shielding design, however validation of the MCNP model is desired. Zeno has developed a prototype device (Z1) to aid in this model validation effort. This project is a collaborative effort between Zeno, the University of Dayton Research Institute (UDRI) and Pacific Northwest National Laboratory (PNNL), where the Z1 prototype was constructed and characterized.

RTG↗
NASA NTRS2007

Applying MDA to SDR for Space to Model Real-time Issues

NASA space communications systems have the challenge of designing SDRs with highly-constrained Size, Weight and Power (SWaP) resources. A study is being conducted to assess the effectiveness of applying the MDA Platform-Independent Model (PIM) and one or more Platform-Specific Models (PSM) specifically to address NASA space domain real-time issues. This paper will summarize our experiences with applying MDA to SDR for Space to model real-time issues. Real-time issues to be examined, measured, and analyzed are: meeting waveform timing requirements and efficiently applying Real-time Operating System (RTOS) scheduling algorithms, applying safety control measures, and SWaP verification. Real-time waveform algorithms benchmarked with the worst case environment conditions under the heaviest workload will drive the SDR for Space real-time PSM design.

Blaser, Tammy M.↗
NASA NTRS2019

Comparison of Structural Concepts for Transport Aircraft with a Tail Cone Turbine

An evaluation of three structural concepts for an advanced aircraft design with a tail cone turbine is presented. Structural models were developed using an innovative rapid finite element modeling tool called Conceptual Design Shop (CDS). CDS is an attempt to fill a gap in current finite element modeling software to automatically connect wings and tails to the fuselage with sufficient support structure in airframe models. For comparison with actual aircraft structures, a model of a transport aircraft design developed using CDS is compared with published structural weight data for a Boeing 737-200. A method for computing aerodynamic stability parameters from an MSC/NASTRAN finite element analysis output deck is also discussed. Finally, the weight effects for using a tail cone turbine in an advanced transport aircraft design are evaluated by comparing three composite structural models, for which component thicknesses and cross-sections are sized by the Hypersizer software.

Mason, Brian H.↗
DOE OSTI2019

The Wave Energy Converter Control Competition: Overview

Over the past two years, a wave energy converter control systems competition (WECCCOMP) has been in progress, with the objective of comparing different wave energy converter (WEC) control paradigms on a standard benchmark problem. The target system is a point absorber, corresponding to a single float with an absolute reference, of the WaveStar WEC prototype. The system was modelled in WEC-Sim, with the hydrodynamic parameters validated against tank test data. Competitors were asked to design and implement a WEC control system for this model, with performance evaluated across six sea states. The evaluation criteria included a weighted combination of average converted power, peak/average power, and the degree to which the system physical constraints were exploited or temporarily exceeded.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Physics-constrained Deep Recurrent Neural Models of Building Thermal Dynamics

We develop physics-constrained and control-oriented predictive deep learning models for the thermal dynamics of a real-world commercial office building. The proposed method is based on the systematic encoding of physics-based prior knowledge into a structured recurrent neural architecture. Specifically, our model mimics the structure of the building thermal dynamics model and leverages penalty methods to model inequality constraints. Additionally, we use constrained matrix parameterization based on the Perron-Frobenius theorem to bound the eigenvalues of the learned network weights. We interpret the stable eigenvalues as dissipativeness of the learned building thermal model. We demonstrate the effectiveness of the proposed approach on a dataset obtained from an office building with $20$ thermal zones.

Building Energy, structured neural networks↗
NASA NTRSDate not supplied

Machine Learning Approach for Aircraft Performance Model Parameter Estimation for Trajectory Prediction Applications

Inaccurate prediction of aircraft trajectory by ground-based decision support tools (DST) is a major concern in air traffic management (ATM). Aircraft trajectory prediction tools rely on a simplified point-mass aircraft performance model (APM) to make their predictions. Even though the performance coefficients and weight of an aircraft are a vital part of the APM’s predictions and accuracy, these coefficients are proprietary in nature and therefore, unavailable to DSTs. Current ATM research focuses on improving the estimate of some APM parameters by freezing all other coefficients. This simplified approach introduces unwanted sources of bias and negatively impacts the accuracy of the performance model. In this paper, we apply machine learning (ML) techniques for the simultaneous prediction of three key APM parameters (two drag coefficients and the initial aircraft weight). To accomplish this, we employ an ordinary differential equation (ODE) fitting approach to generate optimized APM parameter labels customized to each individual flight record. Subsequently, we train ML models to capture the relationship between the historical data and the optimized APM parameters. Two different ML model solutions are applied and APM coefficients are predicted for unseen flights. The results indicate that the ML models are able to capture the relationship between APM parameters and flight-related features with good accuracy.

trajectory prediction, machine learning, aircraft ↗
DOE OSTI2024

Commentary: Duckweeds as model organisms for metabolic studies

Duckweeds have many practical applications, for example in human nutrition, as animal feed, in the production of bioplastics or vaccines, and phytoremediation (Acosta et al., 2021). Under most conditions, they reproduce asexually which provides genetically uniform material with predictable patterns of growth that make them ideal as sentinel organisms for phytotoxicity testing (Park et al., 2021). Asexual growth also results in high biomass production which makes duckweeds promising candidates as biofuel feedstocks (Acosta et al., 2021; Liang et al., 2023). In addition, duckweed species like Lemna minor and Spirodela polyrhiza are also reemerging as model organisms in plant biology as high-quality full genome assemblies and other genomic resources become available (Chang et al., 2016; Acosta et al., 2021). We argue that duckweed species are particularly of interest for the study of primary plant metabolism. Primary metabolism concerns the part of metabolism that is directly involved in the growth and development of plants, and which tends to be highly conserved among plant species. What makes duckweeds particularly attractive is that when grown on liquid media more precise control of physiological conditions can be attained relative to growth of plants in soil. Also, due to their relatively simple anatomical structure and asexual reproduction of fronds by budding, precise characterization of the physiological state under study is possible through one simple metric, i.e., the specific growth rate (rate of dry weight increase per existing dry weight), which can be incorporated relatively easily into metabolic models. This is not possible for land plants, such as Arabidopsis, because over the course of their life cycle, they go through multiple growth stages and phases of anatomical differentiation, which are much more complex to quantify. Furthermore, duckweeds can grow on organic substrates under heterotrophic or photomixotrophic conditions that facilitate isotope tracer studies. For example, in a previous study on duckweed by one of the authors, Lemna gibba (L). was grown on glucose with a position-specific 13 C-label that can be detected and resolved by Mass Spectrometry or Nuclear Magnetic Resonance spectrometry. Using this approach, the 13 C-label was traced into biomass compounds formed from glucose, particularly isoprenoid compounds. Some of the resulting labeling patterns were in apparent disagreement with predictions based on known metabolic pathways for the biosynthesis of isopentenyl pyrophosphate, the universal building block for isoprenoids, (Lichtenthaler et al., 1997). From this data it was deduced that isoprenoid compounds such as carotenoids and isoprenoid chains of phytol and plastoquinone, synthesized in the chloroplast, are produced via a previously unreported plant metabolic pathway, now known as the methylerythitol/deoxyxylulose-5-phosphate pathway (Lichtenthaler et al., 1997).

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1995

Stellar models with microscopic diffusion and rotational mixing. 1: Application to the Sun

The Yale stellar evolution code has been modified to include the combined effects of diffusion and rotational mixing on H-1, H-4, and the trace elements He, Li-6, Li-7, and Be-9. The interaction between rotational mixing and diffusion is studied by calculating a number of calibrated solar models. The rotational mixing inhibits the diffusion in the outer parts of the models, leading to a decrease in the envelope diffusion by 25%-50%. Conversely, diffusion leads to gradients in mean molecular weight which can inhibit the rotational mixing. The degree to which gradients in mean molecular weight inhibit the rotational mixing is somewhat uncertain. A comparison with the observed solar oblateness suggests that gradients in the mean molecular weight play a smaller role in inhibiting the rotational mixing than previously believed. This is reinforced by the fact that the model with the standard value for the inhibiting effect of mean molecular weight on the rotational mixing depletes no Li on the main sequence. This is clear in contrast to the observations. A reduction in the inhibiting effect of mean molecular weight gradients by a factor of 10 loads to noticeable main-sequence Li depletion.

Chaboyer, Brian↗
DOE OSTI2018

Communicating the Impacts of Projected Climate Change on Heavy Rainfall Using a Weighted Ensemble Approach

Urban flood risks are often determined by the frequency analysis of observed rainfall data, communicated using isohyetal maps showing rainfall totals for a range of durations and recurrence intervals. However, to assess future changes in heavy rainfall, it is necessary to study the future projected rainfall time series. Impacts of climate change are typically assessed using climate projections based on global climate model (GCM) outputs and downscaled to finer temporal and spatial scales. The projected data, however, are not generated in a format that urban planners and engineers can easily use to design for future conditions. This paper presents a method to analyze and express climate data in a format that can be readily used in hydrologic models to assess the effects of future extreme rainfall events. Future conditions’ climate data were analyzed using a weighted ensemble approach, which resulted in projected rainfall frequency estimates and their confidence limits. Two multimodel data sets were selected to illustrate this approach in Cook County, Illinois, which belongs to the Chicago metropolitan area. The first data set included statistical downscaling data based on the Intergovernmental Panel for Climate Change’s (IPCC) Coupled Model Intercomparison Project Phase 3 (CMIP3) data. The weighted ensemble analysis applied to this data set produced results that indicated significant increases in projected heavy rainfall. For example, for CMIP3 Scenario A2, for the late 21st century, the 100-year, 24-h rainfall in the northern parts of the county was 29% larger than the model-generated rainfall for the present time. Finally, for the same time horizon and scenario, the confidence interval based on projected data was 87% wider compared with that of the published source (NOAA Atlas 14), calculated using the past observed data. Also, equal-weight delta-corrected IPCC CMIP5-based dynamical downscaling data were applied to the same region for the mid-21st century, producing increases in heavy rainfall fairly similar to those of CMIP3.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Studies of transverse momentum dependent parton distributions and Bessel weighting

In this paper we present a new technique for analysis of transverse momentum dependent parton distribution functions, based on the Bessel weighting formalism. The procedure is applied to studies of the double longitudinal spin asymmetry in semi-inclusive deep inelastic scattering using a new dedicated Monte Carlo generator which includes quark intrinsic transverse momentum within the generalized parton model. Using a fully differential cross section for the process, the effect of four momentum conservation is analyzed using various input models for transverse momentum distributions and fragmentation functions. We observe a few percent systematic offset of the Bessel-weighted asymmetry obtained from Monte Carlo extraction compared to input model calculations, which is due to the limitations imposed by the energy and momentum conservation at the given energy/Q 2 . We find that the Bessel weighting technique provides a powerful and reliable tool to study the Fourier transform of TMDs with controlled systematics due to experimental acceptances and resolutions with different TMD model inputs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗