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At least 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

An Approximate Kalman Filter for Ocean Data Assimilation; An Example with an Idealized Gulf Stream Model

A practical method of data assimilation for use with large, nonlinear, ocean general circulation models is explored. A Kalman filter based on approximations of the state error covariance matrix is presented, employing a reduction of the effective model dimension, the error's asymptotic steady-state limit, and a time-invariant linearization of the dynamic model for the error integration. The approximations lead to dramatic computational savings in applying estimation theory to large complex systems. We examine the utility of the approximate filter in assimilating different measurement types using a twin experiment of an idealized Gulf Stream. A nonlinear primitive equation model of an unstable east-west jet is studied with a state dimension exceeding 170,000 elements. Assimilation of various pseudo measurements is examined, including velocity, density, and volume transport at localized arrays, and realistic distributions of satellite altimetry and acoustic tomography observations. Results are compared in terms of their effects on the accuracies of the estimation. The approximate filter is shown to outperform a previous study that used an empirical nudging scheme. The examples demonstrate that useful approximate estimation errors can be computed in a practical manner for general circulation models.

['Kalman↗
DOE OSTI2014

Simulation of Thermal Stratification in BWR Suppression Pools with One Dimensional Modeling Method

The suppression pool in a boiling water reactor (BWR) plant not only is the major heat sink within the containment system, but also provides the major emergency cooling water for the reactor core. In several accident scenarios, such as a loss-of-coolant accident and extended station blackout, thermal stratification tends to form in the pool after the initial rapid venting stage. Accurately predicting the pool stratification phenomenon is important because it affects the peak containment pressure; the pool temperature distribution also affects the NPSHa (available net positive suction head) and therefore the performance of the Emergency Core Cooling System and Reactor Core Isolation Cooling System pumps that draw cooling water back to the core. Current safety analysis codes use zero dimensional (0-D) lumped parameter models to calculate the energy and mass balance in the pool; therefore, they have large uncertainties in the prediction of scenarios in which stratification and mixing are important. While three-dimensional (3-D) computational fluid dynamics (CFD) methods can be used to analyze realistic 3-D configurations, these methods normally require very fine grid resolution to resolve thin substructures such as jets and wall boundaries, resulting in a long simulation time. For mixing in stably stratified large enclosures, the BMIX++ code (Berkeley mechanistic MIXing code in C++) has been developed to implement a highly efficient analysis method for stratification where the ambient fluid volume is represented by one-dimensional (1-D) transient partial differential equations and substructures (such as free or wall jets) are modeled with 1-D integral models. This allows very large reductions in computational effort compared to multi-dimensional CFD modeling. One heat-up experiment performed at the Finland POOLEX facility, which was designed to study phenomena relevant to Nordic design BWR suppression pool including thermal stratification and mixing, is used for validation. Comparisons between the BMIX++, GOTHIC, and CFD calculations against the POOLEX experimental data are discussed in detail.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Data-driven modeling to enhance municipal water demand estimates in response to dynamic climate conditions

Altered precipitation and temperature patterns from a changing climate will affect supply, demand, and overall municipal water system operations throughout the arid western U.S. While supply forecasts leverage hydrological models to connect climate influences with surface water availability, demand forecasts typically estimate water use independent of climate and other externalities. Stemming from an increased focus on seasonal water demand management, we use the Salt Lake City, Utah municipal water system as a test bed to assess model accuracy versus complexity trade-offs between simple climate-independent econometric-based models and complex climate-sensitive data-driven models to average to extreme wet and dry climate conditions—representative of a new climate normal. Here, the climate-independent model displayed low performance during extreme dry conditions with predictions exceeding 90% and 40% of the observed monthly and seasonal volumetric demands, respectively, which we attribute to insufficient model complexity. The climate-sensitive models displayed greater accuracy in all conditions, with an ordinary least squares model demonstrating a measurable reduction in prediction bias (3.4% vs. -27.3%) and RMSE (74.0 lpcd vs. 294 lpcd) compared to the climate-independent model. The climate-sensitive workflow increased model accuracy and characterized climate-demand interactions, demonstrating a novel tool to enhance water system management.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1996

Effects of Planetary Gear Ratio on Mean Service Life

Planetary gear transmissions are compact, high-power speed reductions which use parallel load paths. The range of possible reduction ratios is bounded from below and above by limits on the relative size of the planet gears. For a single plane transmission, the planet gear has no size at a ratio of two. As the ratio increases, so does the size of the planets relative to the sizes of the sun and ring. Which ratio is best for a planetary reduction can be resolved by studying a series of optimal designs. In this series, each design is obtained by maximizing the service life for a planetary with a fixed size, gear ratio, input speed power and materials. The planetary gear reduction service life is modeled as a function of the two-parameter Weibull distributed service lives of the bearings and gears in the reduction. Planet bearing life strongly influences the optimal reduction lives which point to an optimal planetary reduction ratio in the neighborhood of four to five.

Savage, M.↗
NASA NTRS2010

Fluidic Injection for Jet Noise Reduction

Investigations into fluidic injection for jet noise reduction began over 50 years ago. Studies have included water and air injection for the reduction of noise in scale model jets and jet engines and water injection for the reduction of excess overpressures on the Space Shuttle at lift-off. Injection systems have included high pressure microjets as well as larger scale injectors operating at pressures that can be achieved in real jet engines. An historical perspective highlighting noise reduction potential is presented for injection concepts investigated over the last 50 years. Results from recent investigations conducted at NASA are presented for supersonic and subsonic dual-stream jets. The noise reduction benefits achieved through fluidic contouring using an azimuthally controlled nozzle will be discussed.

Henderson, Brenda↗
DOE OSTI2024

Mixing and dilution controls on marine CO 2 removal using alkalinity enhancement

Marine CO 2 removal (CDR) using enhanced-alkalinity seawater discharge was simulated in the estuarine waters of the Salish Sea, Washington, US. The high-alkalinity seawater would be generated using bipolar membrane electrodialysis technology to remove acid and the alkaline stream returned to the sea. Response of the receiving waters was evaluated using a shoreline resolving hydrodynamic model with biogeochemistry, and carbonate chemistry. Two sites, and two deployment scales, each with enhanced TA of 2997 mmol m -3 and a pH of 9 were simulated. The effects on air-sea CO 2 flux and pH in the near-field as well as over the larger estuary wide domain were assessed. The large-scale deployment (addition of 164 Mmoles TA yr -1 ) in a small embayment (Sequim Bay, 12.5 km 2 ) resulted in removal of 2066 T of CO 2 (45% of total simulated) at rate of 3756 mmol m -2 yr -1 , higher than the 63 mmol m -2 yr -1 required globally to remove 1.0 GT CO 2 yr -1 . It also reduced acidity in the bay, ΔpH ≈ +0.1 pH units, an amount comparable to the historic impacts of anthropogenic acidification in the Salish Sea. The mixing and dilution of added TA with distance from the source results in reduced CDR rates such that comparable amount 2176 T CO 2 yr -1 was removed over >1000 fold larger area of the rest of the model domain. There is the potential for more removal occurring beyond the region modeled. The CDR from reduction of outgassing between October and May accounts for as much as 90% of total CDR simulated. Of the total, only 375 T CO 2 yr -1 (8%) was from the open shelf portion of the model domain. With shallow depths limiting vertical mixing, nearshore estuarine waters may provide a more rapid removal of CO 2 using alkalinity enhancement relative to deeper oceanic sites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Combination of Gold Nanoparticle-Conjugated Tumor Necrosis Factor-α and Radiation Therapy Results in a Synergistic Antitumor Response in Murine Carcinoma Models

Purpose: Although remarkable preclinical antitumor effects have been shown for tumor necrosis factor-α (TNF) alone and combined with radiation, its clinical use has been hindered by systemic dose-limiting toxicities. We investigated the physiological and antitumor effects of radiation therapy combined with the novel nanomedicine CYT-6091, a 27-nm average-diameter polyethylene glycol-TNF-coated gold nanoparticle, which recently passed through phase 1 trials. Methods and Materials: The physiologic and antitumor effects of single and fractionated radiation combined with CYT-6091 were studied in the murine 4T1 breast carcinoma and SCCVII head and neck tumor squamous cell carcinoma models. Results: In the 4T1 murine breast tumor model, we observed a significant reduction in the tumor interstitial fluid pressure (IFP) 24 hours after CYT-6091 alone and combined with a radiation dose of 12 Gy (P<.05 vs control). In contrast, radiation alone (12 Gy) had a negligible effect on the IFP. In the SCCVII head and neck tumor model, the baseline IFP was not markedly elevated, and little additional change occurred in the IFP after single-dose radiation or combined therapy (P>.05 vs control) despite extensive vascular damage observed. The IFP reduction in the 4T1 model was also associated with marked vascular damage and extravasation of red blood cells into the tumor interstitium. A sustained reduction in tumor cell density was observed in the combined therapy group compared with all other groups (P<.05). Finally, we observed a more than twofold delay in tumor growth when CYT-6091 was combined with a single 20-Gy radiation dose—notably, irrespective of the treatment sequence. Moreover, when hypofractionated radiation (12 Gy × 3) was applied with CYT-6091 treatment, a more than five-fold growth delay was observed in the combined treatment group of both tumor models and determined to be synergistic. Conclusions: Our results have demonstrated that TNF-labeled gold nanoparticles combined with single or fractionated high-dose radiation therapy is effective in reducing IFP and tumor growth and shows promise for clinical translation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Machine learning-based ethylene concentration estimation, real-time optimization and feedback control of an experimental electrochemical reactor

With the increase in electricity supply from clean energy sources, electrochemical reduction of carbon dioxide (CO 2 ) has received increasing attention as an alternative source of carbon-based fuels. As CO 2 reduction is becoming a stronger alternative for the clean production of chemicals, the need to model, optimize and control the electrochemical reduction of the CO 2 process becomes inevitable. However, on one hand, a first-principles model to represent the electrochemical CO 2 reduction has not been fully developed yet because of the complexity of its reaction mechanism, which makes it challenging to define a precise state-space model for the control system. On the other hand, the unavailability of efficient concentration measurement sensors continues to challenge our ability to develop feedback control systems. Gas chromatography (GC) is the most common equipment for monitoring the gas product composition, but it requires a period of time to analyze the sample, which means that GC can provide only delayed measurements during the operation. Moreover, the electrochemical CO 2 reduction process is catalyzed by a fast-deactivating copper catalyst and undergoes a selectivity shift from the product-of-interest at the later stages of experiments, which can pose a challenge for conventional control methods. To this end, machine learning (ML) techniques provide a potential approach to overcome those difficulties due to their demonstrated ability to capture the dynamic behavior of a chemical process from data. Motivated by the above considerations, we propose a machine learning-based modeling methodology that integrates support vector regression and first-principles modeling to capture the dynamic behavior of an experimental electrochemical reactor; this model, together with limited gas chromatography measurements, is employed to predict the evolution of gas-phase ethylene concentration. The model prediction is directly used in a proportional-integral (PI) controller that manipulates the applied potential to regulate the gas-phase ethylene concentration at energy-optimal set-point values computed by a real-time process optimizer (RTO). Specifically, the RTO calculates the operation set-point by solving an optimization problem to maximize the economic benefit of the reactor. Finally, suitable compensation methods are introduced to further account for the experimental uncertainties and handle catalyst deactivation. The proposed modeling, optimization, and control approaches are the first demonstration of active control for a CO 2 electrolyzer and contribute to the automation and scale-up efforts for electrified manufacturing of fuels and chemicals starting from CO 2 .

42 ENGINEERING↗
NASA NTRS1989

Markov reliability models for digital flight control systems

The reliability of digital flight control systems can often be accurately predicted using Markov chain models. The cost of numerical solution depends on a model's size and stiffness. Acyclic Markov models, a useful special case, are particularly amenable to efficient numerical solution. Even in the general case, instantaneous coverage approximation allows the reduction of some cyclic models to more readily solvable acyclic models. After considering the solution of single-phase models, the discussion is extended to phased-mission models. Phased-mission reliability models are classified based on the state restoration behavior that occurs between mission phases. As an economical approach for the solution of such models, the mean failure rate solution method is introduced. A numerical example is used to show the influence of fault-model parameters and interphase behavior on system unreliability.

Mcgough, John↗
NASA NTRS1998

Effects of Planetary Speed Reduction Ratio on Mean Service Life

Planetary gear transmissions are compact speed reductions which use parallel-load paths to transmit high power. The range of possible reduction ratios is bounded from below and above by limits on the relative size of the planet gears. For a single plane planetary transmission, the speed-reduction ratio must be greater than two for planet gears to exist. As the ratio increase, so does the size of the planets relative to the sizes of the sun and ring. Which ratio is best for a planetary reduction can be resolved by studying a series of optimal designs. In this series, each design is obtained by maximizing the service life for a spur-gear planetary with a fixed size, speed reduction ratio, input speed, power and materials. The planetary gear reduction service life is modeled as a function of the two-parameter Weibull distributed service lives of the ball bearings and spur gears in the reduction. Planet-bearing life strongly influences the optimal reduction lives which point to an optimal planetary reduction ratio in the neighborhood of four to five.

Savage, M.↗
NASA NTRS1998

Effects of Planetary Speed-Reduction Ratio on Mean Service Life

Planetary-gear transmissions are compact speed reductions which use parallel-load paths to transmit high power. The range of possible reduction ratios is bounded from below and above by limits on the relative size of the planet gears. For a single-plane planetary transmission, the speed-reduction ratio must be greater than two for planet gears to exist. As the ratio increases, so does the size of the planets relative to the sizes of the sun and ring. Which ratio is best for a planetary reduction can be resolved by studying a series of optimal designs. In this series, each design is obtained by maximizing the service life for a spur-gear planetary with a fixed size, speed-reduction ratio, input speed, power and materials. The planetary-gear reduction service life is modeled as a function of the two-parameter Weibull distributed service lives of the ball bearings and spur gears in the reduction. Planet-bearing life strongly influences the optimal reduction lives which point to an optimal planetary reduction ratio in the neighborhood of four to five.

Savage, M.↗
DOE OSTI2015

An Analysis of the Temperature and Field Dependence of the RF Surface Resistance of Nitrogen-Doped Niobium SRF Cavities with Respect to Existing Theoretical Models

Recent progress with the reduction of rf surface resistance (R s ) of niobium SRF cavities via the use of high temperature surface doping by nitrogen has opened a new regime for energy efficient accelerator applications. For particular doping conditions one observes dramatic decreases in R s with increasing surface magnetic fields. The observed variations as a function of temperature may be analyzed in the context of recent theoretical treatments in hopes of gaining insight into the underlying beneficial mechanism of the nitrogen treatment. Systematic data sets of Q 0 vs. E acc vs. temperature acquired during the high Q 0 R&D work of the past year will be compared with theoretical model predictions..

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Fast Response of East Asian Precipitation in June 2020 to Local and Remote Aerosol Emission Reductions during COVID-19

Here, in this study, the fast response of East Asian summer precipitation to COVID-19–induced aerosol emission reductions is examined using the Community Earth System Model, version 2.2 (CESM2.2). The emission reductions decreased aerosol optical depth and cloud cover over northern China in June 2020. The troposphere became warmer, strengthening the land–sea thermal contrast and anomalous southerly winds. The subtropical westerly jet accelerated and shifted southward, favoring low-level convergence, upward air motions, and subsequent condensational heating over the Yangtze River basin (YRB). The feedback of condensational heating in return strengthened the convergence and ascent. The western North Pacific subtropical high was intensified, which further enhanced the moisture advection and convergence over the YRB. Both the enhanced moisture convergence and ascent increased precipitation over the YRB during June 2020. Furthermore, local and remote emission reductions show different impacts on convection and moisture transport over the YRB. The emission reductions over China caused stronger convective precipitation (1.15 vs 0.63 mm day −1 ) but weaker larger-scale precipitation (1.17 vs 2.24 mm day −1 ) than the emission reductions outside China. In addition to the emission reductions, the sea surface temperature (SST) anomalies in 2020 also play an important role in increasing precipitation over the YRB, contributing about 42.8%. The relative contribution of SST anomalies also increases under the COVID-19–induced emission scenario.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Effects of temperature and carbon source on the isotopic fractionations associated with O 2 respiration for 17 O/ 16 O and 18 O/ 16 O ratios in E. coli

18 O/ 16 O and 17 O/ 16 O ratios of atmospheric and dissolved oceanic O 2 are used as biogeochemical tracers of photosynthesis and respiration. Critical to this approach is a quantitative understanding of the isotopic fractionations associated with production, consumption, and transport of O 2 in the ocean both at the surface and at depth. We made measurements of isotopic fractionations associated with O 2 respiration by E. coli . Our study included wild-type strains and mutants with only a single respiratory O 2 reductase in their electron transport chains (either a heme-copper oxygen reductase or a bd oxygen reductase). We tested two common assumptions made in interpretations of O 2 isotope variations and in isotope-enabled models of the O 2 cycle: (i) laboratory-measured respiratory 18 O/ 16 O isotopic fractionation factors ( 18 α) of microorganisms are independent of environmental and experimental conditions including temperature, carbon source, and growth rate; And ( ii ) the respiratory ‘mass law’ exponent, θ, between 18 O/ 16 O and 17 O/ 16 O, 17α = ( 18 α) θ , is universal for aerobic respiration. Results demonstrated that experimental temperatures have an effect on both 18α and θ for aerobic respiration. Specifically, lowering temperatures from 37 to 15 °C decreased the absolute magnitude of 18 α by 0.0025 (2.5‰), and caused the mass law slope to decrease by 0.005. We propose a possible biochemical basis for these variations using a model of O 2 reduction that incorporates two isotopically discriminating steps: the reversible binding and unbinding of O 2 to a terminal reductase, and the irreversible reduction of that O 2 to water. In conclusion, we cast our results in a one-dimensional isopycnal reaction-advection-diffusion model, which demonstrates that enigmatic δ 18 O and Δ 17 O variations of dissolved O 2 in the dark ocean can be understood by invoking the observed temperature dependence of these isotope effects.

58 GEOSCIENCES↗
DOE OSTI2013

Quantifying the Sigma and Pi interactions between U(V) f orbitals and halide, alkyl, alkoxide, amide and ketimide ligands

f Orbital bonding in actinide and lanthanide complexes is critical to their behavior in a variety of areas from separations to magnetic properties. Octahedral f1 hexahalide complexes have been extensively used to study f orbital bonding due to their simple electronic structure and extensive spectroscopic characterization. The recent expansion of this family to include alkyl, alkoxide, amide, and ketimide ligands presents the opportunity to extend this study to a wider variety of ligands. To better understand f orbital bonding in these complexes, the existing molecular orbital (MO) model was refined to include the effect of covalency on spin orbit coupling in addition to its effect on orbital angular momentum (orbital reduction). The new MO model as well as the existing MO model and the crystal field (CF) model were applied to the octahedral f1 complexes to determine the covalency and strengths of the ? and ? bonds formed by the f orbitals. When covalency is significant, MO models more precisely determined the strengths of the bonds derived from the f orbitals; however, when covalency was small, the CF model was better than either MO model. The covalency determined using the new MO model is in better agreement with both experiment and theory than that predicted by the existing MO model. The results emphasize the role played by the orbital energy in determining the strength and covalency of bonds formed by the f orbitals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗