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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Controlling Mass Transport in Direct Carbon Dioxide Zero-Gap Electrolyzers via Cell Compression

The development of high-performance CO 2 electrolyzers is crucial for accelerating the sustainable production of fuels and chemicals integrated with renewable energy sources. Here, we introduce a methodology to actively control mass transport inside a realistic zero-gap membrane electrode assembly of a CO 2 electrolyzer by varying the gasket thickness, which consequently changes the cell compression. This allows control over the thickness and porosity of the gas diffusion electrodes, influencing the overall electrolyzer performance, as demonstrated using Ag-deposited electrodes. At low operating voltages (<2.9 V), both high- and low-compression electrolyzers exhibit similar faradaic efficiencies and partial current densities for CO formation. However, at high voltages, the low-compression electrolyzer with high electrode porosity demonstrates superior CO selectivity and activity with suppressed H 2 formation. These experimental results are validated by the computational membrane electrode assembly (MEA) model developed by using the measured in situ electrode thicknesses and electrode porosities. Additionally, liquid electrolyte saturation at the catalyst layer is found to play a dominant role in determining the mass transport, resulting in a decreased electrolyzer performance with low electrode porosity. Finally, the systematic investigation in this study improves the understanding of the transport dynamics in MEA-based devices and provides insights into optimizing device design parameters for industry-relevant CO 2 electrolysis.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Co-Benefits of Mitigating Aerosol Pollution to Future Solar and Wind Energy in China Toward Carbon Neutrality

The climate commitment to achieving carbon neutrality before 2060 in China has been announced recently. In the context of pursuing carbon neutrality, sharing similar sources as greenhouse gases, aerosol particle and precursor emissions are projected to substantially decrease in China, which can potentially have a great impact on climate. Here, we investigate the effects of future aerosol reductions, because of achieving carbon neutrality, on solar and wind energy in China by using an earth system model. We show that significant reductions in aerosol emissions, particularly in eastern China, lead to increases in the surface downwelling shortwave radiation, surface air temperature and wind speed, which can further enhance the potential of solar and wind energy production. The findings underline that the pursuit of carbon neutrality can yield co-benefits of not only mitigating climate change and air pollution but also fortifying the stability of renewable energy sources.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

HIBP Applications to Advance Understanding of Plasma Transport Physics (2011-2017) (and subsequently titled) Development of Beam Measurements to Advance Understanding of Transients and Improve Validation (2017-2020) (Final Technical Report)

This is the Final Technical Report for the DoE Measurement Innovation (previously Diagnostic Development) grant DE-SC0006077 titled HIBP Applications to Advance Understanding of Plasma Transport Physics (2011-2017), and subsequently titled Development of Beam Measurements to Advance Understanding of Transients and Improve Validation (2017-2020). The grant was funded by the Office of Fusion Energy Sciences (FES) for the period 1 May 2011–17 July 2020. Work performed through the grant has resulted in diagnostic innovations and new measurement capabilities that will improve understanding of transport, magnetic equilibrium, and electric fields in magnetically confined plasmas. We have developed novel hardware and advanced techniques to expand beam-based diagnostic capabilities, and extend measurements to new operating regimes. Some have been realized using a Heavy Ion Beam Probe (HIBP) having traditional features, while other applications have joined our innovations with subsets of advantageous HIBP features. This work has established smaller, more economical detection systems and, in doing so, may enable substantial extension of scenarios in which beam-based diagnostics are deployed. Key Measurement Innovations include: Computer Models and Simulations of HIBP Applications-Computer modeling and simulating of HIBP applications is central to predicting interaction of beam particles with plasmas, designing diagnostic systems, and anticipating measurement characteristics. We have extended the capability and improved measurement fidelity of the HIBP diagnostic on the Madison Symmetric Torus (MST) reversed field pinch (RFP); simulated feasibility of HIBP operation in the Helically Symmetric eXperiment (HSX) optimized stellarator; and investigated the plausibility of HIBP measurements in the ASDEX Upgrade tokamak. We have also developed a new technique that uses ion optics to model a finite phase-space beam. It yields more realistic (than traditional method) estimates of sample volume characteristics, which influence measurement resolution and sensitivity. Extension of Diagnostic Capabilities and Measurements on the MST RFP-Capabilities have been extended using the first and only HIBP installation on an RFP. Challenges associated with operation of the diagnostic on MST include the three-dimensional nature of particle trajectories, temporal topology and amplitude changes in the plasma equilibrium, and strong particle and radiative emission from the plasma. We have addressed these challenges through development of detailed and higher precision diagnostic simulations, calibrated subtraction of noise to resolve secondary ion signals, and implementation of hardware that enables higher fidelity measurement of plasma fluctuations. Development of New Hardware and Measurement Techniques - We have advanced beam-based measurement capabilities via development of new detectors and techniques to determine the poloidal magnetic flux ψ in the plasma, and enable placement of detectors close to the plasma and thus allow a smaller and less expensive diagnostic. We have demonstrated measurement of ψ, an ability that was made possible by development of highly effective noise reduction techniques. We also modeled the effect of non-ideal and instrumentation effects by developing a virtual (simulated) diagnostic. Application of beam-based diagnostics on various devices and multiple magnetic configurations (e.g. stellarator, tokamak, and reversed field pinch) enables investigation of critical physics issues and measurements resulting in the broad parameter space data needed to test and validate theory & modeling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

A consistent and conservative Phase-Field method for multiphase incompressible flows

In the present study, a consistent and conservative Phase-Field method, including both the model and scheme, is developed for multiphase flows with an arbitrary number of immiscible and incompressible fluid phases. The consistency of mass conservation and the consistency of mass and momentum transport are implemented to address the issue of physically coupling the Phase-Field equation, which locates different phases, to the hydrodynamics. These two consistency conditions, as illustrated, provide the “optimal” coupling because (i) the new momentum equation resulting from them is Galilean invariant and implies the kinetic energy conservation, regardless of the details of the Phase-Field equation, and (ii) failures of satisfying the second law of thermodynamics or the consistency of reduction of the multiphase flow model only result from the same failures of the Phase-Field equation but are not due to the new momentum equation. Physical interpretation of the consistency conditions and their formulations are first provided, and general formulations that are obtained from the consistency conditions and independent of the interpretation of the velocity are summarized. Then, the present consistent and conservative multiphase flow model is completed by selecting a reduction consistent Phase-Field equation. Several novel techniques are developed to inherit the physical properties of the multiphase flows after discretization, including the gradient-based phase selection procedure, the momentum conservative method for the surface force, and the general theorems to preserve the consistency conditions on the discrete level. Equipped with those novel techniques, a consistent and conservative scheme for the present multiphase flow model is developed and analyzed. The scheme satisfies the consistency conditions, conserves the mass and momentum, and assures the summation of the volume fractions to be unity, on the fully discrete level and for an arbitrary number of phases. All those properties are numerically validated. Finally, numerical applications demonstrate that the present model and scheme are robust and effective in studying complicated multiphase dynamics, especially for those with large-density ratios.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

WE-AB-207A-01: BEST IN PHYSICS (IMAGING): High-Resolution Cone-Beam CT of the Extremities and Cancellous Bone Architecture with a CMOS Detector

Purpose: Extremity cone-beam CT (CBCT) with an amorphous silicon (aSi) flat-panel detector (FPD) provides low-dose volumetric imaging with high spatial resolution. We investigate the performance of the newer complementary metal-oxide semiconductor (CMOS) detectors to enhance resolution of extremities CBCT to ∼0.1 mm, enabling morphological analysis of trabecular bone. Quantitative in-vivo imaging of bone microarchitecture could present an important advance for osteoporosis and osteoarthritis diagnosis and therapy assessment. Methods: Cascaded systems models of CMOS- and FPD-based extremities CBCT were implemented. Performance was compared for a range of pixel sizes (0.05–0.4 mm), focal spot sizes (0.3–0.6 FS), and x-ray techniques (0.05–0.8 mAs/projection) using detectability of high-, low-, and all-frequency tasks for a nonprewhitening observer. Test-bench implementation of CMOS-based extremity CBCT involved a Teledyne DALSA Xineos3030HR detector with 0.099 mm pixels and a compact rotating anode x-ray source with 0.3 FS (IMD RTM37). Metrics of bone morphology obtained using CMOS-based CBCT were compared in cadaveric specimens to FPD-based system using a Varian PaxScan4030 (0.194 mm pixels). Results: Finer pixel size and reduced electronic noise for CMOS (136 e compared to 2000 e for FPD) resulted in ∼1.9× increase in detectability for high-frequency tasks and ∼1.1× increase for all-frequency tasks. Incorporation of the new x-ray source with reduced focal spot size (0.3 FS vs. 0.5 FS used on current extremities CBCT) improved detectability for CMOS-based CBCT by ∼1.7× for high-frequency tasks. Compared to FPD CBCT, the CMOS detector yielded improved agreement with micro-CT in measurements of trabecular thickness (∼1.7× reduction in relative error), bone volume (∼1.5× reduction), and trabecular spacing (∼3.5× reduction). Conclusion: Imaging performance modelling and experimentation indicate substantial improvements for high-frequency imaging tasks through adoption of the CMOS detector and small FS x-ray source, motivating the use of these components in a new system for quantitative in-vivo imaging of trabecular bone. Financial Support: US NIH grant R01EB018896. Qian Cao is a Howard Hughes Medical Institute International Student Research Fellow. Disclosures: W Zbijewski, J Siewerdsen and A Sisniega receive research funding from Carestream Health.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Molecular characterization of AID-mediated reduction of hepatitis B virus transcripts

Hepatitis B virus (HBV) is the major cause of liver cirrhosis and hepatocellular carcinoma. After entering a hepatocyte, HBV forms a nuclear viral episome and produces pregenomic (pg) RNA with a stem–loop structure called an epsilon, which acts to signal encapsidation. We previously demonstrated that TGF-β upregulates activation-induced cytidine deaminase (AID) expression in hepatocytes, which in turn downregulates HBV transcripts by recruiting the RNA exosome complex. The molecular mechanism underlying AID-mediated HBV RNA reduction remains largely unclear. Here we used a pgRNA reporter system having a reporter gene within pgRNA to identify sis- and trans-acting elements in AID-mediated HBV RNA reduction. We found that the epsilon RNA and C-terminus of AID are required for AID-mediated HBV RNA reduction. Importantly, this reduction was reproduced in a hydrodynamic HBV transfection mouse model. The molecular mechanism of AID-mediated HBV RNA reduction is discussed. - Highlights: • AID-mediated HBV RNA reduction both in a cell line and in a HBV mouse model. • C-terminus of P protein/AID is essential for HBV RNA reduction by AID. • Epsilon RNA structure is required for AID-mediated HBV RNA reduction.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Non‐Linear Dimensionality Reduction With a Variational Encoder Decoder to Understand Convective Processes in Climate Models

Abstract Deep learning can accurately represent sub‐grid‐scale convective processes in climate models, learning from high resolution simulations. However, deep learning methods usually lack interpretability due to large internal dimensionality, resulting in reduced trustworthiness in these methods. Here, we use Variational Encoder Decoder structures (VED), a non‐linear dimensionality reduction technique, to learn and understand convective processes in an aquaplanet superparameterized climate model simulation, where deep convective processes are simulated explicitly. We show that similar to previous deep learning studies based on feed‐forward neural nets, the VED is capable of learning and accurately reproducing convective processes. In contrast to past work, we show this can be achieved by compressing the original information into only five latent nodes. As a result, the VED can be used to understand convective processes and delineate modes of convection through the exploration of its latent dimensions. A close investigation of the latent space enables the identification of different convective regimes: (a) stable conditions are clearly distinguished from deep convection with low outgoing longwave radiation and strong precipitation; (b) high optically thin cirrus‐like clouds are separated from low optically thick cumulus clouds; and (c) shallow convective processes are associated with large‐scale moisture content and surface diabatic heating. Our results demonstrate that VEDs can accurately represent convective processes in climate models, while enabling interpretability and better understanding of sub‐grid‐scale physical processes, paving the way to increasingly interpretable machine learning parameterizations with promising generative properties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Reducing uncertainty of polar to midlatitude linkages using DOE’s E3SM in a coordinated model-experiment setting

This project brought DOE’s climate modeling effort with the Energy Exascale Earth System Model into the Polar Amplification Model Intercomparison Project (PAMIP), which is part of the sixth and latest Coupled Model Intercomparison Project, CMIP6. PAMIP examines the causes and consequences of polar amplification, when external forcing results in a larger temperature increase in high latitudes than the global average, in a coordinated set of model experiments with a common modeling protocol. Our teams from UC Irvine and the University of Toronto have designed, carried out, analyzed, and disseminated PAMIP output from the Energy Exascale Earth System Model (E3SM) and the Community Earth System Model (CESM). PAMIP’s ongoing stream of significant new results have advanced progress in the community’s understanding and led to new outstanding research questions that have motivated further work. PAMIP has led to improved consensus on the atmospheric response to sea ice loss. The important finding is that for a similar sea ice anomaly forcing, the simulated atmospheric response in the troposphere is remarkably consistent among the 16 models’ runs analyzed. The zonal-mean tropospheric response consists of a very robust equatorward shift of the westerly flow in mid-latitudes. However, while the multi-model mean response is robust, it has a weak amplitude relative to internal variability. We identified a weakness in the models (including E3SM) in terms of their response to sea-ice forcing that is related to eddy forcing (or nonlinear dynamical effects) at mid- to high latitudes. In fact, E3SM is an outlier in terms of the models participating, and in that sense, it turned out to be a vital participant model. We found that reductions in energy transport due sea-ice loss and involving dry air only are compensated by increases in moist energy transport from warmer sea surface temperature in midlatitudes. This leads to a large spread in energy transport into the Arctic and is a potential source of spread in Arctic amplification. We identified an important role that climate modes, including tropical modes of variability (El Nino and the Southern Oscillation (ENSO); the Quasi-biennial Oscillation (QBO)) play in the response to sea-ice anomalies, including in ocean coupled experiments. Similarly, we identified and quantified the contribution of sea-ice thickness to the atmospheric response compared to the response to sea-ice extent only. We found that it is important to run large ensembles and even with an ensemble size of 100 simulations the response is largely influenced by internal variability. We demonstrated convincingly that Ural blocking, not sea-ice loss, provides the weakening of the stratospheric polar vortex in fall/early winter and a negative phase of the North Atlantic Oscillation that can last for up to two months. However, sea-ice anomalies can influence the background flow so that the response to Ural blocking is more persistent under low sea-ice conditions in the Barents/Kara Sea than high sea ice Atmospheric model hierarchies that progressively add individual processes have a long history in providing dynamical insight for modeling the atmosphere. Similarly, coupled model hierarchies that progressively add individual ocean processes can provide insights into the workings of the coupled climate system, however such hierarchies have not been available except for a non-dynamical slab ocean model. Because of the missing processes, surface flux corrections must be added to produce a target climate. In this project, we managed to overcome this problem and develop a globally coupled ocean model hierarchy in CESM that can turn on and off the processes of mixed-layer entrainment and Ekman flow. We used the hierarchy to study the impact of Arctic sea-ice loss on the climate system. We find that the effect of mixed-layer entrainment on ocean heat uptake influences the atmospheric circulation by shifting the latitudinal positions of the mid-latitude westerly jet and the Intertropical Convergence Zone (ITCZ). In quadrupled CO 2 experiments, we studied how air-sea coupling affects the response of tropical rainfall under global warming. In order to identify the importance of individual ocean processes, we used the hierarchy of ocean models to separate the effects of seasonal mixed-layer entrainment, wind-driven Ekman flows, and frictional flows. We showed that including Ekman and frictional flows allows our simulation to produce the Pacific Ocean's enhanced equatorial warming pattern and equatorward ITCZ contraction noted in previous climate simulations. We also showed that the frictional flow, which has yet to receive much attention, is as important as the Ekman flow in generating equatorial heat convergence.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2022

Future Climate Change Under SSP Emission Scenarios with GISS-E2.1

This paper presents the response to anthropogenic forcing in the GISS-E2.1 climate models for the 21st century Shared Socioeconomic Pathways emission scenarios within the Coupled Model Intercomparison Project Phase 6 (CMIP6). The experiments were performed using an updated and improved version of the NASA Goddard Institute for Space Studies (GISS) coupled general circulation model that includes two different versions for atmospheric composition: A non-interactive version (NINT) with prescribed composition and a tuned aerosol indirect effect and the One-Moment Aerosol model (OMA) version with fully interactive aerosols which includes a parameterized first indirect aerosol effect on clouds. The effective climate sensitivities are 3.0°C and 2.9°C for the NINT and OMA models, respectively. Each atmospheric version is coupled to two different ocean general circulation models: The GISS ocean model (E2.1-G) and HYCOM (E2.1-H). We describe the global mean responses for all future scenarios and spatial patterns of change for surface air temperature and precipitation for four of the marker scenarios: SSP1-2.6, SSP2-4.5, SSP4-6.0, and SSP5-8.5. By 2100, global mean warming ranges from 1.5°C to 5.2°C relative to 1,850–1,880 mean temperature. Two high-mitigation scenarios SSP1-1.9 and SSP1-2.6 limit the surface warming to below 2°C by the end of the 21st century, except for the NINT E2.1-H model that simulates 2.2°C of surface warming. For the high emission scenario SSP5-8.5, the range is 4.6–5.2°C at 2100. Due to about 15% larger effective climate sensitivity and stronger transient climate response in both NINT and OMA CMIP6 models compared to CMIP5 versions, there is a stronger warming by 2100 in the SSP emission scenarios than in the comparable Representative Concentration Pathway (RCP) scenarios in CMIP5. Changes in sea ice area are highly correlated to global mean surface air temperature anomalies and show steep declines in both hemispheres, with the largest sea ice area decreases occurring during September in the Northern Hemisphere in both E2.1-G (−1.21 × 106 km2/°C) and E2.1-H models (−0.94 × 106 km2/°C). Both coupled models project decreases in the Atlantic overturning stream function by 2100. The largest decrease of 56%–65% in the 21st century overturning stream function is produced in the warmest scenario SSP5-8.5 in the E2.1-G model, comparable to the reduction in the corresponding CMIP5 GISS-E2 RCP8.5 simulation. Both low-end scenarios SSP1-1.9 and SSP1-2.6 also simulate substantial reductions of the overturning (9%–37%) with slow recovery of about 10% by the end of the 21st century (relative to the maximum decrease at the middle of the 21st century).

climate models↗
DOE OSTI2025

MOOSE ProbML: Parallelized probabilistic machine learning and uncertainty quantification for computational energy applications

Here, this paper presents the development and demonstration of massively parallel probabilistic machine learning (ML) and uncertainty quantification (UQ) capabilities within the Multiphysics Object-Oriented Simulation Environment (MOOSE), an open-source computational platform for parallel finite element and finite volume analyses. In addressing the computational expense and uncertainties inherent in complex multiphysics simulations, this paper integrates Gaussian process (GP) variants, active learning, Bayesian inverse UQ, adaptive forward UQ, Bayesian optimization, evolutionary optimization, and Markov chain Monte Carlo (MCMC) within MOOSE. It also elaborates on the interaction among key MOOSE systems — Sampler, MultiApp, Reporter, and Surrogate — in enabling these capabilities. The modularity offered by these systems enables development of a multitude of probabilistic ML and UQ algorithms in MOOSE. Example code demonstrations include parallel active learning and parallel Bayesian inference via active learning. The impact of these developments is illustrated through five applications relevant to computational energy applications: UQ of nuclear fuel fission product release, using parallel active learning Bayesian inference; very rare events analysis in nuclear microreactors using active learning; advanced manufacturing process modeling using multi-output GPs (MOGPs) and dimensionality reduction; fluid flow using deep GPs (DGPs); and tritium transport model parameter optimization for fusion energy, using batch Bayesian optimization. These capabilities are part of the MOOSE framework.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Joint optimization of logistics infrastructure investments and subsidies in a regional logistics network with CO 2 emission reduction targets

This study proposes an optimization model that simultaneously incorporates the selection of logistics infrastructure investments and subsidies for green transport modes to achieve specific CO 2 emission targets in a regional logistics network. The proposed model is formulated as a bi-level formulation, in which the upper level determines the optimal selection of logistics infrastructure investments and subsidies for green transport modes such that the benefit-cost ratio of the entire logistics system is maximized. The lower level describes the selected service routes of logistics users. A genetic and Frank-Wolfe hybrid algorithm is introduced to solve the proposed model. The proposed model is applied to the regional logistics network of Changsha City, China. Findings show that using the joint scheme of the selection of logistics infrastructure investments and green subsidies is more effective than using them solely. In conclusion, carbon emission reduction targets can significantly affect logistics infrastructure investments and subsidy levels.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Light-driven dinitrogen reduction catalyzed by a CdS:nitrogenase MoFe protein biohybrid

The splitting of dinitrogen (N2) and reduction to ammonia (NH3) is a kinetically complex and energetically challenging multistep reaction. In the Haber-Bosch process, N2 reduction is accomplished at high temperature and pressure, whereas N2 fixation by the enzyme nitrogenase occurs under ambient conditions using chemical energy from adenosine 5'-triphosphate (ATP) hydrolysis. We show that cadmium sulfide (CdS) nanocrystals can be used to photosensitize the nitrogenase molybdenum-iron (MoFe) protein, where light harvesting replaces ATP hydrolysis to drive the enzymatic reduction of N2 into NH3. The turnover rate was 75 per minute, 63% of the ATP-coupled reaction rate for the nitrogenase complex under optimal conditions. Inhibitors of nitrogenase (i.e., acetylene, carbon monoxide, and dihydrogen) suppressed N2 reduction. The CdS:MoFe protein biohybrids provide a photochemical model for achieving light-driven N2 reduction to NH3.

09 BIOMASS FUELS↗
NASA NTRS2017

Influence of Shear Stiffness Degradation on Crack Paths in Uni-Directional Composite Laminates

Influence of shear stiffness degradation in an element, due to damage, on crack paths in uni-directional laminates has been demonstrated. A new shear stiffness degradation approach to improve crack path prediction has been developed and implemented in an ABAQUS/Explicit frame work using VUMAT. Three progressive failure analysis models, built-in ABAQUS (TradeMark), original COmplete STress Reduction (COSTR) and the modified COSTR damage models have been utilized in this study to simulate crack paths in five unidirectional notched laminates, 15deg, 30deg, 45deg, 60deg and 75deg under uniaxial tension load. Results such as crack paths and load vs. edge displacement curves are documented in this report. Modified COSTR damage model shows better accuracy in predicting crack paths in all the uni-directional laminates compared to the ABAQUS (TradeMark) and the original COSTR damage models.

Satyanarayana, Arunkumar↗
DOE OSTI2022

Widespread Wildfires Over the Western United States in 2020 Linked to Emissions Reductions During COVID-19

Widespread wildfires struck western United States in 2020, directly damaging properties and threatening human lives. Meanwhile, the COVID-19 pandemic rapidly spread across the globe in 2020, which disrupted human activities and resulted in substantial reductions in anthropogenic emissions. Here, we investigate the effects of the emissions reductions of aerosols, precursors, and greenhouse gases during the pandemic on wildfire weather conditions in 2020 over western United States by using an earth system model together with observational data. We show that the COVID-19 emissions reductions in model experiments increased surface air temperature and decreased precipitation and relative humidity due to a weakened moisture transport, which explains 10-40% of the observed increase in the risk of wildfires over western United States in 2020. In conclusion, this study suggests that COVID-19-related abrupt emissions reductions have an unexpected influence on wildfires, highlighting a different but important role of human activities in affecting wildfire risks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Photoreduction of gaseous oxidized mercury changes global atmospheric mercury speciation, transport and deposition

Anthropogenic mercury (Hg(0)) emissions oxidize to gaseous Hg(II) compounds, before deposition to Earth surface ecosystems. Atmospheric reduction of Hg(II) competes with deposition, thereby modifying the magnitude and pattern of Hg deposition. Global Hg models have postulated that Hg(II) reduction in the atmosphere occurs through aqueous-phase photoreduction that may take place in clouds. Here we report that experimental rainfall Hg(II) photoreduction rates are much slower than modelled rates. We compute absorption cross sections of Hg(II) compounds and show that fast gas-phase Hg(II) photolysis can dominate atmospheric mercury reduction and lead to a substantial increase in the modelled, global atmospheric Hg lifetime by a factor two. Models with Hg(II) photolysis show enhanced Hg (0) deposition to land, which may prolong recovery of aquatic ecosystems long after Hg emissions are lowered, due to the longer residence time of Hg in soils compared with the ocean. Fast Hg(II) photolysis substantially changes atmospheric Hg dynamics and requires further assessment at regional and local scales.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1984

Application of modern structural optimization to vibration reduction in rotorcraft

The helicopter rotor model consists of a four bladed hingeless rotor attached to a fuselage. The helicopter is assumed to be in trimmed forward flight. Each blade is assumed to have flap, lag, and torsional degrees of freedom. The fuselage degrees of freedom are not included in the analysis. Thus the aeroelastic stability and response analysis upon which this study is based is an isolated blade analysis. The helicopter rotor vibration reduction problem expressed as a general class of structural synthesis problems is given.

Friedmann, P. P.↗
DOE OSTI2016

Investigation of industrial-scale carbon dioxide reduction using pulsed electron beams

Carbon dioxide is the most important greenhouse gas contributing to global warming. To help mitigate increasing CO{sub 2} concentrations, we investigate a method of carbon dioxide reduction using high-power electron beams, which can be used on an industrial scale. A series of experiments are conducted in which the reduction of CO{sub 2} is measured for different gas compositions and power deposition rates. An electron beam deposition model is applied to compute reduction rates of CO{sub 2} and energy cost for breaking a CO{sub 2} molecule in flue gas and pure carbon dioxide at atmospheric pressure. For flue gas consisting of 82% N{sub 2}, 6% O{sub 2}, and 12% CO{sub 2}, the calculated energy cost is 85 eV per molecule. In order to dissociate 50% of the CO{sub 2} molecules, beam energy density deposition on the order of 20 J/cm{sup 3} is required. Electron beam irradiation of 12.6 liter gas volume containing 90% CO{sub 2} and 10% CH{sub 4} at beam energy density deposition of 4.2 J/cm{sup 3}, accumulated over 43 shots in a 20 min interval, reduced the CO{sub 2} concentration to 78%. Analogous experiments with a gas mixture containing 11.5% CO{sub 2}, 11.5% CH{sub 4}, and balance of Ar, reduced the CO{sub 2} concentration to below 11% with energy deposition 0.71 J/cm{sup 3}, accumulated over 10 shots in a 5 min interval. The experimental data and the theoretical predictions of CO{sub 2} reduction using pulsed electron beams are in agreement within the experimental error. Other techniques to enhance the removal of CO{sub 2} with pulsed electron beams are also explored, yielding new possible avenues of research.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1988

Dynamic analysis of nonlinear rotor-housing systems

Nonlinear analysis methods are developed which will enable the reliable prediction of the dynamic behavior of the space shuttle main engine (SSME) turbopumps in the presence of bearing clearances and other local nonlinearities. A computationally efficient convolution method, based on discretized Duhamel and transition matrix integral formulations, is developed for the transient analysis. In the formulation, the coupling forces due to the nonlinearities are treated as external forces acting on the coupled subsystems. Iteration is utilized to determine their magnitudes at each time increment. The method is applied to a nonlinear generic model of the high pressure oxygen turbopump (HPOTP). As compared to the fourth order Runge-Kutta numerical integration methods, the convolution approach proved to be more accurate and more highly efficient. For determining the nonlinear, steady-state periodic responses, an incremental harmonic balance method was also developed. The method was successfully used to determine dominantly harmonic and subharmonic responses fo the HPOTP generic model with bearing clearances. A reduction method similar to the impedance formulation utilized with linear systems is used to reduce the housing-rotor models to their coordinates at the bearing clearances. Recommendations are included for further development of the method, for extending the analysis to aperiodic and chaotic regimes and for conducting critical parameteric studies of the nonlinear response of the current SSME turbopumps.

Noah, Sherif T.↗