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NASA NTRS2001

Constraints on Variability of Brightness and Surface Magnetism on Time Scales of Decades to Centuries in the Sun and Sun-Like Stars: A Source of Potential Terrestrial Climate Variability

These four points summarize our work to date. (1) Conciliation of solar and stellar photometric variability. Previous research by us and colleagues suggested that the Sun might at present be showing unusually low photometric variability compared to other sun-like stars. Those early results would question the suitability of the technique of using sun-like stars as proxies for solar irradiance change on time scales of decades to centuries. However, our results indicate the contrary: the Sun's observed short-term (seasonal) and longterm (year-to-year) brightness variations closely agree with observed brightness variations in stars of similar mass and age. (2) We have demonstrated an inverse correlation between the global temperature of the terrestrial lower troposphere, inferred from the NASA Microwave Sounding Unit (MSU) radiometers, and the total area of the Sun covered by coronal holes from January 1979 to present (up to May 2000). Variable fluxes of either solar charged particles or cosmic rays, or both, may influence the terrestrial tropospheric temperature. The geographical pattern of the correlation is consistent with our interpretation of an extra-terrestrial charged particle forcing. (3) Possible climate mechanism amplifying the impact of solar ultraviolet irradiance variations. The key points of our proposed climate hypersensitivity mechanism are: (a) The Sun is more variable in the UV (ultraviolet) than in the visible. However, the increased UV irradiance is mainly absorbed in the lower stratosphere/upper troposphere rather than at the surface. (b) Absorption in the stratosphere raises the temperature moderately around the vicinity of the tropopause, and tends to stabilize the atmosphere against vertical convective/diffusive transport, thus decreasing the flux of heat and moisture carried upward from surface. (c) The decrease in the upward convection of heat and moisture tends to raise the surface temperature because a drier upper atmosphere becomes less cloudy, which in turn allows more solar radiation to reach the Earth's surface. (4) Natural variability in an ocean-atmosphere climate model. We use a 14-region, 6-layer, global thermo-hydrodynamic ocean-atmosphere model to study natural climate variability. All the numerical experiments were performed with no change in the prescribed external boundary conditions (except for the seasonal cycle of the Sun's tilt angle). Therefore, the observed inter-annual variability is of an internal kind. The model results are helpful toward the understanding of the role of nonlinearity in climate change. We have demonstrated a range of possible climate behaviors using our newly developed ocean-atmosphere model. These include climate configurations with no interannual variability, with multi-year periodicities, with continuous chaos, or with chaotically occuring transitions between two discrete substrates. These possible modes of climate behavior are all possible for the real climate, as well as the model. We have shown that small temporary climate influences can trigger shifts both in the mean climate, and among these different types of behavior. Such shifts are not only theoretically plausible, as shown here and elsewhere; they are omnipresent in the climate record on time scales from several years to the age of the Earth. This has two apparently opposite implications for the possibility of anthropogenic global warming. First, any warming which might occur as a result of human influence would be only a fraction of the small-to-large unpredictable natural changes and changes which result from other external causes. On the other hand, small temporary influences such as human influence do have the potential of causing large permanent shifts in mean climate and interannual variability.

Baliunas, Sallie L.↗
DOE OSTI2021

Non-invasive characterization of complex coronary lesions

Conventional invasive diagnostic imaging techniques do not adequately resolve complex Type B and C coronary lesions, which present unique challenges, require personalized treatment and result in worsened patient outcomes. These lesions are often excluded from large-scale non-invasive clinical trials and there does not exist a validated approach to characterize hemodynamic quantities and guide percutaneous intervention for such lesions. This work identifies key biomarkers that differentiate complex Type B and C lesions from simple Type A lesions by introducing and validating a coronary angiography-based computational fluid dynamic (CFD-CA) framework for intracoronary assessment in complex lesions at ultrahigh resolution. Among 14 patients selected in this study, 7 patients with Type B and C lesions were included in the complex lesion group including ostial, bifurcation, serial lesions and lesion where flow was supplied by collateral bed. Simple lesion group included 7 patients with lesions that were discrete, <10mm long and readily accessible. Intracoronary assessment was performed using CFD-CA framework and validated by comparing to clinically measured pressure-based index, such as FFR. Local pressure, endothelial shear stress (ESS) and velocity profiles were derived for all patients. We validates the accuracy of our CFD-CA framework and report excellent agreement with invasive measurements (n=14,R 2 =0.6,p=0.0013). Ultra-high resolution achieved by the model enable physiological assessment in complex lesions and quantify hemodynamic metrics in all vessels up to 1mm in diameter. Importantly, we demonstrate that in contrast to traditional pressure-based metrics, there is a significant difference in the intracoronary hemodynamic forces, such as ESS, in complex lesions compared to simple lesions at both resting and hyperemic physiological states [n = 14, p=0.03]. Higher ESS was observed in the complex lesion group (7.0±4.7 Pa) than in simple lesion group (4.8±3.6 Pa). Complex coronary lesions have higher ESS compared to simple lesions, such differential hemodynamic evaluation can provide much the needed insight into the increase in adverse outcomes for such patients and has incremental prognostic value over traditional pressure-based indices, such as FFR.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Integrated Flue Gas Purification and Latent Heat Recovery for Pressurized Oxy-Combustion (Final Scientific/Technical Report)

Pressurized oxy-combustion has been identified by DOE as a transformational technology for coal power with carbon capture due to the advantages that are realized when the combustion process is pressurized. The staged pressurized oxy-combustion (SPOC) process is particularly attractive as the efficiency of the process is almost 6 percentage points greater than that of first generation oxy-combustion. A critical component of the SPOC process, and potentially other pressurized combustion processes, is the Direct Contact Cooler (DCC) where the latent heat of the flue gas moisture is recovery to improve plant efficiency while simultaneously removing SO x and NO x from the flue gas, so that the FGD and de-NO x processes can be eliminated, and the cost of electricity minimized. The objective of this R&D effort was to advance the TRL of the DCC technology, which included performance testing at a 100 kW scale to validate the process and obtain key engineering data for scale-up. A collateral objective was to study the gas- and liquid-phase kinetics, and the development of a systematic chemical mechanism validated by experimental data. Experiments in a bench-scale stirred reactor provided an updated understanding of the liquid chemistry and the effects of temperature and pH. This information was used to develop a reduced reaction mechanism, which was subsequently incorporated in an ASPENbased process model, to allow for evaluation of the DCC at full scale. A small-pilot DCC column was designed, constructed and tested using simulated flue gas at the pressurized oxy-combustion test facility at Washington University in St. Louis. In the majority of tests, the SO 2 capture approached 100%, making the NO x capture the primary metric of capture efficiency. An NO x capture efficiency of 90% was achieved when the gas residence time was 95 seconds, demonstrating that high capture rates can be attained with reasonable reactor size. At higher temperatures (up to 200°C inlet gas temperature) the total NO x scrubbing efficiency was reduced by approximately 10% (compared to room temp.) and this was attributed to a reduced NO oxidation rate. A significant amount of SO 2 was present in the gas outlet (10%) only when the temperature was high and the N:S ratio was low (N/S < 1), which highlights the necessity of controlling the NOx concentration in the flue gas for complete sulfur scrubbing. After incorporated our optimized chemical mechanism into an ASPEN process model, various full-scale configurations of the DCC were evaluate, and the results indicate that the proposed DCC can accomplish its intended goals at full scale and at a modest size. Thus, the results of this project indicate that the DCC is a promising technology for recovery of the latent heat of the moisture in the flue gas while simultaneously scrubbing the nitrogen and sulfur oxides, thus enabling pressurized oxy-combustion, in general, and the SPOC process, in particular.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS2000

Bioavailability and Pharmacodynamics of Promethazine in Human Subjects

Space Motion Sickness (SMS) is often treated in space with promethazine (PMZ). Anecdotal reports indicate that the common side effects of drowsiness and decrements in cognitive performance that are associated with PMZ administration (50 mg IM on the ground, are absent or less pronounced in space suggesting I that-the bioavailability and/or pharmacodynamic behavior of PMZ may be altered during space flight. There are limited flight opportunities available for clinical research in space, the NRA-99, therefore, solicits research required to improve, or answer specific questions about in-flight diagnosis, therapy, and post-flight rehabilitation. We propose here, to establish a noninvasive method for pharmacodynamic and therapeutic assessment of PMZ. The specific objectives of the proposed research are to, 1. Establish a saliva to plasma ratio of PMZ after administration, 2. Estimate the relative bioavailability of the three flight-specific dosage forms of PMZ, and 3. Establish the dose-response relationship of PMZ. We will estimate the bioavailability of intramuscular injection (IM), oral tablets and rectal suppositories in normal subjects during ambulatory and antiorthostatic; bed rest (ABR) conditions using novel stable isotope techniques. Drowsiness, cognitive performance and salivary flow rate will be measured as a function of circulating drug concentrations after administration of three IM doses of PMZ. We will compare and contrast the bioavailability of PMZ during normal and ABR conditions to examine whether or not ABR can simulate changes in drug, absorption and availability similar to those anticipated in a microgravity environment. Results of this study will validate methods for an approved study with this medication awaiting a flight opportunity for manifestation. These data will also provide the much needed information on the dynamics and therapeutic index. of this medication and their implications on crew fatigue and performance in space. Key words: Promethazine, stable isotopes, bioavailability, pharmacodynamics, cognitive performance, antiorthostatic bed rest.

Putcha, Lakshmi↗
DOE OSTI2025

Hydrogen adsorption and transport in clay-rich geomaterials: Implications for large-volume underground hydrogen storage

Depleted oil and gas reservoirs, characterized by impermeable clay-rich caprocks, are promising sites for large-scale underground hydrogen storage (UHS), which is a key strategy to support hydrogen-based energy systems. However, experimental data on hydrogen storage in clay-rich geomaterials remain scarce. In this work, we experimentally investigated hydrogen adsorption and migration in clay-rich geomaterials in the presence of nitrogen and water under controlled temperatures. Experimental observations showed that hydrogen was adsorbed in dry illite. A dual-porosity transport model was developed to interpret hydrogen transport between large-pore and small-pore domains in illite. The large-pore domain is the space between clay particles (i.e., inter-particle space), whereas the small-pore domain is the nanoscale pore space between clay mineral layers (i.e., inter-layer or intra-particle space). In contrast, nitrogen showed no evidence of adsorption in dry illite because it cannot move into the small-pore domain due to the relatively large kinetic diameter, referred to as the molecular sieving effect. Here, we found that 0.7–1.3 nm is the length scale regulating this molecular sieving effect, matching the interlayer spacing in illite, suggesting that nitrogen is a promising cushion gas in UHS, which aims to maintain adequate pressure in the reservoir for economic operations. In wetted illite, hydrogen was not adsorbed into the interlayer space due to the occupation of adsorption sites by interlayer water, which highlights the critical role of the clay hydration state in controlling hydrogen-clay interactions. Additionally, hydrogen adsorption experiments on crushed shale indicated that the shale surface possessed adsorption sites more favorable for hydrogen than for nitrogen. Through these experiments, we provide new insights into hydrogen storage mechanisms in clay-rich geomaterials and offer valuable laboratory data for evaluating the performance of large-scale UHS systems.

Adsorption↗
DOE OSTI2018

Development of predictive capability of cycle-to-cycle variation in dual-fuel engines using supercomputing-based computational fluid dynamics

Cycle-to-cycle variation (CCV) in internal combustion engines is expected due to variabilities in operating conditions such as in-cylinder fuel stratification, mixing behavior, manifold air pressure, injection timing etc. Generally, engine experimental studies provide averaged quantities such as cylinder pressure, emissions, indicated mean effective pressure (IMEP) from multiple cycles and their CCV of IMEP, and CCV of cylinder pressure from consecutive cycles for a given test condition. Capturing 3D spatial distributions of relevant measures such as fuel-air mixing, temperature, turbulence levels and emissions from such experiments is challenging. Computational Fluid Dynamics (CFD) is an alternative to experiments, that can be used effectively to understand the spatial and temporal distributions of parameters of interest.Quantitative understanding of CCV in dual-fuel (DF) engines will accelerate the development and deployment of engines that provide fuel flexibility, economic advantage and emission compliance. Earlier work [1] performed to develop an understanding of the physics of CCV in large-bore, medium-speed, dual-fuel engines was partially successful. That effort entailed a sparse design of experiment (DOE) of full-cylinder geometry, closed-cycle, dual-fuel CFD simulations in which variabilities within some of the identified global parameters were exercised. The Coefficient of Variation (COV) of cylinder pressure was promising compared with experimental COV. This reinforced the understanding of which global parameters are significant contributors to CCV in DF combustion.The authors have used several high-performance supercomputing facilities in the process of developing predicting capability of CCV in large-bore engines, while operating in dual-fuel, diesel and natural gas (NG), combustion mode [1, 2]. In the current study CCV influencing parameters in a diesel-natural gas dual-fuel engine was studied using a 4th order DOE consisting of 137 concurrent cases. These full-geometry, closed-cycle, CFD simulations were run on the Mira supercomputing facility at the Argonne National Laboratory (ANL). This paper describes key learnings of that study along with a validation of the DOE. Further, the CCV prediction methodology, which is applicable to simulation-based design and testing, is described.

Gubba, Sreenivasa Rao↗
NASA NTRS1999

Simulation of Non-Acoustic Combustion Instability in a Hybrid Rocket Motor

A transient model of a hybrid motor was formulated to study the cause and elimination of non-acoustic combustion instability. The transient model was used to simulate four key tests out of a series of seventeen hybrid motor tests conducted by Thiokol, Rocketdyne and Martin Marietta at NASA/Marshall Space Flight Center (NASA/MSFC). These tests were performed under the Hybrid Propulsion Technology for Launch Vehicle Boosters (HPTLVB) program. The first test resulted in stable combustion. The second test resulted in large-amplitude, 6.5 Hz chamber pressure oscillations that gradually damped away by the end of the test. The third test resulted in large-amplitude, 7.5 Hz chamber pressure oscillations that were sustained throughout the test. The seventh test resulted in the elimination of combustion instability with the installation of an orifice immediately upstream of the injector. The formulation and implementation of the model are the scope of this presentation. The current model is an independent continuation of modeling presented previously by joint Thiokol-Rocketdyne collaborators Boardman, Hawkins, Wassom, and Claflin. The previous model simulated an unstable IR&D hybrid motor test performed by Thiokol. There was very good agreement between the model and the test data. Like the previous model, the current model was developed using Matrix-x simulation software. However, the tests performed at NASA/MSFC under the HPTLVB program were actually simulated. In the current model, the hybrid motor consisting of the liquid oxygen (LOX) injector, the multi-port solid fuel grain and the nozzle was simulated. Also, simulated in the model was the LOX feed system consisting of the tank, venturi, valve and feed lines. All components of the hybrid motor and LOX feed system are treated by a lumped-parameter approach. Agreement between the results of the transient model and the actual test data was very good. This agreement between simulated and actual test data indicated that the combustion instability in the hybrid motor was due to two causes. The first cause was a LOX feed system of insufficient stiffness. The second cause was a LOX injector with an impedance or pressure drop that was too low to provide damping against the feed system oscillations. Also, it was discovered that testing with a new grain of solid fuel sustained the combustion instability. However, testing with a used grain of solid fuel caused the combustion instability to gradually decay.

Rocker, Marvin↗
NASA NTRS1999

Simulation of Non-Acoustic Combustion Instability in a Hybrid Rocket Motor

A transient model of a hybrid motor was formulated to study the cause and elimination of non-acoustic combustion instability. The transient model was used to simulate four key tests out of a series of seventeen hybrid motor tests conducted by Thiokol, Rocketdyne and Martin Marietta at NASA/Marshall Space Flight Center (NASAIMSFC). These tests were performed under the Hybrid Propulsion Technology for Launch Vehicle Boosters (HPTLVB) program. The first test resulted in stable combustion. The second test resulted in large-amplitude, 6.5 Hz chamber pressure oscillations that gradually damped away by the end of the test. The third test resulted in large-amplitude, 7.5 Hz chamber pressure oscillations that were sustained throughout the test. The seventh test resulted in the elimination of combustion instability with the installation of an orifice immediately upstream of the injector. The formulation and implementation of the model are the scope of this presentation. The current model is an independent continuation of modeling presented previously by joint Thiokol-Rocketdyne collaborators Boardman, Hawkins, Wassom, and Claflin. The previous model simulated an unstable IR&D hybrid motor test performed by Thiokol. There was very good agreement between the model and the test data. Like the previous model, the current model was developed using Matrix-x simulation software. However, the tests performed at NASA/MSFC under the HPTLVB program were actually simulated. In the current model, the hybrid motor consisting of the liquid oxygen (LOX) injector, the multi-port solid fuel grain and the nozzle was simulated. Also, simulated in the model was the LOX feed system consisting of the tank, venturi, valve and feed lines. All components of the hybrid motor and LOX feed system are treated by a lumped-parameter approach. Agreement between the results of the transient model and the actual test data was very good. This agreement between simulated and actual test data indicated that the combustion instability in the hybrid motor was due to two causes. The first cause was a LOX feed system of insufficient stiffness. The second cause was a LOX injector with an impedance or pressure drop that was too low to provide damping against the feed system oscillations. Also, it was discovered that testing with a new grain of solid fuel sustained the combustion instability. However, testing with a used grain of solid fuel caused the combustion instability to gradually decay.

Rocker, Marvin↗
NASA NTRS2015

BioSentinel: Mission Development of a Radiation Biosensor to Gauge DNA Damage and Repair Beyond Low Earth Orbit on a 6U Nanosatellite.

We are designing and developing a "6U" (10 x 22 x 34 cm; 14 kg) nanosatellite as a secondary payload to fly aboard NASA's Space Launch System (SLS) Exploration Mission (EM) 1, scheduled for launch in late 2017. For the first time in over forty years, direct experimental data from biological studies beyond low Earth orbit (LEO) will be obtained during BioSentinel's 12- to 18- month mission. BioSentinel will measure the damage and repair of DNA in a biological organism and allow us to compare that to information from onboard physical radiation sensors. In order to understand the relative contributions of the space environment's two dominant biological perturbations, reduced gravity and ionizing radiation, results from deep space will be directly compared to data obtained in LEO (on ISS) and on Earth. These data points will be available for validation of existing biological radiation damage and repair models, and for extrapolation to humans, to assist in mitigating risks during future long-term exploration missions beyond LEO. The BioSentinel Payload occupies 4U of the spacecraft and will utilize the monocellular eukaryotic organism Saccharomyces cerevisiae (yeast) to report DNA double-strand-break (DSB) events that result from ambient space radiation. DSB repair exhibits striking conservation of repair proteins from yeast to humans. Yeast was selected because of 1) its similarity to cells in higher organisms, 2) the well-established history of strains engineered to measure DSB repair, 3) its spaceflight heritage, and 4) the wealth of available ground and flight reference data. The S. cerevisiae flight strain will include engineered genetic defects to prevent growth and division until a radiation-induced DSB activates the yeast's DNA repair mechanisms. The triggered culture growth and metabolic activity directly indicate a DSB and its successful repair. The yeast will be carried in the dry state within the 1-atm P/L container in 18 separate fluidics cards with each card having 16 independent culture microwells, with integral microchannels and filters to supply nutrients and reagents, confine the yeast to the wells, and enable optical measurement. The measurement subsystem will monitor each subgroup of culture wells continuously for several weeks, optically tracking DSBtriggered cell growth and metabolism. BioSentinel will also include physical radiation sensors based on the TimePix sensor, as implemented by JSC's RadWorks group, which record individual radiation events including estimates of their linear-energytransfer (LET) values. Radiation-dose and LET data will be compared directly to the rate of DSB-and-repair events measured by the S. cerevisiae biosentinels. The spacecraft bus will operate in a deep space environment with functions that include command and data handling, communications, power generation (via deployable solar panels) and storage, and attitude determination-and-control system with micropropulsion. Development of the BioSentinel spacecraft will mature and prove multiple nanosatellite advances in order to function well beyond LEO: Communications from distances of ≥ 500,000 km; Autonomous attitude control, momentum management, and safe mode of nanosatellites in deep space; Shielding-, hardening-, design-, and software-derived radiation tolerance for electronics; Reliable functionality for 12 - 18 months of key subsystems for biofluidics, memory, communications, power, etc.; Close integration of living biological radiation event monitors with miniature physical radiation spectrometers; Biological measurement of solar particle events beyond Earth orbit In addition to providing the first biological results from beyond LEO in over 4 decades, BioSentinel will provide an adaptable small-satellite instrument platform to perform a range of human-exploration-relevant measurements that characterize the biological consequences of multiple outer space environments. BioSentinel is being developed under NASA's Advanced Exploration Systems program.

DNA damage↗
NASA NTRS2019

Improving SMAP freeze-thaw retrievals for pavements using effective soil temperature from GEOS-5: Evaluation against in situ road temperature data over the U.S

Seasonal freeze-thaw (FT) affects over half the northern hemisphere and impacts many key processes of the Earth System such as energy exchange, hydrology and vegetation. Nearly all past studies using spaceborne FT retrievals have focused on characterizing FT specifically for natural environments. FT in the built environment is also routinely studied and a topic of great interest, especially with regards to transportation infrastructure. Whereas natural FT process are frequently investigated using spaceborne observations, FT studies of roads are often limited to local scales, using in situ or nearby weather station data only. Comparisons between FT retrievals obtained from NASA's Soil Moisture Active Passive (SMAP) satellite and roads in Alaska (AK) and the Contiguous United States (CONUS) showed that spaceborne FT retrievals had good agreement with road data. But those results also indicated that NASA FT retrievals in CONUS were relatively too warm compared to road data. If SMAP FT retrievals were to be used for identifying FT transition timing for applications by the transportation community, it is also important for frozen conditions to be identified more accurately. This work is primarily concerned with improving frozen retrievals made in CONUS by calculating new Normalized Polarization Ratio (NPR) thresholds as compared to those currently used in SMAP FT. We found that focusing on a temporal subset of October through May for comparisons greatly improved the correlation between NPR and effective soil temperature (Teff, one of SMAP's ancillary datasets), often from about zero to 0.6. We then applied linear regression between NPR and Teff to obtain new NPR thresholds resulting in the FT-Roads (FT-R) product. NASA FT and FT-R were evaluated against road data at about 1000 locations in CONUS and a battery of different tests indicated that FT-R performed better under nearly all conditions compared to NASA FT. Overall, NASA FT accuracies were 69% and 80% for 6 am and 6 pm SMAP retrievals, while FT-R achieved accuracies of 79% and 82%. We also investigated the potential for using Teff for road FT (6 am, only) and found that those comparisons were even more accurate (84%). We've also quantified inter- and intraregional differences of SMAP FT performance and found that accuracy metrics vary over twice as much between geographic subdivisions (9%) as compared to between the states within a subdivision (4%). Most importantly, the main goal of improving the detection of in situ frozen conditions in CONUS was realized, with FT-R accurately detecting frozen conditions >50% more frequently than NASA FT.

Passive microwave↗
NASA NTRS2005

Control of Combustion-Instabilities Through Various Passive Devices

It is well known that under some operating conditions, rocket engines (using solid or liquid fuels) exhibit unstable modes of operation that can lead to engine malfunction and shutdown. The sources of these instabilities are diverse and are dependent on fuel, chamber geometry and various upstream sources such as pumps, valves and injection mechanism. It is believed that combustion-acoustic instabilities occur when the acoustic energy increase due to the unsteady heat release of the flame is greater than the losses of acoustic energy from the system [1, 2]. Giammar and Putnam [3] performed a comprehensive study of noise generated by gasfired industrial burners and made several key observations; flow noise was sometimes more intense than combustion roar, which tended to have a characteristic frequency spectrum. Turbulence was amplified by the flame. The noise power varied directly with combustion intensity and also with the product of pressure drop and heat release rate. Karchmer [4] correlated the noise emitted from a turbofan jet engine with that in the combustion chamber. This is important, since it quantified how much of the noise from an engine originates in the combustor. A physical interpretation of the interchange of energy between sound waves and unsteady heat release rates was given by Rayleigh [5] for inviscid, linear perturbations. Bloxidge et al [6] extended Rayleigh s criterion to describe the interaction of unsteady combustion with one-dimensional acoustic waves in a duct. Solutions to the mass, momentum and energy conservation equations in the pre- and post-flame zones were matched by making several assumptions about the combustion process. They concluded that changes in boundary conditions affect the energy balance of acoustic waves in the combustor. Abouseif et al [7] also solved the one-dimensional flow equations, but they used a onestep reaction to evaluate the unsteady heat release rate by relating it to temperature and velocity perturbations. Their analysis showed that oscillations arise from coupling between entropy waves produced at the flame and pressure waves originating from the nozzle. Yang and Culick [8] assumed a thin flame sheet, which is distorted by velocity and pressure oscillations. Conservation equations were expressed in integral form and solutions for the acoustic wave equations and complex frequencies were obtained. The imaginary part of the frequency indicated stability regions of the flame. Activation energy asymptotics together with a one-step reaction were used by McIntosh [9] to study the effects of acoustic forcing and feedback on unsteady, one-dimensional flames. He found that the flame stability was altered by the upstream acoustic feedback. Shyy et al [10] used a high-accuracy TVD scheme to simulate unsteady, one-dimensional longitudinal, combustion instabilities. However, numerical diffusion was not completely eliminated. Recently, Prasad [11] investigated numerically the interactions of pressure perturbations with premixed flames. He used complex chemistry to study responses of pressure perturbations in one-dimensional combustors. His results indicated that reflected and transmitted waves differed significantly from incident waves.

Frendi, Kader↗
NASA NTRS2016

Atg12 Maintains Skeletal Integrity by Modulating Pro-Osteoclastogenic Signals and Chondrocyte Differentiation

Weightlessness and radiation, two unique elements of space, profoundly decreases bone mass. This bone loss is attributed to increased activity of bone-resorbing osteoclasts and functional changes in bone-forming osteoblasts, cells that give rise to mature osteocytes. Our long-term goal is to identify signaling pathways that may be targeted to mitigate bone loss in scenarios of space exploration, radiotherapy and accidental radiation exposure. We have previously shown that exposure of MLO-Y4 osteocyte-like cells to simulated space radiation (56Fe) increased the expression of the pro-osteoclastogenic gene rankl and decreased protein levels of LC3B-II, a key player in autophagy. In this current study, we aimed to further elucidate the role of autophagy in maintaining structural integrity of the skeleton. We hypothesize that loss of autophagy in bone leads to an imbalance in pro-osteoclastogenic and pro-osteogenic signals, resulting in net bone loss. To test our hypothesis we performed global postnatal deletion of Atg12 using tamoxifeninducible Cre recombinase under the control of the CAG promoter. Six-week-old CAGCreERT2/ FloxAtg12 animals were treated daily with Tamoxifen or Vehicle (Control, oil only) for five days and euthanasia performed two weeks after the onset of treatment. Percent change in body weights (prior to treatment and at euthanasia) was not significantly different between treatment groups within the same gender. Compared to Vehicle (Control) groups, Tamoxifen (Atg12 iKO) groups showed decreased LC3B-I to II conversion and increased p62 protein levels, consistent with loss of autophagy. Quantitative PCR revealed increased expression of proosteoclastogenic cytokines mcp1 and rankl in bone and marrow respectively in male iKOs compared to male controls. Expression levels of these genes were not significantly altered in the Atg12 iKO females compared to females controls. Microcomputed tomography of tibiae revealed decreased cortical bone volume, cortical thickness and periosteal perimeter consistent with bone loss; and a longer primary spongiosa in male Atg12 iKOs display compared to male controls. These decrements were less pronounced in the female Atg12 iKOs. Cancellous bone structure was not significantly different between iKOs and controls in both genders. Histological analysis also revealed that compared to male controls, male iKOs showed a profound increase in chondrocyte column length of the growth plate with hyper-expansion of both proliferating and hypertrophic zones. Taken together, these findings indicate that autophagy plays an important role in the maintenance of bone structural integrity by mediating the production of proosteoclastogenic signals and regulating chondrocyte proliferation and differentiation.

autophagy↗
NASA NTRS2019

Evaluation of NASA's High-Resolution Global Composition Simulations: Understanding a Pollution Event in the Chesapeake Bay During the Summer 2017 OWLETS Campaign

Recirculation of pollutants due to a bay breeze effect is a key meteorological mechanism impacting air quality near urban coastal areas, but regional and global chemical transport models have historically struggled to capture this phenomenon. We present a case study of a high ozone (O3) episode observed over the Chesapeake Bay during the NASA Ozone Water-Land Environmental Transition Study (OWLETS) in summer 2017. OWLETS included a complementary suite of ground-based and airborne observations, with which we characterize the meteorological and chemical context of this event and develop a framework to evaluate model performance. Two publicly-available NASA global high-resolution coupled chemistry-meteorology models (CCMMs) are investigated: GEOS-CF and MERRA2-GMI. The GEOS-CF R squared value for comparisons between the NASA Sherpa C-23 aircraft measurements to the GEOS-CF resulted in good agreement (R squared: 0.67) on July 19th and fair agreement (R squared: 0.55) for July 20th. Compared to surface observations, we find the GEOS-CF product with a 25 x 25 km squared grid box, at an hourly (R squared: 0.62 to 0.87) and 15-minute (R squared: 0.64 to 0.87) interval for six regional sites outperforms the hourly nominally 50 x 50 km squared gridded MERRA2-GMI (R squared: 0.53 to 0.76) for four of the six sites, suggesting it is better capable of simulating complex chemical and meteorological features associated with ozone transport within the Chesapeake Bay airshed. When the GEOS-CF product was compared to the TOLNet LiDAR observations at both NASA Langley Research Center (LaRC) and the Chesapeake Bay Bridge Tunnel (CBBT), the median differences at LaRC were -6 to 8% and at CBBT were ± 7% between 400 to 2000 m ASL. This indicates that, for this case study, the GEOS-CF is able to simulate surface level ozone diurnal cycles and vertical ozone profiles at small scales between the surface level and 2000 m ASL. Evaluating global chemical model simulations at sub-regional scales will help air quality scientists understand the complex processes occurring at small spatial and temporal scales within complex surface terrain changes, simulating nighttime chemistry and deposition, and the potential to use global chemical transport simulations in support of regional and sub-regional field campaigns.

NASA Ozone Water-Land Environmental Transition Stu↗
DOE OSTI2020

Automated, Unmanned Detection and Quantification of Fugitive Methane Emissions

Compressor stations used to move natural gas are one of the largest sources of fugitive methane emissions in the midstream sector, accounting for approximately 50% of all fugitive emissions (Zimmerle et al., 2015). This problem is most widespread at reciprocating compressors (Subramanian et al., 2015) where faulty seals are a key contributor to methane emissions (Johnson et al., 2015). As such, there is a significant need for a robust technology that could provide an early indication of an unexpected emission. Equally important, the technology needs to be able to account for biogenic versus anthropogenic sources of methane. One means of indirectly making this determination, is to leverage optical technologies that can autonomously pinpoint the source of such leaks. This presentation discusses recent work funded by the U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL), focused on the development of an innovative remote sensing technology that can reliably and autonomously detect fugitive methane emissions in near real-time, using computer vision and deep learning. The technology called the Smart Methane Leak Detection (SLED/M) system was initially developed to monitor facilities such as compressor stations in a stationary, pan-tilt-zoom configuration. The system has recently been adapted to monitor facilities from an unmanned aerial system (UAS). The speed and maneuverability of UAS platforms are attractive to leak detection and repair program operators, but introduce several challenges. Many existing methane detection algorithms rely on mostly static backgrounds becoming unusable with motion. In addition, top-down views of fugitive methane emissions present differently in Optical Gas Imagers (OGI) compared to looking across the plume. Our work has focused on overcoming these challenges, enhancing the operators ability to detect methane emissions, and pinpoint their sources. Another recent adaptation to SLED/M is the ability to quantify methane emissions using passive sensors (OGI, thermal camera), environmental conditions, plume modeling, and deep learning. SLED/M advances the state-of-the-art for methane emission detection and quantification by focusing on three key critical criteria for effective methane emission mitigation: (1) autonomy (no need for a human to be in the loop), (2) high reliability (low false alarm rates), and (3) real-time performance. Results from this work will be presented.

03 NATURAL GAS↗
DOE OSTI2024

Passivated Contacts for Direct Wafer Product (Final Technical Report)

This TCF project developed a thin-oxide (SiO 2 )/polycrystalline silicon (poly-Si) passivated contact solar cell on CubicPV's (formally 1366 Technologies, Inc.) Direct Wafer® Product (DWP) kerfless wafers. The project used two NREL-developed technologies described in U.S. Patent No. 9,911,873, Hydrogenation of Passivated Contacts and U.S. Patent Application Serial No. 15/890,172, Doped Passivated Contacts . The project was motivated by a potential higher efficiency cell (compared to a PERC cell) using passivated contacts on the ultra-low cost kerfless wafers grown using the Direct Wafer process. The hope was to accelerate market adoption of the cell and wafer by delivering the lowest LCOE in the PV industry. The project tested both n-type and p-type SiO 2 /poly-Si passivated contacts grown by thermal oxidation and plasma enhanced chemical vapor deposition (PECVD) of the poly-Si layer on DWP with varying wafer resistivities. Both deposition techniques are industry standards and thus economically viable methods for commercializing the contacts. The results indicated that both n-type and p-type poly-Si passivated contacts can be formed on polycrystalline DWP wafers, but implied open-circuit voltages (i Voc ) were limited to below 0.65 mV (compared with ~ 730 mV on n-Cz wafers). Diffusion of H to the Si/SiO 2 /poly-Si interface was key to obtaining high i Voc values. In this study, H was diffused from a high-temperature SiN x layer deposited over the poly-Si layer during a high-temperature firing step, similar to one used for screen printed metals. The study concluded that poly-Si passivated contacts on DWP wafers passivated the surface of the wafers as well as PERC passivated surfaces, which use a less expensive dielectric layer stack. The project showed that Direct Wafer Product wafers grown by CubicPV could produce high i Voc values (~0.647 mV), which could produce a cell over 20% efficient with proper processing and metallization. These cells, though not economically viable in 2024 as a stand-alone cell, could be integrated with a wide-bandgap top solar cell to form a two-junction tandem cell that could be viable under certain circumstances. This is because the bottom cell of a 30%, two-terminal tandem only needs to be a 20% cell under one-sun conditions. Thus, the DWP could be an ideal low-cost wafer for tandems. The project also revealed that a TOPCon type cell could be formed on a p-type DWP wafer using a P-diffused emitter and a p-type poly-Si contact. In fact, the p-type version of the poly-Si contact out-performed the n-type version for a variety of wafer resistivities, from highly doped to lowly doped. This curiosity requires more work to understand because on Cz wafers, the n-type poly-Si contact is of much higher quality than the p-type version.

14 SOLAR ENERGY↗
DOE OSTI2021

A daily, 250 m and real-time gross primary productivity product (2000–present) covering the contiguous United States

Abstract. Gross primary productivity (GPP) quantifies the amount of carbon dioxide (CO2) fixed by plants through photosynthesis. Although as a key quantity of terrestrial ecosystems, there is a lack of high-spatial-and-temporal-resolution, real-time and observation-based GPP products. To address this critical gap, here we leverage a state-of-the-art vegetation index, near-infrared reflectance of vegetation (NIRV), along with accurate photosynthetically active radiation (PAR), to produce a SatelLite Only Photosynthesis Estimation (SLOPE) GPP product for the contiguous United States (CONUS). Compared to existing GPP products, the proposed SLOPE product is advanced in its spatial resolution (250 m versus >500 m), temporal resolution (daily versus 8 d), instantaneity (latency of 1 d versus >2 weeks) and quantitative uncertainty (on a per-pixel and daily basis versus no uncertainty information available). These characteristics are achieved because of several technical innovations employed in this study: (1) SLOPE couples machine learning models with MODIS atmosphere and land products to accurately estimate PAR. (2) SLOPE couples highly efficient and pragmatic gap-filling and filtering algorithms with surface reflectance acquired by both Terra and Aqua MODIS satellites to derive a soil-adjusted NIRV (SANIRV) dataset. (3) SLOPE couples a temporal pattern recognition approach with a long-term Cropland Data Layer (CDL) product to predict dynamic C4 crop fraction. Through developing a parsimonious model with only two slope parameters, the proposed SLOPE product explains 85 % of the spatial and temporal variations in GPP acquired from 49 AmeriFlux eddy-covariance sites (324 site years), with a root-mean-square error (RMSE) of 1.63 gC m−2 d−1. The median R2 over C3 and C4 crop sites reaches 0.87 and 0.94, respectively, indicating great potentials for monitoring crops, in particular bioenergy crops, at the field level. With such a satisfactory performance and its distinct characteristics in spatiotemporal resolution and instantaneity, the proposed SLOPE GPP product is promising for biological and environmental research, carbon cycle research, and a broad range of real-time applications at the regional scale. The archived dataset is available at https://doi.org/10.3334/ORNLDAAC/1786 (download page: https://daac.ornl.gov/daacdata/cms/SLOPE_GPP_CONUS/data/, last access: 20 January 2021) (Jiang and Guan, 2020), and the real-time dataset is available upon request.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

Evaluating Alerting and Guidance Performance of a UAS Detect-And-Avoid System

A key challenge to the routine, safe operation of unmanned aircraft systems (UAS) is the development of detect-and-avoid (DAA) systems to aid the UAS pilot in remaining "well clear" of nearby aircraft. The goal of this study is to investigate the effect of alerting criteria and pilot response delay on the safety and performance of UAS DAA systems in the context of routine civil UAS operations in the National Airspace System (NAS). A NAS-wide fast-time simulation study was conducted to assess UAS DAA system performance with a large number of encounters and a broad set of DAA alerting and guidance system parameters. Three attributes of the DAA system were controlled as independent variables in the study to conduct trade-off analyses: UAS trajectory prediction method (dead-reckoning vs. intent-based), alerting time threshold (related to predicted time to LoWC), and alerting distance threshold (related to predicted Horizontal Miss Distance, or HMD). A set of metrics, such as the percentage of true positive, false positive, and missed alerts, based on signal detection theory and analysis methods utilizing the Receiver Operating Characteristic (ROC) curves were proposed to evaluate the safety and performance of DAA alerting and guidance systems and aid development of DAA system performance standards. The effect of pilot response delay on the performance of DAA systems was evaluated using a DAA alerting and guidance model and a pilot model developed to support this study. A total of 18 fast-time simulations were conducted with nine different DAA alerting threshold settings and two different trajectory prediction methods, using recorded radar traffic from current Visual Flight Rules (VFR) operations, and supplemented with DAA-equipped UAS traffic based on mission profiles modeling future UAS operations. Results indicate DAA alerting distance threshold has a greater effect on DAA system performance than DAA alerting time threshold or ownship trajectory prediction method. Further analysis on the alert lead time (time in advance of predicted loss of well clear at which a DAA alert is first issued) indicated a strong positive correlation between alert lead time and DAA system performance (i.e. the ability of the UAS pilot to maneuver the unmanned aircraft to remain well clear). While bigger distance thresholds had beneficial effects on alert lead time and missed alert rate, it also generated a higher rate of false alerts. In the design and development of DAA alerting and guidance systems, therefore, the positive and negative effects of false alerts and missed alerts should be carefully considered to achieve acceptable alerting system performance by balancing false and missed alerts. The results and methodology presented in this study are expected to help stakeholders, policymakers and standards committees define the appropriate setting of DAA system parameter thresholds for UAS that ensure safety while minimizing operational impacts to the NAS and equipage requirements for its users before DAA operational performance standards can be finalized.

UAS Detect-and-Avoid (DAA) System↗
DOE OSTI2023

A Deep Learning Pipeline for Optimizing Large-scale Phase Field Simulations

Phase field (PF) simulations are computationally expensive but remain a key analysis tool to understand the complex mechanisms of additive manufacturing (AM) processes. Each PF simulation-aided analysis requires thousands of node hours on leadership-class supercomputers. One of the main goals of these analyses is the study of microstructure evolution during the build process which begins with the onset of nucleation. Nucleation occurs under certain thermomechanical conditions which are not known a priori and many PF simulations are required to identify ranges of input thermo-mechanical parameters that can result in the onset of nucleation. Since many of the simulations do not result in nucleation, an analysis campaign often ends up wasting tremendous amounts of precious computing resources executing nucleation-absent simulations. The goal of this work is to design and train deep learning models to inform a PF simulation about the likelihood of the occurrence of nucleation in a future simulation time-step based on the state summary over a finite number of past time-steps of a running simulation. If the prediction determines that the running simulation is unlikely to reach nucleation in the allotted time, then its execution is stopped immediately ultimately resulting in vast reduction in wasted computations when accrued over all the PF simulations typically performed in a single or multiple analysis campaign(s). The paper presents the performance of a machine learning pipeline that uses a convolutional neural network (CNN) model to learn an embedding which is then used with a self-attention network to build a multi-task deep learning model to predict the likelihood of nucleation. The model also predicts the input parameters used in a simulation. Performance is compared with a baseline pipeline that uses an off-the-shelf LeNet-5 model to learn the initial embedding. Despite their smaller size, performance results indicate significant improvement in accuracy of the proposed models compared to the larger baseline models.

Kannan, Ramakrishnan {ramki}↗