SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Superposition method for predicting tube wall temperatures with gas property and heating rate axial variation, noting application to gas flow problems
The case of a cold gas in the absence of external force fields is considered. Since the only energy involved is kinetic energy, the total kinetic action (i.e., the space-time integral of the kinetic energy density) should serve as the total free-energy functional in this case, and as such should be a local minimum for all possible fluctuations about stable flow. This conjecture is tested by calculating explicit, manifestly covariant expressions for the first and second variations of the total kinetic action in the context of Lagrangian kinematics. The general question of the correlation between physical stability and the convexity of any action integral that can be interpreted as the total free-energy functional of the flow is discussed and illustrated for the cases of rectillinear and rotating shearing flows.
Attention is given to the effect of changes in the dynamic pressure of the solar wind on the structure of a centrifugally driven planetary wind from Jupiter. It is suggested that dynamic pressure variations can induce a transition between a super-Alfvenic wind and a sub-Alfvenic wind breeze on Jupiter's dayside. This could possibly account for the observed large-scale changes in the structure of Jupiter's outer magnetosphere. An attempt is then made to conceptually merge planetary wind models of Jupiter's outer magnetosphere with reconnection models of Jupiter's outer magnetosphere.
The annual variation of the total amount of ozone over central Switzerland and the partial pressures in each of 7 layers from the surface to 7.8 m zeta shows the pattern representative of mid-latitude ozone: summer maximum in the troposphere, spring maximum in the lower stratosphere up to 30 mb and summer maximum in the middle stratosphere up to approx. mb. It was also shown that at the level of the ozone maximum the ozone partial pressure has a pronounced period of about 26 months. Total ozone and the ozone concentration in the different layers have marginally significant (at plus or minus sigma) correlations with relative sunspot number. The time lag for these correlations is long in the troposphere (about 36 months) but decreases with height to the level of ozone maximum (to about 2 months). A similar analysis of the data derived from the ozonesonde program at Hohenpeissenberg, Germany (GFR) gave completely consistent results with those discussed above.
The vertical structure of the nighttime thermosphere and exosphere of Venus was discussed. A comparison of the day and nighttime profiles indicates, contrary to the model of Dickinson and Riley (1977), that densities (principally atomic oxygen) dropped sharply from day to night. It was suggested either that the lower estimates were related to cooler exospheric temperatures at night or that the atomic bulge was flatter than expected at lower altitudes. Large periodic oscillations, in both density and inferred exospheric temperatures, were detected with periods of 5 to 6 days. The possibility that cyclic variations in the thermosphere and stratosphere were caused by planetary-scale waves, propagated upward from the lower atmosphere, was investigated using simultaneous temperature measurements obtained by the Venus radiometric temperature experiment (VORTEX). Inferred exospheric temperatures in the morning were found to be lower than in the evening as if the atmosphere rotated in the direction of the planet's rotation, similar to that of earth. Superrotation of the thermosphere and exosphere was discussed as a possible extension of the 4-day cyclic atmospheric rotation near the cloud tops.
Nitrous oxide (N 2 O) is the third most important long-lived greenhouse gas and agriculture is the largest source of N 2 O emissions. Curbing N 2 O emissions requires understanding influences on the flux and sources of N 2 O. We measured flux and evaluated microbial sources of N 2 O using site preference ( S P ; the intramolecular distribution of 15 N in N 2 O) in flux chambers from a grassland tilling and agricultural fertilization experiments and atmosphere. We identified values greater than that of the average atmosphere to reflect nitrification and/or fungal denitrification and those lower than atmosphere as increased denitrification. Our spectroscopic approach was based on an extensive calibration with 18 standards that yielded S P accuracy and reproducibility of 0.7 ‰ and 1.0 ‰, respectively, without preconcentration. Chamber samples from the tilling experiment taken ~ monthly over a year showed a wide range in N 2 O flux (0–1.9 g N 2 O-N ha -1 d -1 ) and S P (- 1.8 to 25.1 ‰). Flux and S P were not influenced by tilling but responded to sampling date. Large fluxes occurred in October and May in no-till when soils were warm and moist and during a spring thaw, an event likely representing release of N 2 O accumulated under snow cover. These high fluxes could not be ascribed to a single microbial process as S P differed among chambers. However, the year-long S P and flux data for no-till showed a slight direct relationship suggesting that nitrification increased with flux. The comparative data in till showed an inverse relationship indicating that high flux events are driven by denitrification. Corn ( Zea mays ) showed high fluxes and S P values indicative of nitrification ~ 4 wk after fertilization with subsequent declines in S P indicating denitrification. Although there was no effect of fertilizer treatment on flux or S P in switchgrass ( Panicum virgatum) , high fluxes occurred ~1 month after fertilization. In both treatments, S P was indicative of denitrification in many instances, but evidence of nitrification/fungal denitrification also prevailed. At 2 m atmospheric N 2 O S P had a range of 31.1 ‰ and 14.6 ‰ in the grassland tilling and agricultural fertilization experiments, respectively. These data suggest the influence of soil microbial processes on atmospheric N 2 O and argue against the use of the global average atmospheric S P in isotopic modeling approaches.
Aims: As woody plants encroach into grassland ecosystems, we expect that altered plant-soil interactions will lead to changes in the microbial processes that affect carbon storage and nutrient cycling. Specifically, this research aimed to address how (1) soil chemistry, (2) microbial nutrient demand, and (3) the rate and source of potential soil C mineralization vary spatially under individual woody shrubs of varying size within a mesic grassland. Methods: Here, we collected soil samples from the center, the midpoint between the center and edge, the edge, and the shrub-grass ecotone of multiple Cornus drummondii shrubs across a shrub-size gradient in infrequently burned tallgrass prairie. Results: We found total soil carbon and total soil nitrogen increased with shrub size in every location but the edge. Microbial demand for nitrogen also increased as shrubs increased in size. Across all shrub sizes and sampling locations, potential soil carbon mineralization rates were higher when microbes broke down proportionally more shrub-derived (C 3 ) organic matter than grass-derived (C 4 ) organic matter. Conclusions: Our results suggest that the spatio-temporal context of woody encroachment is critical for understanding its impact on belowground microbial processes. In this ecosystem, a longer period of occupancy by woody plants increases potentially mineralizable carbon.
Not provided.
Identification of atmospheric conditions within a multivariate atmospheric dataset is a necessary step in the validation of wind plant control strategies. Most often, operating conditions are characterized in terms of aggregated observations and assume that the atmosphere is 'quasi-steady'. Aggregation of observations without regard to covariance between time series discounts the dynamical nature of the atmosphere and is not sufficiently representative of wind plant operating conditions. Identification and characterization of continuous time periods with atmospheric conditions that have a high value for analysis or simulation sets the stage for more advanced model validation and the development of real-time control and operation strategies. Controlling observational data for statistical stationarity highlights significant enhancements to the power production of waked turbines under wake steering wind plant control. Considering the combined energy ratio of the turbine to which yaw offsets are prescribed as well as the waked turbine show only moderate improvements when filtering for total validation. The same quality control that highlights wake steering also serves to underpin the off-nominal operation of the controlled turbine.
Predicting food web structure in future climates is a pressing goal of ecology. These predictions may be impossible without a solid understanding of the factors that structure current food webs. Here, the most fundamental aspect of food web structure—the relationship between the number of links and species—is still poorly understood. Some species interactions may be physically or physiologically ‘forbidden'—like consumption by non-consumer species—with possible consequences for food web structure. We show that accounting for these ‘forbidden interactions' constrains the feasible link-species space, in tight agreement with empirical data. Rather than following one particular scaling relationship, food webs are distributed throughout this space according to shared biotic and abiotic features. Our study provides new insights into the long-standing question of which factors determine this fundamental aspect of food web structure.
Here, the complexity of many-body quantum wave functions is a central aspect of several fields of physics and chemistry where nonperturbative interactions are prominent. Artificial neural networks (ANNs) have proven to be a flexible tool to approximate quantum many-body states in condensed matter and chemistry problems. In this work we introduce a neural-network quantum state ansatz to model the ground-state wave function of light nuclei, and approximately solve the nuclear many-body Schrodinger equation. Using efficient stochastic sampling and optimization schemes, our approach extends pioneering applications of ANNs in the field, which present exponentially scaling algorithmic complexity. We compute the binding energies and point-nucleon densities of A ≤ 4 nuclei as emerging from a leading-order pionless effective field theory Hamiltonian. We successfully benchmark the ANN wave function against more conventional parametrizations based on two- and three-body Jastrow functions, and virtually exact Green's function Monte Carlo results.
Submitted to SolarPACES 2023 Proceedings.
Flanged australite and australasian microtektites chemical compositions, using electron microprobe analysis
Explore the source record for details and available documents.
Explore the source record for details and available documents.