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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 253 records · Page 14
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NASA NTRS1992

Lumley's energy cascade dissipation rate model for boundary-free turbulent shear flows

True dissipation occurs mainly at the highest wavenumbers where the eddy sizes are comparatively small. These high wavenumbers receive their energy through the spectral cascade of energy starting with the largest eddies spilling energy into the smaller eddies, passing through each wavenumber until it is dissipated at the microscopic scale. However, a small percentage of the energy does not spill continuously through the cascade but is instantly passed to the higher wavenumbers. Consequently, the smallest eddies receive a certain amount of energy almost immediately. As the spectral energy cascade continues, the highest wavenumber needs a certain time to receive all the energy which has been transferred from the largest eddies. As such, there is a time delay, of the order of tau, between the generation of energy by the largest eddies and the eventual dissipation of this energy. For equilibrium turbulence at high Reynolds numbers, there is a wide range where energy is neither produced by the large eddies nor dissipated by viscosity, but is conserved and passed from wavenumber to higher wavenumbers. The rate at which energy cascades from one wavenumber to another is proportional to the energy contained within that wavenumber. This rate is constant and has been used in the past as a dissipation rate of turbulent kinetic energy. However, this is true only in steady, equilibrium turbulence. Most dissipation models contend that the production of dissipation is proportional to the production of energy and that the destruction of dissipation is proportional to the destruction of energy. In essence, these models state that the change in the dissipation rate is proportional to the change in the kinetic energy. This assumption is obviously incorrect for the case where there is no production of turbulent energy, yet energy continues to cascade from large to small eddies. If the time lag between the onset on the energy cascade to the destruction of energy at the microscale can be modeled, then there will be a better representation of the dissipation process. Development of an energy cascade time scale equation is discussed.

Duncan, B. S.↗
NASA NTRS2017

Biosignatures in the Context of Low Energy Flux

Many of the features that are thought of as biosignatures - including the mediation of chemical and physical processes with speed, specificity, and selectivity - result directly or indirectly from life's unique capability to mediate and direct energy flux. As such, it is important to consider the impact that differences in energy flux may have on the quantity and quality of evidence for life. Earth differs from every other body in our solar system in the magnitude of biologically-usable energy flux into a liquid water environment. On a global basis, the capture of light energy into photosynthesis and the flux of chemical energy represented in the products of that photosynthesis (organic material + O2) are about six and four orders of magnitude larger, respectively, than the flux of energy represented in geochemical sources. Our conception of what an inhabited world "looks like" and our intuition about how to search for life are based in this high-energy context. Energy fluxes on worlds beyond Earth may be better approximated by the million-fold smaller flux provided to Earth's biosphere by geochemical sources. As a result, the nature, abundance, and quality of evidence for life that could be expected on an inhabited extraterrestrial world within our solar system may differ profoundly from that found on Earth. Understanding this potential difference in quantitative terms provides important context for the formulation of life detection strategies. The influence of energy flux on biosignatures can be evaluated through reference to the two basic purposes into which life partitions energy flux: (1) Life expends energy to sustain existing biomass in a metabolic steady state (metabolically functional but non-growing). The formal representation of this relationship in the traditional microbiology literature equates biomass directly with energy flux. The direct implication is that worlds having lower energy flux will have correspondingly lower potential to support biomass. Life detection strategies that directly target extant organisms should therefore be prepared to encounter average biomass densities that may be many orders of magnitude smaller than those found in most of Earth's surface environments (2) Life expends energy to synthesize new biomass. An end-member case in which new biomass is created at the energy-limited rate and the corresponding cells are immediately destroyed (so that the energy partitioned to cell maintenance is minimized) establishes an upper bound on the rate at which biological material can enter a bulk global pool. For a specified bulk concentration [i] of any particular biological compound, i, or for biologically produced matter overall, this synthesis rate, R (sub i), defines a characteristic time scale tau (sub i) equals [i] divided by R (sub i). tau (sub i) can be thought of as (a) the minimum time required for biosynthesis to yield a specific bulk concentration (e.g., a detection threshold) of i, and (b) the average residence time of i within a bulk pool when [i] is held in steady state through a balance between biosynthesis and attrition by physical, chemical, or biological consumption. tau (sub i) becomes an important quantity in considering the potential utility of enantiomeric excess (as a product of homochiral biosynthesis) as a biosignature. Spontaneous racemization of amino acids acts to "erase" the signature of homochiral synthesis over time scales that may range from hundreds to hundreds of thousands of years, depending on temperature. For environments in which low energy flux translates to low rates of biosynthesis, including the synthesis of homochiral amino acids, amino acid residence times in pools having detectable concentrations may compare to or significantly exceed the time scale for racemization. This and similar consequences of long residence times should be considered in the formulation of life detection strategies based on detection of biologically-produced species. Fluxes of biologically-useful energy on potentially habitable worlds within our solar system are, at present, not well constrained. Improving such constraint has the potential to inform priorities in the formulation and targeting of search-for-life strategies, based on the implications of energy flux for the abundance and quality of biosignatures overall, and in specific categories.

ENERGY FLUX↗
NASA NTRS2014

Renewable Energy at NASA's Johnson Space Center

NASA's Johnson Space Center has implemented a great number of renewable energy systems. Renewable energy systems are necessary to research and implement if we humans are expected to continue to grow and thrive on this planet. These systems generate energy using renewable sources - water, wind, sun - things that we will not run out of. Johnson Space Center is helping to pave the way by installing and studying various renewable energy systems. The objective of this report will be to examine the completed renewable energy projects at NASA's Johnson Space Center for a time span of ten years, beginning in 2003 and ending in early 2014. This report will analyze the success of each project based on actual vs. projected savings and actual vs. projected efficiency. Additionally, both positive and negative experiences are documented so that lessons may be learned from past experiences. NASA is incorporating renewable energy wherever it can, including into buildings. According to the 2012 JSC Annual Sustainability Report, there are 321,660 square feet of green building space on JSC's campus. The two projects discussed here are major contributors to that statistic. These buildings were designed to meet various Leadership in Energy and Environmental Design (LEED) Certification criteria. LEED Certified buildings use 30 to 50 percent less energy and water compared to non-LEED buildings. The objectives of this project were to examine data from the renewable energy systems in two of the green buildings onsite - Building 12 and Building 20. In Building 12, data was examined from the solar photovoltaic arrays. In Building 20, data was examined from the solar water heater system. By examining the data from the two buildings, it could be determined if the renewable energy systems are operating efficiently. Objectives In Building 12, the data from the solar photovoltaic arrays shows that the system is continuously collecting energy from the sun, as shown by the graph below. Building 12 has two solar inverters, located on the second floor, that collected the data from the solar photovoltaic arrays. The data displayed here is the total energy produced by the system. These are cumulative amounts, so the last point on the graph shows all of the energy collected from the system since the start of its operation. The data shown here was manually collected from the solar inverters. However, the data is also automatically recorded through EBI. Through analysis of both sets of data it was determined that the EBI data was faulty. For example, from the manually collected data it can be determined that a total of 73 kWh of energy was collected between the dates of 1/16/2014 – 1/22/2014. The EBI data reports that approximately 17800 kWh of energy was collected during the same time frame. Not only does this exceed the time frame examined, but it also exceeds the total energy collected from the start of collection as recorded from the inverters. This leads to the belief that there is a malfunction with the automatic recording of the energy. In Building 20, data was examined from the solar water heater dating back many months and found that the pump for the solar water heater system was not operating properly, as exhibited in the graph shown below. The pump operates on a solar energy system, meaning that it collects energy throughout the day from the sun. Because of this, the system would stop operating shortly after the sun set because of a lack of sunlight. At that point, the graph should show a zero flow rate, but as exhibited in the graph below, that is not the case. It is clearly shown that the pump is continuously operating, even during the night. It was also observed that the majority of the time the pump would not turn on at all, despite good weather conditions. This led to the conclusion that the pump is malfunctioning, and needs to be examined and fixed.

McDowall, Lindsay↗
NASA NTRS2016

Global Energetics of Solar Flares: Nonthermal Energies - Part III

This study entails the third part of a global flare energetics project, in which Ramaty High-Energy Solar Spectroscopic Imager (RHESSI) data of 191 M and X-class flare events from the first 3.5 years of the Solar Dynamics Observatory mission are analyzed. We fit a thermal and a nonthermal component to RHESSI spectra, yielding the temperature of the differential emission measure (DEM) tail, the nonthermal power-law slope and flux, and the thermal nonthermal cross-over energy eco. From these parameters, we calculate the total nonthermal energy E(sub nt) in electrons with two different methods: (1) using the observed cross-over energy e(sub co) as low-energy cutoff, and (2) using the low-energy cut off e(sub wt) predicted by the warm thick-target bremsstrahlung model of Kontar et al. Based on a mean temperature of T(sub e) = 8.6 MK in active regions, we find low-energy cutoff energies of e(sub wt) = 6.2 +/-1.6 keV for the warm-target model, which is significantly lower than the cross-over energies e(sub co) = 21 +/- 6 keV. Comparing with the statistics of magnetically dissipated energies E(sub mag) and thermal energies E(sub th) from the two previous studies, we find the following mean (logarithmic) energy ratios with the warm-target model: E(sub nt) = 0.41E(sub mag), E(sub th) = 0.08 E(sub mag), and E(sub th) = 0.15 E(sub nt). The total dissipated magnetic energy exceeds the thermal energy in 95% and the nonthermal energy in 71% of the flare events, which confirms that magnetic reconnection processes are sufficient to explain flare energies. The nonthermal energy exceeds the thermal energy in 85% of the events, which largely confirms the warm thick-target model.

Aschwanden, Markus J.↗