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At least 811 records · Page 45

Photovoltaic Engineering Testbed Designed for Calibrating Photovoltaic Devices in Space

Accurate prediction of the performance of solar arrays in space requires that the cells be tested in comparison with a space-flown standard. Recognizing that improvements in future solar cell technology will require an ever-increasing fidelity of standards, the Photovoltaics and Space Environment Branch at the NASA Glenn Research Center, in collaboration with the Ohio Aerospace Institute, designed a prototype facility to allow routine calibration, measurement, and qualification of solar cells on the International Space Station, and then the return of the cells to Earth for laboratory use. For solar cell testing, the Photovoltaic Engineering Testbed (PET) site provides a true air-mass-zero (AM0) solar spectrum. This allows solar cells to be accurately calibrated using the full spectrum of the Sun.

Landis, Geoffrey A.↗

Thermodynamic Structure of Collision-Dominated Expanding Plasma: Heating of Interplanetary Coronal Mass Injections

We investigate the thermodynamic structure of interplanetary coronal mass ejections (ICMEs) using combined surveys of the ejecta between 0.3 and 20 AU. ICMEs are shown to have a moderate expansion in the solar wind compared with theoretical predictions. The expansion seems to be governed by a polytrope with gamma approx. 1.3 in this distance range. We find that Coulomb collisions are important contributors to the ion-ion equilibration process in the ICME plasma. The alpha-proton differential speed quickly drops to below 10 km/s due to strong Coulomb collisions. However, the two species of particles are far from thermal equilibrium with a temperature ratio T(sub alpha/T(sub p) = 4-6, suggestive of a preferential heating of alpha particles. The plasma heating rate as a function of heliocentric &stance required for the temperature profile is deduced by taking into account the expansion and energy transfer between protons and alphas via Coulomb collisions. The turbulence dissipation rate is also inferred from the inertial range power spectrum of magnetic fluctuations within ICMEs. Comparison of the turbulence dissipation rate with the required heating rate shows that turbulence dissipation seems sufficient to explain the ICME heating. Sources powering the turbulence are also investigated by examining the instabilities induced by temperature anisotropies and energy deposition by pickup ions.

Liu, Y.↗

Solar Dynamics Observatory (SDO) HGAS Induced Jitter

This paper presents the results of a comprehensive assessment of High Gain Antenna System induced jitter on the Solar Dynamics Observatory. The jitter prediction is created using a coupled model of the structural dynamics, optical response, control systems, and stepper motor actuator electromechanical dynamics. The paper gives an overview of the model components, presents the verification processes used to evaluate the models, describes validation and calibration tests and model-to-measurement comparison results, and presents the jitter analysis methodology and results.

Liu, Alice↗

Atomic Oxygen Fluence Monitor

This innovation enables a means for actively measuring atomic oxygen fluence (accumulated atoms of atomic oxygen per area) that has impinged upon spacecraft surfaces. Telemetered data from the device provides spacecraft designers, researchers, and mission managers with real-time measurement of atomic oxygen fluence, which is useful for prediction of the durability of spacecraft materials and components. The innovation is a compact fluence measuring device that allows in-space measurement and transmittance of measured atomic oxygen fluence as a function of time based on atomic oxygen erosion yields (the erosion yield of a material is the volume of material that is oxidized per incident oxygen atom) of materials that have been measured in low Earth orbit. It has a linear electrical response to atomic oxygen fluence, and is capable of measuring high atomic oxygen fluences (up to >10(exp 22) atoms/sq cm), which are representative of multi-year low-Earth orbital missions (such as the International Space Station). The durability or remaining structural lifetime of solar arrays that consist of polymer blankets on which the solar cells are attached can be predicted if one knows the atomic oxygen fluence that the solar array blanket has been exposed to. In addition, numerous organizations that launch space experiments into low-Earth orbit want to know the accumulated atomic oxygen fluence that their materials or components have been exposed to. The device is based on the erosion yield of pyrolytic graphite. It uses two 12deg inclined wedges of graphite that are over a grit-blasted fused silica window covering a photodiode. As the wedges erode, a greater area of solar illumination reaches the photodiode. A reference photodiode is also used that receives unobstructed solar illumination and is oriented in the same direction as the pyrolytic graphite covered photodiode. The short-circuit current from the photodiodes is measured and either sent to an onboard data logger, or transmitted to a receiving station on Earth. By comparison of the short-circuit currents from the fluence-measuring photodiode and the reference photodiode, one can compute the accumulated atomic oxygen fluence arriving in the direction that the fluence monitor is pointing. The device produces a signal that is linear with atomic oxygen fluence using a material whose atomic oxygen erosion yield has been measured over a period of several years in low-Earth orbit.

Banks, Bruce A.↗

Wind Magnetic Clouds for 2010-2012: Model Parameter Fittings, Associated Shock Waves, and Comparisons to Earlier Periods

We fitted the parameters of magnetic clouds (MCs) as identified in the Wind spacecraft data from early 2010 to the end of 2012 using the model of Lepping, Jones, and Burlaga (J. Geophys. Res. 95, 1195, 1990). The interval contains 48 MCs and 39 magnetic cloud-like (MCL) events. This work is a continuation of MC model fittings of the earlier Wind sets, including those in a recent publication, which covers 2007 to 2009. This period (2010 - 2012) mainly covers the maximum portion of Solar Cycle 24. Between the previous and current interval, we document 5.7 years of MCs observations. For this interval, the occurrence frequency of MCs markedly increased in the last third of the time. In addition, over approximately the last six years, the MC type (i.e. the profile of the magnetic-field direction within an MC, such as North-to-South, South-to-North, all South) dramatically evolved to mainly North-to-South types when compared to earlier years. Furthermore, this evolution of MC type is consistent with global solar magnetic-field changes predicted by Bothmer and Rust (Coronal Mass Ejections, 139, 1997). Model fit parameters for the MCs are listed for 2010 - 2012. For the 5.7 year interval, the observed MCs are found to be slower, weaker in estimated axial magnetic-field intensity, and shorter in duration than those of the earlier 12.3 years, yielding much lower axial magnetic-field fluxes. For about the first half of this 5.7 year period, i.e. up to the end of 2009, there were very few associated MC-driven shock waves (distinctly fewer than the long-term average of about 50 % of MCs). But since 2010, such driven shocks have increased markedly, reflecting similar statistics as the long-term averages. We estimate that 56 % of the total observed MCs have upstream shocks when the full interval of 1995 - 2012 is considered. However, only 28 % of the total number of MCLs have driven shocks over the same period. Some interplanetary shocks during the 2010 - 2012 interval are seen to apparently occur without an obvious MC-driver, probably indicating an encounter with a distant flank of a MC-driven shock. Some of these may be driven by a different kind of structure, however.

Magnetic clouds↗

Multi-Year Characterization of PSCs Using Solar Occultation Satellite Observations

POAM solar occultation observations from1994 to present are studied for the purpose of determining Type I PSC formation characteristics and winter-long evolution. This information is critical to an improved understanding and predictive capability of stratospheric ozone depletion. Solar occultation satellite observations of these clouds yields more continuous and wide-spread information than can be obtained from aircraft, balloon, or ground-based observations. This multi-winter PSC study is augmented by the use of our Type Ia/Ib discrimination scheme. Recent studies of PSC formation made with POAM observations and simulations during the 1999-2000 Arctic winter have shown characteristics that shed light on the formation mechanisms responsible for Type Ia solid phase PSCs. This study examines PSC observations from many years on a common basis to see if the characteristics observed & cuing the 1999-2000 Arctic winter ai-e observed in other years and if other characteristics can be identified. The results show that Type Ia PSCs form at the beginning of the winter, within several days of the fxst drop in temperature below TNAT, and peak early in the winter. Type Ia PSCs typically outnumber Ib PSCs over the winter, especially at the beginning of the winter. Type Ia and Ib PSC observations continue throughout the winter. Micro-physical models of PSC formation must match these observed characteristics. Some models predict that temperatures must be more 5 K below T-NAT for five days before significant freezing can occur. This is not seen in the POAM observations. Differences in PSC characte ristics between the first two Arctic winters (1 994- 1995 and 1995- 1 996) and later winters also suggest the influence of volcanic perturb ations on PSC formation. Type Ia and Ib PSC characteristics observed by POAM III and SAGE III for the 2002-2003 Arctic winter are compared.

Strawa, A. W.↗

Ultra-fine-scale filamentary structures in the Outer Corona and the Solar Magnetic Field

Filamentary structures following magnetic field lines pervade the Sun's atmosphere and offer us insight into the solar magnetic field. Radio propagation measurements have shown that the smallest filamentary structures in the solar corona are more than 2 orders of magnitude finer than those seen in solar imaging. Here we use radio Doppler measurements to characterize their transverse density gradient and determine their finest scale in the outer corona at 20-30 R(circled dot operator), where open magnetic fields prevail. Filamentary structures overly active regions have the steepest gradient and finest scale, while those overlying coronal holes have the shallowest gradient and least finest scale. Their organization by the underlying corona implies that these subresolution structures extend radially from the entire Sun, confirming that they trace the coronal magnetic field responsible for the radial expansion of the solar wind. That they are rooted all over the Sun elucidates the association between the magnetic field of the photosphere and that of the corona, as revealed by the similarity between the power spectra of the photospheric field and the coronal density fluctuations. This association along with the persistence of filamentary structures far from the Sun demonstrate that subresolution magnetic fields must play an important role not only in magnetic coupling of the photosphere and corona, but also in coronal heating and solar wind acceleration through the process of small-scale magnetic reconnection. They also explain why current widely used theoretical models that extrapolate photospheric magnetic fields into the corona do not predict the correct source of the solar wind.

Sun : Corona↗

Forecasting Solar-Thermal Systems Performance under Transient Operation Using a Data-Driven Machine Learning Approach Based on the Deep Operator Network Architecture

Modeling and prediction of the dynamic behavior of thermal systems operating under intermittent energy input and variable load requirements represent one of the greatest challenges in the development of efficient and reliable renewable-based power generation technologies. In this work, a data-driven machine learning modeling framework was developed based on a modified version of the Deep Operator Network architecture where the time coordinate in the trunk net is replaced with historical data of the predicting quantity. The modeling framework can be used to accurately predict the performance of renewable-based energy conversion technologies including wind- and solar-based power plants. This novel framework was applied on a solar-thermal system that consists of a solar collection loop using a flat plate collector, a power generation loop comprising an Organic Rankine Cycle, and a thermal energy storage tank connecting both loops. Variable solar irradiance, air temperature, and power load profiles were used by the Deep Operator Network to predict the State-of-Charge and the efficiency of the thermal system for several days. The results were compared with the State-of-Charge and efficiency functions calculated using a physics-based model. For a simple operation scenario, characterized by a clear sky solar irradiance profile and constant load, the standard deviation in the State-of-Charge prediction by Deep Operator Network is below 0.9% during a seven-day prediction time horizon. For the most realistic operation scenario that considers real solar irradiance and a rough load profile, the maximum standard deviation in the predictions for the State-of-Charge and efficiency are below 6.8% and 2.5%, respectively. A comparison between Deep Operator Network and Long Short Term Memory network was also performed. In general, both networks predict very well the State-of-Charge for different data density conditions; however, a higher accuracy, with a standard deviation below 2.0%, is obtained by the Deep Operator Network during three and half days using sparser training data of 20-minute points. The same accuracy for the State-of-Charge prediction with the Long Short Term Memory network is achieved only for 14 h. Average standard deviations for the State-of-Charge prediction of 1.1% with the Deep Operator Network and 1.5% with the Long Short Term Memory network are obtained for a four-day prediction time using a denser training data of 5-minute points.

DeepONet↗

Evaluation of concentrated space solar arrays using computer modeling

A general approach is developed for predicting the power output of a concentrator enhanced photovoltaic space array. A ray trace routine determines the concentrator intensity arriving at each solar cell. An iterative calculation determines the cell's operating temperature since cell temperature and cell efficiency are functions of one another. The end result of the iterative calculation is that the individual cell's power output is determined as a function of temperature and intensity. Circuit output is predicted by combining the individual cell outputs using the single diode model of a solar cell. Concentrated array characteristics such as uniformity of intensity and operating temperature at various points across the array are examined using computer modeling techniques. An illustrative example is given showing how the output of an array can be enhanced using solar concentration techniques.

Rockey, D. E.↗

Terrestrial cooling and solar variability

Observational evidence from surface temperature records is presented and discussed which suggests a significant cooling trend over the Northern Hemisphere from 1940 to the present. This cooling trend is associated with an increase of the latitudinal gradient of temperature and the lapse rate, as predicted by climate models with decreased solar input and feedback mechanisms. Evidence suggests that four of these 80- to 100-year cycles of global surface temperature fluctuation may have occurred, and in succession, from 1600 to the present. Interpretation of sunspot activity were used to infer a direct thermal response of terrestrial temperature to solar variability on the time scale of the Gleissberg cycle (90 years, an amplitude of the 11-year cycles). A physical link between the sunspot activity and the solar parameter is hypothesized. Observations of sensible heat flux by stationary planetary waves and transient eddies, as well as general circulation modeling results of these processes, were examined from the viewpoint of the hypothesis of cooling due to reduced insolation.

Agee, E. M.↗

Monte Carlo Computational Modeling of Atomic Oxygen Interactions

Computational modeling of the erosion of polymers caused by atomic oxygen in low Earth orbit (LEO) is useful for determining areas of concern for spacecraft environment durability. Successful modeling requires that the characteristics of the environment such as atomic oxygen energy distribution, flux, and angular distribution be properly represented in the model. Thus whether the atomic oxygen is arriving normal to or inclined to a surface and whether it arrives in a consistent direction or is sweeping across the surface such as in the case of polymeric solar array blankets is important to determine durability. When atomic oxygen impacts a polymer surface it can react removing a certain volume per incident atom (called the erosion yield), recombine, or be ejected as an active oxygen atom to potentially either react with other polymer atoms or exit into space. Scattered atoms can also have a lower energy as a result of partial or total thermal accommodation. Many solutions to polymer durability in LEO involve protective thin films of metal oxides such as SiO2 to prevent atomic oxygen erosion. Such protective films also have their own interaction characteristics. A Monte Carlo computational model has been developed which takes into account the various types of atomic oxygen arrival and how it reacts with a representative polymer (polyimide Kapton H) and how it reacts at defect sites in an oxide protective coating, such as SiO2 on that polymer. Although this model was initially intended to determine atomic oxygen erosion behavior at defect sites for the International Space Station solar arrays, it has been used to predict atomic oxygen erosion or oxidation behavior on many other spacecraft components including erosion of polymeric joints, durability of solar array blanket box covers, and scattering of atomic oxygen into telescopes and microwave cavities where oxidation of critical component surfaces can take place. The computational model is a two dimensional model which has the capability to tune the interactions of how the atomic oxygen reacts, scatters, or recombines on polymer or nonreactive surfaces. In addition to the specification of atomic oxygen arrival details, a total of 15 atomic oxygen interaction parameters have been identified as necessary to properly simulate observed interactions and resulting polymer erosion that have been observed in LEO. The tuning of the Monte Carlo model has been accomplished by adjusting interaction parameters so the erosion patterns produced by the model match those from several actual LEO space experiments. Surface texturing in LEO can also be predicted by the model. Such comparison of space tests with ground laboratory experiments have enabled confidence in ground laboratory lifetime prediction of protected polymers. Results of Monte Carlo tuning, examples of surface texturing and undercutting erosion prediction, and several examples of how the model can be used to predict other LEO and Mars orbital space results are presented.

Monte Carlo Modeling↗

Monte Carlo Computational Modeling of Atomic Oxygen Interactions

Computational modeling of the erosion of polymers caused by atomic oxygen in low Earth orbit (LEO) is useful for determining areas of concern for spacecraft environment durability. Successful modeling requires that the characteristics of the environment such as atomic oxygen energy distribution, flux, and angular distribution be properly represented in the model. Thus whether the atomic oxygen is arriving normal to or inclined to a surface and whether it arrives in a consistent direction or is sweeping across the surface such as in the case of polymeric solar array blankets is important to determine durability. When atomic oxygen impacts a polymer surface it can react removing a certain volume per incident atom (called the erosion yield), recombine, or be ejected as an active oxygen atom to potentially either react with other polymer atoms or exit into space. Scattered atoms can also have a lower energy as a result of partial or total thermal accommodation. Many solutions to polymer durability in LEO involve protective thin films of metal oxides such as SiO2 to prevent atomic oxygen erosion. Such protective films also have their own interaction characteristics. A Monte Carlo computational model has been developed which takes into account the various types of atomic oxygen arrival and how it reacts with a representative polymer (polyimide Kapton H) and how it reacts at defect sites in an oxide protective coating, such as SiO2 on that polymer. Although this model was initially intended to determine atomic oxygen erosion behavior at defect sites for the International Space Station solar arrays, it has been used to predict atomic oxygen erosion or oxidation behavior on many other spacecraft components including erosion of polymeric joints, durability of solar array blanket box covers, and scattering of atomic oxygen into telescopes and microwave cavities where oxidation of critical component surfaces can take place. The computational model is a two dimensional model which has the capability to tune the interactions of how the atomic oxygen reacts, scatters, or recombines on polymer or nonreactive surfaces. In addition to the specification of atomic oxygen arrival details, a total of 15 atomic oxygen interaction parameters have been identified as necessary to properly simulate observed interactions and resulting polymer erosion that have been observed in LEO. The tuning of the Monte Carlo model has been accomplished by adjusting interaction parameters so the erosion patterns produced by the model match those from several actual LEO space experiments. Surface texturing in LEO can also be predicted by the model. Such comparison of space tests with ground laboratory experiments have enabled confidence in ground laboratory lifetime prediction of protected polymers. Results of Monte Carlo tuning, examples of surface texturing and undercutting erosion prediction, and several examples of how the model can be used to predict other LEO and Mars orbital space results are presented.

Atomic Oxygen↗

Probabilistic Model for Low Altitude Trapped Proton Fluxes

A new approach is developed for the assessment of low altitude trapped proton fluxes for future space missions. Low altitude fluxes are dependent on solar activity levels due to the resulting heating and cooling of the upper atmosphere. However, solar activity levels cannot be accurately predicted far enough into the future to accommodate typical spacecraft mission planning. Thus, the approach suggested here is to evaluate the trapped proton flux as a function of confidence level for a given mission time period. This is possible because of a recent advance in trapped proton modeling that uses the solar 10.7 cm radio flux, a measure of solar cycle activity, to calculate trapped proton fluxes as a continuous function of time throughout the solar cycle. This trapped proton model is combined with a new statistical description of the 10.7 cm flux to obtain the probabilistic model for low altitude trapped proton fluxes. Results for proton energies ranging from 1.5 to 81.3 MeV are examined as a function of time throughout solar cycle 22 for various orbits. For altitudes below 1000 km, fluxes are significantly higher and energy spectra are significantly harder than those predicted by the AP8 model.

Xapsos, M. A.↗

Solar cycle variations in the neutral exosphere inferred from the location of the Venus bow shock

Solar UV and EUV varies significantly during the solar cycle. Pioneer Venus can measure this variation both directly and indirectly. A direct measure of the EUV is obtained from the photoelectron current of the Langmuir probe when the spacecraft is in the solar wind. The indirect measure is by monitoring the location of the Venus bow shock. The UV and EUV both heat the upper atmosphere and ionize it. When solar activity is high, the upper atmosphere should be ionized more rapidly. This effect adds a greater number of planetary ions to the magnetosheath plasma as it flows by Venus. It is this increase in mass flow that causes the Venus bow shock to move away from its solar minimum location. Pioneer Venus has now monitored the location of the bow shock for an entire solar cycle. The bow shock location is well correlated with the variation in EUV flux as measured by the Langmuir probe. The bow shock is farther from Venus than expected from the sunspot number or 10.7 cm solar radio flux, indicating that solar UV radiation may be even stronger at the present time than would be predicted from the relationships determined during the previous solar cycle.

Russell, C. T.↗

Electron–Ion Temperature Ratio in Astrophysical Shocks

Collisionless shock waves in supernova remnants and the solar wind heat electrons less effectively than they heat ions, as is predicted by kinetic simulations. However, the values of T e /T p inferred from the Hα profiles of supernova remnant shocks behave differently as a function of Mach number or Alfvén Mach number than what is measured in the solar wind or predicted by simulations. Here we determine T e /T p for supernova remnant shocks using Hα profiles, shock speeds from proper motions, and electron temperatures from X-ray spectra. We also improve the estimates of sound speed and Alfvén speed used to determine Mach numbers. We find that the Hα determinations are robust and that the discrepancies among supernova remnant shocks, solar wind shocks, and computer-simulated shocks remain. We discuss some possible contributing factors, including shock precursors, turbulence, and varying preshock conditions.

79 ASTRONOMY AND ASTROPHYSICS↗

Predictability of weather and climate in a coupled ocean-atmosphere model: A dynamical systems approach

A dynamical systems approach is used to quantify the instantaneous and time-averaged predictability of a low-order moist general circulation model. Specifically, the effects on predictability of incorporating an active ocean circulation, implementing annual solar forcing, and asynchronously coupling the ocean and atmosphere are evaluated. The predictability and structure of the model attractors is compared using the Lyapunov exponents, the local divergence rates, and the correlation, fractal, and Lyapunov dimensions. The Lyapunov exponents measure the average rate of growth of small perturbations on an attractor, while the local divergence rates quantify phase-spatial variations of predictability. These local rates are exploited to efficiently identify and distinguish subtle differences in predictability among attractors. In addition, the predictability of monthly averaged and yearly averaged states is investigated by using attractor reconstruction techniques.

Nese, Jon M.↗

Scattering Effects of Solar Panels on Space Station Antenna Performance

Characterizing the scattering properties of the solar array panels is important in predicting Space Station antenna performance. A series of far-field, near-field, and radar cross section (RCS) scattering measurements were performed at S-Band and Ku-Band microwave frequencies on Space Station solar array panels. Based on investigation of the measured scattering patterns, the solar array panels exhibit similar scattering properties to that of the same size aluminum or copper panel mockup. As a first order approximation, and for worse case interference simulation, the solar array panels may be modeled using perfect reflecting plates. Numerical results obtained using the Geometrical Theory of Diffraction (GTD) modeling technique are presented for Space Station antenna pattern degradation due to solar panel interference. The computational and experimental techniques presented in this paper are applicable for antennas mounted on other platforms such as ship, aircraft, satellite, and space or land vehicle.

Panneton, Robert J.↗