Physiochemical machine learning models predict operational lifetimes of CH 3 NH 3 PbI 3 perovskite solar cells
First machine learning predictions of perovskite solar cell service lifetimes.
Chemistry↗
SEARCH · Engineering Papers
Results for “solar prediction”
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.
A Model for Energy Buildup and Eruption Onset in Coronal Mass Ejections
Coronal mass ejections (CMEs) and eruptive flares (EFs) are the most energetic explosions in the solar system. Their underlying origin is the free energy that builds up slowly in the sheared magnetic field of a filament channel. We report the first end-to-end numerical simulation of a CME/EF, from zero-free-energy initial state through filament channel formation to violent eruption, driven solely by the magnetic-helicity condensation process. Helicity is the topological measure of linkages between magnetic flux systems, and is conserved in the corona, building up inexorably until it is ejected into interplanetary space. Numerous investigations have demonstrated that helicity injected by small-scale vortical motions, such as those observed in the photosphere, undergoes an inverse cascade from small scales to large, “condensing” at magnetic-polarity boundaries. Our new results verify that this process forms a filament channel within a compact bipolar region embedded in a background dipole field, and show for the first time that a fast CME eventually occurs via the magnetic-breakout mechanism. We further show that the trigger for explosive eruption is reconnection onset in the flare current sheet that develops above the polarity inversion line: this reconnection forms flare loops below the sheet and a CME flux rope above, and initiates high-speed outward flow of the CME. Our findings have important implications for magnetic self organization and explosive behavior in solar and other astrophysical plasmas, as well as for understanding and predicting explosive solar activity.
filaments↗
Multivariate degradation modeling using generalized cauchy process and application in life prediction of dye-sensitized solar cells
Recently, the Generalized Cauchy (GC) process has been applied to capture a Long Memory (LM) phenomenon in product degradation modeling and life prediction. Compared with the traditional fractional Brownian motion that captures the LM using a single Hurst parameter, the GC process has two free parameters (Hurst and fractal dimension parameters) that flexibly capture both global LM and local irregularity. However, all existing GC-based degradation models are for a single Degradation Characteristic (DC). In this article, motivated by a real degradation problem of dye-sensitized solar cells that jointly exhibits multiple DCs, global LM, local irregularity and DC-wise cross-correlation, we propose a novel GC-based Multivariate Degradation Model (GC-MDM) to simultaneously capture the aforementioned effects. A maximum likelihood estimation approach is developed to estimate parameters of the GC-MDM. Subsequently, product life prediction based on the GC-MDM is developed. The proposed GC-MDM is validated through a simulation study and a physical experiment of dye-sensitized solar cells. Furthermore, results show that the proposed GC-MDM fundamentally improves the life prediction accuracy in comparison with conventional degradation models which significantly misestimate the uncertainty of product life.
14 SOLAR ENERGY↗
Photoelectrons and Solar Ionizing Radiation at Mars: Predictions Versus MAVEN Observations
Understanding the evolution of the Martian atmosphere requires knowledge of processes transforming solar irradiance into thermal energy well enough to model them accurately. Here we compare Martian photoelectron energy spectra measured at periaps is by Mars Atmosphere and Volatile Evolution MissioN (MAVEN) with calculations made using three photoelectron production codes and three solar irradiance models as well as modeled and measured CO2 densities. We restricted our comparisons to regions where the contribution from solar wind electrons and ions were negligible. The two intervals examined on 19 October 2014 have different observed incident solar irradiance spectra. In spite of the differences in photoionization cross sections and irradiance spectra used, we find the agreement between models to be within the combined uncertainties associated with the observations from the MAVEN neutral density, electron flux, and solar irradiance instruments.
solar ionizing↗
Solar flux forecasting using mutual information with an optimal delay
Solar flux F(sub 10.7) directly affects the atmospheric density, thereby changing the lifetime and prediction of satellite orbits. For this reason, accurate forecasting of F(sub 10.7) is crucial for orbit determination of spacecraft. Our attempts to model and forecast F(sub 10.7) uncovered highly entangled dynamics. We concluded that the general lack of predictability in solar activity arises from its nonlinear nature. Nonlinear dynamics allow us to predict F(sub 10.7) more accurately than is possible using stochastic methods for time scales shorter than a characteristic horizon, and with about the same accuracy as using stochastic techniques when the forecasted data exceed this horizon. The forecast horizon is a function of two dynamical invariants: the attractor dimension and the Lyapunov exponent. In recent years, estimation of the attractor dimension reconstructed from a time series has become an important tool in data analysis. In calculating the invariants of the system, the first necessary step is the reconstruction of the attractor for the system from the time-delayed values of the time series. The choice of the time delay is critical for this reconstruction. For an infinite amount of noise-free data, the time delay can, in principle, be chosen almost arbitrarily. However, the quality of the phase portraits produced using the time-delay technique is determined by the value chosen for the delay time. Fraser and Swinney have shown that a good choice for this time delay is the one suggested by Shaw, which uses the first local minimum of the mutual information rather than the autocorrelation function to determine the time delay. This paper presents a refinement of this criterion and applies the refined technique to solar flux data to produce a forecast of the solar activity.
Ashrafi, S.↗
The Solar Dynamics Observatory: Your Eye on the Sun
The Solar Dynamics Observatory (SDO) was launched on February 11,2010 into partly cloudy skies over Cape Canaveral, Florida. SDO moved into a 28 degree inclined geosynchronous orbit over the longitude of the ground station in New Mexico. SDO is the first Space Weather Mission in NASA's Living With a Star Program. SDO's main goal is to understand and predict those solar variations that influence life on Earth and our technological systems. The SDO science investigations will determine how the Sun's magnetic field is generated and structured, how this stored magnetic energy is released into the heliosphere as the solar wind, energetic particles, and variations in the solar irradiance. The SDO mission consists of three scientific investigations (AIA, EVE, and HMI), a spacecraft bus, and a dedicated Ka-band ground station to handle the 150 Mbps data flow. SDO continues a long tradition of NASA missions providing calibrated solar spectral irradiance data, in this case using multiple measurements of the irradiance and rocket underflights of the spacecraft. The other instruments on SDO will be used to explain and develop predictive models of the solar spectral irradiance in the extreme ultraviolet. Science teams at LMSAL, LASP, and Stanford are responsible for processing, analyzing, distributing, and archiving the science data. We will talk about the building of SDO, its launch, and the data and science it will provide to NASA.
Pesnell, William Dean↗
The Solar Dynamics Observatory: Your On-Orbit Eye on the Sun
The Solar Dynamics Observatory (SDO) was launched on February 11, 2010 into the partly cloudy skies above Cape Canaveral, Florida. Over the next month SDO moved into a 28 degree inclined geosynchronous orbit at the longitude of the ground station in New Mexico. SDO is the first Space Weather Mission in NASA's Living With a Star Program. SDO's main goal is to understand and predict those solar variations that influence life on Earth and our technological systems. The SDO science investigations will determine how the Sun's magnetic field is generated and structured, how this stored magnetic energy is released into the heliosphere as the solar wind, energetic particles, and variations in the solar irradiance. The SDO mission consists of three scientific investigations (AIA, EVE, and HMI), a spacecraft bus, and a dedicated Ka-band ground station to handle the 150 Mbps data flow. SDO continues a long tradition of NASA missions providing calibrated solar spectral irradiance data, in this case using multiple measurements of the irradiance and rocket underflights of the spacecraft. The other instruments on SDO will be used to explain and develop predictive models of the solar spectral irradiance in the extreme ultraviolet. Science teams at LMSAL, LASP, and Stanford are responsible for processing, analyzing, distributing, and archiving the science data. We will talk about the launch of SDO and describe the data and science it is providing to NASA.
Pesnell, W. Dean↗
Prediction of the coronal structure for the solar eclipse of September 22, 1968.
Coronal structure predicted for September 22, 1968 solar eclipse by model constructed for large structure of coronal and interplanetary magnetic fields
Schatten, K. H.↗
Prediction of the coronal structure for the solar eclipse of March 7, 1970
Coronal structure prediction for 7 March 1970 solar eclipse, using model for 22 September 1968 eclipse
Schatten, K. H.↗
Application of advanced computational procedures for modeling solar-wind interactions with Venus: Theory and computer code
Computational procedures are developed and applied to the prediction of solar wind interaction with nonmagnetic terrestrial planet atmospheres, with particular emphasis to Venus. The theoretical method is based on a single fluid, steady, dissipationless, magnetohydrodynamic continuum model, and is appropriate for the calculation of axisymmetric, supersonic, super-Alfvenic solar wind flow past terrestrial planets. The procedures, which consist of finite difference codes to determine the gasdynamic properties and a variety of special purpose codes to determine the frozen magnetic field, streamlines, contours, plots, etc. of the flow, are organized into one computational program. Theoretical results based upon these procedures are reported for a wide variety of solar wind conditions and ionopause obstacle shapes. Plasma and magnetic field comparisons in the ionosheath are also provided with actual spacecraft data obtained by the Pioneer Venus Orbiter.
Stahara, S. S.↗
Solar irradiance change and special longitudes due to r-modes
Sluggish global oscillations, having a periodicity of months and trapped in the sun's convection zone, modulate the amount of energy reaching earth and seem to impose some large-scale order on the distribution of solar surface features. These recently recognized oscillations (r-modes) increase the predictability of solar changes and may improve understanding of rotation and variability in other stars. Most of the 13 periodicities ranging from 13 to 85 days that are caused by r-modes can be detected in Nimbus 7 observations of solar irradiance during 3 years at solar maximum. These modes may also bear on the classical question of persistent longitudes of high solar activity.
Wolff, Charles L.↗
Operational Aspects of Space Radiation
In this session, Session FA4, the discussion focuses on the following topics: Solar Particle Events and the International Space Station; Radiation Environment on Mir and ISS Orbits During the Solar Cycle; New approach to Radiation Risk Assessment; An Industrial Method to Predict Major Solar Flares for a Better Protection of Human Beings in Space; Description of the Space Radiation Control System for the Russian Segment of ISS; Orbit Selection and Its Impact on Radiation Warning Architecture for a Human Mission to Mars; and Space Nuclear Power - Technology, Policy and Risk Considerations in Human Missions to Mars.
Source record↗
ISPAE Research Highlights 1995-1997
This paper presents ISPAE (Institute for Space Physics, Astrophysics and Education) research highlights from 1995-1997. The topics include: 1) High-Energy Astrophysics (Finding the smoking gun in gamma-ray bursts, Playing peekaboo with gamma ray bursts, and Spectral pulses muddle burst source study, Einstein was right: Black holes do spin, Astronomers find "one-man X-ray band", and Cosmic rays from the supernova next door?); 2) Solar Physics (Bright burst confirms solar storm model, Model predicts speed of solar wind in space, and Angry sunspots snap under the strain); 3) Gravitational Physics; 4) Tether Dynamics; and 5) Space Physics (Plasma winds blow form polar regions, De-SCIFERing thermal electrons, and UVI lets scientists see daytime aurora).
Harwell, Ken↗
A Summary of The 2000-2001 NASA Glenn Lear Jet AM0 Solar Cell Calibration Program
Calibration of solar cells for space is extremely important for satellite power system design. Accurate prediction of solar cell performance is critical to solar array sizing, often required to be within 1%. The NASA Glenn Research Center solar cell calibration airplane facility has been in operation since 1963 with 531 flights to date. The calibration includes real data to Air Mass (AM) 0.2 and uses the Langley plot method plus an ozone correction factor to extrapolate to AM0. Comparison of the AM0 calibration data indicates that there is good correlation with Balloon and Shuttle flown solar cells. This paper will present a history of the airplane calibration procedure, flying considerations, and a brief summary of the previous flying season with some measurement results. This past flying season had a record 35 flights. It will also discuss efforts to more clearly define the ozone correction factor.
Scheiman, David↗
Software Displays Data on Active Regions of the Sun
The Solar Active Region Display System is a computer program that generates, in near real time, a graphical display of parameters indicative of the spatial and temporal variations of activity on the Sun. These parameters include histories and distributions of solar flares, active region growth, coronal mass ejections, size, and magnetic configuration. By presenting solar-activity data in graphical form, this program accelerates, facilitates, and partly automates what had previously been a time-consuming mental process of interpretation of solar-activity data presented in tabular and textual formats. Intended for original use in predicting space weather in order to minimize the exposure of astronauts to ionizing radiation, the program might also be useful on Earth for predicting solar-wind-induced ionospheric effects, electric currents, and potentials that could affect radio-communication systems, navigation systems, pipelines, and long electric-power lines. Raw data for the display are obtained automatically from the Space Environment Center (SEC) of the National Oceanic and Atmospheric Administration (NOAA). Other data must be obtained from the NOAA SEC by verbal communication and entered manually. The Solar Active Region Display System automatically accounts for the latitude dependence of the rate of rotation of the Sun, by use of a mathematical model that is corrected with NOAA SEC active-region position data once every 24 hours. The display includes the date, time, and an image of the Sun in H light overlaid with latitude and longitude coordinate lines, dots that mark locations of active regions identified by NOAA, identifying numbers assigned by NOAA to such regions, and solar-region visual summary (SRVS) indicators associated with some of the active regions. Each SRVS indicator is a small pie chart containing five equal sectors, each of which is color-coded to provide a semiquantitative indication of the degree of hazard posed by one aspect of the activity at the indicated location. The five aspects in question are the history of solar flares, the history of coronal mass ejections, the growth or decay of activity, the overall size, and the magnetic configuration. Mouse-clicking on an active-region-marking dot, SRVS indicator, or NOAA region number causes the program to generate a solar-region summary table (SRT) for the active region in question. The SRT contains additional quantitative and qualitative data, beyond those contained in the SRVS: These data include the solar coordinates of the region, the area of the region and its change in area during the past 24 hours, the change in the number of sunspots in the region during the past 24 hours, the magnetic configuration, and the types, dates, and times of the most recent flare and coronal mass ejection.
Golightly, Mike↗
Optimizing Prediction Error for Time-dependent Solar Radiation Modeling
Numerical weather forecasting models and statistical methods have found wide use to help power companies estimate renewable output, but better methods are needed, particularly for extended forecasts. Machine learning approaches have been used here as well, but so far a major limitation is the ability to also predict the corresponding uncertainty in a forecast. Here we show that both can be done and demonstrate this using a long-term-short memory neural network where the difference between predicted and ground truth data are used to train a model for the corresponding forecast uncertainties.
97 MATHEMATICS AND COMPUTING↗
Analysis and prediction of Doppler noise during solar conjunctions
The results of a study of Doppler data noise during solar conjunctions were presented. During the first half of 1975, a sizeable data base of Doppler data noise (estimates) for the Pioneer 10, Pioneer 11, and Helios 1 solar conjunctions was accumulated. To analyze this data, certain physical assumptions are made, leading to the development of a geometric parameter ("ISI") which correlates strongly with Doppler data noise under varying sun-earth-spacecraft geometries. Doppler noise models are then constructed from this parameter, resulting in the newfound ability to predict Doppler data noise during solar conjunctions, and hence to additionally be in a position to validate Doppler data acquired during solar conjunctions.
Berman, A. L.↗
Evaluating the impact of wildfire smoke on solar photovoltaic production
There are growing needs to understand how extreme weather events impact the electrical grid. Renewable energy sources such as solar photovoltaics are expanding in use to help sustainably meet electricity demands. Wildfires and, notably, the widespread smoke resulting from them, are one such extreme event that can impair the performance of solar photovoltaics. However, isolating the impact that smoke has on photovoltaic energy production, separate from ambient conditions, can be difficult. In this work, we seek to understand and quantify the impacts of wildfire smoke on solar photovoltaic production within the Western United States. Our analysis focuses on the construction of a random forest regression model to predict overall solar photovoltaic production. The model is used to separate and quantify the impacts of wildfire smoke in particular. To do so, we fuse historical weather, solar photovoltaic energy production, and PM2.5 particulate matter (primary smoke pollutant) data to train and test our model. The additional weather data allows us to capture interactions between wildfire smoke and other ambient conditions, as well as to create a more powerful predictive model capable of better quantifying the impacts of wildfire smoke on its own. We find that solar PV energy production decreases 8.3% on average during high smoke days at PV sites as compared to similar conditions without smoke present. Finally, this work allows us to improve our understanding of the potential impact on photovoltaic-based energy production estimates due to wildfire events and can help inform grid and operational planning as solar photovoltaic penetration levels continue to grow.
14 SOLAR ENERGY↗