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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

Accelerated/abbreviated test methods for predicting life of solar cell encapsulants to Jet Propulsion Laboratory California Institute of Technology for the encapsulation task of the low-cost solar array project

An important principle is that encapsulants should be tested in a total array system allowing realistic interaction of components. Therefore, micromodule test specimens were fabricated with a variety of encapsulants, substrates, and types of circuitry. One common failure mode was corrosion of circuitry and solar cell metallization due to moisture penetration. Another was darkening and/or opacification of encapsulant. A test program plan was proposed. It includes multicondition accelerated exposure. Another method was hyperaccelerated photochemical exposure using a solar concentrator. It simulates 20 year of sunlight exposure in a short period of one to two weeks. The study was beneficial in identifying some cost effective encapsulants and array designs.

Kolyer, J. M.↗
NASA NTRS1985

Onset of solar flares as predicted by two-dimensional MHD-models of quiescent prominences

The close connection between the sudden disapperance (disparition brusque) of the quiescent prominences and the two-ribbon flares are well known. During this dynamic phase the prominence ascends rapidly (typically with a velocity about 100 Km/sec) and disappears. In another later stage is observed material falling back into the chromosphere. The impact of this downfalling matter on the chromosphere produces the H brightening, which shows the symmetric double pattern. The occurence of the disparition brusque is thought to be a consequence of a plasma instability of magnetohydrostatic (MHD) structures. By means of the MHD-energy principle, the stability properties of four prominence models are analyzed. It is shown that all considered models undergo instabilities for parameters outside of the observed range at quiescent prominences. The possibility that such instabilities in the flare parameter range may indicate just the onset of a flare is considered.

Galindotrejo, J.↗
NASA NTRS2023

Predicting Patterns of Solar Energy Buildout to Identify Opportunities for Biodiversity Conservation

The construction of solar energy facilities can have positive or negative impacts on biodiversity depending on siting and associated land use transitions. We identified drivers of solar siting and quantified patterns of buildout in states surrounding the Chesapeake Bay watershed – a biodiversity hotspot with numerous ecosystem services. Using a convolutional neural network, we mapped the footprints of ground-mounted solar arrays present in satellite imagery annually from 2017 to 2021 in Delaware, Maryland, Pennsylvania, New York, Virginia, and West Virginia. As of 2021, we identified 958 solar arrays covering 52.3 km2 built primarily on previously cultivated land, while avoiding natural landcover. We fit a binomial-Weibull model to these solar timeseries data in a hierarchical, Bayesian framework to quantify the relationship between geospatial covariates and rate of solar development. Solar array construction rate increased in cultivated areas, areas of lower agricultural suitability, lower slope, lower forest cover, lower biodiversity protection, and greater distances from roads. We also estimated changes in the rate of solar construction over time and found differences among states: acceleration in Virginia and deceleration in New York. We used parameter estimates to map the relative likelihood of future solar development across the study area. This methodology can be used to anticipate where solar is likely to be built in different landscapes and how these patterns align with conservation goals. Around the Chesapeake Bay watershed, the selection of lower quality agricultural areas for solar energy minimizes removal of important habitat and provides opportunities for native plant and pollinator restoration.

Artificial Intelligence↗
NASA NTRS2007

Solar Cycle 24 and the Solar Dynamo

We will discuss the polar field precursor method for solar activity prediction, which predicts cycle 24 will be significantly lower than recent activity cycles, and some new ideas rejuvenating Babcock's shallow surface dynamo. The polar field precursor method is based on Babcock and Leighton's dynamo models wherein the polar field at solar minimum plays a major role in generating the next cycle's toroidal field and sunspots. Thus, by examining the polar fields of the Sun near solar minimum, a forecast for the next cycle's activity is obtained. With the current low value for the Sun's polar fields, this method predicts solar cycle 24 will be one of the lowest in recent times, with smoothed F10.7 radio flux values peaking near 135 plus or minus 35 (2 sigma), in the 2012-2013 timeframe (equivalent to smoothed Rz near 80 plus or minus 35 [2 sigma]). One may have to consider solar activity as far back as the early 20th century to find a cycle of comparable magnitude. We discuss unusual behavior in the Sun's polar fields that support this prediction. Normally, the solar precursor method is consistent with the geomagnetic precursor method, wherein geomagnetic variations are thought to be a good measure of the Sun's polar field strength. Because of the unusual polar field, the Earth does not appear to be currently bathed in the Sun's extended polar field (the interplanetary field), hence negating the primal cause behind the geomagnetic precursor technique. We also discuss how percolation may support Babcock's original shallow solar dynamo. In this process ephemeral regions from the solar magnetic carpet, guided by shallow surface fields, may collect to form pores and sunspots.

Pesnell, W. D.↗
NASA NTRS2018

Using Machine-Learning Methods and Expert Prediction Probabilities to Forecast Solar Flares

It has long been known that studying connection between solar flares and properties of magnetic field in active regions is very important for understanding the flare physics and developing space weather forecasts. The Helioseismic and Magnetic Imager onboard the Solar Dynamics Observatory (SDO/HMI) obtains tremendous amounts of magnetic field data products. However the operational NOAA Space Weather Prediction Center (SWPC) forecasts of solar flares still represent prediction probabilities issued by the experts. In this research we investigate the possibilities to enhance the daily operational flare forecasts performed at the SWPC by developing a synergy of the expert predictions and physics-based criteria, and by employing machine-learning methods. Among the physics-based criteria we consider the descriptors of the Polarity Inversion Line (PIL) and Space weather HMI Active Region Patches (SHARP), and derive from them daily characteristics of the entire Sun. We also consider the daily descriptors of the GOES Soft X-Ray (SXR) 1-8 Angstroms flux such as the flare history of the previous days and averaged X-Ray flux. We estimate the effectiveness in separation of flaring and non-flaring cases for each characteristic, as well as for the expert prediction probabilities, and find that some PIL, SHARP and SXR descriptors are as effective as the expert prediction probabilities and should be considered to issue the flare forecast. Finally, we train and test several Machine-Learning classification algorithms (Support Vector Classifiers with various kernel functions, k-Nearest Neighbor Classifier, Random Forest Classifier, and Neural Networks) using the most effective descriptors and expert prediction probabilities, and compare the obtained predictions with the current SWPC forecasts.

Machine-Learning↗
NASA NTRS2004

The Magnetic Field in the Outer Heliosphere

One of the great achievements of Parker was the prediction that the solar magnetic field would be drawn into Archimedian spirals as it is carried away from the Sun by the solar wind. This prediction has been amply confirmed by many in situ measurements in the intervening four decades. But, Parker made his prediction for a solar wind that expands into infinite space while we now know that the local interstellar medium (LISM) is far from empty and, in fact, confines the solar wind to a finite volume, known as the heliosphere, that extends to approximately 100 AU in the upstream direction (the solar system is moving through the LISM). Voyagers 1/2, presently at -80 AU, are approaching the upstream boundaries of the heliosphere and returning data on the properties of the magnetic field. This is important for understanding how galactic cosmic rays (GCRs) reach the Earth. Voyagers show that the IMF at 10-80 AU behaves much as Parker predicted - with two important exceptions. This is not surprising since the field is essentially passively advected by the solar wind out to 80 AU. But, new models say that nearer the heliosphere boundaries the field plays a major role in the solar wind-LISM interaction. However, of the many physical ingredients that constitute the outer heliosphere, the magnetic field poses some of the most interesting and difficult numerical modeling problems. Presently, only a few results have been published and much remains to be done. Here I will summarize the expected and measured behavior of the magnetic field at 80 AU. Then I will describe modeling predictions beyond 80 AU: magnetic "tornadoes", polarity envelopes, the Axford-Cranfill effect, inner and outer magnetic walls and more. I will also list what I believe to be important new modeling objectives. Finally, I will speculate on what is happening with the magnetic field near the nose of the heliosphere. My conclusion is that models of GCR modulation rarely incorporate even crudely realistic magnetic fields so it is a wonder that they are as successful as they are and no surprise that there are still important discrepancies between GCR modulation observations and the models.

Suess, S. T.↗
NASA NTRS1986

The technique of linear prediction filters applied to studies of solar wind-magnetosphere coupling

Linear prediction filtering is a powerful empirical technique suitable for the study of stimulus-response behavior. The technique enables one to determine the most general linear relationship between multiple time-varying quantities, assuming that the physical systems relating the quantities are linear and time invariant. Several researchers have applied linear prediction analysis to investigate solar wind-magnetosphere interactions. This short review describes the method of linear prediction analysis, its application to solar wind-magnetosphere coupling studies both in terms of physical processes, and the results of investigations which have used this technique.

Clauer, C. Robert↗
DOE OSTI2020

Solar+ Optimizer: A Model Predictive Control Optimization Platform for Grid Responsive Building Microgrids

With the falling costs of solar arrays and battery storage and reduced reliability of the grid due to natural disasters, small-scale local generation and storage resources are beginning to proliferate. However, very few software options exist for integrated control of building loads, batteries and other distributed energy resources. The available software solutions on the market can force customers to adopt one particular ecosystem of products, thus limiting consumer choice, and are often incapable of operating independently of the grid during blackouts. In this paper, we present the “Solar+ Optimizer” (SPO), a control platform that provides demand flexibility, resiliency and reduced utility bills, built using open-source software. SPO employs Model Predictive Control (MPC) to produce real time optimal control strategies for the building loads and the distributed energy resources on site. SPO is designed to be vendor-agnostic, protocol-independent and resilient to loss of wide-area network connectivity. The software was evaluated in a real convenience store in northern California with on-site solar generation, battery storage and control of HVAC and commercial refrigeration loads. Preliminary tests showed price responsiveness of the building and cost savings of more than 10% in energy costs alone.

14 SOLAR ENERGY↗
NASA NTRS1979

KAZIA: A computer system for solar-terrestrial data processing and objective prediction

A computer system for solar terrestrial data processing is described. The data base consists mainly of information contained in Ursigrams exchanged between the IUWDS Regional Warning Centers. The system structure and its functions are presented. Solar flare forecasting is described, as one of the prediction techniques incorporated in the system.

Stasiewicz, K.↗
NASA NTRS1991

Evidence of chaotic pattern in solar flux through a reproducible sequence of period-doubling-type bifurcations

Presented here is a preliminary study of the limits to solar flux intensity prediction, and of whether the general lack of predictability in the solar flux arises from the nonlinear chaotic nature of the Sun's physical activity. Statistical analysis of a chaotic signal can extract only its most gross features, and detailed physical models fail, since even the simplest equations of motion for a nonlinear system can exhibit chaotic behavior. A recent theory by Feigenbaum suggests that nonlinear systems that can be led into chaotic behavior through a sequence of period-doubling bifurcations will exhibit a universal behavior. As the control parameter is increased, the bifurcation points occur in such a way that a proper ratio of these will approach the universal Feigenbaum number. Experimental evidence supporting the applicability of the Feigenbaum scenario to solar flux data is sparse. However, given the hypothesis that the Sun's convection zones are similar to a Rayleigh-Bernard mechanism, we can learn a great deal from the remarkable agreement observed between the prediction by theory (period doubling - a universal route to chaos) and the amplitude decrease of the signal's regular subharmonics. The authors show that period-doubling-type bifurcation is a possible route to a chaotic pattern of solar flux that is distinguishable from the logarithm of its power spectral density. This conclusion is the first positive step toward a reformulation of solar flux by a nonlinear chaotic approach. The ultimate goal of this research is to be able to predict an estimate of the upper and lower bounds for solar flux within its predictable zones. Naturally, it is an important task to identify the time horizons beyond which predictability becomes incompatible with computability.

Ashrafi, S.↗
NASA NTRS1991

Evidence of chaotic pattern in solar flux through a reproducible sequence of period-doubling-type bifurcations

A preliminary study of the limits to solar flux intensity prediction, and of whether the general lack of predictability in the solar flux arises from the nonlinear chaotic nature of the Sun's physical activity is presented. Statistical analysis of a chaotic signal can extract only its most gross features, and detailed physical models fail, since even the simplest equations of motion for a nonlinear system can exhibit chaotic behavior. A recent theory by Feigenbaum suggests that nonlinear systems that can be led into chaotic behavior through a sequence of period-doubling bifurcations will exhibit a universal behavior. As the control parameter is increased, the bifurcation points occur in such a way that a proper ratio of these will approach the universal Feigenbaum number. Experimental evidence supporting the applicability of the Feigenbaum scenario to solar flux data is sparse. However, given the hypothesis that the Sun's convection zones are similar to a Rayleigh-Bernard mechanism, we can learn a great deal from the remarkable agreement observed between the prediction by theory (period doubling - a universal route to chaos) and the amplitude decrease of the signal's regular subharmonics. It is shown that period-doubling-type bifurcation is a possible route to a chaotic pattern of solar flux that is distinguishable from the logarithm of its power spectral density. This conclusion is the first positive step toward a reformulation of solar flux by a nonlinear chaotic approach. The ultimate goal of this research is to be able to predict an estimate of the upper and lower bounds for solar flux within its predictable zones. Naturally, it is an important task to identify the time horizons beyond which predictability becomes incompatible with computability.

Ashrafi, S.↗
NASA NTRS2024

An Interesting Correlation Between the Peak Slope and Peak Value of a Sunspot Cycle

The maximum slope of the sunspot number during the rising phase of a sunspot cycle has an excellent correlation with the maximum value of the sunspot number during that cycle. This is demonstrated using a Savitzky–Golay filter to both smooth and calculate the derivative of the sunspot-number data. Version 2 of the International Sunspot Number (S) is used to represent solar activity. The maximum of the slope during the rising phase of each cycle was correlated against the peaks of solar activity. Using three different correlation fits, the average predicted amplitude for Solar Cycle 25 is 130.7 ± 0.5, among the best correlations in solar predictions. A possible explanation for this correlation is given by the similar behavior of a shape function representing the time variation of the sunspot number. This universal function also provides the timing of the solar maximum by the time from the slope maximum to the peak in the function as late 2023 or early 2024. A Hilbert transform gives similar results, which are caused by the dominance of the 11-yr sunspot-cycle period in a Fourier fit of the sunspot number.

W. Dean Pesnell↗