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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 19 records

Estimating the Performance Loss Rate of Photovoltaic Systems Using Time Series Change Point Analysis

The accurate quantification of the performance loss rate of photovoltaic systems is critical for project economics. Following the current research activities in the photovoltaic performance and reliability field, this work presents a comparative assessment between common change point methods for performance loss rate estimation of fielded photovoltaic installations. An extensive testing campaign was thus performed to evaluate time series analysis approaches for performance loss rate evaluation of photovoltaic systems. Historical electrical data from eleven photovoltaic systems installed in Nicosia, Cyprus, and the locations’ meteorological measurements over a period of 8 years were used for this investigation. The application of change point detection algorithms on the constructed monthly photovoltaic performance ratio series revealed that the obtained trend might not always be linear. Specifically, thin film photovoltaic systems showed nonlinear behavior, while nonlinearities were also detected for some crystalline silicon photovoltaic systems. When applying several change point techniques, different numbers and locations of changes were detected, resulting in different performance loss rate values (varying by up to 0.85%/year even for the same number of change points). The results highlighted the importance of the application of nonlinear techniques and the need to extract a robust nonlinear model for detecting significant changes in time series data and estimating accurately the performance loss rate of photovoltaic installations.

photovoltaics↗

Target Detection via Cognitive Radars Using Change-Point Detection, Learning, and Adaptation

Many radar detection algorithms that assume a stationary environment (clutter) have been proposed and analyzed over the years. However, in practice, changes in the nonstationary environment can perturb the parameters of the clutter distribution, or even alter the clutter distribution family, which can greatly deteriorate the target detection capability. To avoid such potential performance degradation, cognitive radar systems are envisioned which are required to rapidly realize the nonstationarity, accurately learn the new characteristics of the environments, and adaptively update the detector. In this paper, aiming to develop a fully cognitive radar for target detection in nonstationary environments, we propose a unifying framework that integrates (i) change-point detection of clutter distributions by using a data-driven cumulative sum (CUSUM) algorithm and its extended version, (ii) learning/identification of clutter distribution by applying sparse theory and kernel density estimation methods, and (iii) adaptive target detection by automatically modifying the likelihood-ratio test and corresponding detection threshold. Further, with extensive numerical examples, we demonstrate the achieved improvements in detection performance due to the proposed framework in comparison to a nonadaptive case, an adaptive matched filter (AMF) method, and the clairvoyant case. Herein, we also use Wilcoxon rank-sum tests to evaluate the statistical significance of the performance improvements

42 ENGINEERING↗

Screening candidate supplementary cementitious materials under standard and accelerated curing through time-series surface resistivity measurements and change-point detection

Time-series surface resistivity (SR) measurements are evaluated as an indicator of pozzolanicity in concretes containing 13 materials of both known and unknown pozzolanicity, under standard and accelerated curing conditions, and the results were validated against portlandite consumption obtained through thermogravimetric analysis. Change-point detection (CPD) analysis is applied to the data to provide a rigorous indicator of hydration age of the onset and rate of the pozzolanic reaction, if occurring. The SR measurements were able to capture the onset of the pozzolanic reactions in concretes curing at elevated temperature regimes, which allows determination of pozzolanicity weeks earlier than at standard curing temperatures. Using CPD along with slope analysis allows a comprehensive analysis of a material's reactivity and determination of pozzolanicity in as quickly as two days. Time-series SR measurements at elevated curing conditions, along with limits on material composition, are recommended for determination of pozzolanic reactivity in novel or variable materials.

36 MATERIALS SCIENCE↗

Change-point Detection and Image Segmentation for Time Series of Astrophysical Images

Many astrophysical phenomena are time-varying, in the sense that their intensity, energy spectrum, and/or the spatial distribution of the emission suddenly change. This paper develops a method for modeling a time series of images. Under the assumption that the arrival times of the photons follow a Poisson process, the data are binned into 4D grids of voxels (time, energy band, and x-y coordinates), and viewed as a time series of non-homogeneous Poisson images. The method assumes that at each time point, the corresponding multiband image stack is an unknown 3D piecewise constant function including Poisson noise. It also assumes that all image stacks between any two adjacent change points (in time domain) share the same unknown piecewise constant function. The proposed method is designed to estimate the number and the locations of all of the change points (in time domain), as well as all of the unknown piecewise constant functions between any pairs of the change points. The method applies the minimum description length principle to perform this task. A practical algorithm is also developed to solve the corresponding complicated optimization problem. Simulation experiments and applications to real data sets show that the proposed method enjoys very promising empirical properties. Applications to two real data sets, the XMM observation of a flaring star and an emerging solar coronal loop, illustrate the usage of the proposed method and the scientific insight gained from it.

79 ASTRONOMY AND ASTROPHYSICS↗

Discovering hydrothermalism from Afar: In Situ methane instrumentation and change-point detection for decision-making

Seafloor hydrothermalism plays a critical role in fundamental interactions between geochemical and biological processes in the deep ocean. A significant number of hydrothermal vents are hypothesized to exist, but many of these remain undiscovered due in part to the difficulty of detecting hydrothermalism using standard sensors on rosettes towed in the water column or robotic platforms performing surveys. Here, we use in situ methane sensors to complement standard sensing technology for hydrothermalism discovery and compare sensors on a towed rosette and an autonomous underwater vehicle (AUV) during a 17 km long transect in the Northern Guaymas Basin in the Gulf of California. This transect spatially intersected with a known hydrothermally active venting site. These data show that methane signalled possible hydrothermal-activity 1.5–3 km laterally (100–150 m vertically) from a known vent. Methane as a signal for hydrothermalism performed similarly to standard turbidity sensors (plume detection 2.2–3.3 km from reference source), and more sensitively and clearly than temperature, salinity, and oxygen instruments which readily respond to physical mixing in background seawater. We additionally introduce change-point detection algorithms—streaming cross-correlation and regime identification—as a means of real-time hydrothermalism discovery and discuss related data supervision technologies that could be used in planning, executing, and monitoring explorative surveys for hydrothermalism.

58 GEOSCIENCES↗

Set-point changes in hierarchically-arranged thermogenic systems

Rats acclimated to either 23 or 5 C were concurrently exposed to cold and hypergravic fields to test the proposal that mammals have parallel controllers for thermoregulation. The two groups of rats were used to evaluate the different relative contributions of shivering and nonshivering thermogenesis to the increased oxygen consumption of the cold-exposed rats in hypergravic fields. The lower magnitude of the cold-induced oxygen consumption observed when cold-exposed rats are moved from 1 G to hypergravic fields is probably due to an inactivation of shivering rather than nonshivering thermogenesis. The observation that shivering, but not nonshivering thermogenesis, appears to be impaired by hypergravic fields is consistent with the representation of central thermoregulation by multiple controllers.

Horowitz, J. M.↗

Precision Oxygen Isotope Measurements of Two C-Rich Hydrated Interplanetary Dust Particles

Introduction: Chondritic-smooth IDPs (Interplanetary Dust Particles) are low porosity objects whose mineralogy is dominated by aqueous alteration products such as Mg-rich phyllosilicates (smectite and serpentine group) and Mg-Fe carbonate minerals. Their hydrated mineralogy combined with low atmospheric entry velocities have been used to infer an origin largely from asteroidal sources. Spectroscopic studies show that the types and abundance of organic matter in CS IDPs is similar to that in CP IDPs. Although CS IDPs show broad similarities to primitive carbonaceous chondrites, only a few particles have been directly linked to specific meteorite groups such as CM and CI chondrites based on the presence of diagnostic minerals. Many CS IDPs however, have carbon contents that greatly exceed that of known meteorite groups suggesting that they either may derive from comets or represent samples of more primitive parent bodies than do meteorites. It is now recognized that many large, dark primitive asteroids in the outer main belt, as well as some trans-Neptunian objects, show spectroscopic evidence for aqueous alteration products on their surfaces. Some CS IDPs exhibit large bulk D enrichments similar to those observed in the cometary CP IDPs. While hydrated minerals in comets have not been unambiguously identified to date, the presence of the smectite group mineral nontronite has been inferred from infrared spectra obtained from the ejecta from comet 9P/Tempel 1 during the Deep Impact mission. Recent observations of low temperature sulfide minerals in Stardust mission samples suggest that limited aqueous activity occurred on comet Wild-2. All of these observations, taken together, suggest that the high-carbon hydrated IDPs are abundant and important samples of primitive solar system objects not represented in meteorite collections. Oxygen isotopic compositions of chondrites reflect mixing between a 16O-rich reservoir and a 17O,18O-rich reservoir produced via mass-independent fractionation. The composition of the 16O-rich reservoir is well constrained but material representing the 17O,18O-rich end-member is rare. Self-shielding models predict that cometary water, presumed to represent this reservoir, should be enriched in 17O and 18O by greater than 200 per mille. The high-carbon hydrated IDPs may be among the best materials available to search for preserved "cometary" H2O signatures. In order to better understand the origin and evolution of these particles, we have obtained 10 hydrated interplanetary dust particles for coordinated mineralogical, isotopic and organic analyses. We have previously reported the results of mineralogical and O isotopic measurements of two hydrated IDPs; here we present results of O isotopic measurements of three additional IDPs. Samples and Methods: Three interplanetary dust particles (L2079C35, L2083D46 and L2083E46) were embedded in S and partially ultramicrotomed into approximately 70 nanometer sections for analysis via transmission electron microscopy (TEM). The remainders of the unsliced particles were removed from S and pressed into high purity Au foil that was cleaned with HF acid and annealed at 800 degrees Centigrade. The pressed IDPs were analyzed via electron microprobe analysis (EPMA) for quantitative bulk chemical analysis. After EPMA analysis, the IDPs were subjected to precision O isotope analysis with the UCLA Cameca IMS-1270 ion probe. A 20 kiloelectronvolt, 0.5 nanoangstrom Cs+ primary beam of approximately 15 micrometers diameter was used for each measurement. Small particles of San Carlos olivine and Burma spinel were pressed into the Au foil for use as standards to correct for instrumental mass fractionation. The detection system was configured for multicollection, with 16O measured on a Faraday cup, and 17O and 18O measured on electron multipliers (EMs). Individual analyses consisted of 15 cycles of 10 seconds per cycle. Additionally, two microtome thin sections were measured for H isotopic compositions with the JSC NanoSIMS 50L ion probe. An 8 picoangstrom, 16 kiloelectronvolt Cs plus primary beam was used. Measurements consisted of H, C, 12C, 16O, and 18O collected with EMs in multicollection. Terrestrial biotite and kerogen were used for isotopic standards. A significant challenge in O isotope measurement of hydrated minerals is the interference from 16OH at mass 17O. We ensured that the 17O and 16OH peaks were fully resolved by using a mass resolution of greater than 7000 and by careful analyses of San Carlos olivine, Burma spinel and chlorite hydrated mineral standards. The hydride was further suppressed with a cold finger attached to an LN2 dewar to trap volatiles in the sample chamber. All sputtered ions were counted (i.e. presputtering was not used); after applying background, yield and deadtime corrections, we performed a change-point analysis on our data via R in order to determine when the sample reached sputtering equilibrium; data points collected prior to the change point were excluded. Change-point analysis was also used to determine whether the IDP had completely sputtered. Results: Mineralogy. IDPs C35 and E46 exhibited hydrated mineralogies, Fe-Ni sulfide grains, nanoglobules and occasional enstatite grains distributed throughout a fine-grained Mg-Fe saponite matrix. C35 also contained breunnerite (Mg,Fe)CO3; solar flare tracks were observed in enstatite, indicating minimal atmospheric entry heating. The mineralogy of D46 is dominated by a large FeS grain with a minor component of adhering silicate material. D46 was strongly heated during atmorpheric entry as evidenced by a well-developed magnetite rim. EPMA analyses show that both C35 and E46 have high carbon contents of 20 weight percentage (approximately 6X CI). D46 contains approximately 6 wt.weight percentage C. A significant amount of the carbon is present as carbon nanoglobules. Results: Hydrogen isotopes: Although the bulk delta D values of both sections of L2079C35 were within error of SMOW (minus 33 plus or minus 19 per mille, 1 plus or minus 14 per mille 1 sigma), several delta D-rich hotspots were also identified, reaching 2000 per mille. As shown in Fig. 1, these hotspots are clearly associated with discrete carbonaceous inclusions that are akin to nanoglobules found in many meteorites and other IDPs. Oxygen Isotopes. Results of the oxygen isotope measurements are shown in Figure 1. The oxygen isotope composition for L2079C35 was delta 18O equals plus11.6 plus or minus 1.9per mille, delta 17O equals plus 7.9 plus or minus 1.9per mille (2 standard errors). The oxygen isotope composition for L2083D46 was delta 18O equals minus 8.1 plus or minus 1.9 per mille, delta 17O equals minus 6.4 plus or minus 3.1 per mille (2 standard errors). The oxygen isotope composition for L2083E46 was delta 18O equals plus 12.0 plus or minus 1.9 per mille, delta 17O equals plus 9.2 plus or minus 2.0 per mille (2 standard errors). Discussion: Despite mineralogical similarities to highly aqueously altered carbonaceous chondrites, the hydrated IDPs we analyzed have oxygen isotopic compositions that are distinct from matrix materials in the CI, CM, and CR chondrites. The IDPs plot along the Young-Russell line, with delta 17O values for C35 and E46 suggestive of interaction with a 16O-poor reservoir. However, we have thus far not observed evidence of extreme 16O-poor reservoirs expected from self-shielding models and observed in Acfer 094 simplectite. The high carbon contents of the IDPs also set them apart from known meteoritic samples. The lack of atmospheric entry heating effects are consistent with low encounter velocities and suggest either an asteroidal source, or a low inclination, low eccentricity cometary origin. Conclusions: The unusual oxygen isotopic compositions, high carbon contents, and the abundance of Drich nanoglobules, together, suggest that the high-carbon, hydrated IDPs are derived from a primitive source that is not yet represented in meteorite collections.

Snead, C. J.↗

Amazonia Disasters: Assessing Methods for Gold Mining-related Deforestation Detection in Amazonia Using NASA Earth Observations

Artisanal and small-scale gold mining (ASGM) is responsible for a large fraction of deforestation and disturbance in Amazonia. These activities cause severe impacts on the rainforest ecosystem and socioeconomic state of the region. NASA DEVELOP partnered with the Asociación para la Conservación de la Cuenca Amazónica (ACCA), NASA SERVIR Science Coordination Office, and the Spatial Informatics Group to enhance ASGM-related deforestation detection methods. ACCA currently uses the Omnibus Q-test Change Point Detection Algorithm to identify changes in Synthetic Aperture Radar (SAR) monthly-aggregated temporal data from the Sentinel-1 satellite. The team determined the algorithm's accuracy by comparing a stratified random sample of change points against data from January 2019 to June 2020 identified using PlanetScope and Landsat 8 Operational Land Imager (OLI) Earth observations through Collect Earth Online. Our results indicated a users' accuracy of 55% for temporal change detection and producer's and user's accuracies of 99% and 97%, respectively, for detecting when change did not occur. Of the labeled change points, only 19% were due to mining activity. This research can help our partners have a more accurate understanding of where illegal gold mining may be taking place and inform decisions to remediate this activity.

DEVELOP Project Summary↗

Amazonia Disasters: Assessing Methods for Gold Mining-Related Deforestation Detection in Amazonia Using NASA Earth Observations

Artisanal and small-scale gold mining (ASGM) is responsible for a large fraction of deforestation and disturbance in Amazonia. These activities cause severe impacts on the rainforest ecosystem and socioeconomic state of the region. NASA DEVELOP partnered with the Asociación para la Conservación de la Cuenca Amazónica (ACCA), NASA SERVIR Science Coordination Office, and the Spatial Informatics Group to enhance ASGM-related deforestation detection methods. ACCA currently uses the Omnibus Q-test Change Point Detection Algorithm to identify changes in Synthetic Aperture Radar (SAR) monthly-aggregated temporal data from the Sentinel-1 satellite. The team determined the algorithm's accuracy by comparing a stratified random sample of change points against data from January 2019 to June 2020 identified using PlanetScope and Landsat 8 Operational Land Imager (OLI) Earth observations through Collect Earth Online. Our results indicated a users' accuracy of 55% for temporal change detection and producer's and user's accuracies of 99% and 97%, respectively, for detecting when change did not occur. Of the labeled change points, only 19% were due to mining activity. This research can help our partners have a more accurate understanding of where illegal gold mining may be taking place and inform decisions to remediate this activity.

DEVELOP Tech Paper↗

A new method for detecting abrupt changes in the dependence among multivariate hydrological series based on moving cut total correlation

Knowledge of how to define and estimate the dependence among multivariate hydrological series is essential for detecting abrupt changes in the dependence. Here, in this paper, a new method (BMCTC) is proposed to detect all possible abrupt change points in the dependence among multivariate hydrological series. The total correlation estimated by the matrix-based Renyi's alpha-order entropy functional is firstly introduced to define and measure the dependence strength among multivariate hydrological series. Then, the moving cut total correlation (MCTC) sequence is built by the moving window technique, which is used to measure changes in the dependence strength among multivariate hydrological series. Finally, the Bernaola-Galvan algorithm is used to detect all change points of the MCTC sequence. Simulations are performed to compare the effectiveness of BMCTC with Pearson correlation (BMCPC) and Spearman correlation (BMCSC), Cramer-von Mises (CvM) and copula-based likelihood-ratio (CLR). The results show that all change points are detected by BMCTC regardless of the samples size, but wrong change points or no change points are detected by other methods in most cases. BMCTC is applied to detect change points in the dependence among annual runoff, precipitation and sediment discharge series in the Xiliugou and the Kuyehe River, China. It is found that the dependence among runoff, precipitation and sediment discharge changed abruptly in 1980 and 1996 in the Kuyehe River and in 1999 in the Xiliugou River. These changes are mainly caused by human activities such as construction of water conservancy projects and coal mining.

54 ENVIRONMENTAL SCIENCES↗

Nonlinear Photovoltaic Degradation Rates: Modeling and Comparison Against Conventional Methods

Although common practice for estimating photovoltaic (PV) degradation rate (RD) assumes a linear behavior, field data have shown that degradation rates are frequently nonlinear. This article presents a new methodology to detect and calculate nonlinear RD based on PV performance time-series from nine different systems over an eight-year period. Prior to performing the analysis and in order to adjust model parameters to reflect actual PV operation, synthetic datasets were utilized for calibration purposes. A change-point analysis is then applied to detect changes in the slopes of PV trends, which are extracted from constructed performance ratio (PR) time-series. Once the number and location of change points is found, the ordinary least squares method is applied to the different segments to compute the corresponding rates. The obtained results verified that the extracted trends from the PR time-series may not always be linear and therefore, “nonconventional” models need to be applied. All thin-film technologies demonstrated nonlinear behavior whereas nonlinearity detected in the crystalline silicon systems is thought to be due to a maintenance event. A comparative analysis between the new methodology and other conventional methods demonstrated levelized cost of energy differences of up to 6.14%, highlighting the importance of considering nonlinear degradation behavior

14 SOLAR ENERGY↗