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At least 1,495 records · Page 83

Re-examination of a Classic Experiment to Measure the Positronium-Helium Cross Section

In 1975, before the advent of positronium beams, a clever experiment was carried out in an attempt to measure low-energy Ps-atom scattering cross-sections, especially that of Ps-He. A series of parallel thin plates was placed in the vessel containing the sample of gas, and positrons were allowed to enter the chamber from a radioactive source. The time spectrum of annihilation radiation was observed in the traditional way, and the pickoff annihilation due to thermalized Ps striking one of the plates was to be the special feature of the experiment. Using a diffusion analysis the authors derived cross- sections for several gases, and for helium the value obtained was sigma = 0.0166 pi(alpha)(sub o, sup 2). Even then this value was thought to be very much too small, while recent measurements and some calculations suggest a more reasonable value would be sigma = 3 to 13 pi(alpha)(sub o,sup 2). It has always been puzzling that an apparently well-designed experiment should give such an unsatisfactory result. We have now re-examined the analysis of the data with some interesting consequences which may explain the discrepancy. Two main observations support our re-analysis. First, we note that the mean free path for Ps-He scattering would be quite long if the cross-section were as small as that quoted above; the diffusion method itself would seem to be questionable. For the larger values, however, there would be no such problem. Second, it was assumed that when the annihilation rate had settled down and was following an exponential decay curve the asymptotic solution of the diffusion equation had been reached. We find, instead, that a superposition of exponentials can accurately represent the decay curve, consistent with the higher cross-section value.

Drachman, Richard J.↗

Does The Nile Reflect Solar Variability?

Historical records of the Nile water level provide a unique opportunity to investigate the possibility that solar variability influences the Earth's climate. Particularly important are the annual records of the water level, which are uninterrupted for the years 622-1470 A.D. These records are non-stationary, so that standard spectral analyses cannot adequately characterize them. Here the Empirical Mode Decomposition technique, which is designed to deal with nonstationary, nonlinear time series, becomes useful. It allows the identification of two characteristic time scales in the water level data that can be linked to solar variability: the 88 year period and a time scale of about 200 years. These time scales are also present in the concurrent aurora data. Auroras are driven by coronal mass ejections and the rate of auroras is an excellent proxy for solar variability. Analysis of auroral data contemporaneous with the Nile data shows peaks at 88 years and about 200 years. This suggests a physical link between solar variability and the low frequency variations of the Nile water level. The link involves the influence of solar variability on the North Annual Mode of atmospheric variability and its North Atlantic and Indian Oceans patterns that affect rainfall over Eastern Equatorial Africa where the Nile originates.

statistical methods↗

Global Gridded Crop Model Evaluation: Benchmarking, Skills, Deficiencies and Implications.

Crop models are increasingly used to simulate crop yields at the global scale, but so far there is no general framework on how to assess model performance. Here we evaluate the simulation results of 14 global gridded crop modeling groups that have contributed historic crop yield simulations for maize, wheat, rice and soybean to the Global Gridded Crop Model Intercomparison (GGCMI) of the Agricultural Model Intercomparison and Improvement Project (AgMIP). Simulation results are compared to reference data at global, national and grid cell scales and we evaluate model performance with respect to time series correlation, spatial correlation and mean bias. We find that global gridded crop models (GGCMs) show mixed skill in reproducing time series correlations or spatial patterns at the different spatial scales. Generally, maize, wheat and soybean simulations of many GGCMs are capable of reproducing larger parts of observed temporal variability (time series correlation coefficients (r) of up to 0.888 for maize, 0.673 for wheat and 0.643 for soybean at the global scale) but rice yield variability cannot be well reproduced by most models. Yield variability can be well reproduced for most major producing countries by many GGCMs and for all countries by at least some. A comparison with gridded yield data and a statistical analysis of the effects of weather variability on yield variability shows that the ensemble of GGCMs can explain more of the yield variability than an ensemble of regression models for maize and soybean, but not for wheat and rice. We identify future research needs in global gridded crop modeling and for all individual crop modeling groups. In the absence of a purely observation-based benchmark for model evaluation, we propose that the best performing crop model per crop and region establishes the benchmark for all others, and modelers are encouraged to investigate how crop model performance can be increased. We make our evaluation system accessible to all crop modelers so that other modeling groups can also test their model performance against the reference data and the GGCMI benchmark.

wheat↗

Demisability of GFRP and CFRP Components of Reentering Orbital Debris: Phase I Test Results

Observations of surviving reentry debris on the ground and research performed by Hyperschall Technologie Göttingen (HTG) [1] indicated that significantly more glass fiber-reinforced polymer (GFRP) and carbon fiber-reinforced polymer (CFRP) components survive reentry than current models predict. NASA’s Orbital Debris Program Office conducted a series of tests to evaluate the accuracy of material demise models for reentering orbital debris used in NASA’s Object Reentry Survival Analysis Tool (ORSAT) and Debris Assessment Software (DAS). Testing is planned in a multi-phase series to allow for quick quantification of results as well as refinement of methods resulting from lessons learned during early phases. The Phase 1 tests discussed here validated ORSAT models for homogeneous metals, provided an efficient quantification of composite material demisability properties like mass loss rate and overall time to demise, and identified potential failure modes, which are currently not well understood. Phase 2 tests will be used to further understand mass loss rates and modes of both thermal and mechanical failure in composite materials. The authors exposed 95 samples of aluminum, CFRP, Kevlar fiber-reinforced polymer, GFRP, and sheets of G10 fiberglass to conditions approximating the reentry environment using an inductively coupled plasma (ICP) torch facility. The cylindrical CFRP samples were exposed to the atmospheric pressure plasma, at both the end and the midpoint, to investigate the difference in demisability between parts with exposed edges, like panels, and parts with no edges, such as carbonoverwrapped pressure vessels (COPVs). In a non-oxidative environment, no composite materials demised within the 5-minute test time. In the oxidative, elevated heat flux environment, CFRP samples demised between 210 s and 270 s. For the first 100 s of insertion time, most of the mass loss was due to pyrolysis of resin, creating an approximately bi-linear mass-loss rate curve with time. In a non-oxidative environment, carbon filaments were observed to unravel from some of the CFRP end-burned samples; however, this effect did not seem to affect the overall time to demise for the samples significantly. These results indicate that both GFRP and CFRP components survive reentry with significantly more remaining mass than current models predict.

Greene, Benton R.↗

Overview of JAXA and NASA Collaboration on Manned and Unmanned Aircraft Operations Integration in Disaster Response

Natural disasters have increased in frequency and intensity. With that increase has come an increased focus on improving disaster response efforts. As part of this focus, the Japan Aerospace Exploration Agency (JAXA) and the National Aeronautics and Space Administration (NASA) have been in collaboration since 2016 to explore improved airspace management for disaster response through the integration of manned aircraft and small Unmanned Aircraft Systems (UAS). The approach to this integration has been through leveraging JAXA’s Disaster Relief Aircraft Information Sharing Network (D-NET) system for the coordinated management of manned aircraft assets combined with NASA’S UAS Traffic Management (UTM) system for the management of UAS assets. To drive the innovation in improved response, JAXA and NASA have successfully connected respective systems and conducted a series of live flight tests first as part of a large-scale disaster drill and later in dedicated research flights. In each case, the D-NET and UTM systems were connected and exchanged data in real-time, which supported the planning and tracking of manned and unmanned operations. Through these test events, a number of key findings were derived through data analysis and stakeholder interviews with respect to the improvements offered by the integrated systems as well as key considerations for situation awareness of pilots regarding other operations in the airspace and flight path management.

disaster response↗

Sample IEEE123 Bus system for OEDI SI

Time series load and PV data from an IEEE123 bus system. An example electrical system, named the OEDI SI feeder, is used to test the workflow in a co-simulation. The system used is the IEEE123 test system, which is a well studied test system (see link below to IEEE PES Test Feeder), but some modifications were made to it to add some solar power modules and measurements on the system. The aim of this project is to create an easy-to-use platform where various types of analytics can be performed on a wide range of electrical grid datasets. The aim is to establish an open-source library of algorithms that universities, national labs and other developers can contribute to which can be used on both open-source and proprietary grid data to improve the analysis of electrical distribution systems for the grid modeling community. OEDI Systems Integration (SI) is a grid algorithms and data analytics API created to standardize how data is sent between different modules that are run as part of a co-simulation. The readme file included in the S3 bucket provides information about the directory structure and how to use the algorithms. The sensors.json file is used to define the measurement locations.

123 bus↗

Daily and 3-hourly Variability in Global Fire Emissions and Consequences for Atmospheric Model Predictions of Carbon Monoxide

Attribution of the causes of atmospheric trace gas and aerosol variability often requires the use of high resolution time series of anthropogenic and natural emissions inventories. Here we developed an approach for representing synoptic- and diurnal-scale temporal variability in fire emissions for the Global Fire Emissions Database version 3 (GFED3). We disaggregated monthly GFED3 emissions during 2003.2009 to a daily time step using Moderate Resolution Imaging Spectroradiometer (MODIS) ]derived measurements of active fires from Terra and Aqua satellites. In parallel, mean diurnal cycles were constructed from Geostationary Operational Environmental Satellite (GOES) Wildfire Automated Biomass Burning Algorithm (WF_ABBA) active fire observations. Daily variability in fires varied considerably across different biomes, with short but intense periods of daily emissions in boreal ecosystems and lower intensity (but more continuous) periods of burning in savannas. These patterns were consistent with earlier field and modeling work characterizing fire behavior dynamics in different ecosystems. On diurnal timescales, our analysis of the GOES WF_ABBA active fires indicated that fires in savannas, grasslands, and croplands occurred earlier in the day as compared to fires in nearby forests. Comparison with Total Carbon Column Observing Network (TCCON) and Measurements of Pollution in the Troposphere (MOPITT) column CO observations provided evidence that including daily variability in emissions moderately improved atmospheric model simulations, particularly during the fire season and near regions with high levels of biomass burning. The high temporal resolution estimates of fire emissions developed here may ultimately reduce uncertainties related to fire contributions to atmospheric trace gases and aerosols. Important future directions include reconciling top ]down and bottom up estimates of fire radiative power and integrating burned area and active fire time series from multiple satellite sensors to improve daily emissions estimates.

Mu, M.↗

Analysis of the long-term drift rates and oscillations of Jupiter’s largest vortices

Jupiter’s troposphere is dynamically characterized by a series of alternating eastward and westward jets. Embedded between these alternating jets, large vortices, characterized by their high speed closed circulations can be found in several latitudinal bands. The Great Red Spot (GRS) and the White Ovals (WOS) located at ≈22 and ≈30 degrees south respectively1 are the largest of these vortices. The GRS has undergone significant changes in size, coloration and maximum circumferential wind speed over the last two decades. The three WOS also experienced changes in size, and they merged over time until there was only one remaining, which since then has been formally known as oval BA. Here we used over four decades worth of data from the Database for Object Positions on Jupiter (JUPOS), to investigate the long-term mean longitudinal drift of these largest vortices, and to characterize the deviations from this mean drift. A linear fit to the GRS drift speed for the last two decades gives a rate of change of (3.1 ± 0.4)^(-3°)/day/year. For oval BA we find that its annual drift rate changed from -0.39°/day in 2016 to -0.58°/day in 2020 following a steep trend that is best fitted by a second order polynomial. Regarding oscillations, we find that for the last two decades the GRS has continued to oscillate longitudinally with the same period (90 days) and peak-to-peak amplitude (1.2 degrees longitude) as reported historically. For the WOS, the data prior to 2000 seems to indicate that they presented similar oscillations with periods of ≈158 days and peak-to-peak amplitudes of ≈1.6 degrees. The analysis of the data for oval BA since the year 2000 reveals evidence of an oscillation with a period of ≈138 days and peak-to-peak amplitude of ≈1.6 degrees longitude.

Raúl Morales-Juberías↗

High-resolution infrared spectroscopy of jet cooled CH 2 Br radicals: The symmetric CH stretch manifold and absence of nuclear spin cooling

Direct laser absorption of a slit supersonic discharge expansion provides the first high-resolution spectroscopic results on the symmetric CH stretch excitation (ν 1 ) of the bromomethyl (CH 2 Br) radical in the ground electronic state. Narrowband (<1 MHz) mid-infrared radiation is produced by difference-frequency generation of two visible laser beams, with the open shell halohydrocarbon radical generated by electron dissociative attachment of CH 2 Br 2 in a discharge and rapidly cooled to T rot = 18 ± 1 K in the subsequent slit-jet supersonic expansion. A rovibrational structure in the radical spectrum is fully resolved, as well as additional splittings due to spin-rotation effects and 79 Br/ 81 Br isotopologues in natural abundance. Spectroscopic constants and band origins are determined by fitting the transition frequencies to a non-rigid Watson Hamiltonian, yielding results consistent with a vibrationally averaged planar radical and an unpaired electron in the out-of-plane p π orbital. Additionally, extensive satellite band structure from a vibrational hot band is observed and analyzed. The hot band data is compared to CFOUR/VPT2 (CCSD(T)cc-pVQZ) ab initio anharmonic predictions of the vibration rotation alpha matrix, which permits unambiguous assignment to CH 2 symmetric-stretch excitation built on the singly excited CH 2 out-of-plane bending mode (ν 1 + ν 4 ← ν 4 ). Longitudinal cooling of the Doppler width in the slit-jet expansion geometry also reveals partially resolved hyperfine structure on transitions out of the lowest angular momentum states in excellent agreement with predictions based on microwave studies. High level ab initio MOLPRO calculations [CCSD(T)-f12b/VnZ-f12 (n = 3, 4, CBS)] are also performed with explicitly correlated f12 electron methods for the out-of-plane CH 2 bending mode over the halogen series CH 2 X (X = F, Cl, Br, I), which clearly reveals a non-planar geometry for X = F (with a ΔE ≈ 0.3 kcal/mol barrier) and yet planar equilibrium geometries for X = Cl, Br, and I. Finally, a detailed Boltzmann analysis of the transition intensities provides support for negligible collisional equilibration of the entangled H atom nuclear spin states on the few hundred microsecond time scale and high collision densities of a slit supersonic expansion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine-Learning Functional Zonation Approach for Characterizing Terrestrial–Aquatic Interfaces: Application to Lake Erie

Ecosystems at coastal terrestrial–aquatic interfaces play a significant role in global biogeochemical cycles. In this study, we aimed to characterize coastal wetlands with particular focus on the co-variability between plant dynamics, topography, soil, and other environmental factors. We proposed a functional zonation approach based on machine learning clustering to identify the spatial regions, i.e., zones that capture these co-varied properties. This approach was applied to publicly available datasets along Lake Erie, in the Great Lakes Region. We investigated the heterogeneity of coastal ecosystem structures as a function of along-shore distance and transverse distance, based on the spatial data layers, including topography, wetland vegetation cover, and the time series of Landsat’s enhanced vegetation index (EVI) between 1990 and 2020. Results showed that the topographic metrics (elevation and slope), soil texture, and plant productivity influence the spatial distribution of wetland land-covers (emergent and phragmites). These results highlight a natural organization along the transverse axis, where the elevation and the EVI increase further away from the coastline. In addition, the clustering analysis allowed us to identify regions with distinct environmental characteristics, as well as the ones that are more sensitive to interannual lake-level variations.

47 OTHER INSTRUMENTATION↗

Efficient parallel algorithms for string editing and related problems

The string editing problem for input strings x and y consists of transforming x into y by performing a series of weighted edit operations on x of overall minimum cost. An edit operation on x can be the deletion of a symbol from x, the insertion of a symbol in x or the substitution of a symbol x with another symbol. This problem has a well known O((absolute value of x)(absolute value of y)) time sequential solution (25). The efficient Program Requirements Analysis Methods (PRAM) parallel algorithms for the string editing problem are given. If m = ((absolute value of x),(absolute value of y)) and n = max((absolute value of x),(absolute value of y)), then the CREW bound is O (log m log n) time with O (mn/log m) processors. In all algorithms, space is O (mn).

Apostolico, Alberto↗

Reflectance stability analysis of Spectralon diffuse calibration panels

The Multi-angle Imaging SpectroRadiometer (MISR) plans to use deployable diffuse reflectance panels to provide periodic radiometric calibrations of its nine cameras while in-flight. Near-Lambertian reflectance characteristics are desirable to facilitate flat-field camera intercomparisons. Also required is panel spatial and spectral uniformity, and stability with time. Spectralon, a commercially available polytetrafluoroethylene (PTFE) compound, has been baselined in the MISR design. To assess the suitability of this material, a series of degradation tests were planned and implemented. These included UV vacuum exposure and proton bombardment tests which simulated the exposure levels to be encountered during the mission life. Proton levels are now considered too low to be of concern, but UV vacuum tests demonstrate sensitivity to material contamination. Material investigations have concluded that hydrocarbons are present in the bulk of the material, and that plastic packaging materials can introduce additional surface-layer contamination. It is found however, that these unwanted elements can be eliminated through vacuum pumping at elevated temperatures. Exposure to a UV source, while in vacuum, is again planned for a set of targets which have been vacuum baked. This will assess the stability of the pure PTFE form.

Bruegge, Carol J.↗

El Nino-Southern Oscillation Correlated Aerosol Angstrom Exponent Anomaly Over the Tropical Pacific Discovered in Satellite Measurements

El Nino.Southern Oscillation (ENSO) is the dominant mode of interannual variability in the tropical atmosphere. ENSO could potentially impact local and global aerosol properties through atmospheric circulation anomalies and teleconnections. By analyzing aerosol properties, including aerosol optical depth (AOD) and Angstrom exponent (AE; often used as a qualitative indicator of aerosol particle size) from the Moderate Resolution Imaging Spectrometer, the Multiangle Imaging Spectroradiometer and the Sea ]viewing Wide Field ]of ]view Sensor for the period 2000.2011, we find a strong correlation between the AE data and the multivariate ENSO index (MEI) over the tropical Pacific. Over the western tropical Pacific (WTP), AE increases during El Nino events and decreases during La Nina events, while the opposite is true over the eastern tropical Pacific (ETP). The difference between AE anomalies in the WTP and ETP has a higher correlation coefficient (>0.7) with the MEI than the individual time series and could be considered another type of ENSO index. As no significant ENSO correlation is found in AOD over the same region, the change in AE (and hence aerosol size) is likely to be associated with aerosol composition changes due to anomalous meteorological conditions induced by the ENSO. Several physical parameters or mechanisms that might be responsible for the correlation are discussed. Preliminary analysis indicates surface wind anomaly might be the major contributor, as it reduces sea ]salt production and aerosol transport during El Nino events. Precipitation and cloud fraction are also found to be correlated with tropical Pacific AE. Possible mechanisms, including wet removal and cloud shielding effects, are considered. Variations in relative humidity, tropospheric ozone concentration, and ocean color during El Nino have been ruled out. Further investigation is needed to fully understand this AE ]ENSO covariability and the underlying physical processes responsible for it.

Li, Jing↗

Assessing Wetland Hydroperiod and Soil Moisture With Remote Sensing: A Demonstration for the NASA Plum Brook Station Year 2

Primary Goal: Assist with the evaluation and measuring of wetlands hydroperiod at the PlumBrook Station using multi-source remote sensing data as part of a larger effort on projecting climate change-related impacts on the station's wetland ecosystems. MTRI expanded on the multi-source remote sensing capabilities to help estimate and measure hydroperiod and the relative soil moisture of wetlands at NASA's Plum Brook Station. Multi-source remote sensing capabilities are useful in estimating and measuring hydroperiod and relative soil moisture of wetlands. This is important as a changing regional climate has several potential risks for wetland ecosystem function. The year two analysis built on the first year of the project by acquiring and analyzing remote sensing data for additional dates and types of imagery, combined with focused field work. Five deliverables were planned and completed: 1) Show the relative length of hydroperiod using available remote sensing datasets 2) Date linked table of wetlands extent over time for all feasible non-forested wetlands 3) Utilize LIDAR data to measure topographic height above sea level of all wetlands, wetland to catchment area radio, slope of wetlands, and other useful variables 4) A demonstration of how analyzed results from multiple remote sensing data sources can help with wetlands vulnerability assessment 5) A MTRI style report summarizing year 2 results. This report serves as a descriptive summary of our completion of these our deliverables. Additionally, two formal meetings were held with Larry Liou and Amanda Sprinzl to provide project updates and receive direction on outputs. These were held on 2/26/15 and 9/17/15 at the Plum Brook Station. Principal Component Analysis (PCA) is a multivariate statistical technique used to identify dominant spatial and temporal backscatter signatures. PCA reduces the information contained in the temporal dataset to the first few new Principal Component (PC) images. Some advantages of PCA include the ability to filter out temporal autocorrelation and reduce speckle to the higher order PC images. A PCA was performed using ERDAS Imagine on a time series of PALSAR dates. Hydroperiod maps were created by separating the PALSAR dates into two date ranges, 2006-2008 and 2010, and performing an unsupervised classification on the PCAs.

Brooks, Colin↗

Metallurgical Analysis of the High Flux Isotope Reactor (HFIR) Carrier Lifting Bails (Rev.1)

The dissolution rates of the aluminum alloys in the High Flux Isotope Reactor (HFIR) element carriers and the Material Test Reactor (MTR) L-bundles in the H-Canyon facility have been identified as the possible cause of extended dissolutions that result in significant time and financial expenditures. A study, carried out by Savannah River National Laboratory (SRNL) to determine relationships between the dissolution rates and the metallurgical properties of the aluminum alloy materials of construction of the HFIR carriers and the L-bundles, considered the dissolution rates of aluminum alloy (AA) series 1100, 6061, and 6063. The study determined that the aluminum alloy compositions played a principal role in the dissolution rate of the carrier/bundle components. Higher dissolution rates were correlated with lower concentrations of the minor element additions in the alloys and with specific element concentrations. Aluminum alloys 1100 and 6063 were found to have similar dissolution rates that were approximately two orders of magnitude (100X) greater than those of AA6061. Based on the results of the dissolution behavior study, a Technical Assistance Request (TAR) was first issued to determine if the replacement of AA6061-T6 with AA6063-T6 is feasible for the HFIR carrier lifting bails. A Technical Task Request was then issued to consider AA6063-T5 as well as other alloys to improve possible supply chain issues. The metallurgical properties of the L-bundle (specifically the end caps) were not evaluated in this report because L-Bundle drawings already allow for the use of AA6063-T6 in all structural components. The HFIR carriers are composed of thin-walled components with significant surface areas that allow for relatively quick overall dissolution times. Conversely, the carrier lifting bails and the supporting constituents are composed of solid bars and thick plate regions with relatively small surface areas that experience longer overall dissolution times. While the MTR L-bundle design includes allowances for the materials of construction to be either AA6061-T6 or AA6063-T6, the HFIR carriers are specified to be constructed fully with AA6061-T6 alloy. This report analyzes the recommendations of the dissolution behavior study to replace the materials of construction of the HFIR carrier lifting bails. The analysis considers the operational requirements of the lifting bail and its supporting structures. To decrease dissolution times, the analysis considers direct replacement of the material as well as reductions in the thicknesses of the components to decrease the mass of the elements. Material reductions are considered on options for using either AA6061 and/or AA6063. The calculations are based on specifications from the American Society of Mechanical Engineer (ASME) and The Aluminum Association, Inc. design codes. The analysis finds that direct replacement of the lifting bail material of construction with AA6063-T6, and AA6063-T5 as well as reductions in the dimensions of the lifting bail components are acceptable. Note that this study considers the structural suitability of the alloys. It does not consider their dissolution rates in the dissolvers.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Neutron-Resonance Transmission Analysis with a Compact Deuterium-Tritium Neutron Generator

Neutron Resonance Transmission Analysis (NRTA) is a spectroscopic technique which uses the resonant absorption of neutrons in the epithermal range to infer the isotopic composition of an object. This spectroscopic technique has relevance in many traditional fields of science and nuclear security. NRTA in the past made use of large, expensive accelerator facilities to achieve precise neutron beams, significantly limiting its applicability. Here, we describe a series of NRTA experiments where we use a compact, low-cost deuterium-tritium (DT) neutron generator to produce short neutron beams (2.6 m) along with a 6 Li-glass neutron detector. The time-of-flight spectral data from five elements – silver, cadmium, tungsten, indium, and 238 U – clearly show the corresponding absorption lines in the 1-30 eV range. The experiments show the applicability of NRTA in this simplified configuration, and prove the feasibility of this compact and low-cost approach. This could significantly broaden the applicability of NRTA, and make it practical and applicable in many fields, such as material science, nuclear engineering, and arms control.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Structural Reliability Analysis and Optimization: Use of Approximations

This report is intended for the demonstration of function approximation concepts and their applicability in reliability analysis and design. Particularly, approximations in the calculation of the safety index, failure probability and structural optimization (modification of design variables) are developed. With this scope in mind, extensive details on probability theory are avoided. Definitions relevant to the stated objectives have been taken from standard text books. The idea of function approximations is to minimize the repetitive use of computationally intensive calculations by replacing them with simpler closed-form equations, which could be nonlinear. Typically, the approximations provide good accuracy around the points where they are constructed, and they need to be periodically updated to extend their utility. There are approximations in calculating the failure probability of a limit state function. The first one, which is most commonly discussed, is how the limit state is approximated at the design point. Most of the time this could be a first-order Taylor series expansion, also known as the First Order Reliability Method (FORM), or a second-order Taylor series expansion (paraboloid), also known as the Second Order Reliability Method (SORM). From the computational procedure point of view, this step comes after the design point identification; however, the order of approximation for the probability of failure calculation is discussed first, and it is denoted by either FORM or SORM. The other approximation of interest is how the design point, or the most probable failure point (MPP), is identified. For iteratively finding this point, again the limit state is approximated. The accuracy and efficiency of the approximations make the search process quite practical for analysis intensive approaches such as the finite element methods; therefore, the crux of this research is to develop excellent approximations for MPP identification and also different approximations including the higher-order reliability methods (HORM) for representing the failure surface. This report is divided into several parts to emphasize different segments of the structural reliability analysis and design. Broadly, it consists of mathematical foundations, methods and applications. Chapter I discusses the fundamental definitions of the probability theory, which are mostly available in standard text books. Probability density function descriptions relevant to this work are addressed. In Chapter 2, the concept and utility of function approximation are discussed for a general application in engineering analysis. Various forms of function representations and the latest developments in nonlinear adaptive approximations are presented with comparison studies. Research work accomplished in reliability analysis is presented in Chapter 3. First, the definition of safety index and most probable point of failure are introduced. Efficient ways of computing the safety index with a fewer number of iterations is emphasized. In chapter 4, the probability of failure prediction is presented using first-order, second-order and higher-order methods. System reliability methods are discussed in chapter 5. Chapter 6 presents optimization techniques for the modification and redistribution of structural sizes for improving the structural reliability. The report also contains several appendices on probability parameters.

Grandhi, Ramana V.↗

Comparative Analysis of Empirical and Machine Learning Models for Chla Extraction Using Sentinel-2 and Landsat OLI Data: Opportunities, Limitations, and Challenges

Remote retrieval of near-surface chlorophyll-a (Chla) concentration in small inland waters is challenging due to substantial optical interferences of various water constituents and uncertainties in the atmospheric correction (AC) process. Although various algorithms have been developed to estimate Chla from moderate-resolution terrestrial missions (∼10–60 m), the production of both accurate distribution maps and time series of Chla has proven challenging, limiting the use of remote analyses for lake monitoring. Here, we develop a support vector regression (SVR) model, which uses satellite-derived remote-sensing reflectance spectra () from Sentinel-2 and Landsat-8 images as input for Chla retrieval in a representative eutrophic prairie lake, Buffalo Pound Lake (BPL), Saskatchewan, Canada. Validated against in situ Chla from seven ice-free seasons (N ∼ 200; 2014–2020), the SVR model outperformed both locally tuned, -fed empirical models (Normalized Difference Chlorophyll Index, 2- and 3-band, and OC3) and Mixture Density Networks (MDNs) by 15–65%, while exhibiting comparable performance to a locally trained MDN, with an error of ∼35%. Comparison of Chla retrieval models, AC processors (iCOR, ACOLITE), and radiometric products (Rayleigh-corrected, surface, and top-of-atmosphere reflectance) showed that the best Chla maps and optimal time series (up to 100 mg m−3) were produced using a coupled SVR-iCOR system.

algal blooms↗