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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Maximizing the probability of satisfying the clinical goals in radiation therapy treatment planning under setup uncertainty

Purpose: This paper introduces a method that maximizes the probability of satisfying the clinical goals in intensity-modulated radiation therapy treatments subject to setup uncertainty. Methods: The authors perform robust optimization in which the clinical goals are constrained to be satisfied whenever the setup error falls within an uncertainty set. The shape of the uncertainty set is included as a variable in the optimization. The goal of the optimization is to modify the shape of the uncertainty set in order to maximize the probability that the setup error will fall within the modified set. Because the constraints enforce the clinical goals to be satisfied under all setup errors within the uncertainty set, this is equivalent to maximizing the probability of satisfying the clinical goals. This type of robust optimization is studied with respect to photon and proton therapy applied to a prostate case and compared to robust optimization using an a priori defined uncertainty set. Results: Slight reductions of the uncertainty sets resulted in plans that satisfied a larger number of clinical goals than optimization with respect to a priori defined uncertainty sets, both within the reduced uncertainty sets and within the a priori, nonreduced, uncertainty sets. For the prostate case, the plans taking reduced uncertainty sets into account satisfied 1.4 (photons) and 1.5 (protons) times as many clinical goals over the scenarios as the method taking a priori uncertainty sets into account. Conclusions: Reducing the uncertainty sets enabled the optimization to find better solutions with respect to the errors within the reduced as well as the nonreduced uncertainty sets and thereby achieve higher probability of satisfying the clinical goals. This shows that asking for a little less in the optimization sometimes leads to better overall plan quality.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2016

MO-B-207B-00: Harmonization & Robustness in Radiomics

Feature extraction for radiomics studies typically comprises the following stages: Imaging, segmentation, image processing, and feature extraction. Each of these stages has associated uncertainties that can affect the quality of a radiomics model created using the resulting image features. For example, the imaging device manufacturer and model have been shown to impact the values of image features, as have pixel size and imaging protocol parameters. Image processing, such as low-pass filtering to reduce noise, also changes calculated image features and should be designed to optimize the information content of the resulting features. The details of certain feature algorithms, such as co-occurrence matrix bin sizes, are also important, and should be optimized for specific radiomics tasks. The volume of the region of interest should be considered as image features can be related to volume and can give unanticipated results when the volumes are too small. In this session we will describe approaches to quantify the variabilities in radiomics studies, including the most recent results quantifying these variabilities for CT, MRI and PET imaging. We will discuss methods to optimize image processing and feature extraction in order to maximize the information content of the image features. Finally, we will describe work to harmonize imaging protocols and feature calculations to help minimize uncertainties in radiomics studies. Learning Objectives: At the end of this session, participants will be able to: Identify the sources of uncertainty in radiomics studies (CT, PET, and MRI imaging) Describe methods for quantifying the magnitude of uncertainties Describe approaches for mitigating the effects of the uncertainties on radiomics models Funding from NIH, CPRIT, Varian, Elekta; L. Court, NCI, CPRIT, Varian, Elekta.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-B-207B-01: Harmonization & Robustness in Radiomics

Feature extraction for radiomics studies typically comprises the following stages: Imaging, segmentation, image processing, and feature extraction. Each of these stages has associated uncertainties that can affect the quality of a radiomics model created using the resulting image features. For example, the imaging device manufacturer and model have been shown to impact the values of image features, as have pixel size and imaging protocol parameters. Image processing, such as low-pass filtering to reduce noise, also changes calculated image features and should be designed to optimize the information content of the resulting features. The details of certain feature algorithms, such as co-occurrence matrix bin sizes, are also important, and should be optimized for specific radiomics tasks. The volume of the region of interest should be considered as image features can be related to volume and can give unanticipated results when the volumes are too small. In this session we will describe approaches to quantify the variabilities in radiomics studies, including the most recent results quantifying these variabilities for CT, MRI and PET imaging. We will discuss methods to optimize image processing and feature extraction in order to maximize the information content of the image features. Finally, we will describe work to harmonize imaging protocols and feature calculations to help minimize uncertainties in radiomics studies. Learning Objectives: At the end of this session, participants will be able to: Identify the sources of uncertainty in radiomics studies (CT, PET, and MRI imaging) Describe methods for quantifying the magnitude of uncertainties Describe approaches for mitigating the effects of the uncertainties on radiomics models Funding from NIH, CPRIT, Varian, Elekta; L. Court, NCI, CPRIT, Varian, Elekta.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Critical temperature of metallic hydrogen sulfide at 225-GPa pressure

The Eliashberg theory generalized for electron—phonon systems with a nonconstant density of electron states and with allowance made for the frequency behavior of the electron mass and chemical potential renormalizations is used to study T{sub c} in the SH{sub 3} phase of hydrogen sulfide under pressure. The phonon contribution to the anomalous electron Green’s function is considered. The pairing within the total width of the electron band and not only in a narrow layer near the Fermi surface is taken into account. The frequency and temperature dependences of the complex mass renormalization ReZ(ω), the density of states N(ε) renormalized by the electron—phonon interactions, and the electron—phonon spectral function obtained computationally are used to calculate the anomalous electron Green’s function. A generalized Eliashberg equation with a variable density of electron states has been solved. The frequency dependence of the real and imaginary parts of the order parameter in the SH{sub 3} phase has been obtained. The value of T{sub c} ≈ 177 K in the SH{sub 3} phase of hydrogen sulfide at pressure P = 225 GPa has been determined by solving the system of Eliashberg equations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Comparison of Modeled to Measured Spectra using MCNP and GADRAS to Benchmark and Contrast Modeling Limitations

The desire to improve nuclear material detection through portal monitors and other low resolution detectors has led to interest in benchmarking the performance of radiation transport codes. These codes can be used to generate a variety and quantity of spectra that may be cost prohibitive to measure directly. Particular characteristics of typical detection scenarios were isolated to compare the performance of radiation transport codes to laboratory experiments. These benchmark experiments were performed to validate simulations in a number of key areas. These experiments included high areal density configurations in both one- and three-dimensional configurations. In addition, off-angle measurements were conducted to investigate the impact of detector response assumptions on complex geometries, for example where an unknown source is not physically collocated with an apparent hot spot. Furthermore, by examining both simple shielding and backscatter configurations, isolation of the scatter emanating from the object and environmental background scatter contributions to the spectra could be elucidated. A series of experiments were performed in which the order of shielding layers and the thickness were evaluated to examine the ability of the simulations to address these variables. Experiments with increasing thickness of polyethylene around a neutron source also allows for examinations of the ability of the transport simulations to properly model n,γ reactions. Finally, depleted uranium (DU) measurements have more complicated spectra than the cobalt-60 and consequently allow for investigations into the ability of transport simulations to model self-shielding. In each case, the results of the experiments were compared to MCNP simulations to judge the performance of the code, as was done previously with GADRAS 18.7.9 simulations [7]. All of the benchmark measurements were taken with a liquid nitrogen cooled 140% high purity germanium (HPGe) detector with a bismuth collimator that had the front tin filter removed. The measurement location and detector configuration were subsequently used for all experimental configurations. The remainder of this report details the experimental measurements, Section 2 and the MCNP model, Section 3. Comparisons between the experimental results and MCNP-generated spectra are performed, Section 4. Section 5 compares the results obtained with MCNP with the previously reported results obtained with GADRAS [2]. Finally, Section 6 presents the conclusions.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2025

Investigation of design principles for metal-binding and conductive protein assemblies

Throughout the lifetime of this initiative, including renewals, we focused on understanding the fundamental principles of protein-protein interface design that enable predictable and modular spatial and kinetic control of multi-component protein self-assembly in 1D, 2D, and 3D, including the interface with inorganic materials, small molecules, and metal ions. We designed individual protein components that bind specific metal ions, including REEs and transport ions across lipid membranes. We created helical 1D filaments of repeating units with programmed periodicity, pitch, and multi-component environmentally responsive self-assembling protein fibers. We showed that these filaments reversibly assemble and disassemble under specific pH conditions and created end-specific caps that independently tune the balance of attachment and detachment rates at each terminus of the filament. Using similar filaments, we succeeded in binding arrays of heme and chlorophyll molecules and assembling patterned helical coatings around carbon nanotubes in efforts to create de novo conductive nanowires. By arraying REE binding sites in a large circular tandem array with a repeat protein-based cyclic oligomer, we created a molecular scaffold for superradiance and paramagnetic quantum sensing. We created a range of one-component and two-component self-assembling 2D arrays and showed that when designed to engage cell receptors, these arrays can control cell behavior from outside the cell signal to inside the cell. We designed helical repeat proteins with variable lengths displaying charged residues in a pattern matched to the cation lattice of mica. achieved a range of ordered states with an epitaxial match to the underlying crystal lattice. We further applied the learned principles of protein-induced biomineralization to design proteins with an interface lattice matching CaCO 3 and guide the formation of specific crystal forms of CaCO 3 from solution, a significant advance toward the global need to manage carbon. In all cases of mineral lattice matching and biomineralization, we followed assembly using molecularly resolved in situ AFM imaging and extracted information about assembly pathways and energetics, applying deep learning to quantify the dynamics of protein self-organization. We developed techniques for using dynamic metal-dependent interfaces on protein nanopores for discriminatively sensing dilute REEs in solution and demonstrated the use of strong metal-binding interfaces to drive nanocage disassembly for conditional nanocompartmentalization applications. This grant supported 11 people, including Asim Bera, Evans Brackenbrough, Andrew Borst, Nikita Hanikel, Timothy Huddy, Emily Joyce, Alex Young-Seug Kang, Ryan Kibler, Joshua Morris Lubner, Harley Pyles, and Shuai Zhang. The research effort culminated in the production of published papers and theses. Electronic Thesis/Dissertation are distributed by ProQuest/UMI Dissertation Publishing and made available on an open access basis through UW Libraries ResearchWorks Service.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

CALIBRATION OF THE MEARTH PHOTOMETRIC SYSTEM: OPTICAL MAGNITUDES AND PHOTOMETRIC METALLICITY ESTIMATES FOR 1802 NEARBY M-DWARFS

The MEarth Project is a photometric survey systematically searching the smallest stars near the Sun for transiting rocky planets. Since 2008, MEarth has taken approximately two million images of 1844 stars suspected to be mid-to-late M dwarfs. We have augmented this survey by taking nightly exposures of photometric standard stars and have utilized this data to photometrically calibrate the MEarth system, identify photometric nights, and obtain an optical magnitude with 1.5% precision for each M dwarf system. Each optical magnitude is an average over many years of data, and therefore should be largely immune to stellar variability and flaring. We combine this with trigonometric distance measurements, spectroscopic metallicity measurements, and 2MASS infrared magnitude measurements in order to derive a color–magnitude–metallicity relation across the mid-to-late M dwarf spectral sequence that can reproduce spectroscopic metallicity determinations to a precision of 0.1 dex. We release optical magnitudes and metallicity estimates for 1567 M dwarfs, many of which did not have an accurate determination of either prior to this work. For an additional 277 stars without a trigonometric parallax, we provide an estimate of the distance, assuming solar neighborhood metallicity. We find that the median metallicity for a volume-limited sample of stars within 20 pc of the Sun is [Fe/H] = −0.03 ± 0.008, and that 29/565 of these stars have a metallicity of [Fe/H] = −0.5 or lower, similar to the low-metallicity distribution of nearby G dwarfs. When combined with the results of ongoing and future planet surveys targeting these objects, the metallicity estimates presented here will be important for assessing the significance of any putative planet–metallicity correlation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

The long-term centimeter variability of active galactic nuclei: a new relation between variability timescale and accretion rate

We study the long-term (≈30 years) radio variability of 43 radio-bright active galactic nuclei (AGNs) by exploiting the database of the University of Michigan Radio Astronomy Observatory monitoring program. We model the periodograms (temporal power spectra) of the observed light curves as simple power-law noise (red noise, spectral power P(f)∝f{sup −β}) using Monte Carlo simulations, taking into account windowing effects (red-noise leak, aliasing). The power spectra of 39 (out of 43) sources are in good agreement with the models, yielding a range in power spectral index (β) from ≈1 to ≈3. We fit a Gaussian function to each flare in a given light curve to obtain the flare duration. We discover a correlation between β and the median duration of the flares. We use the derivative of a light curve to obtain a characteristic variability timescale, which does not depend on the assumed functional form of the flares, incomplete fitting, and so on. We find that, once the effects of relativistic Doppler boosting are corrected for, the variability timescales of our sources are proportional to the accretion rate to the power of 0.25 ± 0.03 over five orders of magnitude in accretion rate, regardless of source type. We further find that modeling the periodograms of four of our sources requires the assumption of broken power-law spectra. From simulating light curves as superpositions of exponential flares, we conclude that strong overlap of flares leads to featureless simple power-law periodograms of AGNs at radio wavelengths in most cases.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Describing rainfall in northern Australia using multiple climate indices

Savanna landscapes are globally extensive and highly sensitive to climate change, yet the physical processes and climate phenomena which affect them remain poorly understood and therefore poorly represented in climate models. Both human populations and natural ecosystems are highly susceptible to precipitation variation in these regions due to the effects on water and food availability and atmosphere–biosphere energy fluxes. Here we quantify the relationship between climate phenomena and historical rainfall variability in Australian savannas and, in particular, how these relationships changed across a strong rainfall gradient, namely the North Australian Tropical Transect (NATT). Climate phenomena were described by 16 relevant climate indices and correlated against precipitation from 1900 to 2010 to determine the relative importance of each climate index on seasonal, annual and decadal timescales. Precipitation trends, climate index trends and wet season characteristics have also been investigated using linear statistical methods. In general, climate index–rainfall correlations were stronger in the north of the NATT where annual rainfall variability was lower and a high proportion of rainfall fell during the wet season. This is consistent with a decreased influence of the Indian–Australian monsoon from the north to the south. Seasonal variation was most strongly correlated with the Australian Monsoon Index, whereas yearly variability was related to a greater number of climate indices, predominately the Tasman Sea and Indonesian sea surface temperature indices (both of which experienced a linear increase over the duration of the study) and the El Niño–Southern Oscillation indices. These findings highlight the importance of understanding the climatic processes driving variability and, subsequently, the importance of understanding the relationships between rainfall and climatic phenomena in the Northern Territory in order to project future rainfall patterns in the region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing heterogeneity of terrestrial hydrological and biogeochemical processes in earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a dataset with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, 500 m, 1, 2, 5, 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98% of variability in the variance of SOC stocks. We found moderately-accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ~ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks can improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Maximizing MWh: A statistical analysis of the performance of utility-scale photovoltaic projects in the United States

Despite significant cost declines utility-scale solar projects have to perform well over their lifetime in order to return profits in a low-PPA environment of under $50/MWh. Using multivariate regression analysis this paper examines the 2014 Net Capacity Factors for 128 utility-scale projects that came online before the end of 2013 and explores the impact (in decreasing order of importance) of global horizontal irradiance, tracking technology, inverter loading ratios and project vintage plus three other interactive variables on performance. The model complies with the assumptions of OLS regressions and explains 93% of the observed NCF variation.

Bolinger, M↗
DOE OSTI2022

Experiments and numerical modeling of surrogate droplet combustion for a 93 octane gasoline calibration fuel

Gasoline is the world’s most prolific liquid transportation fuel for ground transportation vehicles. Yet, a fundamental understanding of its burning characteristics is still lacking. Complicating this matter is the highly multicomponent nature of gasoline (comprised of hundreds of chemical species) and the seasonable variability of its composition due to variations in the crude oil feedstocks used in refining. The need to bring order to this complex problem has led to development of calibration fuels (Tier II in presented study) which on average will provide repeatable metrics that replicate performance of refined gasoline for various engine designs. This study presents results of experiments using the configuration of an isolated droplet to study the combustion dynamics of calibration fuel and three different surrogates (S4, S5, S6) for the calibration fuel. Droplet burning is under microgravity conditions, where gas transport is determined entirely by fuel evaporation in order to promote spherical symmetry in the burning process. The initial droplet diameters ranged between 0.55 mm and 0.60 mm. The droplets were spark-ignited and their burning histories were recorded by digital video cameras to obtain quantitative data. For each fuel, the evolutions of droplet, flame, and soot-shell diameters were measured to calculate the burn rates, flame-droplet diameter ratios (FSR) and soot-droplet diameter ratios. Additionally, a detailed numerical modeling is presented. This simulation includes multicomponent phase equilibrium, unsteady gas and liquid transport, radiative heat transfer, internal liquid diffusion and detailed combustion chemistry of different fuels during their burning process. Experiment results show that the calibration fuel and surrogates have a close burn rates and FSR, and S5 presents a relatively similar results with calibration fuel. Predictions from the numerical simulation using the surrogate are compared with experiment measurements, which showed a good agreement with the experiment results, including the droplet burning rate and FSR.

Guo, Songtao↗
DOE OSTI2012

A Variable Grid FDM Technique for Treating Solid-Liquid and Solid-Air Boundaries in Wave Propagation Modeling of Elastic Waves. Task 2, Computer Program

In Task1 we explained the layout of the staggered grid adopted in the UL0_2.4 a finite difference computer program developed by Pitarka (1996,1999). The objective of the second task is to modify the UL0_2.4 program in order to extend its application to computing elastic wave propagation in heterogeneous structures with irregular surface topography and solid-liquid boundaries. The new program UL0_2.4W preserves the structure and variable-grid finite-difference technique used in the original computer program. The list of computer programs for running the FD code, and programs for post processing the output data is given in the Appendix.

58 GEOSCIENCES↗
DOE OSTI2017

Quantifying Intrinsic Variability of Sagittarius A∗ Using Closure Phase Measurements of the Event Horizon Telescope

General relativistic magnetohydrodynamic (GRMHD) simulations of accretion disks and jets associated with supermassive black holes show variability on a wide range of timescales. On timescales comparable to or longer than the gravitational timescale t{sub G}=GM/c{sup 3}, variation may be dominated by orbital dynamics of the inhomogeneous accretion flow. Turbulent evolution within the accretion disk is expected on timescales comparable to the orbital period, typically an order of magnitude larger than t {sub G}. For Sgr A*, t {sub G} is much shorter than the typical duration of a VLBI experiment, enabling us to study this variability within a single observation. Closure phases, the sum of interferometric visibility phases on a triangle of baselines, are particularly useful for studying this variability. In addition to a changing source structure, variations in observed closure phase can also be due to interstellar scattering, thermal noise, and the changing geometry of projected baselines over time due to Earth rotation. We present a metric that is able to distinguish the latter two from intrinsic or scattering variability. This metric is validated using synthetic observations of GRMHD simulations of Sgr A*. When applied to existing multi-epoch EHT data of Sgr A*, this metric shows that the data are most consistent with source models containing intrinsic variability from source dynamics, interstellar scattering, or a combination of those. The effects of black hole inclination, orientation, spin, and morphology (disk or jet) on the expected closure phase variability are also discussed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

The Preliminary Verification of the 2-D Transport Module of Radiation Shielding Code ARES - Paper 33

ARES is a multi-group SN particle transport code system with arbitrary order anisotropic scattering. It is primarily used for the nuclear systems' shielding calculation and analysis in the case of one dimensional, two dimensional and three dimensional systems. ARES2D is the 2-D transport module of ARES code system. It is used to solve the first-order form of the steady-state Boltzmann transport equation in the two dimensional geometry with uniform rectangular mesh. The equation's energy dependence is modeled using multiple energy groups. The angular dependence is modeled using discrete ordinates method. The spatial variable is modeled using finite differencing scheme. The overall solution technique is source iteration with Partial Current Rebalance acceleration of the scattering source. ARES2D is capable of calculating k eigenvalue and fixed source problem with arbitrary order anisotropic scattering in two dimensional geometry. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2023

Phylogenomics and diversification of Sordariomycetes

The Sordariomycetes is a specious, morphologically diverse, and widely distributed class of the phylum Ascomycota that forms a well-supported clade diverged from Leotiomycetes. Aside from their ecological significance as plant and human pathogens, saprobes, endophytes, and fungicolous taxa, species of Sordariomycetes produces a wide range of chemically novel and diverse metabolites used in important fields. Recent phylogenetic analyses derived from a small number of genes have considerably increased our understanding of the family, order, and subclass relationships within Sordariomycetes, but several important groups have not been resolved well. In addition, there are various paraphyletic or polyphyletic groups. Moreover, the criteria used to establish higher ranks remain highly variable across different studies. Therefore, the taxonomy of Sordariomycetes is in constant flux, remains poorly understood, and is subject to much controversy. Here, for the first time, we have assembled a phylogenetic dataset containing 638 genomes representing the 156 genera, 50 families, and 17 orders and 5 subclasses of Sordariomycetes. This data set is based on 1124 genes and results in a well-resolved phylogenomic tree. We further constructed an evolutionary timeline of Sordariomycetes diversification based on the genomic data sets. Our divergence time estimate results are inconsistent with previous studies, suggesting estimates of node ages are less precise and varied. Based on these results, we discuss the higher ranks of Sordariomycetes and empirically propose an unprecedented taxonomic framework for the class.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Fractional order PID controller for improvement of PMSM speed control in aerospace applications

Because of the benefits reduced size, cost and maintenance, noise, CO2 emissions and increased control flexibility and precision, to meet these expectations, electrical equipment increasingly utilize in modern aircraft systems and aerospace industry rather than conventional mechanic, hydraulic, and pneumatic power systems. Electric motor drives are capable of converting electrical power to drive actuators, pumps, compressors, and other subsystems at variable speeds. In the past decades, permanent magnet synchronous motor (PMSM) and brushless dc (BLDC) motor were investigated for aerospace applications such as aircraft actuators. In this paper, the fractional-order PID controller is used in the design of speed loop of PMSM speed control system. Having more parameters for tuning fractional order PID controller lead to good performance ratio to integer order. This good performance is shown by comparison fractional order PID controller with the conventional PI and tuned PID controller by Genetic algorithm in MATLAB soft wear.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

A Nonstationary and Non-Gaussian Moving Average Model for Solar Irradiance

Historically, power has flowed from large power plants to customers. Increasing penetration of distributed energy resources such as solar power from rooftop photovoltaic has made the distribution network a two-way-street with power being generated at the customer level. The incorporation of renewables introduces additional uncertainty and variability into the power grid. Distribution network operation studies are being adapted to include renewables; however, such studies require high quality solar irradiance data that adequately reflect realistic meteorological variability. Data from satellite-based products are spatially complete, but temporally coarse, whereas solar irradiances exhibit high frequency variation at very fine timescales. We propose a new stochastic method for temporally downscaling global horizontal irradiance (GHI) to 1 min resolution, but we do not consider the spatial aspect due to limited availability of the in situ irradiance measurements. Solar irradiance's first and second-order structures vary diurnally and seasonally, and our model adapts to such nonstationarity. Empirical irradiance data exhibits highly non-Gaussian behavior; we develop a nonstationary and non-Gaussian moving average model that is shown to capture realistic solar variability at multiple timescales. We also propose a new estimation scheme based on Cholesky factors of empirical autocovariance matrices, bypassing difficult and inaccessible likelihood-based approaches. The model is demonstrated for a case study of three locations that are located in diverse climates through the United States. The model is compared against competitors from the literature and is shown to provide better uncertainty and variability quantification on testing data.

Cholesky factor↗