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NASA NTRS2005

A First and Second Order Moment Approach to Probabilistic Control Synthesis

This paper presents a robust control design methodology based on the estimation of the first two order moments of the random variables and processes that describe the controlled response. Synthesis is performed by solving an multi-objective optimization problem where stability and performance requirements in time- and frequency domains are integrated. The use of the first two order moments allows for the efficient estimation of the cost function thus for a faster synthesis algorithm. While reliability requirements are taken into account by using bounds to failure probabilities, requirements related to undesirable variability are implemented by quantifying the concentration of the random outcome about a deterministic target. The Hammersley Sequence Sampling and the First- and Second-Moment- Second-Order approximations are used to estimate the moments, whose accuracy and associated computational complexity are compared numerically. Examples using output-feedback and full-state feedback with state estimation are used to demonstrate the ideas proposed.

Crespo, Luis G.↗

NASA NTRS2010

A New Representative for Small-Body Gravity Estimation

One of the options proposed in the 2009 Review of the U. S. Human Spaceflight Plans Committee calls for the consideration of robotic and human missions to asteroids. Beginning in 2000, the NEAR Shoemaker spacecraft inserted into orbit about the asteroid 433 Eros, and studied it for a year before landing. The Hayabusa satellite journeyed to 25143 Itokawa, and operated in a proximity of the asteroid for several months before landing to collect a return sample. Additionally, the DAWN satellite, which was launched in 2007, will explore the dwarf-planet Ceres and the asteroid 4 Vesta in the next three years. These are just several examples of current interests in exploring asteroids. In this paper, we explore an alternative for estimating the gravity field of a small body using observations of an orbiting satellite. Our approach uses two new mathematical tools, the quadratures (on a sphere) invariant under the icosahedral group, and a multiresolution representation of the gravity potential. With the near optimal quadratures on the sphere, we minimize the number of parameters needed to recover a function. Also, instead of estimating the coefficients of the spherical harmonics, the new quadratures allow us to estimate directly the values of the gravity field since they offer an analogue of the Lagrange-type interpolation.

Jones, Brandon A.↗

DOE OSTI2014

Land-Based Wind Plant Balance-of-System Cost Drivers and Sensitivities (Poster)

With Balance of System (BOS) costs contributing up to 30% of the installed capital cost, it is fundamental to understand the BOS costs for wind projects as well as potential cost trends for larger turbines. NREL developed a BOS model using project cost estimates developed by industry partners. Aspects of BOS covered include engineering and permitting, foundations for various wind turbines, transportation, civil work, and electrical arrays. The data introduce new scaling relationships for each BOS component to estimate cost as a function of turbine parameters and size, project parameters and size, and geographic characteristics. Based on the new BOS model, an analysis to understand the non‐turbine wind plant costs associated with turbine sizes ranging from 1-6 MW and wind plant sizes ranging from 100-1000 MW has been conducted. This analysis establishes a more robust baseline cost estimate, identifies the largest cost components of wind project BOS, and explores the sensitivity of the capital investment cost and the levelized cost of energy to permutations in each BOS cost element. This presentation shows results from the model that illustrate the potential impact of turbine size and project size on the cost of energy from US wind plants.

17 WIND ENERGY↗

DOE OSTI2021

Does jackknife scale really matter for accurate large-scale structure covariances?

ABSTRACT The jackknife method gives an internal covariance estimate for large-scale structure surveys and allows model-independent errors on cosmological parameters. Using the SDSS-III BOSS CMASS sample, we study how the jackknife size and number of resamplings impact the precision of the covariance estimate on the correlation function multipoles and the error on the inferred baryon acoustic scale. We compare the measurement with the MultiDark Patchy mock galaxy catalogues, and we also validate it against a set of lognormal mocks with the same survey geometry. We build several jackknife configurations that vary in size and number of resamplings. We introduce the Hartlap factor in the covariance estimate that depends on the number of jackknife resamplings. We also find that it is useful to apply the tapering scheme to estimate the precision matrix from a limited number of resamplings. The results from CMASS and mock catalogues show that the error estimate of the baryon acoustic scale does not depend on the jackknife scale. For the shift parameter α, we find an average error of 1.6 per cent, 2.2 per cent and 1.2 per cent, respectively, from CMASS, Patchy, and lognormal jackknife covariances. Despite these uncertainties fluctuate significantly due to some structural limitations of the jackknife method, our α estimates are in reasonable agreement with published pre-reconstruction analyses. Jackknife methods will provide valuable and complementary covariance estimates for future large-scale structure surveys.

Favole, Ginevra (ORCID:000000028218563X)↗

NASA NTRS1985

Extraction of aerodynamic parameters for aircraft at extreme flight conditions

The maximum likelihood estimator has been used to extract stability and control derivatives from flight data for many years. Most of the literature on aircraft estimation concentrates on new developments and applications, assuming familiarity with basic concepts. This paper briefly discusses the maximum likelihood estimator and the aircraft equations of motion that the estimator uses. The current strength and limitations associated with obtaining flight-determined aerodynamic coefficients in extreme flight conditions is assessed. The importance of the careful combining of wind tunnel results (or calculations) and flight results and the thorough evaluation of the mathematical model is emphasized. The basic concepts of minimization and estimation are examined for a simple computed aircraft example, and the cost functions that are to be minimized during estimation are defined and discussed. Graphic representations of the cost functions are given to help illustrate the minimization process. Finally, the basic concepts are generalized, and estimation of stability and control derivatives from flight data is discussed.

Iliff, K. W.↗

NASA NTRS1985

Extraction of aerodynamic parameters for aircraft at extreme flight conditions

The maximum likelihood estimator was used to extract stability and control derivatives from flight data for many years. Most of the literature on aircraft estimation concentrates on new development and applications, assuming familiarity with basic concepts. The maximum likelihood estimator and the aircraft equations of motion that the estimator uses are discussed. The current strength and limitations associated with obtaining flight-determined aerodynamic coefficients in extreme flight conditions are assessed. The importance of the careful combining of wind tunnel results (or calculations) and flight results and the thorough evaluation of the mathematical model is emphasized. The basic concepts of minimization and estimation are examined for a simple computed aircraft example, and the cost functions that are to be minimized during estimation are defined and discussed. Graphic representations of the cost functions are given to help illustrate the minimization process. Finally, the basic concepts are generalized, and estimation of stability and control derivatives from flight data is discussed.

Iliff, K. W.↗

DOE OSTI2014

Inequalities for majorizing analytic functions and their applications to rational trigonometric functions and polynomials

New inequalities are established for analytic functions satisfying Meiman's majorization conditions. Estimates for values of and differential inequalities involving rational trigonometric functions with an integer majorant on an interval of length less than the period and with prescribed poles which are symmetrically positioned relative to the real axis, as well as differential inequalities for trigonometric polynomials in some classes, are given as applications. These results improve several theorems due to Meiman, Genchev, Smirnov and Rusak. Bibliography: 27 titles.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Association mapping across a multitude of traits collected in diverse environments in maize

Abstract Classical genetic studies have identified many cases of pleiotropy where mutations in individual genes alter many different phenotypes. Quantitative genetic studies of natural genetic variants frequently examine one or a few traits, limiting their potential to identify pleiotropic effects of natural genetic variants. Widely adopted community association panels have been employed by plant genetics communities to study the genetic basis of naturally occurring phenotypic variation in a wide range of traits. High-density genetic marker data—18M markers—from 2 partially overlapping maize association panels comprising 1,014 unique genotypes grown in field trials across at least 7 US states and scored for 162 distinct trait data sets enabled the identification of of 2,154 suggestive marker-trait associations and 697 confident associations in the maize genome using a resampling-based genome-wide association strategy. The precision of individual marker-trait associations was estimated to be 3 genes based on a reference set of genes with known phenotypes. Examples were observed of both genetic loci associated with variation in diverse traits (e.g., above-ground and below-ground traits), as well as individual loci associated with the same or similar traits across diverse environments. Many significant signals are located near genes whose functions were previously entirely unknown or estimated purely via functional data on homologs. This study demonstrates the potential of mining community association panel data using new higher-density genetic marker sets combined with resampling-based genome-wide association tests to develop testable hypotheses about gene functions, identify potential pleiotropic effects of natural genetic variants, and study genotype-by-environment interaction.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Scaled Vecchia Approximation for Fast Computer-Model Emulation

Many scientific phenomena are studied using computer experiments consisting of multiple runs of a computer model while varying the input settings. Gaussian processes (GPs) are a popular tool for the analysis of computer experiments, enabling interpolation between input settings, but direct GP inference is computationally infeasible for large datasets. We adapt and extend a powerful class of GP methods from spatial statistics to enable the scalable analysis and emulation of large computer experiments. Specifically, we apply Vecchia’s ordered conditional approximation in a transformed input space, with each input scaled according to how strongly it relates to the computer-model response. The scaling is learned from the data by estimating parameters in the GP covariance function using Fisher scoring. Our methods are highly scalable, enabling estimation, joint prediction, and simulation in near-linear time in the number of model runs. In several numerical examples, our approach substantially outperformed existing methods.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Quantifying Uncertainty in Ice Particle Velocity–Dimension Relationships Using MC3E Observations

Abstract Ice particle terminal fall velocity ( V t ) is fundamental for determining microphysical processes, yet remains extremely challenging to measure. Current theoretical best estimates of V t are functions of Reynolds number. The Reynolds number is related to the Best number, which is a function of ice particle mass, area ratio ( A r ), and maximum dimension ( D max ). These estimates are not conducive for use in most models since model parameterizations often take the form , where ( α , β ) depend on habit and D max . A previously developed framework is used to determine surfaces of equally plausible ( α , β ) coefficients whereby ice particle size/shape distributions are combined with V t best estimates to determine mass- ( V M ) or reflectivity-weighted ( V Z ) velocities that closely match parameterized V M ,SD or V Z ,SD calculated using the ( α , β ) coefficients using two approaches. The first uses surfaces of equally plausible ( a , b ) coefficients describing mass ( M )–dimension relationships (i.e., ) to calculate mass- or reflectivity-weighted velocity from size/shape distributions that are then used to determine ( α , β ) coefficients. The second investigates how uncertainties in A r , D max , and size distribution N ( D ) affect V M or V Z . For seven of nine flight legs flown on 20 and 23 May 2011 during the Mesoscale Continental Convective Clouds Experiment (MC3E), uncertainty from natural parameter variability—namely, the variability in ice particle parameters in similar meteorological conditions—exceeds uncertainties arising from different A r assumptions or D max estimates. The combined uncertainty between A r , D max , and N ( D ) produced smaller variability in ( α , β ) compared to varying M ( D ), demonstrating M ( D ) must be accurately quantified for model fall velocities. Primary sources of uncertainty vary considerably depending on environmental conditions. Significance Statement Ice particle fall velocity is fundamental for numerous processes within clouds, and hence is a critical property that must be accurately represented in weather and climate models. Using aircraft observations of ice particle shapes and sizes obtained in clouds behind midlatitude thunderstorms, this work develops a new framework for estimating ice particle fall velocities and their uncertainty, including quantifying the importance of different uncertainty sources from cloud microphysics measurements. Natural parameter variability contributes the most uncertainty in ice particle fall velocity estimates, although other sources can also be important contributors to uncertainty in certain conditions. Additional work examining ice particle data is needed to further understand how dependent uncertainty in certain ice particle properties are to local environmental conditions.

Meteorology & Atmospheric Sciences↗

DOE OSTI2016

Pion Structure Function from Leading Neutron Electroproduction and SU(2) Flavor Asymmetry

We examine the efficacy of pion exchange models to simultaneously describe leading neutron electroproduction at HERA and the dbar-ubar flavor asymmetry in the proton. A detailed chi^2 analysis of the ZEUS and H1 cross sections, when combined with constraints on the pion flux from Drell-Yan data, allows regions of applicability of one-pion exchange to be delineated. The analysis disfavors several models of the pion flux used in the literature, and yields an improved extraction of the pion structure function and its uncertainties at small parton momentum fractions in the pion. We also provide estimates for leading proton structure functions in upcoming tagged deep-inelastic scattering experiments at Jefferson Lab on the deuteron with forward protons.

Melnitchouk, Wolodymyr↗

NASA NTRS1990

PASS Spacecraft Antenna Technology Assessment

The purpose was to generate estimates of mechanical performance for the classes of spacecraft antenna under construction for application to the Personal Access Satellite System (PASS). These performance data are needed for the support of trade studies involving antenna system development. The classes of antenna considered included: (1) rigid non-deployable antenna structures; (2) mechanical deployable antenna concepts; (3) inflatable deployable antenna concepts; and (4) mesh deployable antenna concepts. The estimates of mechanical performance are presented in terms of structural weight and cost as a function of the reflector size. Estimates of aperture surface precision are presented for a few discrete antenna sizes. The range of reflector size is 1 to 4 meters for non-deployable structures and 2 to 8 meters for deployable structures. The range of reflector surface precision is lambda/30 to lambda/50 for 20 and 30 GHz, respectively.

Freeland, R. E.↗

NASA NTRS1991

Expert systems for assembly sequence evaluation

The objective is to identify delivered orbital subassemblies derived from a phase A conceptual space vehicle design while minimizing on-orbit assembly complexity. The topics covered are presented in viewgraph form and include the following: an orbital assembly scenario; subassemblies; subassembly identification and simulation model; estimating subassembly interfaces by engineering functional allocation using MBR; representative data base of interface connections; vehicle decomposition model; connection interface estimation model results; knowledge-source 1 and 2 results; knowledge-source 3 -- connection-index results (Boeing NTR-2016 CI-profile); KS3 algorithm, and KS3 flight manifest results.

Jolly, Steve↗

DOE OSTI2014

Sci—Fri PM: Dosimetry—04: Radiation out-of-field dose in the treatment of pediatric central nervous system malignancies

Children diagnosed with central nervous system (CNS) malignancies often receive radiotherapy, which can cause radiogenic late effects. In order to identify and reduce the risk of these late effects, we must understand the radiation doses that these children receive. Modern treatment planning systems accurately estimate the absorbed dose within the treatment fields but poorly estimate the dose outside them. The purpose of our study was to measure the out-of-field dose for children receiving localized radiotherapy for CNS cancer and apply an analytical model for estimating dose as a function of distance from the field edge. Radiation fields designed for a 12-year-old boy treated in our clinic were applied to an anthropomorphic phantom containing more than 200 thermoluminescent dosimeters. A double-Gaussian function of absorbed dose versus distance from the field edge (i.e., 50% isodose line) was applied, and parameters were allowed to vary and were fit to the model by minimizing the root mean square deviation, RMSD. The fitted model accurately predicted the dose from distances of 4 cm to 50 cm (RMSD = 0.54 cGy/Gy), but the model was not useful in estimating dose for distances less than 4 cm because of wide variation in measured dose, and the double-Gaussian model failed by systematically underestimating the dose beyond 50 cm. In conclusion, the double-Gaussian model may be applicable for points at distances from the field edge between 4 cm and 50 cm, where most children's radiosensitive tissues are located, but for points beyond 50 cm, an improvement should be investigated.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Generalized adsorption isotherms for molecular and dissociative adsorption of a polar molecular species on two polar surface geometries: Perovskite (100) (Pm-3m) and fluorite (111) (Fm-3m)

Lattice based kinetic Monte Carlo simulations have been used to determine a functional form for the second order adsorption isotherms on two commonly investigated crystal surfaces: the (111) fluorite surface and the (100) perovskite surface which has the same geometric symmetry as the NaCl (100) surface. The functional form is generalized to be applicable to all values of the equilibrium constant by a shift along the pressure axis. Functions have been determined for estimating the pressure at which a desired coverage would be achieved and, conversely, for estimating the coverage at a certain pressure. The generalized form has been calculated by investigating the surface adsorbate coverage across a range of thermodynamic equilibrium constants that span the range 10{sup −26} to 10{sup 13}. The equations have been shown to be general for any value of the adsorption equilibrium constant.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Sparse low rank approximation of potential energy surfaces with applications in estimation of anharmonic zero point energies and frequencies

We introduce a method that exploits sparse representation of potential energy surfaces (PES) on a polynomial basis set selected by compressed sensing . The method is useful for studies involving large numbers of PES evaluations, such as the search for local minima, transition states, or integration. We apply this method for estimating zero point energies and frequencies of molecules using a three step approach. In the first step, we interpret the PES as a sparse tensor on polynomial basis and determine its entries by a compressed sensing based algorithm using only a few PES evaluations. Then, we establish a rank reduction strategy to compress this tensor in a suitable low-rank canonical tensor format using standard tensor compression tools. This allows representing a high dimensional PES as a small sum of products of one dimensional functions. Finally, a low dimensional Gauss–Hermite quadrature rule is used to integrate the product of sparse canonical low-rank representation of PES and Green’s function in the second-order diagrammatic vibrational many-body Green’s function theory (XVH2) for estimation of zero-point energies and frequencies. Numerical tests on molecules considered in this work indicate a more efficient scaling of computational cost with molecular size as compared to other methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Biochemical methane potential (BMP) tests: Reducing test time by early parameter estimation

Highlights: • Early parameters prediction of BMP model is achieved by using sensitivity functions. • Minimum testing time for early parameter estimation is related to kinetic constant. • Balanced regression improves the accuracy of estimated parameters. - Abstract: Biochemical methane potential (BMP) test is a key analytical technique to assess the implementation and optimisation of anaerobic biotechnologies. However, this technique is characterised by long testing times (from 20 to >100 days), which is not suitable for waste utilities, consulting companies or plants operators whose decision-making processes cannot be held for such a long time. This study develops a statistically robust mathematical strategy using sensitivity functions for early prediction of BMP first-order model parameters, i.e. methane yield (B{sub 0}) and kinetic constant rate (k). The minimum testing time for early parameter estimation showed a potential correlation with the k value, where (i) slowly biodegradable substrates (k ≤ 0.1 d{sup −1}) have a minimum testing times of ≥15 days, (ii) moderately biodegradable substrates (0.1 −1 ) have a minimum testing times between 8 and 15 days, and (iii) rapidly biodegradable substrates (k ≥ 0.2 d{sup −1}) have testing times lower than 7 days.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2014

Noise correction of turbulent spectra obtained from Acoustic Doppler Velocimeters

Accurately estimated auto-spectral density functions are essential for characterization of turbulent flows, and they also have applications in computational fluid dynamics modeling, site and inflow characterization for hydrokinetic turbines, and inflow turbulence generation. The Acoustic Doppler Velocimeter (ADV) provides single-point temporally resolved data, that are used to characterize turbulent flows in rivers, seas, and oceans. However, ADV data are susceptible to contamination from various sources, including instrument noise, which is the intrinsic limit to the accuracy of acoustic velocity measurements. Due to the presence of instrument noise, the spectra obtained are altered at high frequencies. The focus of this study is to develop a robust and effective method for accurately estimating auto-spectral density functions from ADV data by reducing or removing the spectral contribution derived from instrument noise. For this purpose, the “Noise Auto-Correlation” (NAC) approach was developed, which exploits the correlation properties of instrument noise to identify and remove its contribution from spectra. The spectra estimated using the NAC approach exhibit increased fidelity and a slope of -5/3 in the inertial range, which is typically observed for turbulent flows. Finally, this study also compares the effectiveness of low-pass Gaussian filters in removing instrument noise with that of the NAC approach. For the data used in this study, both the NAC and Gaussian filter approaches are observed to be capable of removing instrument noise at higher frequencies from the spectra. However, the NAC results are closer to the expected frequency power of -5/3 in the inertial sub-range.

Acoustic Doppler Velocimeter↗