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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Curve fitting methods for solar radiation data modeling

This paper studies the use of several type of curve fitting method to smooth the global solar radiation data. After the data have been fitted by using curve fitting method, the mathematical model of global solar radiation will be developed. The error measurement was calculated by using goodness-fit statistics such as root mean square error (RMSE) and the value of R{sup 2}. The best fitting methods will be used as a starting point for the construction of mathematical modeling of solar radiation received in Universiti Teknologi PETRONAS (UTP) Malaysia. Numerical results indicated that Gaussian fitting and sine fitting (both with two terms) gives better results as compare with the other fitting methods.

14 SOLAR ENERGY↗
DOE OSTI2015

Notes on power of normality tests of error terms in regression models

Normality is one of the basic assumptions in applying statistical procedures. For example in linear regression most of the inferential procedures are based on the assumption of normality, i.e. the disturbance vector is assumed to be normally distributed. Failure to assess non-normality of the error terms may lead to incorrect results of usual statistical inference techniques such as t-test or F-test. Thus, error terms should be normally distributed in order to allow us to make exact inferences. As a consequence, normally distributed stochastic errors are necessary in order to make a not misleading inferences which explains a necessity and importance of robust tests of normality. Therefore, the aim of this contribution is to discuss normality testing of error terms in regression models. In this contribution, we introduce the general RT class of robust tests for normality, and present and discuss the trade-off between power and robustness of selected classical and robust normality tests of error terms in regression models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Accurate ab initio vibrational energies of methyl chloride

Two new nine-dimensional potential energy surfaces (PESs) have been generated using high-level ab initio theory for the two main isotopologues of methyl chloride, CH{sub 3}{sup 35}Cl and CH{sub 3}{sup 37}Cl. The respective PESs, CBS-35{sup HL}, and CBS-37{sup HL}, are based on explicitly correlated coupled cluster calculations with extrapolation to the complete basis set (CBS) limit, and incorporate a range of higher-level (HL) additive energy corrections to account for core-valence electron correlation, higher-order coupled cluster terms, scalar relativistic effects, and diagonal Born-Oppenheimer corrections. Variational calculations of the vibrational energy levels were performed using the computer program TROVE, whose functionality has been extended to handle molecules of the form XY {sub 3}Z. Fully converged energies were obtained by means of a complete vibrational basis set extrapolation. The CBS-35{sup HL} and CBS-37{sup HL} PESs reproduce the fundamental term values with root-mean-square errors of 0.75 and 1.00 cm{sup −1}, respectively. An analysis of the combined effect of the HL corrections and CBS extrapolation on the vibrational wavenumbers indicates that both are needed to compute accurate theoretical results for methyl chloride. We believe that it would be extremely challenging to go beyond the accuracy currently achieved for CH{sub 3}Cl without empirical refinement of the respective PESs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

TESTING THE DARK ENERGY WITH GRAVITATIONAL LENSING STATISTICS

We study the redshift distribution of two samples of early-type gravitational lenses, extracted from a larger collection of 122 systems, to constrain the cosmological constant in the {Lambda}CDM model and the parameters of a set of alternative dark energy models (XCDM, Dvali-Gabadadze-Porrati, and Ricci dark energy models), in a spatially flat universe. The likelihood is maximized for {Omega}{sub {Lambda}} = 0.70 {+-} 0.09 when considering the sample excluding the Sloan Lens ACS systems (known to be biased toward large image-separation lenses) and no-evolution, and {Omega}{sub {Lambda}} = 0.81 {+-} 0.05 when limiting to gravitational lenses with image separation {Delta}{theta} > 2'' and no-evolution. In both cases, results accounting for galaxy evolution are consistent within 1{sigma}. The present test supports the accelerated expansion, by excluding the null hypothesis (i.e., {Omega}{sub {Lambda}} = 0) at more than 4{sigma}, regardless of the chosen sample and assumptions on the galaxy evolution. A comparison between competitive world models is performed by means of the Bayesian information criterion. This shows that the simplest cosmological constant model-that has only one free parameter-is still preferred by the available data on the redshift distribution of gravitational lenses. We perform an analysis of the possible systematic effects, finding that the systematic errors due to sample incompleteness, galaxy evolution, and model uncertainties approximately equal the statistical errors, with present-day data. We find that the largest sources of systemic errors are the dynamical normalization and the high-velocity cutoff factor, followed by the faint-end slope of the velocity dispersion function.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2011

Comment on 'Modal expansion approach to optical-frequency-comb generation with monolithic whispering-gallery-mode resonators'

Authors of a recent paper [Y. K. Chembo and N. Yu, Phys. Rev. A 82, 033801 (2010)] claimed to have developed a general framework for description of nonlinear effects in whispering-gallery-mode resonators with particular focus on optical-frequency-comb generation. In this Comment we demonstrate that the author's approach contains mathematical errors affecting some of the results of the paper. Fortunately, analysis of this phenomenon using a mathematically more rigorous approach shows that the main conclusions of that paper remain intact.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Parton physics from a heavy-quark operator product expansion: Lattice QCD calculation of the fourth moment of the pion distribution amplitude

The pion light-cone distribution amplitude (LCDA) is an essential nonperturbative input for a range of high-energy exclusive processes in quantum chromodynamics. Building on our previous work, the continuum limit of the fourth Mellin moment of the pion LCDA is determined in quenched QCD using quark masses which correspond to a pion mass of 𝑚 𝜋 = 550 MeV. This calculation finds ⟨𝜉 2 ⟩ = 0.202⁢(8)⁢(9) and ⟨𝜉 4 ⟩ = 0.039⁢(28)⁢(11) where the first error indicates the combined statistical and systematic uncertainty from the analysis and the second indicates the uncertainty from working with Wilson coefficients computed to next-to-leading order. These results are presented in the $\overline{\textrm{MS}}$ scheme at a renormalization scale of 𝜇 = 2 GeV.

Detmold, William [Massachusetts Inst. of Technolog↗
DOE OSTI2019

X-ray mirror surface figure correction with nanometre precision controlled by layer stresses simulated by FEA

Hard X-rays with energies higher than several kiloelectronvolts can be focused to spot sizes below 10 nm with the present synchrotron beamlines, offering unique advantages for the chemical, elemental and structure analysis of matter. Nevertheless, a surface precision on the nanometre scale for the focusing optics is required and remains the main hurdle limiting X-ray analytical techniques with single-nanometre spatial resolution. On the other hand, to preserve the wavefront properties of coherent X-ray beams, precise control of the reflective mirror surface quality at the nanometre scale is demanded for X-ray free-electron laser applications. In this work, the surface shape of a multilayer-coated X-ray mirror is controlled by layer stresses. The desired surface profile of the mirror is differentiated to its second order to obtain its corresponding curvature profile. With a step size of 1 mm along the mirror length, different coating thicknesses are applied to create different layer thermal stresses from uniform temperature change. The mirror surface profile can be obtained by integrating the curvature profile to its second order and further corrected by moving constant values for the slope and height. The technical process is simulated by finite element analysis (FEA). A case study showed that the residual slope error and the residual height error between the desired shape and the FEA result are 0.22 µrad (r.m.s.) and 1.42 nm (r.m.s.), respectively.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Field-Array Benchmark of Commercial Bifacial PV Technologies with Publicly Available Data

We present results for a 75-kW field array deployed with rows of 5 different commercially available bifacial technologies. Four PERC (multi and mono) and 1 Silicon Heterojunction manufacturers are represented. Reference strings of equivalent monofacial PV modules are also installed in the 10-row field. High accuracy string-level DC monitoring and module-level measurements have been recorded for six months. Analysis indicates performance within expectation, with a cumulative model mean error within +/- 2% for both bifacial and monofacial models and cumulative bifacial energy gain between 6-9%. A custom-module to measure shading loss from the torque-tube was installed. One month data shows up to 6% irradiance non-uniformity. A fixed-tilt test-site with 3 years of bifacial data is also presented, with a bifacial gain of 3%.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2018

An integrated phenology modelling framework in r

Abstract Phenology is a first‐order control on productivity and mediates the biophysical environment by altering albedo, surface roughness length and evapotranspiration. Accurate and transparent modelling of vegetation phenology is therefore key in understanding feedbacks between the biosphere and the climate system. Here, we present the phenor r package and modelling framework. The framework leverages measurements of vegetation phenology from four common phenology observation datasets, the PhenoCam network, the USA National Phenology Network ( USA ‐ NPN ), the Pan European Phenology Project ( PEP 725), MODIS phenology ( MCD 12Q2) combined with (global) retrospective and projected climate data. We show an example analysis, using the phenor modelling framework, which quickly and easily compares 20 included spring phenology models for three plant functional types. An analysis of model skill using the root mean squared ( RMSE ) error shows little or no difference regardless of model structure, corroborating previous studies. We argue that addressing this issue will require novel model development combined with easy data assimilation as facilitated by our framework. In conclusion, we hope the phenor phenology modelling framework in the r language and environment for statistical computing will facilitate reproducibility and community driven phenology model development, in order to increase their overall predictive power, and leverage an ever growing number of phenology data products.

Hufkens, Koen↗
DOE OSTI2011

A Bayesian approach to real-time 3D tumor localization via monoscopic x-ray imaging during treatment delivery

Purpose: Monoscopic x-ray imaging with on-board kV devices is an attractive approach for real-time image guidance in modern radiation therapy such as VMAT or IMRT, but it falls short in providing reliable information along the direction of imaging x-ray. By effectively taking consideration of projection data at prior times and/or angles through a Bayesian formalism, the authors develop an algorithm for real-time and full 3D tumor localization with a single x-ray imager during treatment delivery. Methods: First, a prior probability density function is constructed using the 2D tumor locations on the projection images acquired during patient setup. Whenever an x-ray image is acquired during the treatment delivery, the corresponding 2D tumor location on the imager is used to update the likelihood function. The unresolved third dimension is obtained by maximizing the posterior probability distribution. The algorithm can also be used in a retrospective fashion when all the projection images during the treatment delivery are used for 3D localization purposes. The algorithm does not involve complex optimization of any model parameter and therefore can be used in a ''plug-and-play'' fashion. The authors validated the algorithm using (1) simulated 3D linear and elliptic motion and (2) 3D tumor motion trajectories of a lung and a pancreas patient reproduced by a physical phantom. Continuous kV images were acquired over a full gantry rotation with the Varian TrueBeam on-board imaging system. Three scenarios were considered: fluoroscopic setup, cone beam CT setup, and retrospective analysis. Results: For the simulation study, the RMS 3D localization error is 1.2 and 2.4 mm for the linear and elliptic motions, respectively. For the phantom experiments, the 3D localization error is < 1 mm on average and < 1.5 mm at 95th percentile in the lung and pancreas cases for all three scenarios. The difference in 3D localization error for different scenarios is small and is not statistically significant. Conclusions: The proposed algorithm eliminates the need for any population based model parameters in monoscopic image guided radiotherapy and allows accurate and real-time 3D tumor localization on current standard LINACs with a single x-ray imager.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

On the feasibility of optical-CT imaging in media of different refractive index

Purpose: Achieving accurate optical-CT 3D dosimetry without the use of viscous refractive index (RI) matching fluids would greatly increase convenience. Methods: Software has been developed to simulate optical-CT 3D dosimetry for a range of scanning configurations including parallel-beam, point, and converging light sources. For each configuration the efficacy of three refractive media was investigated: air, water, a fluid closely matched to PRESAGE{sup Registered-Sign }, and perfect matching (RI = 1.00, 1.33, 1.49, and 1.501 respectively). Reconstructions were performed using both filtered backprojection (FBP) and algebraic reconstruction technique (ART). The efficacy of the three configurations and the two algorithms was evaluated by calculating the usable radius (i.e., the outermost radius where data were accurate to within 2%), and gamma ({Gamma}) analysis. This definition recognizes that for optical-CT imaging, errors are greatest near the edge of the dosimeter, where refraction can be most pronounced. Simulations were performed on three types of dose distribution: uniform, volumetric modulated arc therapy (VMAT), and brachytherapy (Cs-137). Results: For a uniformly irradiated dosimeter the usable radius achieved with filtered backprojection was 68% for water-matching and 31% for dry-scanning in air. Algebraic reconstruction gave usable radii of 99% for both water and air (dry-scanning), indicating greater recovery of useful data for the uniform distribution. FBP and ART performed equally well for a VMAT dose distribution where less dose is delivered near the edge of the dosimeter. In this case, the usable radius was 86% and 53% for scanning in water and air, respectively. For brachytherapy, the usable radius was 99% and 98% for scanning in water and air, respectively using FBP, and a major decrease was seen with ART. Point source geometry provided 1%-2% larger usable radii than parallel geometry. Converging geometry recovered less usable dosimetry data (up to 10% reduced usable radii) than point and parallel geometries. A further disadvantage of converging geometry was an increased requirement on detector size by up to 18 Degree-Sign . Conclusions: For applications where dose information is not required in the periphery of the dosimeter, some dry and low-viscous matching configurations may be feasible. For all three dose distributions (uniform, VMAT, brachytherapy) the point source geometry produced slightly more favorable results (an extra 1%-2% usable radii) than parallel and converging. When dosimetry is required on the periphery, best results were obtained using close refractive matching and ART. A concern for water or dry-scanning is the increase in required detector size, introducing potential cost penalties for manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2016

SU-F-J-24: Setup Uncertainty and Margin of the ExacTrac 6D Image Guide System for Patients with Brain Tumors

Purpose: This study evaluated the setup uncertainties for brain sites when using BrainLAB’s ExacTrac X-ray 6D system for daily pretreatment to determine the optimal planning target volume (PTV) margin. Methods: Between August 2012 and April 2015, 28 patients with brain tumors were treated by daily image-guided radiotherapy using the BrainLAB ExacTrac 6D image guidance system of the Novalis-Tx linear accelerator. DUONTM (Orfit Industries, Wijnegem, Belgium) masks were used to fix the head. The radiotherapy was fractionated into 27–33 treatments. In total, 844 image verifications were performed for 28 patients and used for the analysis. The setup corrections along with the systematic and random errors were analyzed for six degrees of freedom in the translational (lateral, longitudinal, and vertical) and rotational (pitch, roll, and yaw) dimensions. Results: Optimal PTV margins were calculated based on van Herk et al.’s [margin recipe = 2.5∑ + 0.7σ − 3 mm] and Stroom et al.’s [margin recipe = 2∑ + 0.7σ] formulas. The systematic errors (∑) were 0.72, 1.57, and 0.97 mm in the lateral, longitudinal, and vertical translational dimensions, respectively, and 0.72°, 0.87°, and 0.83° in the pitch, roll, and yaw rotational dimensions, respectively. The random errors (σ) were 0.31, 0.46, and 0.54 mm in the lateral, longitudinal, and vertical rotational dimensions, respectively, and 0.28°, 0.24°, and 0.31° in the pitch, roll, and yaw rotational dimensions, respectively. According to van Herk et al.’s and Stroom et al.’s recipes, the recommended lateral PTV margins were 0.97 and 1.66 mm, respectively; the longitudinal margins were 1.26 and 3.47 mm, respectively; and the vertical margins were 0.21 and 2.31 mm, respectively. Conclusion: Therefore, daily setup verifications using the BrainLAB ExacTrac 6D image guide system are very useful for evaluating the setup uncertainties and determining the setup margin.∑σ.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

A tutorial review of machine learning-based model predictive control methods

Abstract This tutorial review provides a comprehensive overview of machine learning (ML)-based model predictive control (MPC) methods, covering both theoretical and practical aspects. It provides a theoretical analysis of closed-loop stability based on the generalization error of ML models and addresses practical challenges such as data scarcity, data quality, the curse of dimensionality, model uncertainty, computational efficiency, and safety from both modeling and control perspectives. The application of these methods is demonstrated using a nonlinear chemical process example, with open-source code available on GitHub. The paper concludes with a discussion on future research directions in ML-based MPC.

Wu, Zhe [Department of Chemical and Biomolecular E↗
DOE OSTI2023

IDAES-PSE 2.3.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost, most environmentally sustainable solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications.. New Features and Models • New diagnostics toolboxes and examples o Tutorial for using the DiagnosticsToolbox o Methods to identify potential evaluation errors in models o SVDToolbox for performing singular value decomposition analysis on models to identify possible degeneracies and poor scaling o DegeneracyHunter for identifying irreducible degenerate sets in models • Model for solid-liquid separation which takes two inputs (solid and liquid streams) and produces three outlets (solids, liquid entrained with solids and pure liquid) • Example of temperature swing adsorption in models_extra Deprecation Warnings • With the update to Pyomo 6.7.0, the plate heat exchanger model has begun failing tests on some CI platforms. If this is not addressed by the February release, this model may be removed due to failing tests. See #1294. Offers to help identify the cause and fix this issue are welcome. Improvements and bug fixes • Fixed oversight which precluded using Mixer and Separator models when inherent reactions were present in property package • Added reporting methods to the MSContactor model • Minor corrections in some examples where values were being fixed outside of declared variable bounds

DiagnosticsToolbox,IDAES,PSE,Process Systems Engin↗
DOE OSTI2013

RHIC orbit response analysis with LOCO Run 12

Orbit response matrix analysis (ORM) is a well-established technique used to find and correct linear optics errors in accelerators. The measurement consists of recording the change in the closed orbit around the ring in response to successively changing dipole corrector magnets by a known amount. The analysis is performed by adjusting parameters in the accelerator model until the difference between the modeled response matrix and the measurement is minimized. Typical parameters to adjust are quadrupole and skew quadrupole strength, dipole corrector magnet gains and rolls and BPM gains and rolls. The adjusted model should be a close approximation to the real machine as seen by the BPMS. The calculated changes in gain/strength can be applied to the real machine to return the linear optics to the design.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Measurement Uncertainty in One-of-a-kind Experiments

A golden standard in science is to repeat an experimental measurement multiple times and calculate the measured value with experimental uncertainty by following well developed statistical procedures. For various reasons – cost, technical difficulty, international treaties, ethics of dealing with human or animal subjects, ecology - many important experiments and observations can not be repeated. Astronomy, earthquakes, hurricanes produce data from one-of-a-kind events. When information is not available in any other way, it should not be dismissed as qualitative, anecdotal evidence only. Analyzed in a mathematically rigorous way, it produces quantitative experimental data. Analysis of data from one-of-a-kind event differs from analysis of repeated experiments’ data. For repeated experiments, the experimental error includes a range of true values generated by repetitions of the experiment, and measurement uncertainty caused by detectors. They are independent. Repetitions of any experiment, as similar as achievable, always have built-in differences resulting in a range of the true values rather than in a single value. Measurement uncertainty depends on the measurement system only. Digital measurements have very small uncertainty, frequently smaller than the range of true experimental values resulting from built-in differences in the experiment repetitions. When data from one–of–a kind experiment are analyzed, only the measurement uncertainty can be reported.

42 ENGINEERING↗
DOE OSTI2021

WSF PISA example for SAFER pilot

On October 15, 2021, the Radioactive and Hazardous Waste Management Facility Manager declared a Potential Inadequacy in the Safety Analysis (PISA) due to a new information relating to an error discovered in calculation AB-WSF-20-002. Calculation AB-WSF-20-002 is used to determine source terms and heat release rates for vehicle and aircraft impacts with fuel fires involving TRU waste containers. The source term for an aircraft’s impact has different source terms factors (i.e., DR, ARF, RF, LPF) that are applied to multiple categories of drums impacted in the accident scenario based on the physical stresses of the aircraft impact and involvement in the subsequent fuel pool fire. The source terms of the multiple categories of affected drums are summed to determine the final source term for the accident scenario. Certain categories of affected drums are modeled to lose their lid, causing material to eject and burn unconfined on the ground. For these specific categories, a lower ARF value was incorrectly applied in AB-WSF-20-002 (i.e., an ARF value of 1E-3 was used instead of the DOE-STD-5506-2007 directed ARF value of 1E-2). For these categories, the ARF is applied to a relatively small number of low-activity drums (i.e., 17 drums at 2.9 PE-Ci each) compared to the total number of drums affected (i.e., 166 drums totaling 621.8 PE-Ci). Therefore, this error is not expected to significantly increase final dose for the accident scenario. No immediate actions or compensatory measures are required to maintain the facility in a safe condition.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Implementing machine learning methods on QICK hardware for qubit readout & control

Quantum readout and control is a fundamental aspect of quantum computing that requires accurate measurement of qubit states. Errors emerge in all stages, from initialization to readout, and identifying errors in post-processing necessitates resource-intensive statistical analysis. In our work, we use a lightweight fully-connected neural network (NN) to classify states of a transmon system with no prior processing. Our NN accelerator yields higher fidelities (92%) than the classical matched filter method (84%). By exploiting the natural parallelism of NNs and their placement near the source of data on field-programmable gate arrays (FPGAs), we can achieve ultra-low latency on the Quantum Instrumentation Control Kit (QICK). Integrating machine learning methods on QICK opens several pathways for efficient real-time processing of quantum circuits.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗