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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 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Optimization of an Impedance-Matched Test Fixture with the Modal Projection Error

Across many industries and engineering disciplines, components and systems are designed and deployed into their operational environment of intended use. It is the desire of the design agency to be able to predict whether their component or system will function in its shock and vibration environments or if it will fail due to mechanical stresses. One method to determine if the component will survive the shock and vibration environments is to expose the component to the operational environment in a laboratory. One difficulty in executing a representative laboratory test is that the component may not have the same boundary condition in the laboratory as in the operational configuration. This paper examines the use of parameterized optimization to design the test fixture in order to better match the operational configuration. Several frequency and modal-based objective functions are examined for the optimization. The study shows that the Modal Projection Error objective function performs the best of the functions studied. The efficacy of the Modal Projection Error is demonstrated with respect to dynamic test fixture design on several analytical and experimental exemplars.

dynamic↗
DOE OSTI2016

Error correction in short time steps during the application of quantum gates

We propose a modification of the standard quantum error-correction method to enable the correction of errors that occur due to the interaction with a noisy environment during quantum gates without modifying the codification used for memory qubits. Using a perturbation treatment of the noise that allows us to separate it from the ideal evolution of the quantum gate, we demonstrate that in certain cases it is necessary to divide the logical operation in short time steps intercalated by correction procedures. A prescription of how these gates can be constructed is provided, as well as a proof that, even for the cases when the division of the quantum gate in short time steps is not necessary, this method may be advantageous for reducing the total duration of the computation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Online randomized interpolative decomposition with a posteriori error estimator for temporal PDE data reduction

Traditional low-rank approximation is a powerful tool for compressing large data matrices that arise in simulations of partial differential equations (PDEs), but suffers from high computational cost and requires several passes over the PDE data. The compressed data may also lack interpretability thus making it difficult to identify feature patterns from the original data. Here, to address these issues, we present an online randomized algorithm to compute the interpolative decomposition (ID) of large-scale data matrices in situ. Compared to previous randomized IDs that used the QR decomposition to determine the column basis, we adopt a streaming ridge leverage score-based column subset selection algorithm that dynamically selects proper basis columns from the data and thus avoids an extra pass over the data to compute the coefficient matrix of the ID. In particular, we adopt a single-pass error estimator based on the non-adaptive Hutch++ algorithm to provide real-time error approximation for determining the best coefficients. As a result, our approach only needs a single pass over the original data and thus is suitable for large and high-dimensional matrices stored outside of core memory or generated in PDE simulations. A strategy to improve the accuracy of the reconstructed data gradient, when desired, within the ID framework is also presented. We provide numerical experiments on turbulent channel flow and ignition simulations, and on the NSTX Gas Puff Image dataset, comparing our algorithm with the offline ID algorithm to demonstrate its utility in real-world applications.

Column subset selection↗
DOE OSTI2023

Piecewise linear approximation with minimum number of linear segments and minimum error: A fast approach to tighten and warm start the hierarchical mixed integer formulation

In several areas of economics and engineering, it is often necessary to fit discrete data points or approximate nonlinear functions with continuous functions. Piecewise linear (PWL) functions are a convenient way to achieve this. PWL functions can be modeled in mathematical problems using only linear and integer variables. Moreover, there is a computational benefit in using PWL functions that have the least possible number of segments. This work proposes a novel hierarchical mixed integer linear programming (MILP) formulation that identifies a continuous PWL approximation with minimum number of linear segments for a given target maximum error. The proposed MILP formulation also identifies the solution with the least maximum error among the solutions with minimum number of segments. Then, this work proposes a fast iterative algorithm that identifies non necessarily continuous PWL approximations by solving O(S log N) linear programming (LP) problems, where N is the number of data points and S is the minimum number of segments in the non necessarily continuous case. This work demonstrates that tight bounds for the MILP problem can be derived from these approximations. Next, a fast algorithm is introduced to transform a non necessarily continuous PWL approximation into a continuous one. Finally, the tight bounds and the continuous PWL approximations are used to tighten and warm start the MILP problem. The tightened formulation is shown in experimental results to be more efficient, especially for large data sets, with a solution time that is up to two orders of magnitude less than the existing literature.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Techno-economic implications and cost of forecasting errors in solar PV power production using optimized deep learning models

Accurate solar Photovoltaic (PV) power forecasting is important for enhancing both the performance and economic feasibility of PV systems. This study evaluates several deep learning models, including Dense Neural Networks (DNN), Long Short-Term Memory (LSTM), Convolutional Neural Networks (CNN), and a hybrid LSTMCNN model, for predicting PV power production one day in advance. Prior to optimization, the models exhibited relatively high errors, with the best model (DNN) achieving a Root Mean Square Error (RMSE) of 31.13 kW and a coefficient of determination (R 2 ) of 62.15 %. After employing Bayesian optimization, the LSTM-CNN model demonstrated the best performance, with the RMSE reduced to 9.79 kW and R 2 improved to 97.62 %, showcasing significant enhancement in predictive accuracy. Here, the economic evaluation considered three cases: rewards for underestimation (0.08 USD/kWh), no rewards, and penalties for both over-and underestimation (120 % of the utility tariff). In the rewards scenario, the LSTM-CNN model reduced the Levelized Cost of Electricity (LCOE) by 4 %, while in the penalty scenario, a backup diesel generator would have increased the LCOE by 49 %. Additionally, the LSTM-CNN model minimized financial losses, achieving the lowest penalties and maximizing net cash flow compared to other models, demonstrating its overall technical and economic superiority.

Deep learning↗
DOE OSTI2023

A study of examiner accuracy in cartridge case comparisons. Part 1: Examiner error rates

This report describes a study undertaken to estimate examiner (not laboratory) error rates for false Identifications and false Eliminations when comparing an unknown to a collection of three known cartridge cases. Volunteer active examiners with Association of Firearm and Toolmark Examiners (AFTE) membership or working in laboratories that participate in the Association of Crime Laboratory Directors (ASCLD) were provided with 15 sets of three known and one questioned cartridge cases fired from a collection of 25 new Ruger SR9 handguns. Remington 9-mm Luger (manufacturer designation L9MM3) ammunition was used and comparison sets were made up of cartridge cases fired within 100 cartridges of each other for each gun. Examiners were provided with a background survey, an answer sheet allowing for the AFTE Range of Conclusions, and return shipping materials. In addition to determining whether the known and questioned cartridge cases were fired with the same handgun, examiners were also asked to assess how many of the three knowns in each set were suitable for comparison, providing an estimated rate of how often each firearm used in the study produces useable, quality marks. The participating examiners were provided with both same-source and different-source comparison sets allowing the study to assess both error rates. Responses were received from 218 participating examiners. The overall rate of false Eliminations was estimated as 0.367% from comparisons known to be from the same firearm but reported as Eliminations. The overall rate of false Identifications was estimated as 1.01% from comparisons known to be from different firearms but reported as Identifications. The rates are not uniform across the sample population with a few examiners providing most of the false Identification responses. Rates of poor-quality mark production varied across the 25 sample handguns; those rates were 2.3% (±1.4%). Both false Elimination and false Identification rates are comparable to or lower than the rate of production of poor-quality marks by the firearms used in this study.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Overview of oxygen opacity experiments at the National Ignition Facility and investigation of potential systematic errors

Experiments to measure oxygen opacity at stellar interior conditions have been performed at the National Ignition Facility in a Discovery Science campaign. These experiments utilize the Opacity-on-NIF platform with a sample comprised of O, Mg, and Si. The spectral data from the Opacity Spectrometer cover the 1000–2000 eV photon energy range showing bound-free continuum absorption from O and line absorption from Mg and Si. DANTE and the Gated X-ray Detector are employed to measure the sample plasma’s temperature and density, respectively. Initial data show lower transmission than expected by theoretical models, raising questions of whether potential background or data uniformity concerns could produce systematic errors in the inferred transmission. Here, we investigate three concerns thought to be important for the oxygen opacity data, including instrumental scattered background, sample self-emission non-uniformity, and backlight continuum non-uniformity. Additionally, we show the effect of a recently developed method to account for 2nd order crystal reflection. The total effect of these concerns on one experiment is found to be small compared to the observed difference between the inferred transmission and a model calculation at the inferred temperature and density. Thus, we conclude that these potential sources of systematic error cannot account for the observed difference, increasing the likelihood of a real effect due to the high temperature and density conditions. However, because this is only a single experiment, we cannot make a firm conclusion. More experiments measuring the opacity and necessary calibrations are needed to assess the reproducibility and uncertainty of this result.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Dose Uncertainties in IMPT for Oropharyngeal Cancer in the Presence of Anatomical, Range, and Setup Errors

Purpose: Setup, range, and anatomical uncertainties influence the dose delivered with intensity modulated proton therapy (IMPT), but clinical quantification of these errors for oropharyngeal cancer is lacking. We quantified these factors and investigated treatment fidelity, that is, robustness, as influenced by adaptive planning and by applying more beam directions. Methods and Materials: We used an in-house treatment planning system with multicriteria optimization of pencil beam energies, directions, and weights to create treatment plans for 3-, 5-, and 7-beam directions for 10 oropharyngeal cancer patients. The dose prescription was a simultaneously integrated boost scheme, prescribing 66 Gy to primary tumor and positive neck levels (clinical target volume-66 Gy; CTV-66 Gy) and 54 Gy to elective neck levels (CTV-54 Gy). Doses were recalculated in 3700 simulations of setup, range, and anatomical uncertainties. Repeat computed tomography (CT) scans were used to evaluate an adaptive planning strategy using nonrigid registration for dose accumulation. Results: For the recalculated 3-beam plans including all treatment uncertainty sources, only 69% (CTV-66 Gy) and 88% (CTV-54 Gy) of the simulations had a dose received by 98% of the target volume (D98%) >95% of the prescription dose. Doses to organs at risk (OARs) showed considerable spread around planned values. Causes for major deviations were mixed. Adaptive planning based on repeat imaging positively affected dose delivery accuracy: in the presence of the other errors, percentages of treatments with D98% >95% increased to 96% (CTV-66 Gy) and 100% (CTV-54 Gy). Plans with more beam directions were not more robust. Conclusions: For oropharyngeal cancer patients, treatment uncertainties can result in significant differences between planned and delivered IMPT doses. Given the mixed causes for major deviations, we advise repeat diagnostic CT scans during treatment, recalculation of the dose, and if required, adaptive planning to improve adequate IMPT dose delivery.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Human DNA polymerase η promotes RNA-templated error-free repair of DNA double-strand breaks

A growing body of evidence indicates that RNA plays a critical role in orchestrating DNA double-strand break repair (DSBR). Recently, we showed that homologous nascent RNA can be used as a template for error-free repair of double-strand breaks (DSBs) in the transcribed genome and to restore the missing sequence at the break site via the transcription-coupled classical nonhomologous end-joining (TC-NHEJ) pathway. TC-NHEJ is a complex multistep process in which a reverse transcriptase (RT) is essential for synthesizing the DNA strand from template RNA. However, the identity of the RT involved in the TC-NHEJ pathway remained unknown. Here, we report that DNA polymerase eta (Pol η), known to possess RT activity, plays a critical role in TC-NHEJ. We found that Pol η forms a multiprotein complex with RNAP II and other TC-NHEJ factors, while also associating with nascent RNA. Moreover, purified Pol η, along with DSBR proteins PNKP, XRCC4, and Ligase IV can fully repair RNA templated 3'-phosphate-containing gapped DNA substrate. In addition, we demonstrate here that Pol η deficiency leads to accumulation of R-loops and persistent strand breaks in the transcribed genes. Finally, we determined that, in Pol η depleted but not in control cells, TC-NHEJ-mediated repair was severely abrogated when a reporter plasmid containing a DSB with several nucleotide deletion within the E. coli lacZ gene was introduced for repair in lacZ-expressing mammalian cells. Thus, our data strongly suggest that RT activity of Pol η is required in error-free DSBR.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Leveraging interpolation models and error bounds for verifiable scientific machine learning

Effective verification and validation techniques for modern scientific machine learning workflows are challenging to devise. Statistical methods are abundant and easily deployed, but often rely on speculative assumptions about the data and methods involved. Error bounds for classical interpolation techniques can provide mathematically rigorous estimates of accuracy, but often are difficult or impractical to determine computationally. Here, in this work, we present a best-of-both-worlds approach to verifiable scientific machine learning by demonstrating that (1) multiple standard interpolation techniques have informative error bounds that can be computed or estimated efficiently; (2) comparative performance among distinct interpolants can aid in validation goals; (3) deploying interpolation methods on latent spaces generated by deep learning techniques enables some interpretability for black-box models. We present a detailed case study of our approach for predicting lift-drag ratios from airfoil images. Code developed for this work is available in a public Github repository.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Emittance growth due to random force error

In Refs. Qiang (2019) and Kesting (2015), the authors showed that the emittance growth rate due to the force error of macroparticle sampling will be proportional to the step size of simulation. In this note, we show that for the random force error, the emittance growth rate will be independent of the step size, which is consistent with the simulation observation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Systematic error analysis in the absolute hydrogen gas jet polarimeter at RHIC

The Polarized Atomic Hydrogen Gas Jet Target polarimeter (HJET) is operated at the Relativistic Heavy Ion Collider (RHIC) since 2004 to measure the absolute polarization of each colliding proton beam. Polarimeter detectors and data acquisition were upgraded in 2015 to increase the solid angle, energy range, and to improve the energy and time resolution. These upgrades along with an improved beam intensity and polarization allowed us to greatly reduce the statistical and systematic errors for the proton polarization measurements in RHIC Runs 15 (E beam = 100 GeV) and 17 (255 GeV). For a typical 8 hour RHIC store, the measured proton beam average polarization was about P beam ~ 55 ± 2.0 stat ± 0.3 syst %. The elastic pp analyzing power, AN(t)~0.04, was determined with a precision of about |δA N (t)|~0.0002 in the momentum transfer squared range 0.001<-t<0.020 GeV 2 . In this paper we present a detailed systematic error analysis of the polarization measurements at HJET. Perspectives of using the HJET based absolute polarimeters in the future Electron Ion Collider (EIC) will be also discussed.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

An error-controlled adaptive time-stepping method for particle advancement in coupled CFD-DEM simulations

Coupled Computational-Fluid-Dynamics (CFD) and Discrete-Element-Method (DEM) models provide an accurate description of multiphase physical systems where a solid granular particle phase exists in an underlying gaseous continuous medium. The time integration of the granular phase in these simulations is typically handled using an explicit scheme with a constant time-step among all particles that is invariant in time to resolve inter-particle collisions. A locally third-order accurate adaptive time integration technique for particles that employs an embedded locally second-order scheme for error determination is presented in this work. The particle time-step size is dynamically adapted based on solution error, thus leading to significant savings in computational time. The efficacy of our scheme is quantified using four test cases of varying complexity (binary collision, homogeneous cooling system, fluidized bed and hopper discharge). The adaptive time-stepping method exhibits improved performance (~ 2–3 times in most of the cases studied) compared to three commonly used non-adaptive time-step methods (first-order Euler-explicit, second-order Adams-Bashforth and third-order Runge-Kutta schemes), while maintaining the same level of accuracy and parallel scalability.

42 ENGINEERING↗
DOE OSTI2014

Towards eliminating systematic errors caused by the experimental conditions in Biochemical Methane Potential (BMP) tests

Highlights: • The evaluated factors introduce significant systematic errors (10–38%) in BMP tests. • Ambient temperature (T) has the most substantial impact (∼10%) at low altitude. • Ambient pressure (p) has the most substantial impact (∼68%) at high altitude. • Continuous monitoring of T and p is not necessary for kinetic calculations. - Abstract: The Biochemical Methane Potential (BMP) test is increasingly recognised as a tool for selecting and pricing biomass material for production of biogas. However, the results for the same substrate often differ between laboratories and much work to standardise such tests is still needed. In the current study, the effects from four environmental factors (i.e. ambient temperature and pressure, water vapour content and initial gas composition of the reactor headspace) on the degradation kinetics and the determined methane potential were evaluated with a 2{sup 4} full factorial design. Four substrates, with different biodegradation profiles, were investigated and the ambient temperature was found to be the most significant contributor to errors in the methane potential. Concerning the kinetics of the process, the environmental factors’ impact on the calculated rate constants was negligible. The impact of the environmental factors on the kinetic parameters and methane potential from performing a BMP test at different geographical locations around the world was simulated by adjusting the data according to the ambient temperature and pressure of some chosen model sites. The largest effect on the methane potential was registered from tests performed at high altitudes due to a low ambient pressure. The results from this study illustrate the importance of considering the environmental factors’ influence on volumetric gas measurement in BMP tests. This is essential to achieve trustworthy and standardised results that can be used by researchers and end users from all over the world.

09 BIOMASS FUELS↗
DOE OSTI2021

A quantitative assessment of the model form error of friction models across different interface representations for jointed structures

Hysteretic models are widely used to model frictional interactions in joints to recreate experimental behavior. However, it is unclear which models are best suited for fitting or predicting the responses of structures. Here, the present study evaluates 26 friction model/interface representation combinations to quantify the model form error. A Quasi-Static Modal Analysis approach (termed Rayleigh Quotient Nonlinear Modal Analysis) is adopted to calculate the nonlinear system response, and a Multi-Objective Optimization is solved to fit experimental data of the first mode of the Brake-Reuß Beam. Optimized parameters from the first mode are applied to the second and third bending modes to quantify the predictive ability of the models. Formulations for both tracing full hysteresis loops and recreating hysteresis loops from a single loading curve (Masing assumptions) are considered. Smoothly varying models applied to a five patch representation showed the highest flexibility (for fitting mode 1) and good predictive potential (for modes 2 and 3). For a second formulation, which uses 152 frictional elements to represent the interface, the physically motivated spring in series with a Coulomb slip model (elastic dry friction) has high error for fitting mode 1 and performs near the middle for predicting higher modes. For both interface representation, the best fit models are not the most physical, but rather the ones with the most parameters (as expected); however, the more physical models perform somewhat better for predicting the higher modes.

42 ENGINEERING↗
DOE OSTI2020

Unmasking Static Correlation Error in Hybrid Kohn–Sham Density Functional Theory

To uncover the way Hartree–Fock exchange brings static correlation error into hybrid Kohn–Sham density functional theory, we compare the potential energy curves of four diatomic molecules, namely, H 2 , F 2 , HF, and NaF, using both restricted and unrestricted Kohn–Sham theory. Here, we find that increasing the percentage of Hartree–Fock exchange significantly increases the static correlation error because Hartree–Fock exchange replaces the ability of local exchange in density functionals to account for the localization effects associated with static correlation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

The Good, the Bad, and the Ugly: Pseudopotential Inconsistency Errors in Molecular Applications of Density Functional Theory

The pseudopotential (PP) approximation is one of the most common techniques in computational chemistry. Despite its long history, the development of custom PPs has not tracked with the explosion of different density functional approximations (DFAs). As a result, the use of PPs with exchange/correlation models for which they were not developed is widespread, although this practice is known to be theoretically unsound. The extent of PP inconsistency errors (PPIEs) associated with this practice has not been systematically explored across the types of energy differences commonly evaluated in chemical applications. Here, we evaluate PPIEs for a number of PPs and DFAs across 196 chemically relevant systems of both transition-metal and main-group elements, as represented by the W4-11, TMC34, and S22 data sets. Near the complete basis set limit, these PPs are found to cleanly approach all-electron (AE) results for noncovalent interactions but introduce root-mean-squared errors (RMSEs) upwards of 15 kcal mol –1 into predictions of covalent bond energies for a number of popular DFAs. We achieve significant improvements through the use of empirical atom- and DFA-specific PP corrections, indicating considerable systematicity of the PPIEs. The results of this work have implications for chemical modeling in both molecular contexts and for DFA design, which we discuss.

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

A Nucleotide-Analogue-Induced Gain of Function Corrects the Error-Prone Nature of Human DNA Polymerase iota

Y-family DNA polymerases participate in replication stress and DNA damage tolerance mechanisms. The properties that allow these enzymes to copy past bulky adducts or distorted template DNA can result in a greater propensity for them to make mistakes. Of the four human Y-family members, human DNA polymerase iota (hpol{iota}) is the most error-prone. In the current study, we elucidate the molecular basis for improving the fidelity of hpol{iota} through use of the fixed-conformation nucleotide North-methanocarba-2{prime}-deoxyadenosine triphosphate (N-MC-dATP). Three crystal structures were solved of hpol{iota} in complex with DNA containing a template 2{prime}-deoxythymidine (dT) paired with an incoming dNTP or modified nucleotide triphosphate. The ternary complex of hpol{iota} inserting N-MC-dATP opposite dT reveals that the adenine ring is stabilized in the anti orientation about the pseudo-glycosyl torsion angle, which mimics precisely the mutagenic arrangement of dGTP:dT normally preferred by hpol{iota}. The stabilized anti conformation occurs without notable contacts from the protein but likely results from constraints imposed by the bicyclo[3.1.0]hexane scaffold of the modified nucleotide. Unmodified dATP and South-MC-dATP each adopt syn glycosyl orientations to form Hoogsteen base pairs with dT. The Hoogsteen orientation exhibits weaker base-stacking interactions and is less catalytically favorable than anti N-MC-dATP. Thus, N-MC-dATP corrects the error-prone nature of hpol{iota} by preventing the Hoogsteen base-pairing mode normally observed for hpol{iota}-catalyzed insertion of dATP opposite dT. These results provide a previously unrecognized means of altering the efficiency and the fidelity of a human translesion DNA polymerase.

59 BASIC BIOLOGICAL SCIENCES↗