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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Error mitigation, optimization, and extrapolation on a trapped-ion testbed

Current noisy intermediate-scale quantum (NISQ) trapped-ion devices are subject to errors which can significantly impact the accuracy of calculations if left unchecked. A form of error mitigation called zero noise extrapolation (ZNE) can decrease an algorithm’s sensitivity to these errors without increasing the number of required qubits. Here we explore different methods for integrating this error mitigation technique into the Variational Quantum Eigensolver (VQE) algorithm for calculating the ground state of the HeH + molecule at 0.8 Å in the presence of experimental noise. Using the Quantum Scientific Computing Open User Testbed (QSCOUT) trapped-ion device, we test three methods of scaling noise for extrapolation: time stretching the two-qubit gates, scaling the sideband detuning parameter, and inserting two-qubit gate identity operations into the ansatz circuit. We find that time stretching and sideband detuning scaling fail to scale the noise on our particular hardware in a way that can be extrapolated to zero noise. Scaling our noise with global gate identity insertions and extrapolating after variational optimization, we achieve error suppression of 96.8%, resulting in an energy estimate within –0.004 ± 0.04 hartree of the ground state energy. This is an improvement, but still outside the chemical accuracy threshold of 0.0016 hartree. Furthermore, our results show that the efficacy of this error mitigation technique depends on choosing the correct implementation for a given device architecture.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

AI/ML-Enhanced Wind Forecasts for Reducing Uncertainty in Prescribed Fire Planning

Prescribed fire is a vital tool for ecosystem management and wildfire risk reduction but its escalation is constrained by overly conservative burn windows because of uncertainties, for instance, in wind forecasts. This review describes the state of the art in weather product use by fire/smoke models and identifies three priority research gaps that artificial intelligence/machine learning (AI/ML) is well positioned to address: (1) spatial and temporal downscaling to meter-scale, sub-hourly wind fields; (2) bias correction for systematic model errors in complex terrain; and (3) robust uncertainty quantification to inform ensemble-based simulations. Emerging AI/ML techniques offer promising frameworks to address all three challenges. By providing high-resolution, bias-corrected, and probabilistic wind fields, AI/ML-enhanced forecasts will allow for expanded burn windows, improved ignition strategy design and a reduced reliance on expert intuition, especially when a prescribed fire is introduced into new areas.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Broadband distortion modeling in Lyman-α forest BAO fitting

Recently, the Lyman-α absorption observed in the spectra of high-redshift quasars has been used as a tracer of large-scale structure by means of the three-dimensional Lyman-α forest auto-correlation function at redshift z≃ 2.3, but the need to fit the quasar continuum in every absorption spectrum introduces a broadband distortion that is difficult to correct and causes a systematic error for measuring any broadband properties. Here, we describe a k-space model for this broadband distortion based on a multiplicative correction to the power spectrum of the transmitted flux fraction that suppresses power on scales corresponding to the typical length of a Lyman-α forest spectrum. In implementing the distortion model in fits for the baryon acoustic oscillation (BAO) peak position in the Lyman-α forest auto-correlation, we find that the fitting method recovers the input values of the linear bias parameter b F and the redshift-space distortion parameter β F for mock data sets with a systematic error of less than 0.5%. Applied to the auto-correlation measured for BOSS Data Release 11, our method improves on the previous treatment of broadband distortions in BAO fitting by providing a better fit to the data using fewer parameters and reducing the statistical errors on βF and the combination b F (1+β F ) by more than a factor of seven. The measured values at redshift z=2.3 are βF=1.39 +0.11 +0.24 +0.38 -0.10 -0.19 -0.28 and bF(1+βF)=-0.374 +0.007 +0.013 +0.020 -0.007 -0.014 -0.022 (1σ, 2σ and 3σ statistical errors). Our fitting software and the input files needed to reproduce our main results are publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Understanding the difference in cohesive energies between alpha and beta tin in DFT calculations

The transition temperature between the low-temperature alpha phase of tin to beta tin is close to the room temperature (T{sub αβ} = 13{sup 0}C), and the difference in cohesive energy of the two phases at 0 K of about ΔE{sub coh} =0.02 eV/atom is at the limit of the accuracy of DFT (density functional theory) with available exchange-correlation functionals. It is however critically important to model the relative phase energies correctly for any reasonable description of phenomena and technologies involving these phases, for example, the performance of tin electrodes in electrochemical batteries. Here, we show that several commonly used and converged DFT setups using the most practical and widely used PBE functional result in ΔE{sub coh} ≈0.04 eV/atom, with different types of basis sets and with different models of core electrons (all-electron or pseudopotentials of different types), which leads to a significant overestimation of T{sub αβ}. We show that this is due to the errors in relative positions of s and p –like bands, which, combined with different populations of these bands in α and β Sn, leads to overstabilization of alpha tin. We show that this error can be effectively corrected by applying a Hubbard +U correction to s –like states, whereby correct cohesive energies of both α and β Sn can be obtained with the same computational scheme. We quantify for the first time the effects of anharmonicity on ΔE{sub coh} and find that it is negligible.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Waste Form Release Data Package for the 2005 Integrated Disposal Facility Performance Assessment. Erratum

This report refers to or contains K g values for glasses LAWA44, LAWB45 and LAWC22 affected by calculations errors as identified by Papathanassiu et al. (2011). The corrected K g values are reported in an erratum included in the revised version of the original report. The revised report can be referenced as follows: Pierce E. M. et al. (2004) Waste Form Release Data Package for the 2005 Integrated Disposal Facility Performance Assessment. PNNL-14805 Rev. 0 Erratum. Pacific Northwest National Laboratory, Richland, WA, USA.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Technical Note: On the calculation of stopping-power ratio for stoichiometric calibration in proton therapy

Purpose: The quantitative effects of assumptions made in the calculation of stopping-power ratios (SPRs) are investigated, for stoichiometric CT calibration in proton therapy. The assumptions investigated include the use of the Bethe formula without correction terms, Bragg additivity, the choice of I-value for water, and the data source for elemental I-values. Methods: The predictions of the Bethe formula for SPR (no correction terms) were validated against more sophisticated calculations using the SRIM software package for 72 human tissues. A stoichiometric calibration was then performed at our hospital. SPR was calculated for the human tissues using either the assumption of simple Bragg additivity or the Seltzer-Berger rule (as used in ICRU Reports 37 and 49). In each case, the calculation was performed twice: First, by assuming the I-value of water was an experimentally based value of 78 eV (value proposed in Errata and Addenda for ICRU Report 73) and second, by recalculating the I-value theoretically. The discrepancy between predictions using ICRU elemental I-values and the commonly used tables of Janni was also investigated. Results: Errors due to neglecting the correction terms to the Bethe formula were calculated at less than 0.1% for biological tissues. Discrepancies greater than 1%, however, were estimated due to departures from simple Bragg additivity when a fixed I-value for water was imposed. When the I-value for water was calculated in a consistent manner to that for tissue, this disagreement was substantially reduced. The difference between SPR predictions when using Janni’s or ICRU tables for I-values was up to 1.6%. Experimental data used for materials of relevance to proton therapy suggest that the ICRU-derived values provide somewhat more accurate results (root-mean-square-error: 0.8% versus 1.6%). Conclusions: The conclusions from this study are that (1) the Bethe formula can be safely used for SPR calculations without correction terms; (2) simple Bragg additivity can be reasonably assumed for compound materials; (3) if simple Bragg additivity is assumed, then the I-value for water should be calculated in a consistent manner to that of the tissue of interest (rather than using an experimentally derived value); (4) the ICRU Report 37 I-values may provide a better agreement with experiment than Janni’s tables.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

LOFAR facet callibration

LOFAR, the Low-Frequency Array, is a powerful new radio telescope operating between 10 and 240 MHz. LOFAR allows detailed sensitive high-resolution studies of the low-frequency radio sky. At the same time LOFAR also provides excellent short baseline coverage to map di use extended emission. However, producing high-quality deep images is challenging due to the presence of direction dependent calibration errors, caused by imperfect knowledge of the station beam shapes and the ionosphere. Furthermore, the large data volume and presence of station clock errors present additional di culties. In this paper we present a new calibration scheme, which we name facet calibration, to obtain deep high-resolution LOFAR High Band Antenna images using the Dutch part of the array. This scheme solves and corrects the direction dependent errors in a number of facets that cover the observed eld of view. Facet calibration provides close to thermal noise limited images for a typical 8 hr observing run at ~5'' resolution, meeting the speci cations of the LOFAR Tier-1 northern survey.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Enhancing quantum annealing accuracy through replication-based error mitigation *

Abstract Quantum annealers like those manufactured by D-Wave Systems are designed to find high quality solutions to optimization problems that are typically hard for classical computers. They utilize quantum effects like tunneling to evolve toward low-energy states representing solutions to optimization problems. However, their analog nature and limited control functionalities present challenges to correcting or mitigating hardware errors. As quantum computing advances towards applications, effective error suppression is an important research goal. We propose a new approach called replication based mitigation (RBM) based on parallel quantum annealing (QA). In RBM, physical qubits representing the same logical qubit are dispersed across different copies of the problem embedded in the hardware. This mitigates hardware biases, is compatible with limited qubit connectivity in current annealers, and is well-suited for currently available noisy intermediate-scale quantum annealers. Our experimental analysis shows that RBM provides solution quality on par with previous methods while being more flexible and compatible with a wider range of hardware connectivity patterns. In comparisons against standard QA without error mitigation on larger problem instances that could not be handled by previous methods, RBM consistently gets better energies and ground state probabilities across parameterized problem sets.

Djidjev, Hristo N. (ORCID:0000000192868824)↗
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 OSTI2019

Charge transfer excitation energies from ground state density functional theory calculations

Calculating charge transfer (CT) excitation energies with high accuracy and low computational cost is a challenging task. Kohn-Sham density functional theory (KS-DFT), due to its efficiency and accuracy, has achieved great success in describing ground state problems. To extend to excited state problems, our group recently demonstrated an approach with good numerical results to calculate low-lying and Rydberg excitation energies of an N-electron system from a ground state KS or generalized KS calculations of an (N-1)-electron system via its orbital energies. In the present work, we explore further the same methodology to describe CT excitations. Numerical results from this work show that performance of conventional density functional approximations (DFAs) is not as good for CT excitations as for other excitations due to the delocalization error. Applying localized orbital scaling correction (LOSC) to conventional DFAs, a recently developed method in our group to effectively reduce the delocalization error, can improve the results. Overall, the performance of this methodology is better than time dependent DFT (TDDFT) with conventional DFAs. In addition, it shows that results from LOSC-DFAs in this method reach similar accuracy to other methods, such as ΔSCF, G 0 W 0 with Bethe-Salpeter equations, particle-particle random phase approximation, and even high-level wavefunction methods like CC2. Our analysis shows that the correct 1/R trend for CT excitation can be captured from LOSC-DFA calculations, stressing that the application of DFAs with the minimal delocalization error is essential within this methodology. This work provides an efficient way to calculate CT excitation energies from ground state DFT.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Joint Non-Parametric Correction Estimator for Excess Relative Risk Regression in Survival Analysis with Exposure Measurement Error

Summary Observational epidemiological studies often confront the problem of estimating exposure–disease relationships when the exposure is not measured exactly. We investigate exposure measurement error in excess relative risk regression, which is a widely used model in radiation exposure effect research. In the study cohort, a surrogate variable is available for the true unobserved exposure variable. The surrogate variable satisfies a generalized version of the classical additive measurement error model, but it may or may not have repeated measurements. In addition, an instrumental variable is available for individuals in a subset of the whole cohort. We develop a non-parametric correction estimator by using data from the subcohort and further propose a joint non-parametric correction estimator using all observed data to adjust for exposure measurement error. An optimal linear combination estimator of the joint non-parametric correction and non-parametric correction is further developed. The estimators proposed are non-parametric, which are consistent without imposing a covariate or error distribution, and are robust to heteroscedastic errors. Finite sample performance is examined via a simulation study. We apply the developed methods to data from the Radiation Effects Research Foundation, in which chromosome aberration is used to adjust for the effects of radiation dose measurement error on the estimation of radiation dose responses.

Wang, Ching-Yun↗
DOE OSTI2016

Individual pore and interconnection size analysis of macroporous ceramic scaffolds using high-resolution X-ray tomography

The pore interconnection size of β-tricalcium phosphate scaffolds plays an essential role in the bone repair process. Although, the μCT technique is widely used in the biomaterial community, it is rarely used to measure the interconnection size because of the lack of algorithms. In addition, discrete nature of the μCT introduces large systematic errors due to the convex geometry of interconnections. We proposed, verified and validated a novel pore-level algorithm to accurately characterize the individual pores and interconnections. Specifically, pores and interconnections were isolated, labeled, and individually analyzed with high accuracy. The technique was verified thoroughly by visually inspecting and verifying over 3474 properties of randomly selected pores. This extensive verification process has passed a one-percent accuracy criterion. Scanning errors inherent in the discretization, which lead to both dummy and significantly overestimated interconnections, have been examined using computer-based simulations and additional high-resolution scanning. Then accurate correction charts were developed and used to reduce the scanning errors. Only after the corrections, both the μCT and SEM-based results converged, and the novel algorithm was validated. Material scientists with access to all geometrical properties of individual pores and interconnections, using the novel algorithm, will have a more-detailed and accurate description of the substitute architecture and a potentially deeper understanding of the link between the geometric and biological interaction. - Highlights: •An algorithm is developed to analyze individually all pores and interconnections. •After pore isolating, the discretization errors in interconnections were corrected. •Dummy interconnections and overestimated sizes were due to thin material walls. •The isolating algorithm was verified through visual inspection (99% accurate). •After correcting for the systematic errors, algorithm was validated successfully.

36 MATERIALS SCIENCE↗
DOE OSTI2026

How to Minimize Faradaic Efficiency Error in Electrochemical CO 2 Reduction for Gas Products

Faradaic efficiency (FE) is an important metric for evaluating electrochemical processes, such as carbon dioxide reduction, that is often used for performance comparisons. Although the equation to calculate FE is well-known, details needed to yield accurate values are often overlooked, potentially leading to errors exceeding 100%. Avoiding any errors is crucial for drawing correct conclusions, especially during a catalysis optimization process. Factors with high potential for FE errors include incorrect mass flow rates and temperature values, imprecise gas chromatography calibrations, and uncorrected gas viscosities, while factors with less potential are also identified. In conclusion, this manuscript presents FE calculation guidelines intended for both newcomers and experts in the field of electrochemical fuel production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Effect of light scattering on biological tissue thermometry from photoluminescence spectra of up-conversion nanoparticles

Photoluminescence spectra of the up-conversion nanoparticles NaYF{sub 4} : Y{sup 3+}, Er{sup 3+} arranged under a layer of an adipose tissue have been recorded in a wide temperature range. It is shown that if nanoparticle temperature is determined from the photoluminescence spectra, an error arises related to spectrum distortion due to light scattering in a sample. A correction algorithm for reducing this error is developed. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

A new open‐path eddy covariance method for nitrous oxide and other trace gases that minimizes temperature corrections

Abstract Low‐power, open‐path gas sensors enable eddy covariance (EC) flux measurements in remote areas without line power. However, open‐path flux measurements are sensitive to fluctuations in air temperature, pressure, and humidity. Laser‐based, open‐path sensors with the needed sensitivity for trace gases like methane (CH 4 ) and nitrous oxide (N 2 O) are impacted by additional spectroscopic effects. Corrections for these effects, especially those related to temperature fluctuations, often exceed the flux of gases, leading to large uncertainties in the associated fluxes. For example, the density and spectroscopic corrections arising from temperature fluctuations can be one or two orders of magnitude greater than background N 2 O fluxes. Consequently, measuring background fluxes with laser‐based, open‐path sensors is extremely challenging, particularly for N 2 O and gases with similar high‐precision requirements. We demonstrate a new laser‐based, open‐path N 2 O sensor and a general approach applicable to other gases that minimizes temperature‐related corrections for EC flux measurements. The method identifies absorption lines with spectroscopic effects in the opposite direction of density effects from temperature and, thus, density and spectroscopic effects nearly cancel one another. The new open‐path N 2 O sensor was tested at a corn ( Zea mays L.) field in Southwestern Michigan, United States. The sensor had an optimal precision of 0.1 ppbv at 10 Hz and power consumption of 50 W. Field trials showed that temperature‐related corrections were 6% of density corrections, reducing EC random errors by 20‐fold compared to previously examined lines. Measured open‐path N 2 O EC fluxes showed excellent agreement with those made with static chambers ( m = 1.0 ± 0.3; r 2 = .96). More generally, we identified absorption lines for CO 2 and CH 4 flux measurements that can reduce the temperature‐related corrections by 10–100 times compared to existing open‐path sensors. The proposed method provides a new direction for future open‐path sensors, facilitating the expansion of accurate EC flux measurements.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Bias Correction in Urban Building Energy Modeling for Chicago Using Machine Learning

Urban-scale building energy modeling (UBEM) holds promise for optimizing energy usage across extensive geographic regions. However, there is a recognized bias between simulated energy consumption and actual measured data. This study, based on building data from Chicago, delved into bias correction techniques for enhancing the accuracy of UBEM energy consumption estimates. Initially, the AutoBEM simulation yielded a normalized mean bias error (NMBE) of 1.1% and 51% of Coefficient of the Variation of the Root Mean Square Error (CVRMSE) after outlier exclusion. To address this, three bias correction methods were deployed: Average Mean Bias Error based bias correction, Quantile mapping bias correction, and Machine learning-based bias correction using Linear Regression and Random Forest models. Post-correction results exhibited marked improvement. The NMBE values were diminished to 0 for Average MBE-based, 0.36 for Quantile Mapping, and 0 for Machine Learning-based corrections. Concurrently, the CVRMSE values registered reductions from an original 51 to 50.8 for Quantile Mapping, and 38.56 for Machine Learning-based corrections, pointing towards the effectiveness of specific bias correction methods in refining the precision of UBEM energy predictions. Such accurate estimations are paramount for informed energy planning and urban policy-making.

Chowdhury, Shovan↗
DOE OSTI2024

The rise and fall of stretched bond errors: Extending the analysis of Perdew–Zunger self-interaction corrections of reaction barrier heights beyond the LSDA

Incorporating self-interaction corrections (SIC) significantly improves chemical reaction barrier height predictions made using density functional theory methods. We present a detailed orbital-by-orbital analysis of these corrections for three semi-local density functional approximations (DFAs) situated on the three lowest rungs of Jacob’s ladder of approximations. The analysis is based on Fermi–Löwdin Orbital Self-Interaction Correction (FLOSIC) calculations performed at several steps along the reaction pathway from the reactants (R) to the transition state (TS) to the products (P) for four representative reactions selected from the BH76 benchmark set. For all three functionals, the major contribution to self-interaction corrections of the barrier heights can be traced to stretched bond orbitals that develop near the TS configuration. The magnitude of the ratio of the self-exchange–correlation energy to the self-Hartree energy (XC/H) for a given orbital is introduced as an indicator of one-electron self-interaction error. XC/H = 1.0 implies that an orbital’s self-exchange–correlation energy exactly cancels its self-Hartree energy and that the orbital, therefore, makes no contribution to the SIC in the FLOSIC scheme. For the practical DFAs studied here, XC/H spans a range of values. Here, the largest values are obtained for stretched or strongly lobed orbitals. We show that significant differences in XC/H for corresponding orbitals in the R, TS, and P configurations can be used to identify the major contributors to the SIC of barrier heights and reaction energies. Based on such comparisons, we suggest that barrier height predictions made using the strongly constrained and appropriately normed meta-generalized gradient approximation may have attained the best accuracy possible for a semi-local functional using the Perdew–Zunger SIC approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗