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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A backward SDE method for uncertainty quantification in deep learning

Here, we develop a backward stochastic differential equation based probabilistic machine learning method, which formulates a class of stochastic neural networks as a stochastic optimal control problem. An efficient stochastic gradient descent algorithm is introduced with the gradient computed through a backward stochastic differential equation. Convergence analysis for stochastic gradient descent optimization and numerical experiments for applications of stochastic neural networks are carried out to validate our methodology in both theory and performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Expediting Scientific Data Analysis with Reorganization of Data

Data producers typically optimize the layout of data files to minimize the write time. In most cases, data analysis tasks read these files in access patterns different from the write patterns causing poor read performance. In this paper, we introduce Scientific Data Services (SDS), a framework for bridging the performance gap between writing and reading scientific data. SDS reorganizes data to match the read patterns of analysis tasks and enables transparent data reads from the reorganized data. We implemented a HDF5 Virtual Object Layer (VOL) plugin to redirect the HDF5 dataset read calls to the reorganized data. To demonstrate the effectiveness of SDS, we applied two parallel data organization techniques: a sort-based organization on a plasma physics data and a transpose-based organization on mass spectrometry imaging data. We also extended the HDF5 data access API to allow selection of data based on their values through a query interface, called SDS Query. We evaluated the execution time in accessing various subsets of data through existing HDF5 Read API and SDS Query. We showed that reading the reorganized data using SDS is up to 55X faster than reading the original data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

An Analysis of Muon Neutrino Disappearance from the NuMI Beam Using an Optimal Track Fitter

The NOvA experiment is a long-baseline neutrino oscillation experiment based out of Fermilab National Accelerator Laboratory that uses two liquid scintillator detectors, one at Fermilab (the \near" detector) and a second 14 kton detector in northern Minnesota (the \far" detector.) The primary physics goals of the NOvA experiment are to measure neutrino mixing parameters through both the v μ disappearance and v e appearance channels using neutrinos from the newly upgraded NuMI beam line. The NOvA v μ disappearance analysis can significantly improve the world's best measurement of sin 2 θ 23 . This analysis proceeds by using the measured v μ charged-current energy spectrum in the near detector to predict the spectrum in the far detector, and comparing this to the measured spectrum to obtain a best fit for the oscillation parameters sin 2 θ 23 and Δm 2 32 . Since this fit is governed by the shape of the energy spectrum, the best fit will be maximized by obtaining the best possible energy resolution for the individual neutrino events. This dissertation describes an alternate v μ disappearance analysis technique for the NOvA experiment, based on the idea that estimating the energy resolution of the individual events will allow them to be separated into different energy resolution samples in order to improve the final fit.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

CATS: The Hubble Constant from Standardized TRGB and Type Ia Supernova Measurements

The tip of the red giant branch (TRGB) provides a luminous standard candle for constructing distance ladders to measure the Hubble constant. In practice, its measurements via edge-detection response (EDR) are complicated by the apparent fuzziness of the tip and the multipeak landscape of the EDR. Previously, we optimized an unsupervised algorithm, Comparative Analysis of TRGBs, to minimize the variance among multiple halo fields per host without relying on individualized choices, achieving state-of-the-art ~<0.05 mag distance measures for optimal data. Here we apply this algorithm to an expanded sample of SN Ia hosts to standardize these to multiple fields in the geometric anchor, NGC 4258. In concert with the Pantheon+ SN Ia sample, this analysis produces a (baseline) result of H 0 = 73.22 ± 2.06 km s -1 Mpc -1 . The largest difference in H 0 between this and similar studies employing the TRGB derives from corrections for SN survey differences and local flows used in the most recent SN Ia compilations that were absent in earlier studies. The SN-related differences total ~2.0 km s -1 Mpc -1 . A smaller share, ~1.4 km s -1 Mpc -1 , results from the inhomogeneity of the TRGB calibration across the distance ladder. We employ a grid of 108 variants around the optimal TRGB algorithm and find that the median of the variants is 72.94 ± 1.98 km s -1 Mpc -1 with an additional uncertainty due to algorithm choices of 0.83 km s -1 Mpc -1 . None of these TRGB variants result in an H 0 of less than 71.6 km s -1 Mpc -1 .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Optimal contracting structure between cellulosic biorefineries and farmers to reduce the impact of biomass supply variation: game theoretic analysis

There is considerable year–to–year variability in the supply of cellulosic biomass used in the production of cellulosic biofuels, yet strategies to mitigate these variations in biofuel development are not well understood. Biorefineries and farmers venturing into the cellulosic biofuel industry will require biomass supply and contracting strategies that can minimize the impact of these large variations. Some studies have proposed biomass pre–treatment and storage to address biomass supply variations. Other studies have used transportation modeling approaches to manage supply variations and select the optimal location of a cellulosic biorefinery. However, storage, pre–treatment, and similar engineering approaches lead to higher costs and have other limitations such as additional infrastructural requirements. There is a gap in understanding how contracting strategies between biorefineries and the biomass suppliers (farmers) can reduce the risks with biomass supply variations. In this study, the contracting structure between biorefineries and biomass suppliers is studied under different market structures for the US Corn Belt. A theoretical framework is then developed to use contracting strategies for mitigating the impact of biomass supply variations. First, the trade–offs between intricately linked components of biomass cost, such as biomass transport, biomass price (incentive) to suppliers, variation in biomass supply, biorefinery size, and alternative feedstock availability are examined. Next, an optimal contracting structure is developed between biorefineries and biomass suppliers using game theoretic analysis. Here, the results show that both the impact of biomass supply variations and the overall biomass cost can be significantly reduced through the use of the optimal contracting strategy between biorefineries and suppliers.

cellulosic biofuel↗
DOE OSTI2021

Performance and cost analysis of liquid fuel production from H 2 and CO 2 based on the Fischer-Tropsch process

Electro-fuels can be produced from concentrated sources of carbon dioxide and hydrogen using electricity generated from renewable sources; this process enables energy storage at high volumetric energy density. Among the electro-fuels options, FT (Fischer-Tropsch) fuel is attractive for heavy-duty trucks and non-road transportation applications. This study conducts a techno-economic analysis of FT liquid fuel production from H 2 and CO 2 using a detailed performance analysis. Minimum fuel selling price is estimated for a broad range of H 2 and CO 2 prices and for a range of potential CO 2 credits. The analysis indicates that H 2 price has the largest impact on the minimum selling price of FT fuel. FT fuel production with a CO 2 price of $17.3/metric ton requires an H 2 price of $0.8/kg to be cost-competitive with the pre-tax petroleum diesel price of $3.1/gal in 2050 (before the application of any CO 2 credits). When the H 2 price is $2.0/kg from central water electrolysis (2020 target), the minimum selling price of the FT fuel is $5.4–5.9/gal. A sensitivity analysis shows that future system optimization of FT fuel production could focus on improving the H 2 and CO 2 recycle contributions and FT fuel conversion ratio. The analysis results can be combined with various upstream systems for H 2 and CO 2 production.

08 HYDROGEN↗
DOE OSTI2022

Real-Time Drilling Optimization System for Improved Overall Rate of Penetration and Reduced Cost Per Foot in Geothermal Drilling

The key to success in geothermal drilling is economic feasibility, and a major cost in the development of geothermal resources is the actual drilling of the wells. In this project, a real-time drilling optimization system for geothermal drilling was developed. The system couples three individual components while drilling. The first component is a drill stem vibration analysis model, the second is Mechanical Specific Energy (MSE) analyses, and the third is a detailed PDC Rate of Penetration (ROP) drill bit model for optimum RPM and WOB combinations. The benefit of the coupled system is that the range of WOB and RPM could be selected to avoid drill stem vibrations. Secondly, MSE is used as an efficiency measure and the detailed PDC drill bit model ensures the drill bit does not endure temperatures that exceed the temperature at which the PDC cutters experience accelerated wear. The new detailed PDC bit model is based on rock/bit interaction that physically tracks the PDC cutter wear flats as the bit drills ahead giving the capability to calculate the temperature being generated underneath the worn cutters to better advise on operational parameters to avoid accelerated cutter wear and failure and to ensure that operational parameters are applied so that overall ROP is maximized. By combining the drill stem vibrations and the detailed PDC bit cutter wear and “safe” non-accelerated cutter wear temperature and optimum ranges of operating parameters, it results in higher ROP and lower cost drilling. Single cutter PDC testing performed in different lithologies at Sandia was utilized to verify the PDC cutter forces and depth of cut for new and worn cutters. Based on single cutter PDC temperature modeling, verification using single cutter data from the testing done by National Oilwell Varco (NOV) was performed. Sandia’s Hard-Rock Drilling Facility (HRDF) was utilized to test different drill bit configurations with different cutter designs and wear status with different induced modes of vibration to obtain the critical bit RPM/WOB ranges resulting in ineffective drilling and low ROP. The collected test data were further used to verify and calibrate the full hole PDC ROP model that was developed based on single cutter interaction data. A full coupled drill stem vibration model was formulated and verified with geothermal field data from the Chocolate Mountain Aerial Gunnery Range (CMAGR). A graphical user interface (GUI) was developed using Tkinter library in the computer programming language Python, which integrates all the developed models in one system. The developed system consists mainly of the PDC ROP model, PDC bit wear model, PDC cutter temperature model, Mechanical Specific Energy (MSE) model, and drillstring vibration model integrated into one system. The developed system can be used for both, post well analysis and real-time optimization using different criteria such as ROP maximization or MSE minimization. The software uses Differential Evolution Algorithm (DEA) to find optimum values for operational parameters based on last foot drilled while avoiding the drillstring vibration and cutter temperature critical operating parameters.

15 GEOTHERMAL ENERGY↗
DOE OSTI2013

Optimization of graphene dry etching conditions via combined microscopic and spectroscopic analysis

Single-layer graphene structures and devices are commonly defined using reactive ion etching and plasma etching with O{sub 2} or Ar as the gaseous etchants. Although optical microscopy and Raman spectroscopy are widely used to determine the appropriate duration of dry etching, additional characterization with atomic force microscopy (AFM) reveals that residual graphene and/or etching byproducts persist beyond the point where the aforementioned methods suggest complete graphene etching. Recognizing that incomplete etching may have deleterious effects on devices and/or downstream processing, AFM characterization is used here to determine optimal etching conditions that eliminate graphene dry etching residues.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

SERA: A Hydrogen Infrastructure Capacity Expansion Model

The Scenario Evaluation and Regionalization Analysis (SERA) model is an infrastructure planning optimization model that can guide hydrogen production, delivery, and end-use investment decisions and accelerate the adoption of low-cost hydrogen at scale, whether for fuel cell electric vehicles or non-transportation applications. In this talk, we will review the SERA model objective function as well as the data inputs and outputs. We will also look at a SERA case study identifying potential dispensed costs of hydrogen along major refueling corridors throughout the United States. In addition to the SERA model, Justin will also discuss his recent work for the Office of Manufacturing and Energy Supply Chains on electrolyzer supply chain readiness, and his work for the Hydrogen Fuel Cell Technologies Office and Environmental Protection Agency on the levelized cost of dispensed hydrogen for heavy-duty trucking.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2013

Multifield optimization intensity-modulated proton therapy (MFO-IMPT) for prostate cancer: Robustness analysis through simulation of rotational and translational alignment errors

To evaluate the dosimetric consequences of rotational and translational alignment errors in patients receiving intensity-modulated proton therapy with multifield optimization (MFO-IMPT) for prostate cancer. Ten control patients with localized prostate cancer underwent treatment planning for MFO-IMPT. Rotational and translation errors were simulated along each of 3 axes: anterior-posterior (A-P), superior-inferior (S-I), and left-right. Clinical target-volume (CTV) coverage remained high with all alignment errors simulated. Rotational errors did not result in significant rectum or bladder dose perturbations. Translational errors resulted in larger dose perturbations to the bladder and rectum. Perturbations in rectum and bladder doses were minimal for rotational errors and larger for translational errors. Rectum V45 and V70 increased most with A-P misalignment, whereas bladder V45 and V70 changed most with S-I misalignment. The bladder and rectum V45 and V70 remained acceptable even with extreme alignment errors. Even with S-I and A-P translational errors of up to 5 mm, the dosimetric profile of MFO-IMPT remained favorable. MFO-IMPT for localized prostate cancer results in robust coverage of the CTV without clinically meaningful dose perturbations to normal tissue despite extreme rotational and translational alignment errors.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2019

Online Primal-Dual Methods With Measurement Feedback for Time-Varying Convex Optimization

This paper addresses the design and analysis of feedback-based online algorithms to control systems or networked systems based on performance objectives and engineering constraints that may evolve over time. The emerging timevarying convex optimization formalism is leveraged to model optimal operational trajectories of the systems, as well as explicit local and network-level operational constraints. Departing from existing batch and feed-forward optimization approaches, the design of the algorithms capitalizes on an online implementation of primal-dual projected-gradient methods; the gradient steps are, however, suitably modified to accommodate feedback from the system in the form of measurements - hence, the term 'online optimization with feedback.' By virtue of this approach, the resultant algorithms can cope with model mismatches in the algebraic representation of the system states and outputs, they avoid pervasive measurements of exogenous inputs, and they naturally lend themselves to a distributed implementation. Under suitable assumptions, analytical convergence claims are established in terms of dynamic regret. Furthermore, when the synthesis of the feedback-based online algorithms is based on a regularized Lagrangian function, Q-linear convergence to solutions of the time-varying optimization problem is shown.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Nuclear Fuel Cycle System Simulation Tool Based on High-Fidelity Component Modeling

The DOE is currently directing extensive research into developing fuel cycle technologies that will enable the safe, secure, economic, and sustainable expansion of nuclear energy. The task is formidable considering the numerous fuel cycle options, the large dynamic systems that each represent, and the necessity to accurately predict their behavior. The path to successfully develop and implement an advanced fuel cycle is highly dependent on the modeling capabilities and simulation tools available for performing useful relevant analysis to assist stakeholders in decision making. Therefore a high-fidelity fuel cycle simulation tool that performs system analysis, including uncertainty quantification and optimization was developed. The resulting simulator also includes the capability to calculate environmental impact measures for individual components and the system. An integrated system method and analysis approach that provides consistent and comprehensive evaluations of advanced fuel cycles was developed. A general approach was utilized allowing for the system to be modified in order to provide analysis for other systems with similar attributes. By utilizing this approach, the framework for simulating many different fuel cycle options is provided. Two example fuel cycle configurations were developed to take advantage of used fuel recycling and transmutation capabilities in waste management scenarios leading to minimized waste inventories.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Sequential experimental design based generalised ANOVA

Over the last decade, surrogate modelling technique has gained wide popularity in the field of uncertainty quantification, optimization, model exploration and sensitivity analysis. This approach relies on experimental design to generate training points and regression/interpolation for generating the surrogate. In this work, it is argued that conventional experimental design may render a surrogate model inefficient. In order to address this issue, this paper presents a novel distribution adaptive sequential experimental design (DA-SED). The proposed DA-SED has been coupled with a variant of generalised analysis of variance (G-ANOVA), developed by representing the component function using the generalised polynomial chaos expansion. Moreover, generalised analytical expressions for calculating the first two statistical moments of the response, which are utilized in predicting the probability of failure, have also been developed. The proposed approach has been utilized in predicting probability of failure of three structural mechanics problems. It is observed that the proposed approach yields accurate and computationally efficient estimate of the failure probability.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Laterally self-ordered silicon-germanium islands with optimized confinement properties

We present an analysis of the electronic confinement properties of self-assembled islands forming via silicon and germanium co-deposition in molecular beam epitaxy. This approach allows the fabrication of laterally self-ordered three dimensional islands in the Stranski-Krastanow growth mode. Using a systematic structural analysis, we derive a realistic fit-parameter free island model for band structure simulations. A comparison between these band structure simulations and photoluminescence spectroscopy shows that such islands have a significant three dimensional spatial electron-hole wave function overlap. In addition, we show that this spatial wave function overlap overcompensates a weak wave function spreading in k-space.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Comparison of Rotor Wake Identification and Characterization Methods for the Analysis of Wake Dynamics and Evolution

Optimal wind power plant design requires understanding of wind turbine wake physics and validation of engineering wake models under wake-controlled operating conditions. In this work, we have developed and investigated several different wake identification and characterization methods for analyzing wake evolution and dynamics. The accuracy and robustness of these methods, based on Gaussian function fitting and adaptive contour identification, have been assessed by application to a large-eddy simulation data set. A new contour-based method based on downstream momentum deficit has been considered. Uncertainties arising from wake-identification errors result in characterizations of the wake expansion, recovery, and meandering motion that differ by 19% of the rotor area, 4% of the freestream, and 15% rotor diameter, respectively.

17 WIND ENERGY↗
DOE OSTI2023

Measurements of Higgs boson production in the decay channel with a pair of τ leptons in proton–proton collisions at $\sqrt{s}=13$ TeV

Measurements of Higgs boson production, where the Higgs boson decays into a pair of τ leptons, are presented, using a sample of proton-proton collisions collected with the CMS experiment at a center-of-mass energy of , corresponding to an integrated luminosity of 138 fb –1 . Three analyses are presented. Two are targeting Higgs boson production via gluon fusion and vector boson fusion: a neural network based analysis and an analysis based on an event categorization optimized on the ratio of signal over background events. These are complemented by an analysis targeting vector boson associated Higgs boson production. Results are presented in the form of signal strengths relative to the standard model predictions and products of cross sections and branching fraction to τ leptons, in up to 16 different kinematic regions. For the simultaneous measurements of the neural network based analysis and the analysis targeting vector boson associated Higgs boson production signal strengths are found to be 0.82 ± 0.11 for inclusive Higgs boson production, 0.67 ± 0.19 (0.81 ± 0.17) for the production mainly via gluon fusion (vector boson fusion), and 1.79 ± 0.45 for vector boson associated Higgs boson production.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Distributed Rules-Based Deconfliction of ADMS Applications - Part 2: Conceptual Implementation

This work introduces a rules-based deconfliction methodology for resolving conflicting device control commands issued by advanced power applications considering a range of technical, economic, environmental, and social objectives. The methodology is designed to serve as one of multiple alternative implementations (along with application cooperation and global optimization) for the numerical component of the Deconfliction Pipeline. Development of the methodology is divided into two parts. The first document previously defined the requirements, context, and methods for decomposing the deconfliction problem using the Laminar Coordination Framework and Variable Grid Structures. The deconfliction problem was decomposed into a distributed optimization problem based on the concept of quasi-static grid segments, which form independent distributed areas for control and coordination. It was recommended that selection of the optimal number of decompositions of the deconfliction problem be made based on a tradeoff analysis between computational speed and global optimality. This second document defines an initial set of technical, economic, and environmental criteria, as well as thirty specific qualitative rules that are used as part of the deconfliction methodology to eliminate non-viable setpoint alternatives. The deconfliction optimization problem is converted into a ranking of individual discrete setpoints, which are scored by the extent to which they satisfy specific decision criteria. The ranking is determined through the concepts of deconfliction exclusivity, priority, and preference. Several multi-criteria decision-making frameworks are examined with the simple multi-attribute rating technique exploiting ranks (SMARTER) recommended as a simple implementation alternative that aligns with the steps of the rules-based deconfliction methodology.

97 MATHEMATICS AND COMPUTING↗