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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 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

A study of the contribution of doubly excited ionic states to the properties of hot dense high-Z plasmas

The role of two-electron processes, i.e. dielectronic recombination and autoionization, in the ionization balance and X-ray emission of hot dense plasmas composed of various high-Z materials is explored. Tungsten, gold, lead and uranium are considered. It is shown that the average ion charge and the high-energy emissivity are both sensitive to the dielectronic recombination rate. A systematic study demonstrates the degree of this sensitivity. It is found that the complete neglect of these 2-electron processes introduces a large error but once included, the key physical properties are quite insensitive to the rate over the important 2–3 keV temperature range. The high-energy emissivity depends strongly on temperature, peaking at conditions corresponding to a closed shell system, and on the square of the electron density, as for a coronal system.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Optimization of nutrient utilization efficiency and productivity for algal cultures under light and dark cycles using genome-scale model process control

Abstract Algal cultivations are strongly influenced by light and dark cycles. In this study, genome-scale metabolic models were applied to optimize nutrient supply during alternating light and dark cycles of Chlorella vulgaris . This approach lowered the glucose requirement by 75% and nitrate requirement by 23%, respectively, while maintaining high final biomass densities that were more than 80% of glucose-fed heterotrophic culture. Furthermore, by strictly controlling glucose feeding during the alternating cycles based on model-input, yields of biomass, lutein, and fatty acids per gram of glucose were more than threefold higher with cycling compared to heterotrophic cultivation. Next, the model was incorporated into open-loop and closed-loop control systems and compared with traditional fed-batch systems. Closed-loop systems which incorporated a feed-optimizing algorithm increased biomass yield on glucose more than twofold compared to standard fed-batch cultures for cycling cultures. Finally, the performance was compared to conventional proportional-integral-derivative (PID) controllers. Both simulation and experimental results exhibited superior performance for genome-scale model process control (GMPC) compared to traditional PID systems, reducing the overall measured value and setpoint error by 80% over 8 h. Overall, this approach provides researchers with the capability to enhance nutrient utilization and productivity of cell factories systematically by combining genome-scale models and controllers into an integrated platform with superior performance to conventional fed-batch and PID methodologies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Density functional theory of water with the machine-learned DM21 functional

The delicate interplay between functional-driven and density-driven errors in density functional theory (DFT) has hindered traditional density functional approximations (DFAs) from providing an accurate description of water for over 30 years. Recently, the deep-learned DeepMind 21 (DM21) functional has been shown to overcome the limitations of traditional DFAs as it is free of delocalization error. To determine if DM21 can enable a molecular-level description of the physical properties of aqueous systems within Kohn–Sham DFT, we assess the accuracy of the DM21 functional for neutral, protonated, and deprotonated water clusters. Furthermore, we find that the ability of DM21 to accurately predict the energetics of aqueous clusters varies significantly with cluster size. Additionally, we introduce the many-body MB-DM21 potential derived from DM21 data within the many-body expansion of the energy and use it in simulations of liquid water as a function of temperature at ambient pressure. We find that size-dependent functional-driven errors identified in the analysis of the energetics of small clusters calculated with the DM21 functional result in the MB-DM21 potential systematically overestimating the hydrogen-bond strength and, consequently, predicting a more ice-like local structure of water at room temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Quantum Monte Carlo Calculations in Solids with Downfolded Hamiltonians

We present a systematic downfolding many-body approach for extended systems. Many-body calculations operate on a simpler Hamiltonian which retains material-specific properties. The Hamiltonian is systematically improvable and allows one to dial, in principle, between the simplest model and the original Hamiltonian. As a by-product, pseudopotential errors are essentially eliminated using a frozen-core treatment. The computational cost of the many-body calculation is dramatically reduced without sacrificing accuracy. We use the auxiliary-field quantum Monte Carlo (AFQMC) method to solve the downfolded Hamiltonian. Excellent accuracy is achieved for a range of solids, including semiconductors, ionic insulators, and metals. We further test the method by determining the spin gap in NiO, a challenging prototypical material with strong electron correlation effects. This approach greatly extends the reach of general, ab initio many-body calculations in materials.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Benchmarking performance changes in the simulation of extratropical modes of variability across CMIP generations

In this work, we evaluate extratropical modes of variability in the three most recent phases of the Coupled Model Intercomparison Project (CMIP3, 5, and 6) to gauge improvement of climate models over time. A suite of high-level metrics is employed to objectively evaluate how well climate models simulate the qobserved Northern Annular Mode (NAM), North Atlantic Oscillation (NAO), Pacific North America pattern (PNA), Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO), North Pacific Oscillation (NPO), and North Pacific Gyre Oscillation (NPGO). We apply a Common Basis Function (CBF) approach that projects model anomalies onto observed empirical orthogonal functions (EOFs), together with the traditional EOF approach, to CMIP Historical and AMIP models. We find simulated spatial patterns of those modes have been significantly improved in the newer models, although the skill improvement is sensitive to the mode and season considered. We identify some potential contributions to the pattern improvement of certain modes (e.g., the Southern Hemisphere jet and High-top vertical coordinate), however the performance changes are likely attributed to gradual improvement of the base climate and multiple relevant processes. Less performance improvement is evident in the mode amplitude of these modes and systematic overestimation of the mode amplitude in spring remains in the newer climate models. We find that the post-dominant season amplitude errors in atmospheric modes are not limited to coupled runs but are often already evident in AMIP simulations. This suggests that rectifying the egregious post-dominant season amplitude errors found in many models can be addressed in an atmospheric-only framework making it more tractable to address in the model development process.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Action-based dynamical modeling for the Milky Way disk

We present RoadMapping, a full-likelihood dynamical modeling machinery that aims to recover the Milky Way’s (MW) gravitational potential from large samples of stars in the Galactic disk. RoadMapping models the observed positions and velocities of stars with a parameterized, three-integral distribution function (DF) in a parameterized axisymmetric potential. We investigate through differential test cases with idealized mock data how the breakdown of model assumptions and data properties affect constraints on the potential and DF. Our key results are: (i) If the MW’s true potential is not included in the assumed model potential family, we can—in the axisymmetric case—still find a robust estimate for the potential, with only ≲10% difference in surface density within |z|⩽1.1 kpc inside the observed volume. (ii) Modest systematic differences between the true and model DF are inconsequential. E.g., when binning stars to define sub-populations with simple DFs, binning errors do not affect the modeling as long as the DF parameters of neighboring bins differ by <20%. In addition, RoadMapping ensures unbiased potential estimates for either (iii) small misjudgements of the spatial selection function (i.e., ≲15% at the survey volume’s edge), (iv) if distances are known to within 10%, or (v) if proper motion uncertainties are known within 10% or are smaller than δμ≲1 mas yr{sup −1}. Challenges are the rapidly increasing computational costs for large sample sizes. Overall, RoadMapping is well suited to making precise new measurements of the MW’s potential with data from the upcoming Gaia releases.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Energy Performance Assessment of Radiant Cooling System through Modeling and Calibration at Component Level

The paper describes a case study of an information technology office building with a radiant cooling system and a conventional variable air volume (VAV) system installed side by side so that performancecan be compared. First, a 3D model of the building involving architecture, occupancy, and HVAC operation was developed in EnergyPlus, a simulation tool. Second, a different calibration methodology was applied to develop the base case for assessing the energy saving potential. This paper details the calibration of the whole building energy model to the component level, including lighting, equipment, and HVAC components such as chillers, pumps, cooling towers, fans, etc. Also a new methodology for the systematic selection of influence parameter has been developed for the calibration of a simulated model which requires large time for the execution. The error at the whole building level [measured in mean bias error (MBE)] is 0.2%, and the coefficient of variation of root mean square error (CvRMSE) is 3.2%. The total errors in HVAC at the hourly are MBE = 8.7% and CvRMSE = 23.9%, which meet the criteria of ASHRAE 14 (2002) for hourly calibration. Different suggestions have been pointed out to generalize the energy saving of radiant cooling system through the existing building system. So a base case model was developed by using the calibrated model for quantifying the energy saving potential of the radiant cooling system. It was found that a base case radiant cooling system integrated with DOAS can save 28% energy compared with the conventional VAV system.

Building Energy Simulation↗
DOE OSTI2013

PROBING THE LOW-REDSHIFT STAR FORMATION RATE AS A FUNCTION OF METALLICITY THROUGH THE LOCAL ENVIRONMENTS OF TYPE II SUPERNOVAE

Type II supernovae (SNe) can be used as a star formation tracer to probe the metallicity distribution of global low-redshift star formation. We present oxygen and iron abundance distributions of Type II SN progenitor regions that avoid many previous sources of bias. Because iron abundance, rather than oxygen abundance, is of key importance for the late stage evolution of the massive stars that are the progenitors of core-collapse supernovae, and because iron enrichment lags oxygen enrichment, we find a general conversion from oxygen abundance to iron abundance. The distributions we present here are the best yet observational standard of comparison for evaluating how different classes of supernovae depend on progenitor metallicity. We spectroscopically measure the gas-phase oxygen abundance near a representative subsample of the hosts of Type II SNe from the first-year Palomar Transient Factory (PTF) SN search, using a combination of Sloan Digital Sky Survey (SDSS) spectra near the SN location (9 hosts) and new longslit spectroscopy (25 hosts). The median metallicity of these 34 hosts at or near the SN location is 12+log(O/H) = 8.65, with a median error of 0.09. The median host galaxy stellar mass from fits to SDSS photometry is 10{sup 9.9} M{sub Sun }. They do not show a systematic offset in metallicity or mass from a redshift-matched sample of the MPA/JHU value-added catalog. In contrast to previous SN host metallicity studies, this sample is drawn from a single survey. It is also drawn from an areal rather than a targeted survey, so SNe in the lowest-mass galaxies are not systematically excluded. Indeed, the PTF SN search has a slight bias toward following up transients in low mass galaxies. The progenitor region metallicity distribution we find is statistically indistinguishable from the metallicity distribution of Type II SN hosts found by targeted surveys and by samples from multiple surveys with different selection functions. Using the relationship between iron and oxygen abundances found for Milky Way disk, bulge, and halo stars, we translate our distribution of Type II SN environments as a function of oxygen abundance into an estimate of the iron abundance, since iron varies more steeply than oxygen. We find that though this sample spans only 0.65 dex in oxygen abundance, the gap between the iron and oxygen abundance is 50% wider at the low-metallicity end of our sample than at the high-metallicity end.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Error-correcting codes for fermionic quantum simulation

Utilizing the framework of \mathbb{Z}_2 ℤ 2 lattice gauge theories in the context of Pauli stabilizer codes, we present methodologies for simulating fermions via qubit systems on a two-dimensional square lattice. We investigate the symplectic automorphisms of the Pauli module over the Laurent polynomial ring. This enables us to systematically increase the code distances of stabilizer codes while fixing the rate between encoded logical fermions and physical qubits. We identify a family of stabilizer codes suitable for fermion simulation, achieving code distances of d=2,3,4,5,6,7, allowing correction of any \lfloor \frac{d-1}{2} \rfloor ⌊ d − 1 2 ⌋ -qubit error. In contrast to the traditional code concatenation approach, our method can increase the code distances without decreasing the (fermionic) code rate. In particular, we explicitly show all stabilizers and logical operators for codes with code distances of d=3,4,5. We provide syndromes for all Pauli errors and invent a syndrome-matching algorithm to compute code distances numerically.

Physics↗
DOE OSTI2025

Periodic GFN1-xTB Tight Binding: A Generalized Ewald Partitioning Scheme for the Klopman–Ohno Function

A novel formulation is presented for the treatment of electrostatics in the periodic GFN1-xTB tight-binding model. Periodic GFN1-xTB is hindered by the functional form of the second-order electrostatics, which only recovers Coulombic behavior at large interatomic distances and lacks a closed-form solution for its Fourier transform. We address this by introducing a binomial expansion of the Klopman–Ohno function to partition short- and long-range interactions, enabling the use of a generalized Ewald summation for the solution of the electrostatic energy. This approach is general and is applicable to any damped potential of the form |R n + c| –m . Benchmarks on the X23 molecular crystal dataset and a range of prototypical bulk semiconductors demonstrate that this systematic treatment of the electrostatics eliminates unphysical behavior in the equation of state curves. In the bulk systems studied, we observe a mean absolute error in total energy of 35 meV/atom, comparable to the machine-learned universal force field, M3GNet, and sufficiently precise for structure relaxation. These results highlight the promising potential of GFN1-xTB as a universal tight-binding parametrization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Robust, Accurate, and Efficient: Quantum Embedding Using the Huzinaga Level-Shift Projection Operator for Complex Systems

Using wave function (WF) in density functional theory (DFT) embedding methods provides a framework for performing localized, high-accuracy WF calculations on a system, while not incurring the full computational cost of the WF calculation on the full system. To effectively partition a system into localized WF and DFT subsystems, we utilize the Huzinaga level-shift projection operator within an absolutely localized basis. In this work, we study the ability of the absolutely localized Huzinaga level-shift projection operator method to study complex WF and DFT partitions, including partitions between multiple covalent bonds, a double bond, and transition-metal–ligand bonds. We find that our methodology can accurately describe all of these complex partitions. Additionally, we study the robustness of this method with respect to the WF method, specifically where the embedded systems were described using a multiconfigurational WF method. We found that the method is systematically improvable with respect to both the number of atoms in the WF region and the size of the basis set used, with energy errors less than 1 kcal/mol. Additionally, we calculated the adsorption energy of H2 to a model of an iron metal–organic framework (Fe-MOF-74) to within 1 kcal/mol compared to CASPT2 calculations performed on the full model while incurring only a small fraction of the full computational cost. In conclusion, this work demonstrates that the absolutely localized Huzinaga level-shift projection operator method is applicable to very complex systems with difficult electronic structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

MEASURING THE MASS DISTRIBUTION IN GALAXY CLUSTERS

Cluster mass profiles are tests of models of structure formation. Only two current observational methods of determining the mass profile, gravitational lensing, and the caustic technique are independent of the assumption of dynamical equilibrium. Both techniques enable the determination of the extended mass profile at radii beyond the virial radius. For 19 clusters, we compare the mass profile based on the caustic technique with weak lensing measurements taken from the literature. This comparison offers a test of systematic issues in both techniques. Around the virial radius, the two methods of mass estimation agree to within {approx}30%, consistent with the expected errors in the individual techniques. At small radii, the caustic technique overestimates the mass as expected from numerical simulations. The ratio between the lensing profile and the caustic mass profile at these radii suggests that the weak lensing profiles are a good representation of the true mass profile. At radii larger than the virial radius, the extrapolated Navarro, Frenk and White fit to the lensing mass profile exceeds the caustic mass profile. Contamination of the lensing profile by unrelated structures within the lensing kernel may be an issue in some cases; we highlight the clusters MS0906+11 and A750, superposed along the line of sight, to illustrate the potential seriousness of contamination of the weak lensing signal by these unrelated structures.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Automated label flows for excited states of correlation functions in lattice gauge theory

Extracting excited states from lattice gauge theory correlation functions can be achieved through $χ^2$ minimization fits or algebraic approaches such as the variational method and Prony's method. Performing any kind of error analysis often leads to overlapping confidence regions of model parameters, even when the spectrum is not particularly dense. To correctly estimate errors, one must beware of mislabeling the states. In this work, we provide an algorithm that we call automated label flows which consistently and systematically identifies a deterministic labeling of states. This is a black-box approach in the sense that it gives a sensible set of labels without user guidance. Further, as an example, we pair one black box method with another, analyzing a lattice correlation function from real data using automated label flows in the context of Prony's method.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

The report of Task Group 100 of the AAPM: Application of risk analysis methods to radiation therapy quality management

The increasing complexity of modern radiation therapy planning and delivery challenges traditional prescriptive quality management (QM) methods, such as many of those included in guidelines published by organizations such as the AAPM, ASTRO, ACR, ESTRO, and IAEA. These prescriptive guidelines have traditionally focused on monitoring all aspects of the functional performance of radiotherapy (RT) equipment by comparing parameters against tolerances set at strict but achievable values. Many errors that occur in radiation oncology are not due to failures in devices and software; rather they are failures in workflow and process. A systematic understanding of the likelihood and clinical impact of possible failures throughout a course of radiotherapy is needed to direct limit QM resources efficiently to produce maximum safety and quality of patient care. Task Group 100 of the AAPM has taken a broad view of these issues and has developed a framework for designing QM activities, based on estimates of the probability of identified failures and their clinical outcome through the RT planning and delivery process. The Task Group has chosen a specific radiotherapy process required for “intensity modulated radiation therapy (IMRT)” as a case study. The goal of this work is to apply modern risk-based analysis techniques to this complex RT process in order to demonstrate to the RT community that such techniques may help identify more effective and efficient ways to enhance the safety and quality of our treatment processes. The task group generated by consensus an example quality management program strategy for the IMRT process performed at the institution of one of the authors. This report describes the methodology and nomenclature developed, presents the process maps, FMEAs, fault trees, and QM programs developed, and makes suggestions on how this information could be used in the clinic. The development and implementation of risk-assessment techniques will make radiation therapy safer and more efficient.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Technical Basis for Evaluating Software-Related Common-Cause Failures

The instrumentation and control (I&C) system architecture at a nuclear power plant (NPP) incorporates protections against common-cause failures (CCFs) through the use of diversity and defense-in-depth. Even for well-established analog-based I&C system designs, the potential for CCFs of multiple systems (or redundancies within a system) constitutes a credible threat to defeating the defense-in-depth provisions within the I&C system architectures. The integration of digital technologies into the I&C systems provides many advantages compared to the aging analog systems with respect to reliability, maintenance, operability, and cost effectiveness. However, maintaining the diversity and defense-in-depth for both the hardware and software within the digital system is challenging. In fact, the introduction of digital technologies may actually increase the potential for CCF vulnerabilities because of the introduction of undetected systematic faults. These systematic faults are defined as a “design fault located in a software component” and at a high level, are predominately the result of (1) errors in the requirement specification, (2) inadequate provisions to account for design limits (e.g., environmental stress), or (3) technical faults incorporated in the internal system (or architectural) design or implementation. Other technology-neutral CCF concerns include hardware design errors, equipment qualification deficiencies, installation or maintenance errors, instrument loop scaling and setpoint mistakes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Uncertainty Analysis on the Design of Thermal Conductivity Measurement by a Guarded Cut-Bar Technique

A technique adapted from the guarded-comparative-longitudinal heat flow method was selected for the measurement of the thermal conductivity of a nuclear fuel compact over a temperature range characteristic of its usage. This technique fulfills the requirement for non-destructive measurement of the composite compact. Although numerous measurement systems have been created based on the guarded comparative method, comprehensive systematic (bias) and measurement (precision) uncertainty associated with this technique have not been fully analyzed. In addition to the geometric effect in the bias error, which has been analyzed previously, this paper studies the working condition which is another potential error source. Using finite element analysis, this study showed the effect of these two types of error sources in the thermal conductivity measurement process and the limitations in the design selection of various parameters by considering their effect on the precision error. The results and conclusions provide valuable reference for designing and operating an experimental measurement system using this technique.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2011

Observation of the Decay B- --> Ds(*) K- l- nubar

We report the observation of the decay B{sup -} {yields} D{sub s}{sup (*)+} K{sup -}{ell}{sup -}{bar {nu}}{sub {ell}} based on 342 fb{sup -1} of data collected at the {Upsilon}(4S) resonance with the BABAR detector at the PEP-II e{sup +}e{sup -} storage rings at SLAC. A simultaneous fit to three D{sub s}{sup +} decay chains is performed to extract the signal yield from measurements of the squared missing mass in the B meson decay. We observe the decay B{sup -} {yields} D{sub s}{sup (*)+} K{sup -}{ell}{sup -}{bar {nu}}{sub {ell}} with a significance greater than five standard deviations (including systematic uncertainties) and measure its branching fraction to be {Beta}(B{sup -} {yields} D{sub s}{sup (*)+} K{sup -}{ell}{sup -}{bar {nu}}{sub {ell}}) = [6.13{sub -1.03}{sup +1.04}(stat.) {+-} 0.43(syst.) {+-} 0.51({Beta}(D{sub s}))] x 10{sup -4}, where the last error reflects the limited knowledge of the D{sub s} branching fractions.

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

On representation of temporal variability in electricity capacity planning models

This study systematically investigates how to represent intra-annual temporal variability in models of optimum electricity capacity investment. Inappropriate aggregation of temporal resolution can introduce substantial error into model outputs and associated economic insight. The mechanisms underlying the introduction of this error are shown. How many representative periods are needed to fully capture the variability is then investigated. For a sample dataset, a scenario-robust aggregation of hourly (8760) resolution is possible in the order of 10 representative hours when electricity demand is the only source of variability. The inclusion of wind and solar supply variability increases the resolution of the robust aggregation to the order of 1000. A similar scale of expansion is shown for representative days and weeks. These concepts can be applied to any such temporal dataset, providing, at the least, a benchmark that any other aggregation method can aim to emulate. Finally, how prior information about peak pricing hours can potentially reduce resolution further is also discussed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗