Results for “level set method” — Page 20

DOE OSTI2016

Matter power spectrum and the challenge of percent accuracy

Future galaxy surveys require one percent precision in the theoretical knowledge of the power spectrum over a large range including very nonlinear scales. While this level of accuracy is easily obtained in the linear regime with perturbation theory, it represents a serious challenge for small scales where numerical simulations are required. In this paper we quantify the precision of present-day N -body methods, identifying main potential error sources from the set-up of initial conditions to the measurement of the final power spectrum. We directly compare three widely used N -body codes, Ramses, Pkdgrav3, and Gadget3 which represent three main discretisation techniques: the particle-mesh method, the tree method, and a hybrid combination of the two. For standard run parameters, the codes agree to within one percent at k ≤1 h Mpc{sup −1} and to within three percent at k ≤10 h Mpc{sup −1}. We also consider the bispectrum and show that the reduced bispectra agree at the sub-percent level for k ≤ 2 h Mpc{sup −1}. In a second step, we quantify potential errors due to initial conditions, box size, and resolution using an extended suite of simulations performed with our fastest code Pkdgrav3. We demonstrate that the simulation box size should not be smaller than L =0.5 h {sup −1}Gpc to avoid systematic finite-volume effects (while much larger boxes are required to beat down the statistical sample variance). Furthermore, a maximum particle mass of M {sub p}=10{sup 9} h {sup −1}M{sub ⊙} is required to conservatively obtain one percent precision of the matter power spectrum. As a consequence, numerical simulations covering large survey volumes of upcoming missions such as DES, LSST, and Euclid will need more than a trillion particles to reproduce clustering properties at the targeted accuracy.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Understanding neutron capture processes in uranium deposits using combined U-Sm-Nd isotopic compositions

Valuable insights into the history and evolution of a geologic deposit can be found by investigating neutron capture reactions. Thermal neutron capture reactions occur within both the samarium (Sm) and the uranium (U) systems, where 149 Sm and 235 U can capture neutrons to become 150 Sm and 236 U, respectively. Although largely unexplored, paired measurements of 150 Sm and 236 U could be important for understanding neutron capture effects within uranium ore bodies, and such measurements are potentially useful in nuclear forensics for assessing a material's provenance or mineral exploration. In this work, we refined measurement procedures of Sm isotope compositions utilizing MC-ICPMS. While geologic reference materials were found to have indistinguishable Sm isotope compositions, we found significant isotope variations consistent with nuclear field shift among synthetic Sm standards. Here, this observation highlights that future high-precision Sm isotope investigations need to carefully evaluate synthetic standard(s) against geologic reference materials until an unfractionated and agreed-upon standard is identified. Here, we applied this method to a set of nine uranium ores from the South Australian Beverley North uranium deposits. Although 236 U excesses had been previously reported for these U ores, we found no measurable isotopic shifts in 149 Sm- 150 Sm at the current level of precision (±5 parts per million). One possible explanation for this disparity in the observed neutron capture signatures between U and Sm is that the source(s) of the U and Sm in these ores may be decoupled. This is consistent with the finding that these ores have variable 143 Nd/ 144 Nd, thus demonstrating that diverse sources were involved in the formation of the Beverley North deposits. Alternatively, this deposit may be too young (<50Ma) to have accumulated measurable neutron capture effects in Sm to be detected with the methods employed here.

Mineral exploration↗

DOE OSTI2016

In-Situ Synchrotron and Neutron Radiation at International User Facilities Take Welding Research to a New Level

Over the past century the principal method for understanding the effects of welding on the mechanical and physical integrity of the final joint has been post-weld microstructure analysis, and it’s the interpretation of these microstructures that sets welding metallurgy apart from other related scientific fields. In conjunction with heat flow analysis, thermodynamics, and kinetics, post-weld visual observations have provided the framework for interpreting the events that lead to the final weld microstructure. However, without direct and confirming evidence of the actual phases that exist during welding, or measurement of invisible weld properties such as crystal structure and residual stress, multiple interpretations for microstructural evolution of welds are possible. For these reasons, new methods are being developed for the direct observation of phase transformations that occur both during and as a result of welding, using modern synchrotron and neutron user research facilities.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Electronic structure of intrinsic defects in c -gallium nitride: Density functional theory study without the jellium approximation

Here, we report the first nonjellium, systematic, density functional theory (DFT) study of intrinsic and extrinsic defects and defect levels in zinc-blende (cubic) gallium nitride. We use the local moment counter charge (LMCC) method, the standard Perdew-Becke-Ernzerhoff (PBE) exchange-correlation potential, and two pseudopotentials, where the Ga 3$\textit{d}$ orbitals are either in the core ($d^0$) or explicitly in the valence set ($d^{10}$). We studied 64, 216, 512, and 1000 atom supercells, and demonstrated convergence to the infinite limit, crucial for delineating deep from shallow states near band edges, and for demonstrating the elimination of finite cell-size errors. Contrary to common claims, we find that exact exchange is not required to obtain defect levels across the experimental band gap. As was true in silicon, silicon carbide, and gallium arsenide, the extremal LMCC defect levels of the aggregate of defects yield an effective LMCC defect band gap that is within 10% of the experimental gap (3.3 eV) for both pseudopotentials. We demonstrate that the gallium vacancy is more complicated than previously reported. There is dramatic metastability–a nearest-neighbor nitrogen atom shifts into the gallium site, forming an antisite, nitrogen vacancy pair, which is more stable than the simple vacancy for positive charge states. Our assessment of the $d^0$ and $d^{10}$ pseudopotentials yields minimal differences in defect structures and defect levels. The better agreement of the $d^0$ lattice constant with experiment suggests that the more computationally economical $d^0$ pseudopotentials are sufficient to achieve the fidelity possible within the physical accuracy of DFT, and thereby enable calculations in larger supercells necessary to demonstrate convergence with respect to finite size supercell errors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Greenhouse gas emissions reduction strategies that maximize portfolio-wide life cycle cost reduction, resilience, and environmental justice benefits

While strategies to achieve net-zero emissions at an individual site are well understood, new analysis methods are required for organizations seeking to achieve net-zero across multiple facilities, each with concurrent priority goals. At a portfolio level, distinct locations present varied challenges that cannot be addressed through singular solutions, and competing goals can take precedence with the assumption that net-zero emissions strategies deter from energy resilience and cost savings, therefore negatively impacting nearby communities. This study tests these assumptions by analyzing 16 diverse sites (varying in size, climate, and energy use) to identify strategies that reduce emissions and assess the impact these strategies have on life cycle costs, resilience, and communities with environmental justice concerns. Methods were developed to approximate missing information essential to net-zero evaluation. Established methods were augmented to evaluate life cycle costs, resilience, and environmental justice impacts across a set of strategies and accommodate the multi-criteria analyses. Potential benefits from identified strategies were quantified using site characteristics and a set of corresponding metrics. The net-zero analysis found that 11 sites could use on-site strategies to eliminate all but 2% of emissions generated. The remaining emissions can be offset, for instance through sequestration, executed at the portfolio scale. On-site carbon-free energy was found to reduce 51% of emissions across all sites; efficiency reduced 19% of emissions; sequestration 16%; procured carbon-free energy 15%; fuel switching 1.6%; and fleet electrification 1.3%. Building electrification, however, increased emissions by 4.4%. Different strategies also provide cost, resilience, and/or environmental justice benefits—the degree to which varies with individual site conditions. The findings indicate an advantage to considering the strategies as a comprehensive set, which leads to co-benefits, both in the ability to achieve net-zero goals and in advancing other goals. The results present the case for comprehensive advanced planning at the portfolio level to prioritize investments that will balance the minimization of emissions and life cycle cost with the maximization of resilience and environmental justice benefits. The novel methods for evaluation and integration, valuation of benefits, and consideration at the portfolio scale allow organizations to select investments that simultaneously address multiple key priorities.

Net-Zero Emissions↗

DOE OSTI2019

Theoretical level energies and transition data for ion W{sup 28+}

The ab initio quasirelativistic approach was used to derive transition data for Pd-like tungsten W{sup 28+} ion. This approach was developed specifically for the calculation of spectral parameters for highly charged ions. The relativistic effects were taken into account in the Breit–Pauli approximation. The configuration interaction method was applied to include electron correlation effects. The ground configuration 4p{sup 6}4d{sup 10} and the lowest excited 4p{sup 6}4d{sup 9}4f were considered. The calculations for W{sup 28+} were performed with different sets of interacting configurations in order to evaluate reliability and accuracy of produced results. Level energies, radiative lifetimes τ, Landé g-factors were determined for the excited configuration 4p{sup 6}4d{sup 9}4f of W{sup 28+} levels. The radiative transition wavelengths λ and emission transition probabilities A for the electric and magnetic transitions of various multipole order (up to E5 and M4) among the levels of these two configurations were produced. The uncertainties of computed spectroscopic parameters were evaluated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2016

Cardiac dosimetric evaluation of deep inspiration breath-hold level variances using computed tomography scans generated from deformable image registration displacement vectors

There is a reduction in cardiac dose for left-sided breast radiotherapy during treatment with deep inspiration breath-hold (DIBH) when compared with treatment with free breathing (FB). Various levels of DIBH may occur for different treatment fractions. Dosimetric effects due to this and other motions are a major component of uncertainty in radiotherapy in this setting. Recent developments in deformable registration techniques allow displacement vectors between various temporal and spatial patient representations to be digitally quantified. We propose a method to evaluate the dosimetric effect to the heart from variable reproducibility of DIBH by using deformable registration to create new anatomical computed tomography (CT) scans. From deformable registration, 3-dimensional deformation vectors are generated with FB and DIBH. The obtained deformation vectors are scaled to 75%, 90%, and 110% and are applied to the reference image to create new CT scans at these inspirational levels. The scans are then imported into the treatment planning system and dose calculations are performed. The average mean dose to the heart was 2.5 Gy (0.7 to 9.6 Gy) at FB, 1.2 Gy (0.6 to 3.8 Gy, p < 0.001) at 75% inspiration, 1.1 Gy (0.6 to 3.1 Gy, p = 0.004) at 90% inspiration, 1.0 Gy (0.6 to 3.0 Gy) at 100% inspiration or DIBH, and 1.0 Gy (0.6 to 2.8 Gy, p = 0.019) at 110% inspiration. The average mean dose to the left anterior descending artery (LAD) was 19.9 Gy (2.4 to 46.4 Gy), 8.6 Gy (2.0 to 43.8 Gy, p < 0.001), 7.2 Gy (1.9 to 40.1 Gy, p = 0.035), 6.5 Gy (1.8 to 34.7 Gy), and 5.3 Gy (1.5 to 31.5 Gy, p < 0.001), correspondingly. This novel method enables numerous anatomical situations to be mimicked and quantifies the dosimetric effect they have on a treatment plan.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2022

OperonSEQer: A set of machine-learning algorithms with threshold voting for detection of operon pairs using short-read RNA-sequencing data

Operon prediction in prokaryotes is critical not only for understanding the regulation of endogenous gene expression, but also for exogenous targeting of genes using newly developed tools such as CRISPR-based gene modulation. A number of methods have used transcriptomics data to predict operons, based on the premise that contiguous genes in an operon will be expressed at similar levels. While promising results have been observed using these methods, most of them do not address uncertainty caused by technical variability between experiments, which is especially relevant when the amount of data available is small. In addition, many existing methods do not provide the flexibility to determine the stringency with which genes should be evaluated for being in an operon pair. We present OperonSEQer, a set of machine learning algorithms that uses the statistic and p-value from a non-parametric analysis of variance test (Kruskal-Wallis) to determine the likelihood that two adjacent genes are expressed from the same RNA molecule. We implement a voting system to allow users to choose the stringency of operon calls depending on whether your priority is high recall or high specificity. In addition, we provide the code so that users can retrain the algorithm and re-establish hyperparameters based on any data they choose, allowing for this method to be expanded as additional data is generated. We show that our approach detects operon pairs that are missed by current methods by comparing our predictions to publicly available long-read sequencing data. OperonSEQer therefore improves on existing methods in terms of accuracy, flexibility, and adaptability.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Resilience framework and metrics for energy master planning of communities

Changes in the nature, intensity, and frequency of climate-related extreme events have imposed a higher risk of failure on energy systems, especially those at the community level. Furthermore, the evolving energy demand patterns and transition towards renewable and localised energy supply can affect energy system resilience. How can an energy system be planned and reconfigured to address these challenges without compromising the system's resilience against chronic stresses and extreme events? Unlike energy system reliability, resilience is neither a common nor an explicit consideration in energy master planning at the community level. In addition, there is no universally agreed-upon method or metrics for measuring or estimating resilience and defining mitigation strategies. This paper introduces a multi-layered energy resilience framework and set of metrics for energy master planning of communities, including the new generation of district energy systems. The potential system disturbances and their short and long-term impacts on various components of the energy system are discussed for commonly expected and extreme events. Three layers of energy resilience are discussed: engineering-designed resilience, operational resilience, and community-societal resilience. A starting set of energy resilience metrics to support engineering design and energy master planning for communities is identified. Implications for future research and practice are noted.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2016

Assessing compatibility of direct detection data: halo-independent global likelihood analyses

We present two different halo-independent methods to assess the compatibility of several direct dark matter detection data sets for a given dark matter model using a global likelihood consisting of at least one extended likelihood and an arbitrary number of Gaussian or Poisson likelihoods. In the first method we find the global best fit halo function (we prove that it is a unique piecewise constant function with a number of down steps smaller than or equal to a maximum number that we compute) and construct a two-sided pointwise confidence band at any desired confidence level, which can then be compared with those derived from the extended likelihood alone to assess the joint compatibility of the data. In the second method we define a “constrained parameter goodness-of-fit” test statistic, whose p-value we then use to define a “plausibility region” (e.g. where p≥10%). For any halo function not entirely contained within the plausibility region, the level of compatibility of the data is very low (e.g. p<10%). We illustrate these methods by applying them to CDMS-II-Si and SuperCDMS data, assuming dark matter particles with elastic spin-independent isospin-conserving interactions or exothermic spin-independent isospin-violating interactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2016

Comparing the accuracy of high-dimensional neural network potentials and the systematic molecular fragmentation method: A benchmark study for all-trans alkanes

Many approaches, which have been developed to express the potential energy of large systems, exploit the locality of the atomic interactions. A prominent example is the fragmentation methods in which the quantum chemical calculations are carried out for overlapping small fragments of a given molecule that are then combined in a second step to yield the system’s total energy. Here we compare the accuracy of the systematic molecular fragmentation approach with the performance of high-dimensional neural network (HDNN) potentials introduced by Behler and Parrinello. HDNN potentials are similar in spirit to the fragmentation approach in that the total energy is constructed as a sum of environment-dependent atomic energies, which are derived indirectly from electronic structure calculations. As a benchmark set, we use all-trans alkanes containing up to eleven carbon atoms at the coupled cluster level of theory. These molecules have been chosen because they allow to extrapolate reliable reference energies for very long chains, enabling an assessment of the energies obtained by both methods for alkanes including up to 10 000 carbon atoms. We find that both methods predict high-quality energies with the HDNN potentials yielding smaller errors with respect to the coupled cluster reference.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Push it to the limit: Characterizing the convergence of common sequences of basis sets for intermolecular interactions as described by density functional theory

With the aim of systematically characterizing the convergence of common families of basis sets such that general recommendations for basis sets can be made, we have tested a wide variety of basis sets against complete-basis binding energies across the S22 set of intermolecular interactions—noncovalent interactions of small and medium-sized molecules consisting of first- and second-row atoms—with three distinct density functional approximations: SPW92, a form of local-density approximation; B3LYP, a global hybrid generalized gradient approximation; and B97M-V, a meta-generalized gradient approximation with nonlocal correlation. We have found that it is remarkably difficult to reach the basis set limit; for the methods and systems examined, the most complete basis is Jensen’s pc-4. The Dunning correlation-consistent sequence of basis sets converges slowly relative to the Jensen sequence. The Karlsruhe basis sets are quite cost effective, particularly when a correction for basis set superposition error is applied: counterpoise-corrected def2-SVPD binding energies are better than corresponding energies computed in comparably sized Dunning and Jensen bases, and on par with uncorrected results in basis sets 3-4 times larger. These trends are exhibited regardless of the level of density functional approximation employed. A sense of the magnitude of the intrinsic incompleteness error of each basis set not only provides a foundation for guiding basis set choice in future studies but also facilitates quantitative comparison of existing studies on similar types of systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Asymptotic convergence of the angular discretization error in the scalar flux computed from the particle transport equation with the method of discrete ordinates

The asymptotic convergence of the angular discretization error in the scalar flux solution of the particle transport equation computed with the Discrete Ordinates (S N ) method with increasing quadrature order is examined. Five selected angular quadrature types are considered: Level Symmetric (LS), Legendre-Chebyshev Quadrangular (LCQ), Legendre-Chebyshev Triangular(LCT), Quadruple Range (QR) and Quadruple Range Spence-type (QRS) quadrature sets. We relate the S N angular discretization error to the quadrature error, and split the total flux into the uncollided flux and the fully collided flux, and then we verify the uncollided scalar flux error and the fully collided scalar flux error separately. After developing the theoretical basis for the relationship between true solution regularity and quadrature rule error, we employ a two-dimensional problem to verify the observed and theoretical convergence orders for the region-averaged uncollided and fully collided scalar flux errors. Numerical results show that the angular discretization errors in the region-averaged scalar flux obtained by different quadrature types converge with different rates, that are commensurate with the regularity order of the exact angular flux within the quadrature-designed integration interval. The angular discretization error in the uncollided region-averaged scalar flux obtained by LC class quadratures converges linearly, and the error obtained by QR class quadrature sets converges quadratically. The angular discretization error in the fully collided region-averaged scalar flux converges linearly for LC class quadratures, and faster-than-second order for QR class quadrature sets.

42 ENGINEERING↗

DOE OSTI2018

VARI3D & PERSENT: Perturbation and Sensitivity Analysis

The nodal diffusion method is one of the most widely used approaches in modern reactor analysis. In the nodal diffusion method, a coarse multi-group set of “homogenized” parameters is constructed such that the complex geometry of a reactor core along with the energy dependence of neutron and gamma ray cross sections in a nuclear reactor are conserved in the simpler geometry. The homogenization is typically done on a fuel assembly level as is the case in the DIF3D code developed at Argonne National Laboratory. The nodal methodology is used primarily to predict fuel cycle behavior of nuclear systems of which there is a substantial amount of validation in the literature. Another use of the nodal method is to obtain reactivity coefficients and kinetics parameters for use in a safety analysis of a given nuclear reactor. While there are many ways to obtain reactivity worth and kinetics parameters, the work presented in this manuscript is unique as it provides the user with the ability to compute reactivity worths, kinetics parameters, and cross section sensitivities with a Cartesian and hexagonal geometry based transport code.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2020

VARI3D & PERSENT: Perturbation and Sensitivity Analysis

The nodal diffusion method is one of the most widely used approaches in modern reactor analysis. In the nodal diffusion method, a coarse multi-group set of “homogenized” parameters is constructed such that the complex geometry of a reactor core along with the energy dependence of neutron and gamma ray cross sections in a nuclear reactor are conserved in the simpler geometry. The homogenization is typically done on a fuel assembly level as is the case in the DIF3D code developed at Argonne National Laboratory. The nodal methodology is used primarily to predict fuel cycle behavior of nuclear systems of which there is a substantial amount of validation in the literature. Another use of the nodal method is to obtain reactivity coefficients and kinetics parameters for use in a safety analysis of a given nuclear reactor. While there are many ways to obtain reactivity worth and kinetics parameters, the work presented in this manuscript is unique as it provides the user with the ability to compute reactivity worths, kinetics parameters, and cross section sensitivities with a Cartesian and hexagonal geometry based transport code.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

VARI3D & PERSENT: Perturbation and Sensitivity Analysis

The nodal diffusion method is one of the most widely used approaches in modern reactor analysis. In the nodal diffusion method, a coarse multi-group set of “homogenized” parameters is constructed such that the complex geometry of a reactor core along with the energy dependence of neutron and gamma ray cross sections in a nuclear reactor are conserved in the simpler geometry. The homogenization is typically done on a fuel assembly level as is the case in the DIF3D code developed at Argonne National Laboratory. The nodal methodology is used primarily to predict fuel cycle behavior of nuclear systems of which there is a substantial amount of validation in the literature. Another use of the nodal method is to obtain reactivity coefficients and kinetics parameters for use in a safety analysis of a given nuclear reactor. While there are many ways to obtain reactivity worth and kinetics parameters, the work presented in this manuscript is unique as it provides the user with the ability to compute reactivity worths, kinetics parameters, and cross section sensitivities with a Cartesian and hexagonal geometry based transport code.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

VARI3D & PERSENT: Perturbation and Sensitivity Analysis (Revision 5)

The nodal diffusion method is one of the most widely used approaches in modern reactor analysis. In the nodal diffusion method, a coarse multi-group set of “homogenized” parameters is constructed such that the complex geometry of a reactor core along with the energy dependence of neutron and gamma ray cross sections in a nuclear reactor are conserved in the simpler geometry. The homogenization is typically done on a fuel assembly level as is the case in the DIF3D code developed at Argonne National Laboratory. The nodal methodology is used primarily to predict fuel cycle behavior of nuclear systems of which there is a substantial amount of validation in the literature. Another use of the nodal method is to obtain reactivity coefficients and kinetics parameters for use in a safety analysis of a given nuclear reactor. While there are many ways to obtain reactivity worth and kinetics parameters, the work presented in this manuscript is unique as it provides the user with the ability to compute reactivity worths, kinetics parameters, and cross section sensitivities with a Cartesian and hexagonal geometry-based transport code.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

High-throughput calculations of charged point defect properties with semi-local density functional theory—performance benchmarks for materials screening applications

Abstract Calculations of point defect energetics with Density Functional Theory (DFT) can provide valuable insight into several optoelectronic, thermodynamic, and kinetic properties. These calculations commonly use methods ranging from semi-local functionals with a-posteriori corrections to more computationally intensive hybrid functional approaches. For applications of DFT-based high-throughput computation for data-driven materials discovery, point defect properties are of interest, yet are currently excluded from available materials databases. This work presents a benchmark analysis of automated, semi-local point defect calculations with a-posteriori corrections, compared to 245 “gold standard” hybrid calculations previously published. We consider three different a-posteriori correction sets implemented in an automated workflow, and evaluate the qualitative and quantitative differences among four different categories of defect information: thermodynamic transition levels, formation energies, Fermi levels, and dopability limits. We highlight qualitative information that can be extracted from high-throughput calculations based on semi-local DFT methods, while also demonstrating the limits of quantitative accuracy.

36 MATERIALS SCIENCE↗